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Guhan M, Crane SM, Valerius LS, Cruz DDL, Smith BD, Woodward WA, Mitchell MP, Valero V, Rauch GM, Krishnamurthy S, Warnecke CL, Kuerer HM, Shaitelman SF. Patient Interest in Exploring Nonsurgical Treatment Approaches for Early-Stage Breast Cancer: A Qualitative Study. Int J Radiat Oncol Biol Phys 2024; 118:443-454. [PMID: 37802228 DOI: 10.1016/j.ijrobp.2023.08.065] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2023] [Revised: 07/18/2023] [Accepted: 08/29/2023] [Indexed: 10/08/2023]
Abstract
PURPOSE Advances in radiation therapy have enabled the ability to deliver ablative treatments, but there has been limited application of these treatments to early-stage breast cancers with a goal of omitting surgery. The purpose of this study was to explore patient interest in pursuing nonsurgical treatment approaches for their early-stage breast cancer. METHODS AND MATERIALS We conducted a qualitative study involving interviews with 21 patients with early-stage breast cancer who were eligible for participation in a phase 2 clinical trial offering omission of definitive surgery. Interviews were transcribed and an inductive, thematic analysis was performed by 3 independent reviewers to generate themes and subthemes. RESULTS Data analysis revealed the following factors that affected patient willingness and desire to explore nonsurgical treatment options: (1) perceptions and feelings about their cancer; (2) current quality of life and the level of support available in their daily life; (3) external conversations focusing on family members' and friends' experiences with cancer and/or cancer treatments; (4) personal health care experiences, including their current breast cancer diagnosis; (5) perceptions and feelings about their physicians; (6) conversations with their physicians about their treatment options; and (7) self-identified desire to direct care decisions. Specifically, patients verbalized fearing surgery and surgical recovery; wanting to preserve their breast(s); the prior negative surgical experiences of friends, family, and themselves; a desire to receive treatment per the latest research; wanting to match the level of treatment with the severity of their cancer; and other comorbidities as reasons for wanting to explore omitting surgery. CONCLUSIONS Our findings demonstrate an unmet need directed by patient interest to explore nonsurgical options for early-stage, biologically favorable breast cancer. These results may shape conversations around shared decision-making and clinical trial design, and result in more personalized treatment options for women with early-stage breast cancer.
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Affiliation(s)
- Maya Guhan
- Baylor College of Medicine, Houston, Texas
| | | | | | | | | | | | | | | | | | | | | | - Henry M Kuerer
- Breast Surgical Oncology, University of Texas MD Anderson Cancer Center, Houston, Texas
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Yankeelov TE, Hormuth DA, Lima EA, Lorenzo G, Wu C, Okereke LC, Rauch GM, Venkatesan AM, Chung C. Designing clinical trials for patients who are not average. iScience 2024; 27:108589. [PMID: 38169893 PMCID: PMC10758956 DOI: 10.1016/j.isci.2023.108589] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2024] Open
Abstract
The heterogeneity inherent in cancer means that even a successful clinical trial merely results in a therapeutic regimen that achieves, on average, a positive result only in a subset of patients. The only way to optimize an intervention for an individual patient is to reframe their treatment as their own, personalized trial. Toward this goal, we formulate a computational framework for performing personalized trials that rely on four mathematical techniques. First, mathematical models that can be calibrated with patient-specific data to make accurate predictions of response. Second, digital twins built on these models capable of simulating the effects of interventions. Third, optimal control theory applied to the digital twins to optimize outcomes. Fourth, data assimilation to continually update and refine predictions in response to therapeutic interventions. In this perspective, we describe each of these techniques, quantify their "state of readiness", and identify use cases for personalized clinical trials.
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Affiliation(s)
- Thomas E. Yankeelov
- Department of Biomedical Engineering, The University of Texas at Austin, Austin, TX 78712, USA
- Department of Diagnostic Medicine, The University of Texas at Austin, Austin, TX 78712, USA
- Department of Oncology, The University of Texas at Austin, Austin, TX 78712, USA
- Oden Institute for Computational Engineering and Sciences, The University of Texas at Austin, Austin, TX 78712, USA
- Livestrong Cancer Institutes, The University of Texas at Austin, Austin, TX 78712, USA
- Division of Diagnostic Imaging, The University of Texas M.D. Anderson Cancer Center, Houston, TX 77030, USA
| | - David A. Hormuth
- Oden Institute for Computational Engineering and Sciences, The University of Texas at Austin, Austin, TX 78712, USA
- Livestrong Cancer Institutes, The University of Texas at Austin, Austin, TX 78712, USA
| | - Ernesto A.B.F. Lima
- Oden Institute for Computational Engineering and Sciences, The University of Texas at Austin, Austin, TX 78712, USA
- Texas Advanced Computer Center, The University of Texas at Austin, Austin, TX 78712, USA
| | - Guillermo Lorenzo
- Oden Institute for Computational Engineering and Sciences, The University of Texas at Austin, Austin, TX 78712, USA
- Department of Civil Engineering and Architecture, University of Pavia, 27100 Pavia, Italy
| | - Chengyue Wu
- Oden Institute for Computational Engineering and Sciences, The University of Texas at Austin, Austin, TX 78712, USA
| | - Lois C. Okereke
- Oden Institute for Computational Engineering and Sciences, The University of Texas at Austin, Austin, TX 78712, USA
| | - Gaiane M. Rauch
- Department of Abdominal Imaging, The University of Texas M.D. Anderson Cancer Center, Houston, TX 77030, USA
| | - Aradhana M. Venkatesan
- Department of Abdominal Imaging, The University of Texas M.D. Anderson Cancer Center, Houston, TX 77030, USA
| | - Caroline Chung
- Department of Radiation Oncology, The University of Texas M.D. Anderson Cancer Center, Houston, TX 77030, USA
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Rauch GM. Editorial Comment: Pros and Cons of Implementation of Synoptic Reporting in Oncologic Imaging. AJR Am J Roentgenol 2023; 221:772. [PMID: 37530401 DOI: 10.2214/ajr.23.29942] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/03/2023]
Affiliation(s)
- Gaiane M Rauch
- The University of Texas MD Anderson Cancer Center, Houston, TX,
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4
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Jacobsen MC, Rigaud B, Simiele SJ, Rauch GM, Ning MS, Vedam S, Klopp AH, Stafford RJ, Brock KK, Venkatesan AM. Feasibility of quantitative diffusion-weighted imaging during intra-procedural MRI-guided brachytherapy of locally advanced cervical and vaginal cancers. Brachytherapy 2023; 22:736-745. [PMID: 37612174 DOI: 10.1016/j.brachy.2023.06.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2023] [Revised: 05/30/2023] [Accepted: 06/15/2023] [Indexed: 08/25/2023]
Abstract
PURPOSE To determine the feasibility of quantitative apparent diffusion coefficient (ADC) acquisition during magnetic resonance imaging-guided brachytherapy (MRgBT) using reduced field-of-view (rFOV) diffusion-weighted imaging (DWI). METHODS AND MATERIALS T2-weighted (T2w) MR and full-FOV single-shot echo planar (ssEPI) DWI were acquired in 7 patients with cervical or vaginal malignancy at baseline and prior to brachytherapy, while rFOV-DWI was acquired during MRgBT following brachytherapy applicator placement. The gross target volume (GTV) was contoured on the T2w images and registered to the ADC map. Voxels at the GTV's maximum Maurer distance comprised a central sub-volume (GTVcenter). Contour ADC mean and standard deviation were compared between timepoints using repeated measures ANOVA. RESULTS ssEPI-DWI mean ADC increased between baseline and prebrachytherapy from 1.03 ± 0.18 10-3 mm2/s to 1.34 ± 0.28 10-3 mm2/s for the GTV (p = 0.06) and from 0.84 ± 0.13 10-3 mm2/s to 1.26 ± 0.25 10-3 mm2/s at the level of the GTVcenter (p = 0.03), consistent with early treatment response. rFOV-DWI during MRgBT demonstrated mean ADC values of 1.28 ± 0.14 10-3 mm2/s and 1.28 ± 0.19 10-3 mm2/s for the GTV and GTVcenter, respectively (p = 0.02 and p = 0.03 relative to baseline). No significant differences were observed between ssEPI-DWI and rFOV-DWI ADC measurements. CONCLUSIONS Quantitative ADC measurement in the setting of MRI guided brachytherapy implant placement for cervical and vaginal cancers is feasible using rFOV-DWI, with comparable mean ADC comparable to prebrachytherapy ssEPI-DWI, and may enable MRI-guided radiotherapy targeting of low ADC, radiation resistant sub-volumes of tumor.
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Affiliation(s)
- Megan C Jacobsen
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX.
| | - Bastien Rigaud
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Samantha J Simiele
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Gaiane M Rauch
- Department of Abdominal Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Matthew S Ning
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Sastry Vedam
- University of Maryland, Department of Radiation Oncology, Baltimore, MD
| | - Ann H Klopp
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - R Jason Stafford
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Kristy K Brock
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX; Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Aradhana M Venkatesan
- Department of Abdominal Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX.
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5
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Panthi B, Mohamed RM, Adrada BE, Boge M, Candelaria RP, Chen H, Hunt KK, Huo L, Hwang KP, Korkut A, Lane DL, Le-Petross HC, Leung JWT, Litton JK, Pashapoor S, Perez F, Son JB, Sun J, Thompson A, Tripathy D, Valero V, Wei P, White J, Xu Z, Yang W, Zhou Z, Yam C, Rauch GM, Ma J. Longitudinal dynamic contrast-enhanced MRI radiomic models for early prediction of response to neoadjuvant systemic therapy in triple-negative breast cancer. Front Oncol 2023; 13:1264259. [PMID: 37941561 PMCID: PMC10628525 DOI: 10.3389/fonc.2023.1264259] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2023] [Accepted: 10/09/2023] [Indexed: 11/10/2023] Open
Abstract
Early prediction of neoadjuvant systemic therapy (NAST) response for triple-negative breast cancer (TNBC) patients could help oncologists select individualized treatment and avoid toxic effects associated with ineffective therapy in patients unlikely to achieve pathologic complete response (pCR). The objective of this study is to evaluate the performance of radiomic features of the peritumoral and tumoral regions from dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) acquired at different time points of NAST for early treatment response prediction in TNBC. This study included 163 Stage I-III patients with TNBC undergoing NAST as part of a prospective clinical trial (NCT02276443). Peritumoral and tumoral regions of interest were segmented on DCE images at baseline (BL) and after two (C2) and four (C4) cycles of NAST. Ten first-order (FO) radiomic features and 300 gray-level-co-occurrence matrix (GLCM) features were calculated. Area under the receiver operating characteristic curve (AUC) and Wilcoxon rank sum test were used to determine the most predictive features. Multivariate logistic regression models were used for performance assessment. Pearson correlation was used to assess intrareader and interreader variability. Seventy-eight patients (48%) had pCR (52 training, 26 testing), and 85 (52%) had non-pCR (57 training, 28 testing). Forty-six radiomic features had AUC at least 0.70, and 13 multivariate models had AUC at least 0.75 for training and testing sets. The Pearson correlation showed significant correlation between readers. In conclusion, Radiomic features from DCE-MRI are useful for differentiating pCR and non-pCR. Similarly, predictive radiomic models based on these features can improve early noninvasive treatment response prediction in TNBC patients undergoing NAST.
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Affiliation(s)
- Bikash Panthi
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Rania M. Mohamed
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Beatriz E. Adrada
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Medine Boge
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
- Koc University Hospital, Istanbul, Türkiye
| | - Rosalind P. Candelaria
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Huiqin Chen
- Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Kelly K. Hunt
- Department of Breast Surgical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Lei Huo
- Department of Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Ken-Pin Hwang
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Anil Korkut
- Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Deanna L. Lane
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Huong C. Le-Petross
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Jessica W. T. Leung
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Jennifer K. Litton
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Sanaz Pashapoor
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Frances Perez
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Jong Bum Son
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Jia Sun
- Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Alastair Thompson
- Department of Surgery, Baylor College of Medicine, Houston, TX, United States
| | - Debu Tripathy
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Vicente Valero
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Peng Wei
- Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Jason White
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Zhan Xu
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Wei Yang
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Zijian Zhou
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Clinton Yam
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Gaiane M. Rauch
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
- Department of Abdominal Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Jingfei Ma
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
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6
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Patel MM, Adrada BE, Fowler AM, Rauch GM. Molecular Breast Imaging and Positron Emission Mammography. PET Clin 2023; 18:487-501. [PMID: 37258343 DOI: 10.1016/j.cpet.2023.04.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/02/2023]
Abstract
There is growing interest in application of functional imaging modalities for adjunct breast imaging due to their unique ability to evaluate molecular/pathophysiologic changes, not visible by standard anatomic breast imaging. This has led to increased use of nuclear medicine dedicated breast-specific single photon and coincidence imaging systems for multiple indications, such as supplemental screening, staging of newly diagnosed breast cancer, evaluation of response to neoadjuvant treatment, diagnosis of local disease recurrence in the breast, and problem solving. Studies show that these systems maybe especially useful for specific subsets of patients, not well served by available anatomic breast imaging modalities.
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Affiliation(s)
- Miral M Patel
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, 1515 Holcombe, CPB5.3208, Houston, TX 77030, USA.
| | - Beatriz Elena Adrada
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, 1515 Holcombe, CPB5.3208, Houston, TX 77030, USA
| | - Amy M Fowler
- Department of Radiology, Section of Breast Imaging and Intervention, University of Wisconsin - Madison, 600 Highland Avenue, Madison, WI 53792-3252, USA; Department of Medical Physics, University of Wisconsin Carbone Cancer Center, University of Wisconsin-Madison, 600 Highland Avenue, Madison, WI 53792-3252, USA
| | - Gaiane M Rauch
- Department of Abdominal Imaging, The University of Texas MD Anderson Cancer Center, 1515 Holcombe, Unit 1473, Houston, TX 77030, USA; Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, 1515 Holcombe, Unit 1473, Houston, TX 77030, USA
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7
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Adrada BE, Moseley TW, Kapoor MM, Scoggins ME, Patel MM, Perez F, Nia ES, Khazai L, Arribas E, Rauch GM, Guirguis MS. Triple-Negative Breast Cancer: Histopathologic Features, Genomics, and Treatment. Radiographics 2023; 43:e230034. [PMID: 37792593 PMCID: PMC10560981 DOI: 10.1148/rg.230034] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2023] [Revised: 05/09/2023] [Accepted: 06/01/2023] [Indexed: 10/06/2023]
Abstract
Triple-negative breast cancer (TNBC) is a heterogeneous and aggressive group of tumors that are defined by the absence of estrogen and progesterone receptors and lack of ERBB2 (formerly HER2 or HER2/neu) overexpression. TNBC accounts for 8%-13% of breast cancers. In addition, it accounts for a higher proportion of breast cancers in younger women compared with those in older women, and it disproportionately affects non-Hispanic Black women. TNBC has high metastatic potential, and the risk of recurrence is highest during the 5 years after it is diagnosed. TNBC exhibits benign morphologic imaging features more frequently than do other breast cancer subtypes. Mammography can be suboptimal for early detection of TNBC owing to factors that include the fast growth of this cancer, increased mammographic density in young women, and lack of the typical features of malignancy at imaging. US is superior to mammography for TNBC detection, but benign-appearing features can lead to misdiagnosis. Breast MRI is the most sensitive modality for TNBC detection. Most cases of TNBC are treated with neoadjuvant chemotherapy, followed by surgery and radiation. MRI is the modality of choice for evaluating the response to neoadjuvant chemotherapy. Survival rates for individuals with TNBC are lower than those for persons with hormone receptor-positive and human epidermal growth factor receptor 2-positive cancers. The 5-year survival rates for patients with localized, regional, and distant disease at diagnosis are 91.3%, 65.8%, and 12.0%, respectively. The early success of immunotherapy has raised hope regarding the development of personalized strategies to treat TNBC. Imaging and tumor biomarkers are likely to play a crucial role in the prediction of TNBC treatment response and TNBC patient survival in the future. ©RSNA, 2023 Quiz questions for this article are available in the supplemental material.
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Affiliation(s)
- Beatriz E. Adrada
- From the Departments of Breast Imaging (B.E.A., T.W.M., M.M.K.,
M.E.S., M.M.P., F.P., E.S.N., E.A., G.M.R., M.S.G.), Breast Surgical Oncology
(T.W.M.), Pathology-Anatomical (L.K.), and Abdominal Imaging (G.M.R.), The
University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Unit 1350,
Houston, TX 77030
| | - Tanya W. Moseley
- From the Departments of Breast Imaging (B.E.A., T.W.M., M.M.K.,
M.E.S., M.M.P., F.P., E.S.N., E.A., G.M.R., M.S.G.), Breast Surgical Oncology
(T.W.M.), Pathology-Anatomical (L.K.), and Abdominal Imaging (G.M.R.), The
University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Unit 1350,
Houston, TX 77030
| | - Megha M. Kapoor
- From the Departments of Breast Imaging (B.E.A., T.W.M., M.M.K.,
M.E.S., M.M.P., F.P., E.S.N., E.A., G.M.R., M.S.G.), Breast Surgical Oncology
(T.W.M.), Pathology-Anatomical (L.K.), and Abdominal Imaging (G.M.R.), The
University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Unit 1350,
Houston, TX 77030
| | - Marion E. Scoggins
- From the Departments of Breast Imaging (B.E.A., T.W.M., M.M.K.,
M.E.S., M.M.P., F.P., E.S.N., E.A., G.M.R., M.S.G.), Breast Surgical Oncology
(T.W.M.), Pathology-Anatomical (L.K.), and Abdominal Imaging (G.M.R.), The
University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Unit 1350,
Houston, TX 77030
| | - Miral M. Patel
- From the Departments of Breast Imaging (B.E.A., T.W.M., M.M.K.,
M.E.S., M.M.P., F.P., E.S.N., E.A., G.M.R., M.S.G.), Breast Surgical Oncology
(T.W.M.), Pathology-Anatomical (L.K.), and Abdominal Imaging (G.M.R.), The
University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Unit 1350,
Houston, TX 77030
| | - Frances Perez
- From the Departments of Breast Imaging (B.E.A., T.W.M., M.M.K.,
M.E.S., M.M.P., F.P., E.S.N., E.A., G.M.R., M.S.G.), Breast Surgical Oncology
(T.W.M.), Pathology-Anatomical (L.K.), and Abdominal Imaging (G.M.R.), The
University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Unit 1350,
Houston, TX 77030
| | - Emily S. Nia
- From the Departments of Breast Imaging (B.E.A., T.W.M., M.M.K.,
M.E.S., M.M.P., F.P., E.S.N., E.A., G.M.R., M.S.G.), Breast Surgical Oncology
(T.W.M.), Pathology-Anatomical (L.K.), and Abdominal Imaging (G.M.R.), The
University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Unit 1350,
Houston, TX 77030
| | - Laila Khazai
- From the Departments of Breast Imaging (B.E.A., T.W.M., M.M.K.,
M.E.S., M.M.P., F.P., E.S.N., E.A., G.M.R., M.S.G.), Breast Surgical Oncology
(T.W.M.), Pathology-Anatomical (L.K.), and Abdominal Imaging (G.M.R.), The
University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Unit 1350,
Houston, TX 77030
| | - Elsa Arribas
- From the Departments of Breast Imaging (B.E.A., T.W.M., M.M.K.,
M.E.S., M.M.P., F.P., E.S.N., E.A., G.M.R., M.S.G.), Breast Surgical Oncology
(T.W.M.), Pathology-Anatomical (L.K.), and Abdominal Imaging (G.M.R.), The
University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Unit 1350,
Houston, TX 77030
| | - Gaiane M. Rauch
- From the Departments of Breast Imaging (B.E.A., T.W.M., M.M.K.,
M.E.S., M.M.P., F.P., E.S.N., E.A., G.M.R., M.S.G.), Breast Surgical Oncology
(T.W.M.), Pathology-Anatomical (L.K.), and Abdominal Imaging (G.M.R.), The
University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Unit 1350,
Houston, TX 77030
| | - Mary S. Guirguis
- From the Departments of Breast Imaging (B.E.A., T.W.M., M.M.K.,
M.E.S., M.M.P., F.P., E.S.N., E.A., G.M.R., M.S.G.), Breast Surgical Oncology
(T.W.M.), Pathology-Anatomical (L.K.), and Abdominal Imaging (G.M.R.), The
University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Unit 1350,
Houston, TX 77030
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8
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Johnson HM, Lin H, Shen Y, Diego EJ, Krishnamurthy S, Yang WT, Smith BD, Valero V, Lucci A, Sun SX, Shaitelman SF, Mitchell MP, Boughey JC, White RL, Rauch GM, Kuerer HM. Patient-Reported Outcomes of Omission of Breast Surgery Following Neoadjuvant Systemic Therapy: A Nonrandomized Clinical Trial. JAMA Netw Open 2023; 6:e2333933. [PMID: 37707811 PMCID: PMC10502524 DOI: 10.1001/jamanetworkopen.2023.33933] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/12/2023] [Accepted: 08/07/2023] [Indexed: 09/15/2023] Open
Abstract
Importance Patients should have an active role in decisions about pursuing or forgoing specific therapies in treatment de-escalation trials. Objective To evaluate longitudinal patient-reported outcomes (PROs) encompassing decisional comfort and health-related quality of life (HRQOL) among patients who elected to enroll in a clinical trial evaluating radiotherapy alone, without breast surgery, for invasive breast cancers with exceptional response to neoadjuvant systemic therapy (NST). Design, Setting, and Participants Prospective, single-group, phase 2 clinical trial at 7 US medical centers. Women aged 40 years or older with invasive cT1-2 N0-1 M0 triple-negative or human epidermal growth factor receptor 2 (ERBB2)-positive breast cancer with no pathologic evidence of residual disease following standard NST enrolled from March 6, 2017, to November 9, 2021. Validated PRO measures were administered at baseline and 6, 12, and 36 months post-radiotherapy. Data were analyzed from January to February 2023. Interventions PRO measures included the Decision Regret Scale (DRS), Functional Assessment of Cancer Therapy-Lymphedema (FACT-B+4), and Breast Cancer Treatment Outcomes Scale (BCTOS). Main Outcomes and Measures Changes in PRO measure scores and subscores over time. Results Among 31 patients, the median (IQR) age was 61 (56-66) years, 26 (84%) were White, and 26 (84%) were non-Hispanic. A total of 15 (48%) had triple-negative disease and 16 (52%) had ERBB2-positive disease. Decisional comfort was high at baseline (median [IQR] DRS score 10 [0-25] on a 0-100 scale, with higher scores indicating higher decisional regret) and significantly increased over time (median [IQR] DRS score at 36 months, 0 [0-20]; P < .001). HRQOL was relatively high at baseline (median [IQR] FACT-B composite score 121 [111-134] on a 0-148 scale, with higher scores indicating higher HRQOL) and significantly increased over time (median [IQR] FACT-B score at 36 months, 128 [116-137]; P = .04). Perceived differences between the affected breast and contralateral breast were minimal at baseline (median [IQR] BCTOS score 1.05 [1.00-1.23] on a 1-4 scale, with higher scores indicating greater differences) and increased significantly over time (median [IQR] BCTOS score at 36 months, 1.36 [1.18-1.64]; P < .001). At 36 months postradiotherapy, the cosmetic subscore was 0.45 points higher than baseline (95% CI, 0.16-0.74; P = .001), whereas function, pain, and edema subscores were not significantly different than baseline. Conclusions and Relevance In this nonrandomized phase 2 clinical trial, analysis of PROs demonstrated an overall positive experience for trial participants, with longitudinal improvements in decisional comfort and overall HRQOL over time and minimal lasting adverse effects of therapy. Trial Registration ClinicalTrials.gov Identifier: NCT02945579.
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Affiliation(s)
- Helen M. Johnson
- Department of Breast Surgical Oncology, The University of Texas MD Anderson Cancer Center, Houston
| | - Heather Lin
- Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston
| | - Yu Shen
- Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston
| | - Emilia J. Diego
- Division of Breast Surgery, University of Pittsburgh Medical Center Magee-Womens Hospital, Pittsburgh, Pennsylvania
| | | | - Wei T. Yang
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston
| | - Benjamin D. Smith
- Department of Breast Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston
| | - Vicente Valero
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston
| | - Anthony Lucci
- Department of Breast Surgical Oncology, The University of Texas MD Anderson Cancer Center, Houston
| | - Susie X. Sun
- Department of Breast Surgical Oncology, The University of Texas MD Anderson Cancer Center, Houston
| | - Simona F. Shaitelman
- Department of Breast Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston
| | - Melissa P. Mitchell
- Department of Breast Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston
| | - Judy C. Boughey
- Division of Breast and Melanoma Surgical Oncology, Department of Surgery, Mayo Clinic, Rochester, Minnesota
| | - Richard L. White
- Division of Surgical Oncology, Department of Surgery, Carolinas Medical Center, Levine Cancer Institute, Atrium Health, Charlotte, North Carolina
| | - Gaiane M. Rauch
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston
- Department of Abdominal Imaging, The University of Texas MD Anderson Cancer Center, Houston
| | - Henry M. Kuerer
- Department of Breast Surgical Oncology, The University of Texas MD Anderson Cancer Center, Houston
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9
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Paroder V, Fraum TJ, Nougaret S, Petkovska I, Rauch GM, Kaur H. Key clinical trials in rectal cancer shaping the current treatment paradigms: reference guide for radiologists. Abdom Radiol (NY) 2023; 48:2825-2835. [PMID: 37221342 DOI: 10.1007/s00261-023-03931-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2023] [Revised: 04/18/2023] [Accepted: 04/18/2023] [Indexed: 05/25/2023]
Abstract
Total neoadjuvant therapy (TNT), which includes chemotherapy and radiation prior to surgical resection, has been recently accepted as the new standard of care for patients with locally advanced low and mid rectal cancers. Multiple clinical trials have evaluated this approach in the last several decades and demonstrated improvement in, local control and reduced risk of recurrence. In addition, in the course of these investigations, it has been shown that between a third and a half of patients experience a clinical complete response (cCR) after being treated with the TNT approach, leading to the development of new organ preservation protocol, now known as watch-and-wait (W&W). On this protocol, cCR patients are not referred for surgery after total neoadjuvant treatment. Instead, they remain on close surveillance and, thus, avoid potential complications associated with surgical resection. Multiple clinical trials are ongoing, investigating the long-term outcomes of these new approaches and the development of less toxic and more effective TNT regimens for LARC. Improvements in technology and rectal MRI protocols position radiologists as vital members of multidisciplinary rectal cancer management teams. Rectal MRI has become a critical tool for rectal cancer initial staging, treatment response assessment, and surveillance on W&W protocols. In this review, we summarize the findings of the pivotal clinical trials that contributed to establishing the current treatment paradigms in locally advanced rectal cancer (LARC) management, with the intention of helping radiologists play more effective roles in their multidisciplinary teams.
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Affiliation(s)
- Viktoriya Paroder
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
| | - Tyler J Fraum
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, Saint Louis, MO, USA
| | - Stephanie Nougaret
- Department of Radiology, Montpellier Cancer Institute (ICM), Montpellier, France
| | - Iva Petkovska
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Gaiane M Rauch
- Department of Diagnostic Radiology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Harmeet Kaur
- Department of Diagnostic Radiology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
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10
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Golia Pernicka JS, Rauch GM, Gangai N, Bates DDB, Ernst R, Hope TA, Horvat N, Sheedy SP, Gollub MJ. Imaging of Anal Squamous Cell Carcinoma: Survey Results and Expert Opinion from the Rectal and Anal Cancer Disease-Focused Panel of the Society of Abdominal Radiology. Abdom Radiol (NY) 2023; 48:3022-3032. [PMID: 36932225 PMCID: PMC10929685 DOI: 10.1007/s00261-023-03863-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2023] [Revised: 02/17/2023] [Accepted: 02/20/2023] [Indexed: 03/19/2023]
Abstract
The role and method of image-based staging of anal cancer has evolved with the rapid development of newer imaging modalities and the need to address the rising incidence of this rare cancer. In 2014, the European Society of Medical Oncology mandated pelvic magnetic resonance imaging (MRI) for anal cancer and subsequently other societies such as the National Comprehensive Cancer Network followed suit with similar recommendations. Nevertheless, great variability exists from center to center and even within individual centers. Notably, this is in stark contrast to the imaging of the anatomically nearby rectal cancer. As participating team members for this malignancy, we embarked on a comprehensive literature review of anal cancer imaging to understand the relative merits of these new technologies which developed after computed tomography (CT), e.g., MRI and positron emission tomography/computed tomography (PET/CT). The results of this literature review helped to inform our next stage: questionnaire development regarding the imaging of anal cancer. Next, we distributed the questionnaire to members of the Society of Abdominal Radiology (SAR) Rectal and Anal Disease-Focused Panel, a group of abdominal radiologists with special interest, experience, and expertise in rectal and anal cancer, to provide expert radiologist opinion on the appropriate anal cancer imaging strategy. In our expert opinion survey, experts advocated the use of MRI in general (65% overall and 91-100% for primary staging clinical scenarios) and acknowledged the superiority of PET/CT for nodal assessment (52-56% agreement for using PET/CT in primary staging clinical scenarios compared to 30% for using MRI). We therefore support the use of MRI and PET and suggest further exploration of PET/MRI as an optimal combined evaluation. Our questionnaire responses emphasized the heterogeneity in imaging practice as performed at numerous academic cancer centers across the United States and underscore the need for further reconciliation and establishment of best imaging practice guidelines for optimized patient care in anal cancer.
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Affiliation(s)
- Jennifer S Golia Pernicka
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, 10065, USA.
- , 530 E 74th St, Room 07118, New York, NY, 10021, USA.
| | - Gaiane M Rauch
- Department of Radiology, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Natalie Gangai
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, 10065, USA
| | - David D B Bates
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, 10065, USA
| | - Randy Ernst
- Department of Radiology, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Thomas A Hope
- Departments of Radiology and Biomedical Imaging and Pharmaceutical Chemistry, University of California San Francisco, San Francisco, CA, USA
| | - Natally Horvat
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, 10065, USA
| | | | - Marc J Gollub
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, 10065, USA
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11
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El Homsi M, Sheedy SP, Rauch GM, Ganeshan DM, Ernst RD, Golia Pernicka JS. Follow-up imaging of anal cancer after treatment. Abdom Radiol (NY) 2023; 48:2888-2897. [PMID: 37024606 DOI: 10.1007/s00261-023-03895-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2022] [Revised: 03/21/2023] [Accepted: 03/21/2023] [Indexed: 04/08/2023]
Abstract
Anal cancer treatment response assessment can be challenging with both magnetic resonance imaging (MRI) and clinical evaluation considered essential. MRI, in particular, has shown to be useful for the assessment of treatment response, the detection of recurrent disease in follow up and surveillance, and the evaluation of possible post-treatment complications as well as complications from the tumor itself. In this review, we focus on the role of imaging, mainly MRI, in anal cancer treatment response assessment. We also describe the treatment complications that can occur, and the imaging findings associated with those complications.
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Affiliation(s)
- Maria El Homsi
- Department of Radiology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY, 10065, USA
| | | | - Gaiane M Rauch
- Department of Abdominal Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Dhakshina M Ganeshan
- Department of Abdominal Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Randy D Ernst
- Department of Abdominal Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Jennifer S Golia Pernicka
- Department of Radiology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY, 10065, USA.
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12
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Chen H, Ding Q, Khazai L, Zhao L, Damodaran S, Litton JK, Rauch GM, Yam C, Chang JT, Seth S, Lim B, Thompson AM, Mittendorf EA, Adrada B, Virani K, White JB, Ravenberg E, Song X, Candelaria R, Arun B, Ueno NT, Santiago L, Saleem S, Abouharb S, Murthy RK, Ibrahim N, Routbort MJ, Sahin A, Valero V, Symmans WF, Tripathy D, Wang WL, Moulder S, Huo L. PTEN in triple-negative breast carcinoma: protein expression and genomic alteration in pretreatment and posttreatment specimens. Ther Adv Med Oncol 2023; 15:17588359231189422. [PMID: 37547448 PMCID: PMC10399250 DOI: 10.1177/17588359231189422] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2023] [Accepted: 07/05/2023] [Indexed: 08/08/2023] Open
Abstract
Background Recent advances have been made in targeting the phosphoinositide 3-kinase pathway in breast cancer. Phosphatase and tensin homolog (PTEN) is a key component of that pathway. Objective To understand the changes in PTEN expression over the course of the disease in patients with triple-negative breast cancer (TNBC) and whether PTEN copy number variation (CNV) by next-generation sequencing (NGS) can serve as an alternative to immunohistochemistry (IHC) to identify PTEN loss. Methods We compared PTEN expression by IHC between pretreatment tumors and residual tumors in the breast and lymph nodes after neoadjuvant chemotherapy in 96 patients enrolled in a TNBC clinical trial. A correlative analysis between PTEN protein expression and PTEN CNV by NGS was also performed. Results With a stringent cutoff for PTEN IHC scoring, PTEN expression was discordant between pretreatment and posttreatment primary tumors in 5% of patients (n = 96) and between posttreatment primary tumors and lymph node metastases in 9% (n = 33). A less stringent cutoff yielded similar discordance rates. Intratumoral heterogeneity for PTEN loss was observed in 7% of the patients. Among pretreatment tumors, PTEN copy numbers by whole exome sequencing (n = 72) were significantly higher in the PTEN-positive tumors by IHC compared with the IHC PTEN-loss tumors (p < 0.0001). However, PTEN-positive and PTEN-loss tumors by IHC overlapped in copy numbers: 14 of 60 PTEN-positive samples showed decreased copy numbers in the range of those of the PTEN-loss tumors. Conclusion Testing various specimens by IHC may generate different PTEN results in a small proportion of patients with TNBC; therefore, the decision of testing one versus multiple specimens in a clinical trial should be defined in the patient inclusion criteria. Although a distinct cutoff by which CNV differentiated PTEN-positive tumors from those with PTEN loss was not identified, higher copy number of PTEN may confer positive PTEN, whereas lower copy number of PTEN would necessitate additional testing by IHC to assess PTEN loss. Trial registration NCT02276443.
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Affiliation(s)
- Hui Chen
- Department of Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Qingqing Ding
- Department of Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Laila Khazai
- Department of Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Li Zhao
- Department of Genomic Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Senthil Damodaran
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Jennifer K. Litton
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Gaiane M. Rauch
- Division of Diagnostic Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Clinton Yam
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Jeffrey T. Chang
- Department of Integrative Biology and Pharmacology, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Sahil Seth
- Department of Genomic Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Bora Lim
- Department of Oncology, Baylor College of Medicine, Houston, TX, USA
| | - Alastair M. Thompson
- Division of Surgical Oncology, Section of Breast Surgery, Baylor College of Medicine, Houston, TX, USA
| | - Elizabeth A. Mittendorf
- Division of Breast Surgery, Department of Surgery, Brigham and Women’s Hospital, Boston, MA, USA
| | - Beatriz Adrada
- Division of Diagnostic Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Kiran Virani
- Division of Pathology and Laboratory Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Jason B. White
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Elizabeth Ravenberg
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Xingzhi Song
- Department of Genomic Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Rosalind Candelaria
- Division of Diagnostic Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Banu Arun
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Naoto T. Ueno
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Lumarie Santiago
- Division of Diagnostic Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Sadia Saleem
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Sausan Abouharb
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Rashmi K. Murthy
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Nuhad Ibrahim
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | | | - Aysegul Sahin
- Department of Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Vicente Valero
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - William Fraser Symmans
- Department of Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Debu Tripathy
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Wei-Lien Wang
- Department of Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Stacy Moulder
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Lei Huo
- Department of Pathology, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX 77030, USA
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Zhou Z, Adrada BE, Candelaria RP, Elshafeey NA, Boge M, Mohamed RM, Pashapoor S, Sun J, Xu Z, Panthi B, Son JB, Guirguis MS, Patel MM, Whitman GJ, Moseley TW, Scoggins ME, White JB, Litton JK, Valero V, Hunt KK, Tripathy D, Yang W, Wei P, Yam C, Pagel MD, Rauch GM, Ma J. Predicting pathological complete response to neoadjuvant systemic therapy for triple-negative breast cancers using deep learning on multiparametric MRIs. Annu Int Conf IEEE Eng Med Biol Soc 2023; 2023:1-4. [PMID: 38083160 DOI: 10.1109/embc40787.2023.10340987] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/18/2023]
Abstract
We trained and validated a deep learning model that can predict the treatment response to neoadjuvant systemic therapy (NAST) for patients with triple negative breast cancer (TNBC). Dynamic contrast enhanced (DCE) MRI and diffusion-weighted imaging (DWI) of the pre-treatment (baseline) and after four cycles (C4) of doxorubicin/cyclophosphamide treatment were used as inputs to the model for prediction of pathologic complete response (pCR). Based on the standard pCR definition that includes disease status in either breast or axilla, the model achieved areas under the receiver operating characteristic curves (AUCs) of 0.96 ± 0.05, 0.78 ± 0.09, 0.88 ± 0.02, and 0.76 ± 0.03, for the training, validation, testing, and prospective testing groups, respectively. For the pCR status of breast only, the retrained model achieved prediction AUCs of 0.97 ± 0.04, 0.82 ± 0.10, 0.86 ± 0.03, and 0.83 ± 0.02, for the training, validation, testing, and prospective testing groups, respectively. Thus, the developed deep learning model is highly promising for predicting the treatment response to NAST of TNBC.Clinical Relevance- Deep learning based on serial and multiparametric MRIs can potentially distinguish TNBC patients with pCR from non-pCR at the early stage of neoadjuvant systemic therapy, potentially enabling more personalized treatment of TNBC patients.
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14
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Hwang KP, Elshafeey NA, Kotrotsou A, Chen H, Son JB, Boge M, Mohamed RM, Abdelhafez AH, Adrada BE, Panthi B, Sun J, Musall BC, Zhang S, Candelaria RP, White JB, Ravenberg EE, Tripathy D, Yam C, Litton JK, Huo L, Thompson AM, Wei P, Yang WT, Pagel MD, Ma J, Rauch GM. A Radiomics Model Based on Synthetic MRI Acquisition for Predicting Neoadjuvant Systemic Treatment Response in Triple-Negative Breast Cancer. Radiol Imaging Cancer 2023; 5:e230009. [PMID: 37505106 PMCID: PMC10413296 DOI: 10.1148/rycan.230009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2023] [Revised: 04/18/2023] [Accepted: 06/03/2023] [Indexed: 07/29/2023]
Abstract
Purpose To determine if a radiomics model based on quantitative maps acquired with synthetic MRI (SyMRI) is useful for predicting neoadjuvant systemic therapy (NAST) response in triple-negative breast cancer (TNBC). Materials and Methods In this prospective study, 181 women diagnosed with stage I-III TNBC were scanned with a SyMRI sequence at baseline and at midtreatment (after four cycles of NAST), producing T1, T2, and proton density (PD) maps. Histopathologic analysis at surgery was used to determine pathologic complete response (pCR) or non-pCR status. From three-dimensional tumor contours drawn on the three maps, 310 histogram and textural features were extracted, resulting in 930 features per scan. Radiomic features were compared between pCR and non-pCR groups by using Wilcoxon rank sum test. To build a multivariable predictive model, logistic regression with elastic net regularization and cross-validation was performed for texture feature selection using 119 participants (median age, 52 years [range, 26-77 years]). An independent testing cohort of 62 participants (median age, 48 years [range, 23-74 years]) was used to evaluate and compare the models by area under the receiver operating characteristic curve (AUC). Results Univariable analysis identified 15 T1, 10 T2, and 12 PD radiomic features at midtreatment that predicted pCR with an AUC greater than 0.70 in both the training and testing cohorts. Multivariable radiomics models of maps acquired at midtreatment demonstrated superior performance over those acquired at baseline, achieving AUCs as high as 0.78 and 0.72 in the training and testing cohorts, respectively. Conclusion SyMRI-based radiomic features acquired at midtreatment are potentially useful for identifying early NAST responders in TNBC. Keywords: MR Imaging, Breast, Outcomes Analysis ClinicalTrials.gov registration no. NCT02276443 Supplemental material is available for this article. © RSNA, 2023 See also the commentary by Houser and Rapelyea in this issue.
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Affiliation(s)
- Ken-Pin Hwang
- From the Departments of Imaging Physics (K.P.H., A.K., J.B.S., B.P.,
B.C.M., J.M.), Breast Imaging (N.A.E., M.B., R.M.M., A.H.A., B.E.A., R.P.C.,
W.T.Y., G.M.R.), Biostatistics (H.C., J.S., P.W.), Cancer Systems Imaging (S.Z.,
M.D.P.), Moon Shots Operations (J.B.W.), Breast Medical Oncology (E.E.R., D.T.,
C.Y.), Clinical Research (J.K.L.), Pathology (L.H.), and Abdominal Imaging
(G.M.R.), The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd,
Houston, TX 77030; and Division of Surgical Oncology, Baylor College of
Medicine, Houston, Tex (A.M.T.)
| | - Nabil A. Elshafeey
- From the Departments of Imaging Physics (K.P.H., A.K., J.B.S., B.P.,
B.C.M., J.M.), Breast Imaging (N.A.E., M.B., R.M.M., A.H.A., B.E.A., R.P.C.,
W.T.Y., G.M.R.), Biostatistics (H.C., J.S., P.W.), Cancer Systems Imaging (S.Z.,
M.D.P.), Moon Shots Operations (J.B.W.), Breast Medical Oncology (E.E.R., D.T.,
C.Y.), Clinical Research (J.K.L.), Pathology (L.H.), and Abdominal Imaging
(G.M.R.), The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd,
Houston, TX 77030; and Division of Surgical Oncology, Baylor College of
Medicine, Houston, Tex (A.M.T.)
| | - Aikaterini Kotrotsou
- From the Departments of Imaging Physics (K.P.H., A.K., J.B.S., B.P.,
B.C.M., J.M.), Breast Imaging (N.A.E., M.B., R.M.M., A.H.A., B.E.A., R.P.C.,
W.T.Y., G.M.R.), Biostatistics (H.C., J.S., P.W.), Cancer Systems Imaging (S.Z.,
M.D.P.), Moon Shots Operations (J.B.W.), Breast Medical Oncology (E.E.R., D.T.,
C.Y.), Clinical Research (J.K.L.), Pathology (L.H.), and Abdominal Imaging
(G.M.R.), The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd,
Houston, TX 77030; and Division of Surgical Oncology, Baylor College of
Medicine, Houston, Tex (A.M.T.)
| | - Huiqin Chen
- From the Departments of Imaging Physics (K.P.H., A.K., J.B.S., B.P.,
B.C.M., J.M.), Breast Imaging (N.A.E., M.B., R.M.M., A.H.A., B.E.A., R.P.C.,
W.T.Y., G.M.R.), Biostatistics (H.C., J.S., P.W.), Cancer Systems Imaging (S.Z.,
M.D.P.), Moon Shots Operations (J.B.W.), Breast Medical Oncology (E.E.R., D.T.,
C.Y.), Clinical Research (J.K.L.), Pathology (L.H.), and Abdominal Imaging
(G.M.R.), The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd,
Houston, TX 77030; and Division of Surgical Oncology, Baylor College of
Medicine, Houston, Tex (A.M.T.)
| | - Jong Bum Son
- From the Departments of Imaging Physics (K.P.H., A.K., J.B.S., B.P.,
B.C.M., J.M.), Breast Imaging (N.A.E., M.B., R.M.M., A.H.A., B.E.A., R.P.C.,
W.T.Y., G.M.R.), Biostatistics (H.C., J.S., P.W.), Cancer Systems Imaging (S.Z.,
M.D.P.), Moon Shots Operations (J.B.W.), Breast Medical Oncology (E.E.R., D.T.,
C.Y.), Clinical Research (J.K.L.), Pathology (L.H.), and Abdominal Imaging
(G.M.R.), The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd,
Houston, TX 77030; and Division of Surgical Oncology, Baylor College of
Medicine, Houston, Tex (A.M.T.)
| | - Medine Boge
- From the Departments of Imaging Physics (K.P.H., A.K., J.B.S., B.P.,
B.C.M., J.M.), Breast Imaging (N.A.E., M.B., R.M.M., A.H.A., B.E.A., R.P.C.,
W.T.Y., G.M.R.), Biostatistics (H.C., J.S., P.W.), Cancer Systems Imaging (S.Z.,
M.D.P.), Moon Shots Operations (J.B.W.), Breast Medical Oncology (E.E.R., D.T.,
C.Y.), Clinical Research (J.K.L.), Pathology (L.H.), and Abdominal Imaging
(G.M.R.), The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd,
Houston, TX 77030; and Division of Surgical Oncology, Baylor College of
Medicine, Houston, Tex (A.M.T.)
| | - Rania M. Mohamed
- From the Departments of Imaging Physics (K.P.H., A.K., J.B.S., B.P.,
B.C.M., J.M.), Breast Imaging (N.A.E., M.B., R.M.M., A.H.A., B.E.A., R.P.C.,
W.T.Y., G.M.R.), Biostatistics (H.C., J.S., P.W.), Cancer Systems Imaging (S.Z.,
M.D.P.), Moon Shots Operations (J.B.W.), Breast Medical Oncology (E.E.R., D.T.,
C.Y.), Clinical Research (J.K.L.), Pathology (L.H.), and Abdominal Imaging
(G.M.R.), The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd,
Houston, TX 77030; and Division of Surgical Oncology, Baylor College of
Medicine, Houston, Tex (A.M.T.)
| | - Abeer H. Abdelhafez
- From the Departments of Imaging Physics (K.P.H., A.K., J.B.S., B.P.,
B.C.M., J.M.), Breast Imaging (N.A.E., M.B., R.M.M., A.H.A., B.E.A., R.P.C.,
W.T.Y., G.M.R.), Biostatistics (H.C., J.S., P.W.), Cancer Systems Imaging (S.Z.,
M.D.P.), Moon Shots Operations (J.B.W.), Breast Medical Oncology (E.E.R., D.T.,
C.Y.), Clinical Research (J.K.L.), Pathology (L.H.), and Abdominal Imaging
(G.M.R.), The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd,
Houston, TX 77030; and Division of Surgical Oncology, Baylor College of
Medicine, Houston, Tex (A.M.T.)
| | - Beatriz E. Adrada
- From the Departments of Imaging Physics (K.P.H., A.K., J.B.S., B.P.,
B.C.M., J.M.), Breast Imaging (N.A.E., M.B., R.M.M., A.H.A., B.E.A., R.P.C.,
W.T.Y., G.M.R.), Biostatistics (H.C., J.S., P.W.), Cancer Systems Imaging (S.Z.,
M.D.P.), Moon Shots Operations (J.B.W.), Breast Medical Oncology (E.E.R., D.T.,
C.Y.), Clinical Research (J.K.L.), Pathology (L.H.), and Abdominal Imaging
(G.M.R.), The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd,
Houston, TX 77030; and Division of Surgical Oncology, Baylor College of
Medicine, Houston, Tex (A.M.T.)
| | - Bikash Panthi
- From the Departments of Imaging Physics (K.P.H., A.K., J.B.S., B.P.,
B.C.M., J.M.), Breast Imaging (N.A.E., M.B., R.M.M., A.H.A., B.E.A., R.P.C.,
W.T.Y., G.M.R.), Biostatistics (H.C., J.S., P.W.), Cancer Systems Imaging (S.Z.,
M.D.P.), Moon Shots Operations (J.B.W.), Breast Medical Oncology (E.E.R., D.T.,
C.Y.), Clinical Research (J.K.L.), Pathology (L.H.), and Abdominal Imaging
(G.M.R.), The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd,
Houston, TX 77030; and Division of Surgical Oncology, Baylor College of
Medicine, Houston, Tex (A.M.T.)
| | - Jia Sun
- From the Departments of Imaging Physics (K.P.H., A.K., J.B.S., B.P.,
B.C.M., J.M.), Breast Imaging (N.A.E., M.B., R.M.M., A.H.A., B.E.A., R.P.C.,
W.T.Y., G.M.R.), Biostatistics (H.C., J.S., P.W.), Cancer Systems Imaging (S.Z.,
M.D.P.), Moon Shots Operations (J.B.W.), Breast Medical Oncology (E.E.R., D.T.,
C.Y.), Clinical Research (J.K.L.), Pathology (L.H.), and Abdominal Imaging
(G.M.R.), The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd,
Houston, TX 77030; and Division of Surgical Oncology, Baylor College of
Medicine, Houston, Tex (A.M.T.)
| | - Benjamin C. Musall
- From the Departments of Imaging Physics (K.P.H., A.K., J.B.S., B.P.,
B.C.M., J.M.), Breast Imaging (N.A.E., M.B., R.M.M., A.H.A., B.E.A., R.P.C.,
W.T.Y., G.M.R.), Biostatistics (H.C., J.S., P.W.), Cancer Systems Imaging (S.Z.,
M.D.P.), Moon Shots Operations (J.B.W.), Breast Medical Oncology (E.E.R., D.T.,
C.Y.), Clinical Research (J.K.L.), Pathology (L.H.), and Abdominal Imaging
(G.M.R.), The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd,
Houston, TX 77030; and Division of Surgical Oncology, Baylor College of
Medicine, Houston, Tex (A.M.T.)
| | - Shu Zhang
- From the Departments of Imaging Physics (K.P.H., A.K., J.B.S., B.P.,
B.C.M., J.M.), Breast Imaging (N.A.E., M.B., R.M.M., A.H.A., B.E.A., R.P.C.,
W.T.Y., G.M.R.), Biostatistics (H.C., J.S., P.W.), Cancer Systems Imaging (S.Z.,
M.D.P.), Moon Shots Operations (J.B.W.), Breast Medical Oncology (E.E.R., D.T.,
C.Y.), Clinical Research (J.K.L.), Pathology (L.H.), and Abdominal Imaging
(G.M.R.), The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd,
Houston, TX 77030; and Division of Surgical Oncology, Baylor College of
Medicine, Houston, Tex (A.M.T.)
| | - Rosalind P. Candelaria
- From the Departments of Imaging Physics (K.P.H., A.K., J.B.S., B.P.,
B.C.M., J.M.), Breast Imaging (N.A.E., M.B., R.M.M., A.H.A., B.E.A., R.P.C.,
W.T.Y., G.M.R.), Biostatistics (H.C., J.S., P.W.), Cancer Systems Imaging (S.Z.,
M.D.P.), Moon Shots Operations (J.B.W.), Breast Medical Oncology (E.E.R., D.T.,
C.Y.), Clinical Research (J.K.L.), Pathology (L.H.), and Abdominal Imaging
(G.M.R.), The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd,
Houston, TX 77030; and Division of Surgical Oncology, Baylor College of
Medicine, Houston, Tex (A.M.T.)
| | - Jason B. White
- From the Departments of Imaging Physics (K.P.H., A.K., J.B.S., B.P.,
B.C.M., J.M.), Breast Imaging (N.A.E., M.B., R.M.M., A.H.A., B.E.A., R.P.C.,
W.T.Y., G.M.R.), Biostatistics (H.C., J.S., P.W.), Cancer Systems Imaging (S.Z.,
M.D.P.), Moon Shots Operations (J.B.W.), Breast Medical Oncology (E.E.R., D.T.,
C.Y.), Clinical Research (J.K.L.), Pathology (L.H.), and Abdominal Imaging
(G.M.R.), The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd,
Houston, TX 77030; and Division of Surgical Oncology, Baylor College of
Medicine, Houston, Tex (A.M.T.)
| | - Elizabeth E. Ravenberg
- From the Departments of Imaging Physics (K.P.H., A.K., J.B.S., B.P.,
B.C.M., J.M.), Breast Imaging (N.A.E., M.B., R.M.M., A.H.A., B.E.A., R.P.C.,
W.T.Y., G.M.R.), Biostatistics (H.C., J.S., P.W.), Cancer Systems Imaging (S.Z.,
M.D.P.), Moon Shots Operations (J.B.W.), Breast Medical Oncology (E.E.R., D.T.,
C.Y.), Clinical Research (J.K.L.), Pathology (L.H.), and Abdominal Imaging
(G.M.R.), The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd,
Houston, TX 77030; and Division of Surgical Oncology, Baylor College of
Medicine, Houston, Tex (A.M.T.)
| | - Debu Tripathy
- From the Departments of Imaging Physics (K.P.H., A.K., J.B.S., B.P.,
B.C.M., J.M.), Breast Imaging (N.A.E., M.B., R.M.M., A.H.A., B.E.A., R.P.C.,
W.T.Y., G.M.R.), Biostatistics (H.C., J.S., P.W.), Cancer Systems Imaging (S.Z.,
M.D.P.), Moon Shots Operations (J.B.W.), Breast Medical Oncology (E.E.R., D.T.,
C.Y.), Clinical Research (J.K.L.), Pathology (L.H.), and Abdominal Imaging
(G.M.R.), The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd,
Houston, TX 77030; and Division of Surgical Oncology, Baylor College of
Medicine, Houston, Tex (A.M.T.)
| | - Clinton Yam
- From the Departments of Imaging Physics (K.P.H., A.K., J.B.S., B.P.,
B.C.M., J.M.), Breast Imaging (N.A.E., M.B., R.M.M., A.H.A., B.E.A., R.P.C.,
W.T.Y., G.M.R.), Biostatistics (H.C., J.S., P.W.), Cancer Systems Imaging (S.Z.,
M.D.P.), Moon Shots Operations (J.B.W.), Breast Medical Oncology (E.E.R., D.T.,
C.Y.), Clinical Research (J.K.L.), Pathology (L.H.), and Abdominal Imaging
(G.M.R.), The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd,
Houston, TX 77030; and Division of Surgical Oncology, Baylor College of
Medicine, Houston, Tex (A.M.T.)
| | - Jennifer K. Litton
- From the Departments of Imaging Physics (K.P.H., A.K., J.B.S., B.P.,
B.C.M., J.M.), Breast Imaging (N.A.E., M.B., R.M.M., A.H.A., B.E.A., R.P.C.,
W.T.Y., G.M.R.), Biostatistics (H.C., J.S., P.W.), Cancer Systems Imaging (S.Z.,
M.D.P.), Moon Shots Operations (J.B.W.), Breast Medical Oncology (E.E.R., D.T.,
C.Y.), Clinical Research (J.K.L.), Pathology (L.H.), and Abdominal Imaging
(G.M.R.), The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd,
Houston, TX 77030; and Division of Surgical Oncology, Baylor College of
Medicine, Houston, Tex (A.M.T.)
| | - Lei Huo
- From the Departments of Imaging Physics (K.P.H., A.K., J.B.S., B.P.,
B.C.M., J.M.), Breast Imaging (N.A.E., M.B., R.M.M., A.H.A., B.E.A., R.P.C.,
W.T.Y., G.M.R.), Biostatistics (H.C., J.S., P.W.), Cancer Systems Imaging (S.Z.,
M.D.P.), Moon Shots Operations (J.B.W.), Breast Medical Oncology (E.E.R., D.T.,
C.Y.), Clinical Research (J.K.L.), Pathology (L.H.), and Abdominal Imaging
(G.M.R.), The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd,
Houston, TX 77030; and Division of Surgical Oncology, Baylor College of
Medicine, Houston, Tex (A.M.T.)
| | - Alastair M. Thompson
- From the Departments of Imaging Physics (K.P.H., A.K., J.B.S., B.P.,
B.C.M., J.M.), Breast Imaging (N.A.E., M.B., R.M.M., A.H.A., B.E.A., R.P.C.,
W.T.Y., G.M.R.), Biostatistics (H.C., J.S., P.W.), Cancer Systems Imaging (S.Z.,
M.D.P.), Moon Shots Operations (J.B.W.), Breast Medical Oncology (E.E.R., D.T.,
C.Y.), Clinical Research (J.K.L.), Pathology (L.H.), and Abdominal Imaging
(G.M.R.), The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd,
Houston, TX 77030; and Division of Surgical Oncology, Baylor College of
Medicine, Houston, Tex (A.M.T.)
| | - Peng Wei
- From the Departments of Imaging Physics (K.P.H., A.K., J.B.S., B.P.,
B.C.M., J.M.), Breast Imaging (N.A.E., M.B., R.M.M., A.H.A., B.E.A., R.P.C.,
W.T.Y., G.M.R.), Biostatistics (H.C., J.S., P.W.), Cancer Systems Imaging (S.Z.,
M.D.P.), Moon Shots Operations (J.B.W.), Breast Medical Oncology (E.E.R., D.T.,
C.Y.), Clinical Research (J.K.L.), Pathology (L.H.), and Abdominal Imaging
(G.M.R.), The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd,
Houston, TX 77030; and Division of Surgical Oncology, Baylor College of
Medicine, Houston, Tex (A.M.T.)
| | - Wei T. Yang
- From the Departments of Imaging Physics (K.P.H., A.K., J.B.S., B.P.,
B.C.M., J.M.), Breast Imaging (N.A.E., M.B., R.M.M., A.H.A., B.E.A., R.P.C.,
W.T.Y., G.M.R.), Biostatistics (H.C., J.S., P.W.), Cancer Systems Imaging (S.Z.,
M.D.P.), Moon Shots Operations (J.B.W.), Breast Medical Oncology (E.E.R., D.T.,
C.Y.), Clinical Research (J.K.L.), Pathology (L.H.), and Abdominal Imaging
(G.M.R.), The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd,
Houston, TX 77030; and Division of Surgical Oncology, Baylor College of
Medicine, Houston, Tex (A.M.T.)
| | - Mark D. Pagel
- From the Departments of Imaging Physics (K.P.H., A.K., J.B.S., B.P.,
B.C.M., J.M.), Breast Imaging (N.A.E., M.B., R.M.M., A.H.A., B.E.A., R.P.C.,
W.T.Y., G.M.R.), Biostatistics (H.C., J.S., P.W.), Cancer Systems Imaging (S.Z.,
M.D.P.), Moon Shots Operations (J.B.W.), Breast Medical Oncology (E.E.R., D.T.,
C.Y.), Clinical Research (J.K.L.), Pathology (L.H.), and Abdominal Imaging
(G.M.R.), The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd,
Houston, TX 77030; and Division of Surgical Oncology, Baylor College of
Medicine, Houston, Tex (A.M.T.)
| | - Jingfei Ma
- From the Departments of Imaging Physics (K.P.H., A.K., J.B.S., B.P.,
B.C.M., J.M.), Breast Imaging (N.A.E., M.B., R.M.M., A.H.A., B.E.A., R.P.C.,
W.T.Y., G.M.R.), Biostatistics (H.C., J.S., P.W.), Cancer Systems Imaging (S.Z.,
M.D.P.), Moon Shots Operations (J.B.W.), Breast Medical Oncology (E.E.R., D.T.,
C.Y.), Clinical Research (J.K.L.), Pathology (L.H.), and Abdominal Imaging
(G.M.R.), The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd,
Houston, TX 77030; and Division of Surgical Oncology, Baylor College of
Medicine, Houston, Tex (A.M.T.)
| | - Gaiane M. Rauch
- From the Departments of Imaging Physics (K.P.H., A.K., J.B.S., B.P.,
B.C.M., J.M.), Breast Imaging (N.A.E., M.B., R.M.M., A.H.A., B.E.A., R.P.C.,
W.T.Y., G.M.R.), Biostatistics (H.C., J.S., P.W.), Cancer Systems Imaging (S.Z.,
M.D.P.), Moon Shots Operations (J.B.W.), Breast Medical Oncology (E.E.R., D.T.,
C.Y.), Clinical Research (J.K.L.), Pathology (L.H.), and Abdominal Imaging
(G.M.R.), The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd,
Houston, TX 77030; and Division of Surgical Oncology, Baylor College of
Medicine, Houston, Tex (A.M.T.)
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15
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Rauch GM. Precision Imaging: One Step Closer to Pretreatment Prediction of Breast Cancer Response to Neoadjuvant Systemic Therapy. Radiology 2023; 308:e231482. [PMID: 37432087 DOI: 10.1148/radiol.231482] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/12/2023]
Affiliation(s)
- Gaiane M Rauch
- From the University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Unit 1473, Houston, TX 77030
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16
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Johnson HM, Valero V, Yang WT, Smith BD, Krishnamurthy S, Shen Y, Lin H, Lucci A, Rauch GM, Kuerer HM. Eliminating Breast Surgery for Invasive Cancer with Exceptional Response to Neoadjuvant Systemic Therapy: Prospective Multicenter Clinical Trial Planned Initial Feasibility Endpoint. J Am Coll Surg 2023; 237:101-108. [PMID: 36856291 DOI: 10.1097/xcs.0000000000000670] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/02/2023]
Abstract
BACKGROUND Response to neoadjuvant systemic therapy (NST) for breast cancer enables tailoring of subsequent therapy. Image-guided breast biopsy after NST can accurately predict a pathologic complete response (pCR). The feasibility phase of the clinical trial reported here assesses omission of breast surgery followed by radiotherapy in terms of local recurrence before trial expansion. STUDY DESIGN Women with unicentric, cT1-2 N0-1 M0 triple-negative (TNBC) or human epidermal growth factor receptor 2-positive breast cancer (HER2+BC) cancer with <2 cm residual disease on post-NST imaging were eligible to enroll. If no residual invasive or in situ disease was identified by image-guided, vacuum-assisted core biopsy (VACB), breast surgery was omitted, and radiotherapy delivered. The primary endpoint for the feasibility phase was ipsilateral breast tumor recurrence at 6 months. If any recurrence occurred during the feasibility phase the trial would halt. RESULTS Thirteen patients were enrolled from March 2017 to October 2018. The mean age was 60.8 years (range 51 to 75) and most patients were White (69.2%) and non-Hispanic/Latino (84.6%). All patients had invasive ductal carcinoma (6 TNBC, 7 HER2+BC). Mean tumor size was 2.4 cm (range 0.9 to 5.0) before NST and 0.7 cm (range 0 to 1.8) after NST. Seven patients (53.8%) had residual disease identified on VACB; the remaining 6 (46.2%) comprised the feasibility cohort. At a median follow-up of 44.3 months (range 41.3 to 51.3) there was no ipsilateral breast tumor recurrence in this cohort. CONCLUSIONS These early data suggest that omission of breast surgery in patients with invasive TNBC and HER2+BC with no evidence of residual disease on standardized VACB after NST is potentially feasible. Results from the expansion phase of this clinical trial will be reported per protocol prespecified analyses.
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Affiliation(s)
- Helen M Johnson
- From the Departments of Breast Surgical Oncology (Johnson, Lucci, Kuerer), University of Texas MD Anderson Cancer Center, Houston, TX
| | - Vicente Valero
- From the Departments of Breast Surgical Oncology (Johnson, Lucci, Kuerer), University of Texas MD Anderson Cancer Center, Houston, TX
| | - Wei T Yang
- From the Departments of Breast Surgical Oncology (Johnson, Lucci, Kuerer), University of Texas MD Anderson Cancer Center, Houston, TX
| | - Benjamin D Smith
- From the Departments of Breast Surgical Oncology (Johnson, Lucci, Kuerer), University of Texas MD Anderson Cancer Center, Houston, TX
| | - Savitri Krishnamurthy
- From the Departments of Breast Surgical Oncology (Johnson, Lucci, Kuerer), University of Texas MD Anderson Cancer Center, Houston, TX
| | - Yu Shen
- From the Departments of Breast Surgical Oncology (Johnson, Lucci, Kuerer), University of Texas MD Anderson Cancer Center, Houston, TX
| | - Heather Lin
- From the Departments of Breast Surgical Oncology (Johnson, Lucci, Kuerer), University of Texas MD Anderson Cancer Center, Houston, TX
| | - Anthony Lucci
- From the Departments of Breast Surgical Oncology (Johnson, Lucci, Kuerer), University of Texas MD Anderson Cancer Center, Houston, TX
| | - Gaiane M Rauch
- From the Departments of Breast Surgical Oncology (Johnson, Lucci, Kuerer), University of Texas MD Anderson Cancer Center, Houston, TX
| | - Henry M Kuerer
- From the Departments of Breast Surgical Oncology (Johnson, Lucci, Kuerer), University of Texas MD Anderson Cancer Center, Houston, TX
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17
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Abuhadra N, Sun R, Yam C, Rauch GM, Ding Q, Lim B, Thompson AM, Mittendorf EA, Adrada BE, Damodaran S, Virani K, White J, Ravenberg E, Sun J, Choi J, Candelaria R, Arun B, Ueno NT, Santiago L, Saleem S, Abouharb S, Murthy RK, Ibrahim N, Sahin A, Valero V, Symmans WF, Litton JK, Tripathy D, Moulder S, Huo L. Predictive Roles of Baseline Stromal Tumor-Infiltrating Lymphocytes and Ki-67 in Pathologic Complete Response in an Early-Stage Triple-Negative Breast Cancer Prospective Trial. Cancers (Basel) 2023; 15:3275. [PMID: 37444385 DOI: 10.3390/cancers15133275] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2023] [Revised: 06/11/2023] [Accepted: 06/19/2023] [Indexed: 07/15/2023] Open
Abstract
High stromal tumor-infiltrating lymphocytes (sTILs) are associated with improved pathologic complete response (pCR) in triple-negative breast cancer (TNBC). We hypothesize that integrating high sTILs and additional clinicopathologic features associated with pCR could enhance our ability to predict the group of patients on whom treatment de-escalation strategies could be tested. In this prospective early-stage TNBC neoadjuvant chemotherapy study, pretreatment biopsies from 408 patients were evaluated for their clinical and demographic features, as well as biomarkers including sTILs, Ki-67, PD-L1 and androgen receptor. Multivariate logistic regression models were developed to generate a computed response score to predict pCR. The pCR rate for the entire cohort was 41%. Recursive partitioning analysis identified ≥20% as the optimal cutoff for sTILs to denote 35% (143/408) of patients as having high sTILs, with a pCR rate of 59%, and 65% (265/408) of patients as having low sTILs, with a pCR rate of 31%. High Ki-67 (cutoff > 35%) was identified as the only predictor of pCR in addition to sTILs in the training set. This finding was verified in the testing set, where the highest computed response score encompassing both high sTILa and high Ki-67 predicted a pCR rate of 65%. Integrating Ki67 and sTIL may refine the selection of early stage TNBC patients for neoadjuvant clinical trials evaluating de-escalation strategies.
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Affiliation(s)
- Nour Abuhadra
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Ryan Sun
- Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Clinton Yam
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Gaiane M Rauch
- Division of Diagnostic Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Qingqing Ding
- Department of Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Bora Lim
- Department of Oncology, Baylor College of Medicine, Houston, TX 77030, USA
| | - Alastair M Thompson
- Division of Surgical Oncology, Section of Breast Surgery, Baylor College of Medicine, Houston, TX 77030, USA
| | - Elizabeth A Mittendorf
- Division of Breast Surgery, Department of Surgery, Brigham and Women's Hospital, Boston, MA 02115, USA
| | - Beatriz E Adrada
- Division of Diagnostic Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Senthil Damodaran
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Kiran Virani
- Division of Pathology and Laboratory Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Jason White
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Elizabeth Ravenberg
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Jia Sun
- Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Jaihee Choi
- Department of Statistics, Rice University, Houston, TX 77005, USA
| | - Rosalind Candelaria
- Division of Diagnostic Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Banu Arun
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Naoto T Ueno
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Lumarie Santiago
- Division of Diagnostic Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Sadia Saleem
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Sausan Abouharb
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Rashmi K Murthy
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Nuhad Ibrahim
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Aysegul Sahin
- Department of Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Vicente Valero
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - William Fraser Symmans
- Department of Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Jennifer K Litton
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Debu Tripathy
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Stacy Moulder
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Lei Huo
- Department of Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
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18
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Abstract
Early detection of breast cancer through screening mammography saves lives. However, the sensitivity of mammography for breast cancer detection is reduced in women with dense breast tissue. Imaging modalities for supplemental breast cancer screening include MRI, whole breast US, contrast-enhanced mammography, and molecular breast imaging (MBI). Molecular breast imaging with 99mTc-sestamibi is a functional imaging test to identify metabolically active areas in the breast with positioning analogous to mammography. Since 2011, there have been six large, published studies of screening MBI as a supplement to mammography involving over 6000 women from four different institutions. A multicenter, prospective clinical trial of 3000 women comparing breast cancer detection using screening digital breast tomosynthesis alone or in combination with MBI recently completed enrollment. This review focuses on the current evidence of MBI use for supplemental breast cancer screening, the strengths and limitations of MBI, and recent technological advances.
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Affiliation(s)
| | - Katie N Hunt
- Mayo Clinic, Department of Radiology, Rochester, MN, USA
| | - Gaiane M Rauch
- The University of Texas MD Anderson Cancer Center, Department of Breast Imaging, Houston, TX, USA
- The University of Texas MD Anderson Cancer Center, Department of Abdominal Imaging, Houston, TX, USA
| | - Amy M Fowler
- University of Wisconsin School of Medicine and Public Health, Department of Radiology, Madison, WI, USA
- University of Wisconsin Carbone Cancer Center, Madison, WI, USA
- University of Wisconsin School of Medicine and Public Health, Department of Medical Physics, Madison, WI, USA
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19
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Yam C, Mittendorf EA, Garber HR, Sun R, Damodaran S, Murthy RK, Ramirez D, Karuturi M, Layman RM, Ibrahim N, Rauch GM, Adrada BE, Candelaria RP, White JB, Ravenberg E, Clayborn A, Ding QQ, Symmans WF, Prabhakaran S, Thompson AM, Valero V, Tripathy D, Huo L, Moulder SL, Litton JK. A phase II study of neoadjuvant atezolizumab and nab-paclitaxel in patients with anthracycline-resistant early-stage triple-negative breast cancer. Breast Cancer Res Treat 2023; 199:457-469. [PMID: 37061619 DOI: 10.1007/s10549-023-06929-9] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2023] [Accepted: 03/30/2023] [Indexed: 04/17/2023]
Abstract
PURPOSE Neoadjuvant anti-PD-(L)1 therapy improves the pathological complete response (pCR) rate in unselected triple-negative breast cancer (TNBC). Given the potential for long-term morbidity from immune-related adverse events (irAEs), optimizing the risk-benefit ratio for these agents in the curative neoadjuvant setting is important. Suboptimal clinical response to initial neoadjuvant therapy (NAT) is associated with low rates of pCR (2-5%) and may define a patient selection strategy for neoadjuvant immune checkpoint blockade. We conducted a single-arm phase II study of atezolizumab and nab-paclitaxel as the second phase of NAT in patients with doxorubicin and cyclophosphamide (AC)-resistant TNBC (NCT02530489). METHODS Patients with stage I-III, AC-resistant TNBC, defined as disease progression or a < 80% reduction in tumor volume after 4 cycles of AC, were eligible. Patients received atezolizumab (1200 mg IV, Q3weeks × 4) and nab-paclitaxel (100 mg/m2 IV,Q1 week × 12) as the second phase of NAT before undergoing surgery followed by adjuvant atezolizumab (1200 mg IV, Q3 weeks, × 4). A two-stage Gehan-type design was employed to detect an improvement in pCR/residual cancer burden class I (RCB-I) rate from 5 to 20%. RESULTS From 2/15/2016 through 1/29/2021, 37 patients with AC-resistant TNBC were enrolled. The pCR/RCB-I rate was 46%. No new safety signals were observed. Seven patients (19%) discontinued atezolizumab due to irAEs. CONCLUSION This study met its primary endpoint, demonstrating a promising signal of activity in this high-risk population (pCR/RCB-I = 46% vs 5% in historical controls), suggesting that a response-adapted approach to the utilization of neoadjuvant immunotherapy should be considered for further evaluation in a randomized clinical trial.
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Affiliation(s)
- Clinton Yam
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Dan L. Duncan Building (CPB5.3542), 1515 Holcombe Blvd. Unit 1354, Houston, TX, 77030, USA.
- Department of Translational Molecular Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
| | - Elizabeth A Mittendorf
- Division of Breast Surgery, Department of Surgery, Brigham and Women's Hospital, Boston, MA, USA
- Breast Oncology Program, Dana-Farber/Brigham Cancer Center, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Haven R Garber
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Dan L. Duncan Building (CPB5.3542), 1515 Holcombe Blvd. Unit 1354, Houston, TX, 77030, USA
| | - Ryan Sun
- Department of Biostatistics, Division of Basic Sciences, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Senthil Damodaran
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Dan L. Duncan Building (CPB5.3542), 1515 Holcombe Blvd. Unit 1354, Houston, TX, 77030, USA
| | - Rashmi K Murthy
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Dan L. Duncan Building (CPB5.3542), 1515 Holcombe Blvd. Unit 1354, Houston, TX, 77030, USA
| | - David Ramirez
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Dan L. Duncan Building (CPB5.3542), 1515 Holcombe Blvd. Unit 1354, Houston, TX, 77030, USA
| | - Meghan Karuturi
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Dan L. Duncan Building (CPB5.3542), 1515 Holcombe Blvd. Unit 1354, Houston, TX, 77030, USA
| | - Rachel M Layman
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Dan L. Duncan Building (CPB5.3542), 1515 Holcombe Blvd. Unit 1354, Houston, TX, 77030, USA
| | - Nuhad Ibrahim
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Dan L. Duncan Building (CPB5.3542), 1515 Holcombe Blvd. Unit 1354, Houston, TX, 77030, USA
| | - Gaiane M Rauch
- Department of Breast Imaging, Division of Diagnostic Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Beatriz E Adrada
- Department of Breast Imaging, Division of Diagnostic Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Rosalind P Candelaria
- Department of Breast Imaging, Division of Diagnostic Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Jason B White
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Dan L. Duncan Building (CPB5.3542), 1515 Holcombe Blvd. Unit 1354, Houston, TX, 77030, USA
| | - Elizabeth Ravenberg
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Dan L. Duncan Building (CPB5.3542), 1515 Holcombe Blvd. Unit 1354, Houston, TX, 77030, USA
| | - Alyson Clayborn
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Dan L. Duncan Building (CPB5.3542), 1515 Holcombe Blvd. Unit 1354, Houston, TX, 77030, USA
| | - Qing Qing Ding
- Department of Pathology, Division of Pathology-Laboratory Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - W Fraser Symmans
- Department of Translational Molecular Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Sabitha Prabhakaran
- Department of Genomic Medicine, Division of Cancer Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Alastair M Thompson
- Section of Breast Surgery, Division of Surgical Oncology, Baylor College of Medicine, Houston, TX, USA
| | - Vicente Valero
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Dan L. Duncan Building (CPB5.3542), 1515 Holcombe Blvd. Unit 1354, Houston, TX, 77030, USA
| | - Debu Tripathy
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Dan L. Duncan Building (CPB5.3542), 1515 Holcombe Blvd. Unit 1354, Houston, TX, 77030, USA
| | - Lei Huo
- Department of Pathology, Division of Pathology-Laboratory Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Stacy L Moulder
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Dan L. Duncan Building (CPB5.3542), 1515 Holcombe Blvd. Unit 1354, Houston, TX, 77030, USA
| | - Jennifer K Litton
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Dan L. Duncan Building (CPB5.3542), 1515 Holcombe Blvd. Unit 1354, Houston, TX, 77030, USA.
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20
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Abuhadra N, Sun R, Bassett RL, Huo L, Chang JT, Teshome M, Clayborn AR, White JB, Ravenberg EE, Adrada BE, Candelaria RP, Yang W, Ding Q, Symmans WF, Arun B, Damodaran S, Koenig KB, Layman RM, Lim B, Litton JK, Thompson A, Ueno NT, Piwnica-Worms H, Hortobagyi GN, Valero V, Tripathy D, Rauch GM, Moulder S, Yam C. Targeting chemotherapy resistance in mesenchymal triple-negative breast cancer: a phase II trial of neoadjuvant angiogenic and mTOR inhibition with chemotherapy. Invest New Drugs 2023:10.1007/s10637-023-01357-4. [PMID: 37043123 DOI: 10.1007/s10637-023-01357-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2023] [Accepted: 03/27/2023] [Indexed: 04/13/2023]
Affiliation(s)
- Nour Abuhadra
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX, 77030, USA
| | - Ryan Sun
- Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Roland L Bassett
- Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Lei Huo
- Department of Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Jeffrey T Chang
- Department of Integrative Biology and Pharmacology, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Mediget Teshome
- Department of Breast Surgical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Alyson R Clayborn
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX, 77030, USA
| | - Jason B White
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX, 77030, USA
| | - Elizabeth E Ravenberg
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX, 77030, USA
| | - Beatriz E Adrada
- Department of Diagnostic Radiology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Rosalind P Candelaria
- Department of Diagnostic Radiology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Wei Yang
- Department of Diagnostic Radiology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Qingqing Ding
- Department of Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - W Fraser Symmans
- Department of Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Banu Arun
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX, 77030, USA
| | - Senthil Damodaran
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX, 77030, USA
| | - Kimberly B Koenig
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX, 77030, USA
| | - Rachel M Layman
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX, 77030, USA
| | - Bora Lim
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX, 77030, USA
| | - Jennifer K Litton
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX, 77030, USA
| | - Alastair Thompson
- Department of Breast Surgical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Naoto T Ueno
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX, 77030, USA
| | - Helen Piwnica-Worms
- Department of Experimental Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Gabriel N Hortobagyi
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX, 77030, USA
| | - Vicente Valero
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX, 77030, USA
| | - Debu Tripathy
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX, 77030, USA
| | - Gaiane M Rauch
- Department of Diagnostic Radiology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Stacy Moulder
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX, 77030, USA.
| | - Clinton Yam
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX, 77030, USA.
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21
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Stowers CE, Wu C, Kumar S, Lima EA, Zu X, Yam C, Son JB, Ma J, Tamir JI, Rauch GM, Yankeelov TE. Abstract 845: Developing MRI-based digital-twins via mathematical modeling and deep learning to predict the response of triple-negative breast cancer to neoadjuvant therapy. Cancer Res 2023. [DOI: 10.1158/1538-7445.am2023-845] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/07/2023]
Abstract
Abstract
More than 50% of triple negative breast cancer (TNBC) patients do not respond well to the standard-of-care neoadjuvant therapy (NAT). Therefore, methods capable of predicting treatment response will be highly useful to optimize intervention and outcomes for TNBC patients. To address this problem, we aim to integrate quantitative magnetic resonance imaging (MRI) with biology-based mathematical modeling and deep learning to make patient-specific predictions of TNBC response to NAT using only pretreatment data. TNBC patients (n = 150) enrolled in the ARTEMIS trial (NCT02276443) received doxorubicin/cyclophosphamide (A/C) followed by paclitaxel. MRI exams were acquired for each patient at the following timepoints: (1) before initiation of NAT, (2) after two A/C cycles, (3) after four A/C cycles, and (4) at the conclusion of NAT. Using patient-specific MRI data from the first two exams, we calibrated a biology-based mathematical model to characterize migration, proliferation, and treatment-induced death of tumor cells. We then used this model as a digital twin to predict spatiotemporal tumor response. While effective, this approach requires the patient to have completed at least part of their NAT regime before we are able to predict therapeutic response. To relax this requirement, we have developed an approach that combines deep learning and biology-based mathematical modeling to predict the response of TNBC to NAT before treatment initiation. Specifically, we integrated a U-Net-based convolutional neural network with our mathematical model to regress between pre-treatment data and the model parameters obtained from a training set. Using parameters from learning a network with a subset of 68 patients, our mathematical model yielded concordance correlation coefficients between the predicted and measured patient-specific changes in tumor cellularity and volume at the third imaging point of 0.95 and 0.92, respectively. Spatially, we obtain the median difference between predicted and measured percent change in cellularity from visit one to visit three for each patient, giving a mean (95% confidence interval) of -6.51% (-7.13%, -5.90%) across all patients. These encouraging results may be further improved using methods such as expanding to a spatially-resolved proliferation rate, including genetic and/or histological data, and extending the deep learning framework to the end of the treatment course to predict pathological response. This approach allows us to obtain patient-specific predictions of response before NAT commences, thereby providing the opportunity to optimize interventions and patient outcomes.
Citation Format: Casey E. Stowers, Chengyue Wu, Sidharth Kumar, Ernesto A.B.F. Lima, Xhan Zu, Clinton Yam, Jong Bum Son, Jingfei Ma, Jonathan I. Tamir, Gaiane M. Rauch, Thomas E. Yankeelov. Developing MRI-based digital-twins via mathematical modeling and deep learning to predict the response of triple-negative breast cancer to neoadjuvant therapy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 845.
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Affiliation(s)
| | | | | | | | - Xhan Zu
- 2University of Texas MD Anderson Cancer Center, Houston, TX
| | - Clinton Yam
- 2University of Texas MD Anderson Cancer Center, Houston, TX
| | - Jong Bum Son
- 2University of Texas MD Anderson Cancer Center, Houston, TX
| | - Jingfei Ma
- 2University of Texas MD Anderson Cancer Center, Houston, TX
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22
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Wu C, Stowers CE, Xu Z, Lima EABF, Yam C, Son JB, Ma J, Rauch GM, Yankeelov TE. Abstract 5569: Quantification of tumor-associated vasculature as an imaging biomarker for monitoring the response of triple-negative breast cancer to neoadjuvant chemotherapy. Cancer Res 2023. [DOI: 10.1158/1538-7445.am2023-5569] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/07/2023]
Abstract
Abstract
Introduction: Patients with locally advanced, triple-negative breast cancer (TNBC) typically receive neoadjuvant systemic therapy (NAST). However, the response of TNBC to NAST is varied and a prognostic marker is still lacking. Since angiogenesis plays an important role in cancer progression, the quantification of changes in the tumor vasculature during treatment has the potential to provide useful information for characterizing the treatment response. We have recently developed a method to quantify changes in tumor-associated vasculature through a novel analysis of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). In this study, we investigated its ability to monitor the response of TNBC to NAST.
Methods: Dynamic contrast-enhanced (DCE) MRI was acquired in TNBC patients (N = 50; 25 pathological complete response (pCR), 25 non-pCR) before, after 2 and 4 cycles of Adriamycin/Cyclophosphamide (A/C), as part of the ARTEMIS trial (NCT02276433). Using DCE-MRI, we identified the tumor-associated vessels via a breast vasculature analysis. Specifically, the difference between pre- and post-contrast DCE-MRI images was enhanced by a histogram-based intensity transfer function. The 3D vasculature in the breast was then segmented by applying a Hessian filter. Given the vasculature segmented by the algorithms and the tumor masks segmented by radiologists, a lowest-cost tracking algorithm was used to automatically detect the vessels that are most likely to contact the tumor. These vessels are defined as tumor-associated vessels (TAV). The number of TAVs per patient was tabulated and the Wilcoxon rank sum test compared the TAV values before (V1), after 2 cycles (V2), and after 4 cycles of NAST (V3). Additionally, we compared the percent change of TAV from V1 to V3 between the pCR patients and non-pCR patients. Statistical significance was defined as P < 0.05.
Results: A significant decrease in the number of TAVs was observed during the NAST. In particular, the number of TAVs has a median (interquartile range) of 15 (7 - 24), 7 (3 - 14), and 2 (0 - 8) at V1, V2, V3, respectively, which are (pair-wise) significantly different (P < 0.01). Moreover, pCR patients showed a significantly greater decrease in the number of TAVs as compared to non-pCR patients. The percent changes in the number of TAVs from V1 to V3 have a median (range) of -88.89% (-100.00% - -60.00%) and -66.67% (-87.85% - -40.88%) in the pCR and non-pCR patients, respectively (P < 0.05).
Conclusion: These preliminary results demonstrate that tumor-associated vasculature may be a valuable imaging biomarker for monitoring the response of TNBC to NAST. Ongoing efforts include additional investigation of the TAVs beyond their number, as well as applying the analysis to more patients.
Citation Format: Chengyue Wu, Casey E. Stowers, Zhan Xu, Ernesto A. B. F. Lima, Clinton Yam, Jong Bum Son, Jingfei Ma, Gaiane M. Rauch, Thomas E. Yankeelov. Quantification of tumor-associated vasculature as an imaging biomarker for monitoring the response of triple-negative breast cancer to neoadjuvant chemotherapy. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5569.
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Affiliation(s)
| | | | - Zhan Xu
- 2The University of Texas MD Anderson Cancer Center, Houston, TX
| | | | - Clinton Yam
- 2The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Jong Bum Son
- 2The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Jingfei Ma
- 2The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Gaiane M. Rauch
- 2The University of Texas MD Anderson Cancer Center, Houston, TX
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23
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Awiwi MO, Kaur H, Ernst R, Rauch GM, Morani AC, Stanietzky N, Palmquist SM, Salem UI. Restaging MRI of Rectal Adenocarcinoma after Neoadjuvant Chemoradiotherapy: Imaging Findings and Potential Pitfalls. Radiographics 2023; 43:e220135. [PMID: 36927125 DOI: 10.1148/rg.220135] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/18/2023]
Abstract
Rectal adenocarcinoma constitutes about one-third of all colorectal adenocarcinoma cases. Rectal MRI has become mandatory for evaluation of patients newly diagnosed with rectal cancer because it can help accurately stage the disease, impact the choice to give neoadjuvant therapy or proceed with up-front surgery, and even direct surgical dissection planes. Better understanding of neoadjuvant chemoradiotherapy effects on rectal tumors and recognition that up to 30% of patients can have a pathologic complete response have opened the door for the nonsurgical "watch-and-wait" management approach for rectal adenocarcinoma. Candidates for this organ-preserving approach should have no evidence of malignancy on all three components of response assessment after neoadjuvant therapy (ie, digital rectal examination, endoscopy, and rectal MRI). Hence, rectal MRI again has a major role in directing patient management and possibly sparing patients from unnecessary surgical morbidity. In this article, the authors discuss the indications for neoadjuvant therapy in management of patients with rectal adenocarcinoma, describe expected imaging appearances of rectal adenocarcinoma after completion of neoadjuvant therapy, and outline the MRI tumor regression grading system. Since pelvic sidewall lymph node dissection is associated with a high risk of permanent genitourinary dysfunction, it is performed for only selected patients who have radiologic evidence of sidewall lymph node involvement. Therefore, the authors review the relevant lymphatic compartments of the pelvis and describe lymph node criteria for determining locoregional nodal spread. Finally, the authors discuss limitations of rectal MRI, describe several potential interpretation pitfalls after neoadjuvant therapy, and emphasize how these pitfalls may be avoided. © RSNA, 2023 Quiz questions for this article are available in the supplemental material.
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Affiliation(s)
- Muhammad O Awiwi
- From the Division of Diagnostic Imaging, Department of Abdominal Imaging, University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX 77030
| | - Harmeet Kaur
- From the Division of Diagnostic Imaging, Department of Abdominal Imaging, University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX 77030
| | - Randy Ernst
- From the Division of Diagnostic Imaging, Department of Abdominal Imaging, University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX 77030
| | - Gaiane M Rauch
- From the Division of Diagnostic Imaging, Department of Abdominal Imaging, University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX 77030
| | - Ajaykumar C Morani
- From the Division of Diagnostic Imaging, Department of Abdominal Imaging, University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX 77030
| | - Nir Stanietzky
- From the Division of Diagnostic Imaging, Department of Abdominal Imaging, University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX 77030
| | - Sarah M Palmquist
- From the Division of Diagnostic Imaging, Department of Abdominal Imaging, University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX 77030
| | - Usama I Salem
- From the Division of Diagnostic Imaging, Department of Abdominal Imaging, University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX 77030
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Echeverria GV, Cai S, Tu Y, Shao J, Powell E, Redwood AB, Jiang Y, McCoy A, Rinkenbaugh AL, Lau R, Trevarton AJ, Fu C, Gould R, Ravenberg EE, Huo L, Candelaria R, Santiago L, Adrada BE, Lane DL, Rauch GM, Yang WT, White JB, Chang JT, Moulder SL, Symmans WF, Hilsenbeck SG, Piwnica-Worms H. Predictors of success in establishing orthotopic patient-derived xenograft models of triple negative breast cancer. NPJ Breast Cancer 2023; 9:2. [PMID: 36627285 PMCID: PMC9831981 DOI: 10.1038/s41523-022-00502-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2022] [Accepted: 12/13/2022] [Indexed: 01/12/2023] Open
Abstract
Patient-derived xenograft (PDX) models of breast cancer are an effective discovery platform and tool for preclinical pharmacologic testing and biomarker identification. We established orthotopic PDX models of triple negative breast cancer (TNBC) from the primary breast tumors of patients prior to and following neoadjuvant chemotherapy (NACT) while they were enrolled in the ARTEMIS trial (NCT02276443). Serial biopsies were obtained from patients prior to treatment (pre-NACT), from poorly responsive disease after four cycles of Adriamycin and cyclophosphamide (AC, mid-NACT), and in cases of AC-resistance, after a 3-month course of different experimental therapies and/or additional chemotherapy (post-NACT). Our study cohort includes a total of 269 fine needle aspirates (FNAs) from 217 women, generating a total of 62 PDX models (overall success-rate = 23%). Success of PDX engraftment was generally higher from those cancers that proved to be treatment-resistant, whether poorly responsive to AC as determined by ultrasound measurements mid-NACT (p = 0.063), RCB II/III status after NACT (p = 0.046), or metastatic relapse within 2 years of surgery (p = 0.008). TNBC molecular subtype determined from gene expression microarrays of pre-NACT tumors revealed no significant association with PDX engraftment rate (p = 0.877). Finally, we developed a statistical model predictive of PDX engraftment using percent Ki67 positive cells in the patient's diagnostic biopsy, positive lymph node status at diagnosis, and low volumetric reduction of the patient's tumor following AC treatment. This novel bank of 62 PDX models of TNBC provides a valuable resource for biomarker discovery and preclinical therapeutic trials aimed at improving neoadjuvant response rates for patients with TNBC.
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Affiliation(s)
- Gloria V Echeverria
- Department of Experimental Radiation Oncology, University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA.
- Lester and Sue Smith Breast Cancer Center and Department of Medicine, Baylor College of Medicine, Houston, TX, 77030, USA.
| | - Shirong Cai
- Department of Experimental Radiation Oncology, University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - Yizheng Tu
- Department of Experimental Radiation Oncology, University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - Jiansu Shao
- Department of Experimental Radiation Oncology, University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - Emily Powell
- Department of Experimental Radiation Oncology, University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - Abena B Redwood
- Department of Experimental Radiation Oncology, University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - Yan Jiang
- Department of Experimental Radiation Oncology, University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - Aaron McCoy
- Department of Experimental Radiation Oncology, University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - Amanda L Rinkenbaugh
- Department of Experimental Radiation Oncology, University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - Rosanna Lau
- Department of Pathology, University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - Alexander J Trevarton
- Department of Pathology, University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - Chunxiao Fu
- Department of Pathology, University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - Rebekah Gould
- Department of Pathology, University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - Elizabeth E Ravenberg
- Department of Breast Medical Oncology, University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - Lei Huo
- Department of Pathology, University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - Rosalind Candelaria
- Department of Breast Imaging, University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - Lumarie Santiago
- Department of Breast Imaging, University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - Beatriz E Adrada
- Department of Breast Imaging, University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - Deanna L Lane
- Department of Breast Medical Oncology, University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - Gaiane M Rauch
- Department of Abdominal Imaging, University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - Wei T Yang
- Department of Breast Medical Oncology, University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - Jason B White
- Department of Breast Medical Oncology, University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - Jeffrey T Chang
- Department of Integrative Biology and Pharmacology, University of Texas Health Science Center, Houston, TX, 77030, USA
| | - Stacy L Moulder
- Department of Breast Medical Oncology, University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - W Fraser Symmans
- Department of Pathology, University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - Susan G Hilsenbeck
- Lester and Sue Smith Breast Center, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Helen Piwnica-Worms
- Department of Experimental Radiation Oncology, University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA.
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25
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Musall BC, Adrada BE, Candelaria RP, Mohamed RMM, Abdelhafez AH, Son JB, Sun J, Santiago L, Whitman GJ, Moseley TW, Scoggins ME, Mahmoud HS, White JB, Hwang KP, Elshafeey NA, Boge M, Zhang S, Litton JK, Valero V, Tripathy D, Thompson AM, Yam C, Wei P, Moulder SL, Pagel MD, Yang WT, Ma J, Rauch GM. Quantitative Apparent Diffusion Coefficients From Peritumoral Regions as Early Predictors of Response to Neoadjuvant Systemic Therapy in Triple-Negative Breast Cancer. J Magn Reson Imaging 2022; 56:1901-1909. [PMID: 35499264 PMCID: PMC9626398 DOI: 10.1002/jmri.28219] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2022] [Revised: 04/20/2022] [Accepted: 04/21/2022] [Indexed: 01/05/2023] Open
Abstract
BACKGROUND Pathologic complete response (pCR) to neoadjuvant systemic therapy (NAST) in triple-negative breast cancer (TNBC) is a strong predictor of patient survival. Edema in the peritumoral region (PTR) has been reported to be a negative prognostic factor in TNBC. PURPOSE To determine whether quantitative apparent diffusion coefficient (ADC) features from PTRs on reduced field-of-view (rFOV) diffusion-weighted imaging (DWI) predict the response to NAST in TNBC. STUDY TYPE Prospective. POPULATION/SUBJECTS A total of 108 patients with biopsy-proven TNBC who underwent NAST and definitive surgery during 2015-2020. FIELD STRENGTH/SEQUENCE A 3.0 T/rFOV single-shot diffusion-weighted echo-planar imaging sequence (DWI). ASSESSMENT Three scans were acquired longitudinally (pretreatment, after two cycles of NAST, and after four cycles of NAST). For each scan, 11 ADC histogram features (minimum, maximum, mean, median, standard deviation, kurtosis, skewness and 10th, 25th, 75th, and 90th percentiles) were extracted from tumors and from PTRs of 5 mm, 10 mm, 15 mm, and 20 mm in thickness with inclusion and exclusion of fat-dominant pixels. STATISTICAL TESTS ADC features were tested for prediction of pCR, both individually using Mann-Whitney U test and area under the receiver operating characteristic curve (AUC), and in combination in multivariable models with k-fold cross-validation. A P value < 0.05 was considered statistically significant. RESULTS Fifty-one patients (47%) had pCR. Maximum ADC from PTR, measured after two and four cycles of NAST, was significantly higher in pCR patients (2.8 ± 0.69 vs 3.5 ± 0.94 mm2 /sec). The top-performing feature for prediction of pCR was the maximum ADC from the 5-mm fat-inclusive PTR after cycle 4 of NAST (AUC: 0.74; 95% confidence interval: 0.64, 0.84). Multivariable models of ADC features performed similarly for fat-inclusive and fat-exclusive PTRs, with AUCs ranging from 0.68 to 0.72 for the cycle 2 and cycle 4 scans. DATA CONCLUSION Quantitative ADC features from PTRs may serve as early predictors of the response to NAST in TNBC. EVIDENCE LEVEL 1 TECHNICAL EFFICACY: Stage 4.
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Affiliation(s)
- Benjamin C Musall
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Beatriz E Adrada
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Rosalind P Candelaria
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Rania M M Mohamed
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Abeer H Abdelhafez
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Jong Bum Son
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Jia Sun
- Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Lumarie Santiago
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Gary J Whitman
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Tanya W Moseley
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Marion E Scoggins
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Hagar S Mahmoud
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Jason B White
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Ken-Pin Hwang
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Nabil A Elshafeey
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Medine Boge
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Shu Zhang
- Department of Cancer Systems Imaging, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Jennifer K Litton
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Vicente Valero
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Debu Tripathy
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Alastair M Thompson
- Division of Surgical Oncology, Baylor College of Medicine, Houston, Texas, USA
| | - Clinton Yam
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Peng Wei
- Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Stacy L Moulder
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Mark D Pagel
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
- Department of Cancer Systems Imaging, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Wei T Yang
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Jingfei Ma
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Gaiane M Rauch
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
- Department of Abdominal Imaging, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
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Kuerer HM, Smith BD, Krishnamurthy S, Yang WT, Valero V, Shen Y, Lin H, Lucci A, Boughey JC, White RL, Diego EJ, Rauch GM, Moseley TW, van la Parra RFD, Adrada BE, Leung JWT, Sun SX, Teshome M, Miggins MV, Hunt KK, DeSnyder SM, Ehlers RA, Hwang RF, Colen JS, Arribas, E, Samiian L, Lesnikoski BA, Piotrowski M, Bedrosian I, Chong C, Refinetti AP, Huang M, Candelaria RP, Loveland-Jones C, Mitchell MP, Shaitelman SF. Eliminating breast surgery for invasive breast cancer in exceptional responders to neoadjuvant systemic therapy: a multicentre, single-arm, phase 2 trial. Lancet Oncol 2022; 23:1517-1524. [DOI: 10.1016/s1470-2045(22)00613-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2022] [Revised: 09/29/2022] [Accepted: 09/30/2022] [Indexed: 11/06/2022]
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27
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Wu C, Jarrett AM, Zhou Z, Elshafeey N, Adrada BE, Candelaria RP, Mohamed RMM, Boge M, Huo L, White JB, Tripathy D, Valero V, Litton JK, Yam C, Son JB, Ma J, Rauch GM, Yankeelov TE. MRI-Based Digital Models Forecast Patient-Specific Treatment Responses to Neoadjuvant Chemotherapy in Triple-Negative Breast Cancer. Cancer Res 2022; 82:3394-3404. [PMID: 35914239 PMCID: PMC9481712 DOI: 10.1158/0008-5472.can-22-1329] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2022] [Revised: 06/14/2022] [Accepted: 07/26/2022] [Indexed: 02/07/2023]
Abstract
Triple-negative breast cancer (TNBC) is persistently refractory to therapy, and methods to improve targeting and evaluation of responses to therapy in this disease are needed. Here, we integrate quantitative MRI data with biologically based mathematical modeling to accurately predict the response of TNBC to neoadjuvant systemic therapy (NAST) on an individual basis. Specifically, 56 patients with TNBC enrolled in the ARTEMIS trial (NCT02276443) underwent standard-of-care doxorubicin/cyclophosphamide (A/C) and then paclitaxel for NAST, where dynamic contrast-enhanced MRI and diffusion-weighted MRI were acquired before treatment and after two and four cycles of A/C. A biologically based model was established to characterize tumor cell movement, proliferation, and treatment-induced cell death. Two evaluation frameworks were investigated using: (i) images acquired before and after two cycles of A/C for calibration and predicting tumor status after A/C, and (ii) images acquired before, after two cycles, and after four cycles of A/C for calibration and predicting response following NAST. For Framework 1, the concordance correlation coefficients between the predicted and measured patient-specific, post-A/C changes in tumor cellularity and volume were 0.95 and 0.94, respectively. For Framework 2, the biologically based model achieved an area under the receiver operator characteristic curve of 0.89 (sensitivity/specificity = 0.72/0.95) for differentiating pathological complete response (pCR) from non-pCR, which is statistically superior (P &lt; 0.05) to the value of 0.78 (sensitivity/specificity = 0.72/0.79) achieved by tumor volume measured after four cycles of A/C. Overall, this model successfully captured patient-specific, spatiotemporal dynamics of TNBC response to NAST, providing highly accurate predictions of NAST response. SIGNIFICANCE Integrating MRI data with biologically based mathematical modeling successfully predicts breast cancer response to chemotherapy, suggesting digital twins could facilitate a paradigm shift from simply assessing response to predicting and optimizing therapeutic efficacy.
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Affiliation(s)
- Chengyue Wu
- Oden Institute for Computational Engineering and Sciences, The University of Texas at Austin, Austin, Texas
| | - Angela M Jarrett
- Oden Institute for Computational Engineering and Sciences, The University of Texas at Austin, Austin, Texas.,Livestrong Cancer Institutes, The University of Texas at Austin, Austin, Texas
| | - Zijian Zhou
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Nabil Elshafeey
- Department of Abdominal Imaging, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Beatriz E Adrada
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Rosalind P Candelaria
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Rania M M Mohamed
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Medine Boge
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Lei Huo
- Department of Pathology, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Jason B White
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Debu Tripathy
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Vicente Valero
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Jennifer K Litton
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Clinton Yam
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Jong Bum Son
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Jingfei Ma
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Gaiane M Rauch
- Department of Abdominal Imaging, The University of Texas MD Anderson Cancer Center, Houston, Texas.,Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Thomas E Yankeelov
- Oden Institute for Computational Engineering and Sciences, The University of Texas at Austin, Austin, Texas.,Livestrong Cancer Institutes, The University of Texas at Austin, Austin, Texas.,Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas.,Department of Biomedical Engineering, The University of Texas at Austin, Austin, Texas.,Department of Diagnostic Medicine, The University of Texas at Austin, Austin, Texas.,Department of Oncology, The University of Texas at Austin, Austin, Texas
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28
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Maheshwari E, Nougaret S, Stein EB, Rauch GM, Hwang KP, Stafford RJ, Klopp AH, Soliman PT, Maturen KE, Rockall AG, Lee SI, Sadowski EA, Venkatesan AM. Update on MRI in Evaluation and Treatment of Endometrial Cancer. Radiographics 2022; 42:2112-2130. [PMID: 36018785 DOI: 10.1148/rg.220070] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
Endometrial cancer is the second most common gynecologic cancer worldwide and the most common gynecologic cancer in the United States, with an increasing incidence in high-income countries. Although the International Federation of Gynecology and Obstetrics (FIGO) staging system for endometrial cancer is a surgical staging system, contemporary published evidence-based data and expert opinions recommend MRI for treatment planning as it provides critical diagnostic information on tumor size and depth, extent of myometrial and cervical invasion, extrauterine extent, and lymph node status, all of which are essential in choosing the most appropriate therapy. Multiparametric MRI using a combination of T2-weighted sequences, diffusion-weighted imaging, and multiphase contrast-enhanced imaging is the mainstay for imaging assessment of endometrial cancer. Identification of important prognostic factors at MRI improves both treatment selection and posttreatment follow-up. MRI also plays a crucial role for fertility-preserving strategies and in patients who are not surgical candidates by helping guide therapy and identify procedural complications. This review is a product of the Society of Abdominal Radiology Uterine and Ovarian Cancer Disease-Focused Panel and reflects a multidisciplinary international collaborative effort to summarize updated information highlighting the role of MRI for endometrial cancer depiction and delineation, treatment planning, and follow-up. The article includes information regarding dedicated MRI protocols, tips for MRI reporting, imaging pitfalls, and strategies for image quality optimization. The roles of MRI-guided radiation therapy, hybrid PET/MRI, and advanced MRI techniques that are applicable to endometrial cancer imaging are also discussed. Online supplemental material is available for this article. ©RSNA, 2022.
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Affiliation(s)
- Ekta Maheshwari
- From the Department of Radiology, University of Pittsburgh Medical Center, 200 Lothrop St, Pittsburgh, PA 15213 (E.M.); Department of Abdominal Imaging, Montpellier Cancer Research Institute (IRCM), Montpellier, France (S.N.); Department of Radiology, University of Michigan, Ann Arbor, Mich (E.B.S., K.E.M.); Department of Abdominal Imaging, Division of Diagnostic Imaging (G.M.R., A.M.V.), Department of Imaging Physics (K.P.H., R.J.S.), Department of Radiation Oncology (A.H.K.), and Department of Gynecologic Oncology and Reproductive Medicine (P.T.S.), University of Texas MD Anderson Cancer Center, Houston, Tex; Department of Radiology, Imperial College, London, United Kingdom (A.G.R.); Department of Diagnostic Radiology, Massachusetts General Hospital, Boston, Mass (S.I.L.); and Department of Radiology, University of Wisconsin-Madison, Madison, Wis (E.A.S.)
| | - Stephanie Nougaret
- From the Department of Radiology, University of Pittsburgh Medical Center, 200 Lothrop St, Pittsburgh, PA 15213 (E.M.); Department of Abdominal Imaging, Montpellier Cancer Research Institute (IRCM), Montpellier, France (S.N.); Department of Radiology, University of Michigan, Ann Arbor, Mich (E.B.S., K.E.M.); Department of Abdominal Imaging, Division of Diagnostic Imaging (G.M.R., A.M.V.), Department of Imaging Physics (K.P.H., R.J.S.), Department of Radiation Oncology (A.H.K.), and Department of Gynecologic Oncology and Reproductive Medicine (P.T.S.), University of Texas MD Anderson Cancer Center, Houston, Tex; Department of Radiology, Imperial College, London, United Kingdom (A.G.R.); Department of Diagnostic Radiology, Massachusetts General Hospital, Boston, Mass (S.I.L.); and Department of Radiology, University of Wisconsin-Madison, Madison, Wis (E.A.S.)
| | - Erica B Stein
- From the Department of Radiology, University of Pittsburgh Medical Center, 200 Lothrop St, Pittsburgh, PA 15213 (E.M.); Department of Abdominal Imaging, Montpellier Cancer Research Institute (IRCM), Montpellier, France (S.N.); Department of Radiology, University of Michigan, Ann Arbor, Mich (E.B.S., K.E.M.); Department of Abdominal Imaging, Division of Diagnostic Imaging (G.M.R., A.M.V.), Department of Imaging Physics (K.P.H., R.J.S.), Department of Radiation Oncology (A.H.K.), and Department of Gynecologic Oncology and Reproductive Medicine (P.T.S.), University of Texas MD Anderson Cancer Center, Houston, Tex; Department of Radiology, Imperial College, London, United Kingdom (A.G.R.); Department of Diagnostic Radiology, Massachusetts General Hospital, Boston, Mass (S.I.L.); and Department of Radiology, University of Wisconsin-Madison, Madison, Wis (E.A.S.)
| | - Gaiane M Rauch
- From the Department of Radiology, University of Pittsburgh Medical Center, 200 Lothrop St, Pittsburgh, PA 15213 (E.M.); Department of Abdominal Imaging, Montpellier Cancer Research Institute (IRCM), Montpellier, France (S.N.); Department of Radiology, University of Michigan, Ann Arbor, Mich (E.B.S., K.E.M.); Department of Abdominal Imaging, Division of Diagnostic Imaging (G.M.R., A.M.V.), Department of Imaging Physics (K.P.H., R.J.S.), Department of Radiation Oncology (A.H.K.), and Department of Gynecologic Oncology and Reproductive Medicine (P.T.S.), University of Texas MD Anderson Cancer Center, Houston, Tex; Department of Radiology, Imperial College, London, United Kingdom (A.G.R.); Department of Diagnostic Radiology, Massachusetts General Hospital, Boston, Mass (S.I.L.); and Department of Radiology, University of Wisconsin-Madison, Madison, Wis (E.A.S.)
| | - Ken-Pin Hwang
- From the Department of Radiology, University of Pittsburgh Medical Center, 200 Lothrop St, Pittsburgh, PA 15213 (E.M.); Department of Abdominal Imaging, Montpellier Cancer Research Institute (IRCM), Montpellier, France (S.N.); Department of Radiology, University of Michigan, Ann Arbor, Mich (E.B.S., K.E.M.); Department of Abdominal Imaging, Division of Diagnostic Imaging (G.M.R., A.M.V.), Department of Imaging Physics (K.P.H., R.J.S.), Department of Radiation Oncology (A.H.K.), and Department of Gynecologic Oncology and Reproductive Medicine (P.T.S.), University of Texas MD Anderson Cancer Center, Houston, Tex; Department of Radiology, Imperial College, London, United Kingdom (A.G.R.); Department of Diagnostic Radiology, Massachusetts General Hospital, Boston, Mass (S.I.L.); and Department of Radiology, University of Wisconsin-Madison, Madison, Wis (E.A.S.)
| | - R Jason Stafford
- From the Department of Radiology, University of Pittsburgh Medical Center, 200 Lothrop St, Pittsburgh, PA 15213 (E.M.); Department of Abdominal Imaging, Montpellier Cancer Research Institute (IRCM), Montpellier, France (S.N.); Department of Radiology, University of Michigan, Ann Arbor, Mich (E.B.S., K.E.M.); Department of Abdominal Imaging, Division of Diagnostic Imaging (G.M.R., A.M.V.), Department of Imaging Physics (K.P.H., R.J.S.), Department of Radiation Oncology (A.H.K.), and Department of Gynecologic Oncology and Reproductive Medicine (P.T.S.), University of Texas MD Anderson Cancer Center, Houston, Tex; Department of Radiology, Imperial College, London, United Kingdom (A.G.R.); Department of Diagnostic Radiology, Massachusetts General Hospital, Boston, Mass (S.I.L.); and Department of Radiology, University of Wisconsin-Madison, Madison, Wis (E.A.S.)
| | - Ann H Klopp
- From the Department of Radiology, University of Pittsburgh Medical Center, 200 Lothrop St, Pittsburgh, PA 15213 (E.M.); Department of Abdominal Imaging, Montpellier Cancer Research Institute (IRCM), Montpellier, France (S.N.); Department of Radiology, University of Michigan, Ann Arbor, Mich (E.B.S., K.E.M.); Department of Abdominal Imaging, Division of Diagnostic Imaging (G.M.R., A.M.V.), Department of Imaging Physics (K.P.H., R.J.S.), Department of Radiation Oncology (A.H.K.), and Department of Gynecologic Oncology and Reproductive Medicine (P.T.S.), University of Texas MD Anderson Cancer Center, Houston, Tex; Department of Radiology, Imperial College, London, United Kingdom (A.G.R.); Department of Diagnostic Radiology, Massachusetts General Hospital, Boston, Mass (S.I.L.); and Department of Radiology, University of Wisconsin-Madison, Madison, Wis (E.A.S.)
| | - Pamela T Soliman
- From the Department of Radiology, University of Pittsburgh Medical Center, 200 Lothrop St, Pittsburgh, PA 15213 (E.M.); Department of Abdominal Imaging, Montpellier Cancer Research Institute (IRCM), Montpellier, France (S.N.); Department of Radiology, University of Michigan, Ann Arbor, Mich (E.B.S., K.E.M.); Department of Abdominal Imaging, Division of Diagnostic Imaging (G.M.R., A.M.V.), Department of Imaging Physics (K.P.H., R.J.S.), Department of Radiation Oncology (A.H.K.), and Department of Gynecologic Oncology and Reproductive Medicine (P.T.S.), University of Texas MD Anderson Cancer Center, Houston, Tex; Department of Radiology, Imperial College, London, United Kingdom (A.G.R.); Department of Diagnostic Radiology, Massachusetts General Hospital, Boston, Mass (S.I.L.); and Department of Radiology, University of Wisconsin-Madison, Madison, Wis (E.A.S.)
| | - Katherine E Maturen
- From the Department of Radiology, University of Pittsburgh Medical Center, 200 Lothrop St, Pittsburgh, PA 15213 (E.M.); Department of Abdominal Imaging, Montpellier Cancer Research Institute (IRCM), Montpellier, France (S.N.); Department of Radiology, University of Michigan, Ann Arbor, Mich (E.B.S., K.E.M.); Department of Abdominal Imaging, Division of Diagnostic Imaging (G.M.R., A.M.V.), Department of Imaging Physics (K.P.H., R.J.S.), Department of Radiation Oncology (A.H.K.), and Department of Gynecologic Oncology and Reproductive Medicine (P.T.S.), University of Texas MD Anderson Cancer Center, Houston, Tex; Department of Radiology, Imperial College, London, United Kingdom (A.G.R.); Department of Diagnostic Radiology, Massachusetts General Hospital, Boston, Mass (S.I.L.); and Department of Radiology, University of Wisconsin-Madison, Madison, Wis (E.A.S.)
| | - Andrea G Rockall
- From the Department of Radiology, University of Pittsburgh Medical Center, 200 Lothrop St, Pittsburgh, PA 15213 (E.M.); Department of Abdominal Imaging, Montpellier Cancer Research Institute (IRCM), Montpellier, France (S.N.); Department of Radiology, University of Michigan, Ann Arbor, Mich (E.B.S., K.E.M.); Department of Abdominal Imaging, Division of Diagnostic Imaging (G.M.R., A.M.V.), Department of Imaging Physics (K.P.H., R.J.S.), Department of Radiation Oncology (A.H.K.), and Department of Gynecologic Oncology and Reproductive Medicine (P.T.S.), University of Texas MD Anderson Cancer Center, Houston, Tex; Department of Radiology, Imperial College, London, United Kingdom (A.G.R.); Department of Diagnostic Radiology, Massachusetts General Hospital, Boston, Mass (S.I.L.); and Department of Radiology, University of Wisconsin-Madison, Madison, Wis (E.A.S.)
| | - Susanna I Lee
- From the Department of Radiology, University of Pittsburgh Medical Center, 200 Lothrop St, Pittsburgh, PA 15213 (E.M.); Department of Abdominal Imaging, Montpellier Cancer Research Institute (IRCM), Montpellier, France (S.N.); Department of Radiology, University of Michigan, Ann Arbor, Mich (E.B.S., K.E.M.); Department of Abdominal Imaging, Division of Diagnostic Imaging (G.M.R., A.M.V.), Department of Imaging Physics (K.P.H., R.J.S.), Department of Radiation Oncology (A.H.K.), and Department of Gynecologic Oncology and Reproductive Medicine (P.T.S.), University of Texas MD Anderson Cancer Center, Houston, Tex; Department of Radiology, Imperial College, London, United Kingdom (A.G.R.); Department of Diagnostic Radiology, Massachusetts General Hospital, Boston, Mass (S.I.L.); and Department of Radiology, University of Wisconsin-Madison, Madison, Wis (E.A.S.)
| | - Elizabeth A Sadowski
- From the Department of Radiology, University of Pittsburgh Medical Center, 200 Lothrop St, Pittsburgh, PA 15213 (E.M.); Department of Abdominal Imaging, Montpellier Cancer Research Institute (IRCM), Montpellier, France (S.N.); Department of Radiology, University of Michigan, Ann Arbor, Mich (E.B.S., K.E.M.); Department of Abdominal Imaging, Division of Diagnostic Imaging (G.M.R., A.M.V.), Department of Imaging Physics (K.P.H., R.J.S.), Department of Radiation Oncology (A.H.K.), and Department of Gynecologic Oncology and Reproductive Medicine (P.T.S.), University of Texas MD Anderson Cancer Center, Houston, Tex; Department of Radiology, Imperial College, London, United Kingdom (A.G.R.); Department of Diagnostic Radiology, Massachusetts General Hospital, Boston, Mass (S.I.L.); and Department of Radiology, University of Wisconsin-Madison, Madison, Wis (E.A.S.)
| | - Aradhana M Venkatesan
- From the Department of Radiology, University of Pittsburgh Medical Center, 200 Lothrop St, Pittsburgh, PA 15213 (E.M.); Department of Abdominal Imaging, Montpellier Cancer Research Institute (IRCM), Montpellier, France (S.N.); Department of Radiology, University of Michigan, Ann Arbor, Mich (E.B.S., K.E.M.); Department of Abdominal Imaging, Division of Diagnostic Imaging (G.M.R., A.M.V.), Department of Imaging Physics (K.P.H., R.J.S.), Department of Radiation Oncology (A.H.K.), and Department of Gynecologic Oncology and Reproductive Medicine (P.T.S.), University of Texas MD Anderson Cancer Center, Houston, Tex; Department of Radiology, Imperial College, London, United Kingdom (A.G.R.); Department of Diagnostic Radiology, Massachusetts General Hospital, Boston, Mass (S.I.L.); and Department of Radiology, University of Wisconsin-Madison, Madison, Wis (E.A.S.)
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Irajizad E, Wu R, Vykoukal J, Murage E, Spencer R, Dennison JB, Moulder S, Ravenberg E, Lim B, Litton J, Tripathym D, Valero V, Damodaran S, Rauch GM, Adrada B, Candelaria R, White JB, Brewster A, Arun B, Long JP, Do KA, Hanash S, Fahrmann JF. Application of Artificial Intelligence to Plasma Metabolomics Profiles to Predict Response to Neoadjuvant Chemotherapy in Triple-Negative Breast Cancer. Front Artif Intell 2022; 5:876100. [PMID: 36034598 PMCID: PMC9403735 DOI: 10.3389/frai.2022.876100] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2022] [Accepted: 05/03/2022] [Indexed: 11/13/2022] Open
Abstract
There is a need to identify biomarkers predictive of response to neoadjuvant chemotherapy (NACT) in triple-negative breast cancer (TNBC). We previously obtained evidence that a polyamine signature in the blood is associated with TNBC development and progression. In this study, we evaluated whether plasma polyamines and other metabolites may identify TNBC patients who are less likely to respond to NACT. Pre-treatment plasma levels of acetylated polyamines were elevated in TNBC patients that had moderate to extensive tumor burden (RCB-II/III) following NACT compared to those that achieved a complete pathological response (pCR/RCB-0) or had minimal residual disease (RCB-I). We further applied artificial intelligence to comprehensive metabolic profiles to identify additional metabolites associated with treatment response. Using a deep learning model (DLM), a metabolite panel consisting of two polyamines as well as nine additional metabolites was developed for improved prediction of RCB-II/III. The DLM has potential clinical value for identifying TNBC patients who are unlikely to respond to NACT and who may benefit from other treatment modalities.
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Affiliation(s)
- Ehsan Irajizad
- Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Ranran Wu
- Department of Clinical Cancer Prevention, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Jody Vykoukal
- Department of Clinical Cancer Prevention, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Eunice Murage
- Department of Clinical Cancer Prevention, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Rachelle Spencer
- Department of Clinical Cancer Prevention, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Jennifer B. Dennison
- Department of Clinical Cancer Prevention, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Stacy Moulder
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Elizabeth Ravenberg
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Bora Lim
- Breast Cancer Research Program, Baylor College of Medicine, Houston, TX, United States
| | - Jennifer Litton
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Debu Tripathym
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Vicente Valero
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Senthil Damodaran
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Gaiane M. Rauch
- Department of Abdominal Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Beatriz Adrada
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Rosalind Candelaria
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Jason B. White
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Abenaa Brewster
- Department of Clinical Cancer Prevention, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Banu Arun
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - James P. Long
- Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Kim Anh Do
- Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Sam Hanash
- Department of Clinical Cancer Prevention, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
- *Correspondence: Sam Hanash
| | - Johannes F. Fahrmann
- Department of Clinical Cancer Prevention, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
- Johannes F. Fahrmann
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Lopez BP, Rauch GM, Adrada B, Kappadath SC. Functional tumor diameter measurement with Molecular Breast Imaging: development and clinical application. Biomed Phys Eng Express 2022; 8. [PMID: 35917778 DOI: 10.1088/2057-1976/ac85f0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2022] [Accepted: 08/02/2022] [Indexed: 11/12/2022]
Abstract
Purpose:Molecular breast imaging (MBI) is used clinically to visualize the uptake of99mTc-sestamibi in breast cancers. Here, we use Monte Carlo simulations to develop a methodology to estimate tumor diameter in focal lesions and explore a semi-automatic implementation for clinical data.Methods:A validated Monte Carlo simulation of the GE Discovery NM 750b was used to simulate >75,000 unique spherical/ellipsoidal tumor, normal breast, and image acquisition conditions. Subsets of this data were used to 1) characterize the dependence of the full-width at half-maximum (FWHM) of a tumor profile on tumor, normal breast, and acquisition conditions, 2) develop a methodology to estimate tumor diameters, and 3) quantify the diameter accuracy in a broad range of clinical conditions. Finally, the methodology was implemented in patient images and compared to diameter estimates from physician contours on MBI, mammography, and ultrasound imaging.Results:Tumor profile FWHM was determined be linearly dependent on tumor diameter but independent of other factors such as tumor shape, uptake, and distance from the detector. A linear regression was used to calculate tumor diameter from the FWHM estimated from a background-corrected profile across a tumor extracted from a median-filtered single-detector MBI image, i.e., diameter = 1.2 mm + 1.2 x FWHM, for FWHM ≥ 13 mm. Across a variety of simulated clinical conditions, the mean error of the methodology was 0.2 mm (accuracy), with >50% of cases estimated within 1-pixel width of the truth (precision). In patient images, the semi-automatic methodology provided the longest diameter in 94% (60/64) of cases. The estimated true diameters, for oval lesions with homogeneous uptake, differed by ± 5 mm from physician measurements.Conclusion:This work demonstrates the feasibility of accurately quantifying tumor diameter in clinical MBI, and to our knowledge, is the first to explore its implementation and application in patient data.
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Affiliation(s)
- Benjamin P Lopez
- Imaging Physics, The University of Texas MD Anderson Cancer Center, 1155 Pressler St, Houston, Texas, 77030, UNITED STATES
| | - Gaiane M Rauch
- Breast Imaging, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, Texas, 77030, UNITED STATES
| | - Beatriz Adrada
- Breast Imaging, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, Texas, 77030, UNITED STATES
| | - S Cheenu Kappadath
- Imaging Physics, The University of Texas MD Anderson Cancer Center, 1155 Pressler St, Unit 1352, Houston, Texas, 77030, UNITED STATES
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Yam C, Abuhadra N, Sun R, Adrada BE, Ding QQ, White JB, Ravenberg EE, Clayborn AR, Valero V, Tripathy D, Damodaran S, Arun BK, Litton JK, Ueno NT, Murthy RK, Lim B, Baez L, Li X, Buzdar AU, Hortobagyi GN, Thompson AM, Mittendorf EA, Rauch GM, Candelaria RP, Huo L, Moulder SL, Chang JT. Molecular Characterization and Prospective Evaluation of Pathologic Response and Outcomes with Neoadjuvant Therapy in Metaplastic Triple-Negative Breast Cancer. Clin Cancer Res 2022; 28:2878-2889. [PMID: 35507014 PMCID: PMC9250637 DOI: 10.1158/1078-0432.ccr-21-3100] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2021] [Revised: 02/28/2022] [Accepted: 04/29/2022] [Indexed: 01/03/2023]
Abstract
PURPOSE Metaplastic breast cancer (MpBC) is a rare subtype of breast cancer that is commonly triple-negative and poorly responsive to neoadjuvant therapy in retrospective studies. EXPERIMENTAL DESIGN To better define clinical outcomes and correlates of response, we analyzed the rate of pathologic complete response (pCR) to neoadjuvant therapy, survival outcomes, and genomic and transcriptomic profiles of the pretreatment tumors in a prospective clinical trial (NCT02276443). A total of 211 patients with triple-negative breast cancer (TNBC), including 39 with MpBC, received doxorubicin-cyclophosphamide-based neoadjuvant therapy. RESULTS Although not meeting the threshold for statistical significance, patients with MpBCs were less likely to experience a pCR (23% vs. 40%; P = 0.07), had shorter event-free survival (29.4 vs. 32.2 months, P = 0.15), metastasis-free survival (30.3 vs. 32.4 months, P = 0.22); and overall survival (32.6 vs. 34.3 months, P = 0.21). This heterogeneity is mirrored in the molecular profiling. Mutations in PI3KCA (23% vs. 9%, P = 0.07) and its pathway (41% vs. 18%, P = 0.02) were frequently observed and enriched in MpBCs. The gene expression profiles of each histologically defined subtype were distinguishable and characterized by distinctive gene signatures. Among nonmetaplastic (non-Mp) TNBCs, 10% possessed a metaplastic-like gene expression signature and had pCR rates and survival outcomes similar to MpBC. CONCLUSIONS Further investigations will determine if metaplastic-like tumors should be treated more similarly to MpBC in the clinic. The 23% pCR rate in this study suggests that patients with MpBC should be considered for NAT. To improve this rate, a pathway analysis predicted enrichment of histone deacetylase (HDAC) and RTK/MAPK pathways in MpBC, which may serve as new targetable vulnerabilities.
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Affiliation(s)
- Clinton Yam
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Nour Abuhadra
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Ryan Sun
- Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Beatriz E. Adrada
- Department of Diagnostic Radiology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Qing-Qing Ding
- Department of Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Jason B. White
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Elizabeth E. Ravenberg
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Alyson R. Clayborn
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Vicente Valero
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Debu Tripathy
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Senthilkumar Damodaran
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Banu K. Arun
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Jennifer K. Litton
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Naoto T. Ueno
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Rashmi K. Murthy
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Bora Lim
- Department of Oncology, Baylor College of Medicine, Houston, TX, USA
| | - Luis Baez
- PROncology (Private Practice), University of Puerto Rico. San Juan, Puerto Rico
| | - Xiaoxian Li
- Department of Pathology & Laboratory Medicine, Winship Cancer Institute - Emory University Hospital, Atlanta, GA, USA
| | - Aman U. Buzdar
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Gabriel N. Hortobagyi
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Alistair M. Thompson
- Division of Surgical Oncology, Section of Breast Surgery, Baylor College of Medicine, Houston, TX, USA
| | - Elizabeth A. Mittendorf
- Division of Breast Surgery, Department of Surgery, Brigham and Women’s Hospital, Boston, MD, USA.,Breast Oncology Program, Dana-Farber/Brigham and Women’s Cancer Center, Boston, MA, USA
| | - Gaiane M. Rauch
- Department of Diagnostic Radiology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Rosalind P. Candelaria
- Department of Diagnostic Radiology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Lei Huo
- Department of Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Stacy L. Moulder
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Jeffrey T. Chang
- Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.,Department of Integrative Biology and Pharmacology, The University of Texas Health Science Center at Houston, TX, USA
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Jacobsen MC, Beriwal S, Dyer BA, Klopp AH, Lee SI, McGinnis GJ, Robbins JB, Rauch GM, Sadowski EA, Simiele SJ, Stafford RJ, Taunk NK, Yashar CM, Venkatesan AM. Contemporary image-guided cervical cancer brachytherapy: Consensus imaging recommendations from the Society of Abdominal Radiology and the American Brachytherapy Society. Brachytherapy 2022; 21:369-388. [PMID: 35725550 DOI: 10.1016/j.brachy.2022.04.005] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2022] [Revised: 04/15/2022] [Accepted: 04/24/2022] [Indexed: 11/02/2022]
Abstract
PURPOSE To present recommendations for the use of imaging for evaluation and procedural guidance of brachytherapy for cervical cancer patients. METHODS An expert panel comprised of members of the Society of Abdominal Radiology Uterine and Ovarian Cancer Disease Focused Panel and the American Brachytherapy Society jointly assessed the existing literature and provide data-driven guidance on imaging protocol development, interpretation, and reporting. RESULTS Image-guidance during applicator implantation reduces rates of uterine perforation by the tandem. Postimplant images may be acquired with radiography, computed tomography (CT), or magnetic resonance imaging (MRI), and CT or MRI are preferred due to a decrease in severe complications. Pre-brachytherapy T2-weighted MRI may be used as a reference for contouring the high-risk clinical target volume (HR-CTV) when CT is used for treatment planning. Reference CT and MRI protocols are provided for reference. CONCLUSIONS Image-guided brachytherapy in locally advanced cervical cancer is essential for optimal patient management. Various imaging modalities, including orthogonal radiographs, ultrasound, computed tomography, and magnetic resonance imaging, remain integral to the successful execution of image-guided brachytherapy.
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Affiliation(s)
- Megan C Jacobsen
- The University of Texas MD Anderson Cancer Center, Department of Imaging Physics, Houston, TX
| | - Sushil Beriwal
- Allegheny Health Network, Department of Radiation Oncology, Pittsburgh, PA; Varian Medical Systems, Palo Alto, CA
| | - Brandon A Dyer
- Legacy Health, Department of Radiation Oncology, Portland, OR
| | - Ann H Klopp
- The University of Texas MD Anderson Cancer Center, Department of Radiation Oncology, Houston, TX
| | - Susanna I Lee
- Massachusetts General Hospital, Department of Radiology, Boston, MA
| | - Gwendolyn J McGinnis
- The University of Texas MD Anderson Cancer Center, Department of Radiation Oncology, Houston, TX
| | | | - Gaiane M Rauch
- The University of Texas MD Anderson Cancer Center, Department of Abdominal Imaging, Houston, TX
| | | | - Samantha J Simiele
- The University of Texas MD Anderson Cancer Center, Department of Radiation Physics, Houston, TX
| | - R Jason Stafford
- The University of Texas MD Anderson Cancer Center, Department of Imaging Physics, Houston, TX
| | - Neil K Taunk
- University of Pennsylvania, Department of Radiation Oncology, Philadelphia, PA
| | - Catheryn M Yashar
- University of California San Diego, Department of Radiation Oncology, San Diego, CA
| | - Aradhana M Venkatesan
- The University of Texas MD Anderson Cancer Center, Department of Abdominal Imaging, Houston, TX.
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Wu C, Jarrett AM, Zhou Z, Elshafeey N, Adrada BE, Candelaria RP, Mohamed R, Boge M, Huo L, White J, Tripathy D, Valero V, Litton J, Yam C, Son JB, Ma J, Rauch GM, Yankeelov TE. Abstract 2736: Forecasting treatment response to neoadjuvant therapy in triple-negative breast cancer via an image-guided digital twin. Cancer Res 2022. [DOI: 10.1158/1538-7445.am2022-2736] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Abstract
Introduction: Patients with locally advanced, triple-negative breast cancer (TNBC) typically receive neoadjuvant therapy (NAT) to downstage the tumor and to improve the outcome of subsequent breast conservation surgery. There are currently no methods to accurately predict how a TNBC patient will respond to NAT before surgery. In this work, we applied a digital twin framework to address this unmet clinical need, by integrating quantitative magnetic resonance imaging (MRI) data with mechanism-based mathematical modeling.
Methods: Multiparametric MRI was acquired in patients (N = 50) before, after 2 and 4 cycles of Adriamycin/Cyclophosphamide (A/C), and again after 12 cycles of Paclitaxel as part of the ARTEMIS (NCT02276433) trial. Within each imaging session, dynamic contrast-enhanced (DCE) MRI, diffusion-weighted imaging (DWI), and a pre-contrast T1-map were acquired. The images were processed by a pipeline consisting of motion correction, multiparametric image alignment, inter-visit image registration to align the tumor and surrounding breast tissue, tissue segmentation, and estimation of tumor cellularity from DWI. A mechanism-based mathematical model, a reaction-diffusion equation, is used to characterize the mobility of tumor cells via diffusion damped by mechanical tissue properties, tumor proliferation via logistic growth, and treatment-induced cell death via the delivery and decay of therapies. For each patient, pre-treatment images were used for model initialization. The model calibration and prediction were implemented with two strategies: 1) using images acquired during the A/C for calibration and predicting up to the end of A/C, and 2) using images acquired during and after the A/C for calibration and predicting up to the end of NAT. For strategy 1), we evaluated the model by comparing its predicted tumor volume and total tumor cellularity to the imaging measurements at the end of A/C. For strategy 2), we evaluated the model by comparing its predicted final response to the post-surgical pathological findings.
Results: For strategy 1), our framework predicted the change of tumor volume and total tumor cellularity with Pearson correlation coefficients of 0.91 and 0.89, respectively. Regarding strategy 2), our framework achieved an area under the receiver operator characteristic curve of 0.88 for distinguishing pCR from non-pCR. As a comparison, imaging measurement of tumor volume at the end of A/C achieved an AUC of 0.79.
Conclusion: Our approach successfully captures the patient-specific dynamics of TNBC response to NAT and provides an improved prediction of final response, which demonstrates the potential of a digital twin framework to be a powerful tool for predicting response to NAT. Once validated, the method will provide a unique opportunity for optimizing treatment plans on a patient-specific basis.
Citation Format: Chengyue Wu, Angela M. Jarrett, Zijian Zhou, Nabil Elshafeey, Beatriz E. Adrada, Rosalind P. Candelaria, Rania Mohamed, Medine Boge, Lei Huo, Jason White, Debu Tripathy, Vicente Valero, Jennifer Litton, Clinton Yam, Jong Bum Son, Jingfei Ma, Gaiane M. Rauch, Thomas E. Yankeelov. Forecasting treatment response to neoadjuvant therapy in triple-negative breast cancer via an image-guided digital twin [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2736.
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Affiliation(s)
- Chengyue Wu
- 1The University of Texas at Austin, Austin, TX
| | | | - Zijian Zhou
- 2The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Nabil Elshafeey
- 2The University of Texas MD Anderson Cancer Center, Houston, TX
| | | | | | - Rania Mohamed
- 2The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Medine Boge
- 2The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Lei Huo
- 2The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Jason White
- 2The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Debu Tripathy
- 2The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Vicente Valero
- 2The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Jennifer Litton
- 2The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Clinton Yam
- 2The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Jong Bum Son
- 2The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Jingfei Ma
- 2The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Gaiane M. Rauch
- 2The University of Texas MD Anderson Cancer Center, Houston, TX
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Hruska CB, Corion C, de Geus-Oei LF, Adrada BE, Fowler AM, Hunt KN, Kappadath SC, Pilkington P, Arias-Bouda LMP, Rauch GM. SNMMI Procedure Standard/EANM Practice Guideline for Molecular Breast Imaging with Dedicated γ-Cameras. J Nucl Med Technol 2022. [DOI: 10.2967/jnmt.121.264204] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
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35
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Guhan M, Crane S, Valerius L, De La Cruz D, Smith BD, Woodward WA, Valero V, Rauch GM, Krishnamurthy S, Warneke CL, Kuerer HM, Shaitelman SF. Patient interest in exploring nonsurgical treatment approaches for early-stage breast cancer: A qualitative study. J Clin Oncol 2022. [DOI: 10.1200/jco.2022.40.16_suppl.578] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
578 Background: Advances in radiotherapy allow the ability to deliver ablative treatments without compromising outcomes, but there has been limited application of these treatments to early-stage breast cancers. The purpose of this study was to explore patients’ interest in pursuing nonsurgical treatment approaches for their early-stage breast cancer. Methods: Investigators conducted a qualitative descriptive study involving semi-structured interviews with 21 early-stage breast cancer patients eligible for participation in a phase 2 trial offering omission of surgery. Interviews were transcribed, and three independent reviewers performed an inductive, thematic analysis to generate themes and subthemes. Results: Data analysis revealed the following factors that impacted patients’ willingness and desire to explore nonsurgical treatment options: Perceptions and feelings about their cancer; Current quality of life and the level of support available in their daily life; External conversations focusing on family members’ and friends’ experiences with cancer and/or cancer treatments; Personal healthcare experiences, including with their current breast cancer diagnosis; Perceptions and feelings about their physicians; Conversations with their physicians about their treatment options; and Self-identified desire to direct care decisions. Specifically, patients described fearing surgery and surgical recovery and wanting to avoid negative surgery-related events previously experienced by friends, family, and themselves. Participants also expressed a desire to preserve their breast(s), receive treatment per the latest research, match the level of treatment with the severity of their cancer, and avoid other comorbidities as reasons for omitting surgery. Patient reasons for pursuing surgery included the desire to remove their cancer immediately, prior positive experiences of friends, family, and themselves with surgery, lack of concern about preserving their breast(s), and prior negative experiences of friends, family, and themselves with radiation. Conclusions: The results of this study highlight that there is patient interest in nonsurgical options for biologically favorable early stage breast cancers. A key factor hindering patient education and awareness of nonsurgical options is how the physician frames the discussion and presents treatment options. In addition, patients’ self-identity and the prior experiences of friends, family, and self with cancer treatment and surgery in general appear to be key factors in their decision-making. The findings from this study demonstrate an unmet need to explore nonsurgical options for early-stage breast cancer. Study results can help shape conversations around shared decision making and clinical trial design and result in more personalized treatment options for women with early-stage breast cancer.
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Affiliation(s)
- Maya Guhan
- UT MD Anderson Cancer Center, Houston, TX
| | - Stacey Crane
- University of Texas Health Science Center School of Nursing, Houston, TX
| | - Lillian Valerius
- University of Texas Health Science Center School of Nursing, Houston, TX
| | | | | | | | - Vicente Valero
- The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Gaiane M. Rauch
- The University of Texas MD Anderson Cancer Center, Houston, TX
| | | | | | - Henry Mark Kuerer
- NRG Oncology/The University of Texas MD Anderson Cancer Center, Houston, TX
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Candelaria RP, Adrada BE, Lane DL, Rauch GM, Moulder SL, Thompson AM, Bassett RL, Arribas EM, Le-Petross HT, Leung JWT, Spak DA, Ravenberg EE, White JB, Valero V, Yang WT. Mid-treatment Ultrasound Descriptors as Qualitative Imaging Biomarkers of Pathologic Complete Response in Patients with Triple-Negative Breast Cancer. Ultrasound Med Biol 2022; 48:1010-1018. [PMID: 35300879 PMCID: PMC9050953 DOI: 10.1016/j.ultrasmedbio.2022.01.018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/17/2021] [Revised: 01/06/2022] [Accepted: 01/27/2022] [Indexed: 06/03/2023]
Abstract
This study aimed to investigate mid-treatment breast tumor ultrasound characteristics that may predict eventual pathologic complete response (pCR) in triple-negative breast cancer; specifically, we examined associations between pCR and two parameters: tumor response pattern and tumor appearance. Ultrasound was performed at mid-treatment, defined as the completion of four cycles of anthracycline-based chemotherapy and before receiving taxane-based chemotherapy. Consensus imaging review was performed while blinded to pathology results (i.e., pCR/non-pCR) from surgery. Tumor response pattern was described as "complete," "concentric," "fragmented," "stable" or "progression." Tumor appearance was designated as "mass," "architectural distortion," "flat tumor bed" or "clip only." Univariate and multivariate regression analyses of 144 participants showed significant associations between mid-treatment response pattern and pCR (p = 0.0348 and p = 0.0173, respectively), with complete and concentric response patterns more likely to achieve pCR than other patterns. Univariate and multivariate regression analyses further showed significant associations between mid-treatment tumor appearance and pCR (p < 0.0001 for both), with persistent appearance of mass less likely than other appearances to achieve pCR. To conclude, our study demonstrated strong associations between pCR and both tumor response pattern and tumor appearance, thereby suggesting that these parameters have potential as qualitative imaging biomarkers of pCR in triple-negative breast cancer.
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Affiliation(s)
- Rosalind P Candelaria
- Department of Breast Imaging, University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
| | - Beatriz E Adrada
- Department of Breast Imaging, University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Deanna L Lane
- Department of Breast Imaging, University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Gaiane M Rauch
- Department of Breast Imaging, University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Stacy L Moulder
- Department of Breast Medical Oncology, University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Alastair M Thompson
- Department of Breast Surgical Oncology, University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Roland L Bassett
- Department of Biostatistics, University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Elsa M Arribas
- Department of Breast Imaging, University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Huong T Le-Petross
- Department of Breast Imaging, University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Jessica W T Leung
- Department of Breast Imaging, University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - David A Spak
- Department of Breast Imaging, University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Elizabeth E Ravenberg
- Department of Breast Medical Oncology, University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Jason B White
- Department of Breast Medical Oncology, University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Vicente Valero
- Department of Breast Medical Oncology, University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Wei T Yang
- Department of Breast Imaging, University of Texas MD Anderson Cancer Center, Houston, Texas, USA
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Jimenez JE, Abdelhafez A, Mittendorf EA, Elshafeey N, Yung JP, Litton JK, Adrada BE, Candelaria RP, White J, Thompson AM, Huo L, Wei P, Tripathy D, Valero V, Yam C, Hazle JD, Moulder SL, Yang WT, Rauch GM. A model combining pretreatment MRI radiomic features and tumor-infiltrating lymphocytes to predict response to neoadjuvant systemic therapy in triple-negative breast cancer. Eur J Radiol 2022; 149:110220. [DOI: 10.1016/j.ejrad.2022.110220] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2021] [Revised: 12/13/2021] [Accepted: 02/10/2022] [Indexed: 12/20/2022]
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Patel MM, Adrada BE, Lopez B, Candelaria RP, Sun J, Boge M, Mohamed RM, Elshafeey N, Whitman G, Le-Petross HT, Santiago L, Scoggins ME, Lane D, Moseley T, Zylberman G, Saddler J, Leung JWT, Yang WT, Valero V, Kappadath SC, Rauch GM. Abstract P3-02-03: Quantitative molecular breast imaging for early prediction of neoadjuvant systemic therapy response in locally advanced breast cancer patients. Cancer Res 2022. [DOI: 10.1158/1538-7445.sabcs21-p3-02-03] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Abstract
BACKGROUND: Increasing use of neoadjuvant systemic therapy (NAT) for early and locally advanced breast cancer led to critical need for development of tools capable of early treatment response assessment after NAT. Tc-99m sestamibi Molecular breast Imaging (MBI) as a functional imaging modality has a promise to detect changes in the tumor prior to anatomical changes detected by mammogram or ultrasound. PURPOSE: To evaluate the ability of quantitative MBI parameters to predict pathologic complete response (pCR) after completion of NAT in breast cancer patients. MATERIALS AND METHODS: Patients with invasive breast cancer (T1-T4, N0-N3, M0) planned for NAT followed by surgery were enrolled in a prospective IRB approved trial. MBI was performed at baseline and after two cycles of NAT. Patient demographic and tumor biology information (Ki-67, HER2, ER/PR) was collected. MBI images were quantified using a novel approach with corrections for scatter and attenuation and regions of interest (ROI) were drawn over tumors to compute three quantitative MBI uptake metrics for correlation with pathologic response: MBI-specific standardized uptake value (SUV), tumor to background ratio (TBR), and tumor volume. Pathologic complete response was determined based on final histopathology report at the time of surgery as absence of the invasive disease in the breast and axillary lymph nodes. MBI metrics at baseline, after 2 cycles of NAT and interval change were correlated with pCR and tumor biology using the Wilcoxon Rank Sum test, Kruskal-Wallis test or Fisher’s exact test. Statistical analysis was carried out using R (version 3.6.3, R Development Core Team). RESULTS: A total of 70 patients with median age 47.5 years (range 30-77) were included in the analysis. Breast cancer subtypes were: HER2 negative (ER/PR+) 35.7% (25/70), HER2 positive (ER/PR +/-) 35.7% (25/70), and triple negative (HER2-, ER/PR-) 28.6% (20/70). Change in SUV after 2 cycles of NAT was higher in patients with pCR compared to those who did not achieve pCR (mean decrease in SUV of 15.57 and 4.83 respectively, p<0.001). Additionally, change in TBR in patients with pCR was also higher compared to patients who did not achieve pCR (mean decreases of 1.14 and 0.56, respectively, p<0.001). No correlation was found between baseline SUV, baseline TBR, change in volume, and pCR. CONCLUSION: MBI-specific SUV and TBR changes after two cycles of NAT correlate and may predict pCR in patients with locally advanced breast cancer. Quantitative MBI parameters are novel promising imaging tools that may help to detect early clinical benefit and optimize management in patients receiving NAT.
Citation Format: Miral M Patel, Beatriz E Adrada, Benjamin Lopez, Rosalind P Candelaria, Jia Sun, Medine Boge, Rania M Mohamed, Nabil Elshafeey, Gary Whitman, MD, Huong T Le-Petross, Lumarie Santiago, Marion E Scoggins, Deanna Lane, Tanya Moseley, Galit Zylberman, Jerica Saddler, Jessica WT Leung, Wei T Yang, Vincente Valero, S Cheenu Kappadath, Gaiane M Rauch. Quantitative molecular breast imaging for early prediction of neoadjuvant systemic therapy response in locally advanced breast cancer patients [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P3-02-03.
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Affiliation(s)
- Miral M Patel
- The University of Texas MD Anderson Cancer Center, Houston, TX
| | | | - Benjamin Lopez
- The University of Texas MD Anderson Cancer Center, Houston, TX
| | | | - Jia Sun
- The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Medine Boge
- The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Rania M Mohamed
- The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Nabil Elshafeey
- The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Gary Whitman
- The University of Texas MD Anderson Cancer Center, Houston, TX
| | | | | | | | - Deanna Lane
- The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Tanya Moseley
- The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Galit Zylberman
- The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Jerica Saddler
- The University of Texas MD Anderson Cancer Center, Houston, TX
| | | | - Wei T Yang
- The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Vincente Valero
- The University of Texas MD Anderson Cancer Center, Houston, TX
| | | | - Gaiane M Rauch
- The University of Texas MD Anderson Cancer Center, Houston, TX
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Guirguis MS, Adrada BE, Candelaria RP, Sun J, Whitman GJ, Yang WT, Boge M, Mohamed RM, Elshafeey NA, Lane DL, Le-Petross H, Leung JWT, Santiago L, Scoggins ME, Spak DA, Patel M, Perez F, Wei P, Tripathy D, White J, Ravenberg E, Huo L, Litton J, Arun B, Valero V, Thompson A, Moulder S, Yam C, Rauch GM. Abstract P3-03-06: Prediction of response to neoadjuvant systemic therapy in triple negative breast cancer using baseline tumor MRI characteristics and imaging patterns of response. Cancer Res 2022. [DOI: 10.1158/1538-7445.sabcs21-p3-03-06] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Abstract
Background: Triple negative breast cancer (TNBC) has a poor prognosis. In particular, TNBC patients who have significant residual disease at the time of surgery following completion of neoadjuvant systemic therapy (NST) have an especially poor prognosis. In an effort to identify patients who are unlikely to achieve pathologic complete response (pCR), we investigated if pre-treatment breast MRI morphological characteristics and imaging response patterns during NST can predict pCR in TNBC patients. Materials and Methods: As part of a prospective IRB-approved clinical trial (ARTEMIS, NCT02276443), 199 patients with biopsy-proven stage I-III TNBC received NST and were classified as pCR or non-pCR based on histopathology at surgery. Patients underwent breast MRI at baseline (BL), after 2 cycles (C2), and 4 cycles (C4) of Adriamycin-based chemotherapy (AC). Subsequently, patients received either taxane-based NST or targeted therapy guided by mid-treatment imaging response. MRI studies were reviewed by two fellowship-trained breast radiologists who were blinded to the pathology results. ACR MRI BIRADS lexicon (5th Ed) was used to describe BL tumor morphology. Imaging response pattern at C2 and C4 MRI was classified as follows: type 0 (complete), type 1 (concentric shrinkage), type 2 (crumble), type 3 (diffuse enhancement), type 4 (stable), or type 5 (progression). Morphological baseline features and response patterns were summarized and compared to the pCR status on surgical pathology using Fisher’s exact test. P values less than 0.05 were considered statistically significant. Results: Median age was 53 years, range 24-79. Of 199 patients, 95 (48%) had pCR and 104 (52%) had non-pCR. At BL MRI, an irregularly-shaped mass and homogenous or clumped non-mass enhancement were associated with pCR (p=0.026 and p=0.013, respectively). Multifocality, peritumoral edema, and intratumoral necrosis were independent of pCR. Following NST, the most common MRI response pattern was type 1, seen with equal frequency in pCR and non-pCR at C2 (58% and 42%, respectively) and C4 (47% and 53%, respectively). The following response pattern associations were found: type 0 was associated with pCR at both C2 and C4 timepoints (p<0.001), while types 4 and 5 were associated with non-pCR at C2, (p<0.001). The four patterns: types 2, 3, 4, 5, were associated with non-pCR at C4 (p<0.001). Conclusion: Baseline MRI tumor morphological characteristics and MRI imaging response patterns during NST may be valuable markers for pCR prediction in TNBC. Qualitative breast MRI assessment may act as an accessible tool to identify TNBC patients who are unlikely to achieve pCR and may benefit from targeted therapies.
Citation Format: Mary S Guirguis, Beatriz E Adrada, Rosalind P Candelaria, Jia Sun, Gary J Whitman, Wei T Yang, Medine Boge, Rania M Mohamed, Nabil A Elshafeey, Deanna L Lane, Huong Le-Petross, Jessica WT Leung, Lumarie Santiago, Marion E Scoggins, David A Spak, Miral Patel, Frances Perez, Peng Wei, Debu Tripathy, Jason White, Elizabeth Ravenberg, Lei Huo, Jennifer Litton, Banu Arun, Vincente Valero, Alastair Thompson, Stacy Moulder, Clinton Yam, Gaiane M Rauch. Prediction of response to neoadjuvant systemic therapy in triple negative breast cancer using baseline tumor MRI characteristics and imaging patterns of response [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P3-03-06.
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Affiliation(s)
| | | | | | - Jia Sun
- University of Texas MD Anderson Cancer Center, Houston, TX
| | - Gary J Whitman
- University of Texas MD Anderson Cancer Center, Houston, TX
| | - Wei T Yang
- University of Texas MD Anderson Cancer Center, Houston, TX
| | - Medine Boge
- University of Texas MD Anderson Cancer Center, Houston, TX
| | | | | | - Deanna L Lane
- University of Texas MD Anderson Cancer Center, Houston, TX
| | | | | | | | | | - David A Spak
- University of Texas MD Anderson Cancer Center, Houston, TX
| | - Miral Patel
- University of Texas MD Anderson Cancer Center, Houston, TX
| | - Frances Perez
- University of Texas MD Anderson Cancer Center, Houston, TX
| | - Peng Wei
- University of Texas MD Anderson Cancer Center, Houston, TX
| | - Debu Tripathy
- University of Texas MD Anderson Cancer Center, Houston, TX
| | - Jason White
- University of Texas MD Anderson Cancer Center, Houston, TX
| | | | - Lei Huo
- University of Texas MD Anderson Cancer Center, Houston, TX
| | | | - Banu Arun
- University of Texas MD Anderson Cancer Center, Houston, TX
| | | | | | | | - Clinton Yam
- University of Texas MD Anderson Cancer Center, Houston, TX
| | - Gaiane M Rauch
- University of Texas MD Anderson Cancer Center, Houston, TX
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Wu C, Jarrett AM, Zhou Z, Elshafeey N, Adrada BE, Candelaria RP, Mohamed RM, Boge M, Huo L, White J, Tripathy D, Valero V, Litton J, Moulder S, Yam C, Son JB, Ma J, Rauch GM, Yankeelov TE. Abstract P1-08-08: Forecasting treatment response to neoadjuvant systemic therapy in triple negative breast cancer viamathematical modeling and quantitative MRI. Cancer Res 2022. [DOI: 10.1158/1538-7445.sabcs21-p1-08-08] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Abstract
Introduction:. Patients with locally advanced triple-negative breast cancer (TNBC) typically receive neoadjuvant therapy (NAT) to downstage the tumor and to improve the outcome of the subsequent breast conservation surgery. A critical unmet need is the lack of a method to accurately predict how a patient with TNBC will respond to NAT before surgery. In this work, we applied a clinical-computational framework to predict response of TNBC early in the course of NAT, by integrating quantitative MRI with mechanism-based mathematical modeling. Methods:. Patients and Data. Multiparametric quantitative MRI was acquired in patients (n = 46) before, and after 2 and 4 cycles of Adriamycin/Cyclophosphamide (A/C) regimen as part of the MD Anderson Cancer Center TNBC Moonshot Program. Within each imaging session, dynamic contrast-enhanced (DCE-), diffusion-weighted imaging (DWI), and a pre-contrast T1-map were acquired. Image processing. The processing pipeline consisted of three components. First, the images within each visit were registered to account for patient motion, and the parametric maps from the DCE and DWI images were computed. Second, inter-visit image registration was achieved by a non-rigid registration applied on breast, with a rigid penalty applied on the tumor region to preserve its size and shape. Third, post-processing was performed for preparation of modeling, including segmentation of the breast contour and tissues, and calculation of voxel-wise cellularity within tumors. Mathematical modeling. A predictive model was developed based on a reaction-diffusion equation (Eq. 1). The mobility of tumor cells is represented by diffusion coupled to mechanical properties of the tissue (Eq. 2), and the proliferation of the tumor is described with logistic growth. The injection and decay of administered therapies, inducing tumor cell death, is also represented in the model (Eq. 3). The variables and parameters used are listed in Table 1. Eq. 1: ∂N(x,t)/∂t = ∇⋅(D(x,t) ∇N(x,t)) + k(x) (1 - N(x,t)/θ)N(x,t) - (λ1(x,t) + λ2(x,t))N(x,t). Eq. 2: D(x,t) = D0 e-γσ(x,t). Eq. 3: λn(x,t) = αne-βn t C(x,t), n = 1, 2. For each patient, the domain and initial condition were generated from the pre-treatment images, and the images acquired during NAT were used for patient-specific calibration of parameters. The calibrated model was then used to predict the response to be observed at the end of NAT. We evaluated the model by comparing its predictions of tumor volume, longest axis, voxel-wise cellularity, and total tumor cellularity to the imaging measurements at the end of A/C. Results:. Our model predicted the tumor volume, total cellularity, and longest axis with a Pearson correlation coefficient (PCC) of 0.85, 0.80, and 0.60, respectively. The accuracy of voxel-wise cellularity achieved a PCC with the median (range) of 0.89 (0.77 - 0.93) between the prediction and the actual measurement. Moreover, we set criteria of 70% shrinkage of tumor volume to define response versus non-response cases, with which our model achieved a differentiation sensitivity/specificity of 0.90/0.73. Discussion:. Preliminary results of our study demonstrate the potential of the clinical-computational framework as a powerful tool for predicting response to NAT. Once validated, the method could also assist in optimizing treatment plans on a patient specific basis, or guiding patient selection in trials for novel NAT regimens.
Table 1. Summary of the variables and parameters in the modelQuantitiesDefinition AssignmentDomainsΩbreast tissue domainGenerated from pre-treatment MRITEnd time point of NAT procedureDetermined from NAT schedulexCoordinate in breast tissueAssociated with spatial domain, ΩttimeAssociated with temporal domain, [0, T]VariablesN(x,t)Tumor cell numberInitialized from pre-treatment ADC, computed via Eq. 1D(x,t)Diffusive mobility of tumor cellsComputed via Eq. 2λn(x,t)Death rate induced by nth type of drugComputed via Eq. 3, n = 1 and 2 for A/Cσ(x,t)Von Mises stressComputed from gradient of N(x,t), based on Hormuth et al., 2018C(x,t)Spatiotemporal distribution of drugsAssigned based on NAT schedule and DCE imagesParametersk(x)Proliferation rate of tumor cellsLocally calibratedθTumor cells carry capacityGlobally calibratedαnEfficacy rate of nth type of drugGlobally calibratedβnDecay rate of of nth type of drugGlobally calibratedD0Diffusion coefficient of tumor cells in the absence of mechanical restrictionsGlobally calibratedγStress-tumor cell diffusion coupling constantAssigned based on Hormuth et al., 2018
Citation Format: Chengyue Wu, Angela M. Jarrett, Zijian Zhou, Nabil Elshafeey, Beatriz E. Adrada, Rosalind P. Candelaria, Rania M. Mohamed, Medine Boge, Lei Huo, Jason White, Debu Tripathy, Vicente Valero, Jennifer Litton, Stacy Moulder, Clinton Yam, Jong Bum Son, Jingfei Ma, Gaiane M. Rauch, Thomas E. Yankeelov. Forecasting treatment response to neoadjuvant systemic therapy in triple negative breast cancer viamathematical modeling and quantitative MRI [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P1-08-08.
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Affiliation(s)
- Chengyue Wu
- The University of Texas at Austin, Austin, TX
| | | | - Zijian Zhou
- The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Nabil Elshafeey
- The University of Texas MD Anderson Cancer Center, Houston, TX
| | | | | | | | - Medine Boge
- The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Lei Huo
- The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Jason White
- The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Debu Tripathy
- The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Vicente Valero
- The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Jennifer Litton
- The University of Texas MD Anderson Cancer Center, Houston, TX
| | | | - Clinton Yam
- The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Jong Bum Son
- The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Jingfei Ma
- The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Gaiane M. Rauch
- The University of Texas MD Anderson Cancer Center, Houston, TX
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Adrada BE, Guirguis MS, Hoang T, Spak DA, Rauch GM, Moseley TW. MRI-guided Breast Biopsy Case-based Review: Essential Techniques and Approaches to Challenging Cases. Radiographics 2022; 42:E46-E47. [PMID: 35119965 PMCID: PMC8906341 DOI: 10.1148/rg.210126] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
MRI-guided breast biopsy is often necessary to distinguish between benign and
malignant lesions depicted at MRI, and meticulous preparation and
radiologic-pathologic correlation aid in definitive diagnosis.
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Affiliation(s)
- Beatriz E. Adrada
- From the Departments of Breast Imaging (B.E.A., M.S.G., D.A.S., G.M.R., T.W.M.), Interventional Radiology (T.H.), Abdominal Imaging (G.M.R.), and Surgical Oncology (T.W.M.), The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Unit 1350, Houston, TX 77030. T.W.M. has provided disclosures (see end of article); all other authors have disclosed no relevant relationships
| | - Mary S. Guirguis
- From the Departments of Breast Imaging (B.E.A., M.S.G., D.A.S., G.M.R., T.W.M.), Interventional Radiology (T.H.), Abdominal Imaging (G.M.R.), and Surgical Oncology (T.W.M.), The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Unit 1350, Houston, TX 77030. T.W.M. has provided disclosures (see end of article); all other authors have disclosed no relevant relationships
| | - Tuan Hoang
- From the Departments of Breast Imaging (B.E.A., M.S.G., D.A.S., G.M.R., T.W.M.), Interventional Radiology (T.H.), Abdominal Imaging (G.M.R.), and Surgical Oncology (T.W.M.), The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Unit 1350, Houston, TX 77030. T.W.M. has provided disclosures (see end of article); all other authors have disclosed no relevant relationships
| | - David A. Spak
- From the Departments of Breast Imaging (B.E.A., M.S.G., D.A.S., G.M.R., T.W.M.), Interventional Radiology (T.H.), Abdominal Imaging (G.M.R.), and Surgical Oncology (T.W.M.), The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Unit 1350, Houston, TX 77030. T.W.M. has provided disclosures (see end of article); all other authors have disclosed no relevant relationships
| | - Gaiane M. Rauch
- From the Departments of Breast Imaging (B.E.A., M.S.G., D.A.S., G.M.R., T.W.M.), Interventional Radiology (T.H.), Abdominal Imaging (G.M.R.), and Surgical Oncology (T.W.M.), The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Unit 1350, Houston, TX 77030. T.W.M. has provided disclosures (see end of article); all other authors have disclosed no relevant relationships
| | - Tanya W. Moseley
- From the Departments of Breast Imaging (B.E.A., M.S.G., D.A.S., G.M.R., T.W.M.), Interventional Radiology (T.H.), Abdominal Imaging (G.M.R.), and Surgical Oncology (T.W.M.), The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Unit 1350, Houston, TX 77030. T.W.M. has provided disclosures (see end of article); all other authors have disclosed no relevant relationships
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Guirguis MS, Checka C, Adrada BE, Whitman GJ, Dryden MJ, Sun J, Ding QQ, Le-Petross H, Rauch GM, Clemens M, Moseley T. Bracketing with Multiple Radioactive Seeds to Achieve Negative Margins in Breast Conservation Surgery: Multiple Seeds in Breast Surgery. Clin Breast Cancer 2022; 22:e158-e166. [PMID: 34187752 PMCID: PMC8639835 DOI: 10.1016/j.clbc.2021.05.013] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2021] [Revised: 05/24/2021] [Accepted: 05/25/2021] [Indexed: 02/03/2023]
Abstract
INTRODUCTION Breast conservation surgery (BCS) is the treatment of choice for unifocal, early-stage breast cancer. The ability to offer BCS to a wider subset of patients, including those with multifocal/multicentric cancer as well as extensive ductal carcinoma in situ, has emerged over time, especially in those undergoing joint oncoplastic reconstruction and those treated with neoadjuvant therapy. However, localization techniques using multiple radioactive seeds for bracketing in this patient subset have not been validated. MATERIALS AND METHODS A single-institution retrospective review was conducted of all patients with breast cancer who underwent BCS, guided by multiple bracketed iodine I 125 radioactive seeds between January 2014 and April 2017. RESULTS Bracketing of breast cancer using 2 or more radioactive seeds was performed in 157 breasts in 156 patients. Negative margins were achieved in 124 of 157 (79%) breasts, including 33 cases (21%) that underwent targeted margin reexcision at the time of surgery after intraoperative, multidisciplinary margin assessment. Thirty-three cases (21%) resulted in close or positive margins, of which 11 (7%) and 10 (6.4%) underwent completion mastectomy or repeat lumpectomy, respectively. Twelve patients (7.6%) did not undergo reexcision. En bloc resection was successful in 134 of 157 (85.4%) lumpectomies. Eighty-nine percent of the procedures were coupled with oncoplastic reconstruction. CONCLUSION Bracketing techniques using multiple radioactive seeds expands the indications for breast conservation therapy in patients who would have traditionally required mastectomy. Intraoperative margin assessment improves surgical and pathologic success. Larger defects created by multifocal resection are optimally managed in concert with oncoplastic reconstruction to minimize asymmetries and aesthetic defects.
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Affiliation(s)
| | - Cristina Checka
- University of Texas MD Anderson Cancer Center, Breast Surgical Oncology
| | | | - Gary J. Whitman
- University of Texas MD Anderson Cancer Center, Breast Imaging
| | - Mark J. Dryden
- University of Texas MD Anderson Cancer Center, Breast Imaging
| | - Jia Sun
- University of Texas MD Anderson Cancer Center, Biostatistics
| | - Qing-Qing Ding
- University of Texas MD Anderson Cancer Center, Anatomical Pathology
| | | | - Gaiane M. Rauch
- University of Texas MD Anderson Cancer Center, Abdominal Imaging
| | - Mark Clemens
- University of Texas MD Anderson Cancer Center, Plastic Surgery
| | - Tanya Moseley
- University of Texas MD Anderson Cancer Center, Breast Imaging
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Candelaria RP, Spak DA, Rauch GM, Huo L, Bassett RL, Santiago L, Scoggins ME, Guirguis MS, Patel MM, Whitman GJ, Moulder SL, Thompson AM, Ravenberg EE, White JB, Abuhadra NK, Valero V, Litton J, Adrada BE, Yang WT. BI-RADS Ultrasound Lexicon Descriptors and Stromal Tumor-Infiltrating Lymphocytes in Triple-Negative Breast Cancer. Acad Radiol 2022; 29 Suppl 1:S35-S41. [PMID: 34272161 PMCID: PMC8755852 DOI: 10.1016/j.acra.2021.06.007] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2021] [Revised: 06/09/2021] [Accepted: 06/09/2021] [Indexed: 01/03/2023]
Abstract
PURPOSE Increased levels of stromal tumor-infiltrating lymphocytes (sTILs) have recently been considered a favorable independent prognostic and predictive biomarker in triple-negative breast cancer (TNBC). The purpose of this study was to determine the relationship between BI-RADS (Breast Imaging Reporting and Data System) ultrasound lexicon descriptors and sTILs in TNBC. MATERIALS AND METHODS Patients with stage I-III TNBC were evaluated within a single-institution neoadjuvant clinical trial. Two fellowship-trained breast radiologists used the BI-RADS ultrasound lexicon to assess pretreatment tumor shape, margin, echo pattern, orientation, posterior features, and vascularity. sTILs were defined as low <20 or high ≥20 on the pretreatment biopsy. Fisher's exact tests were used to assess the association between lexicon descriptors and sTIL levels. RESULTS The 284 patients (mean age 52 years, range 24-79 years) were comprised of 68% (193/284) with low-sTIL tumors and 32% (91/284) with high-sTIL tumors. TNBC tumors with high sTILs were more likely to have the following features: (1) oval/round shape than irregular shape (p = 0.003), (2) circumscribed or microlobulated margins than spiculated, indistinct, or angular margins (p = 0.0005); (3) complex cystic and solid pattern than heterogeneous pattern (p = 0.006); and (4) posterior enhancement than shadowing (p = 0.002). There was no significant association between sTILs and descriptors for orientation and vascularity (p = 0.06 and p = 0.49, respectively). CONCLUSION BI-RADS ultrasound descriptors of the pretreatment appearance of a TNBC tumor can be useful in discriminating between tumors with low and high sTIL levels. Therefore, there is a potential use of ultrasound tumor characteristics to complement sTILs when used as stratification factors in treatment algorithms for TNBC.
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Covington MF, Parent EE, Dibble EH, Rauch GM, Fowler AM. Advances and Future Directions in Molecular Breast Imaging. J Nucl Med 2021; 63:17-21. [PMID: 34887334 DOI: 10.2967/jnumed.121.261988] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2021] [Revised: 11/16/2021] [Indexed: 12/11/2022] Open
Abstract
Molecular breast imaging (MBI) using 99mTc-sestamibi has advanced rapidly over the past decade. Technical advances allow lower-dose, higher-resolution imaging and biopsy capability. MBI can be used for supplemental breast cancer screening with mammography for women with dense breasts, as well as to assess neoadjuvant therapy response, evaluate disease extent, and predict breast cancer risk. This article highlights the current state of the art and future directions in MBI.
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Affiliation(s)
- Matthew F Covington
- Center for Quantitative Cancer Imaging, Huntsman Cancer Institute and University of Utah Department of Radiology and Imaging Sciences, Salt Lake City, Utah;
| | | | - Elizabeth H Dibble
- Warren Alpert Medical School of Brown University/Rhode Island Hospital Department of Diagnostic Imaging, Providence, Rhode Island
| | - Gaiane M Rauch
- M.D. Anderson Cancer Center, Departments of Abdominal and Breast Imaging, Houston, Texas; and
| | - Amy M Fowler
- University of Wisconsin School of Medicine and Public Health, Departments of Radiology and Medical Physics and the University of Wisconsin Carbone Cancer Center, Madison, Wisconsin
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Abstract
Knowledge of axillary nodal status is highly important for correct staging and treatment planning in patients with breast cancer. Axillary US is a recognized highly specific and cost-effective tool for assessing nodal status and guiding appropriate treatment. Axillary US imaging with US-guided biopsy is routinely performed throughout the world. However, because of recent developments in the surgical management of the axilla in patients with newly diagnosed breast cancer (American College of Surgeons Oncology Group [ACOSOG] Z0011 trial) and in patients with breast cancer receiving neoadjuvant systemic therapy (ACOSOG Z1071, SENTinel NeoAdjuvant [SENTINA] and Sentinel Node biopsy aFter NeoAdjuvant Chemotherapy [SN FNAC] trials), some have questioned the utility of axillary US for nodal staging. Here, we review the evidence to date supporting the additional value of axillary US for patients with breast cancer. Nodal US in patients with newly diagnosed breast cancer is useful for staging; in a significant proportion of patients, nodal US identifies additional axillary level II or level III nodal disease, which allows for appropriate treatment of disease. Furthermore, ongoing clinical trials may show that axillary surgery can be omitted in patients with negative findings on axillary US. In patients with lymph node-positive disease undergoing neoadjuvant systemic therapy, nodal US can guide the approach to axillary surgery. A more personalized patient approach, taking into the account tumor biology, among other factors, may help to mitigate the controversy surrounding the role of axillary US in breast cancer patients.
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Affiliation(s)
- Gaiane M Rauch
- The University of Texas MD Anderson Cancer Center, Departments of Abdominal and Breast Imaging, Houston, TX, USA
| | - Henry M Kuerer
- The University of Texas MD Anderson Cancer Center, Department of Breast Surgical Oncology, Houston, TX, USA
| | - Maxine S Jochelson
- Memorial Sloan Kettering Cancer Center, Department of Diagnostic Radiology, New York City, NY, USA
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46
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Kilcoyne A, Gottumukkala RV, Kang SK, Akin EA, Hauck C, Hindman NM, Huang C, Khanna N, Paspulati R, Rauch GM, Said T, Shinagare AB, Stein EB, Venkatesan AM, Maturen KE. ACR Appropriateness Criteria® Staging and Follow-up of Primary Vaginal Cancer. J Am Coll Radiol 2021; 18:S442-S455. [PMID: 34794599 DOI: 10.1016/j.jacr.2021.08.011] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2021] [Accepted: 08/28/2021] [Indexed: 11/30/2022]
Abstract
Primary vaginal cancer is rare, comprising 1% to 2% of gynecologic malignancies and 20% of all malignancies involving the vagina. More frequently, the vagina is involved secondarily by direct invasion from malignancies originating in adjacent organs or by metastases from other pelvic or extrapelvic primary malignancies. Data on the use of imaging in vaginal cancer are sparse. Insights are derived from the study of imaging in cervical cancer and have reasonable generalizability to vaginal cancer due to similar tumor biology. Given the trend toward definitive chemoradiation for both cancers in all but early stage lesions, principles of postchemoradiation tumor response evaluation are largely analogous. Accordingly, many of the recommendations outlined here are informed by principles translated from the literature on cervical cancer. For pretreatment assessment of local tumor burden and in the case of recurrent vaginal cancer, MRI is the preferred imaging modality. PET/CT has demonstrated utility for the detection of nodal metastatic and unexpected distant metastatic disease. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision include an extensive analysis of current medical literature from peer reviewed journals and the application of well-established methodologies (RAND/UCLA Appropriateness Method and Grading of Recommendations Assessment, Development, and Evaluation or GRADE) to rate the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where evidence is lacking or equivocal, expert opinion may supplement the available evidence to recommend imaging or treatment.
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Affiliation(s)
- Aoife Kilcoyne
- Panel Vice Chair, Massachusetts General Hospital, Boston, Massachusetts.
| | | | - Stella K Kang
- Panel Chair, New York University Medical Center, New York, New York
| | - Esma A Akin
- The George Washington University Medical Center, Washington, District of Columbia; ABNM Board Member; and IAC Board Member
| | - Carlin Hauck
- Sutter Medical Center Sacramento, Sacramento, California
| | - Nicole M Hindman
- Associate Chair, Diversity & Health Equity, MR Safety Officer, and Director, Female Pelvic Imaging, New York University Medical Center, New York, New York; and Fellow Rep., Board of the Society for Advanced Body Imaging
| | - Chenchan Huang
- New York University Langone Medical Center, New York, New York
| | - Namita Khanna
- Emory University, Atlanta, Georgia; Society of Gynecologic Oncology
| | | | - Gaiane M Rauch
- The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Tamer Said
- Program Director, Family Medicine Residency Program, University Hospitals Cleveland Medical Center, Cleveland, Ohio; and Primary care physician
| | - Atul B Shinagare
- Chief, Abdominal Imaging and Intervention, Brigham & Women's Hospital Dana-Farber Cancer Institute, Boston, Massachusetts
| | - Erica B Stein
- Director, Body CT, University of Michigan Medical Center, Ann Arbor, Michigan
| | | | - Katherine E Maturen
- Specialty Chair, University of Michigan, Ann Arbor, Michigan; and Member, Society of Abdominal Radiology Board of Directors
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47
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Zhang S, Rauch GM, Adrada BE, Boge M, Mohamed RMM, Abdelhafez AH, Son JB, Sun J, Elshafeey NA, White JB, Musall BC, Miyoshi M, Wang X, Kotrotsou A, Wei P, Hwang KP, Ma J, Pagel MD. Assessment of Early Response to Neoadjuvant Systemic Therapy in Triple-Negative Breast Cancer Using Amide Proton Transfer-weighted Chemical Exchange Saturation Transfer MRI: A Pilot Study. Radiol Imaging Cancer 2021; 3:e200155. [PMID: 34477453 PMCID: PMC8489465 DOI: 10.1148/rycan.2021200155] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/15/2023]
Abstract
Purpose To determine if amide proton transfer-weighted chemical exchange saturation transfer (APTW CEST) MRI is useful in the early assessment of treatment response in persons with triple-negative breast cancer (TNBC). Materials and Methods In this prospective study, a total of 51 participants (mean age, 51 years [range, 26-79 years]) with TNBC were included who underwent APTW CEST MRI with 0.9- and 2.0-µT saturation power performed at baseline, after two cycles (C2), and after four cycles (C4) of neoadjuvant systemic therapy (NAST). Imaging was performed between January 31, 2019, and November 11, 2019, and was a part of a clinical trial (registry number NCT02744053). CEST MR images were analyzed using two methods-magnetic transfer ratio asymmetry (MTRasym) and Lorentzian line shape fitting. The APTW CEST signals at baseline, C2, and C4 were compared for 51 participants to evaluate the saturation power levels and analysis methods. The APTW CEST signals and their changes during NAST were then compared for the 26 participants with pathology reports for treatment response assessment. Results A significant APTW CEST signal decrease was observed during NAST when acquisition at 0.9-µT saturation power was paired with Lorentzian line shape fitting analysis and when the acquisition at 2.0 µT was paired with MTRasym analysis. Using 0.9-µT saturation power and Lorentzian line shape fitting, the APTW CEST signal at C2 was significantly different from baseline in participants with pathologic complete response (pCR) (3.19% vs 2.43%; P = .03) but not with non-pCR (2.76% vs 2.50%; P > .05). The APTW CEST signal change was not significant between pCR and non-pCR at all time points. Conclusion Quantitative APTW CEST MRI depended on optimizing acquisition saturation powers and analysis methods. APTW CEST MRI monitored treatment effects but did not differentiate participants with TNBC who had pCR from those with non-pCR. © RSNA, 2021 Clinical trial registration no. NCT02744053 Supplemental material is available for this article.Keywords Molecular Imaging-Cancer, Molecular Imaging-Clinical Translation, MR-Imaging, Breast, Technical Aspects, Tumor Response, Technology Assessment.
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48
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Yam C, Yen EY, Chang JT, Bassett RL, Alatrash G, Garber H, Huo L, Yang F, Philips AV, Ding QQ, Lim B, Ueno NT, Kannan K, Sun X, Sun B, Parra Cuentas ER, Symmans WF, White JB, Ravenberg E, Seth S, Guerriero JL, Rauch GM, Damodaran S, Litton JK, Wargo JA, Hortobagyi GN, Futreal A, Wistuba II, Sun R, Moulder SL, Mittendorf EA. Immune Phenotype and Response to Neoadjuvant Therapy in Triple-Negative Breast Cancer. Clin Cancer Res 2021; 27:5365-5375. [PMID: 34253579 DOI: 10.1158/1078-0432.ccr-21-0144] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2021] [Revised: 05/10/2021] [Accepted: 07/07/2021] [Indexed: 11/16/2022]
Abstract
PURPOSE Increasing tumor-infiltrating lymphocytes (TIL) is associated with higher rates of pathologic complete response (pCR) to neoadjuvant therapy (NAT) in patients with triple-negative breast cancer (TNBC). However, the presence of TILs does not consistently predict pCR, therefore, the current study was undertaken to more fully characterize the immune cell response and its association with pCR. EXPERIMENTAL DESIGN We obtained pretreatment core-needle biopsies from 105 patients with stage I-III TNBC enrolled in ARTEMIS (NCT02276443) who received NAT from Oct 22, 2015 through July 24, 2018. The tumor-immune microenvironment was comprehensively profiled by performing T-cell receptor (TCR) sequencing, programmed death-ligand 1 (PD-L1) IHC, multiplex immunofluorescence, and RNA sequencing on pretreatment tumor samples. The primary endpoint was pathologic response to NAT. RESULTS The pCR rate was 40% (42/105). Higher TCR clonality (median = 0.2 vs. 0.1, P = 0.03), PD-L1 positivity (OR: 2.91, P = 0.020), higher CD3+:CD68+ ratio (median = 14.70 vs. 8.20, P = 0.0128), and closer spatial proximity of T cells to tumor cells (median = 19.26 vs. 21.94 μm, P = 0.0169) were associated with pCR. In a multivariable model, closer spatial proximity of T cells to tumor cells and PD-L1 expression enhanced prediction of pCR when considered in conjunction with clinical stage. CONCLUSIONS In patients receiving NAT for TNBC, deep immune profiling through detailed phenotypic characterization and spatial analysis can improve prediction of pCR in patients receiving NAT for TNBC when considered with traditional clinical parameters.
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Affiliation(s)
- Clinton Yam
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Er-Yen Yen
- Department of Genomic Medicine, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Jeffrey T Chang
- Department of Integrative Biology and Pharmacology, The University of Texas Health Science Center at Houston, Houston, Texas
| | - Roland L Bassett
- Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Gheath Alatrash
- Department of Stem Cell Transplantation and Cellular Therapy, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Haven Garber
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Lei Huo
- Department of Pathology, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Fei Yang
- Department of Translational Molecular Pathology, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Anne V Philips
- Department of Stem Cell Transplantation and Cellular Therapy, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Qing-Qing Ding
- Department of Pathology, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Bora Lim
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Naoto T Ueno
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Kasthuri Kannan
- Department of Translational Molecular Pathology, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Xiangjie Sun
- Department of Translational Molecular Pathology, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Baohua Sun
- Department of Translational Molecular Pathology, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Edwin Roger Parra Cuentas
- Department of Translational Molecular Pathology, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - William Fraser Symmans
- Department of Pathology, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Jason B White
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Elizabeth Ravenberg
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Sahil Seth
- Department of Genomic Medicine, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Jennifer L Guerriero
- Division of Breast Surgery, Department of Surgery, Brigham and Women's Hospital, Boston, Massachusetts.,Breast Oncology Program, Dana-Farber/Brigham and Women's Cancer Center, Boston, Massachusetts
| | - Gaiane M Rauch
- Department of Diagnostic Radiology, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Senthil Damodaran
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Jennifer K Litton
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Jennifer A Wargo
- Department of Genomic Medicine, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Gabriel N Hortobagyi
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Andrew Futreal
- Department of Genomic Medicine, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Ignacio I Wistuba
- Department of Translational Molecular Pathology, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Ryan Sun
- Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Stacy L Moulder
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Elizabeth A Mittendorf
- Division of Breast Surgery, Department of Surgery, Brigham and Women's Hospital, Boston, Massachusetts. .,Breast Oncology Program, Dana-Farber/Brigham and Women's Cancer Center, Boston, Massachusetts.,Ludwig Center at Harvard, Boston, Massachusetts
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49
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Lopez BP, Guan F, Rauch GM, Kappadath SC. Monte Carlo simulation of pixelated CZT detector with Geant4: validation of clinical molecular breast imaging system. Phys Med Biol 2021; 66. [PMID: 34038878 DOI: 10.1088/1361-6560/ac0588] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2021] [Accepted: 05/26/2021] [Indexed: 11/12/2022]
Abstract
Purpose. Molecular breast imaging (MBI) of99mTc-sestamibi with dual-headed, pixelated, cadmium-zinc-telluride (CZT) detectors is increasingly used in breast cancer care for screening/detecting lesions, monitoring response to therapy, and predicting risk of cancer. MBI as a truly quantitative tool in these applications, however, is limited due the lack of absolute99mTc-sestamibi uptake quantification. To help advance the field of quantitative MBI, we have developed a Monte Carlo simulation application of the GE Discovery NM 750b system.Methods. Our simulation consists of a two-step process using the Geant4 toolkit to model the detector and source geometry and to track photon interactions and a MATLAB script to model the charge transport within the pixelated CZT detector. Simulated detector and detector response model parameters were selected to match measured and simulated standard performance characteristics using various99mTc point-, line-, and film-sources in air. The final model parameters were verified by comparing the count profiles, energy spectra, and region of interest counts between simulated and measured images of a breast phantom with two spherical lesions in 5 cm thick medium of air or water.Results. Final performance characteristics with99mTc sources in air were: (1) energy resolution: 6.1% measured versus 5.9% simulated photopeak full-width at half-maximum (FWHM), (2) spatial resolution: mean error between measured and simulated FWHM of 0.08 mm across 4.4-14.0 mm FWHM range, and (3) sensitivity: 572 cpm/μCi measured versus 567 cpm/μCi simulated (<1% error). Good agreement was observed in the breast phantom line profiles through the spherical lesions and overall energy spectra, with <5% difference in sphere counts between simulated and measured data.Conclusion. A pixelated CZT charge transport and induction model was successfully implemented and validated to simulate imaging with the GE Discovery NM 750b system. This work will enable investigations improving MBI image quality and developing algorithms for uptake quantification.
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Affiliation(s)
- Benjamin P Lopez
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, United States of America.,MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences, Houston, TX 77030, United States of America
| | - Fada Guan
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, United States of America
| | - Gaiane M Rauch
- Department of Abdominal Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, United States of America
| | - S Cheenu Kappadath
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, United States of America.,MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences, Houston, TX 77030, United States of America
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50
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Yam C, Mittendorf EA, Sun R, Huo L, Damodaran S, Rauch GM, Candelaria RP, Adrada BE, Seth S, Symmans WF, Murthy RK, White JB, Ravenberg E, Clayborn A, Prabhakaran S, Valero V, Thompson AM, Tripathy D, Moulder SL, Litton JK. Neoadjuvant atezolizumab (atezo) and nab-paclitaxel (nab-p) in patients (pts) with triple-negative breast cancer (TNBC) with suboptimal clinical response to doxorubicin and cyclophosphamide (AC). J Clin Oncol 2021. [DOI: 10.1200/jco.2021.39.15_suppl.592] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
592 Background: Neoadjuvant anti-PD-(L)1 therapy confers an improvement in pathological complete response (pCR) rate in unselected TNBC. However, given the potential for long-term morbidity from immune related adverse events (irAE), it is important to optimize the risk-benefit ratio for the use of these novel agents in the curative neoadjuvant setting. Suboptimal clinical response to neoadjuvant therapy (NAT) by sonography is associated with low rates of pCR rate (2-5%, GeparTrio and Aberdeen trials). Here, we report the results of a single arm phase II study of atezo and nab-p as the second phase of NAT in pts with TNBC with suboptimal clinical response to AC (NCT02530489). Methods: Pts with stage I-III TNBC showing suboptimal response to 4 cycles of doxorubicin and cyclophosphamide (AC), defined as disease progression or a <80% reduction in tumor volume by sonography, were eligible. Pts received atezo (1200mg IV, Q3 weeks x 4), and nab-p (100mg/m2 IV, Q1 week, x 12) as the second phase of NAT before undergoing surgery followed by adjuvant atezo (1200mg IV, Q3 weeks, x 4 cycles). This single arm, two-stage Gehan-type study was designed to detect an improvement in pCR from 5% to 20% in order to deem the regimen worthy of further study in a large, randomized, phase II/III trial; success was defined as pCR in 8 out of 37 pts enrolled. In a subset of pts, sufficient baseline tumor tissue was available for stromal TIL assessment (n=29). Results: 34 pts were enrolled from 2/2016-12/2020. Among the 33 pts who have completed NAT, the pCR rate was 30% (10/33, 95% CI: 16-49%) and the pCR/RCB-I rate was 42% (14/33, 95% CI: 25-61%). Clinicopathological characteristics are described in the table below. Treatment-related adverse events (all grades) occurring in ≥ 20% of pts include fatigue (73%), anemia (55%), peripheral sensory neuropathy (55%), neutropenia (48%), rash (42%), ALT elevation (39%), AST elevation (33%), nausea (30%), anorexia (24%), diarrhea (21%), myalgia (21%). Discontinuation of atezo due to irAEs occurred in 4 pts (12%, nephritis [n=2]; adrenal insufficiency [n=1]; hepatitis [n=1]); 2 of these pts had pCR. Conclusions: This study met its primary endpoint, demonstrating a promising signal of activity in this high risk pt population (pCR=30% vs 5% in historical controls). The 12% discontinuation rate due to irAEs confirms that further evaluation of a strategy administering immunotherapy only to pts with high risk disease not responding to AC warrants further investigation. Exploratory genomic and immunological correlative studies are ongoing. Clinical trial information: NCT02530489. [Table: see text]
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Affiliation(s)
- Clinton Yam
- The University of Texas MD Anderson Cancer Center, Houston, TX
| | | | - Ryan Sun
- The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Lei Huo
- The University of Texas MD Anderson Cancer Center, Houston, TX
| | | | - Gaiane M Rauch
- The University of Texas MD Anderson Cancer Center, Houston, TX
| | | | | | - Sahil Seth
- The University of Texas MD Anderson Cancer Center, Houston, TX
| | | | | | - Jason B White
- The University of Texas MD Anderson Cancer Center, Houston, TX
| | | | - Alyson Clayborn
- The University of Texas MD Anderson Cancer Center, Houston, TX
| | | | - Vicente Valero
- The University of Texas MD Anderson Cancer Center, Houston, TX
| | | | - Debu Tripathy
- The University of Texas MD Anderson Cancer Center, Houston, TX
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