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Hayward JH, Linden OE, Lewin AA, Weinstein SP, Bachorik AE, Balija TM, Kuzmiak CM, Paulis LV, Salkowski LR, Sanford MF, Scheel JR, Sharpe RE, Small W, Ulaner GA, Slanetz PJ. ACR Appropriateness Criteria® Monitoring Response to Neoadjuvant Systemic Therapy for Breast Cancer: 2022 Update. J Am Coll Radiol 2023; 20:S125-S145. [PMID: 37236739 DOI: 10.1016/j.jacr.2023.02.016] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2023] [Accepted: 02/27/2023] [Indexed: 05/28/2023]
Abstract
Imaging plays a vital role in managing patients undergoing neoadjuvant chemotherapy, as treatment decisions rely heavily on accurate assessment of response to therapy. This document provides evidence-based guidelines for imaging breast cancer before, during, and after initiation of neoadjuvant chemotherapy. 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 process support the systematic analysis of the medical literature from peer reviewed journals. Established methodology principles such as Grading of Recommendations Assessment, Development, and Evaluation or GRADE are adapted to evaluate the evidence. The RAND/UCLA Appropriateness Method User Manual provides the methodology to determine the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where peer reviewed literature is lacking or equivocal, experts may be the primary evidentiary source available to formulate a recommendation.
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Affiliation(s)
| | - Olivia E Linden
- Research Author, University of California, San Francisco, San Francisco, California
| | - Alana A Lewin
- Panel Chair, New York University Grossman School of Medicine, New York, New York
| | - Susan P Weinstein
- Panel Vice-Chair, Perelman School of Medicine of the University of Pennsylvania, Philadelphia, Pennsylvania
| | | | - Tara M Balija
- Hackensack University Medical Center, Hackensack, New Jersey; American College of Surgeons
| | - Cherie M Kuzmiak
- University of North Carolina Hospital, Chapel Hill, North Carolina
| | | | - Lonie R Salkowski
- University of Wisconsin School of Medicine & Public Health, Madison, Wisconsin
| | | | | | | | - William Small
- Loyola University Chicago, Stritch School of Medicine, Department of Radiation Oncology, Cardinal Bernardin Cancer Center, Maywood, Illinois
| | - Gary A Ulaner
- Hoag Family Cancer Institute, Newport Beach, California, and University of Southern California, Los Angeles, California; Commission on Nuclear Medicine and Molecular Imaging
| | - Priscilla J Slanetz
- Specialty Chair, Boston University School of Medicine, Boston, Massachusetts
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2
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Zhang K, Lin J, Lin F, Wang Z, Zhang H, Zhang S, Mao N, Qiao G. Radiomics of contrast-enhanced spectral mammography for prediction of pathological complete response to neoadjuvant chemotherapy in breast cancer. JOURNAL OF X-RAY SCIENCE AND TECHNOLOGY 2023:XST221349. [PMID: 37066960 DOI: 10.3233/xst-221349] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/19/2023]
Abstract
BACKGROUND Neoadjuvant chemotherapy (NAC) has been regarded as one of the standard treatments for patients with locally advanced breast cancer. No previous study has investigated the feasibility of using a contrast-enhanced spectral mammography (CESM)-based radiomics nomogram to predict pathological complete response (pCR) after NAC. OBJECTIVE To develop and validate a CESM-based radiomics nomogram to predict pCR after NAC in breast cancer. METHODS A total of 118 patients were enrolled, which are divided into a training dataset including 82 patients (with 21 pCR and 61 non-pCR) and a testing dataset of 36 patients (with 9 pCR and 27 non-pCR). The tumor regions of interest (ROIs) were manually segmented by two radiologists on the low-energy and recombined images and radiomics features were extracted. Intraclass correlation coefficients (ICCs) were used to assess the intra- and inter-observer agreements of ROI features extraction. In the training set, the variance threshold, SelectKBest method, and least absolute shrinkage and selection operator regression were used to select the optimal radiomics features. Radiomics signature was calculated through a linear combination of selected features. A radiomics nomogram containing radiomics signature score (Rad-score) and clinical risk factors was developed. The receiver operating characteristic (ROC) curve and calibration curve were used to evaluate prediction performance of the radiomics nomogram, and decision curve analysis (DCA) was used to evaluate the clinical usefulness of the radiomics nomogram. RESULTS The intra- and inter- observer ICCs were 0.769-0.815 and 0.786-0.853, respectively. Thirteen radiomics features were selected to calculate Rad-score. The radiomics nomogram containing Rad-score and clinical risk factor showed an encouraging calibration and discrimination performance with area under the ROC curves of 0.906 (95% confidence interval (CI): 0.840-0.966) in the training dataset and 0.790 (95% CI: 0.554-0.952) in the test dataset. CONCLUSIONS The CESM-based radiomics nomogram had good prediction performance for pCR after NAC in breast cancer; therefore, it has a good clinical application prospect.
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Affiliation(s)
- Kun Zhang
- Department of Breast Surgery, The Affiliated Yantai Yuhuangding Hospital of Qingdao University, Yantai, China
| | - Jun Lin
- Department of Breast Surgery, The Affiliated Yantai Yuhuangding Hospital of Qingdao University, Yantai, China
| | - Fan Lin
- Department of Radiology, The Affiliated Yantai Yuhuangding Hospital of Qingdao University, Yantai, China
| | - Zhongyi Wang
- Department of Radiology, The Affiliated Yantai Yuhuangding Hospital of Qingdao University, Yantai, China
| | - Haicheng Zhang
- Department of Radiology, The Affiliated Yantai Yuhuangding Hospital of Qingdao University, Yantai, China
| | - Shijie Zhang
- Department of Radiology, The Affiliated Yantai Yuhuangding Hospital of Qingdao University, Yantai, China
| | - Ning Mao
- Department of Radiology, The Affiliated Yantai Yuhuangding Hospital of Qingdao University, Yantai, China
| | - Guangdong Qiao
- Department of Breast Surgery, The Affiliated Yantai Yuhuangding Hospital of Qingdao University, Yantai, China
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Surgical Planning after Neoadjuvant Treatment in Breast Cancer: A Multimodality Imaging-Based Approach Focused on MRI. Cancers (Basel) 2023; 15:cancers15051439. [PMID: 36900231 PMCID: PMC10001061 DOI: 10.3390/cancers15051439] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2023] [Revised: 02/19/2023] [Accepted: 02/21/2023] [Indexed: 03/12/2023] Open
Abstract
Neoadjuvant chemotherapy (NACT) today represents a cornerstone in the treatment of locally advanced breast cancer and highly chemo-sensitive tumors at early stages, increasing the possibilities of performing more conservative treatments and improving long term outcomes. Imaging has a fundamental role in the staging and prediction of the response to NACT, thus aiding surgical planning and avoiding overtreatment. In this review, we first examine and compare the role of conventional and advanced imaging techniques in preoperative T Staging after NACT and in the evaluation of lymph node involvement. In the second part, we analyze the different surgical approaches, discussing the role of axillary surgery, as well as the possibility of non-operative management after-NACT, which has been the subject of recent trials. Finally, we focus on emerging techniques that will change the diagnostic assessment of breast cancer in the near future.
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Howard FM, He G, Peterson JR, Pfeiffer JR, Earnest T, Pearson AT, Abe H, Cole JA, Nanda R. Highly accurate response prediction in high-risk early breast cancer patients using a biophysical simulation platform. Breast Cancer Res Treat 2022; 196:57-66. [PMID: 36063220 PMCID: PMC9550684 DOI: 10.1007/s10549-022-06722-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2022] [Accepted: 08/19/2022] [Indexed: 11/28/2022]
Abstract
PURPOSE Pathologic complete response (pCR) to neoadjuvant chemotherapy (NAC) in early breast cancer (EBC) is largely dependent on breast cancer subtype, but no clinical-grade model exists to predict response and guide selection of treatment. A biophysical simulation of response to NAC has the potential to address this unmet need. METHODS We conducted a retrospective evaluation of a biophysical simulation model as a predictor of pCR. Patients who received standard NAC at the University of Chicago for EBC between January 1st, 2010 and March 31st, 2020 were included. Response was predicted using baseline breast MRI, clinicopathologic features, and treatment regimen by investigators who were blinded to patient outcomes. RESULTS A total of 144 tumors from 141 patients were included; 59 were triple-negative, 49 HER2-positive, and 36 hormone-receptor positive/HER2 negative. Lymph node disease was present in half of patients, and most were treated with an anthracycline-based regimen (58.3%). Sensitivity and specificity of the biophysical simulation for pCR were 88.0% (95% confidence interval [CI] 75.7 - 95.5) and 89.4% (95% CI 81.3 - 94.8), respectively, with robust results regardless of subtype. In patients with predicted pCR, 5-year event-free survival was 98%, versus 79% with predicted residual disease (log-rank p = 0.01, HR 4.57, 95% CI 1.36 - 15.34). At a median follow-up of 5.4 years, no patients with predicted pCR experienced disease recurrence. CONCLUSION A biophysical simulation model accurately predicts pCR and long-term outcomes from baseline MRI and clinical data, and is a promising tool to guide escalation/de-escalation of NAC.
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Affiliation(s)
- Frederick M Howard
- Department of Medicine, University of Chicago, 5841 S. Maryland Avenue
- MC 2115, Chicago, IL, 60637, USA.
| | - Gong He
- Department of Medicine, University of Chicago, 5841 S. Maryland Avenue
- MC 2115, Chicago, IL, 60637, USA
| | | | | | | | - Alexander T Pearson
- Department of Medicine, University of Chicago, 5841 S. Maryland Avenue
- MC 2115, Chicago, IL, 60637, USA
| | - Hiroyuki Abe
- Department of Radiology, University of Chicago, Chicago, IL, USA
| | | | - Rita Nanda
- Department of Medicine, University of Chicago, 5841 S. Maryland Avenue
- MC 2115, Chicago, IL, 60637, USA
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5
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Prediction of pathologic complete response on MRI in patients with breast cancer receiving neoadjuvant chemotherapy according to molecular subtypes. Eur Radiol 2022; 32:4056-4066. [PMID: 34989844 DOI: 10.1007/s00330-021-08461-0] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2021] [Revised: 10/06/2021] [Accepted: 11/08/2021] [Indexed: 12/24/2022]
Abstract
OBJECTIVES This study aimed to investigate the predictability of breast MRI for pathologic complete response (pCR) by molecular subtype in patients with breast cancer receiving neoadjuvant chemotherapy (NAC) and investigate the MRI findings that can mimic residual malignancy. METHODS A total of 506 patients with breast cancer who underwent MRI after NAC and underwent surgery between January and December 2018 were included. Two breast radiologists dichotomized the post-NAC MRI findings as radiologic complete response (rCR) and no-rCR. The diagnostic performance of MRI predicting pCR was evaluated. pCR was determined based on the final pathology reports. Tumors were divided according to hormone receptor (HR) and human epidermal growth factor receptor (HER) 2. Residual lesions on post-NAC MRI were divided into overt and subtle which classified as nodularity or delayed enhancement. Pearson's χ2 and Wilcoxon rank-sum tests were used for MRI findings causing false-negative pCR. RESULTS The overall pCR rate was 30.04%. The overall accuracy for predicting pCR using MRI was 76.68%. The accuracy was significantly different by subtypes (p < 0.001), as follows in descending order: HR - /HER2 - (85.63%), HR + /HER2 - (82.84%), HR + /HER2 + (69.37%), and HR - /HER2 + (62.38%). MRI in the HR - /HER2 + type showed the highest false-negative rate (18.81%) for predicting pCR. The subtle residual enhancement observed only in the delayed phase was associated with false-negative findings (76.2%, p = 0.016). CONCLUSIONS The diagnostic accuracy of MRI for predicting pCR differed by molecular subtypes. When the residual enhancement on MRI after NAC is subtle and seen only in the delayed phase, overinterpretation of residual tumors should be performed with caution. KEY POINTS • In patients with breast cancer after completion of neoadjuvant chemotherapy, the diagnostic accuracy of MRI for predicting pathologic complete response (pCR) differed according to molecular subtype. • When residual enhancement on MRI is subtle and seen only in the delayed phase, this finding could be associated with false-negative pCR results.
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Choudhery S, Gomez-Cardona D, Favazza CP, Hoskin TL, Haddad TC, Goetz MP, Boughey JC. MRI Radiomics for Assessment of Molecular Subtype, Pathological Complete Response, and Residual Cancer Burden in Breast Cancer Patients Treated With Neoadjuvant Chemotherapy. Acad Radiol 2022; 29 Suppl 1:S145-S154. [PMID: 33160859 PMCID: PMC8093323 DOI: 10.1016/j.acra.2020.10.020] [Citation(s) in RCA: 27] [Impact Index Per Article: 13.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2020] [Revised: 10/11/2020] [Accepted: 10/16/2020] [Indexed: 01/03/2023]
Abstract
RATIONALE AND OBJECTIVES There are limited data on pretreatment imaging features that can predict response to neoadjuvant chemotherapy (NAC). To extract volumetric pretreatment MRI radiomics features and assess corresponding associations with breast cancer molecular subtypes, pathological complete response (pCR), and residual cancer burden (RCB) in patients treated with NAC. MATERIALS AND METHODS In this IRB-approved study, clinical and pretreatment MRI data from patients with biopsy-proven breast cancer who received NAC between September 2009 and July 2016 were retrospectively analyzed. Tumors were manually identified and semi-automatically segmented on first postcontrast images. Morphological and three-dimensional textural features were computed, including unfiltered and filtered image data, with spatial scaling factors (SSF) of 2, 4, and 6 mm. Wilcoxon rank-sum tests and area under the receiver operating characteristic curve were used for statistical analysis. RESULTS Two hundred and fifty nine patients with unilateral breast cancer, including 73 (28.2%) HER2+, 112 (43.2%) luminal, and 74 (28.6%) triple negative breast cancers (TNBC), were included. There was a significant difference in the median volume (p = 0.008), median longest axial tumor diameter (p = 0.009), and median longest volumetric diameter (p = 0.01) among tumor subtypes. There was also a significant difference in minimum signal intensity and entropy among the tumor subtypes with SSF = 4 mm (p = 0.009 and p = 0.02 respectively) and SSF = 6 mm (p = 0.007 and p < 0.001 respectively). Additionally, sphericity (p = 0.04) in HER2+ tumors and entropy with SSF = 2, 4, 6 mm (p = 0.004, 0.02, 0.047 respectively) in luminal tumors were significantly associated with pCR. Multiple features demonstrated significant association (p < 0.05) with pCR in TNBC and with RCB in luminal tumors and TNBC, with standard deviation of intensity with SSF = 6 mm achieving the highest AUC (AUC = 0.734) for pCR in TNBC. CONCLUSION MRI radiomics features are associated with different molecular subtypes of breast cancer, pCR, and RCB. These features may be noninvasive imaging biomarkers to identify cancer subtype and predict response to NAC.
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Affiliation(s)
| | | | | | - Tanya L Hoskin
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN
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Graeser M, Schrading S, Gluz O, Strobel K, Würstlein R, Kümmel S, Schumacher C, Grischke E, Forstbauer H, Braun M, Christgen M, Adams J, Nitzsche H, Just M, Fischer HH, Aktas B, Potenberg J, von Schumann R, Kolberg‐Liedtke C, Harbeck N, Kuhl CK, Nitz U. Early response by MR imaging and ultrasound as predictor of pathologic complete response to 12-week neoadjuvant therapy for different early breast cancer subtypes: Combined analysis from the WSG ADAPT subtrials. Int J Cancer 2021; 148:2614-2627. [PMID: 33533487 PMCID: PMC8048810 DOI: 10.1002/ijc.33495] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2020] [Revised: 12/18/2020] [Accepted: 12/21/2020] [Indexed: 12/31/2022]
Abstract
We evaluated the role of early response after 3 weeks of neoadjuvant treatment (NAT) assessed by ultrasound (US), magnetic resonance imaging (MRI) and Ki-67 dynamics for prediction of pathologic complete response (pCR) in different early breast cancer subtypes. Patients with HR+/HER2+, HR-/HER2- and HR-/HER2+ tumors enrolled into three neoadjuvant WSG ADAPT subtrials underwent US, MRI and Ki-67 assessment at diagnosis and after 3 weeks of NAT. Early response was defined as complete or partial response (US, MRI) and ≥30% proliferation decrease or <500 invasive tumor cells (Ki-67). Predictive values and area under the receiver operating characteristic (AUC) curves for prediction of pCR (ypT0/is ypN0) after 12-week NAT were calculated. Two hundred twenty-six had MRI and 401 US; 107 underwent both MRI and US. All three methods yielded a similar AUC in HR+/HER2+ (0.66-0.67) and HR-/HER2- tumors (0.53-0.63), while MRI and Ki-67 performed better than US in HR-/HER2+ tumors (0.83 and 0.79 vs 0.56). Adding MRI+/-Ki-67 increased AUC of US in HR-/HER2+ tumors to 0.64 to 0.75. MRI and Ki-67 demonstrated highest sensitivity in HR-/HER2- (0.8-1) and HR-/HER2+ tumors (1, both). Negative predictive value was similar for all methods in HR+/HER2+ (0.71-0.74) and HR-/HER2- tumors (0.85-1), while it was higher for MRI and Ki-67 compared to US in HR-/HER2+ subtype (1 vs 0.5). Early response assessed by US, MRI and Ki-67 is a strong predictor for pCR after 12-week NAT. Strength of pCR prediction varies according to tumor subtype. Adding MRI+/-Ki-67 to US did not improve pCR prediction in majority of our patients.
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Affiliation(s)
- Monika Graeser
- West German Study GroupMoenchengladbachGermany
- Ev. Hospital Bethesda, Breast Center NiederrheinMoenchengladbachGermany
- Department of GynecologyUniversity Medical Center HamburgHamburgGermany
| | - Simone Schrading
- Department of Diagnostic and Interventional RadiologyHospital of the University of Aachen, RWTHAachenGermany
| | - Oleg Gluz
- West German Study GroupMoenchengladbachGermany
- Ev. Hospital Bethesda, Breast Center NiederrheinMoenchengladbachGermany
- University Hospital CologneCologneGermany
| | - Kevin Strobel
- Department of Diagnostic and Interventional RadiologyHospital of the University of Aachen, RWTHAachenGermany
| | - Rachel Würstlein
- West German Study GroupMoenchengladbachGermany
- Breast Center, Department of Gynecology and Obstetrics and CCCLMULMU University HospitalMunichGermany
| | - Sherko Kümmel
- West German Study GroupMoenchengladbachGermany
- Breast UnitKliniken Essen‐MitteEssenGermany
- University Hospital Charité, Humboldt University BerlinBerlinGermany
| | | | | | | | - Michael Braun
- Department of GynecologyBreast Center, Red Cross Hospital MunichMunichGermany
| | | | | | - Henrik Nitzsche
- Ev. Hospital Bethesda, Breast Center NiederrheinMoenchengladbachGermany
| | | | | | - Bahriye Aktas
- Department of Gynecology and ObstetricsUniversity Clinics EssenEssenGermany
- Department of GynecologyUniversity Hospital LeipzigLeipzigGermany
| | | | | | - Cornelia Kolberg‐Liedtke
- University Hospital Charité, Humboldt University BerlinBerlinGermany
- Department of Gynecology and ObstetricsUniversity Clinics EssenEssenGermany
| | - Nadia Harbeck
- West German Study GroupMoenchengladbachGermany
- Breast Center, Department of Gynecology and Obstetrics and CCCLMULMU University HospitalMunichGermany
| | - Christiane K. Kuhl
- Department of Diagnostic and Interventional RadiologyHospital of the University of Aachen, RWTHAachenGermany
| | - Ulrike Nitz
- West German Study GroupMoenchengladbachGermany
- Ev. Hospital Bethesda, Breast Center NiederrheinMoenchengladbachGermany
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Adrada BE, Candelaria R, Moulder S, Thompson A, Wei P, Whitman GJ, Valero V, Litton JK, Santiago L, Scoggins ME, Moseley TW, White JB, Ravenberg EE, Yang WT, Rauch GM. Early ultrasound evaluation identifies excellent responders to neoadjuvant systemic therapy among patients with triple-negative breast cancer. Cancer 2021; 127:2880-2887. [PMID: 33878210 DOI: 10.1002/cncr.33604] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2020] [Revised: 03/06/2021] [Accepted: 03/18/2021] [Indexed: 01/12/2023]
Abstract
BACKGROUND Heterogeneity exists in the response of triple-negative breast cancer (TNBC) to standard anthracycline (AC)/taxane-based neoadjuvant systemic therapy (NAST), with 40% to 50% of patients having a pathologic complete response (pCR) to therapy. Early assessment of the imaging response during NAST may identify a subset of TNBCs that are likely to have a pCR upon completion of treatment. The authors aimed to evaluate the performance of early ultrasound (US) after 2 cycles of neoadjuvant NAST in identifying excellent responders to NAST among patients with TNBC. METHODS Two hundred fifteen patients with TNBC were enrolled in the ongoing ARTEMIS (A Robust TNBC Evaluation Framework to Improve Survival) clinical trial. The patients were divided into a discovery cohort (n = 107) and a validation cohort (n = 108). A receiver operating characteristic analysis with 95% confidence intervals (CIs) and a multivariate logistic regression analysis were performed to model the probability of a pCR on the basis of the tumor volume reduction (TVR) percentage by US from the baseline to after 2 cycles of AC. RESULTS Overall, 39.3% of the patients (42 of 107) achieved a pCR. A positive predictive value (PPV) analysis identified a cutoff point of 80% TVR after 2 cycles; the pCR rate was 77% (17 of 22) in patients with a TVR ≥ 80%, and the area under the curve (AUC) was 0.84 (95% CI, 0.77-0.92; P < .0001). In the validation cohort, the pCR rate was 44%. The PPV for pCR with a TVR ≥ 80% after 2 cycles was 76% (95% CI, 55%-91%), and the AUC was 0.79 (95% CI, 0.70-0.87; P < .0001). CONCLUSIONS The TVR percentage by US evaluation after 2 cycles of NAST may be a cost-effective early imaging biomarker for a pCR to AC/taxane-based NAST.
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Affiliation(s)
- Beatriz E Adrada
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Rosalind Candelaria
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Stacy Moulder
- Department of Breast Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Alastair Thompson
- Department of Breast Surgery, University of Baylor College of Medicine, Houston, Texas.,Lester and Sue Smith Breast Cancer, University of Baylor College of Medicine, Houston, Texas
| | - Peng Wei
- Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Gary J Whitman
- Department of Breast Imaging, 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
| | - Lumarie Santiago
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Marion E Scoggins
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Tanya W Moseley
- Department of Breast Imaging and Surgical Oncology, 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 E Ravenberg
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Wei T Yang
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Gaiane M Rauch
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, Texas
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Pasquero G, Surace A, Ponti A, Bortolini M, Tota D, Mano MP, Arisio R, Benedetto C, Baù MG. Role of Magnetic Resonance Imaging in the Evaluation of Breast Cancer Response to Neoadjuvant Chemotherapy. In Vivo 2020; 34:909-915. [PMID: 32111803 DOI: 10.21873/invivo.11857] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2019] [Revised: 12/12/2019] [Accepted: 12/18/2019] [Indexed: 02/06/2023]
Abstract
BACKGROUND/AIM The aim of the study was to evaluate whether residual tumor assessment by magnetic resonance imaging (MRI) after neoadjuvant chemotherapy (NACT) is fundamental for a successive surgical strategy. PATIENTS AND METHODS We collected 55 MRIs performed after NACT. RESULTS Pathological response rate was 20%. MRI's sensitivity, specificity, PPV and NPV were 50%, 88%, 54% and 86%, respectively. We observed a high variability between the different subgroups, with high number of false positives in luminal A/B tumors. Triple negative and HER2+ tumors had almost the same specificity and sensitivity (81% and 50%). Nevertheless, in the HER2+ group, PPV was greater than that in the triple negative group (71% and 33% respectively) and the NPV of the triple negative group was greater than that of the HER2+ one (90% and 64%, respectively). Statistical analysis showed a weak but significant correlation between MRI and pathological assessment of residual tumor dimension. CONCLUSION The present study, confirms literature data about MRI accuracy in diagnosing HER2+ and triple negative tumors, but suggests caution in case of luminal tumors' evaluation.
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Affiliation(s)
- Giorgia Pasquero
- Gynecology and Obstetrics 1, Department of Surgical Sciences, City of Health and Science, University of Turin, Turin, Italy
| | - Alessandra Surace
- Gynecology and Obstetrics 2, Department of Surgical Sciences, City of Health and Science, University of Turin, Turin, Italy
| | - Antonio Ponti
- AOU Città della Salute e della Scienza, CPO Piemonte and EUSOMA Data Centre, Turin, Italy
| | | | - Donatella Tota
- Radiology, Department of Diagnostic Imaging and Radiotherapy, City of Health and Science, University of Turin, Turin, Italy
| | - Maria Piera Mano
- AOU Città della Salute e della Scienza, CPO Piemonte and EUSOMA Data Centre, Turin, Italy
| | - Riccardo Arisio
- Pathology, Department of Laboratory Medicine, City of Health and Science, University of Turin, Turin, Italy
| | - Chiara Benedetto
- Gynecology and Obstetrics 1, Department of Surgical Sciences, City of Health and Science, University of Turin, Turin, Italy
| | - Maria Grazia Baù
- Gynecology and Obstetrics 3, Department of Surgical Sciences, City of Health and Science, University of Turin, Turin, Italy
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Yu N, Leung VWY, Meterissian S. MRI Performance in Detecting pCR After Neoadjuvant Chemotherapy by Molecular Subtype of Breast Cancer. World J Surg 2019; 43:2254-2261. [PMID: 31101952 DOI: 10.1007/s00268-019-05032-9] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
BACKGROUND MRI performance in detecting pathologic complete response (pCR) post-neoadjuvant chemotherapy (NAC) in breast cancer has been previously explored. However, since tumor response varies by molecular subtype, it is plausible that imaging performance also varies. Therefore, we performed a literature review on subtype-specific MRI performance in detecting pCR post-NAC. METHODS Two reviewers searched Cochrane, PubMed, and EMBASE for articles published between 2013 and 2018 that examined MRI performance in detecting pCR post-NAC. After filtering, ten primary research articles were included. Statistical metrics, such as sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV), were extracted per study for triple negative, HR+/HER2-, and HER2+ patients. RESULTS Ten studies involving 2310 patients were included. In triple negative breast cancer, MRI showed NPV (58-100%) and PPV (72.7-94.7%) across 446 patients and sensitivity (45.5-100%) and specificity (49-94.4%) in 375 patients. In HR+/HER2- breast cancer patients, MRI showed NPV (29.4-100%) and PPV (21.4-95.1%) across 851 patients and sensitivity (43-100%) and specificity (45-93%) across 780 patients. In HER2+-enriched subtype, MRI showed NPV (62-94.6%) and PPV (34.9-72%) in 243 patients and sensitivity (36.2-83%) and specificity (47-90%) in 255 patients. CONCLUSION MRI accuracy in detecting pCR post-NAC by subtype is not as consistent, nor as high, as individual studies suggest. Larger studies using standardized pCR definition with appropriate timing of surgery and MRI need to be conducted. This study has shown that MRI is in fact not an accurate prediction of pCR, and thus, clinicians may need to rely on other approaches such as biopsies of the tumor bed.
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Affiliation(s)
- Nancy Yu
- Faculty of Medicine, McGill University, Montréal, QC, H4A3T2, Canada
| | - Vivian W Y Leung
- Faculty of Medicine, McGill University, Montréal, QC, H4A3T2, Canada
| | - Sarkis Meterissian
- Faculty of Medicine, McGill University, Montréal, QC, H4A3T2, Canada.
- Department of Oncology, McGill University, Montréal, QC, H4A3T2, Canada.
- Department of Surgery, McGill University, Montréal, QC, H3G1A4, Canada.
- Research Institute of MUHC, Glen Site, 1001 Decarie Boulevard, Montreal, QC, H4A 3J1, Canada.
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11
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Kontopodis E, Venianaki M, Manikis GC, Nikiforaki K, Salvetti O, Papadaki E, Papadakis GZ, Karantanas AH, Marias K. Investigating the Role of Model-Based and Model-Free Imaging Biomarkers as Early Predictors of Neoadjuvant Breast Cancer Therapy Outcome. IEEE J Biomed Health Inform 2019; 23:1834-1843. [DOI: 10.1109/jbhi.2019.2895459] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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12
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Tsukada H, Tsukada J, Schrading S, Strobel K, Okamoto T, Kuhl CK. Accuracy of multi-parametric breast MR imaging for predicting pathological complete response of operable breast cancer prior to neoadjuvant systemic therapy. Magn Reson Imaging 2019; 62:242-248. [PMID: 31352016 DOI: 10.1016/j.mri.2019.07.008] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2019] [Revised: 07/12/2019] [Accepted: 07/13/2019] [Indexed: 10/26/2022]
Abstract
OBJECTIVES To evaluate whether multiparametric breast-MRI, obtained before the initiation of neoadjuvant systemic therapy (NST) for operable breast cancer, predicts which cancer will achieve a pathological complete response (pCR) after the completion of NST. METHODS This was an IRB-approved retrospective study on 31 consecutive patients (median age, 56 years) with operable invasive breast cancer (median size: 22 mm; triple-negative: 11/31 [35%], HER2-positive: 7/31 [23%], triple-positive: 13/31 [42%]) who underwent multiparametric DCE-MRI before the initiation of NST. The MRI protocol consisted of high-resolution dynamic contrast-enhanced MRI (DCE-MRI), T2-TSE, and DWI (b-values 0, 100, 800 s/mm2). The results of surgical pathology after the completion of NST served as a standard of reference. Patient characteristics (age and menopausal status), pathological tumor characteristics (type, stage, nuclear grade, ER/PR and HER2 receptor status, and Ki-67 staining), and MRI characteristics (size, morphology, T2 signal intensity, enhancement kinetics, and ADC values) before NST were evaluated and compared between patients achieving pCR vs. non-pCR. RESULTS Among 31 patients, 17 achieved pCR (55%) and 14 non-pCR (45%). No correlation was observed between patient- or tumor pathology-derived characteristics and pCR vs. non-pCR. Among MRI-derived tumor characteristics, tumor growth orientation parallel to Cooper's ligaments (p = 0.002) and wash-out rates (p = 0.019) correlated with pCR. Pre-NST ADC values were lower in patients achieving pCR (P = 0.086). CONCLUSIONS A tumor growth pattern parallel with Cooper's ligaments and a fast wash-out rate on pre-treatment multiparametric MRI are predictive of pCR and more closely associated with pCR than ADC values.
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Affiliation(s)
- Hiroko Tsukada
- Department of Diagnostic and Interventional Radiology, Hospital of the University of Aachen, RWTH, Pauwelsstrasse 30, 52074 Aachen, Germany; Department of Surgery II, School of Medicine, Tokyo Women's Medical University, 8-1, Kawada-cho, Shinjuku-ku, 162-8666 Tokyo, Japan.
| | - Jitsuro Tsukada
- Department of Radiology, Nihon University School of Medicine, 30-1, Oyaguchi Kami-Cho, Itabashi-ku, 173-8610 Tokyo, Japan
| | - Simone Schrading
- Department of Diagnostic and Interventional Radiology, Hospital of the University of Aachen, RWTH, Pauwelsstrasse 30, 52074 Aachen, Germany
| | - Kevin Strobel
- Department of Diagnostic and Interventional Radiology, Hospital of the University of Aachen, RWTH, Pauwelsstrasse 30, 52074 Aachen, Germany
| | - Takahiro Okamoto
- Department of Surgery II, School of Medicine, Tokyo Women's Medical University, 8-1, Kawada-cho, Shinjuku-ku, 162-8666 Tokyo, Japan
| | - Christiane K Kuhl
- Department of Diagnostic and Interventional Radiology, Hospital of the University of Aachen, RWTH, Pauwelsstrasse 30, 52074 Aachen, Germany
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13
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Mazari FAK, Sharma N, Dodwell D, Horgan K. Human Epidermal Growth Factor 2-positive Breast Cancer with Mammographic Microcalcification: Relationship to Pathologic Complete Response after Neoadjuvant Chemotherapy. Radiology 2018; 288:366-374. [PMID: 29786482 DOI: 10.1148/radiol.2018170960] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/11/2024]
Abstract
Purpose To determine the relationship between the presence or absence of mammographic calcifications in human epidermal growth factor receptor 2 (HER2)-positive breast cancers and pathologic complete response (pCR) to neoadjuvant chemotherapy and to determine other tumor and clinical characteristics that may be predictive of such a response. Materials and Methods A database of all patients with HER2-positive breast cancer who underwent neoadjuvant chemotherapy between 2007 and 2015 was retrospectively reviewed. Patient demographic characteristics, mammographic appearance, molecular subtype of cancer (luminal or nonluminal), radiologic response (based on breast magnetic resonance images), surgery, and pathologic response to treatment were recorded. Inter- and subgroup comparison was performed for presence of mammographic microcalcification and cancer subtype by using Mann-Whitney and χ2 tests and logistic regression. Results A total of 111 patients with a median age of 49 years (interquartile range, 40-57 years) were evaluated. Of these, 64.9% (72 of 111) had mammographic microcalcifications, 63.1% (70 of 111) had luminal B cancer, and 36.9% (41 of 111) had nonluminal HER2-positive cancer. Radiologic response to neoadjuvant chemotherapy was observed in 70.3% (78 of 111) of patients. Surgery was performed in 97.3% (108 of 111) of patients, and 30.6% (34 of 111) of patients underwent breast conservation. pCR was observed in 33.3% (37 of 111) of patients; 16.2% (18 of 111) showed residual ductal carcinoma in situ and 50.5% (56 of 111) had residual invasive disease. The pCR rate was the same (P = .21) in patients with mammographic microcalcification (29.2% [21 of 72]) as in those without calcification (41.0% [16 of 39]). The pCR rate in patients with nonluminal HER2-positive cancers (46.3% [19 of 41]) was higher (P = .01) than in those with luminal B cancers (25.7% [18 of 70]). pCR was associated with nonluminal HER2-positive subtype (odds ratio, 5.4; 95% confidence interval: 1.8, 16.0; P = .01) and complete radiologic response (odds ratio, 20.4; 95% confidence interval: 3.3, 126.6; P = .01). Conclusion Patients with HER2-positive cancer and mammographic microcalcification can achieve pCR after neoadjuvant chemotherapy. Nonluminal HER2-positive subtype and complete radiologic response are predictors of pCR.
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Affiliation(s)
- Fayyaz A K Mazari
- From the Leeds Breast Unit (F.A.K.M., K.H.) and the Departments of Radiology (N.S.) and Oncology (D.D.), Leeds Teaching Hospitals NHS Trust, St James's University Hospital, Beckett Street, Leeds LS9 7TF, England
| | - Nisha Sharma
- From the Leeds Breast Unit (F.A.K.M., K.H.) and the Departments of Radiology (N.S.) and Oncology (D.D.), Leeds Teaching Hospitals NHS Trust, St James's University Hospital, Beckett Street, Leeds LS9 7TF, England
| | - David Dodwell
- From the Leeds Breast Unit (F.A.K.M., K.H.) and the Departments of Radiology (N.S.) and Oncology (D.D.), Leeds Teaching Hospitals NHS Trust, St James's University Hospital, Beckett Street, Leeds LS9 7TF, England
| | - Kieran Horgan
- From the Leeds Breast Unit (F.A.K.M., K.H.) and the Departments of Radiology (N.S.) and Oncology (D.D.), Leeds Teaching Hospitals NHS Trust, St James's University Hospital, Beckett Street, Leeds LS9 7TF, England
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14
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Slanetz PJ, Moy L, Baron P, diFlorio RM, Green ED, Heller SL, Holbrook AI, Lee SJ, Lewin AA, Lourenco AP, Niell B, Stuckey AR, Trikha S, Vincoff NS, Weinstein SP, Yepes MM, Newell MS. ACR Appropriateness Criteria ® Monitoring Response to Neoadjuvant Systemic Therapy for Breast Cancer. J Am Coll Radiol 2018; 14:S462-S475. [PMID: 29101985 DOI: 10.1016/j.jacr.2017.08.037] [Citation(s) in RCA: 49] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2017] [Accepted: 08/14/2017] [Indexed: 12/28/2022]
Abstract
Patients with locally advanced invasive breast cancers are often treated with neoadjuvant chemotherapy prior to definitive surgical intervention. The primary aims of this approach are to: 1) reduce tumor burden thereby permitting breast conservation rather than mastectomy; 2) promptly treat possible metastatic disease, whether or not it is detectable on preoperative staging; and 3) potentially tailor future chemotherapeutic decisions by monitoring in-vivo tumor response. Accurate radiological assessment permits optimal management and planning in this population. However, assessment of tumor size and response to treatment can vary depending on the modality used, the measurement technique (such as single longest diameter, 3-D measurements, or calculated tumor volume), and varied response of different tumor subtypes to neoadjuvant chemotherapy (such as concentric shrinkage or tumor fragmentation). As discussed in further detail, digital mammography, digital breast tomosynthesis, US and MRI represent the key modalities with potential to help guide patient management. 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)
| | - Priscilla J Slanetz
- Principal Author, Beth Israel Deaconess Medical Center, Boston, Massachusetts.
| | - Linda Moy
- Panel Vice Chair, NYU Clinical Cancer Center, New York, New York
| | - Paul Baron
- Roper St. Francis Physician Partners Breast Surgery, Charleston, South Carolina; American College of Surgeons
| | | | - Edward D Green
- The University of Mississippi Medical Center, Jackson, Mississippi
| | | | | | - Su-Ju Lee
- University of Cincinnati, Cincinnati, Ohio
| | - Alana A Lewin
- New York University School of Medicine, New York, New York
| | - Ana P Lourenco
- Alpert Medical School of Brown University and Rhode Island Hospital, Providence, Rhode Island
| | | | - Ashley R Stuckey
- Women and Infants Hospital, Providence, Rhode Island; American Congress of Obstetricians and Gynecologists
| | | | - Nina S Vincoff
- Hofstra Northwell School of Medicine, Manhasset, New York
| | - Susan P Weinstein
- Perelman School of Medicine of the University of Pennsylvania, Philadelphia, Pennsylvania
| | | | - Mary S Newell
- Panel Chair, Emory University Hospital, Atlanta, Georgia
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15
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Kang H, Hainline A, Arlinghaus LR, Elderidge S, Li X, Abramson VG, Chakravarthy AB, Abramson RG, Bingham B, Fakhoury K, Yankeelov TE. Combining multiparametric MRI with receptor information to optimize prediction of pathologic response to neoadjuvant therapy in breast cancer: preliminary results. J Med Imaging (Bellingham) 2017; 5:011015. [PMID: 29322067 DOI: 10.1117/1.jmi.5.1.011015] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2017] [Accepted: 12/05/2017] [Indexed: 01/28/2023] Open
Abstract
Pathologic complete response following neoadjuvant therapy (NAT) is used as a short-term surrogate marker of eventual outcome in patients with breast cancer. Analyzing voxel-level heterogeneity in MRI-derived parametric maps, obtained before and after the first cycle of NAT ([Formula: see text]), in conjunction with receptor status, may improve the predictive accuracy of tumor response to NAT. Toward that end, we incorporated two MRI-derived parameters, the apparent diffusion coefficient and efflux rate constant, with receptor status in a logistic ridge-regression model. The area under the curve (AUC) and Brier score of the model computed via 10-fold cross validation were 0.94 (95% CI: 0.85, 0.99) and 0.11 (95% CI: 0.06, 0.16), respectively. These two statistics strongly support the hypothesis that our proposed model outperforms the other models that we investigated (namely, models without either receptor information or voxel-level information). The contribution of the receptor information was manifested by an 8% to 15% increase in AUC and a 14% to 21% decrease in Brier score. These data indicate that combining multiparametric MRI with hormone receptor status has a high likelihood of improved prediction of pathologic response to NAT in breast cancer.
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Affiliation(s)
- Hakmook Kang
- Vanderbilt University Medical Center, Department of Biostatistics, Nashville, Tennessee, United States.,Vanderbilt University Medical Center, Center for Quantitative Sciences, Nashville, Tennessee, United States
| | - Allison Hainline
- Vanderbilt University Medical Center, Department of Biostatistics, Nashville, Tennessee, United States
| | - Lori R Arlinghaus
- Vanderbilt University Medical Center, Institute of Imaging Science, Nashville, Tennessee, United States
| | - Stephanie Elderidge
- University of Texas, Institute of Computational and Engineering Sciences, Austin, Texas, United States.,University of Texas, Department of Biomedical Engineering, Austin, Texas, United States
| | - Xia Li
- GE Global Research, Niskayuna, New York, United States
| | - Vandana G Abramson
- Vanderbilt University Medical Center, Ingram Cancer Center, Nashville, Tennessee, United States.,Vanderbilt University Medical Center, Medical Oncology, Nashville, Tennessee, United States
| | - Anuradha Bapsi Chakravarthy
- Vanderbilt University Medical Center, Ingram Cancer Center, Nashville, Tennessee, United States.,Vanderbilt University Medical Center, Department of Radiation Oncology, Nashville, Tennessee, United States
| | - Richard G Abramson
- Vanderbilt University Medical Center, Center for Quantitative Sciences, Nashville, Tennessee, United States.,Vanderbilt University Medical Center, Department of Radiology and Radiological Science, Nashville, Tennessee, United States
| | - Brian Bingham
- Vanderbilt University Medical Center, School of Medicine, Nashville, Tennessee, United States
| | - Kareem Fakhoury
- Vanderbilt University Medical Center, School of Medicine, Nashville, Tennessee, United States
| | - Thomas E Yankeelov
- University of Texas, Institute of Computational and Engineering Sciences, Austin, Texas, United States.,University of Texas, Department of Biomedical Engineering, Austin, Texas, United States
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16
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Mao X, He J, Li T, Lu Z, Sun J, Meng Y, Abliz Z, Chen J. Application of imaging mass spectrometry for the molecular diagnosis of human breast tumors. Sci Rep 2016; 6:21043. [PMID: 26868906 PMCID: PMC4751527 DOI: 10.1038/srep21043] [Citation(s) in RCA: 43] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2015] [Accepted: 01/15/2016] [Indexed: 01/02/2023] Open
Abstract
Distinguishing breast invasive ductal carcinoma (IDC) and breast ductal carcinoma in situ (DCIS) is a key step in breast surgery, especially to determine whether DCIS is associated with tumor cell micro-invasion. However, there is currently no reliable method to obtain molecular information for breast tumor analysis during surgery. Here, we present a novel air flow-assisted ionization (AFAI) mass spectrometry imaging method that can be used in ambient environments to differentiate breast cancer by analyzing lipids. In this study, we demonstrate that various subtypes and histological grades of IDC and DCIS can be discriminated using AFAI-MSI: phospholipids were more abundant in IDC than in DCIS, whereas fatty acids were more abundant in DCIS than in IDC. The classification of specimens in the subtype and grade validation sets showed 100% and 78.6% agreement with the histopathological diagnosis, respectively. Our work shows the rapid classification of breast cancer utilizing AFAI-MSI. This work suggests that this method could be developed to provide surgeons with nearly real-time information to guide surgical resections.
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Affiliation(s)
- Xinxin Mao
- Department of Pathology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China
| | - Jiuming He
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China
| | - Tiegang Li
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China
| | - Zhaohui Lu
- Department of Pathology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China
| | - Jian Sun
- Department of Pathology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China
| | - Yunxiao Meng
- Department of Pathology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China
| | - Zeper Abliz
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China
| | - Jie Chen
- Department of Pathology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China
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