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Guirguis MS, Arribas EM, Kapoor MM, Patel MM, Perez F, Nia ES, Ding Q, Moseley TW, Adrada BE. Multimodality Imaging of Benign and Malignant Diseases of the Nipple-Areolar Complex. Radiographics 2024; 44:e230113. [PMID: 38483829 DOI: 10.1148/rg.230113] [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: 03/19/2024]
Abstract
The nipple-areolar complex (NAC), a unique anatomic structure of the breast, encompasses the terminal intramammary ducts and skin appendages. Several benign and malignant diseases can arise within the NAC. As several conditions have overlapping symptoms and imaging findings, understanding the distinctive nipple anatomy, as well as the clinical and imaging features of each NAC disease process, is essential. A multimodality imaging approach is optimal in the presence or absence of clinical symptoms. The authors review the ductal anatomy and anomalies, including congenital abnormalities and nipple retraction. They then discuss the causes of nipple discharge and highlight best practices for the imaging workup of pathologic nipple discharge, a common condition that can pose a diagnostic challenge and may be the presenting symptom of breast cancer. The imaging modalities used to evaluate and differentiate benign conditions (eg, dermatologic conditions, epidermal inclusion cyst, mammary ductal ectasia, periductal mastitis, and nonpuerperal abscess), benign tumors (eg, papilloma, nipple adenoma, and syringomatous tumor of the nipple), and malignant conditions (eg, breast cancer and Paget disease of the breast) are reviewed. Breast MRI is the current preferred imaging modality used to evaluate for NAC involvement by breast cancer and select suitable candidates for nipple-sparing mastectomy. Different biopsy techniques (US -guided biopsy and stereotactic biopsy) for sampling NAC masses and calcifications are described. This multimodality imaging approach ensures an accurate diagnosis, enabling optimal clinical management and patient outcomes. ©RSNA, 2024 Test Your Knowledge questions for this article are available in the supplemental material.
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Affiliation(s)
- Mary S Guirguis
- From the Departments of Breast Imaging (M.S.G., E.M.A., M.M.K., M.M.P., F.P., E.S.N., T.W.M., B.E.A.), Pathology-Anatomical (Q.D.), and Breast Surgical Oncology (T.W.M.), The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Unit 1350, Houston, TX 77030
| | - Elsa M Arribas
- From the Departments of Breast Imaging (M.S.G., E.M.A., M.M.K., M.M.P., F.P., E.S.N., T.W.M., B.E.A.), Pathology-Anatomical (Q.D.), and Breast Surgical Oncology (T.W.M.), 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 (M.S.G., E.M.A., M.M.K., M.M.P., F.P., E.S.N., T.W.M., B.E.A.), Pathology-Anatomical (Q.D.), and Breast Surgical Oncology (T.W.M.), 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 (M.S.G., E.M.A., M.M.K., M.M.P., F.P., E.S.N., T.W.M., B.E.A.), Pathology-Anatomical (Q.D.), and Breast Surgical Oncology (T.W.M.), The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Unit 1350, Houston, TX 77030
| | - Frances Perez
- From the Departments of Breast Imaging (M.S.G., E.M.A., M.M.K., M.M.P., F.P., E.S.N., T.W.M., B.E.A.), Pathology-Anatomical (Q.D.), and Breast Surgical Oncology (T.W.M.), 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 (M.S.G., E.M.A., M.M.K., M.M.P., F.P., E.S.N., T.W.M., B.E.A.), Pathology-Anatomical (Q.D.), and Breast Surgical Oncology (T.W.M.), The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Unit 1350, Houston, TX 77030
| | - Qingqing Ding
- From the Departments of Breast Imaging (M.S.G., E.M.A., M.M.K., M.M.P., F.P., E.S.N., T.W.M., B.E.A.), Pathology-Anatomical (Q.D.), and Breast Surgical Oncology (T.W.M.), 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 (M.S.G., E.M.A., M.M.K., M.M.P., F.P., E.S.N., T.W.M., B.E.A.), Pathology-Anatomical (Q.D.), and Breast Surgical Oncology (T.W.M.), The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Unit 1350, Houston, TX 77030
| | - Beatriz E Adrada
- From the Departments of Breast Imaging (M.S.G., E.M.A., M.M.K., M.M.P., F.P., E.S.N., T.W.M., B.E.A.), Pathology-Anatomical (Q.D.), and Breast Surgical Oncology (T.W.M.), The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Unit 1350, Houston, TX 77030
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Musall BC, Rauch DE, Mohamed RMM, Panthi B, Boge M, Candelaria RP, Chen H, Guirguis MS, Hunt KK, Huo L, Hwang KP, Korkut A, Litton JK, Moseley TW, Pashapoor S, Patel MM, Reed BJ, Scoggins ME, Son JB, Tripathy D, Valero V, Wei P, White JB, Whitman GJ, Xu Z, Yang WT, Yam C, Adrada BE, Ma J. Diffusion Tensor Imaging for Characterizing Changes in Triple-Negative Breast Cancer During Neoadjuvant Systemic Therapy. J Magn Reson Imaging 2024. [PMID: 38294179 DOI: 10.1002/jmri.29267] [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: 07/31/2023] [Revised: 01/18/2024] [Accepted: 01/18/2024] [Indexed: 02/01/2024] Open
Abstract
BACKGROUND Assessment of treatment response in triple-negative breast cancer (TNBC) may guide individualized care for improved patient outcomes. Diffusion tensor imaging (DTI) measures tissue anisotropy and could be useful for characterizing changes in the tumors and adjacent fibroglandular tissue (FGT) of TNBC patients undergoing neoadjuvant systemic treatment (NAST). PURPOSE To evaluate the potential of DTI parameters for prediction of treatment response in TNBC patients undergoing NAST. STUDY TYPE Prospective. POPULATION Eighty-six women (average age: 51 ± 11 years) with biopsy-proven clinical stage I-III TNBC who underwent NAST followed by definitive surgery. 47% of patients (40/86) had pathologic complete response (pCR). FIELD STRENGTH/SEQUENCE 3.0 T/reduced field of view single-shot echo-planar DTI sequence. ASSESSMENT Three MRI scans were acquired longitudinally (pre-treatment, after 2 cycles of NAST, and after 4 cycles of NAST). Eleven histogram features were extracted from DTI parameter maps of tumors, a peritumoral region (PTR), and FGT in the ipsilateral breast. DTI parameters included apparent diffusion coefficients and relative diffusion anisotropies. pCR status was determined at surgery. STATISTICAL TESTS Longitudinal changes of DTI features were tested for discrimination of pCR using Mann-Whitney U test and area under the receiver operating characteristic curve (AUC). A P value <0.05 was considered statistically significant. RESULTS 47% of patients (40/86) had pCR. DTI parameters assessed after 2 and 4 cycles of NAST were significantly different between pCR and non-pCR patients when compared between tumors, PTRs, and FGTs. The median surface/average anisotropy of the PTR, measured after 2 and 4 cycles of NAST, increased in pCR patients and decreased in non-pCR patients (AUC: 0.78; 0.027 ± 0.043 vs. -0.017 ± 0.042 mm2 /s). DATA CONCLUSION Quantitative DTI features from breast tumors and the peritumoral tissue may be useful for predicting 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
| | - David E Rauch
- Department of Imaging Physics, 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
| | - Bikash Panthi
- Department of Imaging Physics, 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
| | - Rosalind P Candelaria
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Huiqin Chen
- Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Mary S Guirguis
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Kelly K Hunt
- Department of Breast Surgical Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Lei Huo
- Department of Pathology, 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
| | - Anil Korkut
- Department of Breast 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
| | - Tanya W Moseley
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
- Department of Breast Surgical Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Sanaz Pashapoor
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Miral M Patel
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Brandy J Reed
- Department of Imaging Physics, 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
| | - Jong Bum Son
- Department of Imaging Physics, 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
| | - Vicente Valero
- 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
| | - Jason B White
- Department of Breast Medical Oncology, 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
| | - Zhan Xu
- Department of Imaging Physics, 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
| | - Clinton Yam
- Department of Breast Medical Oncology, 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
| | - Jingfei Ma
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
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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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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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Engel AJ, Shin K, Adrada BE, Moseley TW, Krishnamurthy S, Whitman GJ. Review of the Sonographic Features of Interpectoral (Rotter) Lymph Nodes in Breast Cancer Staging. Ultrasound Q 2023; 39:69-73. [PMID: 35439235 DOI: 10.1097/ruq.0000000000000601] [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: 11/26/2022]
Abstract
ABSTRACT This article reviews the ultrasound evaluation and staging of breast cancer with respect to the involvement of interpectoral (Rotter) lymph nodes. The primary objective is to demonstrate and assess the characteristic sonographic findings of interpectoral (Rotter) lymph nodes to help provide accurate nodal staging information. We aim to provide a comprehensive review and serve as an imaging guide for the identification and evaluation of Rotter lymph nodes. The detection of abnormalities and pathologic features of metastatic axillary nodal disease in the interpectoral region is reviewed, and the impact on clinical management and treatment is discussed. In the radiology literature, there is no comprehensive review of the sonographic appearance and evaluation of Rotter lymph nodes.
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Affiliation(s)
| | - Kyungmin Shin
- Division of Diagnostic Imaging, Department of Breast Imaging, University of Texas MD Anderson Cancer Center, Houston, TX
| | - Beatriz E Adrada
- Division of Diagnostic Imaging, Department of Breast Imaging, University of Texas MD Anderson Cancer Center, Houston, TX
| | | | - Savitri Krishnamurthy
- Division of Pathology and Laboratory Medicine, Department of Pathology, University of Texas MD Anderson Cancer Center, Houston, TX
| | - Gary J Whitman
- Division of Diagnostic Imaging, Department of Breast Imaging, University of Texas MD Anderson Cancer Center, Houston, TX
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Chung HL, Joiner J, Ferreira Dalla Pria HR, Jean S, Vishwanath V, De Jesus C, Elhatw A, Guirguis MS, Patel MM, Moseley TW. Breast Imaging Considerations in Symptomatic Young, Pregnant, and Lactating Women. Curr Breast Cancer Rep 2023. [DOI: 10.1007/s12609-023-00485-3] [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: 04/08/2023]
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Jean S, Vishwanath V, Chung HL, Moseley TW. Identifying and Reducing Barriers to Breast Imaging. Curr Breast Cancer Rep 2023; 15:114-118. [PMID: 37293273 PMCID: PMC10074341 DOI: 10.1007/s12609-023-00480-8] [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] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/21/2023] [Indexed: 04/08/2023]
Abstract
Purpose of Review The purpose of this review is to discuss disparities in breast health care access and outcomes related to race, gender, cultural diversity, sexual orientation, socioeconomic status, geographic location, and disability. The authors recognize the complexity of eliminating inequalities in health care but are optimistic that all patients will one day have equal access to care through dialogue, acknowledgment, recognition, and action. Recent Findings After lung cancer, breast cancer is the second leading cause of death among American women. Mammography as a preventative screening tool has resulted in significant reductions in breast cancer mortality. Despite existing breast cancer recommendations, it has been projected that 43,250 women will die from breast cancer in 2022. Summary Disparities in healthcare outcomes exist for many reasons including inequalities based on race, gender, cultural diversity, religion, sexual orientation, and socioeconomic status. Disparities, no matter how large or complex, are not insurmountable.
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Affiliation(s)
- Shanen Jean
- Arizona College of Osteopathic Medicine, Midwestern University, Glendale, AZ USA
| | - Varnita Vishwanath
- Arizona College of Osteopathic Medicine, Midwestern University, Glendale, AZ USA
| | - Hannah L. Chung
- Division of Diagnostic Imaging, University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Box 1350, Houston, TX 77030 USA
| | - Tanya W. Moseley
- Division of Diagnostic Imaging, University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Box 1350, Houston, TX 77030 USA
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Elhatw A, Chung HL, Kamal RM, De Jesus C, Jean S, Vishwanath V, Ferreira Dalla Pria HR, Patel MM, Guirguis MS, Moseley TW. Advanced Breast Imaging Modalities — DBT, CEM, MBI, PEM, MRI, AI. Curr Breast Cancer Rep 2023. [DOI: 10.1007/s12609-023-00483-5] [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: 04/07/2023]
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De Jesus C, Moseley TW, Diaz V, Vishwanath V, Jean S, Elhatw A, Pria HRFD, Chung HL, Guirguis MS, Patel MM. The Benefits of Screening Mammography. Curr Breast Cancer Rep 2023. [DOI: 10.1007/s12609-023-00479-1] [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] [Indexed: 04/05/2023]
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De Jesus C, Moseley TW, Diaz V, Vishwanath V, Jean S, Elhatw A, Ferreira Dalla Pria HR, Chung HL, Guirguis MS, Patel MM. Supplemental Screening for Breast Cancer. Curr Breast Cancer Rep 2023. [DOI: 10.1007/s12609-023-00481-7] [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: 04/05/2023]
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Weaver OO, Yang WT, Scoggins ME, Adrada BE, Arribas E, Moseley TW, Esquivel J, Melgar Y, Kornecki A. Challenging Contrast-Enhanced Mammography-Guided Biopsies: Practical Approach Using Real-Time Multimodality Imaging and a Proposed Procedural Algorithm. AJR Am J Roentgenol 2023; 220:512-523. [PMID: 36321982 DOI: 10.2214/ajr.22.28572] [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: 11/05/2022]
Abstract
Contrast-enhanced mammography (CEM) is an emerging functional breast imaging technique that entails the acquisition of dual-energy digital mammographic images after IV administration of iodine-based contrast material. CEM-guided biopsy technology was introduced in 2019 and approved by the U.S. FDA in 2020. This technology's availability enables direct sampling of suspicious enhancement seen only on or predominantly on recombined CEM images and addresses a major obstacle to the clinical implementation of CEM technology. The literature describing clinical indications and procedural techniques of CEM-guided biopsy is scarce. This article describes our initial experience in performing challenging CEM-guided biopsies and proposes a step-by-step procedural algorithm designed to proactively address anticipated technical difficulties and thereby increase the likelihood of achieving successful targeting.
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Affiliation(s)
- Olena O Weaver
- Department of Breast Imaging, Unit 1350, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX 77030
| | - Wei T Yang
- Department of Breast Imaging, Unit 1350, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX 77030
| | - Marion E Scoggins
- Department of Breast Imaging, Unit 1350, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX 77030
| | - Beatriz E Adrada
- Department of Breast Imaging, Unit 1350, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX 77030
| | - Elsa Arribas
- Department of Breast Imaging, Unit 1350, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX 77030
| | - Tanya W Moseley
- Department of Breast Imaging, Unit 1350, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX 77030
- Department of Breast Surgical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Joanna Esquivel
- Department of Breast Imaging, Unit 1350, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX 77030
| | - Yamile Melgar
- Department of Breast Imaging, Unit 1350, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX 77030
| | - Anat Kornecki
- Department of Medical Imaging, Schulich School of Medicine and Dentistry, The University of Western Ontario, London, ON, Canada
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12
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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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13
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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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14
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Liang DH, Black D, Yi M, Luo CK, Singh P, Sahin A, Scoggins ME, Moseley TW, Hunt KK. Correction to: Clinical Outcomes Using Magnetic Seeds as a Non-wire, Non-radioactive Alternative for Localization of Non-palpable Breast Lesions. Ann Surg Oncol 2022; 29:10.1245/s10434-022-11652-8. [PMID: 35298763 DOI: 10.1245/s10434-022-11652-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Affiliation(s)
- Diana H Liang
- Department of Breast Surgical Oncology, MD Anderson Cancer Center, Houston, TX, USA
| | - Dalliah Black
- Department of Breast Surgical Oncology, MD Anderson Cancer Center, Houston, TX, USA
| | - Min Yi
- Department of Breast Surgical Oncology, MD Anderson Cancer Center, Houston, TX, USA
| | - Catherine K Luo
- Department of Breast Surgical Oncology, MD Anderson Cancer Center, Houston, TX, USA
| | - Puneet Singh
- Department of Breast Surgical Oncology, MD Anderson Cancer Center, Houston, TX, USA
| | - Aysegul Sahin
- Department of Pathology, MD Anderson Cancer Center, Houston, TX, USA
| | - Marion E Scoggins
- Department of Breast Imaging, MD Anderson Cancer Center, Houston, TX, USA
| | - Tanya W Moseley
- Department of Breast Surgical Oncology, MD Anderson Cancer Center, Houston, TX, USA
- Department of Breast Imaging, MD Anderson Cancer Center, Houston, TX, USA
| | - Kelly K Hunt
- Department of Breast Surgical Oncology, MD Anderson Cancer Center, Houston, TX, USA.
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15
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Liang DH, Black D, Yi M, Luo CK, Singh P, Sahin A, Scoggins ME, Moseley TW, Hunt KK. Clinical Outcomes Using Magnetic Seeds as a Non-wire, Non-radioactive Alternative for Localization of Non-palpable Breast Lesions. Ann Surg Oncol 2022; 29:3822-3828. [PMID: 35233742 DOI: 10.1245/s10434-022-11443-1] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2021] [Accepted: 01/25/2022] [Indexed: 12/19/2022]
Abstract
BACKGROUND Nonpalpable breast lesions require precise preoperative localization to facilitate negative margins with breast-conserving therapy. The traditional use of wires has several challenges including patient discomfort, wire migration, and coordination of schedules between radiology and the operating room. Radioactive seed localization overcomes some of these challenges, but radiation safety requirements have limited adoption of this technology. The authors examined their institutional experience with Magseed as an alternative technology for localization and compared outcomes with those of wire and radioactive seed localization. METHODS An institutional review board (IRB)-approved retrospective study was performed to evaluate patients who underwent excisional biopsy or segmental mastectomy after wire-guided localization (WGL), radioactive seed localization (RSL), or Magseed localization (ML). The clinical and pathologic factors of the three groups were assessed with a negative margin rate as the primary outcome measure. RESULTS Of the 1835 patients in the study, 825 underwent WGL, 449 underwent RSL, and 561 underwent ML. For the patients with either multiple lesions or a large lesion that required bracketing, multiple localization devices were placed in 31% of the WGL patients, 28% of the RSL patients, and 23% of the ML patients (p = 0.006). Negative margins were achieved in 91% of the WGL patients, 89% of the RSL patients, and 89% of the ML patients (p = 0.4). CONCLUSION Localization of non-palpable breast lesions using Magseed is a safe and effective alternative to WGL and RSL that overcomes radiation safety limitations and increases radiology and surgery scheduling efficiency.
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Affiliation(s)
- Diana H Liang
- Department of Breast Surgical Oncology, MD Anderson Cancer Center, 1400 Pressler Street, FCT 7.5010, Houston, TX, USA
| | - Dalliah Black
- Department of Breast Surgical Oncology, MD Anderson Cancer Center, 1400 Pressler Street, FCT 7.5010, Houston, TX, USA
| | - Min Yi
- Department of Breast Surgical Oncology, MD Anderson Cancer Center, 1400 Pressler Street, FCT 7.5010, Houston, TX, USA
| | - Catherine K Luo
- Department of Breast Surgical Oncology, MD Anderson Cancer Center, 1400 Pressler Street, FCT 7.5010, Houston, TX, USA
| | - Puneet Singh
- Department of Breast Surgical Oncology, MD Anderson Cancer Center, 1400 Pressler Street, FCT 7.5010, Houston, TX, USA
| | - Aysegul Sahin
- Department of Pathology, MD Anderson Cancer Center, Houston, TX, USA
| | - Marion E Scoggins
- Department of Breast Imaging, MD Anderson Cancer Center, Houston, TX, USA
| | - Tanya W Moseley
- Department of Breast Surgical Oncology, MD Anderson Cancer Center, 1400 Pressler Street, FCT 7.5010, Houston, TX, USA.,Department of Breast Imaging, MD Anderson Cancer Center, Houston, TX, USA
| | - Kelly K Hunt
- Department of Breast Surgical Oncology, MD Anderson Cancer Center, 1400 Pressler Street, FCT 7.5010, Houston, TX, USA.
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16
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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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17
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Patel MM, Moseley TW, Nia ES, Perez F, Kapoor MM, Whitman GJ. Team Science: A Practical Approach to Starting Collaborative Projects. J Breast Imaging 2021; 3:721-726. [PMID: 34805982 DOI: 10.1093/jbi/wbab034] [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: 01/27/2021] [Indexed: 11/14/2022]
Abstract
A collaborative approach to treating patients is well taught in medical training. However, collaboration and team building in clinical and laboratory research may have been given less emphasis. More scientific discoveries are now being made with multidisciplinary teams, requiring a thoughtful approach in order to achieve research goals while mitigating potential conflicts. Specific steps for a successful team science project include building the team, assigning roles and responsibilities, allocating rules, and discussing authorship guidelines. Building a team involves bringing individuals together and developing a common research goal while establishing psychological safety for all members of the team. Clear assignment of roles and responsibilities avoids confusion and allows each member's contributions to be acknowledged. Allocating rules involves discussing how decisions in the team will be made, how data and knowledge sharing will occur, and how potential conflicts will be resolved. Discussing authorship at the start of the project ensures that the entire team knows what work must be completed for authorship to be obtained.
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Affiliation(s)
- Miral M Patel
- The University of Texas MD Anderson Cancer Center, Department of Breast Imaging, Houston, TX, USA
| | - Tanya W Moseley
- 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 Breast Surgical Oncology, Houston, TX, USA
| | - Emily S Nia
- The University of Texas MD Anderson Cancer Center, Department of Breast Imaging, Houston, TX, USA
| | - Frances Perez
- The University of Texas MD Anderson Cancer Center, Department of Breast Imaging, Houston, TX, USA
| | - Megha M Kapoor
- The University of Texas MD Anderson Cancer Center, Department of Breast Imaging, Houston, TX, USA
| | - Gary J Whitman
- The University of Texas MD Anderson Cancer Center, Department of Breast Imaging, Houston, TX, USA
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18
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Whitman GJ, Moseley TW. Stand-Alone Machine Learning: More Work Is Needed. Radiology 2021; 302:105-106. [PMID: 34665035 DOI: 10.1148/radiol.2021211885] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Affiliation(s)
- Gary J Whitman
- From the Department of Breast Imaging, University of Texas MD Anderson Cancer Center, Unit 1350, 1155 Pressler St, Houston, TX 77030-3721
| | - Tanya W Moseley
- From the Department of Breast Imaging, University of Texas MD Anderson Cancer Center, Unit 1350, 1155 Pressler St, Houston, TX 77030-3721
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19
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Kapoor MM, Moseley TW. Fluid-filled breast: A unique clinical presentation of invasive micropapillary carcinoma. Radiol Case Rep 2021; 16:2731-2735. [PMID: 34336079 PMCID: PMC8313496 DOI: 10.1016/j.radcr.2021.06.034] [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] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2021] [Accepted: 06/12/2021] [Indexed: 11/15/2022] Open
Abstract
Invasive micropapillary carcinoma is a rare variant of invasive ductal carcinoma of the breast. This variant has been described as clinically aggressive due to its high frequency of lymphovascular invasion, axillary nodal metastases, and a greater degree of loco-regional recurrence. Invasive micropapillary carcinoma can have a variety of imaging presentations, typically presenting as an irregular mass. This case report describes a unique presentation of invasive micropapillary carcinoma and illustrates the propensity of invasive micropapillary carcinoma to secrete fluid and have a lack of regional lymphadenopathy. The challenges of the accompanying diagnostic imaging-work up are discussed.
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Affiliation(s)
- Megha M Kapoor
- Department of Breast Imaging, University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Tanya W Moseley
- Department of Breast Imaging, University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.,Department of Breast Surgical Oncology, University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
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20
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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] [What about the content of this article? (0)] [Affiliation(s)] [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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21
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Shu H, Chiang T, Wei P, Do KA, Lesslie MD, Cohen EO, Srinivasan A, Moseley TW, Chang Sen LQ, Leung JWT, Dennison JB, Hanash SM, Weaver OO. A Deep Learning Approach to Re-create Raw Full-Field Digital Mammograms for Breast Density and Texture Analysis. Radiol Artif Intell 2021; 3:e200097. [PMID: 34350403 DOI: 10.1148/ryai.2021200097] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2020] [Revised: 03/18/2021] [Accepted: 03/30/2021] [Indexed: 11/11/2022]
Abstract
Purpose To develop a computational approach to re-create rarely stored for-processing (raw) digital mammograms from routinely stored for-presentation (processed) mammograms. Materials and Methods In this retrospective study, pairs of raw and processed mammograms collected in 884 women (mean age, 57 years ± 10 [standard deviation]; 3713 mammograms) from October 5, 2017, to August 1, 2018, were examined. Mammograms were split 3088 for training and 625 for testing. A deep learning approach based on a U-Net convolutional network and kernel regression was developed to estimate the raw images. The estimated raw images were compared with the originals by four image error and similarity metrics, breast density calculations, and 29 widely used texture features. Results In the testing dataset, the estimated raw images had small normalized mean absolute error (0.022 ± 0.015), scaled mean absolute error (0.134 ± 0.078) and mean absolute percentage error (0.115 ± 0.059), and a high structural similarity index (0.986 ± 0.007) for the breast portion compared with the original raw images. The estimated and original raw images had a strong correlation in breast density percentage (Pearson r = 0.946) and a strong agreement in breast density grade (Cohen κ = 0.875). The estimated images had satisfactory correlations with the originals in 23 texture features (Pearson r ≥ 0.503 or Spearman ρ ≥ 0.705) and were well complemented by processed images for the other six features. Conclusion This deep learning approach performed well in re-creating raw mammograms with strong agreement in four image evaluation metrics, breast density, and the majority of 29 widely used texture features.Keywords: Mammography, Breast, Supervised Learning, Convolutional Neural Network (CNN), Deep learning algorithms, Machine Learning AlgorithmsSee also the commentary by Chan in this issue.Supplemental material is available for this article.©RSNA, 2021.
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Affiliation(s)
- Hai Shu
- Departments of Biostatistics (H.S., P.W., K.A.D.), Diagnostic Radiology (T.C., M.D.L., E.O.C., A.S., T.W.M., L.Q.C.S., J.W.T.L., O.O.W.), and Clinical Cancer Prevention (J.B.D., S.M.H.), The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX 77030; and Department of Biostatistics, School of Global Public Health, New York University, New York, NY (H.S.)
| | - Tingyu Chiang
- Departments of Biostatistics (H.S., P.W., K.A.D.), Diagnostic Radiology (T.C., M.D.L., E.O.C., A.S., T.W.M., L.Q.C.S., J.W.T.L., O.O.W.), and Clinical Cancer Prevention (J.B.D., S.M.H.), The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX 77030; and Department of Biostatistics, School of Global Public Health, New York University, New York, NY (H.S.)
| | - Peng Wei
- Departments of Biostatistics (H.S., P.W., K.A.D.), Diagnostic Radiology (T.C., M.D.L., E.O.C., A.S., T.W.M., L.Q.C.S., J.W.T.L., O.O.W.), and Clinical Cancer Prevention (J.B.D., S.M.H.), The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX 77030; and Department of Biostatistics, School of Global Public Health, New York University, New York, NY (H.S.)
| | - Kim-Anh Do
- Departments of Biostatistics (H.S., P.W., K.A.D.), Diagnostic Radiology (T.C., M.D.L., E.O.C., A.S., T.W.M., L.Q.C.S., J.W.T.L., O.O.W.), and Clinical Cancer Prevention (J.B.D., S.M.H.), The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX 77030; and Department of Biostatistics, School of Global Public Health, New York University, New York, NY (H.S.)
| | - Michele D Lesslie
- Departments of Biostatistics (H.S., P.W., K.A.D.), Diagnostic Radiology (T.C., M.D.L., E.O.C., A.S., T.W.M., L.Q.C.S., J.W.T.L., O.O.W.), and Clinical Cancer Prevention (J.B.D., S.M.H.), The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX 77030; and Department of Biostatistics, School of Global Public Health, New York University, New York, NY (H.S.)
| | - Ethan O Cohen
- Departments of Biostatistics (H.S., P.W., K.A.D.), Diagnostic Radiology (T.C., M.D.L., E.O.C., A.S., T.W.M., L.Q.C.S., J.W.T.L., O.O.W.), and Clinical Cancer Prevention (J.B.D., S.M.H.), The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX 77030; and Department of Biostatistics, School of Global Public Health, New York University, New York, NY (H.S.)
| | - Ashmitha Srinivasan
- Departments of Biostatistics (H.S., P.W., K.A.D.), Diagnostic Radiology (T.C., M.D.L., E.O.C., A.S., T.W.M., L.Q.C.S., J.W.T.L., O.O.W.), and Clinical Cancer Prevention (J.B.D., S.M.H.), The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX 77030; and Department of Biostatistics, School of Global Public Health, New York University, New York, NY (H.S.)
| | - Tanya W Moseley
- Departments of Biostatistics (H.S., P.W., K.A.D.), Diagnostic Radiology (T.C., M.D.L., E.O.C., A.S., T.W.M., L.Q.C.S., J.W.T.L., O.O.W.), and Clinical Cancer Prevention (J.B.D., S.M.H.), The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX 77030; and Department of Biostatistics, School of Global Public Health, New York University, New York, NY (H.S.)
| | - Lauren Q Chang Sen
- Departments of Biostatistics (H.S., P.W., K.A.D.), Diagnostic Radiology (T.C., M.D.L., E.O.C., A.S., T.W.M., L.Q.C.S., J.W.T.L., O.O.W.), and Clinical Cancer Prevention (J.B.D., S.M.H.), The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX 77030; and Department of Biostatistics, School of Global Public Health, New York University, New York, NY (H.S.)
| | - Jessica W T Leung
- Departments of Biostatistics (H.S., P.W., K.A.D.), Diagnostic Radiology (T.C., M.D.L., E.O.C., A.S., T.W.M., L.Q.C.S., J.W.T.L., O.O.W.), and Clinical Cancer Prevention (J.B.D., S.M.H.), The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX 77030; and Department of Biostatistics, School of Global Public Health, New York University, New York, NY (H.S.)
| | - Jennifer B Dennison
- Departments of Biostatistics (H.S., P.W., K.A.D.), Diagnostic Radiology (T.C., M.D.L., E.O.C., A.S., T.W.M., L.Q.C.S., J.W.T.L., O.O.W.), and Clinical Cancer Prevention (J.B.D., S.M.H.), The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX 77030; and Department of Biostatistics, School of Global Public Health, New York University, New York, NY (H.S.)
| | - Sam M Hanash
- Departments of Biostatistics (H.S., P.W., K.A.D.), Diagnostic Radiology (T.C., M.D.L., E.O.C., A.S., T.W.M., L.Q.C.S., J.W.T.L., O.O.W.), and Clinical Cancer Prevention (J.B.D., S.M.H.), The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX 77030; and Department of Biostatistics, School of Global Public Health, New York University, New York, NY (H.S.)
| | - Olena O Weaver
- Departments of Biostatistics (H.S., P.W., K.A.D.), Diagnostic Radiology (T.C., M.D.L., E.O.C., A.S., T.W.M., L.Q.C.S., J.W.T.L., O.O.W.), and Clinical Cancer Prevention (J.B.D., S.M.H.), The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX 77030; and Department of Biostatistics, School of Global Public Health, New York University, New York, NY (H.S.)
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22
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Moseley TW, Conners AL, He H, Barth JE, Lightfoote JB, Parikh JR, Whitman GJ. Mitigating the Transmission of COVID-19 with the Appropriate Usage of Personal Protective Protocols and Equipment in Breast Imaging and Intervention. J Breast Imaging 2021; 3:215-220. [PMID: 33778489 PMCID: PMC7928886 DOI: 10.1093/jbi/wbab007] [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] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2020] [Indexed: 01/13/2023]
Abstract
The integration of personal protective equipment (PPE) and procedures into breast imaging and intervention practices will mitigate the risk of transmission of COVID-19 during the pandemic. Although supply chain shortages have improved, understanding the proper use of PPE and protocols to mitigate overconsumption are important to ensure efficacious utilization of PPE. Protocols and best practices are reviewed, and guidelines and resource materials are referenced in order to support breast imaging healthcare professionals.
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Affiliation(s)
- Tanya W Moseley
- The University of Texas MD Anderson Cancer Center, Department of Breast Imaging, Houston, TX, USA
| | - Amy L Conners
- Mayo Clinic, Department of Radiology, Rochester, MN, USA
| | - Hongying He
- The University of Texas Health Science Center at Houston, Department of Diagnostic and Interventional Imaging, Houston, TX, USA
| | - Jean E Barth
- Mayo Clinic, Department of Infection Prevention and Control, Rochester, MN, USA
| | | | - Jay R Parikh
- The University of Texas MD Anderson Cancer Center, Department of Breast Imaging, Houston, TX, USA
| | - Gary J Whitman
- The University of Texas MD Anderson Cancer Center, Department of Breast Imaging, Houston, TX, USA
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23
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Elshafeey N, Adrada BE, Candelaria RP, Abdelhafez AH, Musall BC, Sun J, Boge M, Mohamed RM, Mahmoud HS, Son JB, Kotrosou A, Zhang S, Leung J, Lane D, Scoggins M, Spak D, Arribas E, Santiago L, Whitman GJ, Le-Petross HT, Moseley TW, White JB, Ravenberg E, Hwang KP, Wei P, Litton JK, Huo L, Tripathy D, Valero V, Thompson AM, Moulder S, Yang WT, Pagel MD, Ma J, Rauch GM. Abstract PD6-06: Radiomic phenotypes from dynamic contrast-enhanced MRI (DCE-MRI) parametric maps for early prediction of response to neoadjuvant systemic therapy (NAST) in triple negative breast cancer (TNBC) patients. Cancer Res 2021. [DOI: 10.1158/1538-7445.sabcs20-pd6-06] [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] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Abstract
Background and Purpose:Early and accurate assessment ofbreast cancer response to NAST is important for patient management. In this study, we investigated the value of radiomic phenotypes derived from semi-quantitative and quantitative DCE-MRI parametric maps for early prediction of NASTresponse in TNBC patients. MATERIALS AND METHODS:This IRB approved study included 74 patients with stage I-III TNBC who were enrolled in the prospective ARTEMIS trial (NCT02276443). Pathologic complete response (pCR) and non-pCR were assessed by surgical histopathology after NAST (pCR=34; non-pCR=40).MRI scans were obtained at 3 time points during the NAST treatment with every 2-week anthracycline-based chemotherapy (AC): at baseline (BSL=74), post-2 cycles of AC (C2= 27) and post-4 cycles of AC (C4= 27). Patients went on to receive taxane-based chemotherapy prior to surgery. Tumor regions of interest (ROIs) were segmented by a breast radiologist at the early-phase subtractions of DCE-MRI scans using in-house developed software, followed by co-registration of the ROIs with quantitative (Ktrans, Veand Kep), and semi-quantitative DCE parametric maps (Maximum Slope Increase (MSI), Positive Enhancement Integral (PEI) and Peak Signal Enhancement Ratio (SER)).A total of 93 first order radiomic features were extracted from the tumor ROIs of each time point semi-quantitative DCE parametric map, while a total of 390 extracted radiomic features (first order-histogram features and second order grey-level-co-occurrence matrix) were extracted from each quantitative DCE parametric map using an in-house developed Matlab software.Radiomic features at each time point and changes between the 3 time points were compared between pCR and non-pCR using Wilcoxon Rank Sum test and Fisher’s exact test. Area under the receiver operating characteristics curve (AUC) was used to determine which features predicted pCR.Logistic regression was performed for feature selection, and used to build the radiomic phenotype model. The model performance was assessed by leave-one-out cross validation and 3-fold cross validation. RESULTS:Thirty-three radiomic features from PEI map were significantly different between pCR and non-pCR. The PEI most significant features were changesbetween BSL and C4 in skewness, mean and median (AUC=0.87, 0.85 and 0.87, p=<0.001, 0.001 and 0.002 respectively). Additionally, 31 MSI features were significantly different between pCR and non-pCR. The top 2 features were the interscan-change in skewness between BSL and C2 (AUC=0.80, P=0.007) and C4 standard deviation (AUC=0.80, P=0.006). Four BSL Veradiomic features were statistically significant between pCR and non-pCR with the best being range of difference variance (AUC=0.64, P=0.03). One BSL Kepfeature (Angular-Variance of Information measure of correlation-2) was able to differentiate pCR from non-pCR (AUC=0.64, P=0.04). Five C4-Ktrans features were able to differentiate pCR and non-pCR, with the most significant being mean value (AUC=0.86, P=0.001). BSL-Kepradiomic model built from 24 features (AUC=0.80, p=0.003) and combined (Ktrans, Veand Kep)C2-radiomic model consisting of 20 features (AUC=0.97, p=0.01) showed the best performance for prediction of pCR. CONCLUSIONS:Radiomic phenotypes form DCE-MRI parametric maps were useful for differentiation between pCR and non-pCR and showed promise as noninvasive imaging biomarkers for early prediction of NAST response in TNBC. Potentially, DCE-MRI radiomic features may be used for development of diagnostic predictive model for early noninvasive assessment of NAST treatment response in TNBC patients.
Citation Format: Nabil Elshafeey, Beatriz E Adrada, Rosalind P Candelaria, Abeer H Abdelhafez, Benjamin C Musall, Jia Sun, Medine Boge, Rania M.M Mohamed, Hagar S Mahmoud, Jong Bum Son, Aikaterini Kotrosou, Shu Zhang, Jessica Leung, Deanna Lane, Marion Scoggins, David Spak, Elsa Arribas, Lumarie Santiago, Gary J. Whitman, Huong T Le-Petross, Tanya W Moseley, Jason B White, Elizabeth Ravenberg, Ken-Pin Hwang, Peng Wei, Jennifer K Litton, Lei Huo, Debu Tripathy, Vicente Valero, Alastair M Thompson, Stacy Moulder, Wei T Yang, Mark D Pagel, Jingfei Ma, Gaiane M Rauch. Radiomic phenotypes from dynamic contrast-enhanced MRI (DCE-MRI) parametric maps for early prediction of response to neoadjuvant systemic therapy (NAST) in triple negative breast cancer (TNBC) patients [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PD6-06.
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Affiliation(s)
- Nabil Elshafeey
- 1Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Beatriz E Adrada
- 1Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX
| | | | - Abeer H Abdelhafez
- 2Abdominal Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Benjamin C Musall
- 3Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, United States, Houston, TX
| | - Jia Sun
- 4Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX, United States, Houston, TX
| | - Medine Boge
- 1Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Rania M.M Mohamed
- 1Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Hagar S Mahmoud
- 1Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Jong Bum Son
- 5Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Aikaterini Kotrosou
- 6Cancer Systems Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Shu Zhang
- 6Cancer Systems Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Jessica Leung
- 1Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Deanna Lane
- 1Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Marion Scoggins
- 1Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - David Spak
- 1Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Elsa Arribas
- 1Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Lumarie Santiago
- 1Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Gary J. Whitman
- 1Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Huong T Le-Petross
- 1Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Tanya W Moseley
- 1Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Jason B White
- 7Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Elizabeth Ravenberg
- 7Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Ken-Pin Hwang
- 5Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Peng Wei
- 5Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Jennifer K Litton
- 7Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Lei Huo
- 8Department of Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Debu Tripathy
- 7Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Vicente Valero
- 7Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX
| | | | - Stacy Moulder
- 7Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Wei T Yang
- 1Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Mark D Pagel
- 10Imaging Physics and Cancer Systems Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Jingfei Ma
- 5Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Gaiane M Rauch
- 11Breast and Abdominal Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX
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Zhang S, Rauch GM, Adrada BE, Boge M, Mohamed RMM, Abdelhafez AH, Son JB, Sun J, Elshafeey NA, White JB, Lane DL, Leung JWT, Scoggins ME, Spak DA, Arribas E, Ravenberg E, Santiago L, Moseley TW, Whitman GJ, Le-Petross H, Musall BC, Miyoshi M, Wang X, Willis B, Hash S, Kotrotsou A, Wei P, Hwang KP, Thompson A, Moulder SL, Candelaria RP, Yang W, Ma J, Pagel MD. Abstract PS3-08: Assessment of early response to neoadjuvant systemic therapy (NAST) of triple-negative breast cancer (TNBC) using chemical exchange saturation transfer (CEST) MRI: A pilot study. Cancer Res 2021. [DOI: 10.1158/1538-7445.sabcs20-ps3-08] [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 CEST MRI permits quantitation of macromolecules such as amide proteins that are of interest in cancer metabolism. However, optimal CEST acquisition and analysis methods remain undetermined. In this study, we investigated CEST MRI as an imaging biomarker for early treatment response in 51 TNBC patients receiving NAST and compared the performance with two different CEST saturation power levels and two analysis methods.
Methods A total of 51 stage I-III TNBC patients enrolled in the prospective ARTEMIS trial (NCT02276443) had CEST imaging performed on a 3T MRI scanner at baseline before NAST (BL, N = 51), after 2 cycles (C2, N = 37), and 4 cycles (C4, N = 44) of NAST. 33 of the 51 patients had imaging at all 3 time points. 29 of the 33 patients had pathological findings, with N = 16 with pathological complete response (pCR) and N = 13 with non-pCR. Two sets of CEST images using 0.9 and 2.0 µT saturation power levels were acquired and analyzed using the magnetization transfer ratio asymmetry (MTRasym) and the Lorentzian line fitting (Mag3.5) methods, for a total of 4 acquisition/analysis combinations. The group averaged CEST signals, MTRasym at 0.9 and 2.0 µT and Mag3.5 at 0.9 and 2.0 µT, at BL, C2 and C4 were determined and evaluated using unpaired (51 patients) and paired (33 patients) Kruskal-Wallis tests. The Mag3.5 at 0.9 µT and the MTRasym at 2.0 µT were further compared between pCR and non-pCR. The group averaged CEST signals at BL, C2, and C4 were evaluated using the Friedman test for the pCR and the non-PCR groups. Separately, the change in the CEST signal from BL to C2 and C4 was determined for each patient and evaluated using the Mann-Whitney test for both groups. P < 0.05 was considered statistically significant.
Results The MTRasym at BL was higher at 2.0 µT than at 0.9 µT. In contrast, the Mag3.5 at BL was higher at 0.9 µT than at 2.0 µT. The MTRasym at 2.0 µT and the Mag3.5 at 0.9 µT decreased during treatment while the MTRasym at 0.9 µT and the Mag3.5 at 2.0 µT were similar. Both the unpaired and the paired Mag3.5 at 0.9 µT showed a significant decrease at C2 and C4 vs. BL (p < 0.01). The unpaired and paired MTRasym at 2.0 µT showed a decrease, although the change was not significant except for the unpaired data at C4. The decrease in the group averaged Mag3.5 at 0.9 µT was significant at C2 vs. BL for the pCR group (p = 0.04), while it was not significant for the pCR group at C4 vs. BL and for the non-pCR group at either C2 or C4 vs. BL. The group averaged MTRasym at 2.0 µT changes were not significant for either the pCR or the non-pCR groups. None of the CEST signal changes on a per patient basis at C2-BL, C4-BL and C4-C2 were significantly different between the pCR and the non-pCR groups. Further, none of the group averaged CEST signals at BL, C2 and C4 were significantly different between the pCR and the non-pCR groups.
Conclusion Our study demonstrates that the CEST quantitation in TNBC patients undergoing NAST depends on acquisition and analysis. For a maximum change in the CEST effect, Lorentzian line fitting is better paired with acquisition at a low saturation power (0.9 µT) and MTRasym is better paired with acquisition at a high saturation power (2.0 µT). Further, a significant CEST signal decrease was observed in TNBC patients with pCR after NAST when a 0.9 µT saturation power and the Lorentzian line fitting were used. In comparison, the decrease was not significant in non-pCR patients using the same saturation power and analysis method. The results suggest that the CEST signal acquired at 0.9 µT saturation power and analyzed using Lorentzian line fitting may be able to differentiate between pCR and non-pCR among TNBC patients undergoing NAST. Additional studies with a larger patient population are ongoing to further validate our findings and their potential for determining pCR.
Citation Format: Shu Zhang, Gaiane M Rauch, Beatriz E Adrada, Medine Boge, Rania MM Mohamed, Abeer H Abdelhafez, Jong Bum Son, Jia Sun, Nabil A Elshafeey, Jason B White, Deanna L Lane, Jessica WT Leung, Marion E Scoggins, David A Spak, Elsa Arribas, Elizabeth Ravenberg, Lumarie Santiago, Tanya W Moseley, Gary J Whitman, Huong Le-Petross, Benjamin C Musall, Mitsuharu Miyoshi, Xinzeng Wang, Brandy Willis, Stacy Hash, Aikaterini Kotrotsou, Peng Wei, Ken-Pin Hwang, Alastair Thompson, Stacy L Moulder, Rosalind P Candelaria, Wei Yang, Jingfei Ma, Mark D Pagel. Assessment of early response to neoadjuvant systemic therapy (NAST) of triple-negative breast cancer (TNBC) using chemical exchange saturation transfer (CEST) MRI: A pilot study [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PS3-08.
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Affiliation(s)
- Shu Zhang
- 1UT MD Anderson Cancer Center, Houston, TX
| | | | | | | | | | | | | | - Jia Sun
- 1UT MD Anderson Cancer Center, Houston, TX
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | - Stacy Hash
- 1UT MD Anderson Cancer Center, Houston, TX
| | | | - Peng Wei
- 1UT MD Anderson Cancer Center, Houston, TX
| | | | | | | | | | - Wei Yang
- 1UT MD Anderson Cancer Center, Houston, TX
| | - Jingfei Ma
- 1UT MD Anderson Cancer Center, Houston, TX
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25
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Rauch GM, Beatriz AE, Candelaria RP, Elshafeey N, Abdelhafez AH, Musall BC, Sun J, Boge M, Mohamed RM, Son JB, Zhang S, Leung J, Lane D, Scoggins M, Spak D, Arribas E, Santiago L, Whitman GJ, Le-Petross HT, Moseley TW, White JB, Ravenberg E, Hwang KP, Wei P, Huo L, Litton JK, Valero V, Tripathy D, Thompson AM, Pagel MD, Ma J, Yang WT, Moulder S. Abstract PD6-07: Volumetric changes on longitudinal dynamic contrast enhanced MR imaging (DCE-MRI) as an early treatment response predictor to neoadjuvant systemic therapy (NAST) in triple negative breast cancer (TNBC) patients. Cancer Res 2021. [DOI: 10.1158/1538-7445.sabcs20-pd6-07] [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 and Purpose:There is currently a lack of recognized imaging criteria for prediction of treatment response to NAST in breast cancer patients with recent reports showing that breast MRI is the most accurate modality for evaluation of NAST response. DCE-MRI evaluates tumor perfusion that influences tumor enhancement at the post-contrast subtraction images and allows for more accurate measurement of changes in tumor volume during NAST. In this study, we evaluated the ability of tumor volumetric changes after 2 and 4 cycles of NAST by longitudinal ultrafast DCE-MRI to predict pathologic complete response (pCR) in TNBC undergoing NAST. Materials and Methods: Stage I-III TNBC patients enrolled in an IRB approved prospective clinical trial (ARTEMIS, NCT02276433) who had ultrafast DCE-MRI at baseline (BL, N=103), post 2 cycles (C2, N=59), and post 4 cycles (C4, N=103) of anthracycline-based NAST,and had surgery, were included in this analysis. Tumor volume was calculated using 3D measurements of the index lesion at BL, C2, and C4. Percent change of tumor volume (%TV) between BL, C2, and C4 was calculated at early (9-12 sec) and delayed (360-480 sec) phases of DCE-MRI. The largest lesion was used for analysis in patients with multicentric or multifocal disease. Demographic, clinical, and pathologic data and treatment response at surgery (pCR versus non-pCR) were documented. Receiver operating characteristics curve (ROC) analysis was performed for prediction of pCR status. Positive predictive value (PPV), negative predictive value (NPV) and Youden Index were used to select %TV cut-off thresholds for pCR prediction.Results: 103 patients (median age, 53 years; range, 24-79 years) were included, 48 (47%) had pCR, and 55 (53%) had non-pCR at surgical pathology. The %TV reduction at C2 DCE-MRI was predictive of pCR on both early phase DCE MRI (AUC, 0.873; CI:0.779-0.968, p < .0001) and delayed phase DCE MRI (AUC, 0.844; CI:0.742-0.947, p < .0001). Optimal thresholds were as follows: 70% TV reduction on early phase DCE MRI with Youden’s index of 1.58 was able to predict pCR correctly for 79% of patients with PPV of 81%; 75% TV reduction on delayed phase with Youden’s Index of 1.44 was able to predict pCR correctly for 71% of patients with PPV of 85%.%TV reduction was also predictive of pCR at the C4 time point on both early phase DCE MRI (AUC, 0.761; CI:0.665-0.856, p < .0001) and delayed phase DCE MRI (AUC, 0.737; CI:0.641-0.833, p < .0001). Optimal thresholds were as follows: 90% TV reduction on early phase DCE MRI with Youden’s index of 1.43 was able to correctly predict pCR in 72% of patients with PPV of 70%; and 90% TV reduction on delayed phase with Youden’s Index of 1.34 was able to predict pCR correctly in 68% of patients with PPV of 71%.Conclusion: Our data shows that percent tumor volume reduction by DCE-MRI after 2 and 4 cycles of NAST was able to predict pCR in TNBC with high accuracy and can be used as an early imaging biomarker of NAST response prediction. Volumetric changes by longitudinal DCE-MRI can be used to differentiate chemoresistant and chemosensitive TNBC patients as early as after 2 cycles of NAST, and can help to triage patients for treatment de-escalation or targeted therapy.
Citation Format: Gaiane Margishvili Rauch, Adrada E Beatriz, Rosalind P Candelaria, Nabil Elshafeey, Abeer H Abdelhafez, Benjamin C Musall, Jia Sun, Medina Boge, Rania M.M Mohamed, Jong Bum Son, Shu Zhang, Jessica Leung, Deanna Lane, Marion Scoggins, David Spak, Elsa Arribas, Lumarie Santiago, Gary J Whitman, Huong T. Le-Petross, Tanya W Moseley, Jason B. White, Elizabeth Ravenberg, Ken-Pin Hwang, Peng Wei, Lei Huo, Jennifer K Litton, Vicente Valero, Debu Tripathy, Alastair M Thompson, Mark D Pagel, Jingfei Ma, Wei T Yang, Stacy Moulder. Volumetric changes on longitudinal dynamic contrast enhanced MR imaging (DCE-MRI) as an early treatment response predictor to neoadjuvant systemic therapy (NAST) in triple negative breast cancer (TNBC) patients [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PD6-07.
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Affiliation(s)
| | - Adrada E Beatriz
- 1Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX
| | | | - Nabil Elshafeey
- 1Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Abeer H Abdelhafez
- 2Abdominal Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Benjamin C Musall
- 3Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Jia Sun
- 4Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Medina Boge
- 1Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Rania M.M Mohamed
- 1Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Jong Bum Son
- 3Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Shu Zhang
- 5Cancer Systems Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Jessica Leung
- 1Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Deanna Lane
- 1Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Marion Scoggins
- 1Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - David Spak
- 1Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Elsa Arribas
- 1Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Lumarie Santiago
- 1Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Gary J Whitman
- 1Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Huong T. Le-Petross
- 1Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Tanya W Moseley
- 1Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Jason B. White
- 6Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Elizabeth Ravenberg
- 6Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Ken-Pin Hwang
- 3Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Peng Wei
- 4Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Lei Huo
- 7Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Jennifer K Litton
- 6Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Vicente Valero
- 6Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Debu Tripathy
- 6Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX
| | | | - Mark D Pagel
- 9Imaging Physics and Cancer Systems Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Jingfei Ma
- 3Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Wei T Yang
- 1Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Stacy Moulder
- 6Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX
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Abdelhafez AH, Musall BC, Adrada BE, Hess K, Son JB, Hwang KP, Candelaria RP, Santiago L, Whitman GJ, Le-Petross HT, Moseley TW, Arribas E, Lane DL, Scoggins ME, Leung JWT, Mahmoud HS, White JB, Ravenberg EE, Litton JK, Valero V, Wei P, Thompson AM, Moulder SL, Pagel MD, Ma J, Yang WT, Rauch GM. Tumor necrosis by pretreatment breast MRI: association with neoadjuvant systemic therapy (NAST) response in triple-negative breast cancer (TNBC). Breast Cancer Res Treat 2020; 185:1-12. [PMID: 32920733 DOI: 10.1007/s10549-020-05917-7] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [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: 05/25/2020] [Accepted: 09/01/2020] [Indexed: 10/23/2022]
Abstract
PURPOSE To determine if tumor necrosis by pretreatment breast MRI and its quantitative imaging characteristics are associated with response to NAST in TNBC. METHODS This retrospective study included 85 TNBC patients (mean age 51.8 ± 13 years) with MRI before NAST and definitive surgery during 2010-2018. Each MRI included T2-weighted, diffusion-weighted (DWI), and dynamic contrast-enhanced (DCE) imaging. For each index carcinoma, total tumor volume including necrosis (TTV), excluding necrosis (TV), and the necrosis-only volume (NV) were segmented on early-phase DCE subtractions and DWI images. NV and %NV were calculated. Percent enhancement on early and late phases of DCE and apparent diffusion coefficient were extracted from TTV, TV, and NV. Association between necrosis with pathological complete response (pCR) was assessed using odds ratio (OR). Multivariable analysis was used to evaluate the prognostic value of necrosis with T stage and nodal status at staging. Mann-Whitney U tests and area under the curve (AUC) were used to assess performance of imaging metrics for discriminating pCR vs non-pCR. RESULTS Of 39 patients (46%) with necrosis, 17 had pCR and 22 did not. Necrosis was not associated with pCR (OR, 0.995; 95% confidence interval [CI] 0.4-2.3) and was not an independent prognostic factor when combined with T stage and nodal status at staging (P = 0.46). None of the imaging metrics differed significantly between pCR and non-pCR in patients with necrosis (AUC < 0.6 and P > 0.40). CONCLUSION No significant association was found between necrosis by pretreatment MRI or the quantitative imaging characteristics of tumor necrosis and response to NAST in TNBC.
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Affiliation(s)
- Abeer H Abdelhafez
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd., Unit 1350, Houston, TX, 77030, USA
| | - Benjamin C Musall
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd., Unit 1472, Houston, TX, 77030, USA
| | - Beatriz E Adrada
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd., Unit 1350, Houston, TX, 77030, USA
| | - KennethR Hess
- Department of Biostatistics, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd., Unit 1411, Houston, TX, 77030, USA
| | - Jong Bum Son
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd., Unit 1472, Houston, TX, 77030, USA
| | - Ken-Pin Hwang
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd., Unit 1472, Houston, TX, 77030, USA
| | - Rosalind P Candelaria
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd., Unit 1350, Houston, TX, 77030, USA
| | - Lumarie Santiago
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd., Unit 1350, Houston, TX, 77030, USA
| | - Gary J Whitman
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd., Unit 1350, Houston, TX, 77030, USA
| | - Huong T Le-Petross
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd., Unit 1350, Houston, TX, 77030, USA
| | - Tanya W Moseley
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd., Unit 1350, Houston, TX, 77030, USA
| | - Elsa Arribas
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd., Unit 1350, Houston, TX, 77030, USA
| | - Deanna L Lane
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd., Unit 1350, Houston, TX, 77030, USA
| | - Marion E Scoggins
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd., Unit 1350, Houston, TX, 77030, USA
| | - Jessica W T Leung
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd., Unit 1350, Houston, TX, 77030, USA
| | - Hagar S Mahmoud
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd., Unit 1350, Houston, TX, 77030, USA
| | - Jason B White
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd., Unit 1354, Houston, TX, 77030, USA
| | - Elizabeth E Ravenberg
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, 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, 1515 Holcombe Blvd., Unit 1354, Houston, TX, 77030, USA
| | - Vicente Valero
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd., Unit 1354, Houston, TX, 77030, USA
| | - Peng Wei
- Department of Biostatistics, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd., Unit 1411, Houston, TX, 77030, USA
| | - Alastair M Thompson
- Department of Surgery, Baylor College of Medicine, 7200 Cambridge St., Houston, TX, 77030, USA
| | - Stacy L Moulder
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd., Unit 1354, Houston, TX, 77030, USA
| | - Mark D Pagel
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd., Unit 1472, Houston, TX, 77030, USA.,Department of Cancer Systems Imaging, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd., Unit 1907, Houston, TX, 77030, USA
| | - Jingfei Ma
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd., Unit 1472, Houston, TX, 77030, USA
| | - Wei T Yang
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd., Unit 1350, Houston, TX, 77030, USA
| | - Gaiane M Rauch
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd., Unit 1350, Houston, TX, 77030, USA. .,Division of Diagnostic Imaging, Department of Abdominal Imaging, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd., Unit 1473, Houston, TX, 77030, USA.
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Adrada BE, Abdelhafez AH, Musall BC, Hess KR, Son JB, Pagel MD, Hwang KP, Candelaria RP, Santiago L, Whitman GJ, Le-Petross H, Moseley TW, Arribas E, Lane DL, Scoggins ME, Spak DA, Leung JW, Damodaran S, Lim B, Valeo V, White JB, Thompson AM, Litton JK, Moulder SL, Ma J, Yang WT, Rauch GM. Abstract P6-02-03: Quantitative apparent diffusion coefficient (ADC) radiomics of tumor and peritumoral regions as potential predictors of treatment response to neoadjuvant chemotherapy (NACT) in triple negative breast cancer (TNBC) patients. Cancer Res 2020. [DOI: 10.1158/1538-7445.sabcs19-p6-02-03] [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 and Purpose: TNBC is comprised of biologically aggressive tumors with diverse clinical behavior and response to chemotherapy. Prediction of disease response to NACT is critical to the development of personalized medicine in TNBC. We evaluated first-order radiomic features from quantitative ADC maps of the tumor and peritumoral region as discriminators of response to NACT in TNBC patients.
Materials and Methods: This IRB-approved prospective study (ARTEMIS trial, NCT02276443) included 34 patients with biopsy proven stage I-III TNBC who underwent evaluation of treatment response by multi-parametric MRI. Patients had a baseline MRI (BL) and a second MRI after 4 cycles (C4) of their treatment. After completion of NACT, all patients underwent surgery and were classified as pathologic complete response (pCR) or non-pCR.
Both MRI exams included T2W series, a dynamic contrast enhanced series (DCE), a conventional diffusion weighted imaging (DWI) series, and a reduced field of view (rFOV) DWI series. Tumor volumes were contoured by an experienced breast radiologist on ADC maps with reference to b1000 DWI images. Regions with necrosis or clip artifacts were excluded from the contour. Peritumoral regions were defined as a 5 mm rim of tissue surrounding the tumor based on DCE series, T2-weighted images with fat suppression and ADC maps. Thirteen first-order radiomic features, including mean, minimum, maximum, percentiles, kurtosis and skewness at a single measurement and the difference between BL and C4 were compared between pCR and non-pCR using Receiver Operating Characteristic (ROC) curve and Wilcoxon rank sum test.
Results: The kurtosis of tumor at C4 by conventional DWI was significantly higher in non-pCR than in pCR patients (AUC=0.785, p=0.0097). The change in kurtosis from BL to C4 by conventional DWI was also significantly higher in non-pCR than in pCR patients (AUC=0.73, p=0.043). The skewness of tumor at C4 by rFOV DWI scan was significantly lower in pCR than non-pCR patients (AUC=0.73, p=0.023).
The 10th percentile of the peritumoral region’s ADC was significantly different between pCR and non-pCR (mean=1.19, SD is ± 0.27 10-3 mm2/s vs mean=1.34, SD ± 0.27 10-3 mm2/s respectively, AUC=0.70, p=0.048). The kurtosis and 25th percentile of the ADC of peritumoral region were borderline significantly different between pCR and non-pCR (AUC=0.69, p=0.067; AUC=0.69, p= 0.073 respectively).
Conclusion: ADC first-order radiomic features from tumor and peritumoral region in TNBC may be useful for predicting treatment response to NACT. Larger study is necessary and is currently in progress to validate these findings.
Citation Format: Beatriz E. Adrada, Abeer H. Abdelhafez, Benjamin C. Musall, Kenneth R. Hess, Jong Bum Son, Mark D. Pagel, Ken-Pin Hwang, Rosalind P. Candelaria, Lumarie Santiago, Gary J. Whitman, Huong Le-Petross, Tanya W. Moseley, Elsa Arribas, Deanna L. Lane, Marion E. Scoggins, David A. Spak, Jessica W.T. Leung, Senthil Damodaran, Bora Lim, Vicente Valeo, Jason B White, Alastair M. Thompson, Jennifer K. Litton, Stacy L. Moulder, Jingfei Ma, Wei T. Yang, Gaiane M Rauch. Quantitative apparent diffusion coefficient (ADC) radiomics of tumor and peritumoral regions as potential predictors of treatment response to neoadjuvant chemotherapy (NACT) in triple negative breast cancer (TNBC) patients [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P6-02-03.
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Affiliation(s)
| | | | | | - Kenneth R. Hess
- 1The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Jong Bum Son
- 1The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Mark D. Pagel
- 1The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Ken-Pin Hwang
- 1The University of Texas MD Anderson Cancer Center, Houston, TX
| | | | | | - Gary J. Whitman
- 1The University of Texas MD Anderson Cancer Center, Houston, TX
| | | | | | - Elsa Arribas
- 1The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Deanna L. Lane
- 1The University of Texas MD Anderson Cancer Center, Houston, TX
| | | | - David A. Spak
- 1The University of Texas MD Anderson Cancer Center, Houston, TX
| | | | | | - Bora Lim
- 1The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Vicente Valeo
- 1The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Jason B White
- 1The University of Texas MD Anderson Cancer Center, Houston, TX
| | | | | | | | - Jingfei Ma
- 1The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Wei T. Yang
- 1The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Gaiane M Rauch
- 1The University of Texas MD Anderson Cancer Center, Houston, TX
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Moseley TW, Shah SS, Brandt KR, Huo L. ASO Author Reflections: Mucocele-Like Lesions of the Breast-Excision or No Excision? Ann Surg Oncol 2019; 26:826-827. [PMID: 31691107 DOI: 10.1245/s10434-019-07620-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2019] [Indexed: 11/18/2022]
Affiliation(s)
- Tanya W Moseley
- Department of Diagnostic Radiology, Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Sejal S Shah
- Department of Anatomic Pathology, Mayo Clinic, Rochester, MN, USA
| | - Kathy R Brandt
- Department of Radiology, College of Medicine, Mayo Clinic, Rochester, MN, USA.
| | - Lei Huo
- Department of Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
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Moseley TW, Shah SS, Nguyen CV, Rosenblat J, Resetkova E, Sneige N, Brandt KR, Huo L. Clinical Management of Mucocele-Like Lesions of the Breast with Limited or no Epithelial Atypia on Core Biopsy: Experience from Two Institutions. Ann Surg Oncol 2019; 26:3478-3488. [PMID: 31187364 DOI: 10.1245/s10434-019-07377-w] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2019] [Indexed: 11/18/2022]
Abstract
PURPOSE Mucocele-like lesions of the breast identified on core biopsy are rare high-risk lesions associated with variable upgrade rates to carcinoma on excision. We aimed to identify the clinicoradiopathological features that can help optimize management of this lesion. METHODS We evaluated 50 mucocele-like lesions identified on core biopsies from two institutions, including 36 with no atypia and 14 with limited atypia. Outcome data from excision or clinicoradiological follow-up were reviewed with core biopsy results. RESULTS Radiological targets were calcifications in 74% of cases, calcifications with associated mass or density in 16%, and mass in 10%. One of the 16 excised lesions without atypia on core biopsy, which was a mass lesion, was upgraded to mucinous carcinoma on excision. Of the 12 excised lesions with limited atypia, none were upgraded on excision. Among the lesions not excised, 20 without atypia had a median follow-up of 61 months, and 2 with limited atypia had follow-up of 97 and 109 months. None of these 22 patients had new development of their lesions on follow-up. The upgrade rate was 2% in our entire cohort, 3% for lesions without atypia, and 0% for lesions with limited atypia. CONCLUSIONS Clinicoradiological surveillance can be appropriate when a mucocele-like lesion without atypia is identified on core biopsy for a non-mass lesion with pathological-radiological concordance. For mucocele-like lesions with limited atypia, a nonsurgical approach could be considered if the atypia by itself does not warrant excision. The latter recommendation requires careful clinicopathological correlation and support from additional studies.
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Affiliation(s)
- Tanya W Moseley
- Department of Diagnostic Radiology, Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Sejal S Shah
- Department of Anatomic Pathology, Mayo Clinic, Rochester, MN, USA
| | - Christopher V Nguyen
- Department of Pathology, Unit 85, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd., Houston, TX, 77030, USA
| | - Juliana Rosenblat
- Department of Diagnostic Radiology, Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Erika Resetkova
- Department of Pathology, Unit 85, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd., Houston, TX, 77030, USA
| | - Nour Sneige
- Department of Pathology, Unit 85, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd., Houston, TX, 77030, USA
| | - Kathy R Brandt
- Department of Radiology, College of Medicine, Mayo Clinic, Rochester, MN, 55905, USA.
| | - Lei Huo
- Department of Pathology, Unit 85, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd., Houston, TX, 77030, USA.
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Balema WA, Moseley TW, Weaver O, Hess KR, Brewster AM. The association between volumetric breast density and breast cancer subtypes among women newly diagnosed with breast cancer. J Clin Oncol 2019. [DOI: 10.1200/jco.2019.37.15_suppl.e13115] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [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
e13115 Background: Increased breast density is a strong risk factor for breast cancer, women with high breast density have a four to six-fold increased risk of breast cancer compared to those with low density. This study explores breast density as a risk factor for specific breast cancer subtypes in order to improve risk assessment and screening recommendations for the general population. Methods: 790 women ≥ 18 years with breast cancer were evaluated who had volumetric percent density and volumetric density grade (VDG) assessed from diagnostic mammograms obtained within 9 months of diagnosis. Breast cancer subtypes were approximated based on the estrogen receptor (ER), progesterone (PR) and Her2neu status; ER and/or PR positive/Her2 negative or positive (HR+), ER and PR negative and Her2 positive (Her2-positive) and ER, PR and Her2 negative (TN). A linear model on a log scale was conducted to evaluate the associations between percentage volumetric breast density and VDG and breast cancer subtypes and race. Results: 36% of women were < 50 years and 64% ≥50 years, 76% were white, 12% Black and 12% other race. There was no significant association between breast cancer subtype with age ( P = 0.068), BMI ( P = 0.81) or race ( P = 0.11). Women with VDG 1 or 2 were more likely to have HR+ (81.3%) than Her2-positive (5.1%) or TN subtypes (13.6%) (P = 0.024). There was no significant association between the percent volumetric breast density and breast tumor subtype or race. Conclusions: We found a significant association between lower breast density measured using VDG and the HR+ breast cancer subtype. This suggests a potential opportunity for assessing volumetric density grade for the development of individualized risk prediction models and for the identification of women who may benefit from preventive therapy to reduce HR+ breast cancer risk.
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Affiliation(s)
| | | | - Olena Weaver
- The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Kenneth R. Hess
- The University of Texas MD Anderson Cancer Center, Houston, TX
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Moseley TW, Stanley A, Wei W, Parikh JR. Impact on Clinical Management of After-Hours Emergent or Urgent Breast Ultrasonography in Patients with Clinically Suspected Breast Abscesses. Diagnostics (Basel) 2018; 8:diagnostics8010017. [PMID: 29473859 PMCID: PMC5872000 DOI: 10.3390/diagnostics8010017] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2018] [Revised: 01/31/2018] [Accepted: 02/11/2018] [Indexed: 02/03/2023] Open
Abstract
Newly diagnosed breast abscesses are generally treated as a medical emergency that may necessitate immediate interventional treatment. At our institution, there is no in-house after-hours coverage for breast ultrasonography. We could find no peer-reviewed studies on the cost-effectiveness or clinical management impact of on-call ultrasound technologist coverage for imaging of breast abscesses. The purposes of this study were to determine the incidence of breast abscess in patients with clinical findings highly suggestive of abscess, identify clinical factors associated with breast abscess in such patients, and determine the impact of after-hours emergent or urgent breast ultrasonography on the clinical management of breast abscesses in both outpatients and inpatients. We retrospectively reviewed 100 after-hours breast ultrasound studies performed at our tertiary care center from 2011 to 2015 for evaluation of a suspected breast abscess. Only 26% of our patients with clinically suspected abscess ultimately had a confirmed abscess. Factors associated with breast abscess were a palpable abnormality and a history of breast surgery within the eight weeks before presentation. After-hours diagnosis of an abscess was associated with after-hours clinical intervention. Of the 74 patients in whom after-hours ultrasound imaging showed no evidence of abscess, only three patients underwent after-hours drainage. Our findings support overnight and weekend breast ultrasound coverage in large tertiary care centers.
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Affiliation(s)
- Tanya W Moseley
- Section of Breast Imaging, Department of Diagnostic Radiology, The University of Texas MD Anderson Cancer Center, 1155 Pressler St., Unit 1350, Houston, TX 77030, USA.
| | - Ashley Stanley
- Section of Breast Imaging, Department of Diagnostic Radiology, The University of Texas MD Anderson Cancer Center, 1155 Pressler St., Unit 1350, Houston, TX 77030, USA.
- Radiology Partners, CHI St. Luke's Way, The Woodlands, Houston, TX 77384, USA.
| | - Wei Wei
- Department of Biostatistics, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX 77030, USA.
| | - Jay R Parikh
- Section of Breast Imaging, Department of Diagnostic Radiology, The University of Texas MD Anderson Cancer Center, 1155 Pressler St., Unit 1350, Houston, TX 77030, USA.
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Le-Petross HT, Hess KR, Knudtson JD, Lane DL, Moseley TW, Geiser WR, Whitman GJ. Effect of Mammography on Marker Clip Migration After Stereotactic-Guided Core Needle Breast Biopsy. Curr Probl Diagn Radiol 2017; 46:410-414. [DOI: 10.1067/j.cpradiol.2017.02.001] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2016] [Accepted: 02/13/2017] [Indexed: 11/22/2022]
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