Literature DB >> 29708782

MRI, Clinical Examination, and Mammography for Preoperative Assessment of Residual Disease and Pathologic Complete Response After Neoadjuvant Chemotherapy for Breast Cancer: ACRIN 6657 Trial.

John R Scheel1, Eunhee Kim2, Savannah C Partridge1, Constance D Lehman3, Mark A Rosen4, Wanda K Bernreuter5, Etta D Pisano6, Helga S Marques7, Elizabeth A Morris8, Paul T Weatherall9, Sandra M Polin10, Gillian M Newstead11, Laura J Esserman12, Mitchell D Schnall4, Nola M Hylton12.   

Abstract

OBJECTIVE: The objective of our study was to determine the accuracy of preoperative measurements for detecting pathologic complete response (CR) and assessing residual disease after neoadjuvant chemotherapy (NACT) in patients with locally advanced breast cancer. SUBJECTS AND METHODS: The American College of Radiology Imaging Network 6657 Trial prospectively enrolled women with ≥ 3 cm invasive breast cancer receiving NACT. Preoperative measurements of residual disease included longest diameter by mammography, MRI, and clinical examination and functional volume on MRI. The accuracy of preoperative measurements for detecting pathologic CR and the association with final pathology size were assessed for all lesions, separately for single masses and nonmass enhancements (NMEs), multiple masses, and lesions without ductal carcinoma in situ (DCIS).
RESULTS: In the 138 women with all four preoperative measures, longest diameter by MRI showed the highest accuracy for detecting pathologic CR for all lesions and NME (AUC = 0.76 and 0.84, respectively). There was little difference across preoperative measurements in the accuracy of detecting pathologic CR for single masses (AUC = 0.69-0.72). Longest diameter by MRI and longest diameter by clinical examination showed moderate ability for detecting pathologic CR for multiple masses (AUC = 0.78 and 0.74), and longest diameter by MRI and longest diameter by mammography showed moderate ability for detecting pathologic CR for tumors without DCIS (AUC = 0.74 and 0.71). In subjects with residual disease, longest diameter by MRI exhibited the strongest association with pathology size for all lesions and single masses (r = 0.33 and 0.47). Associations between preoperative measures and pathology results were not significantly influenced by tumor subtype or mammographic density.
CONCLUSION: Our results indicate that measurement of longest diameter by MRI is more accurate than by mammography and clinical examination for preoperative assessment of tumor residua after NACT and may improve surgical planning.

Entities:  

Keywords:  MRI; clinical examination; locally advanced breast cancer; mammography; neoadjuvant chemotherapy; pathologic complete response

Mesh:

Year:  2018        PMID: 29708782      PMCID: PMC6615034          DOI: 10.2214/AJR.17.18323

Source DB:  PubMed          Journal:  AJR Am J Roentgenol        ISSN: 0361-803X            Impact factor:   3.959


  21 in total

Review 1.  MRI Performance in Detecting pCR After Neoadjuvant Chemotherapy by Molecular Subtype of Breast Cancer.

Authors:  Nancy Yu; Vivian W Y Leung; Sarkis Meterissian
Journal:  World J Surg       Date:  2019-09       Impact factor: 3.352

2.  Phase II Single-Arm Study of Preoperative Letrozole for Estrogen Receptor-Positive Postmenopausal Ductal Carcinoma In Situ: CALGB 40903 (Alliance).

Authors:  E Shelley Hwang; Terry Hyslop; Laura H Hendrix; Stephanie Duong; Isabelle Bedrosian; Elissa Price; Abigail Caudle; Tina Hieken; Joseph Guenther; Clifford A Hudis; Eric Winer; Alan P Lyss; Diana Dickson-Witmer; Richard Hoefer; David W Ollila; Timothy Hardman; Jeffrey Marks; Yunn-Yi Chen; Gregor Krings; Laura Esserman; Nola Hylton
Journal:  J Clin Oncol       Date:  2020-03-03       Impact factor: 44.544

3.  Robustness Evaluation of a Deep Learning Model on Sagittal and Axial Breast DCE-MRIs to Predict Pathological Complete Response to Neoadjuvant Chemotherapy.

Authors:  Raffaella Massafra; Maria Colomba Comes; Samantha Bove; Vittorio Didonna; Gianluca Gatta; Francesco Giotta; Annarita Fanizzi; Daniele La Forgia; Agnese Latorre; Maria Irene Pastena; Domenico Pomarico; Lucia Rinaldi; Pasquale Tamborra; Alfredo Zito; Vito Lorusso; Angelo Virgilio Paradiso
Journal:  J Pers Med       Date:  2022-06-10

Review 4.  The Impact of Dense Breasts on the Stage of Breast Cancer at Diagnosis: A Review and Options for Supplemental Screening.

Authors:  Paula B Gordon
Journal:  Curr Oncol       Date:  2022-05-17       Impact factor: 3.109

5.  Visual Evaluation of Ultrafast MRI in the Assessment of Residual Breast Cancer after Neoadjuvant Systemic Therapy: A Preliminary Study Association with Subtype.

Authors:  Maya Honda; Masako Kataoka; Mami Iima; Rie Ota; Akane Ohashi; Ayami Ohno Kishimoto; Kanae Kawai Miyake; Marcel Dominik Nickel; Yosuke Yamada; Masakazu Toi; Yuji Nakamoto
Journal:  Tomography       Date:  2022-06-10

6.  Is Clinical Exam of the Axilla Sufficient to Select Node-Positive Patients Who Downstage After NAC for SLNB? A Comparison of the Accuracy of Clinical Exam Versus MRI.

Authors:  Tracy-Ann Moo; Maxine S Jochelson; Emily C Zabor; Michelle Stempel; Monica Raiss; Anita Mamtani; Audree B Tadros; Mahmoud El-Tamer; Monica Morrow
Journal:  Ann Surg Oncol       Date:  2019-10-03       Impact factor: 5.344

7.  Factors affecting the concordance of radiologic and pathologic tumor size in breast carcinoma.

Authors:  Ameer Hamza; Sidrah Khawar; Ramen Sakhi; Ahmed Alrajjal; Shelby Miller; Warda Ibrar; Jacob Edens; Sajad Salehi; Daniel Ockner
Journal:  Ultrasound       Date:  2018-10-23

8.  Margin Assessment and Re-excision Rates for Patients Who Have Neoadjuvant Chemotherapy and Breast-Conserving Surgery.

Authors:  Cindy Cen; Jennifer Chun; Elianna Kaplowitz; Deborah Axelrod; Richard Shapiro; Amber Guth; Freya Schnabel
Journal:  Ann Surg Oncol       Date:  2021-02-26       Impact factor: 5.344

9.  Early prediction of neoadjuvant chemotherapy response by exploiting a transfer learning approach on breast DCE-MRIs.

Authors:  Maria Colomba Comes; Annarita Fanizzi; Samantha Bove; Vittorio Didonna; Sergio Diotaiuti; Daniele La Forgia; Agnese Latorre; Eugenio Martinelli; Arianna Mencattini; Annalisa Nardone; Angelo Virgilio Paradiso; Cosmo Maurizio Ressa; Pasquale Tamborra; Vito Lorusso; Raffaella Massafra
Journal:  Sci Rep       Date:  2021-07-08       Impact factor: 4.379

10.  Radiogenomics of magnetic resonance imaging and a new multi-gene classifier for predicting recurrence prognosis in estrogen receptor-positive breast cancer: A preliminary study.

Authors:  Yukiko Tokuda; Masahiro Yanagawa; Kaori Minamitani; Yasuto Naoi; Shinzaburo Noguchi; Noriyuki Tomiyama
Journal:  Medicine (Baltimore)       Date:  2020-04       Impact factor: 1.817

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