Literature DB >> 33586845

Functional Tumor Volume by Fast Dynamic Contrast-Enhanced MRI for Predicting Neoadjuvant Systemic Therapy Response in Triple-Negative Breast Cancer.

Benjamin C Musall1, Abeer H Abdelhafez2, Beatriz E Adrada2, Rosalind P Candelaria2, Rania M M Mohamed2, Medine Boge2, Huong Le-Petross2, Elsa Arribas2, Deanna L Lane2, David A Spak2, Jessica W T Leung2, Ken-Pin Hwang1, Jong Bum Son1, Nabil A Elshafeey2, Hagar S Mahmoud2, Peng Wei3, Jia Sun3, Shu Zhang4, Jason B White5, Elizabeth E Ravenberg5, Jennifer K Litton5, Senthil Damodaran5, Alastair M Thompson6, Stacy L Moulder5, Wei T Yang2, Mark D Pagel1,4, Gaiane M Rauch2,7, Jingfei Ma1.   

Abstract

BACKGROUND: Dynamic contrast-enhanced (DCE) MRI is useful for diagnosis and assessment of treatment response in breast cancer. Fast DCE MRI offers a higher sampling rate of contrast enhancement curves in comparison to conventional DCE MRI, potentially characterizing tumor perfusion kinetics more accurately for measurement of functional tumor volume (FTV) as a predictor of treatment response.
PURPOSE: To investigate FTV by fast DCE MRI as a predictor of neoadjuvant systemic therapy (NAST) response in triple-negative breast cancer (TNBC). STUDY TYPE: Prospective. POPULATION/
SUBJECTS: Sixty patients with biopsy-confirmed TNBC between December 2016 and September 2020. FIELD STRENGTH/SEQUENCE: A 3.0 T/3D fast spoiled gradient echo-based DCE MRI ASSESSMENT: Patients underwent MRI at baseline and after four cycles (C4) of NAST, followed by definitive surgery. DCE subtraction images were analyzed in consensus by two breast radiologists with 5 (A.H.A.) and 2 (H.S.M.) years of experience. Tumor volumes (TV) were measured on early and late subtractions. Tumors were segmented on 1 and 2.5-minute early phases subtractions and FTV was determined using optimized signal enhancement thresholds. Interpolated enhancement curves from segmented voxels were used to determine optimal early phase timing. STATISTICAL TESTS: Tumor volumes were compared between patients who had a pathologic complete response (pCR) and those who did not using the area under the receiver operating curve (AUC) and Mann-Whitney U test.
RESULTS: About 26 of 60 patients (43%) had pCR. FTV at 1 minute after injection at C4 provided the best discrimination between pCR and non-pCR, with AUC (95% confidence interval [CI]) = 0.85 (0.74,0.95) (P < 0.05). The 1-minute timing was optimal for FTV measurements at C4 and for the change between C4 and baseline. TV from the early phase at C4 also yielded a good AUC (95%CI) of 0.82 (0.71,0.93) (P < 0.05). DATA
CONCLUSION: FTV and TV measured at 1 minute after injection can predict response to NAST in TNBC. LEVEL OF EVIDENCE: 1 TECHNICAL EFFICACY: 4.
© 2021 International Society for Magnetic Resonance in Medicine.

Entities:  

Keywords:  DCE MRI; Triple-negative breast cancer; breast MRI; functional tumor volume; treatment response

Year:  2021        PMID: 33586845     DOI: 10.1002/jmri.27557

Source DB:  PubMed          Journal:  J Magn Reson Imaging        ISSN: 1053-1807            Impact factor:   4.813


  5 in total

1.  MRI-Based Digital Models Forecast Patient-Specific Treatment Responses to Neoadjuvant Chemotherapy in Triple-Negative Breast Cancer.

Authors:  Chengyue Wu; Angela M Jarrett; Zijian Zhou; Nabil Elshafeey; Beatriz E Adrada; Rosalind P Candelaria; Rania M M Mohamed; Medine Boge; Lei Huo; Jason B White; Debu Tripathy; Vicente Valero; Jennifer K Litton; Clinton Yam; Jong Bum Son; Jingfei Ma; Gaiane M Rauch; Thomas E Yankeelov
Journal:  Cancer Res       Date:  2022-09-16       Impact factor: 13.312

2.  Preoperative Breast Magnetic Resonance Imaging as a Predictor of Response to Neoadjuvant Chemotherapy.

Authors:  Robert Browne; Peter McAnena; Niamh O'Halloran; Brian M Moloney; Emily Crilly; Michael J Kerin; Aoife J Lowery
Journal:  Breast Cancer (Auckl)       Date:  2022-06-24

3.  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

4.  Predictive Value of Multiparametric MRI for Response to Single-Cycle Induction Chemo-Immunotherapy in Locally Advanced Head and Neck Squamous Cell Carcinoma.

Authors:  Konstantin Hellwig; Stephan Ellmann; Markus Eckstein; Marco Wiesmueller; Sandra Rutzner; Sabine Semrau; Benjamin Frey; Udo S Gaipl; Antoniu Oreste Gostian; Arndt Hartmann; Heinrich Iro; Rainer Fietkau; Michael Uder; Markus Hecht; Tobias Bäuerle
Journal:  Front Oncol       Date:  2021-10-21       Impact factor: 6.244

Review 5.  Radiomics, deep learning and early diagnosis in oncology.

Authors:  Peng Wei
Journal:  Emerg Top Life Sci       Date:  2021-12-21
  5 in total

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