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Role of Diffusion-Weighted Magnetic Resonance Imaging in Prediction of Pathological Complete Response to Neoadjuvant Chemotherapy in Locally Advanced Breast Cancer and Its Molecular Subtypes

Purpose  The aim of this study was to evaluate the role of apparent diffusion coefficient (ADC) and hence diffusion-weighted imaging in prediction of pathological complete response (pCR) to neoadjuvant chemotherapy (NACT) in locally advanced breast cancer (LABC) and its molecular subtypes. Methods  ...

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Autores principales: Singh, Neetu, Jain, Shivi, Verma, Ashish, Khanna, Seema, Shukla, Ram Chandra
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Thieme Medical and Scientific Publishers Pvt. Ltd. 2022
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9514905/
https://www.ncbi.nlm.nih.gov/pubmed/36177282
http://dx.doi.org/10.1055/s-0042-1750155
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author Singh, Neetu
Jain, Shivi
Verma, Ashish
Khanna, Seema
Shukla, Ram Chandra
author_facet Singh, Neetu
Jain, Shivi
Verma, Ashish
Khanna, Seema
Shukla, Ram Chandra
author_sort Singh, Neetu
collection PubMed
description Purpose  The aim of this study was to evaluate the role of apparent diffusion coefficient (ADC) and hence diffusion-weighted imaging in prediction of pathological complete response (pCR) to neoadjuvant chemotherapy (NACT) in locally advanced breast cancer (LABC) and its molecular subtypes. Methods  In this tertiary hospital-based prospective study, 30 patients aged 30 to 65 years, having clinically/cytologically diagnosed LABC, were included. Magnetic resonance imaging (MRI) was done to obtain prechemotherapy ADC (ADC (pre) ), postchemotherapy ADC (ADC (post) ), change in ADC (ΔADC), and ΔADC% for each tumor and its subtype. Postsurgical pCR was used as the reference standard for determining tumor response. All four ADC parameters were compared between pCR and non-pCR groups. Results  Of the 30 patients, 19 (63.3%) patients showed pCR, while 11 (36.7%) patients did not. The pCR group showed significantly lower mean ADC (pre) ( p <   0.001) and higher mean ADC (post) ( p <   0.05), ΔADC, and ΔADC% ( p  = 0.000) than non-pCR group. The best cutoff values to differentiate responders from nonresponders with receiver operating characteristic curve analysis of ADC (pre) , ADC (post) , and ΔADC% were 0.98 × 10 (−3) mm (2) /s (68.4% sensitivity, 63.6% specificity), 1.31×10 (−3) mm (2) /s (68.4% sensitivity, 63.6% specificity), and 25% (84.2% sensitivity, 90.9% specificity), respectively. Human epidermal growth factor receptor 2 (HER2)-enriched subtype showed significant difference in mean ADC (pre) ( p  = 0.045), while triple-negative subtype showed significant differences in mean ADC (post) ( p  = 0.032) and mean ΔADC ( p  = 0.019) between the two groups. Conclusion  ADC (pre) , ADC (post) , and ΔADC can predict pCR to NACT in LABC. Among molecular subtypes, ADC (pre) was predictive only in HER2-enriched subtype, while ADC (post) and ΔADC were predictive only in triple-negative subtype.
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spelling pubmed-95149052022-09-28 Role of Diffusion-Weighted Magnetic Resonance Imaging in Prediction of Pathological Complete Response to Neoadjuvant Chemotherapy in Locally Advanced Breast Cancer and Its Molecular Subtypes Singh, Neetu Jain, Shivi Verma, Ashish Khanna, Seema Shukla, Ram Chandra Indian J Radiol Imaging Purpose  The aim of this study was to evaluate the role of apparent diffusion coefficient (ADC) and hence diffusion-weighted imaging in prediction of pathological complete response (pCR) to neoadjuvant chemotherapy (NACT) in locally advanced breast cancer (LABC) and its molecular subtypes. Methods  In this tertiary hospital-based prospective study, 30 patients aged 30 to 65 years, having clinically/cytologically diagnosed LABC, were included. Magnetic resonance imaging (MRI) was done to obtain prechemotherapy ADC (ADC (pre) ), postchemotherapy ADC (ADC (post) ), change in ADC (ΔADC), and ΔADC% for each tumor and its subtype. Postsurgical pCR was used as the reference standard for determining tumor response. All four ADC parameters were compared between pCR and non-pCR groups. Results  Of the 30 patients, 19 (63.3%) patients showed pCR, while 11 (36.7%) patients did not. The pCR group showed significantly lower mean ADC (pre) ( p <   0.001) and higher mean ADC (post) ( p <   0.05), ΔADC, and ΔADC% ( p  = 0.000) than non-pCR group. The best cutoff values to differentiate responders from nonresponders with receiver operating characteristic curve analysis of ADC (pre) , ADC (post) , and ΔADC% were 0.98 × 10 (−3) mm (2) /s (68.4% sensitivity, 63.6% specificity), 1.31×10 (−3) mm (2) /s (68.4% sensitivity, 63.6% specificity), and 25% (84.2% sensitivity, 90.9% specificity), respectively. Human epidermal growth factor receptor 2 (HER2)-enriched subtype showed significant difference in mean ADC (pre) ( p  = 0.045), while triple-negative subtype showed significant differences in mean ADC (post) ( p  = 0.032) and mean ΔADC ( p  = 0.019) between the two groups. Conclusion  ADC (pre) , ADC (post) , and ΔADC can predict pCR to NACT in LABC. Among molecular subtypes, ADC (pre) was predictive only in HER2-enriched subtype, while ADC (post) and ΔADC were predictive only in triple-negative subtype. Thieme Medical and Scientific Publishers Pvt. Ltd. 2022-08-17 /pmc/articles/PMC9514905/ /pubmed/36177282 http://dx.doi.org/10.1055/s-0042-1750155 Text en Indian Radiological Association. This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. ( https://creativecommons.org/licenses/by-nc-nd/4.0/ ) https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License, which permits unrestricted reproduction and distribution, for non-commercial purposes only; and use and reproduction, but not distribution, of adapted material for non-commercial purposes only, provided the original work is properly cited.
spellingShingle Singh, Neetu
Jain, Shivi
Verma, Ashish
Khanna, Seema
Shukla, Ram Chandra
Role of Diffusion-Weighted Magnetic Resonance Imaging in Prediction of Pathological Complete Response to Neoadjuvant Chemotherapy in Locally Advanced Breast Cancer and Its Molecular Subtypes
title Role of Diffusion-Weighted Magnetic Resonance Imaging in Prediction of Pathological Complete Response to Neoadjuvant Chemotherapy in Locally Advanced Breast Cancer and Its Molecular Subtypes
title_full Role of Diffusion-Weighted Magnetic Resonance Imaging in Prediction of Pathological Complete Response to Neoadjuvant Chemotherapy in Locally Advanced Breast Cancer and Its Molecular Subtypes
title_fullStr Role of Diffusion-Weighted Magnetic Resonance Imaging in Prediction of Pathological Complete Response to Neoadjuvant Chemotherapy in Locally Advanced Breast Cancer and Its Molecular Subtypes
title_full_unstemmed Role of Diffusion-Weighted Magnetic Resonance Imaging in Prediction of Pathological Complete Response to Neoadjuvant Chemotherapy in Locally Advanced Breast Cancer and Its Molecular Subtypes
title_short Role of Diffusion-Weighted Magnetic Resonance Imaging in Prediction of Pathological Complete Response to Neoadjuvant Chemotherapy in Locally Advanced Breast Cancer and Its Molecular Subtypes
title_sort role of diffusion-weighted magnetic resonance imaging in prediction of pathological complete response to neoadjuvant chemotherapy in locally advanced breast cancer and its molecular subtypes
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9514905/
https://www.ncbi.nlm.nih.gov/pubmed/36177282
http://dx.doi.org/10.1055/s-0042-1750155
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