Cargando…
Diffusion-weighted MR imaging of locally advanced breast carcinoma: the optimal time window of predicting the early response to neoadjuvant chemotherapy
BACKGROUND: It is very difficult to predict the early response to NAC only on the basis of change in tumor size. ADC value derived from DWI promises to be a valuable parameter for evaluating the early response to treatment. This study aims to establish the optimal time window of predicting the early...
Autores principales: | , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2018
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6206724/ https://www.ncbi.nlm.nih.gov/pubmed/30373679 http://dx.doi.org/10.1186/s40644-018-0173-5 |
_version_ | 1783366408208384000 |
---|---|
author | Yuan, Li Li, Jian-Jun Li, Chang-Qing Yan, Cheng-Gong Cheng, Ze-Long Wu, Yuan-Kui Hao, Peng Lin, Bing-Quan Xu, Yi-Kai |
author_facet | Yuan, Li Li, Jian-Jun Li, Chang-Qing Yan, Cheng-Gong Cheng, Ze-Long Wu, Yuan-Kui Hao, Peng Lin, Bing-Quan Xu, Yi-Kai |
author_sort | Yuan, Li |
collection | PubMed |
description | BACKGROUND: It is very difficult to predict the early response to NAC only on the basis of change in tumor size. ADC value derived from DWI promises to be a valuable parameter for evaluating the early response to treatment. This study aims to establish the optimal time window of predicting the early response to neoadjuvant chemotherapy (NAC) for different subtypes of locally advanced breast carcinoma using diffusion-weighted imaging (DWI). METHODS: We conducted an institutional review board-approved prospective clinical study of 142 patients with locally advanced breast carcinoma. All patients underwent conventional MR and DW examinations prior to treatment and after first, second, third, fourth, sixth and eighth cycle of NAC. The response to NAC was classified into a pathologic complete response (pCR) and a non-pCR group. DWI parameters were compared between two groups, and the optimal time window for predicting tumor response was established for each chemotherapy regimen. RESULTS: For all the genomic subtypes, there were significant differences in baseline ADC value between pCR and non-pCR group (p < 0.05). The time point prior to treatment could be considered as the ideal time point regardless of genomic subtype. In the group that started with taxanes or anthracyclines, for Luminal A or Luminal B subtype, postT1 could be used as the ideal time point during chemotherapy; for Basal-like or HER2-enriched subtype, postT2 as the ideal time point during chemotherapy. In the group that started with taxanes and anthracyclines, for HER2-enriched, Luminal B or Basal-like subtype, postT1 could be used as the ideal time point during chemotherapy; for Luminal A subtype, postT2 as the ideal time point during chemotherapy. CONCLUSIONS: The time point prior to treatment can be considered as the optimal time point regardless of genomic subtype. For each chemotherapy regimen, the optimal time point during chemotherapy varies across different genomic subtypes. |
format | Online Article Text |
id | pubmed-6206724 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-62067242018-10-31 Diffusion-weighted MR imaging of locally advanced breast carcinoma: the optimal time window of predicting the early response to neoadjuvant chemotherapy Yuan, Li Li, Jian-Jun Li, Chang-Qing Yan, Cheng-Gong Cheng, Ze-Long Wu, Yuan-Kui Hao, Peng Lin, Bing-Quan Xu, Yi-Kai Cancer Imaging Research Article BACKGROUND: It is very difficult to predict the early response to NAC only on the basis of change in tumor size. ADC value derived from DWI promises to be a valuable parameter for evaluating the early response to treatment. This study aims to establish the optimal time window of predicting the early response to neoadjuvant chemotherapy (NAC) for different subtypes of locally advanced breast carcinoma using diffusion-weighted imaging (DWI). METHODS: We conducted an institutional review board-approved prospective clinical study of 142 patients with locally advanced breast carcinoma. All patients underwent conventional MR and DW examinations prior to treatment and after first, second, third, fourth, sixth and eighth cycle of NAC. The response to NAC was classified into a pathologic complete response (pCR) and a non-pCR group. DWI parameters were compared between two groups, and the optimal time window for predicting tumor response was established for each chemotherapy regimen. RESULTS: For all the genomic subtypes, there were significant differences in baseline ADC value between pCR and non-pCR group (p < 0.05). The time point prior to treatment could be considered as the ideal time point regardless of genomic subtype. In the group that started with taxanes or anthracyclines, for Luminal A or Luminal B subtype, postT1 could be used as the ideal time point during chemotherapy; for Basal-like or HER2-enriched subtype, postT2 as the ideal time point during chemotherapy. In the group that started with taxanes and anthracyclines, for HER2-enriched, Luminal B or Basal-like subtype, postT1 could be used as the ideal time point during chemotherapy; for Luminal A subtype, postT2 as the ideal time point during chemotherapy. CONCLUSIONS: The time point prior to treatment can be considered as the optimal time point regardless of genomic subtype. For each chemotherapy regimen, the optimal time point during chemotherapy varies across different genomic subtypes. BioMed Central 2018-10-29 /pmc/articles/PMC6206724/ /pubmed/30373679 http://dx.doi.org/10.1186/s40644-018-0173-5 Text en © The Author(s). 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Article Yuan, Li Li, Jian-Jun Li, Chang-Qing Yan, Cheng-Gong Cheng, Ze-Long Wu, Yuan-Kui Hao, Peng Lin, Bing-Quan Xu, Yi-Kai Diffusion-weighted MR imaging of locally advanced breast carcinoma: the optimal time window of predicting the early response to neoadjuvant chemotherapy |
title | Diffusion-weighted MR imaging of locally advanced breast carcinoma: the optimal time window of predicting the early response to neoadjuvant chemotherapy |
title_full | Diffusion-weighted MR imaging of locally advanced breast carcinoma: the optimal time window of predicting the early response to neoadjuvant chemotherapy |
title_fullStr | Diffusion-weighted MR imaging of locally advanced breast carcinoma: the optimal time window of predicting the early response to neoadjuvant chemotherapy |
title_full_unstemmed | Diffusion-weighted MR imaging of locally advanced breast carcinoma: the optimal time window of predicting the early response to neoadjuvant chemotherapy |
title_short | Diffusion-weighted MR imaging of locally advanced breast carcinoma: the optimal time window of predicting the early response to neoadjuvant chemotherapy |
title_sort | diffusion-weighted mr imaging of locally advanced breast carcinoma: the optimal time window of predicting the early response to neoadjuvant chemotherapy |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6206724/ https://www.ncbi.nlm.nih.gov/pubmed/30373679 http://dx.doi.org/10.1186/s40644-018-0173-5 |
work_keys_str_mv | AT yuanli diffusionweightedmrimagingoflocallyadvancedbreastcarcinomatheoptimaltimewindowofpredictingtheearlyresponsetoneoadjuvantchemotherapy AT lijianjun diffusionweightedmrimagingoflocallyadvancedbreastcarcinomatheoptimaltimewindowofpredictingtheearlyresponsetoneoadjuvantchemotherapy AT lichangqing diffusionweightedmrimagingoflocallyadvancedbreastcarcinomatheoptimaltimewindowofpredictingtheearlyresponsetoneoadjuvantchemotherapy AT yanchenggong diffusionweightedmrimagingoflocallyadvancedbreastcarcinomatheoptimaltimewindowofpredictingtheearlyresponsetoneoadjuvantchemotherapy AT chengzelong diffusionweightedmrimagingoflocallyadvancedbreastcarcinomatheoptimaltimewindowofpredictingtheearlyresponsetoneoadjuvantchemotherapy AT wuyuankui diffusionweightedmrimagingoflocallyadvancedbreastcarcinomatheoptimaltimewindowofpredictingtheearlyresponsetoneoadjuvantchemotherapy AT haopeng diffusionweightedmrimagingoflocallyadvancedbreastcarcinomatheoptimaltimewindowofpredictingtheearlyresponsetoneoadjuvantchemotherapy AT linbingquan diffusionweightedmrimagingoflocallyadvancedbreastcarcinomatheoptimaltimewindowofpredictingtheearlyresponsetoneoadjuvantchemotherapy AT xuyikai diffusionweightedmrimagingoflocallyadvancedbreastcarcinomatheoptimaltimewindowofpredictingtheearlyresponsetoneoadjuvantchemotherapy |