Cargando…
Diffusion-weighted MR imaging in prediction of response to neoadjuvant chemotherapy in patients with breast cancer
This study aims to evaluate the potential of apparent diffusion coefficient (ADC) derived from diffusion-weighted MR imaging for predicting the treatment response to neoadjuvant chemotherapy (NACT) in patients with breast cancer. Magnetic resonance imaging was performed prior to NACT and after two c...
Autores principales: | , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Impact Journals LLC
2017
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5668077/ https://www.ncbi.nlm.nih.gov/pubmed/29108344 http://dx.doi.org/10.18632/oncotarget.18999 |
_version_ | 1783275610820313088 |
---|---|
author | Hu, Xue-Ying Li, Ying Jin, Guan-Qiao Lai, Shao-Lv Huang, Xiang-Yang Su, Dan-Ke |
author_facet | Hu, Xue-Ying Li, Ying Jin, Guan-Qiao Lai, Shao-Lv Huang, Xiang-Yang Su, Dan-Ke |
author_sort | Hu, Xue-Ying |
collection | PubMed |
description | This study aims to evaluate the potential of apparent diffusion coefficient (ADC) derived from diffusion-weighted MR imaging for predicting the treatment response to neoadjuvant chemotherapy (NACT) in patients with breast cancer. Magnetic resonance imaging was performed prior to NACT and after two cycles of NACT. The correlation between mean ADC(pre) values, mean ADC(post) values, changes in ADC values and changes in tumor diameters after NACT was examined using Spearman rank correlation. A total of 164 breast cancers were enrolled in this study. Mean ADC(pre) values of responders ([0.85 ± 0.16] × 10(-3) mm(2)/s) and non-responders ([0.84 ± 0.21] × 10(-3) mm(2)/s) had no significant difference (P = 0.759). While mean ADC(post) value of responders was significantly higher than that of non-responders ([1.17 ± 0.37] × 10(-3) mm(2)/s vs. [1.01 ± 0.28] × 10(-3) mm(2)/s; P = 0.002). Both mean ADC(post) values (r = 0.288, P = 0.000) and changes in mean ADC values (r = 0.222, P = 0.004) were positively correlated to changes in tumor diameter after NACT, except for mean ADC(pre) values (r = 0.031, P = 0.695). Our results indicated that mean ADC(post) values and changes in ADC values after NACT might be a biological marker for assessing the efficacy of chemotherapy. |
format | Online Article Text |
id | pubmed-5668077 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Impact Journals LLC |
record_format | MEDLINE/PubMed |
spelling | pubmed-56680772017-11-04 Diffusion-weighted MR imaging in prediction of response to neoadjuvant chemotherapy in patients with breast cancer Hu, Xue-Ying Li, Ying Jin, Guan-Qiao Lai, Shao-Lv Huang, Xiang-Yang Su, Dan-Ke Oncotarget Clinical Research Paper This study aims to evaluate the potential of apparent diffusion coefficient (ADC) derived from diffusion-weighted MR imaging for predicting the treatment response to neoadjuvant chemotherapy (NACT) in patients with breast cancer. Magnetic resonance imaging was performed prior to NACT and after two cycles of NACT. The correlation between mean ADC(pre) values, mean ADC(post) values, changes in ADC values and changes in tumor diameters after NACT was examined using Spearman rank correlation. A total of 164 breast cancers were enrolled in this study. Mean ADC(pre) values of responders ([0.85 ± 0.16] × 10(-3) mm(2)/s) and non-responders ([0.84 ± 0.21] × 10(-3) mm(2)/s) had no significant difference (P = 0.759). While mean ADC(post) value of responders was significantly higher than that of non-responders ([1.17 ± 0.37] × 10(-3) mm(2)/s vs. [1.01 ± 0.28] × 10(-3) mm(2)/s; P = 0.002). Both mean ADC(post) values (r = 0.288, P = 0.000) and changes in mean ADC values (r = 0.222, P = 0.004) were positively correlated to changes in tumor diameter after NACT, except for mean ADC(pre) values (r = 0.031, P = 0.695). Our results indicated that mean ADC(post) values and changes in ADC values after NACT might be a biological marker for assessing the efficacy of chemotherapy. Impact Journals LLC 2017-07-05 /pmc/articles/PMC5668077/ /pubmed/29108344 http://dx.doi.org/10.18632/oncotarget.18999 Text en Copyright: © 2017 Hu et al. http://creativecommons.org/licenses/by/3.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/) 3.0 (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Clinical Research Paper Hu, Xue-Ying Li, Ying Jin, Guan-Qiao Lai, Shao-Lv Huang, Xiang-Yang Su, Dan-Ke Diffusion-weighted MR imaging in prediction of response to neoadjuvant chemotherapy in patients with breast cancer |
title | Diffusion-weighted MR imaging in prediction of response to neoadjuvant chemotherapy in patients with breast cancer |
title_full | Diffusion-weighted MR imaging in prediction of response to neoadjuvant chemotherapy in patients with breast cancer |
title_fullStr | Diffusion-weighted MR imaging in prediction of response to neoadjuvant chemotherapy in patients with breast cancer |
title_full_unstemmed | Diffusion-weighted MR imaging in prediction of response to neoadjuvant chemotherapy in patients with breast cancer |
title_short | Diffusion-weighted MR imaging in prediction of response to neoadjuvant chemotherapy in patients with breast cancer |
title_sort | diffusion-weighted mr imaging in prediction of response to neoadjuvant chemotherapy in patients with breast cancer |
topic | Clinical Research Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5668077/ https://www.ncbi.nlm.nih.gov/pubmed/29108344 http://dx.doi.org/10.18632/oncotarget.18999 |
work_keys_str_mv | AT huxueying diffusionweightedmrimaginginpredictionofresponsetoneoadjuvantchemotherapyinpatientswithbreastcancer AT liying diffusionweightedmrimaginginpredictionofresponsetoneoadjuvantchemotherapyinpatientswithbreastcancer AT jinguanqiao diffusionweightedmrimaginginpredictionofresponsetoneoadjuvantchemotherapyinpatientswithbreastcancer AT laishaolv diffusionweightedmrimaginginpredictionofresponsetoneoadjuvantchemotherapyinpatientswithbreastcancer AT huangxiangyang diffusionweightedmrimaginginpredictionofresponsetoneoadjuvantchemotherapyinpatientswithbreastcancer AT sudanke diffusionweightedmrimaginginpredictionofresponsetoneoadjuvantchemotherapyinpatientswithbreastcancer |