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Diffusion Tensor Imaging for Assessment of Response to Neoadjuvant Chemotherapy in Patients With Breast Cancer
In this study, the prognostic significance of tumor metrics derived from diffusion tensor imaging (DTI) was evaluated in patients with locally advanced breast cancer undergoing neoadjuvant therapy. DTI and contrast-enhanced magnetic resonance imaging were acquired at 1.5 T in 34 patients before trea...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Grapho Publications, LLC
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5844277/ https://www.ncbi.nlm.nih.gov/pubmed/29527574 http://dx.doi.org/10.18383/j.tom.2016.00271 |
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author | Wilmes, Lisa J. Li, Wen Shin, Hee Jung Newitt, David C. Proctor, Evelyn Harnish, Roy Hylton, Nola M. |
author_facet | Wilmes, Lisa J. Li, Wen Shin, Hee Jung Newitt, David C. Proctor, Evelyn Harnish, Roy Hylton, Nola M. |
author_sort | Wilmes, Lisa J. |
collection | PubMed |
description | In this study, the prognostic significance of tumor metrics derived from diffusion tensor imaging (DTI) was evaluated in patients with locally advanced breast cancer undergoing neoadjuvant therapy. DTI and contrast-enhanced magnetic resonance imaging were acquired at 1.5 T in 34 patients before treatment and after 3 cycles of taxane-based therapy (early treatment). Tumor fractional anisotropy (FA), principal eigenvalues (λ1, λ2, and λ3), and apparent diffusion coefficient (ADC) were estimated for tumor regions of interest drawn on DTI data. The association between DTI metrics and final tumor volume change was evaluated with Spearman rank correlation. DTI metrics were investigated as predictors of pathological complete response (pCR) by calculating the area under the receiver operating characteristic curve (AUC). Early changes in tumor FA and ADC significantly correlated with final tumor volume change post therapy (ρ = −0.38, P = .03 and ρ = −0.71, P < .001, respectively). Pretreatment tumor ADC was significantly lower in the pCR than in the non-pCR group (P = .04). At early treatment, patients with pCR had significantly higher percent changes of tumor λ1, λ2, λ3, and ADC than those without pCR. The AUCs for early percent changes in tumor FA and ADC were 0.60 and 0.83, respectively. The early percent changes in tumor eigenvalues and ADC were the strongest DTI-derived predictors of pCR. Although early percent change in tumor FA had a weak association with pCR, the significant correlation with final tumor volume change suggests that this metric changes with therapy and may merit further evaluation. |
format | Online Article Text |
id | pubmed-5844277 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Grapho Publications, LLC |
record_format | MEDLINE/PubMed |
spelling | pubmed-58442772018-03-09 Diffusion Tensor Imaging for Assessment of Response to Neoadjuvant Chemotherapy in Patients With Breast Cancer Wilmes, Lisa J. Li, Wen Shin, Hee Jung Newitt, David C. Proctor, Evelyn Harnish, Roy Hylton, Nola M. Tomography Research Articles In this study, the prognostic significance of tumor metrics derived from diffusion tensor imaging (DTI) was evaluated in patients with locally advanced breast cancer undergoing neoadjuvant therapy. DTI and contrast-enhanced magnetic resonance imaging were acquired at 1.5 T in 34 patients before treatment and after 3 cycles of taxane-based therapy (early treatment). Tumor fractional anisotropy (FA), principal eigenvalues (λ1, λ2, and λ3), and apparent diffusion coefficient (ADC) were estimated for tumor regions of interest drawn on DTI data. The association between DTI metrics and final tumor volume change was evaluated with Spearman rank correlation. DTI metrics were investigated as predictors of pathological complete response (pCR) by calculating the area under the receiver operating characteristic curve (AUC). Early changes in tumor FA and ADC significantly correlated with final tumor volume change post therapy (ρ = −0.38, P = .03 and ρ = −0.71, P < .001, respectively). Pretreatment tumor ADC was significantly lower in the pCR than in the non-pCR group (P = .04). At early treatment, patients with pCR had significantly higher percent changes of tumor λ1, λ2, λ3, and ADC than those without pCR. The AUCs for early percent changes in tumor FA and ADC were 0.60 and 0.83, respectively. The early percent changes in tumor eigenvalues and ADC were the strongest DTI-derived predictors of pCR. Although early percent change in tumor FA had a weak association with pCR, the significant correlation with final tumor volume change suggests that this metric changes with therapy and may merit further evaluation. Grapho Publications, LLC 2016-12 /pmc/articles/PMC5844277/ /pubmed/29527574 http://dx.doi.org/10.18383/j.tom.2016.00271 Text en © 2016 The Authors. Published by Grapho Publications, LLC https://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY 4.0 license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Research Articles Wilmes, Lisa J. Li, Wen Shin, Hee Jung Newitt, David C. Proctor, Evelyn Harnish, Roy Hylton, Nola M. Diffusion Tensor Imaging for Assessment of Response to Neoadjuvant Chemotherapy in Patients With Breast Cancer |
title | Diffusion Tensor Imaging for Assessment of Response to Neoadjuvant Chemotherapy in Patients With Breast Cancer |
title_full | Diffusion Tensor Imaging for Assessment of Response to Neoadjuvant Chemotherapy in Patients With Breast Cancer |
title_fullStr | Diffusion Tensor Imaging for Assessment of Response to Neoadjuvant Chemotherapy in Patients With Breast Cancer |
title_full_unstemmed | Diffusion Tensor Imaging for Assessment of Response to Neoadjuvant Chemotherapy in Patients With Breast Cancer |
title_short | Diffusion Tensor Imaging for Assessment of Response to Neoadjuvant Chemotherapy in Patients With Breast Cancer |
title_sort | diffusion tensor imaging for assessment of response to neoadjuvant chemotherapy in patients with breast cancer |
topic | Research Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5844277/ https://www.ncbi.nlm.nih.gov/pubmed/29527574 http://dx.doi.org/10.18383/j.tom.2016.00271 |
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