Diffusion Tensor Imaging for Assessment of Response to Neoadjuvant Chemotherapy in Patients with Breast Cancer
Author(s) -
Lisa J. Wilmes,
Wen Li,
Hee Jung Shin,
David C. Newitt,
Evelyn Proctor,
Roy Harnish,
Nola M. Hylton
Publication year - 2016
Publication title -
tomography
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.074
H-Index - 9
eISSN - 2379-139X
pISSN - 2379-1381
DOI - 10.18383/j.tom.2016.00271
Subject(s) - diffusion mri , effective diffusion coefficient , medicine , fractional anisotropy , breast cancer , rank correlation , receiver operating characteristic , magnetic resonance imaging , taxane , nuclear medicine , oncology , cancer , radiology , machine learning , computer science
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.
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