Advanced Diffusion-weighted Imaging Modeling for Prostate Cancer Characterization: Correlation with Quantitative Histopathologic Tumor Tissue Composition-A Hypothesis-generating Study.

Advanced Diffusion-weighted Imaging Modeling for Prostate Cancer Characterization: Correlation with Quantitative Histopathologic Tumor Tissue Composition-A Hypothesis-generating Study.

Radiology. 2017 Nov 08;:170904

Authors: Hectors SJ, Semaan S, Song C, Lewis S, Haines GK, Tewari A, Rastinehad AR, Taouli B

Abstract
Purpose To correlate quantitative diffusion-weighted imaging (DWI) parameters derived from conventional monoexponential DWI, stretched exponential DWI, diffusion kurtosis imaging (DKI), and diffusion-tensor imaging (DTI) with quantitative histopathologic tumor tissue composition in prostate cancer in a preliminary hypothesis-generating study. Materials and Methods This retrospective institutional review board-approved study included 24 patients with prostate cancer (mean age, 63 years) who underwent magnetic resonance (MR) imaging, including high-b-value DWI and DTI at 3.0 T, before prostatectomy. The following parameters were calculated in index tumors and nontumoral peripheral zone (PZ): apparent diffusion coefficient (ADC) obtained with monoexponential fit (ADCME), ADC obtained with stretched exponential modeling (ADCSE), anomalous exponent (α) obtained at stretched exponential DWI, ADC obtained with DKI modeling (ADCDKI), kurtosis with DKI, ADC obtained with DTI (ADCDTI), and fractional anisotropy (FA) at DTI. Parameters in prostate cancer and PZ were compared by using paired Student t tests. Pearson correlations between tumor DWI and quantitative histologic parameters (nuclear, cytoplasmic, cellular, stromal, luminal fractions) were determined. Results All DWI parameters were significantly different between prostate cancer and PZ (P < .012). ADCME, ADCSE, and ADCDKI all showed significant negative correlation with cytoplasmic and cellular fractions (r = 0.546 to -0.435; P < .034) and positive correlation with stromal fractions (r = 0.619-0.669; P < .001). ADCDTI and FA showed correlation only with stromal fraction (r = 0.512 and -0.413, respectively; P < .045). α did not correlate with histologic parameters, whereas kurtosis showed significant correlations with histopathologic parameters (r = 0.487, 0.485, -0.422 for cytoplasmic, cellular, and stromal fractions, respectively; P < .040). Conclusion Advanced DWI methods showed significant correlations with histopathologic tissue composition in prostate cancer. These findings should be validated in a larger study. (©) RSNA, 2017 Online supplemental material is available for this article.

PMID: 29117481 [PubMed - as supplied by publisher]

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