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J Magn Reson Imaging ; 46(6): 1786-1796, 2017 12.
Article in English | MEDLINE | ID: mdl-28383776

ABSTRACT

PURPOSE: To quantify and compare the histological components and architectural patterns of Gleason grades in cancerous areas with restriction on apparent diffusion coefficient (ADC) maps. MATERIALS AND METHODS: Twelve consecutive cases with 14 separate ADC restriction areas, positive for cancer in the peripheral zone (PZ) and transition zone (TZ) were included. All had 3 Tesla MRI and radical prostatectomy. Ten regions of interest (ROIs) within and outside the 14 ADC restriction areas positive for cancer were selected. For each ROI, we performed quantitative analysis of (a) prostate benign and malignant histological component surface ratios, including stroma, glands, epithelium, lumen, cellular nuclei; (b) percent of Gleason grades and measures of ADC values. Means of histological components according to ADC restriction for cancerous area were compared with analyses of variance with repeated measures. RESULTS: Independent predictors of the probability of cancer were median epithelium/ROI ratio (P = 0.001) and nuclei/ROI ratio (P = 0.03). Independent predictors of the probability of ADC restriction were malignant glands/ROI and luminal space/ROI (P < 0.0001). Effect of malignant glands/ROI area was different according to the localization of the ROI (P = 0.03). We observed an overall difference between the means for all of the histological components for the comparison of true positive and false negative (P < 0.0001), except for the percent of Gleason grade 4 (P = 0.18). In TZ cancers, a predominant grade 3 pattern was associated with low ADC values. In PZ cancers, a predominant grade 4 pattern was associated with low ADC values. CONCLUSION: Determinants of low ADC were high ratio of malignant glands/ROI area which may be seen in Gleason grades 3 or 4 cancers. LEVEL OF EVIDENCE: 3 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2017;46:1786-1796.


Subject(s)
Diffusion Magnetic Resonance Imaging/methods , Image Processing, Computer-Assisted/methods , Prostatic Neoplasms/diagnostic imaging , Prostatic Neoplasms/pathology , Aged , Humans , Image Interpretation, Computer-Assisted/methods , Male , Neoplasm Grading , Prostate/diagnostic imaging , Prostate/pathology , Reproducibility of Results
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