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Prostate Cancer Prostatic Dis ; 19(2): 168-73, 2016 06.
Article in English | MEDLINE | ID: mdl-26754261

ABSTRACT

BACKGROUND: Magnetic resonance imaging (MRI) is emerging as a robust, noninvasive method for detecting and characterizing prostate cancer (PCa), but limitations remain in its ability to distinguish cancerous from non-cancerous tissue. We evaluated the performance of a novel MRI technique, restriction spectrum imaging (RSI-MRI), to quantitatively detect and grade PCa compared with current standard-of-care MRI. METHODS: In a retrospective evaluation of 33 patients with biopsy-proven PCa who underwent RSI-MRI and standard MRI before radical prostatectomy, receiver-operating characteristic (ROC) curves were performed for RSI-MRI and each quantitative MRI term, with area under the ROC curve (AUC) used to compare each term's ability to differentiate between PCa and normal prostate. Spearman rank-order correlations were performed to assess each term's ability to predict PCa grade in the radical prostatectomy specimens. RESULTS: RSI-MRI demonstrated superior differentiation of PCa from normal tissue, with AUC of 0.94 and 0.85 for RSI-MRI and conventional diffusion MRI, respectively (P=0.04). RSI-MRI also demonstrated superior performance in predicting PCa aggressiveness, with Spearman rank-order correlation coefficients of 0.53 (P=0.002) and -0.42 (P=0.01) for RSI-MRI and conventional diffusion MRI, respectively, with tumor grade. CONCLUSIONS: RSI-MRI significantly improves upon current noninvasive PCa imaging and may potentially enhance its diagnosis and characterization.


Subject(s)
Magnetic Resonance Imaging/methods , Prostatic Neoplasms/diagnostic imaging , Prostatic Neoplasms/pathology , Aged , Humans , Image Processing, Computer-Assisted , Male , Middle Aged , Neoplasm Grading , Neoplasm Staging , Prostatic Neoplasms/surgery , ROC Curve , Retrospective Studies , Tumor Burden
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