PURPOSE: To investigate differences in apparent diffusion coefficient (ADC) and T2 values between dense and sparse regions in prostate cancer. MATERIALS AND METHODS: Eighteen patients (median age, 61 years; range, 44-72 years) gave informed consent for this retrospective Research Ethics Board-approved study. Prior to radical prostatectomy, ADC (b value, 600 sec/mm(2)) and T2 maps were obtained by using 1.5-T magnetic resonance (MR) imaging. Twenty-eight peripheral zone (PZ) tumors were reviewed by using whole-mount histologic findings, and regions assessed to contain primarily (>60%) normal PZ tissue were delineated. Tumors were categorized as "sparse" if more than 50% of their cross-sectional areas were these primarily normal PZ regions and were considered "dense" otherwise. Normal PZ tissue was outlined separately on the same section. Tumor and normal tissue outlines were transferred to corresponding ADC and T2 maps, and median values were calculated. Values were compared by using multiple regression analysis. Matched-pair tumor-to-normal tissue differences and log(2)-transformed ratios were assessed by using nonparametric tests. RESULTS: Thirty-six percent (10 of 28) of tumors were sparse; 64% (18 of 28) were dense. For both overall and intrapatient comparisons, dense tumors had significantly lower ADC and T2 values than normal PZ tissue (P < .05), but no significant differences were observed between sparse tumors and normal tissue. Log(2)-transformed tumor-to-normal tissue ratios were significantly less than zero for dense tumors for both ADC and T2 (P < .01) measurements but not for sparse tumors. Both matched-pair differences and log(2)-transformed ratios were significantly different between sparse and dense tumors (P < .01). ADC and T2 values were moderately correlated (Pearson correlation coefficient range, r = 0.770-0.804). CONCLUSION: Sparse prostate tumors have similar ADC and T2 values to those of normal PZ tissue. This may limit MR imaging detection and the assessment of tumor volume of some cancers. RSNA, 2008
PURPOSE: To investigate differences in apparent diffusion coefficient (ADC) and T2 values between dense and sparse regions in prostate cancer. MATERIALS AND METHODS: Eighteen patients (median age, 61 years; range, 44-72 years) gave informed consent for this retrospective Research Ethics Board-approved study. Prior to radical prostatectomy, ADC (b value, 600 sec/mm(2)) and T2 maps were obtained by using 1.5-T magnetic resonance (MR) imaging. Twenty-eight peripheral zone (PZ) tumors were reviewed by using whole-mount histologic findings, and regions assessed to contain primarily (>60%) normal PZ tissue were delineated. Tumors were categorized as "sparse" if more than 50% of their cross-sectional areas were these primarily normal PZ regions and were considered "dense" otherwise. Normal PZ tissue was outlined separately on the same section. Tumor and normal tissue outlines were transferred to corresponding ADC and T2 maps, and median values were calculated. Values were compared by using multiple regression analysis. Matched-pair tumor-to-normal tissue differences and log(2)-transformed ratios were assessed by using nonparametric tests. RESULTS: Thirty-six percent (10 of 28) of tumors were sparse; 64% (18 of 28) were dense. For both overall and intrapatient comparisons, dense tumors had significantly lower ADC and T2 values than normal PZ tissue (P < .05), but no significant differences were observed between sparse tumors and normal tissue. Log(2)-transformed tumor-to-normal tissue ratios were significantly less than zero for dense tumors for both ADC and T2 (P < .01) measurements but not for sparse tumors. Both matched-pair differences and log(2)-transformed ratios were significantly different between sparse and dense tumors (P < .01). ADC and T2 values were moderately correlated (Pearson correlation coefficient range, r = 0.770-0.804). CONCLUSION: Sparse prostate tumors have similar ADC and T2 values to those of normal PZ tissue. This may limit MR imaging detection and the assessment of tumor volume of some cancers. RSNA, 2008
Authors: Hashim U Ahmed; Oguz Akin; Jonathan A Coleman; Sarah Crane; Mark Emberton; Larry Goldenberg; Hedvig Hricak; Mike W Kattan; John Kurhanewicz; Caroline M Moore; Chris Parker; Thomas J Polascik; Peter Scardino; Nicholas van As; Arnauld Villers Journal: BJU Int Date: 2011-11-11 Impact factor: 5.588
Authors: Andrew B Rosenkrantz; Hersh Chandarana; Nicole Hindman; Fang-Ming Deng; James S Babb; Samir S Taneja; Christian Geppert Journal: Eur Radiol Date: 2013-06-12 Impact factor: 5.315
Authors: Aritrick Chatterjee; Roger M Bourne; Shiyang Wang; Ajit Devaraj; Alexander J Gallan; Tatjana Antic; Gregory S Karczmar; Aytekin Oto Journal: Radiology Date: 2018-02-02 Impact factor: 11.105