OBJECTIVE: The purpose of this article is to evaluate the relationship between apparent diffusion coefficient (ADC) values, tumor volume, and total Gleason grade in patients with prostate cancer before radical prostatectomy. MATERIALS AND METHODS: A total of 110 patients with prostate cancer who had undergone endorectal prostate MRI at 1.5 T before radical prostatectomy were included. ADC values were derived by drawing a region of interest on the histologically confirmed tumors. Tumor volume was obtained by manual segmentation on T2-weighted images (T2WIs) and ADC maps. The relationship between the ADC value or tumor volume and the Gleason grade was assessed by using multivariate mixed linear and effect models. Multivariate analysis was performed to evaluate the accuracy of ADC and tumor volume in determining the aggressiveness of prostate cancer. RESULTS: A total of 197 tumors were studied; 128 (65%) tumors were found in the peripheral zone and 69 (35%) were found in the central gland. The ADC value was found to be negatively correlated with the Gleason grade (r = -0.39 for peripheral zone cancer). Higher ADC values were found to be associated with lower Gleason grades in the peripheral zone prostate cancers. No association was found in the central zone prostate cancers. Both ADC values and tumor volumes were found to significantly predict tumor aggressiveness, specifically in the peripheral zone (area under the curve, 0.78). CONCLUSION: ADC values were found to be negatively correlated with the postsurgical Gleason grade in patients with prostate cancer. Our results show that ADC values might help to predict prostate cancer, especially for tumors in the peripheral zone. Given the substantial overlap in the ADC values, the addition of other MR parameters, such as volumetry, and technical improvements in diffusion-weighted imaging might improve accuracy in the stratification of patients.
OBJECTIVE: The purpose of this article is to evaluate the relationship between apparent diffusion coefficient (ADC) values, tumor volume, and total Gleason grade in patients with prostate cancer before radical prostatectomy. MATERIALS AND METHODS: A total of 110 patients with prostate cancer who had undergone endorectal prostate MRI at 1.5 T before radical prostatectomy were included. ADC values were derived by drawing a region of interest on the histologically confirmed tumors. Tumor volume was obtained by manual segmentation on T2-weighted images (T2WIs) and ADC maps. The relationship between the ADC value or tumor volume and the Gleason grade was assessed by using multivariate mixed linear and effect models. Multivariate analysis was performed to evaluate the accuracy of ADC and tumor volume in determining the aggressiveness of prostate cancer. RESULTS: A total of 197 tumors were studied; 128 (65%) tumors were found in the peripheral zone and 69 (35%) were found in the central gland. The ADC value was found to be negatively correlated with the Gleason grade (r = -0.39 for peripheral zone cancer). Higher ADC values were found to be associated with lower Gleason grades in the peripheral zone prostate cancers. No association was found in the central zone prostate cancers. Both ADC values and tumor volumes were found to significantly predict tumor aggressiveness, specifically in the peripheral zone (area under the curve, 0.78). CONCLUSION: ADC values were found to be negatively correlated with the postsurgical Gleason grade in patients with prostate cancer. Our results show that ADC values might help to predict prostate cancer, especially for tumors in the peripheral zone. Given the substantial overlap in the ADC values, the addition of other MR parameters, such as volumetry, and technical improvements in diffusion-weighted imaging might improve accuracy in the stratification of patients.
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: Sonia Gaur; Stephanie Harmon; Lauren Rosenblum; Matthew D Greer; Sherif Mehralivand; Mehmet Coskun; Maria J Merino; Bradford J Wood; Joanna H Shih; Peter A Pinto; Peter L Choyke; Baris Turkbey Journal: AJR Am J Roentgenol Date: 2018-05-07 Impact factor: 3.959
Authors: Sonia Gaur; Stephanie Harmon; Rajan T Gupta; Daniel J Margolis; Nathan Lay; Sherif Mehralivand; Maria J Merino; Bradford J Wood; Peter A Pinto; Joanna H Shih; Peter L Choyke; Baris Turkbey Journal: Acad Radiol Date: 2018-04-25 Impact factor: 3.173