| Literature DB >> 27439401 |
Sungmin Woo1, Sang Youn Kim1, Jeong Yeon Cho1,2, Seung Hyup Kim1,2.
Abstract
Background Length of capsular contact (LCC) is a promising biomarker for predicting extracapsular extension (ECE), but the most optimal magnetic resonance imaging (MRI) sequence for measuring LCC is yet to be determined. Purpose To evaluate LCC using different MRI sequences for determining ECE in prostate cancer. Material and Methods A total of 185 patients underwent prostate MRI followed by radical prostatectomy. LCC was measured separately on T2-weighted (T2W) images, apparent diffusion coefficient (ADC) maps, and dynamic contrast-enhanced (DCE) MRI. LCCs (LCCT2, LCCADC, LCCDCE, and LCCmax [greatest value of 3 LCCs]) were compared between sequences using Wilcoxon signed rank test and was tested for determining ECE using the Mann-Whitney U test, ROC curve analysis, and logistic regression analysis. Results There were no significant differences among LCCs ( P = 0.333-0.837). All LCCs were significantly greater in patients with ECE ( P < 0.001). The optimal threshold value for predicting ECE was >14, >13, >12, and >14 mm for LCCT2, LCCADC, LCCDCE, and LCCmax, respectively. LCCmax yielded the highest area under the curve (0.895) which was significantly greater than that by LCCADC (0.858, P = 0.030). Otherwise, there were no significant difference between LCCs ( P = 0.052-0.985). At univariate analysis, age, clinical stage, PSA, Gleason score, and all LCCs were significantly associated with ECE ( P < 0.001-0.040). At multivariate analysis, GS ( P ≤ 0.008) and all LCCs ( P < 0.001) were independently predictive factors. Conclusion LCC measured on any sequence was significantly different in patients with and without ECE and was independently associated with the presence of ECE. Although LCCmax showed the greatest ability to predict ECE, there was relatively equivalent performance among different MRI sequences.Entities:
Keywords: Prostate cancer; extracapsular extension; length of capsular contact; magnetic resonance imaging
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Year: 2016 PMID: 27439401 DOI: 10.1177/0284185116658684
Source DB: PubMed Journal: Acta Radiol ISSN: 0284-1851 Impact factor: 1.990