Histogram analysis of stretched‐exponential and monoexponential diffusion‐weighted imaging models for distinguishing low and intermediate/high gleason scores in prostate carcinoma

Background Noninvasive measures to evaluate the aggressiveness of prostate carcinoma (PCa) may benefit patients. Purpose To assess the value of stretched‐exponential and monoexponential diffusion‐weighted imaging (DWI) for predicting the aggressiveness of PCa. Study Type Retrospective study. Subject...

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Vydáno v:Journal of magnetic resonance imaging Ročník 48; číslo 2; s. 491 - 498
Hlavní autoři: Liu, Wei, Liu, Xiao H., Tang, Wei, Gao, Hong B., Zhou, Bing N., Zhou, Liang P.
Médium: Journal Article
Jazyk:angličtina
Vydáno: United States Wiley Subscription Services, Inc 01.08.2018
Témata:
aggressiveness
Correlation analysis
Diffusion
Diffusion coefficient
diffusion‐weighted imaging
Field strength
histogram analysis
Imaging
Magnetic resonance imaging
monoexponential model
Patients
Prostate
Prostate cancer
Prostate carcinoma
Regression analysis
Statistical analysis
Statistical tests
stretched exponential model
Tumors
monoexponential model
histogram analysis
diffusion-weighted imaging
prostate carcinoma
aggressiveness
stretched exponential model
ISSN:1053-1807, 1522-2586, 1522-2586
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Shrnutí:Background Noninvasive measures to evaluate the aggressiveness of prostate carcinoma (PCa) may benefit patients. Purpose To assess the value of stretched‐exponential and monoexponential diffusion‐weighted imaging (DWI) for predicting the aggressiveness of PCa. Study Type Retrospective study. Subjects Seventy‐five patients with PCa. Field Strength 3T DWI examinations were performed using b‐values of 0, 500, 1000, and 2000 s/mm2. Assessment The research were based on entire‐tumor histogram analysis and the reference standard was radical prostectomy. Statistical Tests The correlation analysis was programmed with Spearman's rank‐order analysis between the histogram variables and Gleason grade group (GG). Receiver operating characteristic (ROC) regression was used to analyze the ability of these histogram variables to differentiate low‐grade (LG) from intermediate/high‐grade (HG) PCa. Results The percentiles and mean of apparent diffusion coefficient (ADC) and distributed diffusion coefficient (DDC) were correlated with GG (ρ: 0.414–0.593), while there was no significant relation among α value, skewnesses, and kurtosises with GG (ρ:0.034–0.323). HG tumors (ADC:484 ± 136, 592 ± 139, 670 ± 144, 788 ± 146, 895 ± 141 mm2/s; DDC: 410 ± 142, 532 ± 172, 666 ± 193, 786 ± 196, 914 ± 181 mm2/s) had lower values in the 10th, 25th, 50th, 75th percentiles and means than LG tumors (ADC: 644 ± 779, 737 ± 84, 836 ± 83, 919 ± 82, 997 ± 107 mm2/s; DDC: 552 ± 82, 680 ± 94, 829 ± 112, 931 ± 106, 1045 ± 100 mm2/s). However, there was no difference between LG and HG tumors in α value (0.671 ± 0.041 vs. 0.633 ± 0.114), kurtosises (ADC 0.09 vs. 0.086; DDC –0.033 vs. –0.317), or skewnesses (ADC –0.036 vs. 0.073; DDC –0.063 vs. 0.136). The above statistics were P < 0.01. ADC10 with AUC = 0.840 and DDC10 with AUC = 0.799 were similar in discriminating between LG and HG PCa at P < 0.05. Data Conclusion Histogram variables of DDC and ADC may predict the aggressiveness of PCa, while α value does not. The abilities of ADC10 and DDC10 to discriminate LG from HG tumors were similar, and both better than their respective means. Level of Evidence: 3 Technical Efficacy: Stage 1 J. MAGN. RESON. IMAGING 2018;48:491–498.
Bibliografie:The first two authors contributed equally to this work.
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ISSN:1053-1807
1522-2586
1522-2586
DOI:10.1002/jmri.25958