Literature DB >> 29412492

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

Wei Liu1,2, Xiao H Liu2,3, Wei Tang2,3, Hong B Gao2, Bing N Zhou2, Liang P Zhou2,3.   

Abstract

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.
© 2018 International Society for Magnetic Resonance in Medicine.

Entities:  

Keywords:  aggressiveness; diffusion-weighted imaging; histogram analysis; monoexponential model; prostate carcinoma; stretched exponential model

Mesh:

Year:  2018        PMID: 29412492     DOI: 10.1002/jmri.25958

Source DB:  PubMed          Journal:  J Magn Reson Imaging        ISSN: 1053-1807            Impact factor:   4.813


  8 in total

1.  Clinical impact of ultra-high b-value (3000 s/mm2) diffusion-weighted magnetic resonance imaging in prostate cancer at 3T: comparison with b-value of 2000 s/mm2.

Authors:  Tsutomu Tamada; Ayumu Kido; Yu Ueda; Mitsuru Takeuchi; Takeshi Fukunaga; Teruki Sone; Akira Yamamoto
Journal:  Br J Radiol       Date:  2021-09-24       Impact factor: 3.039

Review 2.  Diffusion-weighted imaging in prostate cancer.

Authors:  Tsutomu Tamada; Yu Ueda; Yoshiko Ueno; Yuichi Kojima; Ayumu Kido; Akira Yamamoto
Journal:  MAGMA       Date:  2021-09-07       Impact factor: 2.533

3.  Evaluation of microvascular invasion of hepatocellular carcinoma using whole-lesion histogram analysis with the stretched-exponential diffusion model.

Authors:  Hongxiang Li; LiLi Wang; Jing Zhang; Qing Duan; Yikai Xu; Yunjing Xue
Journal:  Br J Radiol       Date:  2022-01-07       Impact factor: 3.629

4.  Histogram analysis from stretched exponential model on diffusion-weighted imaging: evaluation of clinically significant prostate cancer.

Authors:  EunJu Kim; Chan Kyo Kim; Hyun Soo Kim; Dong Pyo Jang; In Young Kim; Jinwoo Hwang
Journal:  Br J Radiol       Date:  2020-01-09       Impact factor: 3.039

5.  Cervical Cancer: Associations between Metabolic Parameters and Whole Lesion Histogram Analysis Derived from Simultaneous 18F-FDG-PET/MRI.

Authors:  Hans-Jonas Meyer; Sandra Purz; Osama Sabri; Alexey Surov
Journal:  Contrast Media Mol Imaging       Date:  2018-07-30       Impact factor: 3.161

6.  Non-Gaussian models of diffusion weighted imaging for detection and characterization of prostate cancer: a systematic review and meta-analysis.

Authors:  V Brancato; C Cavaliere; M Salvatore; S Monti
Journal:  Sci Rep       Date:  2019-11-14       Impact factor: 4.379

7.  The Histogram Analysis of Intravoxel Incoherent Motion-Kurtosis Model in the Diagnosis and Grading of Prostate Cancer-A Preliminary Study.

Authors:  Chunmei Li; Lu Yu; Yuwei Jiang; Yadong Cui; Ying Liu; Kaining Shi; Huimin Hou; Ming Liu; Wei Zhang; Jintao Zhang; Chen Zhang; Min Chen
Journal:  Front Oncol       Date:  2021-10-27       Impact factor: 6.244

8.  Discrimination between clinical significant and insignificant prostate cancer with apparent diffusion coefficient - a systematic review and meta analysis.

Authors:  Hans-Jonas Meyer; Andreas Wienke; Alexey Surov
Journal:  BMC Cancer       Date:  2020-05-27       Impact factor: 4.430

  8 in total

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