Literature DB >> 27300199

Differentiation of prostate cancer lesions with high and with low Gleason score by diffusion-weighted MRI.

Sebastiano Barbieri1, Michael Brönnimann1, Silvan Boxler2, Peter Vermathen1, Harriet C Thoeny3.   

Abstract

OBJECTIVES: To differentiate prostate cancer lesions with high and with low Gleason score by diffusion-weighted-MRI (DW-MRI).
METHODS: This prospective study was approved by the responsible ethics committee. DW-MRI of 84 consenting prostate and/or bladder cancer patients scheduled for radical prostatectomy were acquired and used to compute apparent diffusion coefficient (ADC), intravoxel incoherent motion (IVIM: the pure diffusion coefficient D t, the pseudo-diffusion fraction F p and the pseudo-diffusion coefficient D p), and high b value (as acquired and Hessian filtered) parameters within the index lesion. These parameters (separately and combined in a logistic regression model) were used to differentiate lesions depending on whether whole-prostate histopathological analysis after prostatectomy determined a high (≥7) or low (6) Gleason score.
RESULTS: Mean ADC and D t differed significantly (p of independent two-sample t test < 0.01) between high- and low-grade lesions. The highest classification accuracy was achieved by the mean ADC (AUC 0.74) and D t (AUC 0.70). A logistic regression model based on mean ADC, mean F p and mean high b value image led to an AUC of 0.74 following leave-one-out cross-validation.
CONCLUSIONS: Classification by IVIM parameters was not superior to classification by ADC. DW-MRI parameters correlated with Gleason score but did not provide sufficient information to classify individual patients. KEY POINTS: • Mean ADC and diffusion coefficient differ between high- and low-grade prostatic lesions. • Accuracy of trivariate logistic regression is not superior to using ADC alone. • DW-MRI is not a valid substitute for biopsies in clinical routine yet.

Entities:  

Keywords:  ADC; Diffusion-weighted MRI; IVIM; Logistic regression; Prostate cancer

Mesh:

Year:  2016        PMID: 27300199     DOI: 10.1007/s00330-016-4449-5

Source DB:  PubMed          Journal:  Eur Radiol        ISSN: 0938-7994            Impact factor:   5.315


  14 in total

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2.  Efficacy of 68Ga-PSMA-11 PET/CT with biparametric MRI in diagnosing prostate cancer and predicting risk stratification: a comparative study.

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Journal:  Br J Radiol       Date:  2021-09-19       Impact factor: 3.039

Review 4.  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

5.  Risk Stratification Among Men With Prostate Imaging Reporting and Data System version 2 Category 3 Transition Zone Lesions: Is Biopsy Always Necessary?

Authors:  Ely R Felker; Steven S Raman; Daniel J Margolis; David S K Lu; Nicholas Shaheen; Shyam Natarajan; Devi Sharma; Jiaoti Huang; Fred Dorey; Leonard S Marks
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6.  The Primacy of High B-Value 3T-DWI Radiomics in the Prediction of Clinically Significant Prostate Cancer.

Authors:  Alessandro Bevilacqua; Margherita Mottola; Fabio Ferroni; Alice Rossi; Giampaolo Gavelli; Domenico Barone
Journal:  Diagnostics (Basel)       Date:  2021-04-21

7.  Prediction of prostate cancer grade using fractal analysis of perfusion MRI: retrospective proof-of-principle study.

Authors:  Florian Michallek; Henkjan Huisman; Bernd Hamm; Sefer Elezkurtaj; Andreas Maxeiner; Marc Dewey
Journal:  Eur Radiol       Date:  2021-12-16       Impact factor: 7.034

8.  Magnetic Resonance Diffusion Kurtosis Imaging versus Diffusion-Weighted Imaging in Evaluating the Pathological Grade of Hepatocellular Carcinoma.

Authors:  Guang-Zhi Wang; Ling-Fei Guo; Gui-Hua Gao; Yao Li; Xi-Zhen Wang; Zhen-Guo Yuan
Journal:  Cancer Manag Res       Date:  2020-06-29       Impact factor: 3.989

9.  Optimising preoperative risk stratification tools for prostate cancer using mpMRI.

Authors:  Lars A R Reisæter; Jurgen J Fütterer; Are Losnegård; Yngve Nygård; Jan Monssen; Karsten Gravdal; Ole J Halvorsen; Lars A Akslen; Martin Biermann; Svein Haukaas; Jarle Rørvik; Christian Beisland
Journal:  Eur Radiol       Date:  2017-10-06       Impact factor: 5.315

10.  IVIM Parameters on MRI Could Predict ISUP Risk Groups of Prostate Cancers on Radical Prostatectomy.

Authors:  Chun-Bi Chang; Yu-Chun Lin; Yon-Cheong Wong; Shin-Nan Lin; Chien-Yuan Lin; Yu-Han Lin; Ting-Wen Sheng; Chen-Chih Huang; Lan-Yan Yang; Li-Jen Wang
Journal:  Front Oncol       Date:  2021-07-01       Impact factor: 6.244

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