Literature DB >> 33684304

Value of MRI texture analysis for predicting new Gleason grade group.

Xiaojing He1, Hui Xiong1, Haiping Zhang1, Xinjie Liu1, Jun Zhou1, Dajing Guo1.   

Abstract

OBJECTIVES: To explore the potential value of multiparametric magnetic resonance imaging (mpMRI) texture analysis (TA) to predict new Gleason Grade Group (GGG).
METHODS: Fifty-eight lesions of fifty patients who underwent mpMRI scanning, including T2-weighted imaging (T2WI) and diffusion-weighted imaging (DWI) prior to trans-rectal ultrasound (TRUS)-guided core prostate biopsy, were retrospectively enrolled. TA parameters were obtained by the postprocessing software, and each lesion was assigned to its corresponding GGG. TA parameters derived from T2WI and DWI were statistically analyzed in detail.
RESULTS: Energy, inertia, and correlation derived from apparent diffusion coefficient (ADC) maps and T2WI had a statistically significant difference among the five groups. Kurtosis, energy, inertia, correlation on ADC maps and Energy, inertia on T2WI were moderately related to the GGG trend. ADC-energy and T2-energy were significant independent predictors of the GGG trend. ADC-energy, T2WI-energy, and T2WI-correlation had a statistically significant difference between GGG1 and GGG2-5. ADC-energy were significant independent predictors of the GGG1. ADC-energy, T2WI-energy, and T2WI-correlation showed satisfactory diagnostic efficiency of GGG1 (area under the curve (AUC) 84.6, 74.3, and 83.5%, respectively), and ADC-energy showed excellent sensitivity and specificity (88.9 and 95.1%, respectively).
CONCLUSION: TA parameters ADC-energy and T2-energy played an important role in predicting GGG trend. Both ADC-energy and T2-correlation produced a high diagnostic power of GGG1, and ADC-energy was perfect predictors of GGG1. ADVANCES IN KNOWLEDGE: TA parameters were innovatively used to predict new GGG trend, and the predictive factors of GGG1 were screen out.

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Year:  2021        PMID: 33684304      PMCID: PMC8506181          DOI: 10.1259/bjr.20210005

Source DB:  PubMed          Journal:  Br J Radiol        ISSN: 0007-1285            Impact factor:   3.039


  34 in total

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2.  Classification of prostatic carcinomas.

Authors:  D F Gleason
Journal:  Cancer Chemother Rep       Date:  1966-03

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Authors:  J Y Yu; H P Zhang; Z Y Tang; J Zhou; X J He; Y Y Liu; X J Liu; D J Guo
Journal:  Clin Radiol       Date:  2018-05-24       Impact factor: 2.350

4.  Biochemical outcome after radical prostatectomy, external beam radiation therapy, or interstitial radiation therapy for clinically localized prostate cancer.

Authors:  A V D'Amico; R Whittington; S B Malkowicz; D Schultz; K Blank; G A Broderick; J E Tomaszewski; A A Renshaw; I Kaplan; C J Beard; A Wein
Journal:  JAMA       Date:  1998-09-16       Impact factor: 56.272

5.  Prostate cancer aggressiveness: assessment with whole-lesion histogram analysis of the apparent diffusion coefficient.

Authors:  Olivio F Donati; Yousef Mazaheri; Asim Afaq; Hebert A Vargas; Junting Zheng; Chaya S Moskowitz; Hedvig Hricak; Oguz Akin
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Review 6.  Prostate Imaging Reporting and Data System Version 2.1: 2019 Update of Prostate Imaging Reporting and Data System Version 2.

Authors:  Baris Turkbey; Andrew B Rosenkrantz; Masoom A Haider; Anwar R Padhani; Geert Villeirs; Katarzyna J Macura; Clare M Tempany; Peter L Choyke; Francois Cornud; Daniel J Margolis; Harriet C Thoeny; Sadhna Verma; Jelle Barentsz; Jeffrey C Weinreb
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7.  Analysis of Diffusion-weighted MR Images Based on a Gamma Distribution Model to Differentiate Prostate Cancers with Different Gleason Score.

Authors:  Hiroko Tomita; Shigeyoshi Soga; Yohsuke Suyama; Keiichi Ito; Tomohiko Asano; Hiroshi Shinmoto
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8.  "Textural analysis of multiparametric MRI detects transition zone prostate cancer".

Authors:  Harbir S Sidhu; Salvatore Benigno; Balaji Ganeshan; Nikos Dikaios; Edward W Johnston; Clare Allen; Alex Kirkham; Ashley M Groves; Hashim U Ahmed; Mark Emberton; Stuart A Taylor; Steve Halligan; Shonit Punwani
Journal:  Eur Radiol       Date:  2016-09-12       Impact factor: 5.315

Review 9.  Systematic review of complications of prostate biopsy.

Authors:  Stacy Loeb; Annelies Vellekoop; Hashim U Ahmed; James Catto; Mark Emberton; Robert Nam; Derek J Rosario; Vincenzo Scattoni; Yair Lotan
Journal:  Eur Urol       Date:  2013-06-04       Impact factor: 20.096

10.  Dynamic contrast-enhanced (DCE) MR imaging: the role of qualitative and quantitative parameters for evaluating prostate tumors stratified by Gleason score and PI-RADS v2.

Authors:  Sohrab Afshari Mirak; Amirhossein Mohammadian Bajgiran; Kyunghyun Sung; Nazanin H Asvadi; Daniela Markovic; Ely R Felker; David Lu; Anthony Sisk; Robert E Reiter; Steven S Raman
Journal:  Abdom Radiol (NY)       Date:  2020-07
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  1 in total

Review 1.  More than Meets the Eye: Using Textural Analysis and Artificial Intelligence as Decision Support Tools in Prostate Cancer Diagnosis-A Systematic Review.

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Journal:  J Pers Med       Date:  2022-06-16
  1 in total

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