Literature DB >> 33483545

Utility of T2-weighted MRI texture analysis in assessment of peripheral zone prostate cancer aggressiveness: a single-arm, multicenter study.

Gabriel A Nketiah1,2, Mattijs Elschot3,4, Tom W Scheenen5, Marnix C Maas5, Tone F Bathen3,4, Kirsten M Selnæs3,4.   

Abstract

T2-weighted (T2W) MRI provides high spatial resolution and tissue-specific contrast, but it is predominantly used for qualitative evaluation of prostate anatomy and anomalies. This retrospective multicenter study evaluated the potential of T2W image-derived textural features for quantitative assessment of peripheral zone prostate cancer (PCa) aggressiveness. A standardized preoperative multiparametric MRI was performed on 87 PCa patients across 6 institutions. T2W intensity and apparent diffusion coefficient (ADC) histogram, and T2W textural features were computed from tumor volumes annotated based on whole-mount histology. Spearman correlations were used to evaluate association between textural features and PCa grade groups (i.e. 1-5). Feature utility in differentiating and classifying low-(grade group 1) vs. intermediate/high-(grade group ≥ 2) aggressive cancers was evaluated using Mann-Whitney U-tests, and a support vector machine classifier employing "hold-one-institution-out" cross-validation scheme, respectively. Textural features indicating image homogeneity and disorder/complexity correlated significantly (p < 0.05) with PCa grade groups. In the intermediate/high-aggressive cancers, textural homogeneity and disorder/complexity were significantly lower and higher, respectively, compared to the low-aggressive cancers. The mean classification accuracy across the centers was highest for the combined ADC and T2W intensity-textural features (84%) compared to ADC histogram (75%), T2W histogram (72%), T2W textural (72%) features alone or T2W histogram and texture (77%), T2W and ADC histogram (79%) combined. Texture analysis of T2W images provides quantitative information or features that are associated with peripheral zone PCa aggressiveness and can augment their classification.

Entities:  

Year:  2021        PMID: 33483545     DOI: 10.1038/s41598-021-81272-x

Source DB:  PubMed          Journal:  Sci Rep        ISSN: 2045-2322            Impact factor:   4.379


  33 in total

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Authors:  Niall M Corcoran; Matthew K H Hong; Rowan G Casey; Antonio Hurtado-Coll; Justin Peters; Laurence Harewood; S Larry Goldenberg; Chris M Hovens; Anthony J Costello; Martin E Gleave
Journal:  BJU Int       Date:  2011-03-28       Impact factor: 5.588

2.  Prediction of prognosis for prostatic adenocarcinoma by combined histological grading and clinical staging.

Authors:  D F Gleason; G T Mellinger
Journal:  J Urol       Date:  1974-01       Impact factor: 7.450

3.  Fluoroquinolone resistant rectal colonization predicts risk of infectious complications after transrectal prostate biopsy.

Authors:  Michael A Liss; Stephen A Taylor; Deepak Batura; Deborah Steensels; Methee Chayakulkeeree; Charlotte Soenens; G Gopal Rao; Atreya Dash; Samuel Park; Nishant Patel; Jason Woo; Michelle McDonald; Unwanaobong Nseyo; Pooya Banapour; Stephen Unterberg; Thomas E Ahlering; Hendrik Van Poppel; Kyoko Sakamoto; Joshua Fierer; Peter C Black
Journal:  J Urol       Date:  2014-06-10       Impact factor: 7.450

4.  Head-to-head Comparison of Transrectal Ultrasound-guided Prostate Biopsy Versus Multiparametric Prostate Resonance Imaging with Subsequent Magnetic Resonance-guided Biopsy in Biopsy-naïve Men with Elevated Prostate-specific Antigen: A Large Prospective Multicenter Clinical Study.

Authors:  Marloes van der Leest; Erik Cornel; Bas Israël; Rianne Hendriks; Anwar R Padhani; Martijn Hoogenboom; Patrik Zamecnik; Dirk Bakker; Anglita Yanti Setiasti; Jeroen Veltman; Huib van den Hout; Hans van der Lelij; Inge van Oort; Sjoerd Klaver; Frans Debruyne; Michiel Sedelaar; Gerjon Hannink; Maroeska Rovers; Christina Hulsbergen-van de Kaa; Jelle O Barentsz
Journal:  Eur Urol       Date:  2018-11-23       Impact factor: 20.096

5.  Upgrading and downgrading of prostate cancer from biopsy to radical prostatectomy: incidence and predictive factors using the modified Gleason grading system and factoring in tertiary grades.

Authors:  Jonathan I Epstein; Zhaoyong Feng; Bruce J Trock; Phillip M Pierorazio
Journal:  Eur Urol       Date:  2012-02-08       Impact factor: 20.096

6.  Relationship between apparent diffusion coefficients at 3.0-T MR imaging and Gleason grade in peripheral zone prostate cancer.

Authors:  Thomas Hambrock; Diederik M Somford; Henkjan J Huisman; Inge M van Oort; J Alfred Witjes; Christina A Hulsbergen-van de Kaa; Thomas Scheenen; Jelle O Barentsz
Journal:  Radiology       Date:  2011-05       Impact factor: 11.105

Review 7.  Can Clinically Significant Prostate Cancer Be Detected with Multiparametric Magnetic Resonance Imaging? A Systematic Review of the Literature.

Authors:  Jurgen J Fütterer; Alberto Briganti; Pieter De Visschere; Mark Emberton; Gianluca Giannarini; Alex Kirkham; Samir S Taneja; Harriet Thoeny; Geert Villeirs; Arnauld Villers
Journal:  Eur Urol       Date:  2015-02-02       Impact factor: 20.096

8.  Assessment of prostate cancer aggressiveness using dynamic contrast-enhanced magnetic resonance imaging at 3 T.

Authors:  Eline K Vos; Geert J S Litjens; Thiele Kobus; Thomas Hambrock; Christina A Hulsbergen-van de Kaa; Jelle O Barentsz; Henkjan J Huisman; Tom W J Scheenen
Journal:  Eur Urol       Date:  2013-05-31       Impact factor: 20.096

Review 9.  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
Journal:  Eur Urol       Date:  2019-03-18       Impact factor: 20.096

10.  A Contemporary Prostate Cancer Grading System: A Validated Alternative to the Gleason Score.

Authors:  Jonathan I Epstein; Michael J Zelefsky; Daniel D Sjoberg; Joel B Nelson; Lars Egevad; Cristina Magi-Galluzzi; Andrew J Vickers; Anil V Parwani; Victor E Reuter; Samson W Fine; James A Eastham; Peter Wiklund; Misop Han; Chandana A Reddy; Jay P Ciezki; Tommy Nyberg; Eric A Klein
Journal:  Eur Urol       Date:  2015-07-10       Impact factor: 20.096

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  2 in total

1.  Machine and Deep Learning Prediction Of Prostate Cancer Aggressiveness Using Multiparametric MRI.

Authors:  Elena Bertelli; Laura Mercatelli; Chiara Marzi; Eva Pachetti; Michela Baccini; Andrea Barucci; Sara Colantonio; Luca Gherardini; Lorenzo Lattavo; Maria Antonietta Pascali; Simone Agostini; Vittorio Miele
Journal:  Front Oncol       Date:  2022-01-13       Impact factor: 6.244

2.  Prediction of Clinically Significant Cancer Using Radiomics Features of Pre-Biopsy of Multiparametric MRI in Men Suspected of Prostate Cancer.

Authors:  Chidozie N Ogbonnaya; Xinyu Zhang; Basim S O Alsaedi; Norman Pratt; Yilong Zhang; Lisa Johnston; Ghulam Nabi
Journal:  Cancers (Basel)       Date:  2021-12-09       Impact factor: 6.639

  2 in total

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