Literature DB >> 32516697

MRI phenotype of the prostate: Transition zone radiomics analysis improves explanation of prostate-specific antigen (PSA) serum level compared to volume measurement alone.

Tobias Krauss1, Hannes Engel1, Cordula A Jilg2, Christian Gratzke2, Fabian Bamberg1, Matthias Benndorf3.   

Abstract

PURPOSE: To determine the value of a radiomics MRI phenotype of the transition zone to explain PSA level in patients with low suspicion for clinically significant cancer to confirm hyperplastic changes.
MATERIALS AND METHODS: T2 weighted images from 36 consecutive PI-RADS 2 and 3 cases with volume adapted systematic transperineal biopsy as reference standard (all biopsies negative, 34.8 biopsy cores per patient in average, mean PSA level 10.77 ng/mL) are manually segmented to define transition zone (TZ) volume. 54 radiomic features (RF) are derived for each TZ. RF are tested for significant correlation with PSA level, Bonferroni correction is applied. We build regression models to explain PSA level with a) TZ volume b) RF c) TZ volume+RF. We apply all models to a control group with clinically significant transition zone cancer.
RESULTS: TZ volume is moderately correlated with PSA level (r = 0.44). 5/54 RF are significantly correlated with PSA level (r: 0.53-0.69, p < 0.05). Inclusion of each of these five features into the regression model significantly improves the explanatory value for PSA level (p < 0.05). Furthermore, RF alone better explain PSA level compared to TZ volume alone (p < 0.01). A systematic and significant trend for positive residuals is observed when regression models are applied to the malignant control group.
CONCLUSION: A radiomics analysis of the transition zone has the potential to improve explanation of corresponding PSA level in patients with low suspicion. This knowledge may reassure radiologists to read prostate MRI cases as unremarkable, despite present hyperplastic changes.
Copyright © 2020 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  BPH; PSA; Prostate MRI; Radiomics; Texture

Mesh:

Substances:

Year:  2020        PMID: 32516697     DOI: 10.1016/j.ejrad.2020.109063

Source DB:  PubMed          Journal:  Eur J Radiol        ISSN: 0720-048X            Impact factor:   3.528


  3 in total

Review 1.  Overview of radiomics in prostate imaging and future directions.

Authors:  Hwan-Ho Cho; Chan Kyo Kim; Hyunjin Park
Journal:  Br J Radiol       Date:  2021-11-29       Impact factor: 3.039

2.  Quantitative Analysis of Diffusion Weighted Imaging May Improve Risk Stratification of Prostatic Transition Zone Lesions.

Authors:  Hannes Engel; Benedict Oerther; Marco Reisert; Elias Kellner; August Sigle; Christian Gratzke; Peter Bronsert; Tobias Krauss; Fabian Bamberg; Matthias Benndorf
Journal:  In Vivo       Date:  2022 Sep-Oct       Impact factor: 2.406

Review 3.  Radiomics in prostate cancer: an up-to-date review.

Authors:  Matteo Ferro; Ottavio de Cobelli; Gennaro Musi; Francesco Del Giudice; Giuseppe Carrieri; Gian Maria Busetto; Ugo Giovanni Falagario; Alessandro Sciarra; Martina Maggi; Felice Crocetto; Biagio Barone; Vincenzo Francesco Caputo; Michele Marchioni; Giuseppe Lucarelli; Ciro Imbimbo; Francesco Alessandro Mistretta; Stefano Luzzago; Mihai Dorin Vartolomei; Luigi Cormio; Riccardo Autorino; Octavian Sabin Tătaru
Journal:  Ther Adv Urol       Date:  2022-07-04
  3 in total

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