Literature DB >> 33026934

Predicting Pathological Tumor Size in Prostate Cancer Based on Multiparametric Prostate Magnetic Resonance Imaging and Preoperative Findings.

Aydin Pooli1, David C Johnson1, Joseph Shirk1, Daniela Markovic2, Taylor Y Sadun1, Anthony E Sisk3, Amirhossein Mohammadian Bajgiran4, Sohrab Afshari Mirak4, Ely R Felker4, Alexa K Hughes5, Steven S Raman4, Robert E Reiter1.   

Abstract

PURPOSE: Oncologic efficacy of focal therapies in prostate cancer depends heavily on accurate tumor size estimation. We aim to evaluate the agreement between radiologic tumor size and pathological tumor size, and identify predictors of pathological tumor size.
MATERIALS AND METHODS: This single arm study cohort included all consecutive patients with biopsy proven prostate cancer and a corresponding PI-RADS®v2 3 or greater index tumor on multiparametric magnetic resonance imaging who subsequently underwent radical prostatectomy. Radiologic tumor size was defined as maximum tumor diameter on multiparametric magnetic resonance imaging and compared to whole mount histopathology tumor correlates. The difference between radiologic tumor size and pathological tumor size was assessed, and clinical, pathological and radiographic predictors of pathological tumor size were examined.
RESULTS: A total of 461 consecutive lesions in 441 men were included for statistical analysis. Mean radiologic tumor size and pathological tumor size was 1.57 and 2.37 cm, respectively (p <0.001). Radiologic tumor size consistently underestimated pathological tumor size regardless of the preoperative covariates, and the degree of underestimation increased with smaller radiologic tumor size and lower PI-RADSv2 scores. Pathological tumor size was significantly larger for biopsy Gleason Grade Group (GG) 5 compared to GG1 (mean change 0.37 cm, p=0.014), PI-RADSv2 5 lesions compared to PI-RADSv2 4 (mean change 0.26, p=0.006) and higher prostate specific antigen density. The correlations between radiologic tumor size vs pathological tumor size according to biopsy GG and radiologic covariates were generally low with correlation coefficients ranging between 0.1 and 0.65.
CONCLUSIONS: Multiparametric magnetic resonance imaging frequently underestimates pathological tumor size and the degree of underestimation increases with smaller radiologic tumor size and lower PI-RADSv2 scores. Therefore, a larger ablation margin may be required for smaller tumors and lesions with lower PI-RADSv2 scores. These variables must be considered when estimating treatment margins in focal therapy.

Entities:  

Keywords:  multiparametric magnetic resonance imaging; prostate-specific antigen; prostatic neoplasms; tumor burden

Year:  2020        PMID: 33026934     DOI: 10.1097/JU.0000000000001389

Source DB:  PubMed          Journal:  J Urol        ISSN: 0022-5347            Impact factor:   7.450


  10 in total

1.  Risk Estimation of Metastatic Recurrence After Prostatectomy: A Model Using Preoperative Magnetic Resonance Imaging and Targeted Biopsy.

Authors:  Thomas Bommelaere; Arnauld Villers; Philippe Puech; Guillaume Ploussard; Julien Labreuche; Elodie Drumez; Xavier Leroy; Jonathan Olivier
Journal:  Eur Urol Open Sci       Date:  2022-05-19

2.  Prostate biopsy in the era of MRI-targeting: towards a judicious use of additional systematic biopsy.

Authors:  Dominik Deniffel; Nathan Perlis; Sangeet Ghai; Stephanie Girgis; Gerard M Healy; Neil Fleshner; Robert Hamilton; Girish Kulkarni; Ants Toi; Theodorus van der Kwast; Alexandre Zlotta; Antonio Finelli; Masoom A Haider
Journal:  Eur Radiol       Date:  2022-05-04       Impact factor: 7.034

3.  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

4.  Defining radio-recurrent intra-prostatic target volumes using PSMA-targeted PET/CT and multi-parametric MRI.

Authors:  Wei Liu; Hatim Fakir; Gurpreet Randhawa; Ryan Alfano; Mark Corkum; Zahra Kassam; Irina Rachinsky; Hans T Chung; Peter Chung; Andrew Loblaw; Gerard Morton; Tracy Sexton; Anil Kapoor; Aaron Ward; Katherine Zukotynski; Louise Emmett; Glenn Bauman
Journal:  Clin Transl Radiat Oncol       Date:  2021-11-14

5.  Multiparametric Magnetic Resonance Imaging Grades the Aggressiveness of Prostate Cancer.

Authors:  Juan Morote; Angel Borque-Fernando; Marina Triquell; Anna Celma; Lucas Regis; Richard Mast; Inés M de Torres; María E Semidey; Anna Santamaría; Jacques Planas; Luis M Esteban; Enrique Trilla
Journal:  Cancers (Basel)       Date:  2022-04-05       Impact factor: 6.639

6.  Focal therapy for prostate cancer with irreversible electroporation: Oncological and functional results of a single institution study.

Authors:  William John Yaxley; Troy Gianduzzo; Boon Kua; Rachel Oxford; John William Yaxley
Journal:  Investig Clin Urol       Date:  2022-05

7.  Investigation of the Disparities in Ultrasound Imaging Features of miR-323, miR-409-3p, and VEGF Expression Scales in Different Clinicopathological Features of Prostate Carcinoma and Their Correlation with Prognosis.

Authors:  Bao Liu; Jingqi Wang; Yanhua Cui; Hui He
Journal:  Biomed Res Int       Date:  2022-06-18       Impact factor: 3.246

Review 8.  The use of advanced imaging in guiding the further investigation and treatment of primary prostate cancer.

Authors:  Heying Duan; Andrei Iagaru
Journal:  Cancer Imaging       Date:  2022-09-03       Impact factor: 5.605

9.  Combined Systematic and MRI-US Fusion Prostate Biopsy Has the Highest Grading Accuracy When Compared to Final Pathology.

Authors:  Iulia Andras; Emanuel Darius Cata; Andreea Serban; Pierre Kadula; Teodora Telecan; Maximilian Buzoianu; Maria Bungardean; Dan Vasile Stanca; Ioan Coman; Nicolae Crisan
Journal:  Medicina (Kaunas)       Date:  2021-05-22       Impact factor: 2.430

Review 10.  Focal Therapy for Prostate Cancer: Complications and Their Treatment.

Authors:  Arnas Rakauskas; Giancarlo Marra; Isabel Heidegger; Veeru Kasivisvanathan; Alexander Kretschmer; Fabio Zattoni; Felix Preisser; Derya Tilki; Igor Tsaur; Roderick van den Bergh; Claudia Kesch; Francesco Ceci; Christian Fankhauser; Giorgio Gandaglia; Massimo Valerio
Journal:  Front Surg       Date:  2021-07-12
  10 in total

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