Literature DB >> 27570122

Bladder spatial-dose descriptors correlate with acute urinary toxicity after radiation therapy for prostate cancer.

I Improta1, F Palorini2, C Cozzarini3, T Rancati4, B Avuzzi5, P Franco6, C Degli Esposti7, E Del Mastro8, G Girelli9, C Iotti10, V Vavassori11, R Valdagni12, C Fiorino2.   

Abstract

PURPOSE: To assess bladder spatial-dose parameters predicting acute urinary toxicity after radiotherapy for prostate cancer (PCa) through a pixel-wise method for analysis of bladder dose-surface maps (DSMs). MATERIALS &
METHODS: The final cohort of a multi-institutional study, consisting of 539 patients with PCa treated with conventionally (CONV:1.8-2Gy/fr) or moderately hypo-fractionated radiotherapy (HYPO:2.2-2.7Gy/fr) was considered. Urinary toxicity was evaluated through the International Prostate Symptoms Score (IPSS) administered before and after radiotherapy. IPSS increases ⩾10 and 15 points at the end of radiotherapy (ΔIPSS⩾10 and ΔIPSS⩾15) were chosen as endpoints. Average DSMs (corrected into 2Gy-equivalent doses) of patients with/without toxicity were compared through a pixel-wise method. This allowed the extraction of selected spatial descriptors discriminating between patients with/without toxicity. Previously logistic models based on dose-surface histograms (DSH) were considered and replaced with DSM descriptors. Discrimination power, calibration and log-likelihood were considered to evaluate the impact of the inclusion of spatial descriptors.
RESULTS: Data of 375/539 patients were available. ΔIPSS⩾10 was recorded in 76/375 (20%) patients, while 30/375 (8%) experienced ΔIPSS⩾15. The posterior dose at 12mm from the bladder base (roughly corresponding to the trigone region) resulted significantly associated to toxicity in the whole/HYPO populations. The cranial extension of the 75Gy isodose along the bladder central axis was the best DSM-based predictor in CONV patients. Multi-variable models including DSM descriptors showed better discrimination (AUC=0.66-0.77) when compared to DSH-based models (AUC=0.58-0.71) and higher log-likelihoods.
CONCLUSION: DSMs are correlated with the risk of acute GU toxicity. The incorporation of spatial descriptors improves discrimination and log-likelihood of multi-variable models including dosimetric and clinical parameters.
Copyright © 2016 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Acute urinary toxicity; Bladder spatial-dose descriptors; Dose-surface maps; Prostate radiotherapy

Mesh:

Year:  2016        PMID: 27570122     DOI: 10.1016/j.ejmp.2016.08.013

Source DB:  PubMed          Journal:  Phys Med        ISSN: 1120-1797            Impact factor:   2.685


  4 in total

1.  A Deep Learning Model for Predicting Xerostomia Due to Radiation Therapy for Head and Neck Squamous Cell Carcinoma in the RTOG 0522 Clinical Trial.

Authors:  Kuo Men; Huaizhi Geng; Haoyu Zhong; Yong Fan; Alexander Lin; Ying Xiao
Journal:  Int J Radiat Oncol Biol Phys       Date:  2019-06-13       Impact factor: 7.038

2.  A case-control study using motion-inclusive spatial dose-volume metrics to account for genito-urinary toxicity following high-precision radiotherapy for prostate cancer.

Authors:  Oscar Casares-Magaz; Ludvig P Muren; Niclas Pettersson; Maria Thor; Austin Hopper; Rick Knopp; Joseph O Deasy; Michael Væth; John Einck; Vitali Moiseenko
Journal:  Phys Imaging Radiat Oncol       Date:  2018-10-05

Review 3.  Regional Responses in Radiation-Induced Normal Tissue Damage.

Authors:  Daniëlle C Voshart; Julia Wiedemann; Peter van Luijk; Lara Barazzuol
Journal:  Cancers (Basel)       Date:  2021-01-20       Impact factor: 6.639

4.  Increased Dose to Organs in Urinary Tract Associates With Measures of Genitourinary Toxicity in Pooled Voxel-Based Analysis of 3 Randomized Phase III Trials.

Authors:  Marco Marcello; James W Denham; Angel Kennedy; Annette Haworth; Allison Steigler; Peter B Greer; Lois C Holloway; Jason A Dowling; Michael G Jameson; Dale Roach; David J Joseph; Sarah L Gulliford; David P Dearnaley; Matthew R Sydes; Emma Hall; Martin A Ebert
Journal:  Front Oncol       Date:  2020-07-22       Impact factor: 6.244

  4 in total

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