Local dose analysis to predict acute and late urinary toxicities after prostate cancer radiotherapy: Assessment of cohort and method effects.


Journal

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
ISSN: 1879-0887
Titre abrégé: Radiother Oncol
Pays: Ireland
ID NLM: 8407192

Informations de publication

Date de publication:
06 2020
Historique:
received: 06 10 2019
revised: 28 01 2020
accepted: 28 02 2020
pubmed: 1 4 2020
medline: 15 4 2021
entrez: 1 4 2020
Statut: ppublish

Résumé

To perform bladder dose-surface map (DSM) analysis for (1) identifying symptom-related sub-surfaces (Ssurf) and evaluating their prediction capability of urinary toxicity, (2) comparing DSM with dose-volume map (DVM) (method effect), and (3) assessing the reproducibility of DSM (cohort effect). Urinary toxicities were prospectively analyzed for 254 prostate cancer patients treated with IMRT/IGRT at 78/80 Gy. DSMs were generated by unfolding bladder surfaces in a 2D plane. Pixel-by-pixel analysis was performed to identify symptom-related Ssurf. Likewise, voxel-by-voxel DVM analysis was performed to identify sub-volumes (Svol). The prediction capability of Ssurf and Svol DVHs was assessed by logistic/Cox regression using the area under the ROC curve (AUC). The Ssurf localization and prediction capability were compared to (1) the Svol obtained by DVM analysis in the same cohort and (2) the Ssurf obtained from other DSM studies. Three Ssurf were identified in the bladder: posterior for acute retention (AUC = 0.64), posterior-superior for late retention (AUC = 0.68), and inferior-anterior-lateral for late dysuria (AUC = 0.73). Five Svol were identified: one in the urethra for acute incontinence and four in the posterior bladder part for acute and late retention, late dysuria, and hematuria. The overlap between Ssurf and Svol was moderate for acute retention, good for late retention, and bad for late dysuria, and AUCs ranged from 0.62 to 0.81. The prediction capabilities of Ssurf and Svol models were not significantly different. Among five symptoms comparable between cohorts, common Ssurf was found only for late dysuria, with a good spatial agreement. Spatial agreement between methods is relatively good although DVM identified more sub-regions. Reproducibility of identified Ssurf between cohorts is low.

Identifiants

pubmed: 32224316
pii: S0167-8140(20)30113-4
doi: 10.1016/j.radonc.2020.02.028
pii:
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

40-49

Informations de copyright

Copyright © 2020 Elsevier B.V. All rights reserved.

Auteurs

Eugenia Mylona (E)

Univ Rennes, CLCC Eugène Marquis, INSERM, LTSI - UMR 1099, F-35000, Rennes, France.

Alessandro Cicchetti (A)

Prostate Cancer Program, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy; Università degli Studi di Pavia, Physics Department, Italy.

Tiziana Rancati (T)

Prostate Cancer Program, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy.

Federica Palorini (F)

Prostate Cancer Program, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy.

Claudio Fiorino (C)

Department of Medical Physics, San Raffaele Scientific Institute, Milano, Italy.

Stephane Supiot (S)

Department of Radiation Oncology, Centre Georges François Leclerc, Dijon, France.

Nicolas Magne (N)

Radiotherapy Department, Lucien Neuwirth Cancer Institute, St Priest en Jarez, France.

Gilles Crehange (G)

Medical Physics Department, Institut de Cancérologie de l'Ouest, Saint Herblain, France.

Riccardo Valdagni (R)

Prostate Cancer Program, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy; Department of Oncology and Hemato-Oncology, Università degli Studi di Milano, Milan, Italy; Department of Radiation Oncology 1, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy.

Oscar Acosta (O)

Univ Rennes, CLCC Eugène Marquis, INSERM, LTSI - UMR 1099, F-35000, Rennes, France.

Renaud de Crevoisier (R)

Univ Rennes, CLCC Eugène Marquis, INSERM, LTSI - UMR 1099, F-35000, Rennes, France.

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Classifications MeSH