Literature DB >> 22401919

Contouring variability of the penile bulb on CT images: quantitative assessment using a generalized concordance index.

Viviana Carillo1, Cesare Cozzarini, Lucia Perna, Mauro Calandra, Stefano Gianolini, Tiziana Rancati, Antonello Enrico Spinelli, Vittorio Vavassori, Sergio Villa, Riccardo Valdagni, Claudio Fiorino.   

Abstract

PURPOSE: Within a multicenter study (DUE-01) focused on the search of predictors of erectile dysfunction and urinary toxicity after radiotherapy for prostate cancer, a dummy run exercise on penile bulb (PB) contouring on computed tomography (CT) images was carried out. The aim of this study was to quantitatively assess interobserver contouring variability by the application of the generalized DICE index. METHODS AND MATERIALS: Fifteen physicians from different Institutes drew the PB on CT images of 10 patients. The spread of DICE values was used to objectively select those observers who significantly disagreed with the others. The analyses were performed with a dedicated module in the VODCA software package.
RESULTS: DICE values were found to significantly change among observers and patients. The mean DICE value was 0.67, ranging between 0.43 and 0.80. The statistics of DICE coefficients identified 4 of 15 observers who systematically showed a value below the average (p value range, 0.013 - 0.059): Mean DICE values were 0.62 for the 4 "bad" observers compared to 0.69 of the 11 "good" observers. For all bad observers, the main cause of the disagreement was identified. Average DICE values were significantly worse from the average in 2 of 10 patients (0.60 vs. 0.70, p < 0.05) because of the limited visibility of the PB. Excluding the bad observers and the "bad" patients," the mean DICE value increased from 0.67 to 0.70; interobserver variability, expressed in terms of standard deviation of DICE spread, was also reduced.
CONCLUSIONS: The obtained values of DICE around 0.7 shows an acceptable agreement, considered the small dimension of the PB. Additional strategies to improve this agreement are under consideration and include an additional tutorial of the so-called bad observers with a recontouring procedure, or the recontouring by a single observer of the PB for all patients included in the DUE-01 study.
Copyright © 2012 Elsevier Inc. All rights reserved.

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Year:  2012        PMID: 22401919     DOI: 10.1016/j.ijrobp.2011.12.057

Source DB:  PubMed          Journal:  Int J Radiat Oncol Biol Phys        ISSN: 0360-3016            Impact factor:   7.038


  5 in total

1.  Clinical evaluation of deep learning-based clinical target volume three-channel auto-segmentation algorithm for adaptive radiotherapy in cervical cancer.

Authors:  Chen-Ying Ma; Ju-Ying Zhou; Xiao-Ting Xu; Song-Bing Qin; Miao-Fei Han; Xiao-Huan Cao; Yao-Zong Gao; Lu Xu; Jing-Jie Zhou; Wei Zhang; Le-Cheng Jia
Journal:  BMC Med Imaging       Date:  2022-07-09       Impact factor: 2.795

2.  Baseline status and dose to the penile bulb predict impotence 1 year after radiotherapy for prostate cancer.

Authors:  Cesare Cozzarini; Tiziana Rancati; Fabio Badenchini; Federica Palorini; Barbara Avuzzi; Claudio Degli Esposti; Giuseppe Girelli; Ilaria Improta; Vittorio Vavassori; Riccardo Valdagni; Claudio Fiorino
Journal:  Strahlenther Onkol       Date:  2016-04-14       Impact factor: 3.621

3.  Towards ultrasound-guided adaptive radiotherapy for cervical cancer: Evaluation of Elekta's semiautomated uterine segmentation method on 3D ultrasound images.

Authors:  Sarah A Mason; Tuathan P O'Shea; Ingrid M White; Susan Lalondrelle; Kate Downey; Mariwan Baker; Claus F Behrens; Jeffrey C Bamber; Emma J Harris
Journal:  Med Phys       Date:  2017-06-16       Impact factor: 4.071

4.  Improved 3D U-Net robustness against JPEG 2000 compression for male pelvic organ segmentation in radiotherapy.

Authors:  Karim El Khoury; Martin Fockedey; Eliott Brion; Benoît Macq
Journal:  J Med Imaging (Bellingham)       Date:  2021-04-05

5.  Deep learning-based auto-segmentation of clinical target volumes for radiotherapy treatment of cervical cancer.

Authors:  Chen-Ying Ma; Ju-Ying Zhou; Xiao-Ting Xu; Jian Guo; Miao-Fei Han; Yao-Zong Gao; Hui Du; Johannes N Stahl; Jonathan S Maltz
Journal:  J Appl Clin Med Phys       Date:  2021-11-22       Impact factor: 2.102

  5 in total

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