Systematic evaluation of three different commercial software solutions for automatic segmentation for adaptive therapy in head-and-neck, prostate and pleural cancer

Abstract

PurposeTo validate, in the context of adaptive radiotherapy, three commercial software solutions for atlas-based segmentation.Methods and materialsFifteen patients, five for each group, with cancer of the Head&Neck, pleura, and prostate were enrolled in the study. In addition to the treatment planning CT (pCT) images, one replanning CT (rCT) image set was acquired for each patient during the RT course. Three experienced physicians outlined on the pCT and rCT all the volumes of interest (VOIs). We used three software solutions (VelocityAI 2.6.2 (V), MIM 5.1.1 (M) by MIMVista and ABAS 2.0 (A) by CMS-Elekta) to generate the automatic contouring on the repeated CT. All the VOIs obtained with automatic contouring (AC) were successively corrected manually. We recorded the time needed for: 1) ex novo ROIs definition on rCT; 2) generation of AC by the three software solutions; 3) manual correction of AC.To compare the quality of the volumes obtained automatically by the software and manually corrected with those drawn from scratch on rCT, we used the following indexes: overlap coefficient (DICE), sensitivity, inclusiveness index, difference in volume, and displacement differences on three axes (x, y, z) from the isocenter.ResultsThe time saved by the three software solutions for all the sites, compared to the manual contouring from scratch, is statistically significant and similar for all the three software solutions. The time saved for each site are as follows: about an hour for Head&Neck, about 40 minutes for prostate, and about 20 minutes for mesothelioma. The best DICE similarity coefficient index was obtained with the manual correction for: A (contours for prostate), A and M (contours for H&N), and M (contours for mesothelioma).ConclusionsFrom a clinical point of view, the automated contouring workflow was shown to be significantly shorter than the manual contouring process, even though manual correction of the VOIs is always needed.

Characterization of Tympanic Cavity Volume in Newborns using Computerized Tomography Scanning

“…This provided additional evidence on the validity and applicability of our image processing protocol and selection criterions for segmenting TC. Our findings based on the Dice and Jaccard analysis were in agrement with those of the previous studies who sized other body organs or anatomical structures (Chang et al, 2009;Duda et al, 2001;Lee et al, 2003;La Macchia et al, 2012).…”

Accuracy of software-assisted contour propagation from planning CT to cone beam CT in head and neck radiotherapy

“…Unsupervised contour propagation in large datasets of daily imaging could enable a comparison of delivered and planned doses for the OARs described in this article, excluding the esophagus and esophagus inlet muscle. Previous studies have already described the benefits of DIR for the purpose of reducing contouring time during treatment [15,16,26]. Another application of the method might be replacing any CT being performed during treatment for adaptive purposes.…”

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The utility of atlas-assisted segmentation in the male pelvis is dependent on the interobserver agreement of the structures segmented

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