A qualitative and a quantitative analysis of an auto-segmentation module for prostate cancer

Huyskens, D.; Maingon, P.; Vanuytsel, L.; Remouchamps, Vincent; Roques, Tom; Dubray, Bernard; Haas, Benjamin de; Kunz, Patrik; Coradi, Thomas; Bühlman, René; Reddick, Robin; Esch, A. Van; Salamon, E.

doi:10.1016/j.radonc.2008.08.007

Cited by 59 publications

(47 citation statements)

References 22 publications

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“…The smallest contouring variations of the prostate were found in the lateral parts. The largest variations were identified in the region of the seminal vesicles, and the posterior and anterior parts close to the apex (16,17). The retrograde application of contrast on FBCT via an urethrogram (no contrast in the bladder!)…”

Section: Discussionmentioning

confidence: 99%

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Clinical Evaluation of Soft Tissue Organ Boundary Visualization on Cone-Beam Computed Tomographic Imaging

Weiss

Sleeman

et al. 2010

International Journal of Radiation Oncology*Biology*Physics

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Purpose Cone-beam computed tomographic images (CBCTs) are increasingly used for set up correction, soft tissue targeting and image-guided adaptive radiotherapy (IGART). However, CBCT image quality is limited by low contrast and imaging artifacts. This analysis investigates the detectability of soft tissue boundaries in CBCT by performing a multiple-observer segmentation study. Material and Methods In 4 prostate cancer patients prostate, bladder and rectum were repeatedly delineated by 5 observers on CBCTs and fan beam CTs (FBCTs). A volumetric analysis of contouring variations was performed by calculating coefficients of variation (COV: standard deviation/average volume). The topographical distribution of contouring variations was analyzed using an average surface mesh-based method. Results Observer- and patient-averaged COVs for FBCT/CBCT were 0.09/0.19 for prostate, 0.05/0.08 for bladder and 0.09/0.08 for rectum. Contouring variations on FBCT were significantly smaller than on CBCT for prostate (p<0.03) and bladder (p<0.04), but not for rectum (p<0.37) (intermodality differences). Intraobserver variations from repeated contouring of the same image set were not significant for either FBCT or CBCT (p<0.05). Average standard deviations of individual observers’ contour differences from average surface meshes on FBCT versus CBCT were 1.5 versus 2.1 mm for prostate, 0.7 versus 1.4 mm for bladder, and 1.3 versus 1.5 mm for rectum. The topographical distribution of contouring variations was similar for FBCT and CBCT. Conclusion Contouring variations were larger on CBCT than FBCT, except for rectum. Given the well-documented uncertainty in soft tissue contouring in the pelvis, improvement of CBCT image quality and establishment of well-defined soft tissue identification rules are desirable for image-guided radiotherapy.

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Section: Discussionmentioning

confidence: 99%

“…The largest variations for the bladder were observed in the contact area between prostate and bladder. Rectum contour variations were largest in the area close to the prostatic apex, the urogenital diaphragm and the sphincter muscle (16) and smallest superior to the prostate where the rectum is surrounded by low density tissue.…”

Section: Discussionmentioning

confidence: 99%

Clinical Evaluation of Soft Tissue Organ Boundary Visualization on Cone-Beam Computed Tomographic Imaging

Weiss

Sleeman

et al. 2010

International Journal of Radiation Oncology*Biology*Physics

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“…In this context, a fast, robust, and automatic region-of-interest (ROI) delineation method is needed and has led to a growing array of automatic contouring (AC) software [5-7]. These algorithms generally deform one set of contours from an initial CT to fit the anatomy of a second CT, and they can also redraw the ROI of interest for each CT from scratch.…”

Section: Introductionmentioning

confidence: 99%

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

Macchia¹,

Fellin²,

Amichetti³

et al. 2012

Radiat Oncol

146

131

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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.

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“…However, these approaches were developed for the standard parallel-needle HDR template, which consists of a small set of needles that do not cover the set of needle configurations made possible with freehand techniques. There has also been work in autosegmentation of organ structures [23], and the afterloading device allows execution of HDR-BT dwell times without human intervention.…”

Section: Background and Related Workmentioning

confidence: 99%

Initial experiments toward automated robotic implantation of skew-line needle arrangements for HDR brachytherapy

Garg¹,

Siauw²,

Berenson³

et al. 2012

2012 IEEE International Conference on Automation Science and Engineering (CASE)

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Abstract-One of the goals of automation is to increase the reliability and quality of a given process. This study aims to automate high dose rate brachytherapy (HDR-BT), a radiation therapy that places radioactive sources at the site of the tumor using needles. Although HDR-BT has a high rate of clinical success in curing prostate cancer, it also has several side effects related to needle and dose trauma. A new planning algorithm from previous work optimizes needle arrangements using skewlines (non-parallel, non-intersecting lines). This paper presents initial experiments towards an automated system for implanting skew-line needle arrangements computed from a planning system. We describe the interface, calibration and integration of the robotic hardware with the planning system, and present experiments using our robotic system to implant needles into anatomically-correct tissue phantoms. Results suggest that this system can achieve HDR-BT treatment objectives with reduced trauma to organs and low demands on operator skill, thus making the procedure repeatable at lower cost. We believe that in the future, robotic HDR-BT will result in improved treatment quality with reduced dependence on physician skill.

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A qualitative and a quantitative analysis of an auto-segmentation module for prostate cancer

Cited by 59 publications

References 22 publications

Clinical Evaluation of Soft Tissue Organ Boundary Visualization on Cone-Beam Computed Tomographic Imaging

Clinical Evaluation of Soft Tissue Organ Boundary Visualization on Cone-Beam Computed Tomographic Imaging

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

Initial experiments toward automated robotic implantation of skew-line needle arrangements for HDR brachytherapy

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