Inter-observer variability of organ contouring for preclinical studies with cone beam Computed Tomography imaging.

BACKGROUND AND PURPOSE: In preclinical radiation studies, there is great interest in quantifying the radiation response of healthy tissues. Manual contouring has significant impact on the treatment-planning because of variation introduced by human interpretation. This results in inconsistencies when assessing normal tissue volumes. Evaluation of these discrepancies can provide a better understanding on the limitations of the current preclinical radiation workflow. In the present work, interobserver variability (IOV) in manual contouring of rodent normal tissues on cone-beam Computed Tomography, in head and thorax regions was evaluated. MATERIALS AND METHODS: Two animal technicians performed manually (assisted) contouring of normal tissues located within the thorax and head regions of rodents, 20 cases per body site. Mean surface distance (MSD), displacement of center of mass (ΔCoM), DICE similarity coefficient (DSC) and the 95th percentile Hausdorff distance (HD95) were calculated between the contours of the two observers to evaluate the IOV. RESULTS: For the thorax organs, right lung had the lowest IOV (ΔCoM: 0.08 ±â€¯0.04 mm, DSC: 0.96 ±â€¯0.01, MSD:0.07 ±â€¯0.01 mm, HD95:0.20 ±â€¯0.03 mm) while spinal cord, the highest IOV (ΔCoM:0.5 ±â€¯0.3 mm, DSC:0.81 ±â€¯0.05, MSD:0.14 ±â€¯0.03 mm, HD95:0.8 ±â€¯0.2 mm). Regarding head organs, right eye demonstrated the lowest IOV (ΔCoM:0.12 ±â€¯0.08 mm, DSC: 0.93 ±â€¯0.02, MSD: 0.15 ±â€¯0.04 mm, HD95: 0.29 ±â€¯0.07 mm) while complete brain, the highest IOV (ΔCoM: 0.2 ±â€¯0.1 mm, DSC: 0.94 ±â€¯0.02, MSD: 0.3 ±â€¯0.1 mm, HD95: 0.5 ±â€¯0.1 mm). CONCLUSIONS: Our findings reveal small IOV, within the sub-mm range, for thorax and head normal tissues in rodents. The set of contours can serve as a basis for developing an automated delineation method for e.g., treatment planning.

Organ Contouring for Lung Cancer Patients with a Seed Generation Scheme and Random Walks.

In this study, we proposed a semi-automated and interactive scheme for organ contouring in radiotherapy planning for patients with non-small cell lung cancers. Several organs were contoured, including the lungs, airway, heart, spinal cord, body, and gross tumor volume (GTV). We proposed some schemes to automatically generate and vanish the seeds of the random walks (RW) algorithm. We considered 25 lung cancer patients, whose computed tomography (CT) images were obtained from the China Medical University Hospital (CMUH) in Taichung, Taiwan. The manual contours made by clinical oncologists were taken as the gold standard for comparison to evaluate the performance of our proposed method. The Dice coefficient between two contours of the same organ was computed to evaluate the similarity. The average Dice coefficients for the lungs, airway, heart, spinal cord, and body and GTV segmentation were 0.92, 0.84, 0.83, 0.73, 0.85 and 0.66, respectively. The computation time was between 2 to 4 min for a whole CT sequence segmentation. The results showed that our method has the potential to assist oncologists in the process of radiotherapy treatment in the CMUH, and hopefully in other hospitals as well, by saving a tremendous amount of time in contouring.

Evaluation of automatic contour propagation in T2-weighted 4DMRI for normal-tissue motion assessment using internal organ-at-risk volume (IRV).

PURPOSE: The purpose of this study was to evaluate the quality of automatically propagated contours of organs at risk (OARs) based on respiratory-correlated navigator-triggered four-dimensional magnetic resonance imaging (RC-4DMRI) for calculation of internal organ-at-risk volume (IRV) to account for intra-fractional OAR motion. METHODS AND MATERIALS: T2-weighted RC-4DMRI images were of 10 volunteers acquired and reconstructed using an internal navigator-echo surrogate and concurrent external bellows under an IRB-approved protocol. Four major OARs (lungs, heart, liver, and stomach) were delineated in the 10-phase 4DMRI. Two manual-contour sets were delineated by two clinical personnel and two automatic-contour sets were propagated using free-form deformable image registration. The OAR volume variation within the 10-phase cycle was assessed and the IRV was calculated as the union of all OAR contours. The OAR contour similarity between the navigator-triggered and bellows-rebinned 4DMRI was compared. A total of 2400 contours were compared to the most probable ground truth with a 95% confidence level (S95) in similarity, sensitivity, and specificity using the simultaneous truth and performance level estimation (STAPLE) algorithm. RESULTS: Visual inspection of automatically propagated contours finds that approximately 5-10% require manual correction. The similarity, sensitivity, and specificity between manual and automatic contours are indistinguishable (P > 0.05). The Jaccard similarity indexes are 0.92 ± 0.02 (lungs), 0.89 ± 0.03 (heart), 0.92 ± 0.02 (liver), and 0.83 ± 0.04 (stomach). Volume variations within the breathing cycle are small for the heart (2.6 ± 1.5%), liver (1.2 ± 0.6%), and stomach (2.6 ± 0.8%), whereas the IRV is much larger than the OAR volume by: 20.3 ± 8.6% (heart), 24.0 ± 8.6% (liver), and 47.6 ± 20.2% (stomach). The Jaccard index is higher in navigator-triggered than bellows-rebinned 4DMRI by 4% (P < 0.05), due to the higher image quality of navigator-based 4DMRI. CONCLUSION: Automatic and manual OAR contours from Navigator-triggered 4DMRI are not statistically distinguishable. The navigator-triggered 4DMRI image provides higher contour quality than bellows-rebinned 4DMRI. The IRVs are 20-50% larger than OAR volumes and should be considered in dose estimation.

Commissioning of an atlas-based auto-segmentation software for application in organ contouring of radiotherapy planning / 中华放射肿瘤学杂志

Objective To perform a preclinical test of a delineation software based on atlas-based auto-segmentation (ABAS),to evaluate its accuracy in the delineation of organs at risk (OARs) in radiotherapy planning for nasopharyngeal carcinoma (NPC),and to provide a basis for its clinical application.Methods Using OARs manually contoured by physicians on planning-CT images of 22 patients with NPC as the standard,the automatic delineation using two different algorithms (general and head/neck) of the ABAS software were applied to the following tests:(1) to evaluate the restoration of the atlas by the software,automatic delineation was performed on copied images from each patient using the contours of OARs manually delineated on the original images as atlases;(2) to evaluate the accuracy of automatic delineation on images from various patients using a single atlas,the contours manually delineated on images from one patients were used as atlases for automatic delineation of OARs on images from other patients.Dice similarity coefficient (DSC),volume difference (Vdiff),correlation between the DSC and the volume of OARs,and efficiency difference between manual delineation and automatic delineation plus manual modification were used as indices for evaluation.Wilcoxon signed rank test and Spearman correlation analysis were used.Results The head/neck algorithm had superior restoration of the atlas over the general algorithm.The DSC was positively correlated with the volume of OARs and was higher than 0.8 for OARs larger than 1 cc in volume in the restoration test.For automatic delineation with the head/neck algorithm using a single atlas,the mean DSC and Vdiff were 0.81-0.90 and 2.73％-16.02％,respectively,for the brain stem,temporal lobes,parotids,and mandible,while the mean DSC was 0.45-0.49 for the temporomandibular joint and optic chiasm.Compared with manual delineation,automatic delineation plus manual modification saved 68％ of the time.Conclusions A preclinical test is able to determine the accuracy and conditions of the ABAS software in specific clinical application.The tested software can help to improve the efficiency of OAR delineation in radiotherapy planning for NPC.However,it is not suitable for delineation of OAR with a relatively small volume.