Feasibility of multi-atlas cardiac segmentation from thoracic planning CT in a probabilistic framework.

Toxicity to cardiac and coronary structures is an important late morbidity for patients undergoing left-sided breast radiotherapy. Many current studies have relied on estimates of cardiac doses assuming standardised anatomy, with a calculated increase in relative risk of 7.4% per Gy (mean heart dose). To provide individualised estimates for dose, delineation of various cardiac structures on patient images is required. Automatic multi-atlas based segmentation can provide a consistent, robust solution, however there are challenges to this method. We are aiming to develop and validate a cardiac atlas and segmentation framework, with a focus on the limitations and uncertainties in the process. We present a probabilistic approach to segmentation, which provides a simple method to incorporate inter-observer variation, as well as a useful tool for evaluating the accuracy and sources of error in segmentation. A dataset consisting of 20 planning computed tomography (CT) images of Australian breast cancer patients with delineations of 17 structures (including whole heart, four chambers, coronary arteries and valves) was manually contoured by three independent observers, following a protocol based on a published reference atlas, with verification by a cardiologist. To develop and validate the segmentation framework a leave-one-out cross-validation strategy was implemented. Performance of the automatic segmentations was evaluated relative to inter-observer variability in manually-derived contours; measures of volume and surface accuracy (Dice similarity coefficient (DSC) and mean absolute surface distance (MASD), respectively) were used to compare automatic segmentation to the consensus segmentation from manual contours. For the whole heart, the resulting segmentation achieved a DSC of [Formula: see text], with a MASD of [Formula: see text] mm. Quantitative results, together with the analysis of probabilistic labelling, indicate the feasibility of accurate and consistent segmentation of larger structures, whereas this is not the case for many smaller structures, where a major limitation in segmentation accuracy is the inter-observer variability in manual contouring.

Recovery of the sub-basal nerve plexus and superficial nerve terminals after corneal epithelial injury in mice.

Our aim was to compare regeneration of the sub-basal nerve plexus (SBNP) and superficial nerve terminals (SNT) following corneal epithelial injury. We also sought to compare agreement when quantifying nerve parameters using different image analysis techniques. Anesthetized, female C57BL/6 mice received central 1-mm corneal epithelial abrasions. Four-weeks post-injury, eyes were enucleated and processed for PGP9.5 to visualize the corneal nerves using wholemount immunofluorescence staining and confocal microscopy. The percentage area of the SBNP and SNT were quantified using: ImageJ automated thresholds, ImageJ manual thresholds and manual tracings in NeuronJ. Nerve sum length was quantified using NeuronJ and Imaris. Agreement between methods was considered with Bland-Altman analyses. Four-weeks post-injury, the sum length of nerve fibers in the SBNP, but not the SNT, was reduced compared with naïve eyes. In the periphery, but not central cornea, of both naïve and injured eyes, nerve fiber lengths in the SBNP and SNT were strongly correlated. For quantifying SBNP nerve axon area, all image analysis methods were highly correlated. In the SNT, there was poor correlation between manual methods and auto-thresholding, with a trend towards underestimating nerve fiber area using auto-thresholding when higher proportions of nerve fibers were present. In conclusion, four weeks after superficial corneal injury, there is differential recovery of epithelial nerve axons; SBNP sum length is reduced, however the sum length of SNTs is similar to naïve eyes. Care should be taken when selecting image analysis methods to compare nerve parameters in different depths of the corneal epithelium due to differences in background autofluorescence.