Purpose: The costal cartilage is a prominent feature of the anterior chest wall that is subject to developmental and acquired abnormalities. A fully automatic algorithm to reconstruct the human costal cartilage from multidetector computed tomography (MDCT) images was developed and tested.
Methods: The reconstruction algorithm includes three steps: (1) estimation of length, curvature and end points for each costal cartilage centre-line, (2) costal cartilage cross-section area approximation, and (3) transformation of the estimated cross-section to the centre-line into a cylindrical coordinate system. Four different models were as follows: circle, vertical ellipse, horizontal ellipse and a non-geometric shape have been assumed for the cross-section. Shape estimates were based on each patient's dataset, so the algorithm is patient-specific and anatomically faithful. MDCT datasets from 15 patients were evaluated with the automated algorithm and the results compared with reference masks provided by an experienced radiologist.
Results: The costal cartilage reconstruction result and the reference mask were visually consistent. Based on evaluation results, the circular model cross-section with area of twice M (mean area of all rib cross-sections in the mid-coronal plane) had the highest Dice similarity coefficient (DSC = 77.5%) with only 2.12 mm registration distance.
Conclusion: Costal cartilage 3D morphology can be extracted from MDCT scans with an automated method, using a circular cross-section with area equal to twice M.