TU-AB-202-08: Generating Organ Surfaces to Overcome Random Contouring Errors and Slice Thickness Variations On Multimodality Images

Authors


Abstract

Purpose:

To propose a new method that generates smooth organ surface meshes that overcomes random contouring errors and volume averaging artifacts for hollow organs.

Methods:

The proposed contour-to-smooth mesh generation method (CSMG) consists of two parts; 1) reconstructing the inner and outer surfaces of the hollow organ with triangular meshes based on parametric active surface (PAS) and 2) modifying the reconstructed inner surface in order to satisfy minimum wall thickness constraints and matching the patient's known organ wall volume. In both steps, PAS evolved gradually to physician contours by minimizing defined energy functions. CSMG surface meshes were evaluated using two digital phantoms and 72 contours from 3 cervix cancer patients (4 images per patient, 3 organs per image, 2 inner-and-outer-wall contours per organ). The CSMG and treatment planning system (TPS) surface meshes were compared using Gaussian curvature, Dice conformity index (DCI) and signed minimum distance (SMD). DCI and SMD were calculated between the physician contours and the contour extracted by averaging the surface over the slice thickness.

Results:

CSMG meshes were smoother and more continuous than TPS surface meshes. The DCI differences between CSMG and TPS were 0.2%, 0.9% and 1.5% on average for bladder, rectum and vagina, respectively. TPS meshes had larger average SMDs (0.44±0.64, 0.43±0.62 and 0.42±0.61 mm for the three organs) compared to CSMG meshes (0.01±0.84, −0.05±0.93 and 0.13±0.91 mm). Larger grand mean and smaller pooled standard deviation of TPS SMDs implied that TPS overfitted the noise on contours but PM smoothed out the noise. The wall thicknesses were 2.7±1.3, 2.6±1.1 and 1.6±0.5 mm for bladder, rectum and vagina, respectively. The wall volume differed from reference volume less than ±2.5%.

Conclusion:

The proposed method reconstructs the smooth and continuous organ surface from sparsely sampled data points without introducing large systematic errors.

This work was supported in part by Varian Research agreement. The authors have the following disclosures: NIH (Williamson, Hugo, Christensen, and Weiss), Philips research agreement (Hugo and Weiss), Varian license agreement (Hugo and Weiss), Roger Koch fund (Christensen), UpToDate royalties (Weiss). There is no COI.

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