Registration of Longitudinal Liver Examinations for Tumor Progress Assessment

TL;DR

This paper introduces a liver image registration method based on geometrical and anatomical information to improve tumor progression assessment in longitudinal CT scans, ensuring smoother deformations and better tumor volume preservation.

Contribution

A novel registration approach utilizing only liver segmentation data, reducing distortion of tumor regions and enhancing accuracy in tumor progression evaluation.

Findings

Outperforms existing registration techniques in smoothness of deformation.

Preserves tumor burden more effectively during registration.

Validated on a large dataset of longitudinal liver CT scans.

Abstract

Assessing cancer progression in liver CT scans is a clinical challenge, requiring a comparison of scans at different times for the same patient. Practitioners must identify existing tumors, compare them with prior exams, identify new tumors, and evaluate overall disease evolution. This process is particularly complex in liver examinations due to misalignment between exams caused by several factors. Indeed, longitudinal liver examinations can undergo different non-pathological and pathological changes due to non-rigid deformations, the appearance or disappearance of pathologies, and other variations. In such cases, existing registration approaches, mainly based on intrinsic features may distort tumor regions, biasing the tumor progress evaluation step and the corresponding diagnosis. This work proposes a registration method based only on geometrical and anatomical information from liver segmentation, aimed at aligning longitudinal liver images for aided diagnosis. The proposed method is trained and tested on longitudinal liver CT scans, with 317 patients for training and 53 for testing. Our experimental results support our claims by showing that our method is better than other registration techniques by providing a smoother deformation while preserving the tumor burden (total volume of tissues considered as tumor) within the volume. Qualitative results emphasize the importance of smooth deformations in preserving tumor appearance.