AB038. Establishing a reliable semi-automated segmentation method for assessing chemoradiotherapy effects on the non-tumoral brain
Abstract

AB038. Establishing a reliable semi-automated segmentation method for assessing chemoradiotherapy effects on the non-tumoral brain

Eu Jin Lim1, Nicole Keong Chwee Har2

1Duke-NUS Medical School, Singapore, Singapore; 2Department of Neurosurgery, National Neuroscience Institute, Singapore, Singapore

Correspondence to: Eu Jin Lim, BSc. Duke-NUS Medical School, 8 College Rd., Singapore 169857, Singapore. Email: e0032127@u.nus.edu.

Background: Current voxel-based morphometry (VBM) studies of chemoradiotherapy effects on healthy tissues of the glioblastoma multiforme (GBM) brain face a challenge with neuroanatomical distortions (tumor, tumor edema, and resection cavities) and limited comparisons can be drawn across studies due to lack of a universally accepted software package. Our aim is to compare current semi-automated segmentation methods and optimize them for reliability in investigating the effects of chemoradiotherapy on GBM patients.

Methods: A publicly available dataset was used based on predefined inclusion and exclusion criteria. VBM pipelines CAT12 and FSL were tested and optimized to reduce the impact of neuroanatomical distortions. T1-weighted images were screened, and post-processed with FSL and CAT12. Gray matter (GM) and white matter (WM), and cerebrospinal fluid (CSF) volumes of whole brain, tumour-containing and non-tumor containing hemispheres, pre- and post-chemoradiotherapy were calculated and analyzed with Wilcoxon signed-rank tests. Agreement and consistency between FSL and CAT12 were assessed using Bland-Altman plots and intraclass correlation coefficients (ICCs).

Results: Post-chemoradiotherapy GM volumes were significantly reduced in whole brain with a compensatory significant increase in CSF volumes, while WM volumes had no significant changes. Similar trends were noted in tumor-containing and non-tumor-containing hemispheres. Bland-Altman plots showed good agreement between FSL and CAT12 processed GM and WM volumes of whole brain, tumor-containing, and non-tumor-containing hemispheres. ICC ≥0.70 was observed in GM [0.70 (0.53–0.82)] and WM [0.75 (0.60–0.85)] volumes of non-tumor-containing hemisphere, and WM [0.71 (0.55–0.83)] volumes of whole brain. GM volumes of tumor-containing hemisphere had good agreement but surprisingly, poor consistency [0.50 (0.25–0.68)]. CSF volumes in non-tumor-containing hemisphere had better agreement and consistency [0.55 (0.32–0.71)] than whole brain [0.49 (0.25–0.67)] and tumor-containing hemisphere CSF [0.36 (0.10–0.58)] volumes. Visual inspection revealed both CAT12 and FSL mis-segmented in the presence of neuroanatomical distortion although CAT12 was more susceptible in the presence of a hematoma.

Conclusions: VBM studies of chemoradiotherapy effects on the brain post-tumor resection remain challenging due to neuroanatomical distortions. A reliable alternative is to use non-tumor-containing hemispheres with no anatomical distortion. Should tumor-containing brains be used, FSL is a more suitable choice, especially in the presence of hematoma distortion.

Keywords: Voxel-based morphometry (VBM); glioblastoma; chemoradiotherapy


Acknowledgments

Funding: None.


Footnote

Conflicts of Interest: Both authors have completed the ICMJE uniform disclosure form (available at: https://cco.amegroups.com/article/view/10.21037/cco-24-ab038/coif). E.J.L. reported that he is a recipient of a grant under Duke-NUS Medical School (grant name: AM-ETHOS Duke-NUS Medical Student Fellowship Grant) to support costs of journal publications and conferences. The other author has no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study was conducted using data obtained from the Burdenko’s Glioblastoma Progression Dataset (https://doi.org/10.7937/E1QP-D183). Written informed consent was obtained from all subjects, and participating sites (Burdenko National Medical Research Center of Neurosurgery) involved in the study received approval from their respective governing Institutional Review Boards.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the noncommercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.


Cite this abstract as: Lim EJ, Har NKC. AB038. Establishing a reliable semi-automated segmentation method for assessing chemoradiotherapy effects on the non-tumoral brain. Chin Clin Oncol 2024;13(Suppl 1):AB038. doi: 10.21037/cco-24-ab038

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