Textural analysis as an instrument to detect differences on sacral chordoma MRI post-radiation therapy.

OBJECTIVE

Sacral chordoma is a rare bone tumor frequently treated with pre-surgical radiation; however, treatment response is difficult to determine based on imaging features of conventional MRI. We hypothesized that MRI texture analysis may be capable of demonstrating the effects of radiation therapy.

MATERIALS AND

METHODS

We retrospectively examined pre- and post-radiation therapy MRI of patients with sacral chordomas. Firstly, the regions of interest delimiting the largest cross-sectional area of the tumors on coronal T1-weighted images were compared between pre- and post-radiation therapy MRI. Texture analysis features were extracted, analyzed, and classified. Secondly, all the coronal T1-weighted images were compared using large language models (LLM) to extract texture features.

RESULTS

A total of 22 patients received pre-surgical radiation therapy (RT) and obtained pre- and post-radiation therapy MRI. A linear discriminant analysis model of the top 10 texture analysis features classified correctly 79.5% of chordomas pre- vs. post-treatment. The top 4 textural features had 81.8% sensitivity and 77.2% specificity in differentiating pre- vs. post-radiation chordomas, with a receiver operator area under the curve (AUC) of 84.5% (P = 0.003). Three texture features were related to pixel relationships and one to variations in pixel gray level (wavelet). The second approach using all the coronal-T1 images analyzing gray-level co-occurrence matrix (GLCM) features revealed a significant increase in correlation after RT (mean pre, 0.92; mean post, 0.95; P = 0.016).

CONCLUSION

Texture analysis is a quantitative tool capable of differentiating pre- and post-radiotherapy chordomas and may provide biomarkers of treatment response.