Quantification of Tissue Compression Identifies High-Grade Glioma Patients with Reduced Survival

Simple Summary A growing high-grade glioma exerts a local pressure on its surroundings, resulting in a tissue displacement known as the gross mass effect that is considered a major cause of acute neurological symptoms in patients with brain cancer. Mass effects are usually manifested when significant deformations caused by the tumor growth are observed radiologically or clinically; however, minor deformations in peritumoral tissue could provide early evidence of processes related to tumor relapse and recurrence. In this study, we propose an automated method to quantify the subtle deformations that occur in the peritumoral region. We also propose four biomarkers for differentiating where peritumoral displacements translate into compression. Biomarkers quantifying peritumoral compression were found to be associated with patient progression and prognosis and demonstrated the ability to stratify patients between long-time and short-time survivors. We conclude that compression biomarkers can be key to early treatment assessment during follow-up. The compression of peritumoral healthy tissue in brain tumor patients is considered a major cause of the life-threatening neurologic symptoms. Although significant deformations caused by the tumor growth can be observed radiologically, the quantification of minor tissue deformations have not been widely investigated. In this study, we propose a method to quantify subtle peritumoral deformations. A total of 127 MRI longitudinal studies from 23 patients with high-grade glioma were included. We estimate longitudinal displacement fields based on a symmetric normalization algorithm and we propose four biomarkers. We assess the interpatient and intrapatient association between proposed biomarkers and the survival based on Cox analyses, and the potential of the biomarkers to stratify patients according to their survival based on Kaplan-Meier analysis. Biomarkers show a significant intrapatient association with survival (p < 0.05); however, only compression biomarkers show the ability to stratify patients between those with higher and lower overall survival (AUC = 0.83, HR = 6.30, p < 0.05 for CompCH). The compression biomarkers present three times higher Hazard Ratios than those representing only displacement. Our study provides a robust and automated method for quantifying and delineating compression in the peritumoral area. Based on the proposed methodology, we found an association between lower compression in the peritumoral area and good prognosis in high-grade glial tumors.

Automated summary

This study proposes an automated method to quantify subtle deformations in the peritumoral region and identifies compression biomarkers associated with patient progression and prognosis. The compression biomarkers have the ability to stratify patients based on their survival. This study highlights the importance of compression biomarkers in early treatment assessment.