A new study published in CNS Oncology demonstrates how artificial intelligence and advanced imaging analysis can help predict survival in patients with recurrent glioblastoma, the most aggressive form of brain cancer.
The research, led by Dr. Benjamin M. Ellingson and colleagues at UCLA, utilized Neosoma's innovative NSHGlio AI technology to perform precise measurements of tumor volumes across multiple timepoints. This automated segmentation technology, combined with novel radio-pathomic mapping techniques pioneered by Dr. Peter LaViolette at the Medical College of Wisconsin, enabled researchers to track both volumetric changes and cellular characteristics of tumors over time.
Key findings from the study revealed:
Post-treatment volumetric growth rates were significantly correlated with overall survival
Changes in tumor cellularity provided additional predictive value
The combination of AI-powered volumetric analysis and radio-pathomic mapping offered new insights into treatment response
"This research demonstrates the power of combining advanced AI segmentation with novel imaging biomarkers," said Dr. Ellingson. "The Neosoma platform's ability to provide consistent, accurate tumor measurements was essential to our analysis."
The study represents an important collaboration between academic research and industry innovation. Neosoma's AI technology, designed specifically for brain tumor analysis, provided the foundational measurements that enabled the broader investigation of cellular growth kinetics and their relationship to patient outcomes.
Reference: Oshima S, Yao J, Bobholz S, et al. Radio-pathomic estimates of cellular growth kinetics predict survival in recurrent glioblastoma. CNS Oncology. 2024;13(1):2415285.
To read the complete paper, please click here.
コメント