Weill Cornell Medicine develops an AI tool to score and track disease severity in blood cancer from bone marrow imaging.
Key Details
- 1New AI-based method analyzes the spatial architecture and morphology of cells in bone marrow biopsies for myelodysplastic neoplasms (MDS).
- 2Produces the MDS-Microarchitectural Perturbation Score (MDS-MAPS) from 82 features to indicate disease severity.
- 3Tool leverages routinely collected samples and standard imaging protocols, making hospital adoption feasible.
- 4MDS-MAPS shows improved ability to classify disease progression compared to current pathologist methods.
- 5Planned validation studies in larger patient cohorts and other related conditions are underway.
- 6Research also offers insights into gene mutations (e.g., TP53) and their impact on bone marrow structure.
Why It Matters
This method could provide clinicians and patients with clearer, more actionable information for managing MDS, representing a step forward for AI-assisted pathology and precision medicine in hematologic cancer. Adoption of such tools may standardize and improve response assessment in a disease with traditionally subjective analysis.
Source
EurekAlert
Related News
•EurekAlert
AI Pathology Tool SÉMIL Improves Stage II Bowel Cancer Risk Assessment
A La Trobe University-developed AI tool accurately predicts relapse risk in stage II bowel cancer using digital pathology images and descriptions.
•EurekAlert
AI-Guided Handheld Cardiac Ultrasound Reduces Referrals and Costs in Spain
AI-guided handheld cardiac ultrasound enables primary care physicians to detect heart failure, reducing specialist referrals and saving costs.
•EurekAlert
AI Tool Predicts Which Rectal Cancer Patients Benefit from Intensive Therapy
UCL researchers developed an AI that analyzes biopsy slides to identify rectal cancer patients who benefit from adding irinotecan to standard chemoradiotherapy.