Combining Novel Imaging Biomarkers with AI-Accelerated Diagnosis for Equitable Patient Selection To Proactive Treatment With Middle Meningeal Artery Embolisation To Improve Outcomes in cSDH

  • Bammer, Roland (Primary Chief Investigator (PCI))
  • Amukotuwa, Shalini (Chief Investigator (CI))
  • Chandra, Ronil (Chief Investigator (CI))
  • Drummond, Katharine Jann (Chief Investigator (CI))
  • Goldschlager, Tony (Chief Investigator (CI))
  • Thijs, Vincent (Chief Investigator (CI))
  • Lim, Kwang (Chief Investigator (CI))

Project: Research

Project Details

Project Description

CHRONIC SUBDURAL HAEMATOMA (cSDH) is a debilitating disease of the elderly that is caused by accumulation of blood & fluid on the brain’s surface. It can lead to life-threatening brain compression (30% 12mo-mortality) & irreversible neurological injury in a vulnerable, frail patient group. Treatment options are limited and often ineffective. cSDH is poised to become the most common intracranial disease needing surgical intervention by 2030, yet the HEALTH SYSTEM IS NOT ADDRESSING IT ADEQUATELY. Surgical evacuation is the mainstay of treatment for cSDH, but associated with high morbidity, mortality, lengthy hospital stays, costs and 40% recurrence, prolonging disability.
MIDDLE MENINGEAL ARTERY EMBOLISATION (MMAE) has recently been introduced as cSDH treatment: arteries that cause fluid exudation are blocked via a minimally-invasive approach. It can be performed as a day procedure and carries less morbidity, mortality, and costs. TARGETING THE RIGHT cSDH PATIENTS FOR MMAE IS CRITICAL since it is an invasive and resource-consuming procedure & to avoid futile treatment. We have developed a unique, world-first battery of imaging-based AI-tools for EARLY DETECTION that can reliably identify patients with cSDHs that are likely to grow BEFORE they need surgery.
PREEMPT is an RCT of preventative MMAE within 2 wk of presentation in patients at high risk of developing brain compression within 90 days. The aim is to decrease disability & hospital stays (+costs & burden) by proactively treating these patients. The trial will be conducted at 10 sites from our established, experienced Australian network. It involves close collaboration between teams at rural & metropolitan areas. The min. sample size (70) has 80% power to detect 30% difference in excellent functional outcome or 50% reduction in need for surgery at 90 days. Adaptive sample size re-estimation after 62 patients allows expansion to a max. sample size (196) to detect a 20% difference in excellent functional outcome.
Short titleAI-guided cSDH patient triage to MMAE
Effective start/end date1/06/2231/12/25