ENZERRO

About

Smart catheter system for safer embolization

ENZERRO is an advanced microcatheter system that enhances safety in embolization procedures by detecting reflux, the unintended backward flow of embolic particles into surrounding organs. A miniature sensor continuously monitors pressure and flow, triggering real-time alerts or automatic shutoff if dangerous patterns emerge. AI-powered recognition adapts to patient-specific flow profiles, distinguishing risk from routine variation. Seamlessly integrating into existing workflows, ENZERRO not only improves clinical safety but also supports training, with potential applications across interventional radiology

Trends

# Health Therapies

University

Jordan University of Science and Technology

Team

Mohammad Ajwad Al Salkhadi
Jordan University of Science and Technology
Mohammad Ajwad Al Salkhadi is a medical intern who earned his MD from Jordan University of Science and Technology, with a strong interest in precision medicine and oncology care. He has led award-winning research projects applying AI in healthcare and presented his work at international medical conferences, broadening his perspective on global health challenges. Committed to advancing targeted therapies and improving patient outcomes, he aspires to contribute to the future of global healthcare. Upon completion of his internship, Mohammad Ajwad plans to pursue advanced medical training at the intersection of clinical care, research, and innovation.more
Dr. Hassan Al-Balas
Jordan University of Science and Technology
Supervising Professormore
Dr. Naser Obeidat
Jordan University of Science and Technology
Supervising Professormore
Haitham Alhazaimeh
Jordan University of Science and Technology
Haitham Alhazaimeh is a medical intern who recently earned his medical degree from Jordan University of Science and Technology, with a strong interest in minimally invasive interventional procedures, neurology, and neuroradiology. He has developed and contributed to several projects presented at major international conferences, with several ongoing and submitted studies soon coming to light. His work focuses on applying artificial intelligence and machine learning to real clinical challenges, particularly in medical imaging and image-guided interventions. Haitham has led and collaborated on research across different domains and study designs, including deep learning, large clinical datasets, systematic reviews, observational studies, and AI-assisted research workflows. He is the founder of the Neurology Interest Group at JUST and has mentored multiple students in advancing their research capabilities. His long-term vision is to build a career that combines clinical practice with innovation and research, ultimately developing intelligent, safety-enhancing technologies that improve diagnostic accuracy and procedural outcomes in interventional radiology and neuro-intervention.more