Researchers use 3D printed blood vessels to study strokes
Simulations show natural blood-flow patterns - long considered the hardest part to reproduce
According to the University of Sydney, 3D printed blood vessels on glass that replicate real vascular anatomy and blood-flow behaviour could become a powerful tool for understanding stroke. The research, published in Advanced Materials, is already producing insights and may eventually help clinicians test treatments tailored to individual patients.
“We’re not just printing blood vessels – we’re printing hope for millions at risk of stroke worldwide. With continued support and collaboration, we aim to make personalised vascular medicine accessible to every patient who needs it,” said PhD candidate Charles Zhao from the School of Biomedical Engineering.
Coming from a mechanical engineering background, Zhao applied his fluid-dynamics expertise to replicate both healthy and damaged blood vessels, including microscopic dents and divots seen in stroke patients. Using CT scans as blueprints, the team miniaturized carotid artery models to 200–300 micrometres (full size is 5–7 mm) and cut manufacturing time from 10 hours to two. Instead of resin moulds – which are slow and error-prone – they printed directly onto glass slides, producing structures that resemble delicate engravings.
“When it comes to heart attack and stroke diagnosis, speed and accuracy is key,” said Zhao, the first graduate student and founding member of the Mechanobiology and Biomechanics Laboratory (MBL). “Clinicians typically have an approximately 12-hour decision-making window after symptom onset.”
The resulting ‘artery on a chip‘ successfully mimicked real blood vessels, and simulations showed natural blood-flow patterns – long considered the hardest part to reproduce. Blood viscosity varies between patients, and this affects clot-forming behaviour. Dr Zihao Wang, postdoctoral chief engineer of the MBL group, noted that this “first-of-its-kind bioengineering endeavour in Australia” aims to fill major gaps in heart-disease prediction without using animal models.
During testing, researchers observed platelet behaviour and clot formation in real time. Areas experiencing higher mechanical stress – common in hypertension and atherosclerosis – showed seven to ten times more platelet movement, a critical factor in stroke risk.
Professor Arnold Ju said the team had created a ‘physical twin’ of patient blood vessels. Helen Zhao added that the next step is integrating AI to build digital twins that can forecast stroke before it occurs: “Imagine a future where we can take a patient’s CT scan, rapidly print their blood vessel model, test their blood response, and use AI to predict their stroke risk years in advance.”
The work brings together the School of Biomedical Engineering, Charles Perkins Centre, and the Heart Research Institute, supported by the Snow Medical Research Foundation and the National Heart Foundation.
