HUS developed AI algorithm spots cerebral haemorrhage from CT scan

Neurosurgery researchers at the Helsinki University Hospital (HUS) have been developing an artificial intelligence-based algorithm which can effectively identify a subarachnoid haemorrhage (SAH) from a CT scan, said an official press release on Friday.

A study published in the renowned journal Neurology examines how well the AI-based algorithm works in cerebral haemorrhage diagnostics.

Artificial intelligence was taught at HUS based on material from CT scans performed on the heads of patients undergoing treatment. The functionality of the artificial intelligence tool was also examined against more extensive international data.

Patients arriving at an emergency room complaining of a severe headache are given a computer tomography (CT) scan to eliminate the possibility of a cerebral haemorrhage. Identifying the cause of a cerebral haemorrhage is important for the treatment of the patient. Up to 75 percent of patients with subarachnoid haemorrhage die within a year of a new haemorrhage, if the original haemorrhage is not identified in proper time.

“CT scans of the head are among the most common imaging studies in hospital emergency care and SAH is the most frequent cause of sudden death connected with disturbances in blood circulation in the brain among people of working age. The AI algorithm was capable of precise detection of subarachnoid haemorrhages. Artificial intelligence could assist radiologists in the interpretation of images by sorting out the CT images which require urgent attention, said Miikka Korja, Chief Neurosurgeon at Neurocenter. 

The artificial intelligence tool correctly identified 136 of 137 cases of subarachnoid haemorrhage out of a total of 1,300 CT scans. The material comprised a 49,000 image slices from which artificial intelligence identified SAH in 1845 slices out of 2,110 image slices.

“Opening the artificial intelligence algorithm transparently for use by the research community is a significant innovation in the field of medical imaging and we consider this type of action to be of central importance for developing models for clinical work based on artificial intelligence”, said Heikki Peura, a HUS doctor and one of the two main researchers of the project.

The artificial intelligence algorithm which identifies subarachnoid haemorrhages, has been openly distributed for further development.

HUS hopes to get the package clinically tested in 2023, and also hopes that in the future it can get official approval for the use of the algorithm in patient care as well.