Artificial Intelligence Tool To Help Make Real Time Diagnosis During Surgery, Says Study

The study was published in journal Nature Biomedical Engineering.

A new study has demonstrated the development of an artificial intelligence tool to assist in real-time diagnosis during surgery, boosting the quality of images to increase the accuracy of rapid diagnostics.

The study was published in Nature Biomedical Engineering and has been titled ‘AI method can make time-sensitive, critical diagnosis easier and more accessible to pathologists.’ According to the research, artificial used to translate between frozen sections and the gold-standard approach.¬†

Faisal Mahmood, PhD, Corresponding Author, Division of Computational Pathology at US-based Brigham and Women’s Hospital said in a press release, “We are using the power of artificial intelligence to address an age-old problem at the intersection of surgery and pathology. Making a rapid diagnosis from frozen tissue samples is challenging and requires specialized training, but this kind of diagnosis is a critical step in caring for patients during surgery.”

According to the study, pathologists utilise formalin-fixed and paraffin-embedded (FFPE) tissue samples to make final diagnoses. This process preserves tissue in a way that yields high-quality images but is labour-intensive and can take several days. To ensure a rapid diagnosis which takes minutes, cryosectioning is used which involves fast freezing tissue, cutting sections and observing these thin slices under a microscope. The drawback of this approach is that it can distort cellular details and compromise or tear delicate tissue.

The researchers then created a deep-learning model that can translate between frozen sections and more commonly used FFPE tissue. The team’s research demonstrated that the method can subtype various types of cancer, including gliomas and non-small-cell lung tumours.

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Furthermore, the authors state that prospective clinical studies in real-world hospital settings should be conducted in the future to confirm and validate the artificial intelligence method in terms of diagnostic accuracy and surgical decision-making.

“Our work shows that AI has the potential to make a time-sensitive, critical diagnosis easier and more accessible to pathologists. And it could potentially be applied to any type of cancer surgery. It opens up many possibilities for improving diagnosis and patient care,” Dr Mahmood stated in the press release.¬†

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