Patient-specific AI technique could make minimally invasive surgeries safer and more precise

Researchers from MIT and collaborating institutions have developed an innovative technique that utilizes artificial intelligence to rapidly and accurately match real-time X-rays taken during surgeries with patients' preoperative 3D medical scans. This breakthrough technique, named xvr (X-ray volume registration), could significantly enhance the safety and precision of minimally invasive surgical procedures.

Traditionally, clinicians perform minimally invasive surgeries using real-time X-rays to guide devices like catheters and endoscopes through tiny incisions. However, the flat nature of X-rays makes it difficult to determine the exact location and orientation of surgical tools within the patient's body, increasing the risk of complications. Clinicians may manually align X-rays with preoperative 3D medical images, but this process is slow and challenging for many patients.

The xvr system, created by the researchers, uses an AI model that adapts to each patient in approximately five minutes. This AI model automatically matches a patient's X-rays with 3D scans in seconds with submillimeter precision. The xvr framework outperforms existing AI methods by an order of magnitude across various patients, body parts, and medical procedures.

This advancement in AI technology has the potential to make highly specialized lifesaving procedures more accessible to a broader population, as many Americans live more than an hour away from centers capable of performing noninvasive procedures, such as emergency stroke interventions. By combining 2D X-ray information with 3D medical scans, the xvr system allows for safer and more efficient surgical procedures.