In a new study, researchers found a novel method of combining advanced optical imaging with an artificial intelligence (AI) algorithm that produces an accurate, real-time diagnosis of brain tumors.
The research was conducted by a team at NYU Grossman School of Medicine and elsewhere.
In the study, to build the AI tool, the researchers trained a deep convolutional neural network with more than 2.5 million samples from 415 patients to classify tissue into 13 histologic categories that represent the most common brain tumors, including malignant glioma, lymphoma, metastatic tumors, and meningioma.
In order to validate the neural network, the team enrolled 278 patients undergoing brain tumor resection or epilepsy surgery at three university medical centers in the prospective clinical trial.
They examined the diagnostic accuracy of brain tumor image classification through machine learning, compared with the accuracy of pathologist interpretation of conventional histologic images.
The results for both methods were comparable: the AI-based diagnosis was 94.6% accurate, compared with 93.9% for the pathologist-based interpretation.
The imaging technique stimulated Raman histology (SRH), reveals tumor infiltration in human tissue by collecting scattered laser light, illuminating essential features not typically seen in standard histologic images.
The microscopic images are then processed and analyzed with artificial intelligence, and in under two and a half minutes, surgeons are able to see a predicted brain tumor diagnosis.
Using the same technology, after the resection, they are able to accurately detect and remove the otherwise undetectable tumor.
The team says with this imaging technology, cancer operations are safer and more effective than ever before.
The implementation of this new tool is the most recent of NYU Langone’s efforts to integrate AI in clinical practice to improve the diagnostics of cancer.
Researchers and clinicians at NYU Langone’s Perlmutter Cancer Center have made recent strides in lung cancer, breast cancer, and brain tumor.
One author of the study is Daniel A. Orringer, MD, an associate professor of Neurosurgery.
The study is published in Nature Medicine.
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