LabCorp, Philips and the Mount Sinai Health System are coming together to develop an artificial intelligence-driven pathology center of excellence, initially aimed at cancer diagnosis.
The center will work to integrate digital pathology into clinical practices across Mount Sinai’s hospitals, starting with interpretations of prostate cancer and other genitourinary tumors, as well as cancers of the head and neck.
From there, the project is slated to expand in scope, to tap Mount Sinai pathologists for consultations for nationwide cases through LabCorp’s Dianon Pathology specialty laboratory, the companies said in a joint statement.
Over the next several months, the center of excellence will deploy Philips’ IntelliSite Pathology Solution for primary diagnosis and consultations at the eight Mount Sinai hospitals across the New York metropolitan area, as well as in select ambulatory care centers. The system’s academic department already processes more than 80 million diagnostic tests a year, the companies said, making it one of the largest of its kind.
“Digital pathology gives us the unprecedented opportunity to expand our services to the community at large and engage members of our department, considered key opinion leaders in their field, to provide expert diagnostic opinions in complex cases,” said Carlos Cordon-Cardo, chairman of Mount Sinai’s pathology department, and a professor of oncological sciences, pathology, and genetics and genomic sciences at the Icahn School of Medicine.
“This, in addition to our new predictive AI-based tests, introduces the potential for optimization of treatment efficacy and provides the opportunity for improved clinical outcomes,” Cordon-Cardo said.
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Mount Sinai had previously participated in the evaluation of Philips’ digital pathology system as it obtained market clearance in the U.S., which helped provide a foundation for the development of Mount Sinai’s AI diagnostics, the companies said.
The Amsterdam-based company’s IntelliSite platform helps pathologists review digital images of surgical pathology slides through an automated management system, including a scanner, high-resolution display and workflow software tools.
The collaboration follows on from Mount Sinai’s plans to establish a broader center for AI and healthcare development at its Icahn School of Medicine.
The Hamilton and Amabel James Center for Artificial Intelligence and Human Health aims to combine AI with data science and genomics at a standalone site in Manhattan, slated to open in late 2021. It plans to launch with about 40 principal investigators, plus 250 graduate students, postdoctoral fellows, computer scientists and support staff.
The center will focus on applying big data and machine learning techniques to genomic data, including single-cell epigenomics and pharmacogenomics, alongside data from patient health records and wearable devices.
In addition, researchers will work to bring AI to diagnostic imaging technologies, including X-ray, MRI, CT and PET scans, as well as molecular imaging.
“We see a huge potential in using algorithms to automate the image interpretation and to acquire images much more quickly at high resolution—so that we can better detect disease and make it less burdensome for the patient,” said Zahi Fayad, director of Mount Sinai’s Translational and Molecular Imaging Institute, and vice chair for research for the Department of Radiology.
“In addition to AI, we envision advance capabilities in two important areas: computer vision and augmented reality, and next-generation medical technology enabling development of new medical devices, sensors and robotics,” Fayad said.