[{"innerBlocks":[],"name":"core\/freeform","postId":102,"blockType":{"name":"core\/freeform","keywords":[],"attributes":{"content":{"type":"string","source":"raw"},"lock":{"type":"object"}},"providesContext":[],"usesContext":[],"selectors":[],"supports":{"className":false,"customClassName":false,"reusable":false},"styles":[],"variations":[],"apiVersion":3,"title":"Classic","description":"Use the classic WordPress editor.","category":"text"},"originalContent":"An algorithm is being paired with existing CT data to identify patients with bone fragility who would be at high risk for bone fractures.A medical study to determine the viability of the approach makes the case that the results can be used to find patients who could benefit from preventive treatment, researchers say.The study was conducted at the Clalit Research Institute and Ben-Gurion University, using an osteoporosis algorithm developed by Zebra Medical Vision, an Israel-based artificial intelligence company.

What\u2019s unique about the research is that the algorithm was shown to be able to calculate bone density and identify existing compression fractures using CT scans that had already been performed for other purposes, thus offering the prospect that clinicians could leverage existing CT studies to find patients at risk for osteoporosis.That would reduce the need for additional procedures, reducing overall cost and radiation exposure for patients.The results are also significant because of the prevalence of osteoporosis, the cost of treating the health issues and the risk of complications from bone fractures. Researchers estimate it costs nearly $18 billion annually in the U.S. alone to treat. Other research suggests that one in three women and one in five men older than 50 will suffer an osteoporotic fracture. In addition, compliance with standard bone density screening is low, so many patients with the condition are not diagnosed or pre-emptively treated.\u201cWe have always been aware that this is a common disease with a high risk of fatality, and even though there are some treatment options for prevention, we don\u2019t identify at-risk patients early enough,\u201d says Eldad Elnekave, MD, CMO at Zebra Medical Vision. \u201cWe found that all the information we need pertaining to at-risk patients already exists in CT tests done for other reasons. It\u2019s time to utilize that information.\u201dThe study, published recently in Nature Medicine Journal, helps illustrate an example of how analytic capabilities and big data techniques can help aid public health.\u201cThere are hidden medical insights in imaging studies that the human eye cannot capture, but have the potential to save lives,\u201d says Ran Balicer, professor and director of the Clalit Research Institute. \u201cWe are on the verge of developing a system that will present improved fracture prediction risk scores to all Clalit physicians and patients."There\u2019s potential to expand the use of the analytics to screen larger populations for osteoporosis, researchers add.\u201cThis AI capability is now proven at scale to be able to massively increase the screened population for osteoporosis without exposing the patients for more imaging scans or radiation,\u201c adds Eyal Gura co-founder and CEO at Zebra Medical Vision.The article on the research can be found here<\/a>.","saveContent":"An algorithm is being paired with existing CT data to identify patients with bone fragility who would be at high risk for bone fractures.A medical study to determine the viability of the approach makes the case that the results can be used to find patients who could benefit from preventive treatment, researchers say.The study was conducted at the Clalit Research Institute and Ben-Gurion University, using an osteoporosis algorithm developed by Zebra Medical Vision, an Israel-based artificial intelligence company.

What\u2019s unique about the research is that the algorithm was shown to be able to calculate bone density and identify existing compression fractures using CT scans that had already been performed for other purposes, thus offering the prospect that clinicians could leverage existing CT studies to find patients at risk for osteoporosis.That would reduce the need for additional procedures, reducing overall cost and radiation exposure for patients.The results are also significant because of the prevalence of osteoporosis, the cost of treating the health issues and the risk of complications from bone fractures. Researchers estimate it costs nearly $18 billion annually in the U.S. alone to treat. Other research suggests that one in three women and one in five men older than 50 will suffer an osteoporotic fracture. In addition, compliance with standard bone density screening is low, so many patients with the condition are not diagnosed or pre-emptively treated.\u201cWe have always been aware that this is a common disease with a high risk of fatality, and even though there are some treatment options for prevention, we don\u2019t identify at-risk patients early enough,\u201d says Eldad Elnekave, MD, CMO at Zebra Medical Vision. \u201cWe found that all the information we need pertaining to at-risk patients already exists in CT tests done for other reasons. It\u2019s time to utilize that information.\u201dThe study, published recently in Nature Medicine Journal, helps illustrate an example of how analytic capabilities and big data techniques can help aid public health.\u201cThere are hidden medical insights in imaging studies that the human eye cannot capture, but have the potential to save lives,\u201d says Ran Balicer, professor and director of the Clalit Research Institute. \u201cWe are on the verge of developing a system that will present improved fracture prediction risk scores to all Clalit physicians and patients."There\u2019s potential to expand the use of the analytics to screen larger populations for osteoporosis, researchers add.\u201cThis AI capability is now proven at scale to be able to massively increase the screened population for osteoporosis without exposing the patients for more imaging scans or radiation,\u201c adds Eyal Gura co-founder and CEO at Zebra Medical Vision.The article on the research can be found here<\/a>.","order":0,"get_parent":{},"attributes":[],"attributesType":{"content":{"type":"string","source":"raw"},"lock":{"type":"object"}},"dynamicContent":""}]

Algorithm assesses CT scans to find patients at risk for bone fractures

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