AI Software HealthOST Gets FDA 510(k) Clearance for Enhanced CT Analysis of Vertebral Compression Fractures
The new artificial intelligence-powered software from Nanox reportedly identifies findings suggestive of compression fractures and low density on computed tomography (CT) images and facilitates more precise measurement of these fractures.
Seventy-five percent of compression fractures are misdiagnosed or not reported, according to the World Congress of Osteoporosis. However, an emerging artificial intelligence (AI) software platform, which just received FDA 510(k) clearance, may help improve the assessment of vertebral compression fractures with computed tomography (CT).
Nanox said the AI software HealthOST provides enhanced qualitative and quantitative analysis of spine CT images to help assess patients for musculoskeletal diseases such as osteoporosis. This analysis includes:
• labeling of T1-L4 vertebrae
• measurement of height loss in each of these vertebra
• measurement of mean Hounsfield units (HUs) in volume of interest within vertebra (T11-L4)
Indicated for patients 50 years of age and older who are getting CT imaging for at least four vertebrae in either the T1-L4 or T11-L4 areas of the spine, HealthOST helps detect findings that are suspicious for possible compression fractures and low bone density, according to Nanox.
“With the FDA clearance of HealthOST, we are thrilled to offer radiologists a new tool that provides deeper analysis of medical images to support identifying these patients who may be at risk of developing prevalent musculoskeletal conditions, such as osteoporosis, to help promote further workup and treatment of these patients,” noted Pini Ben Elazar, the general manager of Nanox.AI.
Newsletter
Stay at the forefront of radiology with the Diagnostic Imaging newsletter, delivering the latest news, clinical insights, and imaging advancements for today’s radiologists.
Twenty Years of CT Colonography for Colorectal Cancer Screening: What the Research Reveals
July 29th 2025Computed tomography colonography (CTC) demonstrated a 91.6 percent positive predictive value (PPV) for polyps > 6 mm, according to new research involving over 9,000 patients who underwent CTC for primary asymptomatic colorectal cancer screening.
Chest CT for Post-COVID-19 Abnormalities: Nine Takeaways from a Multi-Society Consensus Statement
July 22nd 2025Developed by 21 thoracic radiologists, the new international consensus statement addresses appropriate indications, scan acquisition and keys to reporting for the use of chest CT imaging in evaluating for residual lung abnormalities from COVID-19.
Study Reveals Significant Prevalence of Abnormal PET/MRI and Dual-Energy CT Findings with Long Covid
July 22nd 2025In a prospective study involving nearly 100 patients with Long Covid, 57 percent of patients had PET/MRI abnormalities and 90 percent of the cohort had abnormalities on dual-energy CT scans.
