Icometrix Gets First CPT III Code Issued by AMA for AI Brain MRI Software
Reportedly receiving the first Current Procedural Terminology (CPT) III code from the American Medical Association (AMA) for artificial intelligence (AI)-enabled brain magnetic resonance imaging (MRI) software, Icometrix says its adjunctive quantification software can be utilized for diagnosis and assessment of conditions ranging from Alzheimer’s disease and epilepsy to stroke and dementia.
Creating a potential path for reimbursement, the American Medical Association (AMA) has issued a Current Procedural Terminology (CPT) III code for the use of icometrix’s artificial intelligence (AI)-powered brain magnetic resonance imaging (MRI) quantification software.
Icometrix, which has five Food and Drug Administration (FDA)-cleared AI software applications for brain MRI and computed tomography (CT), said the CPT III code is the first one issued for adjunctive AI quantification of brain MRI scans.
“Precision medicine is vital for improving treatment of neurological conditions, and especially for multiple sclerosis,” noted Tim Coetzee, PhD, the chief advocacy, services, and science officer at the National Multiple Sclerosis Society. “This recognition creates a path for icometrix’s innovative technology to be integrated into the management of multiple sclerosis (MS) and takes us one step closer to a future where precision medicine guides treatment decisions.”
Icobrain ms, one of the aforementioned AI software applications, facilitates objective quantification and tracking of white matter hyperintensities on FLAIR, TI MRI and contrast-enhanced T1 MRI, according to icometrix. The company added that its portfolio of AI-enabled neuroimaging software can be utilized in the diagnosis and assessment of treatment for conditions ranging from Alzheimer’s disease and MS to stroke and epilepsy.
Meta-Analysis Shows Merits of AI with CTA Detection of Coronary Artery Stenosis and Calcified Plaque
April 16th 2025Artificial intelligence demonstrated higher AUC, sensitivity, and specificity than radiologists for detecting coronary artery stenosis > 50 percent on computed tomography angiography (CTA), according to a new 17-study meta-analysis.
Can CT-Based AI Radiomics Enhance Prediction of Recurrence-Free Survival for Non-Metastatic ccRCC?
April 14th 2025In comparison to a model based on clinicopathological risk factors, a CT radiomics-based machine learning model offered greater than a 10 percent higher AUC for predicting five-year recurrence-free survival in patients with non-metastatic clear cell renal cell carcinoma (ccRCC).
