Assessing Fat and Muscle Separately: AIRS Medical MRI Analysis Software Receives FDA Clearance

Changes in body weight do not necessarily reveal what is happening inside the body: where fat is stored and whether muscle is being lost require more detailed measurements. On October 5, AIRS Medical announced that its artificial intelligence MRI analysis software, SwiftSight Body Composition, had received 510(k) clearance from the U.S. Food and Drug Administration (FDA). SimonMed Imaging will become its first customer to adopt the software, giving this body composition analysis tool a concrete setting for use.

The software is designed to turn images into comparable tissue measurements. According to the company's product page, after images of the abdomen, liver and thighs are acquired, AI automatically identifies and segments muscle and fat regions to generate a structured report. The manufacturer says image acquisition can be completed within five minutes. This refers to scan time and cannot be taken directly as the total examination time from check-in to receipt of the report.

One focus of the analysis is to measure subcutaneous fat separately from visceral fat within the abdominal cavity and around organs. In addition to composition proportions, muscle assessment examines fat infiltration within muscle as an imaging indicator of “muscle quality.” This information can supplement differences that body weight and body mass index (BMI) cannot readily capture, but muscle composition on imaging still cannot directly replace assessments of muscle strength or physical function.

Liver fat is also part of the report. The product page states that the software calculates the mean proton density fat fraction (PDFF) using three regions of interest and includes a color distribution map, providing a trackable numerical measure of liver fat content. Repeat examinations can be used to compare changes in fat distribution, muscle composition and liver fat. MRI's lack of ionizing radiation provides one condition that supports ongoing monitoring.

However, interpreting the values also requires knowing the basis for comparison. The company says reports provide percentile information using an age- and sex-matched reference population, but this press release and the product page do not disclose the size or population composition of the reference database. Nor do they list segmentation accuracy, repeat measurement error or validation results across scanner models. The product page also notes that the demonstration report uses synthetic patient data, so the displayed images cannot be treated as evidence of clinical validation.

510(k) clearance means that the FDA permits the product to enter the U.S. market under a framework of substantial equivalence to legally marketed devices. It does not, by itself, demonstrate that adding this measurement to health management can improve patient health outcomes. The clearance is stated in both the company's press release and its product page, both of which are manufacturer sources. Formal regulatory documents are still needed to confirm the full scope of intended use and limitations on use.

SimonMed's planned adoption means the tool will enter actual imaging service workflows, but the current announcement does not specify a launch date, deployment locations or pricing arrangements. The next key question is whether these measurements can remain consistent in routine examinations and help healthcare professionals understand changes more clearly. When a report shows changes in fat or muscle composition, interpreting them alongside other clinical information is the next step toward turning numbers into medical value.