Sam Brusco, Associate Editor06.26.23
MEDICAL IP, an artificial intelligence (AI)-based digital twin company, has earned U.S. Food and Drug Administration (FDA) 510(k) clearance for its CT-based, automatic body composition analysis AI software, DeepCatch.
The DeepCath SaMD (software as a medical device) automatically segments and analyzes anatomical structures in CT scans and offers results as a report with 3D visual and quantitative info. According to Medical IP, it’s the only FDA-cleared AI software to automatically analyze body components like skin, bone, muscle, visceral fat, subcutaneous fat, internal organ, and central nervous system through whole-body CT.
Last July a CPT code was issued for quantitative CT tissue characterization—including interpretation and report—gathered without concurrent CT examination of any structure contained in previous diagnostic imaging. This FDA clearance will offer DeepCatch to be quickly introduced in the U.S.
Using the software, medical staff can provide further screening for potential body composition-related diseases based on the DeepCatch report. Patients can also receive further info about diseases like obesity, metabolic diseases, or sarcopenia by using CT images taken during treatment or health checkups.
A company official told the press, "DeepCatch has proven that it provides accurate body composition analysis results to anyone regardless of race, gender, or age. It will contribute to the development of the medical industry through fast, accurate, and efficient CT-based body composition analysis technology."
DeepCatch was tested for bias of various CT scanners, medical institutions, race, and ethnicity in a series of multi-national clinical trials. According to the company, accuracy of AI-based analysis—including measurement of volume and area of body components and body circumference—was confirmed through validation.
Unlike methods like BIA (bioelectrical impedance analysis), which are affected by measurement environment or body condition, or DXA (dual-energy X-ray absorptiometry) which can’t separately quantify areas like visceral fat in 3D, DeepCatch can derive clinically valid 3D body composition analysis results using CT.
MEDICAL IP CEO Joon S. Park said, "There are various diseases related to body composition, such as geriatric diseases, cardiovascular diseases, and metabolic diseases such as diabetes and sarcopenia in the elderly and cancer patients, and DeepCatch is a product that can provide additional clinical information on these diseases. DeepCatch can be introduced to any medical institution around the world that takes CT scans, so with this FDA Clearance, we will be able to accelerate our strategy for global expansion."
The DeepCath SaMD (software as a medical device) automatically segments and analyzes anatomical structures in CT scans and offers results as a report with 3D visual and quantitative info. According to Medical IP, it’s the only FDA-cleared AI software to automatically analyze body components like skin, bone, muscle, visceral fat, subcutaneous fat, internal organ, and central nervous system through whole-body CT.
Last July a CPT code was issued for quantitative CT tissue characterization—including interpretation and report—gathered without concurrent CT examination of any structure contained in previous diagnostic imaging. This FDA clearance will offer DeepCatch to be quickly introduced in the U.S.
Using the software, medical staff can provide further screening for potential body composition-related diseases based on the DeepCatch report. Patients can also receive further info about diseases like obesity, metabolic diseases, or sarcopenia by using CT images taken during treatment or health checkups.
A company official told the press, "DeepCatch has proven that it provides accurate body composition analysis results to anyone regardless of race, gender, or age. It will contribute to the development of the medical industry through fast, accurate, and efficient CT-based body composition analysis technology."
DeepCatch was tested for bias of various CT scanners, medical institutions, race, and ethnicity in a series of multi-national clinical trials. According to the company, accuracy of AI-based analysis—including measurement of volume and area of body components and body circumference—was confirmed through validation.
Unlike methods like BIA (bioelectrical impedance analysis), which are affected by measurement environment or body condition, or DXA (dual-energy X-ray absorptiometry) which can’t separately quantify areas like visceral fat in 3D, DeepCatch can derive clinically valid 3D body composition analysis results using CT.
MEDICAL IP CEO Joon S. Park said, "There are various diseases related to body composition, such as geriatric diseases, cardiovascular diseases, and metabolic diseases such as diabetes and sarcopenia in the elderly and cancer patients, and DeepCatch is a product that can provide additional clinical information on these diseases. DeepCatch can be introduced to any medical institution around the world that takes CT scans, so with this FDA Clearance, we will be able to accelerate our strategy for global expansion."