Numerous diseases, including obesity and metabolic disorders like sarcopenia, osteoporosis, cardiovascular disease, and diabetes, have been established to have a strong correlation with body composition. This implies that the proportional distribution of different elements within the human body significantly impacts overall health.
Given the global population's aging trend, the prevention of diseases prior to their onset has gained paramount significance.
Medical IP, a Korean digital twin-based medical artificial intelligence (AI) solutions company, announced its ambition to provide a new global standard with DeepCatch, the world's first whole-body composition analysis AI solution.
According to the company, DeepCatch has been consistently utilized in medical research across different areas since its launch. Its effectiveness has been confirmed through its application in over 20 SCI-grade journals.
"DeepCatch has proven its applicability in predicting the occurrence of body composition-related diseases and the survival rate of cancer patients," the company said. "In addition, based on DeepCatch's body composition analysis results, the company is planning on conducting a clinical trial to predict the occurrence of chronic diseases and diseases that are difficult to accurately diagnose."
A study published in Radiology has validated the clinical use of DeepCatch. The study demonstrated a correlation between adipopenia and the five-year overall survival rate of patients with non-small cell lung cancer (NSCLC). It further suggested that DeepCatch could be utilized to predict the mortality risk for these patients.
Another paper recently published in Nature Medicine, titled "Body Composition and Lung Cancer-associated cachexia in TRACERx," also mentioned analysis of the body composition of lung cancer patients from CT images using DeepCatch.
"The study found that patients with a loss of more than 20 percent of skeletal muscle or adipose tissue had lower lung cancer-specific survival or overall survival rate," the company said.
Multiple studies have generated significant interest within the healthcare sector, highlighting the need for a proactive and effective health management and monitoring solution. Consequently, the company anticipates an increase in demand for DeepCatch as a response to this growing interest.
Since receiving approval from the Ministry of Food and Drug Safety in December 2020, DeepCatch has been installed at medical centers to provide extensive health screenings to patients.
"DeepCatch has helped provide additional information on various diseases to examinees that have undergone CT scans for screening purposes and have received positive feedback from such centers for enhancing their health management plan," the company said.
Medical IP to target global market with DeepCatch
The company also plans to accelerate DeepCatch's entry into the U.S. market as it received 510(k) clearance from the U.S. Food and Drug Administration on Wednesday.
In addition, Medical IP plans to use the FDA nod in the medical market of countries requiring FDA certification, such as the Middle East and Southeast Asia.
To advance into Europe, the company recently participated in the European Society of Gastrointestinal and Abdominal Radiology (ESGAR) 2023, where it presented three research abstracts using DeepCatch.
Notably, during the conference, the company received several proposals to use DeepCatch's accurate body composition analysis results to establish a standard value suitable for the population of a specific country and introduce it into national health management.
"Unlike the bioelectrical impedance analysis (BIA) method, which is affected by the measurement environment or physical condition, DeepCatch can obtain clinically useful results through a whole-body CT," Medical IP CEO Park Sang-joon said. "We hope that DeepCatch, which helps to easily and accurately analyze human body information, will be used as a solution to sustain a healthy life globally."
Park also stressed that MRI-based DeepCatch is also about to be released soon after the technology development is over.
"When MRI-based DeepCatch is combined with the existing CT-based DeepCatch, a new standard of body composition analysis will be created that can be used for predicting disease prognosis and managing health by accurately analyzing body composition with imaging equipment," Park said.