Written by 2:12 pm AI, Discussions, Uncategorized

– Leveraging AI Tool for Muscle Mass Evaluation: Experts’ Innovative Approach

The growth chart could be a fast and accessible resource to indicate lean muscle mass in children.

As per research conducted by experts from Brigham and Women’s Hospital, a growth chart has been devised to monitor muscle size in growing children. An AI-driven tool has been created by the researchers to track muscle mass indicators through routine MRIs. This tool is reported to offer a consistent, accurate, and reliable option for children facing challenges with low muscle mass.

The image is credited to Kamon_saejueng on adobe.com.

Individuals with conditions leading to reduced lean muscle mass are at a higher risk of premature mortality or various ailments that can diminish their quality of life, as per the press release. Conversely, lean muscle mass has been linked to survival and overall well-being. Previously, the assessment of lean muscle mass relied on the body mass index (BMI) with limited additional methods. However, researchers noted a limitation in using BMI as it does not differentiate between muscle and fat content in the body. While other techniques were utilized by scientists to measure muscle strength, they proved to be ineffective.

There is currently no standardized method to gauge the extent of muscle mass challenges in pediatric cancer patients. Dr. Ben Kann, a radiation oncologist and senior author of Mass General Brigham’s Synthetic Intelligence in Medicine Program, expressed the inspiration behind employing artificial intelligence to evaluate temporalis body thickness and establish a consistent reference point. This innovative approach led to the creation of a growth chart that enables the continuous monitoring of muscle texture development in children, ensuring they are progressing appropriately.

Collaborating with the Boston Children’s Radiology Department, the researchers analyzed MRI scans of pediatric patients treated for brain tumors at Boston Kids’ Hospital/Dana-Farber Cancer Institute to develop the AI tool. By studying 23,852 individuals with normal brain MRI scans aged between 4 and 35, a standard-reference growth chart for temporalis body thickness (iTMT) was formulated.

The researchers successfully generated sex-specific iTMT normal progression charts with peaks and percentiles suitable for diverse populations, as highlighted in the press release.

Similar to the customary use of height and weight growth charts in medical settings, Dr. Kann mentioned in a statement that the objective is to utilize this growth chart to evaluate each patient’s muscle mass within the normal spectrum.

The press release emphasized the significance of accurate measurements and the potential impact of suboptimal decisions on interpretations and outcomes. The scarcity of MRI datasets beyond the United States and Europe poses a challenge in creating a comprehensive global overview.

Nonetheless, the researchers remain hopeful that the growth chart development could enable healthcare professionals to promptly assist individuals grappling with muscle issues.

Looking ahead, Dr. Kann expressed the prospect of exploring whether iTMT values could justify routine MRIs for a broader audience. The intention is to further train the model on complex cases to enhance its performance. Future applications of iTMT could facilitate disease monitoring, prognosis, and identification of critical physiological conditions requiring intervention.

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Last modified: February 21, 2024
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