Deltoid Muscle Ultrasound May Help Detect Diabetes
By MedImaging International staff writers Posted on 24 Jan 2022 |

Image: Normal gradient of the deltoid muscle to the supraspinatus tendon (A), and reversal in a T2D patient (D: Deltoid, S: Supraspinatus, H: Humerus) (Photo courtesy of RSNA)
A new study suggests that sonographic evaluation of the deltoid muscle could provide a dedicated, simple, and noninvasive method to detect type 2 diabetes (T2D).
For the study, researchers at Henry Ford Hospital (Detroit, MI, USA) conducted deltoid muscle ultrasound imaging of 124 diabetic patients, who were categorized as obese T2D, non-obese T2D, obese non-T2D diabetes, and non-obese non-T2D diabetes. Three musculoskeletal radiologists (blinded to patient category) measured grayscale pixel intensity of the deltoid muscle and humeral cortex to calculate a muscle/bone ratio for each patient. Age, gender, race, body mass index (BMI), insulin usage, and hemoglobin A1c level were analyzed, and the difference among the four groups was compared.
Following baseline measurement, and over a period of three weeks, repeated measurements were done on 40 patients at time. The results showed a statistically significant difference in muscle/bone ratios between the groups; obese T2D - 0.54; non-obese T2D - 0.48; obese non-T2D diabetes - 0.42; and non-obese non-T2D diabetes, 0.35. The overall sensitivity for detecting type 2 diabetes was 80%, with a specificity of 63%. The study was presented at the RSNA annual meeting, held during November 2021 in Chicago (IL, USA).
“Quantitative deltoid muscle ultrasound can detect type two diabetes with the potential for a highly sensitive noninvasive screening method,” concluded lead author and study presenter Steven Bishoy Soliman, DO, RMSK. “This process could translate into a dedicated, simple and noninvasive screening method to detect T2D. The process could help identify some of the 232 million undiagnosed persons globally and could prove especially beneficial in screening of underserved and underrepresented communities.”
In healthy patients, the echogenic appearance of deltoid muscle is darker than that of the underlying rotator cuff tendon. For diabetic patients, the gradient is just the opposite, and the deltoid muscle appears much brighter. The researchers theorized that the brighter appearance is due to low levels of glycogen in the muscle caused by patients’ insulin resistance.
Related Links:
Henry Ford Hospital
For the study, researchers at Henry Ford Hospital (Detroit, MI, USA) conducted deltoid muscle ultrasound imaging of 124 diabetic patients, who were categorized as obese T2D, non-obese T2D, obese non-T2D diabetes, and non-obese non-T2D diabetes. Three musculoskeletal radiologists (blinded to patient category) measured grayscale pixel intensity of the deltoid muscle and humeral cortex to calculate a muscle/bone ratio for each patient. Age, gender, race, body mass index (BMI), insulin usage, and hemoglobin A1c level were analyzed, and the difference among the four groups was compared.
Following baseline measurement, and over a period of three weeks, repeated measurements were done on 40 patients at time. The results showed a statistically significant difference in muscle/bone ratios between the groups; obese T2D - 0.54; non-obese T2D - 0.48; obese non-T2D diabetes - 0.42; and non-obese non-T2D diabetes, 0.35. The overall sensitivity for detecting type 2 diabetes was 80%, with a specificity of 63%. The study was presented at the RSNA annual meeting, held during November 2021 in Chicago (IL, USA).
“Quantitative deltoid muscle ultrasound can detect type two diabetes with the potential for a highly sensitive noninvasive screening method,” concluded lead author and study presenter Steven Bishoy Soliman, DO, RMSK. “This process could translate into a dedicated, simple and noninvasive screening method to detect T2D. The process could help identify some of the 232 million undiagnosed persons globally and could prove especially beneficial in screening of underserved and underrepresented communities.”
In healthy patients, the echogenic appearance of deltoid muscle is darker than that of the underlying rotator cuff tendon. For diabetic patients, the gradient is just the opposite, and the deltoid muscle appears much brighter. The researchers theorized that the brighter appearance is due to low levels of glycogen in the muscle caused by patients’ insulin resistance.
Related Links:
Henry Ford Hospital
Latest Ultrasound News
- Wireless Chronic Pain Management Device to Reduce Need for Painkillers and Surgery
- New Medical Ultrasound Imaging Technique Enables ICU Bedside Monitoring
- New Incision-Free Technique Halts Growth of Debilitating Brain Lesions
- AI-Powered Lung Ultrasound Outperforms Human Experts in Tuberculosis Diagnosis
- AI Identifies Heart Valve Disease from Common Imaging Test
- Novel Imaging Method Enables Early Diagnosis and Treatment Monitoring of Type 2 Diabetes
- Ultrasound-Based Microscopy Technique to Help Diagnose Small Vessel Diseases
- Smart Ultrasound-Activated Immune Cells Destroy Cancer Cells for Extended Periods
- Tiny Magnetic Robot Takes 3D Scans from Deep Within Body
- High Resolution Ultrasound Speeds Up Prostate Cancer Diagnosis
- World's First Wireless, Handheld, Whole-Body Ultrasound with Single PZT Transducer Makes Imaging More Accessible
- Artificial Intelligence Detects Undiagnosed Liver Disease from Echocardiograms
- Ultrasound Imaging Non-Invasively Tracks Tumor Response to Radiation and Immunotherapy
- AI Improves Detection of Congenital Heart Defects on Routine Prenatal Ultrasounds
- AI Diagnoses Lung Diseases from Ultrasound Videos with 96.57% Accuracy
- New Contrast Agent for Ultrasound Imaging Ensures Affordable and Safer Medical Diagnostics
Channels
Radiography
view channel
AI Detects Fatty Liver Disease from Chest X-Rays
Fatty liver disease, which results from excess fat accumulation in the liver, is believed to impact approximately one in four individuals globally. If not addressed in time, it can progress to severe conditions... Read more
AI Detects Hidden Heart Disease in Existing CT Chest Scans
Coronary artery calcium (CAC) is a major indicator of cardiovascular risk, but its assessment typically requires a specialized “gated” CT scan that synchronizes with the heartbeat. In contrast, most chest... Read moreMRI
view channel
AI Model Outperforms Doctors at Identifying Patients Most At-Risk of Cardiac Arrest
Hypertrophic cardiomyopathy is one of the most common inherited heart conditions and a leading cause of sudden cardiac death in young individuals and athletes. While many patients live normal lives, some... Read more
New MRI Technique Reveals Hidden Heart Issues
Traditional exercise stress tests conducted within an MRI machine require patients to lie flat, a position that artificially improves heart function by increasing stroke volume due to gravity-driven blood... Read moreNuclear Medicine
view channel
Novel Bacteria-Specific PET Imaging Approach Detects Hard-To-Diagnose Lung Infections
Mycobacteroides abscessus is a rapidly growing mycobacteria that primarily affects immunocompromised patients and those with underlying lung diseases, such as cystic fibrosis or chronic obstructive pulmonary... Read more
New Imaging Approach Could Reduce Need for Biopsies to Monitor Prostate Cancer
Prostate cancer is the second leading cause of cancer-related death among men in the United States. However, the majority of older men diagnosed with prostate cancer have slow-growing, low-risk forms of... Read moreGeneral/Advanced Imaging
view channel
CT Colonography Beats Stool DNA Testing for Colon Cancer Screening
As colorectal cancer remains the second leading cause of cancer-related deaths worldwide, early detection through screening is vital to reduce advanced-stage treatments and associated costs.... Read more
First-Of-Its-Kind Wearable Device Offers Revolutionary Alternative to CT Scans
Currently, patients with conditions such as heart failure, pneumonia, or respiratory distress often require multiple imaging procedures that are intermittent, disruptive, and involve high levels of radiation.... Read more
AI-Based CT Scan Analysis Predicts Early-Stage Kidney Damage Due to Cancer Treatments
Radioligand therapy, a form of targeted nuclear medicine, has recently gained attention for its potential in treating specific types of tumors. However, one of the potential side effects of this therapy... Read moreImaging IT
view channel
New Google Cloud Medical Imaging Suite Makes Imaging Healthcare Data More Accessible
Medical imaging is a critical tool used to diagnose patients, and there are billions of medical images scanned globally each year. Imaging data accounts for about 90% of all healthcare data1 and, until... Read more
Global AI in Medical Diagnostics Market to Be Driven by Demand for Image Recognition in Radiology
The global artificial intelligence (AI) in medical diagnostics market is expanding with early disease detection being one of its key applications and image recognition becoming a compelling consumer proposition... Read moreIndustry News
view channel
GE HealthCare and NVIDIA Collaboration to Reimagine Diagnostic Imaging
GE HealthCare (Chicago, IL, USA) has entered into a collaboration with NVIDIA (Santa Clara, CA, USA), expanding the existing relationship between the two companies to focus on pioneering innovation in... Read more
Patient-Specific 3D-Printed Phantoms Transform CT Imaging
New research has highlighted how anatomically precise, patient-specific 3D-printed phantoms are proving to be scalable, cost-effective, and efficient tools in the development of new CT scan algorithms... Read more
Siemens and Sectra Collaborate on Enhancing Radiology Workflows
Siemens Healthineers (Forchheim, Germany) and Sectra (Linköping, Sweden) have entered into a collaboration aimed at enhancing radiologists' diagnostic capabilities and, in turn, improving patient care... Read more