AI Article Synopsis
- Scientists are studying how to better find a type of bone injury called bone marrow edema (BME) using a new imaging method called three-material decomposition (TMD) instead of regular CT scans.
- They tested this method on 81 bone parts with BME and 80 without it, having two doctors look at the images to check for signs of BME.
- The results showed the TMD method is really good at finding BME, making it useful for doctors in emergency situations to quickly detect these injuries.
Article Abstract
Background: Detecting bone marrow edema (BME) as a sign of acute fractures is challenging on conventional computed tomography (CT). This study evaluated the diagnostic performance of a three-material decomposition (TMD) approach for detecting traumatic BME of the extremities on spectral computed tomography (SCT).
Methods: This retrospective diagnostic study included 81 bone compartments with and 80 without BME. A TMD application to visualize BME was developed in collaboration with Philips Healthcare. The following bone compartments were included: distal radius, proximal femur, proximal tibia, distal tibia and fibula, and long bone diaphysis. Two blinded radiologists reviewed each case independently in random order for the presence or absence of BME.
Results: The interrater reliability was 0.84 ( < 0.001). The different bone compartments showed sensitivities of 86.7% to 93.8%, specificities of 84.2% to 94.1%, positive predictive values of 82.4% to 94.7%, negative predictive values of 87.5% to 93.3%, and area under the curve (AUC) values of 85.7% to 93.1%. The distal radius showed the highest sensitivity and the proximal femur showed the lowest sensitivity, while the proximal femur presented the highest specificity and the distal tibia presented the lowest specificity.
Conclusions: Our TMD approach provides high diagnostic performance for detecting BME of the extremities. Therefore, this approach could be used routinely in the emergency setting.
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Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10486895 | PMC |
| http://dx.doi.org/10.3390/diagnostics13172745 | DOI Listing |
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