Objectives
To evaluate the imaging performance of a handheld ultrasound system and the accuracy of an automated lumbar spine computer-aided detection (CAD) algorithm in the spines of human subjects.
Materials and Methods
This study was approved by the Institutional Review Board of the University of Virginia. The authors designed a handheld ultrasound system with enhanced bone image quality and fully automated computer-aided detection (CAD) of lumbar spine anatomy. The imaging performance was evaluated by imaging the lumbar spines of 68 volunteers with BMI between 18.5 and 48 kg/m2. The accuracy, sensitivity, and specificity of the lumbar spine CAD algorithm was assessed by comparing the algorithm’s results to ground-truth segmentations of neuraxial anatomy provided by radiologists.
Results
The lumbar spine CAD algorithm detected the epidural space with a sensitivity of 94.2% (95% CI: 85.1–98.1) and a specificity of 85.5% (95% CI: 81.7–88.6) and measured its depth with an error of approximately ± 0.5 cm compared to measurements obtained manually from the 2D ultrasound images. The spine midline was detected with a sensitivity of 93.9% (95% CI: 85.8–97.7) and specificity of 91.3% (95% CI: 83.6–96.9), and its lateral position within the ultrasound image was measured with an error of approximately ± 0.3 cm. The bone enhancement imaging mode produced images with 5.1 to 10-fold enhanced bone contrast when compared to a comparable handheld ultrasound imaging system.
Conclusions
The results of this study demonstrate the feasibility of CAD for assisting with real-time interpretation of ultrasound images of the lumbar spine at the bedside.