Tiouririne Mohamed, Dixon Adam J, Mauldin F William, Scalzo David, Krishnaraj Arun
From the *Department of Anesthesiology, University of Virginia Health System; †Department of Biomedical Engineering, University of Virginia; ‡Rivanna Medical; and §Department of Radiology, University of Virginia Health System, Charlottesville, VA.
Invest Radiol. 2017 Aug;52(8):447-455. doi: 10.1097/RLI.0000000000000361.
The aim of this study was 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.
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 CAD of lumbar spine anatomy. The imaging performance was evaluated by imaging the lumbar spines of 68 volunteers with body mass index between 18.5 and 48 kg/m. The accuracy, sensitivity, and specificity of the lumbar spine CAD algorithm were assessed by comparing the algorithm's results to ground-truth segmentations of neuraxial anatomy provided by radiologists.
The lumbar spine CAD algorithm detected the epidural space with a sensitivity of 94.2% (95% confidence interval [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 with measurements obtained manually from the 2-dimensional 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 with a comparable handheld ultrasound imaging system.
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.
本研究旨在评估手持式超声系统的成像性能以及自动腰椎计算机辅助检测(CAD)算法在人体脊柱中的准确性。
本研究经弗吉尼亚大学机构审查委员会批准。作者设计了一种具有增强骨图像质量和腰椎解剖结构全自动CAD功能的手持式超声系统。通过对68名体重指数在18.5至48kg/m之间的志愿者的腰椎进行成像来评估成像性能。通过将该算法的结果与放射科医生提供的神经轴解剖结构的真实分割结果进行比较,评估腰椎CAD算法的准确性、敏感性和特异性。
腰椎CAD算法检测硬膜外腔的敏感性为94.2%(95%置信区间[CI],85.1%-98.1%),特异性为85.5%(95%CI,81.7%-88.6%),与从二维超声图像手动获得的测量结果相比,测量其深度的误差约为±0.5cm。检测脊柱中线的敏感性为93.9%(95%CI,85.8%-97.7%),特异性为91.3%(95%CI,83.6%-96.9%),测量其在超声图像中的横向位置的误差约为±0.3cm。与可比的手持式超声成像系统相比,骨增强成像模式产生的图像骨对比度提高了5.1至10倍。
本研究结果证明了CAD在床边辅助实时解读腰椎超声图像的可行性。