Department of Radiological Sciences, University of California-Irvine, Orange, Calif, USA.
Radiology. 2013 Jul;268(1):69-78. doi: 10.1148/radiol.13121351. Epub 2013 Feb 28.
To design and validate a computer system for automated detection and quantitative characterization of sclerotic metastases of the thoracolumbar spine on computed tomography (CT) images.
This retrospective study was approved by the institutional review board and was HIPAA compliant; informed consent was waived. The data set consisted of CT examinations in 49 patients (14 female, 35 male patients; mean age, 57.0 years; range, 12-77 years), demonstrating a total of 532 sclerotic lesions of the spine of greater than 0.3 cm(3) in volume, and in 10 control case patients (four women, six men; mean age, 55.2 years; range, 19-70 years) without spinal lesions. CT examinations were divided into training and test sets, and images were analyzed according to prototypical fully-automated computer-aided detection (CAD) software. Free-response receiver operating characteristic analysis was performed.
Lesion detection sensitivity on images in the training set was 90%, relative to reference-standard marked lesions (95% confidence interval [CI]: 83%, 97%), at a false-positive rate (FPR) of 10.8 per patient (95% CI: 6.6, 15.0). For images in the testing set, sensitivity was 79% (95% CI: 74%, 84%), with an FPR of 10.9 per patient (95% CI: 8.5, 13.3). False-negative findings were most commonly (37 [40%] of 93) a result of endplate proximity, with 32 (34% of 93) caused by low CT attenuation. Marginal sclerosis caused by degenerative change (174 [28.1%] of 620 actual detections) was the most common cause of false-positive detections, followed by partial volume averaging with vertebral endplates (173 [27.9%] of 620) and pedicle cortex parallel to the axial imaging plane (121 [19.5%] 620).
This CAD system successfully identified and segmented sclerotic lesions in the thoracolumbar spine.
设计并验证一种用于在计算机断层扫描 (CT) 图像上自动检测和定量表征胸腰椎硬化性转移的计算机系统。
本回顾性研究获得了机构审查委员会的批准，并符合 HIPAA 规定；豁免了知情同意。数据集包括 49 例患者（14 例女性，35 例男性；平均年龄 57.0 岁；范围 12-77 岁）的 CT 检查，共显示 532 个体积大于 0.3cm³的脊柱硬化性病变，以及 10 例对照患者（4 例女性，6 例男性；平均年龄 55.2 岁；范围 19-70 岁）无脊柱病变。CT 检查分为训练集和测试集，根据典型的全自动计算机辅助检测 (CAD) 软件分析图像。进行了自由响应接收器操作特性分析。
在训练集图像上，与参考标准标记病变相比，病变检测灵敏度为 90%（95%置信区间 [CI]：83%，97%），假阳性率（FPR）为每例 10.8 个（95% CI：6.6，15.0）。对于测试集图像，灵敏度为 79%（95% CI：74%，84%），FPR 为每例 10.9 个（95% CI：8.5，13.3）。假阴性结果最常见（93 个中有 37 个[40%]）是由于终板接近所致，32 个（93 个中有 32 个[34%]）是由于 CT 衰减低所致。由退行性变引起的边缘硬化（620 个实际检测中有 174 个[28.1%]）是假阳性检测最常见的原因，其次是与椎骨终板的部分容积平均（620 个中有 173 个[27.9%]）和与轴向成像平面平行的椎弓根皮质（620 个中有 121 个[19.5%]）。
该 CAD 系统成功地识别和分割了胸腰椎的硬化性病变。
