Automated detection of ureteral wall thickening on multi-detector row CT urography
Automated detection of ureteral wall thickening on multi-detector row CT urography
复制标题
多排CT尿路造影自动检测输尿管壁增厚
DOI：
10.1117/12.771325
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发表时间：
2008
期刊：
影响因子：
--
通讯作者：
H. Chan
中科院分区：
文献类型：
--
作者：
Lubomir M. Hadjiiski;B. Sahiner;E. Caoili;R. Cohan;Chuan Zhou;H. Chan
我们正在开发一种计算机辅助检测（CAD）系统，用于在多排CT尿路造影上自动检测输尿管壁增厚，这可能有助于放射科医生检测输尿管癌。在我们的CAD系统的第一阶段中，给定起点，基于造影剂填充的管腔的CT值来跟踪输尿管。在第二阶段中，输尿管壁被分割并且基于极变换、输尿管壁与背景的分离以及测量壁厚度来估计输尿管壁厚度。在这项初步研究中，使用了20例患者的22条输尿管异常的有限数据集。14例患者共有16条输尿管伴恶性输尿管壁增厚。其中2例患者在左、右输尿管均出现恶性管壁增厚。其余6例患者6条输尿管均为良性输尿管壁增厚。所有恶性壁增厚活检证实。良性增厚通过活检或2年随访确定。此外，还使用3个正常输尿管来确定CAD系统的假阳性（FP）检出率。追踪程序成功追踪了25条输尿管（22条异常和3条正常），并检测到90%（20/22）的输尿管壁增厚，每条输尿管2.3（7/3）个FP。恶性输尿管壁增厚检出率为93%（15/16），良性输尿管壁增厚检出率为83%（5/6）。漏诊的输尿管壁增厚是在充满造影剂的输尿管部分周围不对称发展的，我们目前的CAD系统中的检测标准无法可靠地识别它们。初步结果表明，我们的检测系统可以跟踪输尿管，并可以检测输尿管壁增厚。
We are developing a computer-aided detection (CAD) system for automated detection of ureteral wall thickening on multi-detector row CT urography, which potentially can assist radiologists in detecting ureter cancer. In the first stage of our CAD system, given a starting point, the ureter is tracked based on the CT values of the contrast-filled lumen. In the second stage, the ureter wall is segmented and the ureter wall thickness is estimated based on polar transformation, separation of the ureter wall from the background and measuring the wall thickness. In this pilot study, a limited data set of 20 patients with 22 abnormal ureters was used. Fourteen patients had a total of 16 ureters with malignant ureteral wall thickening. Two of the patients had malignant wall thickening in both the left and right ureters. The other six patients had 6 ureters with benign ureteral wall thickening. All malignant wall thickenings were biopsy-proven. The benign thickenings were determined by biopsy or by 2-year follow-up. In addition 3 normal ureters were used to determine the false positive (FP) detection rate of the CAD system. The tracking program successfully tracked the 25 ureters (22 abnormal and 3 normal) and detected 90% (20/22) of the ureters having wall thickening with 2.3 (7/3) FPs per ureter. 93% (15/16) of the ureters with malignant wall thickening and 83% (5/6) of the ureters with benign wall thickening were detected. The missed ureteral wall thickenings were developed asymmetrically around the part of the ureter filled with contrast and the detection criteria in our current CAD system was not able to identify them reliably. The preliminary results show that our detection system can track the ureter and can detect ureteral wall thickening.