OBJECTIVE: To assess whether the performance of a computer-assisted detection (CAD) algorithm for acute pulmonary embolism (PE) differs in pulmonary CT angiographies acquired at various institutions. METHODS: In this retrospective study, we included 40 consecutive scans with and 40 without PE from 3 institutions (n = 240) using 64-slice scanners made by different manufacturers (General Electric; Philips; Siemens). CAD markers were classified as true or false positive (FP) using independent evaluation by two readers and consultation of a third chest radiologist in discordant cases. Image quality parameters were subjectively scored using 4/5-point scales. Image noise and vascular enhancement were measured. Statistical analysis was done to correlate image quality of the three institutions with CAD stand-alone performance. RESULTS: Patient groups were comparable with respect to age (p = 0.22), accompanying lung disease (p = 0.12) and inpatient/outpatient ratio (p = 0.67). The sensitivity was 100% (34/34), 97% (37/38) and 92% (33/36), and the specificity was 18% (8/44), 15% (6/41) and 13% (5/39). Neither significantly differed between the institutions (p = 0.21 and p = 0.820, respectively). The mean number of FP findings (4.5, 6.2 and 3.7) significantly varied (p = 0.02 and p = 0.03), but median numbers (2, 3 and 3) were comparable. Image quality parameters were significantly associated with the number of FP findings (p<0.05) but not with sensitivity. After correcting for noise and vascular enhancement, the number of FPs did not significantly differ between the three institutions (p = 0.43). CONCLUSIONS: CAD stand-alone performance is independent of scanner type but strongly related to image quality and thus scanning protocols.
OBJECTIVE: To assess whether the performance of a computer-assisted detection (CAD) algorithm for acute pulmonary embolism (PE) differs in pulmonary CT angiographies acquired at various institutions. METHODS: In this retrospective study, we included 40 consecutive scans with and 40 without PE from 3 institutions (n = 240) using 64-slice scanners made by different manufacturers (General Electric; Philips; Siemens). CAD markers were classified as true or false positive (FP) using independent evaluation by two readers and consultation of a third chest radiologist in discordant cases. Image quality parameters were subjectively scored using 4/5-point scales. Image noise and vascular enhancement were measured. Statistical analysis was done to correlate image quality of the three institutions with CAD stand-alone performance. RESULTS:Patient groups were comparable with respect to age (p = 0.22), accompanying lung disease (p = 0.12) and inpatient/outpatient ratio (p = 0.67). The sensitivity was 100% (34/34), 97% (37/38) and 92% (33/36), and the specificity was 18% (8/44), 15% (6/41) and 13% (5/39). Neither significantly differed between the institutions (p = 0.21 and p = 0.820, respectively). The mean number of FP findings (4.5, 6.2 and 3.7) significantly varied (p = 0.02 and p = 0.03), but median numbers (2, 3 and 3) were comparable. Image quality parameters were significantly associated with the number of FP findings (p<0.05) but not with sensitivity. After correcting for noise and vascular enhancement, the number of FPs did not significantly differ between the three institutions (p = 0.43). CONCLUSIONS: CAD stand-alone performance is independent of scanner type but strongly related to image quality and thus scanning protocols.
Authors: Martine Remy-Jardin; Massimo Pistolesi; Lawrence R Goodman; Warren B Gefter; Alexander Gottschalk; John R Mayo; H Dirk Sostman Journal: Radiology Date: 2007-09-11 Impact factor: 11.105
Authors: U Joseph Schoepf; Alex C Schneider; Marco Das; Susan A Wood; Jugesh I Cheema; Philip Costello Journal: J Thorac Imaging Date: 2007-11 Impact factor: 3.000