Pulmonary embolism: computer-aided detection at multidetector row spiral computed tomography.
BACKGROUND
We aimed to evaluate the feasibility and performance of a computer-aided detection (CAD) tool for automated detection of segmental and subsegmental pulmonary emboli.


METHODS
A CAD tool (ImageChecker CT, R2 Technology, Inc) for automated detection of pulmonary emboli was evaluated on multidetector-row CT studies of varying diagnostic quality in 23 patients (13 female, mean age 52 y) with pulmonary embolism (PE) and of 13 patients (all female, mean age 49 y) without PE. A collimation of 16 x 1 mm and a reconstructed section width of 1.25 mm had been used in each patient. The performance of the CAD tool for the detection of emboli in the segmental and subsegmental pulmonary arterial tree was assessed. Consensus reading of the same studies by 2 radiologists, with a third for adjudication, for the identification of segmental and subsegmental pulmonary emboli was used as the standard of reference.


RESULTS
Consensus reading revealed 130 segmental pulmonary emboli and 107 subsegmental pulmonary emboli in the 23 patients with PE. All 23 patients with PE were correctly identified as having PE by the CAD system. In a vessel-by-vessel analysis, the sensitivity of the CAD algorithm was 92% (119/130) for the detection of segmental pulmonary emboli and 90% (92/107) for subsegmental pulmonary emboli. The overall specificity, positive predictive value (95% confidence interval) and negative predictive value (95% confidence interval) of the algorithm were 89.9%, 63.2% (57.9%-68.2%) and 97.7% (96.7%-98.4%), respectively. The average false positive rate of the CAD algorithm was 4.8 (range 1 to 9) false positive detection marks per case.


CONCLUSIONS
CAD of segmental and subsegmental pulmonary emboli based on 1-mm multidetector-row CT studies is feasible. Application of CAD tools may improve the diagnostic accuracy and decrease the interpretation time of computed tomographic angiography for the detection of pulmonary emboli in the peripheral arterial tree and further enhance the acceptance of this test as the first line diagnostic modality for suspected PE.
Department of Radiology, Medical University of South Carolina, Charleston, SC 29425, USA. schoepf@musc.edu
U Joseph
UJ
Schoepf
Alex C
AC
Schneider
Marco
M
Das
Susan A
SA
Wood
Jugesh I
JI
Cheema
Philip
P
Costello
D000465:Algorithms; D003936:Diagnosis, Computer-Assisted; D005240:Feasibility Studies; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D011237:Predictive Value of Tests; D011655:Pulmonary Embolism / Q000000981:diagnostic imaging*; D012680:Sensitivity and Specificity; D036542:Tomography, Spiral Computed