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Proceedings Paper

A comparison of 2D and 3D evaluation methods for pulmonary embolism detection in CT images
Author(s): Atilla P. Kiraly; Carol L. Novak; David P. Naidich; Ioannis Vlahos; Jane P. Ko; Geraldine T. Brusca-Augello
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Paper Abstract

Pulmonary embolism (PE) is a life-threatening disease, requiring rapid diagnosis and treatment. Contrast enhanced computed tomographic (CT) images of the lungs allow physicians to confirm or rule out PE, but the large number of images per study and the complexity of lung anatomy may cause some emboli to be overlooked. We evaluated a novel three-dimensional (3D) visualization technique for detecting PE, and compared it with traditional 2D axial interpretation. Three readers independently marked 10 cases using the 3D method, and a separate interpretation was performed at a later date using only source axial images. An experienced thoracic radiologist adjudicated all marks, classifying clots according to location and confidence. There were a total of 8 positive examinations with 69 validated emboli. 44 (64%) of the clots were segmental while 12 (17%) proved subsegmental. Using the traditional 2D method for examination, readers detected a mean of 45 PE for 66% sensitivity. Using the 3D method, readers detected a mean of 35 PE (50% sensitivity). Combining both methods, readers detected a mean of 51 PE (74% sensitivity), significantly higher than either single method (p<0.001). Considered by arterial level, significant improvement was observed for detection of segmental and subsegmental clots (p<0.001) when comparing combined reading with either single method. The mean number of false positives per patient was 0.23 for both 2D and 3D readings and 0.4 for combined reading. 3D visualization of pulmonary arteries allowed readers to detect a significant number of additional emboli not detected during 2D axial interpretations and thus may lead to a more accurate diagnosis of PE.

Paper Details

Date Published: 17 March 2006
PDF: 9 pages
Proc. SPIE 6146, Medical Imaging 2006: Image Perception, Observer Performance, and Technology Assessment, 61460H (17 March 2006); doi: 10.1117/12.652430
Show Author Affiliations
Atilla P. Kiraly, Siemens Corporate Research (United States)
Carol L. Novak, Siemens Corporate Research (United States)
David P. Naidich, New York Univ. Medical Ctr. (United States)
Ioannis Vlahos, New York Univ. Medical Ctr. (United States)
Jane P. Ko, New York Univ. Medical Ctr. (United States)
Geraldine T. Brusca-Augello, New York Univ. Medical Ctr. (United States)

Published in SPIE Proceedings Vol. 6146:
Medical Imaging 2006: Image Perception, Observer Performance, and Technology Assessment
Yulei Jiang; Miguel P. Eckstein, Editor(s)

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