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Proceedings Paper

Automated detection of colorectal lesions with dual-energy CT colonography
Author(s): Janne J. Näppi; Se Hyung Kim; Hiroyuki Yoshida
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Paper Abstract

Conventional single-energy computed tomography colonography (CTC) tends to miss polyps 6 - 9 mm in size and flat lesions. Dual-energy CTC (DE-CTC) provides more complete information about the chemical composition of tissue than does conventional CTC. We developed an automated computer-aided detection (CAD) scheme for detecting colorectal lesions in which dual-energy features were used to identify different bowel materials and their partial-volume artifacts. Based on these features, the dual-energy CAD (DE-CAD) scheme extracted the region of colon by use of a lumen-tracking method, detected lesions by use of volumetric shape features, and reduced false positives by use of a statistical classifier. For validation, 20 patients were prepared for DE-CTC by use of reduced bowel cleansing and orally administered fecal tagging with iodine and/or barium. The DE-CTC was performed in dual positions by use of a dual-energy CT scanner (SOMATOM Definition, Siemens) at 140 kVp and 80 kVp energy levels. The lesions identified by subsequent same-day colonoscopy were correlated with the DE-CTC data. The detection accuracies of the DE-CAD and conventional CAD schemes were compared by use of leave-one-patient-out evaluation and a bootstrap analysis. There were 25 colonoscopy-confirmed lesions: 22 were 6 - 9 mm and 3 were flat lesions ≥10 mm in size. The DE-CAD scheme detected the large flat lesions and 95% of the 6 - 9 mm lesions with 9.9 false positives per patient. The improvement in detection accuracy by the DE-CAD was statistically significant.

Paper Details

Date Published: 23 February 2012
PDF: 6 pages
Proc. SPIE 8315, Medical Imaging 2012: Computer-Aided Diagnosis, 83150Y (23 February 2012); doi: 10.1117/12.911708
Show Author Affiliations
Janne J. Näppi, Massachusetts General Hospital (United States)
Harvard Medical School (United States)
Se Hyung Kim, Seoul National Univ. Hospital (Korea, Republic of)
Hiroyuki Yoshida, Massachusetts General Hospital (United States)
Harvard Medical School (United States)

Published in SPIE Proceedings Vol. 8315:
Medical Imaging 2012: Computer-Aided Diagnosis
Bram van Ginneken; Carol L. Novak, Editor(s)

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