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Proceedings Paper

Diagnostic performance of different measurement methods for lung nodule enhancement at quantitative contrast-enhanced computed tomography
Author(s): Dag Wormanns; Ernst Klotz; Uwe Dregger; Florian Beyer; Walter Heindel
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Paper Abstract

Lack of angiogenesis virtually excludes malignancy of a pulmonary nodule; assessment with quantitative contrast-enhanced CT (QECT) requires a reliable enhancement measurement technique. Diagnostic performance of different measurement methods in the distinction between malignant and benign nodules was evaluated. QECT (unenhanced scan and 4 post-contrast scans) was performed in 48 pulmonary nodules (12 malignant, 12 benign, 24 indeterminate). Nodule enhancement was the difference between the highest nodule density at any post-contrast scan and the unenhanced scan. Enhancement was determined with: A) the standard 2D method; B) a 3D method consisting of segmentation, removal of peripheral structures and density averaging. Enhancement curves were evaluated for their plausibility using a predefined set of criteria. Sensitivity and specificity were 100% and 33% for the 2D method resp. 92% and 55% for the 3D method using a threshold of 20 HU. One malignant nodule did not show significant enhancement with method B due to adjacent atelectasis which disappeared within the few minutes of the QECT examination. Better discrimination between benign and malignant lesions was achieved with a slightly higher threshold than proposed in the literature. Application of plausibility criteria to the enhancement curves rendered less plausibility faults with the 3D method. A new 3D method for analysis of QECT scans yielded less artefacts and better specificity in the discrimination between benign and malignant pulmonary nodules when using an appropriate enhancement threshold. Nevertheless, QECT results must be interpreted with care.

Paper Details

Date Published: 4 May 2004
PDF: 8 pages
Proc. SPIE 5372, Medical Imaging 2004: Image Perception, Observer Performance, and Technology Assessment, (4 May 2004); doi: 10.1117/12.535209
Show Author Affiliations
Dag Wormanns, Westfaelische Wilhelms-Univ. Hospital Muenster (Germany)
Ernst Klotz, Siemens Medical Solutions (Germany)
Uwe Dregger, Westfaelische Wilhelms-Univ. Hospital Muenster (Germany)
Florian Beyer, Westfaelische Wilhelms-Univ. Hospital Muenster (Germany)
Walter Heindel, Westfaelische Wilhelms-Univ. Hospital Muenster (Germany)

Published in SPIE Proceedings Vol. 5372:
Medical Imaging 2004: Image Perception, Observer Performance, and Technology Assessment
Dev P. Chakraborty; Miguel P. Eckstein, Editor(s)

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