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Proceedings Paper

Virtual hybrid bronchoscopy using PET/CT data sets
Author(s): Karl-Hans Englmeier; Marcus D. Seemann
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Paper Abstract

The aim of this study was to demonstrate the possibilities, advantages and limitations of virtual bronchoscopy using data sets from positron emission tomography (PET) and computed tomography (CT). Eight consecutive patients with lung cancer underwent PET/CT. PET was performed with F-18-labelled 2-[fluorine-18]-fluoro-2-deoxy-D: -glucose ((18)F-FDG). The tracheobronchial system was segmented with a volume-growing algorithm, using the CT data sets, and visualized with a shaded-surface rendering method. The primary tumours and the lymph node metastases were segmented for virtual CT-bronchoscopy using the CT data set and for virtual PET/CT-bronchoscopy using the PET/CT data set. Virtual CT-bronchoscopy using the low-dose or diagnostic CT facilitates the detection of anatomical/morphological structure changes of the tracheobronchial system. Virtual PET/CT-bronchoscopy was superior to virtual CT-bronchoscopy in the detection of lymph node metastases (P=0.001), because it uses the CT information and the molecular/metabolic information from PET. Virtual PET/CT-bronchoscopy with a transparent colour-coded shaded-surface rendering model is expected to improve the diagnostic accuracy of identification and characterization of malignancies, assessment of tumour staging, differentiation of viable tumour tissue from atelectases and scars, verification of infections, evaluation of therapeutic response and detection of an early stage of recurrence that is not detectable or is misjudged in comparison with virtual CT-bronchoscopy.

Paper Details

Date Published: 29 March 2007
PDF: 8 pages
Proc. SPIE 6511, Medical Imaging 2007: Physiology, Function, and Structure from Medical Images, 65111O (29 March 2007); doi: 10.1117/12.709130
Show Author Affiliations
Karl-Hans Englmeier, Institute of Medical Informatics (Germany)
Marcus D. Seemann, Technical Univ. of Munich (Germany)

Published in SPIE Proceedings Vol. 6511:
Medical Imaging 2007: Physiology, Function, and Structure from Medical Images
Armando Manduca; Xiaoping P. Hu, Editor(s)

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