Clinical evaluation of semi-automatic landmark-based lesion tracking software for CT-scans

Dankerl P, Dietzel M, Tsymbal A, Kramer M, Seifert S, Uder M, Hammon M, Cavallaro AJ (2014)

Publication Type: Journal article

Publication year: 2014

Journal

Cancer Imaging e-med

Publisher: e-med

Book Volume: 14

Pages Range: 6

Journal Issue: 1

DOI: 10.1186/1470-7330-14-6

Abstract

To evaluate a semi-automatic landmark-based lesion tracking software enabling navigation between RECIST lesions in baseline and follow-up CT-scans.The software automatically detects 44 stable anatomical landmarks in each thoraco/abdominal/pelvic CT-scan, sets up a patient specific coordinate-system and cross-links the coordinate-systems of consecutive CT-scans. Accuracy of the software was evaluated on 96 RECIST lesions (target- and non-target lesions) in baseline and follow-up CT-scans of 32 oncologic patients (64 CT-scans). Patients had to present at least one thoracic, one abdominal and one pelvic RECIST lesion. Three radiologists determined the deviation between lesions' centre and the software's navigation result in consensus.The initial mean runtime of the system to synchronize baseline and follow-up examinations was 19.4 ± 1.2 seconds, with subsequent navigation to corresponding RECIST lesions facilitating in real-time. Mean vector length of the deviations between lesions' centre and the semi-automatic navigation result was 10.2 ± 5.1 mm without a substantial systematic error in any direction. Mean deviation in the cranio-caudal dimension was 5.4 ± 4.0 mm, in the lateral dimension 5.2 ± 3.9 mm and in the ventro-dorsal dimension 5.3 ± 4.0 mm.The investigated software accurately and reliably navigates between lesions in consecutive CT-scans in real-time, potentially accelerating and facilitating cancer staging.

Authors with CRIS profile

Michael Uder Lehrstuhl für Diagnostische Radiologie Matthias Hammon Institute of Radiology Alexander Josef Cavallaro Institute of Radiology

Involved external institutions

Siemens AG DE Germany (DE)

How to cite

APA:

Dankerl, P., Dietzel, M., Tsymbal, A., Kramer, M., Seifert, S., Uder, M.,... Cavallaro, A.J. (2014). Clinical evaluation of semi-automatic landmark-based lesion tracking software for CT-scans. Cancer Imaging, 14(1), 6. https://doi.org/10.1186/1470-7330-14-6

MLA:

Dankerl, Peter, et al. "Clinical evaluation of semi-automatic landmark-based lesion tracking software for CT-scans." Cancer Imaging 14.1 (2014): 6.

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