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

BACKGROUND: To evaluate a semi-automatic landmark-based lesion tracking software enabling navigation between RECIST lesions in baseline and follow-up CT-scans. METHODS: The software automatically detects 44 stable anatomical landmarks in each thoraco/abdominal/pelvic CT-scan, sets up a patient speci...

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Autores principales: Dankerl, Peter, Cavallaro, Alexander, Dietzel, Matthias, Tsymbal, Alexey, Kramer, Martin, Seifert, Sascha, Uder, Michael, Hammon, Matthias
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4212533/
https://www.ncbi.nlm.nih.gov/pubmed/25609496
http://dx.doi.org/10.1186/1470-7330-14-6
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author Dankerl, Peter
Cavallaro, Alexander
Dietzel, Matthias
Tsymbal, Alexey
Kramer, Martin
Seifert, Sascha
Uder, Michael
Hammon, Matthias
author_facet Dankerl, Peter
Cavallaro, Alexander
Dietzel, Matthias
Tsymbal, Alexey
Kramer, Martin
Seifert, Sascha
Uder, Michael
Hammon, Matthias
author_sort Dankerl, Peter
collection PubMed
description BACKGROUND: To evaluate a semi-automatic landmark-based lesion tracking software enabling navigation between RECIST lesions in baseline and follow-up CT-scans. METHODS: 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. RESULTS: 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. CONCLUSION: The investigated software accurately and reliably navigates between lesions in consecutive CT-scans in real-time, potentially accelerating and facilitating cancer staging.
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spelling pubmed-42125332014-10-30 Clinical evaluation of semi-automatic landmark-based lesion tracking software for CT-scans Dankerl, Peter Cavallaro, Alexander Dietzel, Matthias Tsymbal, Alexey Kramer, Martin Seifert, Sascha Uder, Michael Hammon, Matthias Cancer Imaging Research Article BACKGROUND: To evaluate a semi-automatic landmark-based lesion tracking software enabling navigation between RECIST lesions in baseline and follow-up CT-scans. METHODS: 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. RESULTS: 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. CONCLUSION: The investigated software accurately and reliably navigates between lesions in consecutive CT-scans in real-time, potentially accelerating and facilitating cancer staging. BioMed Central 2014-04-22 /pmc/articles/PMC4212533/ /pubmed/25609496 http://dx.doi.org/10.1186/1470-7330-14-6 Text en Copyright © 2014 Dankerl et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Dankerl, Peter
Cavallaro, Alexander
Dietzel, Matthias
Tsymbal, Alexey
Kramer, Martin
Seifert, Sascha
Uder, Michael
Hammon, Matthias
Clinical evaluation of semi-automatic landmark-based lesion tracking software for CT-scans
title Clinical evaluation of semi-automatic landmark-based lesion tracking software for CT-scans
title_full Clinical evaluation of semi-automatic landmark-based lesion tracking software for CT-scans
title_fullStr Clinical evaluation of semi-automatic landmark-based lesion tracking software for CT-scans
title_full_unstemmed Clinical evaluation of semi-automatic landmark-based lesion tracking software for CT-scans
title_short Clinical evaluation of semi-automatic landmark-based lesion tracking software for CT-scans
title_sort clinical evaluation of semi-automatic landmark-based lesion tracking software for ct-scans
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4212533/
https://www.ncbi.nlm.nih.gov/pubmed/25609496
http://dx.doi.org/10.1186/1470-7330-14-6
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