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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...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2014
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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. |
format | Online Article Text |
id | pubmed-4212533 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
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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