ArticleJournal of experimental & clinical cancer research : CR2012
Lung tumour growth kinetics in SPC-c-Raf-1-BB transgenic mice assessed by longitudinal in-vivo micro-CT quantification.
Article in Journal of experimental & clinical cancer research : CR, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed, 9 citations in OpenAlex.
- Deep Learning Based Automated Orthotopic Lung Tumor Segmentation in Whole-Body Mouse CT-Scans.Cancers · 2021Article
- A Novel Method for Quantifying Total Thoracic Tumor Burden in Mice.Neoplasia (New York, N.Y.) · 2018Article
- A respiratory-gated micro-CT comparison of respiratory patterns in free-breathing and mechanically ventilated rats.Physiological reports · 2017Article
- Quantification of Tumor Burden in a Genetically Engineered Mouse Model of Lung Cancer by Micro-CT and Automated Analysis.Translational oncology · 2015Article
- Growth pattern analysis of murine lung neoplasms by advanced semi-automated quantification of micro-CT images.PloS one · 2013Article
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Authors and funding
9 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundSPC-c-Raf-1-BxB transgenic mice develop genetically induced disseminated lung adenocarcinoma allowing examination of carcinogenesis and evaluation of novel treatment strategies. We report on assessment of lung tumour growth kinetics using a semiautomated region growing segmentation algorithm.
methods156 non contrast-enhanced respiratory gated micro-CT of the lungs were obtained in 12 SPC-raf transgenic (n = 9) and normal (n = 3) mice at different time points. Region-growing segmentation of the aerated lung areas was obtained as an inverse surrogate for tumour burden. Time course of segmentation volumes was assessed to demonstrate the potential of the method for follow-up studies.
resultsMicro-CT allowed assessment of tumour growth kinetics and semiautomated region growing enabled quantitative analysis. Significant changes of the segmented lung volumes over time could be shown (p = 0.009). Significant group differences could be detected between transgenic and normal animals for time points 8 to 13 months (p = 0.043), when marked tumour progression occurred.
conclusionThe presented region-growing segmentation algorithm allows in-vivo quantification of multifocal lung adenocarcinoma in SPC-raf transgenic mice. This enables the assessment of tumour load and progress for the study of carcinogenesis and the evaluation of novel treatment strategies.
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