3D whole body preclinical micro-CT database of subcutaneous tumors in mice with annotations from 3 annotators
Year: 2024
Type: data-paper
Abstract: A pivotal animal model for development of anticancer molecules is mice with subcutaneous tumors, grown by injection of xenografted tumor cells, where micro-Computed Tomography (µCT) of the mice is used to analyze the efficacy of the anticancer molecule. Manual delineation of the tumor region is necessary for the analysis, which is time-consuming and inconsistent, highlighting the need for automatic segmentation (AS) tools. This study introduces a preclinical µCT database, comprising 452 whole-body scans from 223 individual mice with subcutaneous tumors, spanning ten diverse µCT datasets conducted between 2014 and 2020 on a preclinical PET/CT scanner, making it the hitherto largest dataset of its kind. Each tumor is annotated manually by three expert annotators, allowing for robust model development. Inter-annotator agreement was analyzed, and we report an overall annotation agreement of 0.903 ± 0.046 (mean ± std) Fleiss’ Kappa and a mean deviation in volume estimation of 0.015 ± 0.010 cm 3 (6.9% ± 4.7), which establishes a human baseline accuracy for delineation of subcutaneous tumors, while showing good inter-annotator agreement.
Source: Scientific Data
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,290
Award: G2752088381
OpenAlex ID: W4402665615
