3D whole body preclinical micro-CT database of subcutaneous tumors in mice with annotations from 3 annotators

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 cm³ (6.9% ± 4.7), which establishes a human baseline accuracy for delineation of subcutaneous tumors, while showing good inter-annotator agreement.

Fig. 1

Example of a µCT scan for each of the 10 datasets, with an axial slice containing the tumor with and without the tumor mask overlayed in red, and a 3D Maximum Intensity Projection of the entire scan shown below the axial slices.

Fig. 2

Sørensen-Dice coefficient across annotators on each dataset and difference in volume. Each dataset is color-coded, while the annotator pairs are indicated by the hatching: Annotator A vs. B, A vs. C and B vs. C is shown. The middle line is the median, box ends are quartiles, whiskers are 1.5 interquartile range and dots are outliers outside the 1.5 interquartile range. (a) depicts the Sørensen-Dice coefficient, (b) depicts the difference in volume estimation and (b) depicts the root mean squared error between the mean tumor volume estimated from all 3 annotators, and the volume each annotator has estimated. The metrics were calculated over the 3D tumor volumes.

Fig. 3

Overview of the folder structure for the datasets. MXX is the mouse number and Xh or Xd is the hours or days since the first scan of the mouse, respectively.