Back to the list
Congress: ECR25
Poster Number: C-13515
Type: Poster: EPOS Radiologist (scientific)
Authorblock: M. Correia De Verdier1, R. Saluja2, L. Gagnon3, U. Baid4, A. Abayazeed5, R. Huang6, S. Bakas4, E. Calabrese7, J. D. Rudie8; 1Uppsala/SE, 2New York, NY/US, 3Quebec City, QC/CA, 4Indianapolis, IN/US, 5Stanford, CA/US, 6Boston, MA/US, 7Durham, NC/US, 8La Jolla, CA/US
Disclosures:
Maria Correia De Verdier: Nothing to disclose
Rachit Saluja: Nothing to disclose
Louis Gagnon: Nothing to disclose
Ujjwal Baid: Nothing to disclose
Aly Abayazeed: Nothing to disclose
Raymond Huang: Nothing to disclose
Spyridon Bakas: Nothing to disclose
Evan Calabrese: Nothing to disclose
Jeffrey D. Rudie: Nothing to disclose
Keywords: Artificial Intelligence, Neuroradiology brain, MR, Neural networks, Segmentation, Cancer
Results

The dataset comprises 1936 cases, and data was contributed from six different academic medical centers (Figure 5, Table 1).

Fig 5: Map showing institutions from the USA contributing data to the 2024 BraTS post-treatment glioma challenge and their relative sample size.
Table 1: Number of cases per contributing site, imaging data, and clinical data. *1 mpMRI in the validation set was performed on a 1.16 T Hitachi scanner, and 1 mpMRI in the test set was performed on a 7 T Siemens scanner. Information on the manufacturer was not available in 13 mpMRI (4 in the training set, 4 in the validation set, and 5 in the test set). Information on field strength was not available in 37 mpMRI in the test set **Information on age was not available in 27 mpMRI (1 in the training set and 26 in the test set).

This dataset has been used by BraTS-PTG challenge participants to develop, containerize, and evaluate their automated segmentation models, predicting the six sub-regions on validation data from April 2024 through July 2024. Thirty-seven teams participated in the validation phase and evaluated their models on the validation data. Six teams participated in the test phase in August 2024, and their models were tested on the hidden testing data. The results and the winner of the challenge were announced at the Medical Image Computing and Computer Assisted Intervention (MICCAI) Conference in October 2024 (Table 2).

Table 2: Lesion-wise Dice similarity coefficient and 95% Hausdorff distance presented as mean ± SD (median) for each team and sub-region evaluated. Team rankings within the challenge are also included. Sub-region abbreviations: ET – enhancing tissue, NETC – non-enhancing tumor core, SNFH – surrounding non-enhancing FLAIR hyperintensity, RC – resection cavity, TC – tumor core (ET plus NETC), WT – whole tumor (ET plus NETC plus SNFH).

 

GALLERY