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Congress: ECR25
Poster Number: C-12773
Type: Poster: EPOS Radiologist (scientific)
Authorblock: K. Bartnik1, T. Bartczak2, M. Krzyziński2, K. Korzeniowski1, K. J. Lamparski1, T. Wróblewski2, K. Mech2, M. M. Januszewicz1, P. Biecek2; 1Warszawa/PL, 2Warsaw/PL
Disclosures:
Krzysztof Bartnik: Grant Recipient: Integra WUM-PW (No. 1W12/ INTEGRA.1.6/N/23)
Tomasz Bartczak: Nothing to disclose
Mateusz Krzyziński: Nothing to disclose
Krzysztof Korzeniowski: Nothing to disclose
Krzysztof Jacek Lamparski: Nothing to disclose
Tadeusz Wróblewski: Nothing to disclose
Katarzyna Mech: Nothing to disclose
Magdalena Maria Januszewicz: Nothing to disclose
Przemysław Biecek: Nothing to disclose
Keywords: Artificial Intelligence, Liver, Oncology, CT, CT-Quantitative, Chemoembolisation, Outcomes analysis, Cancer, Cirrhosis
Results

The WAT-TACE dataset comprises four key components: clinical data, imaging, segmentations, and radiomic features. The dataset includes clinical variables and outcome measures for 233 patients (median age: 66 years; 185 male, 48 female), with a median overall survival of 27 months and a median progression-free survival of 18 months. Imaging data consists of contrast-enhanced CT scans across multiple phases, including precontrast, late arterial, portal venous, and delayed phases. Segmentation data include 377 HCC lesion masks and 104 organ volumes of interest (VOIs) per patient. Additionally, radiomic feature extraction yielded more than 3000 features across all VOIs, presented in tabular format. The dataset is publicly available for research and model development.