PETWB-REP: A Multi-Cancer Whole-Body FDG PET/CT Dataset with Corresponding Radiology Reports

Abstract

Publicly available, large-scale medical imaging datasets are crucial for developing and validating artificial intelligence (AI) models and conducting retrospective clinical research. However, multimodal datasets that integrate functional and anatomical imaging with high-quality radiology reports across diverse malignancies remain scarce. Here, we present PETWB-REP, a curated dataset comprising whole-body ¹⁸F-Fluorodeoxyglucose (FDG) Positron Emission Tomography/Computed Tomography (PET/CT) scans and corresponding radiology reports from 490 patients. The cohort encompasses a broad spectrum of malignancies, including but not limited to lung, liver, breast, prostate, and ovarian cancers. Distinct from existing resources, PETWB-REP is organized following the Brain Imaging Data Structure (BIDS) standard, providing both raw data (with 3D de-facing for privacy) and processed derivatives (SUV-converted and registered). Each case includes bilingual (Chinese and English) de-identified textual reports and structured clinical metadata. This dataset is uniquely positioned to support multi-center validation and cross-disciplinary research in medical imaging, radiomics, automated report generation, and multimodal representation learning.

Ähnliche Arbeiten