Data for NSCLC Radiogenomics Collection

Medical image biomarkers of cancer promise improvements in patient care through advances in precision medicine. Compared to genomic biomarkers, image biomarkers provide the advantages of being a non-invasive procedure, and characterizing a heterogeneous tumor in its entirety, as opposed to limited tissue available for biopsy. We developed a unique radiogenomic dataset from a Non-Small Cell Lung Cancer (NSCLC) cohort of 211 subjects. The dataset comprises Computed Tomography (CT), Positron Emission Tomography (PET)/CT images, semantic annotations of the tumors as observed on the medical images using a controlled vocabulary, segmentation maps of tumors in the CT scans, and quantitative values obtained from the PET/CT scans. Imaging data are also paired with gene mutation, RNA sequencing data from samples of surgically excised tumor tissue, and clinical data, including survival outcomes. This dataset was created to facilitate the discovery of the underlying relationship between genomic and medical image features, as well as the development and evaluation of prognostic medical image biomarkers.

癌症医学影像生物标志物有望通过精准医学的进步改善患者诊疗效果。相较于基因组生物标志物，影像生物标志物具备无创检测的优势，且能够完整表征异质性肿瘤，而活检可获取的组织样本往往较为有限。本研究从包含211名受试者的非小细胞肺癌（Non-Small Cell Lung Cancer, NSCLC）队列中构建了独特的放射基因组数据集。该数据集涵盖计算机断层扫描（Computed Tomography, CT）、正电子发射断层扫描/计算机断层扫描（Positron Emission Tomography, PET/CT）影像，采用受控词汇表对医学影像中观测到的肿瘤进行语义标注，包含CT扫描中肿瘤的分割掩码图，以及从PET/CT扫描中获取的定量数值。影像数据还与手术切除肿瘤组织样本的基因突变数据、RNA测序数据，以及包含生存结局在内的临床数据进行了配对整合。本数据集的构建旨在助力探索基因组特征与医学影像特征之间的潜在关联，同时推动预后性医学影像生物标志物的开发与性能评估。

搜集汇总

背景与挑战

背景概述

该数据集是一个非小细胞肺癌（NSCLC）放射基因组学集合，包含211名受试者的多模态数据，如CT、PET/CT图像、肿瘤分割图、基因突变和RNA测序数据以及临床信息。其特点是整合了影像、基因组和临床数据，旨在探索影像与基因组特征之间的关联，并开发预后医学影像生物标志物，以促进精准医疗研究。