Breast cancer-related VOCs

This dataset was collected to evaluate the diagnostic performance of breath-omics to differentiate between benign and malignant breast lesions and assess the diagnostic performance of a multi-omics approach combining breath-omics, ultrasound radiomics, and clinic-omics via a nested cohort study. This dataset includes three parts data all finally enroll 238 participants: 1) breath-omics data: the mass spectrum of participants breath samples on high-pressure photon ionization time-of-flight mass spectrometry (HPPI-TOF-MS); 2) basic clinic data: the basic clinical characteristics of all enrolled participant; 3) ultrasound radiomics data: the radiomics features calculated based the delineated lesion via Pyradiomics package.

本数据集旨在通过嵌套队列研究，评估呼吸组学（breath-omics）鉴别乳腺良恶性病变的诊断效能，并评估融合呼吸组学、超声放射组学与临床组学的多组学联合诊断策略的诊断性能。本数据集最终共纳入238名受试者，包含三部分数据：1）呼吸组学数据：采用高压光电离飞行时间质谱（HPPI-TOF-MS）采集的受试者呼吸样本质谱数据；2）基础临床数据：所有入组受试者的基础临床特征；3）超声放射组学数据：通过Pyradiomics软件包对勾画的病灶提取得到的放射组学特征。