The Research for Precision Oncology Program (RePOP) is a research activity that established a cohort of Veterans diagnosed with cancer and had genomic analyses performed on their tumor tissue as part of the standard of care. All data relevant to a patient’s cancer and cancer care were collected under RePOP, including patient demographics, comorbidities, genomic analysis, treatments, medications, lab values, imaging...
This dataset was generated to train models for research in the Radiation Planning Assistant (RPA), aimed at auto-contouring cervical lymph node levels in the head and neck.
- Patients: Training = 32 (31 unique); Test = 15
- Acquisition Protocol: See accompanying spreadsheet (TCIA_RPA_HN_LNs_Aquisition_Protocols) for more details....
We provide an annotated imaging dataset of cancerous CT spines to help develop artificial intelligence frameworks for automatic vertebrae segmentation and classification. This collection contains a dataset of 55 CT scans collected on patients with a large range of primary cancers and corresponding bone metastatic lesions obtained for patients with metastatic spine disease. The subjects of the study planned for radiotherapy...
The dataset is a collection of retrospective pre-operative brain magnetic resonance imaging (MRI) scans, clinically acquired from six diagnostic centers in Nigeria. The scans are from 146 patients who have brain MRIs indicating central nervous system neoplasms, diffuse glioma, low-grade glioma, or glioblastoma/high-grade glioma. The brain scans were multiparametric MR images (mpMRI), specifically T1, T1 CE, T2, and...
The Cancer Moonshot Biobank is a National Cancer Institute initiative to support current and future investigations into drug resistance and sensitivity and other NCI-sponsored cancer research initiatives, with an aim of improving researchers' understanding of cancer and how to intervene in cancer initiation and progression. During the course of this study, biospecimens...
The Cancer Moonshot Biobank is a National Cancer Institute initiative to support current and future investigations into drug resistance and sensitivity and other NCI-sponsored cancer research initiatives, with an aim of improving researchers' understanding of cancer and how to intervene in cancer initiation and progression. During the course of this study, biospecimens...
The dataset concerns patients with lymphadenopathy (i.e., swelling of lymph nodes) due to illness or disease, such as cancer or infections. Lymph node disease involvement is due to the body’s immune response.
The cohort is a cross-institutional dataset of chest CT scans acquired from 513 patients during treatment for various cancer types, curated for the
Background: Pediatric tumors of the central nervous system are the leading cause of cancer-related death among children. High-grade gliomas (HGGs) in children have a five-year survival rate of less than 20%. Due to their rarity, diagnosis is often delayed, treatment strategies rely on historical protocols, and clinical trials necessitate collaboration across multiple institutions.
Summary: The...
Quantitative imaging biomarkers (QIB) are increasingly used in clinical research to advance precision medicine approaches in oncology. Unlike biopsy-based biomarkers, QIBs are non-invasive and can estimate the spatial and temporal heterogeneity of total tumor burden. Computed tomography (CT) is a modality of choice for cancer diagnosis, prognosis, and response assessment due to its reliability and global accessibility.
In...
Hyperspectral imaging technology combines the main features of two existing technologies: conventional imaging and spectroscopy. Thus, hyperspectral cameras make it possible to analyze, at the same time and in a non-contact way, the morphological features and chemical composition of the objects captured. The information provided by hyperspectral imaging can be used to detect patterns, cells, or biomarkers to identify...