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...
This collection includes data from 211 patients who presented with head and neck cancer and were treated using radiation therapy at a single institution using 6 MV Intensity Modulated Radiation Therapy (IMRT) from a linear accelerator. All patients were prescribed identical prescriptions of 70 Gray (Gy) in 33 fractions for the primary planning target volume (PTV) and one, none, or a combination of integrated boost...
The RADCURE dataset was collected clinically for radiation therapy treatment planning and retrospectively reconstructed for quantitative imaging research.
Inclusion: The dataset used for this study consists of 3,346 head and neck cancer CT image volumes collected from 2005-2017 treated with definitive RT at the University Health Network (UHN) in Toronto, Canada
Acquisition and...
Patient images were collected from three sources: the Yale New Haven Health database (2013-2021), the Yale tumor board registry (2021), and the Yale gamma knife registry (2017-2021).
Inclusion criteria included a pathologically proven diagnosis of brain metastasis and availability of a pretreatment scan with standard MRI sequences...
This dataset consists of 256 breast ultrasound scans collected from 256 patients and 266 benign and malignant segmented lesions. It includes patient-level labels, image-level annotations, and tumor-level labels with all cases confirmed by follow-up care or biopsy result. Each scan was manually annotated and labeled by a radiologist experienced in breast ultrasound examination. In particular, each tumor was identified...
Ductal carcinoma in situ with microinvasion (DCISM) is a challenging subtype of breast cancer with controversial invasiveness and prognosis. Accurate diagnosis of DCISM from ductal carcinoma in situ (DCIS) is crucial for optimal treatment and improved clinical outcomes. This dataset provides histopathology images and paired CK5/6 immunohistochemical staining images from patients with DCISM, as well as multiphoton microscopy...
The application of deep-learning methods to breast MRI has a potential to improve diagnosis as well as predict pathological features of the tumors and their response to therapy, and is currently widely investigated. Standard contrast-enhanced MRI of the breast provides high sensitivity but variable specificity in detecting breast cancer, and may lead to excessive benign biopsies. Large, well annotated datasets are...
In this single institution retrospective study, we reviewed 950 consecutive patients with prostate adenocarcinoma receiving definitive radiotherapy between 2011 and 2019, and identified among them 112 patients with anatomic variations (edge cases) seen on simulation CT and/or MRI imaging. These variations included hip arthroplasty, prostate median lobe hypertrophy, so-called “droopy” seminal vesicles, presence...
