The Cancer Imaging Archive Updates : May 2023

[The Cancer Imaging Program]

The Cancer Imaging Archive Updates : May 2023 New TCIA Datasets Brain Tumor Recurrence Prediction after Gamma Knife Radiotherapy from MRI and Related DICOM-RT: An Open Annotated Dataset and Baseline Algorithm  The Brain-TR-GammaKnife dataset contains  brain cancer MRIs  with  companion Gamma Knife treatment planning and clinical  data. The dataset contains original patient MRI images (in DICOM format), radiation therapy structure data (in DICOM and NRRD format), code, and clinical information. 244 lesions from 47 subjects were annotated.  Each lesion MRI is paired with its radiation dose MRI. The release of this dataset is expected to contribute to the development of automated brain tumor recurrence prediction algorithms. Burdenko's Glioblastoma Progression Dataset  The Burdenko-GBM-Progression dataset contains imaging from 180 patients with primary glioblastoma treated at the Burdenko National Medical Research Center of Neurosurgery between 2014 and 2020. For each patient, the dataset includes imaging studies conducted for radiotherapy planning and follow-up studies. The radiotherapy studies consist of 4 MRI sequences (T1, T1C, T2, FLAIR), a topometric CT scan, and associated radiotherapy planning files (RTSTRUCT, RTPLAN, and RTDOSE). Follow-up studies (from 1 to 8-time per patient) include 2-4 MRI sequences (with a minimal set of T1C and FLAIR) per patient. Additional genetic information (IDH1/2, MGMT mutations) and treatment response status (tumour progression, tumour pseudoprogression, treatment response) are available for a subset of patients. New Annotations CALGB50303-Tumor-Annotations The CALGB50303-Tumor-Annotations dataset contains tumor segmentations and seed points generated from the TCIA NCI clinical trial imaging data collection “Rituximab and Combination Chemotherapy in Treating Patients With Diffuse Large B-Cell Non-Hodgkin's Lymphoma (CALGB50303)”.   It is hoped that these annotations along with the provided supporting documentation and Jupyter Notebooks will facilitate algorithmic analysis of the images collected for this trial. TCIA data featured on CTV News Canada Engineers at the University of Waterloo were recently highlighted by CTV News Canada for their development of a novel AI tool that can help personalize treatment for breast cancer. The tool used the ACRIN6698 collection available on TCIA, and has the potential to help some patients avoid the serious side-effects of chemotherapy while making it easier for patients who would benefit from the treatment to receive it. It is part of the open-source "Cancer-Net" information-sharing initiative led by Dr. Alexander Wong, a professor of systems design engineering at the university. Stay Connected with The Cancer Imaging Archive  Manage Subscriptions | Help The Cancer imaging Archive is funded in part by Frederick Natational Lab for Cancer Research.

 

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