The‌ ‌Cancer‌ ‌Imaging‌ ‌Archive‌ ‌Updates:‌ January 2024

[The Cancer Imaging Program]

The Cancer Imaging Archive Updates : January 2024 New Clinical Trial Image Annotations The Cancer Imaging Program continues to provide new expert-generated tumor segmentations and annotations to NCI Clinical trial datasets on TCIA.  These can be found in the  analysis results section of  the TCIA website. The latest additions include annotations of hepatoblastomas, nasopharyngeal cancers, desmoid tumors or aggressive fibromatosis and head-neck squamous cell carcinomas. New Imaging Data Collections “A morphological dataset of white blood cells from patients with 4 different genetic AML entities and non-malignant controls (AML-Cytomorphology_MLL_Helmholtz)" is now available. This dataset includes digitized blood smears and clniical data from 189 subjects in the Munich Leukemia Laboratory database, covering four prevalent AML subtypes with defining genetic abnormalities and typical morphological features according to the WHO 2022 classification, and a control group of healthy stem cell donors. Mammography, MRI, and CT scans from 500 subjects in the "Abbreviated Breast MRI and Digital Tomosynthesis Mammography in Screening Women With Dense Breasts (EA1141)" phase II trial dataset are available on TCIA. The trial studied how MRI/DBT imaging techniques work in detecting cancer in women with dense breasts. The "Low-Dose CT Images of Healthy Cohort (Healthy-Total-Body CTs)" collection is now available on TCIA. It includes low-dose whole body CT images and tissue segmentations of 30 healthy participants who underwent PET/CT imaging on the uEXPLORER total-body PET/CT system at UC Davis. CT images are included in the data set from either three or six timepoints. The tissue segmentations include 37 tissues consisting of 13 abdominal organs, 20 different bones, subcutaneous and visceral fat, skeletal and psoas muscle. New Analysis Results Collections The "Sparsely Annotated Region and Organ Segmentation (SAROS)" dataset adds segmentations for existing CT images from 882 subjects on TCIA with the goal of providing high-quality annotations for building body composition analysis tools. TCIA-Related Tools A new  Python tutorial is available that helps coders working with tumor or organ segmentation datasets on TCIA to match the segmentations to the appropriate scans. The Cancer Imaging Archive Stay Connected with The Cancer Imaging Archive  To subscribe click here and select “The Cancer Imaging Program” Manage Subscriptions | Help The Cancer imaging Archive is funded in part by Frederick Natational Lab for Cancer Research.

 

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