Summary
thThis data set includes low-dose whole body CT images and tissue segmentations of thirty healthy adult research participants who underwent a PET/CT scan on the uEXPLORER total-body PET system at UC Davis. Participants included in this study were healthy adults 18 years of age or older who were able to provide informed written consent. The participants age, gender, weight, height, and body mass index are also provided.
Fifteen participants underwent a CT scan at three different timepoints during a 3-hour period (0 minutes, 90 minutes, and 180 minutes), while the remaining 15 participants underwent six CT scans during a 12-hour period (additionally at 360 minutes, 540 minutes, and 720 minutes). The tissue segmentations include 37 tissues consisting of 13 abdominal organs, 20 different bones, subcutaneous and visceral fat, skeletal and psoas muscle.
The uEXPLORER CT scanner is an 80-row, 160 slice CT scanner typically used for anatomical imaging and attenuation correction for PET/CT imaging. The CT scan obtained at 90 minutes was performed with 140 kVp and an average of 50 mAs for all subjects while at all other time-points (0 minutes, 180 minutes, ect.) the CT scan was obtained with 140 kVp and average of 5 mAs. CT images were reconstructed into a 512x512x828 image matrix with 0.9766x0.9766x2.344 mm3 voxel size. It is planned to add the FDG PET dynamic total-body sequences in a future version update.
This data is useful as a benchmark for evaluating normal physiological state, and comparing it to pathological states. Combined with other data sets, it can be used to evaluate the progress and impact of aging related diseases, cancer progression and response to treatment, and other conditions. It is unique in including healthy research participants, as well as for including full body images from the brain to the feet. It can also be used to train AI algorithms to enable automatic segmentation of the previously described tissues.
Acknowledgements
We would like to acknowledge the individuals and institutions that have provided data for this collection:
Funding for this work was provided by NIH grant R01 CA206187, which is supported by NCI, NIBIB and the Office of the Director, and by R01 CA249422.
Data Access
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Data Type | Download all or Query/Filter | License |
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Images, (DICOM, XX.X GB) | (Download requires NBIA Data Retriever) | |
Segmentations (NIfTI) | ||
Clinical data (CSV) Segmentation Organ values |
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Detailed Description
Image Statistics | Radiology Image Statistics |
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Modalities | CT |
Number of Patients | 30 |
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Citations & Data Usage Policy
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TCIA Citation
Clark, K., Vendt, B., Smith, K., Freymann, J., Kirby, J., Koppel, P., Moore, S., Phillips, S., Maffitt, D., Pringle, M., Tarbox, L., & Prior, F. (2013). The Cancer Imaging Archive (TCIA): Maintaining and Operating a Public Information Repository. In Journal of Digital Imaging (Vol. 26, Issue 6, pp. 1045–1057). Springer Science and Business Media LLC. https://doi.org/10.1007/s10278-013-9622-7
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Version 1 (Current): Updated yyyy/mm/dd
Data Type | Download all or Query/Filter | License |
---|---|---|
Images | (Download requires the NBIA Data Retriever) | |
Segmentations (NIfTI) | ||
Clinical data (CSV) Segmentation Organ values |