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The patients in this dataset should fulfill: (1) Pathologically proven Adrenocortical carcinoma, (2) underwent surgical resection of the tumour, (3) the Ki-67 index was determined as part of the histopathological evaluation of the resected tissue, (4) imaging data (pre-resection contrast-enhanced CT of the abdomen) were available. Data from patients whose Ki-67 was quantified in biopsied tissue samples rather than from resected whole tumor, were excluded from this study. This exclusion was based on previous studies concluding that Ki-67 quantification should be based on tissue samples collected from the whole tumour. Voxel level segmentation of the adrenal lesion in will be included as well.
This dataset can serve as a training set for any machine learning algorithm for various purposes. We used the radiomic features extracted to predict the Ki-67 index (through regression) without the need of surgical intervention, it also can be used for multiple purposes for segmentation, and classification of adrenal tumors. In addition, there is no public available library for adrenal lesions, and this should be important to scientific community. |
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We would like to acknowledge the individuals and institutions that have provided data for this collection:
Mohab M. Elmohr
Aya A. Ahmed
Localtab Group |
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Localtab |
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active | true |
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title | Data Access |
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| Data AccessData Type | Download all or Query/Filter | License |
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Images and Segmentations (DICOM, 9.9 GB)
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(Download requires the NBIA Data Retriever) | | Clinical data (CSV) | | |
Click the Versions tab for more info about data releases. Please contact help@cancerimagingarchive.net with any questions regarding usage. |
Localtab |
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title | Detailed Description |
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| Detailed DescriptionImage Statistics | Radiology Image statistics |
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Modalities | CT, SEG | Number of Patients | 53 | Number of Studies | 65 | Number of Series | 177 | Number of Images | 18,255 | Images Size (GB) | 9.9 GB |
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Localtab |
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title | Citations & Data Usage Policy |
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| Citations & Data Usage Policy Tcia license 4 international |
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Info |
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title | Publication Citation |
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| Ahmed, A. A., Elmohr, M. M., Fuentes, D., Habra, M. A., Fisher, S. B., Perrier, N. D., Zhang, M., & Elsayes, K. M. (2020). Radiomic mapping model for prediction of Ki-67 expression in adrenocortical carcinoma. In Clinical Radiology (Vol. 75, Issue 6, p. 479.e17-479.e22). Elsevier BV. https://doi.org/10.1016/j.crad.2020.01.012 | Info |
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| Only if they ask for special acknowledgments like funding sources, grant numbers, etc in their proposal. |
Info |
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| Clark K, Vendt B, Smith K, Freymann J, Kirby J, Koppel P, Moore S, Phillips S, Maffitt D, Pringle M, Tarbox L, Prior F. The Cancer Imaging Archive (TCIA): Maintaining and Operating a Public Information Repository, Journal of Digital Imaging, Volume 26, Number 6, December, 2013, pp 1045-1057. DOI: 10.1007/s10278-013-9622-7 |
Other Publications Using This DataTCIA maintains a list of publications which leverage TCIA data. If you have a manuscript you'd like to add please contact the TCIA Helpdesk. |
Localtab |
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| Version 1 (Current): Updated 2022/01/ddData Type | Download all or Query/Filter | License |
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Images (DICOM, xx.x GB) | Clinical Data (CSV | Link |
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