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ANTI-PD-1_LUNG

Anti-PD-1_Lung | Anti-PD-1 Immunotherapy Lung

DOI: 10.7937/tcia.2019.zjjwb9ip | Data Citation Required | Image Collection

Location Species Subjects Data Types Cancer Types Size Status Updated
Lung Human 46 CT, PT, SC Lung Cancer 61.24GB Public, Complete 2019/04/19

Summary

This collection includes 46 lung cases treated with anti-PD1 immunotherapy in 2016, each with pre-treatment and most with 1 imaging follow-up timepoint.

Data Access

Version 1: Updated 2019/04/19

Title Data Type Format Access Points Subjects Studies Series Images License
Images CT, SC, PT DICOM
Download requires NBIA Data Retriever
 46 86 677 134,465 CC BY 3.0

Additional Resources for this Dataset

The NCI Cancer Research Data Commons (CRDC) provides access to additional data and a cloud-based data science infrastructure that connects data sets with analytics tools to allow users to share, integrate, analyze, and visualize cancer research data.

Citations & Data Usage Policy

Data Citation Required: Users must abide by the TCIA Data Usage Policy and Restrictions. Attribution must include the following citation, including the Digital Object Identifier:

Data Citation

Madhavi, P., Patel, S., & Tsao, A. S. (2019). Data from Anti-PD-1 Immunotherapy Lung [Data set]. The Cancer Imaging Archive. DOI:  10.7937/tcia.2019.zjjwb9ip

Other Publications Using this Data

TCIA maintains a list of publications which leverage our data. If you have a publication you’d like to add please contact TCIA’s Helpdesk.

  • Kosareva, A. A., Paulenka, D. A., Snezhko, E. V., Bratchenko, I. A., & Kovalev, V. A. (2022). Examining the Validity of Input Lung CT Images Submitted to the AI-Based Computerized Diagnosis. Journal of Biomedical Photonics & Engineering, 8(3). doi: https://doi.org/10.18287/JBPE22.08.030307
  • Leitner, B. P., & Perry, R. J. (2020). The Impact of Obesity on Tumor Glucose Uptake in Breast and Lung Cancer. JNCI Cancer Spectrum. doi:10.1093/jncics/pkaa007
  • Sinthia, P., Malathi, M., K, A., & Suresh Anand, M. (2022). Improving lung cancer detection using faster region‐based convolutional neural network aided with fuzzy butterfly optimization algorithm. Concurrency and Computation: Practice and Experience. doi:https://doi.org/10.1002/cpe.7251
  • Trebeschi, S., Bodalal, Z., van Dijk, N., Boellaard, T. N., Apfaltrer, P., Tareco Bucho, T. M., . . . Beets-Tan, R. G. H. (2021). Development of a Prognostic AI-Monitor for Metastatic Urothelial Cancer Patients Receiving Immunotherapy. Front Oncol, 11, 637804. doi:10.3389/fonc.2021.637804

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
Analysis Results Using This Collection