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4D-LUNG

4D-Lung | Data from 4D Lung Imaging of NSCLC Patients

DOI: 10.7937/K9/TCIA.2016.ELN8YGLE | Data Citation Required | Image Collection

Location Species Subjects Data Types Cancer Types Size Supporting Data Status Updated
Lung Human 20 CT, RTSTRUCT Non-small Cell Lung Cancer 183.04GB Image Analyses Public, Complete 2016/10/19

Summary

This data collection consists of images acquired during chemoradiotherapy of 20 locally-advanced, non-small cell lung cancer patients. The images include four-dimensional (4D) fan beam (4D-FBCT) and 4D cone beam CT (4D-CBCT). All patients underwent concurrent radiochemotherapy to a total dose of 64.8-70 Gy using daily 1.8 or 2 Gy fractions. 

4D-FBCT images were acquired on a 16-slice helical CT scanner (Brilliance Big Bore, Philips Medical Systems, Andover, MA) as respiration-correlated CTs with 10 breathing phases (0 to 90%, phase-based binning) and 3 mm slice thickness. 4D-FBCT images were acquired during simulation, prior to therapy, and used for therapy planning. In 14 of the 20 subjects, 4D-FBCTs were also acquired on the same scanner weekly during therapy. 4D-CBCT images were acquired on a commercial CBCT scanner (On-Board Imager™, Varian Medical Systems, Inc.). An external surrogate (Real-time Position Management, Varian Medical Systems, Inc.) was integrated into the CBCT acquisition system to stamp each CBCT projection with the surrogate respiratory signal through in-house software and hardware tools. Approximately 2500 projections were acquired over a period of 8-10 minutes in half-fan mode with half bow-tie filter. The technique was 125 kVp, 20 mA, and 20 ms in a single 360° slow gantry arc. Using the external surrogate, the CBCT projections were sorted into 10 breathing phases (0 to 90%, phase-based binning) and reconstructed with an in-house FDK reconstruction algorithm.

Audio-visual biofeedback was performed for all 4D-FBCT and 4D-CBCT acquisitions in all subjects. A single Radiation Oncologist delineated targets and organs at risk in all 4D-FBCT and a limited number of 4D-CBCT images, on all 10 phases per scan. Seven of the subjects had gold coils implanted as fiducial markers in or near the tumor. 

The dataset is most fully described in detail in Balik et al.1  Seven of the subjects had gold coils implanted as fiducial markers in or near the tumor. The implantation procedure and details of marker location are described in detail in Roman et al.2

References

Data Access

Version 2: Updated 2016/10/19

Any download of this dataset prior to October 18 2016 contains data that was updated after that date by the investigators. It is recommended that you download a fresh copy before applying your analysis.

Title Data Type Format Access Points Subjects Studies Series Images License
Images and Radiation Therapy Structures RTSTRUCT, CT DICOM
Download requires NBIA Data Retriever
 20 589 6,690 347,330 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

Hugo, G. D., Weiss, E., Sleeman, W. C., Balik, S., Keall, P. J., Lu, J., & Williamson, J. F. (2016). Data from 4D Lung Imaging of NSCLC Patients (Version 2) [Data set]. The Cancer Imaging Archive. https://doi.org/10.7937/K9/TCIA.2016.ELN8YGLE

Acknowledgements

Data collection and analysis was supported by NIH P01CA116602.

Other Publications Using this Data

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

Publication Citation

Hugo, G. D., Weiss, E., Sleeman, W. C., Balik, S., Keall, P. J., Lu, J., & Williamson, J. F. (2017). A longitudinal four-dimensional computed tomography and cone beam computed tomography dataset for image-guided radiation therapy research in lung cancer. In Medical Physics (Vol. 44, Issue 2, pp. 762–771). Wiley. https://doi.org/10.1002/mp.12059

Publication Citation

Balik, S., Weiss, E., Jan, N., Roman, N., Sleeman, W. C., Fatyga, M., Christensen, G. E., Zhang, C., Murphy, M. J., Lu, J., Keall, P., Williamson, J. F., & Hugo, G. D. (2013). Evaluation of 4-dimensional Computed Tomography to 4-dimensional Cone-Beam Computed Tomography Deformable Image Registration for Lung Cancer Adaptive Radiation Therapy. In International Journal of Radiation Oncology*Biology*Physics (Vol. 86, Issue 2, pp. 372–379). Elsevier BV. PMCID: PMC3647023. https://doi.org/10.1016/j.ijrobp.2012.12.023

Publication Citation

Roman, N. O., Shepherd, W., Mukhopadhyay, N., Hugo, G. D., & Weiss, E. (2012). Interfractional Positional Variability of Fiducial Markers and Primary Tumors in Locally Advanced Non-Small-Cell Lung Cancer During Audiovisual Biofeedback Radiotherapy. In International Journal of Radiation Oncology*Biology*Physics (Vol. 83, Issue 5, pp. 1566–1572). Elsevier BV. https://doi.org/10.1016/j.ijrobp.2011.10.051

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

Previous Versions

Version 1: Updated 2015/09/14

deprecated

Title Data Type Format Access Points Studies Series Images License