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Summary

Excerpt

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.

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). A single Radiation Oncologist delineated targets and organs at risk in all 4D-FBCT and a limited number of 4D-CBCT images. All patients underwent concurrent radiochemotherapy to a total dose of 64.8-70 Gy using daily 1.8 or 2 Gy fractions.  The dataset is more fully described in the ‘Description’ section below.

 

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titleData Access

Data Access

This is a limited access data set. To request access, please contact help@cancerimagingarchive.net. Once access is granted, you can view and download these images on The Cancer Imaging Archive (TCIA) by logging in and selecting the 4D-Lung collection.

Data TypeDownload all or Query/Filter
Images (DICOM, ??GB) Image Removed

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locationhttps://www.cancerimagingarchive.net/collection/4d-lung/

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titleDetailed Description

Detailed Description

Collection Statistics

Update 09/14/2015

Modalities

CT, RTSTRUCT

Number of Patients

20

Number of Studies

589

Number of Series

6,690

Number of Images

347,330

Image Size (GB) 
Excerpt

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.

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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.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

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For questions and information regarding this dataset, please contact Geoff Hugo, gdhugo@vcu.edu.

Data collection and analysis was supported by NIH P01CA116602.

 

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titleCitations & Data Usage Policy

Citations & Data Usage Policy 

This is a limited access data set. Upon receiving access you may only use it for the purposes outlined in your request to the data provider. You are not allowed to redistribute the data or use it for other purposes. See TCIA's Data Usage Policies and Restrictions for additional details. Questions may be directed to help@cancerimagingarchive.net.

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title

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The Cancer Imaging Archive Team. Data From 4D-Lung. (DOI coming soon)

Info
titleTCIA 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. 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. (paper)

Other Publications Using This Data

TCIA maintains a list of publications which leverage our data. At this time we are not aware of any publications based on this data. If you have a publication you'd like to add please contact the TCIA Helpdesk.

 

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References

1 S. Balik et al., “Evaluation of 4-Dimensional Computed Tomography to 4-Dimensional Cone-Beam Computed Tomography Deformable Image Registration for Lung Cancer Adaptive Radiation Therapy.” Int. J. Radiat. Oncol. Biol. Phys. 86, 372–9 (2013) PMCID: PMC3647023.

2 N.O. Roman, W. Shepherd, N. Mukhopadhyay, G.D. Hugo, and E. Weiss, “Interfractional Positional Variability of Fiducial Markers and Primary Tumors in Locally Advanced Non-Small-Cell Lung Cancer during Audiovisual Biofeedback Radiotherapy.” Int. J. Radiat. Oncol. Biol. Phys. 83, 1566–72 (2012).

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Acknowledgements

Data collection and analysis was supported by NIH P01CA116602.


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activetrue
titleData Access

Data Access

 

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Data TypeDownload all or Query/Filter

...

License
Images and Radiation Therapy Structures

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(DICOM,

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183GB)

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Localtab
activetrue
titleFiles
Data Type (Click to download)
Note

Images

Updated 2015-08-28
Clinical DataUpdated 2015-xx-xx

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titleDescription

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Collection Statistics

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(updated 2015/09/14)


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urlhttps://wiki.cancerimagingarchive.net/download/attachments/21267414/doiJNLP-Y71kLpdQ.tcia?version=1&modificationDate=1534787014809&api=v2



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labelSearch
urlhttps://nbia.cancerimagingarchive.net/nbia-search/?CollectionCriteria=4D-Lung



(Download requires NBIA Data Retriever)

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Nci_crdc additional resources




Localtab
titleDetailed Description

Detailed Description


Collection Statistics


Modalities

CT, RTSTRUCT

Number of

...

Participants

20

Number of Studies

589

Number of Series

6,690

Number of Images

347,330

...

Image Size (GB)

...

 

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. The dataset -- including 4D fan and cone beam CT technique and collection protocol, delineation protocol, an -- is most fully described in detail in Balik et al.Briefly, 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 implantation procedure and details of marker location are described in detail in Roman et al.2

For questions and information regarding this dataset, please contact Geoff Hugo, gdhugo@vcu.edu.

Data collection and analysis was supported by NIH P01CA116602.

References

 

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titleReferences

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183





Localtab
titleCitations & Data Usage Policy

Citations & Data Usage Policy 

Tcia limited license policy

Info
titleData 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


Info
titlePublication 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


Info
titlePublication 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.

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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


Info
titlePublication Citation

Roman, N. O., Shepherd, W., Mukhopadhyay, N., Hugo

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, G. D.

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, & Weiss,

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E

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. (2012). Interfractional Positional Variability of Fiducial Markers and Primary Tumors in Locally Advanced Non-Small-Cell Lung Cancer

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During Audiovisual Biofeedback Radiotherapy.

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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


Info
titleTCIA 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. 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 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.





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title

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titleVersions

 

 

 

 

 

Versions

Version 2 (Current): 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.


Data TypeDownload all or Query/Filter
Images (DICOM, 183GB)
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labelSearch
urlhttps://nbia.cancerimagingarchive.net/nbia-search/?MinNumberOfStudiesCriteria=1&CollectionCriteria=4D-Lung


(Download requires the NBIA Data Retriever .)


Version 1 : 2015/09/14


Data TypeDownload all or Query/Filter
Images (DICOM, 183GB)


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(Download requires the NBIA Data Retriever .)

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