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Summary

Excerpt

This collection is a set of head and neck cancer patients' multiple positron emission tomography/computed tomography (PET/CT) 18F-FDG scans–before and after therapy–with follow up scans where clinically indicated. The data was provided to help facilitate research activities of the National Cancer Institute's (NCI's) Quantitative Imaging Network (QIN). This collection was supported by Grants: U24 CA180918 (http://qiicr.org) and U01 CA140206.

The following schematic summarizes much of the work done within the QIICR grant to augment the PET/CT scans with segmentations and clinical data using the DICOM standard: (click to enlarge)

About the NCI QIN

The mission of the QIN is to improve the role of quantitative imaging for clinical decision making in oncology by developing and validating data acquisition, analysis methods, and tools to tailor treatment for individual patients and predict or monitor the response to drug or radiation therapy. More information is available on the Quantitative Imaging Network Collections page. Interested investigators can apply to the QIN at: Quantitative Imaging for Evaluation of Responses to Cancer Therapies (U01) PAR-11-150.

 

 


Localtab Group



Localtab
activetrue
titleData Access

Data Access

Choosing the Download option will provide you with a file to launch the TCIA Download Manager to download the entire collection. If you want to browse or filter the data to select only specific scans/studies please use the Search By Collection option.

Tcia head license access

Data TypeDownload all or Query/FilterLicense
Images and Segmentations (DICOM,
104GB)
Image Removed Image Removed
DICOM Metadata Digest (CSV)Image Removed
Clinical data(See Detailed Description tab)
201.2 GB)


Tcia button generator
urlhttps://wiki.cancerimagingarchive.net/download/attachments/6885289/QIN-HEADNECK%20NBIA-manifest.tcia_20200914.tcia?api=v2



Tcia button generator
labelSearch
urlhttps://nbia.cancerimagingarchive.net/nbia-search/?MinNumberOfStudiesCriteria=1&CollectionCriteria=QIN-HEADNECK


  

(Download requires NBIA Data Retriever)

Tcia restricted license

Clinical Data (.xlsx 68 kB)

(See also Detailed Description)


Tcia button generator
urlhttps://wiki.cancerimagingarchive.net/download/attachments/6885289/Batch_01%20and%20Batch_02%20Clinical%20Data_aug242020.xlsx?api=v2




Tcia cc by 3


Click the Versions tab for more info about data releases.




 

Metadata

Access to this collection's clinical data is restricted due to the type of information included and/or the informed consent procedure under which the data were collected. If you  believe this data will be useful for a current or planned research project, you may request access to this clinical data by completing the attached Data Use Agreement and forwarding it via e-mail to the TCIA help desk (help@cancerimagingarchive.net). The Data Use Agreement will be promptly reviewed by a TCIA review committee and you will be informed of their decision. In most cases access will be granted and members of your research team will be granted access to the clinical data. Note: you must have TCIA login credentials in order to access any restricted collection
Localtab
titleDetailed Description

Detailed Description


Collection Statistics

 


Modalities

PET, CT, SR, SEG, RWV

Number of

Patients

Participants

156

279

Number of Studies

651

1032

Number of Series

429

3837

Number of Images

353

701,

408

002

Image Size (GB)
104
201.2

Associated Clinical Metadata

  • Structured Report DICOM objects (Modality SR), are available for a subset of these subjects in the DICOM downloads and can be distinguished from image files by the series description "Clinical Data." Note, there is no image preview thumbnail for a Structured Report.




Localtab
titleCitations & Data Usage Policy

Citations & Data Usage Policy 

This collection is freely available to browse, download, and use for commercial, scientific and educational purposes as outlined in the Creative Commons Attribution 3.0 Unported License.  See TCIA's Data Usage Policies and Restrictions for additional details. Questions may be directed to help@cancerimagingarchive.net.

Please be sure to include the following citations in your work if you use this data set:

Tcia limited license policy

Info
titleData Citation

Beichel, R. R., Ulrich, E. J., Bauer, C., Wahle, A., Brown, B., Chang, T., Plichta, K A., Smith, B J., Sunderland, J J., Braun, T., Fedorov, A., Clunie, D., Onken, M., Magnotta, V. A., Menda, Y., Riesmeier, J., Pieper, S., Kikinis, R., Graham, M.M., Casavant T. L., Sonka M,. & Buatti, J M. (2015). Data From QIN-HEADNECK (Version 4) [Data set]. The Cancer Imaging Archive. http https://doi.org/10.7937/K9/TCIA.2015.K0F5CGLI


Info
titlePublication Citation

Fedorov, A., Clunie, D., Ulrich, E., Bauer, C., Wahle, A., Brown, B., Onken, M., Riesmeier, J., Pieper, S., Kikinis, R., Buatti, J., & Beichel RR, R. R. (2016). DICOM for quantitative imaging biomarker development: a standards based approach to sharing clinical data and structured PET/CT analysis results in head and neck cancer research. In PeerJ 4:e2057 (Vol. 4, p. e2057). PeerJ. https://doi.org/10.7717/peerj.2057


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. (2013).  The Cancer Imaging Archive (TCIA): Maintaining and Operating a Public Information Repository, . In Journal of Digital Imaging , Volume (Vol. 26, Number Issue 6, December, 2013, pp 1045-1057. (paper)1045–1057). Springer Science and Business Media LLC. https://doi.org/10.1007/s10278-013-9622-7 PMCID: PMC3824915

Other Publications Using This Data

TCIA maintains a list of publications which leverage our data, including citations of this CollectionTCIA data. If you have a publication manuscript you'd like to add please contact the TCIA's Helpdesk. 

  • Ahmadvand, P., Duggan, N., Bénard, F., & Hamarneh, G. (2016). Tumor Lesion Segmentation from 3D PET Using a Machine Learning Driven Active Surface.  International Workshop on Machine Learning in Medical Imaging. doi: 10.1007/978-3-319-47157-0_33
  • Fedorov, A., Beichel, R., Kalpathy-Cramer, J., Clunie, D., Onken, M., Riesmeier, J., . . . Kikinis, R. (2020). Quantitative Imaging Informatics for Cancer Research. JCO Clin Cancer Inform, 4, 444-453. doi:https://doi.org/10.1200/CCI.19.00165
  • Fedorov, A., Clunie, D., Ulrich, E., Bauer, C., Wahle, A., Brown, B., . . . Beichel, R. R. (2016). DICOM for quantitative imaging biomarker development: a standards based approach to sharing clinical data and structured PET/CT analysis results in head and neck cancer research. PeerJ, 4, e2057. doi: 10.7717/peerj.2057
  • Ghattas, A. E. (2017). Medical Imaging Segmentation Assessment via Bayesian Approaches to Fusion, Accuracy and Variability Estimation with Application to Head and Neck Cancer. (PhD). The University of Iowa, Retrieved from http://ir.uiowa.edu/etd/5759
  • Liang, X., Bassenne, M., Hristov, D. H., Islam, M. T., Zhao, W., Jia, M., . . . Xing, L. (2022). Human-level comparable control volume mapping with a deep unsupervised-learning model for image-guided radiation therapy. Comput Biol Med, 141, 105139. doi: 10.1016/j.compbiomed.2021.105139
  • Lv, W., Zhou, Z., Peng, J., Peng, L., Lin, G., Wu, H., . . . Lu, L. (2023). Functional-structural Sub-region Graph Convolutional Network (FSGCN): Application to the Prognosis of Head and Neck Cancer with PET/CT imaging. Computer Methods and Programs in Biomedicine. doi:  10.1016/j.cmpb.2023.107341
  • Sinha, A. (2018). Deformable registration using shape statistics with applications in sinus surgery. (Ph. D.). Johns Hopkins University, Retrieved from http://jhir.library.jhu.edu/handle/1774.2/59202
  • Sinha, A., Billings, S. D., Reiter, A., Liu, X., Ishii, M., Hager, G. D., & Taylor, R. H. (2019). The deformable most-likely-point paradigm. Medical image analysis, 55, 148-164. doi: 10.1016/j.media.2019.04.013
  • Sinha et al. Towards automatic initialization of registration algorithms using simulated endoscopy images.  link to article
  • Sinha, A., Ishii, M., Hager, G. D., & Taylor, R. H. (2019). Endoscopic navigation in the clinic: registration in the absence of preoperative imaging. Int J Comput Assist Radiol Surg, 14(9), 1495-1506. doi: 10.1007/s11548-019-02005-0
  • Smith, B. J., Buatti, J. M., Bauer, C., Ulrich, E. J., Ahmadvand, P., Budzevich, M. M., . . . Beichel, R. R. (2020). Multisite Technical and Clinical Performance Evaluation of Quantitative Imaging Biomarkers from 3D FDG PET Segmentations of Head and Neck Cancer Images. Tomography, 6(2), 65-76. doi: 10.18383/j.tom.2020.00004
  • Stoll, M., Stoiber, E. M., Grimm, S., Debus, J., Bendl, R., & Giske, K. (2016). Comparison of Safety Margin Generation Concepts in Image Guided Radiotherapy to Account for Daily Head and Neck Pose Variations. PLoS One, 11(12), e0168916. doi: 10.1371/journal.pone.0168916
  • Taghanaki, S. A., Duggan, N., Ma, H., Hou, X., Celler, A., Benard, F., & Hamarneh, G. (2018). Segmentation-free direct tumor volume and metabolic activity estimation from PET scans. Comput Med Imaging Graph, 63, 52-66. doi: 10.1016/j.compmedimag.2017.12.004
  • Thomas, R., Schalck, E., Fourure, D., Bonnefoy, A., & Cervera-Marzal, I. (2021). 2Be3-Net: Combining 2D and 3D Convolutional Neural Networks for 3D PET Scans Predictions. Paper presented at the International Conference on Medical Imaging and Computer-Aided Diagnosis (MICAD 2021). doi: 10.1007/978-981-16-3880-0_27
  • 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
  • Vrtovec, T., Močnik, D., Strojan, P., Pernuš, F., & Ibragimov, B. (2020). Auto‐segmentation of organs at risk for head and neck radiotherapy planning: from atlas‐based to deep learning methods. Medical Physics, 47, e929-e950. doi: 10.1002/mp.14320
  • Zschaeck, S., Li, Y., Lin, Q., Beck, M., Amthauer, H., Bauersachs, L., . . . Hofheinz, F. (2020). Prognostic value of baseline [18F]-fluorodeoxyglucose positron emission tomography parameters MTV, TLG and asphericity in an international multicenter cohort of nasopharyngeal carcinoma patients. PLoS One, 15(7), e0236841. doi: 10.1371/journal.pone.0236841





Localtab
titleVersions

Version 4 (Current) : Updated 2020/09/15

Data TypeDownload all or Query/Filter
Images and Segmentations (DICOM 201.2 GB)


Tcia button generator
urlhttps://wiki.cancerimagingarchive.net/download/attachments/6885289/QIN-HEADNECK%20NBIA-manifest.tcia_20200914.tcia?api=v2



Tcia button generator
labelSearch
urlhttps://nbia.cancerimagingarchive.net/nbia-search/?MinNumberOfStudiesCriteria=1
(Current):
&CollectionCriteria=QIN-HEADNECK



(Download requires the NBIA Data Retriever)

Clinical Data  (.xlsx 68 kB)


Tcia button generator
urlhttps://wiki.cancerimagingarchive.net/download/attachments/6885289/Batch_01%20and%20Batch_02%20Clinical%20Data_aug242020.xlsx?api=v2



Added 123 new subjects (Patient IDs = QIN-HeadNeck-02-####).  Added missing PT or CT pre-treatment and follow up scans to 28 of the previously existing QIN-HeadNeck-01-#### subjects.  Added supporting clinical data in XLSX format for all patients.

Version 3: Updated 2019/07/24

Data TypeDownload all or Query/Filter
Images (DICOM, 103.5 GB)


Tcia button generator
urlhttps://wiki.cancerimagingarchive.net/download/attachments/6885289/TCIA_QIN-HEADNECK_2019-07-24.tcia?version=3&modificationDate=1563997513437&api=v2


  

DICOM Metadata Digest (CSV)


Tcia button generator
urlhttps://wiki.cancerimagingarchive.net/download/attachments/6885289/QIN-HEADNECK_TCIAmanifest_metadata_Jul2019.csv?version=2&modificationDate=1563997454543&api=v2



Lifted restriction from SR object data download.

Version 2: Updated 2017/12/06

Downloads require the NBIA Data Retriever .

Data TypeDownload all or Query/Filter
Images (DICOM, 104 GB)


Tcia button generator
urlhttps://wiki.cancerimagingarchive.net/download/attachments/6885289/QIN-HEADNECK-12-06-2017-doiJNLP-Hb7bP6pf.tcia?version=1&modificationDate=1534786972624&api=v2



DICOM Metadata Digest (CSV)


Tcia button generator
urlhttps://wiki.cancerimagingarchive.net/download/attachments/6885289/QIN-HEADNECK_MetaData.csv?version=1&modificationDate=1495728510607&api=v2



Added associated DICOM SEG, SR, and RWV objects

Version 1: Updated 2015/08/20

Data TypeDownload all or Query/Filter
Images (DICOM,
104GB)Image Removed Image Removed
102.76 GB)


Tcia button generator
urlhttps://wiki.cancerimagingarchive.net/download/attachments/6885289/TCIA_QIN-HEADNECK_06-22-2015.tcia?version=1&modificationDate=1534787423317&api=v2



DICOM Metadata Digest (CSV)
Image Removed
 


Tcia button generator
urlhttps://wiki.cancerimagingarchive.net/download/attachments/6885289/QIN-HEADNECK_MetaData.csv?version=1&modificationDate=1495728510607&api=v2