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Summary

Excerpt

Put Collection Abstract here.  If it's really long ask them to help you break it up such that the most important summary stuff is here and the rest goes in the Detailed Description tab.

Acknowledgements

We would like to acknowledge the individuals and institutions that have provided data for this collection:

...

Hospital/Institution Name city, state, country - Special thanks to First Last Names, degree PhD, MD, etc from the Department of xxxxxx, Additional Names from same location.

...

This dataset contains image annotations derived from the NCI Clinical Trial "Radiation Therapy, Amifostine, and Chemotherapy in Treating Young Patients With Newly Diagnosed Nasopharyngeal Cancer (ARAR0331)”.  This dataset was generated as part of an NCI project to augment TCIA datasets with annotations that will improve their value for cancer researchers and AI developers.

Annotation Protocol

For each patient, all scans were reviewed to identify and annotate the clinically relevant time points and sequences/series. In a typical patient all available time points were annotated. The following annotation rules were followed:

  1. PERCIST criteria was followed for PET imaging. Specifically, the lesions estimated to have the most elevated SUVmax were annotated.
  2. RECIST 1.1 was otherwise generally followed for MR and CT imaging. A maximum of 5 lesions were annotated per patient scan (timepoint); no more than 2 per organ. The same 5 lesions were annotated at each time point. Lymph nodes were annotated if >1.5 cm in short axis. Other lesions were annotated if >1 cm. 
  3. Three-dimensional segmentations of lesions were created in the axial plane. If no axial plane was available, lesions were annotated in the coronal plane.
  4. MRIs were annotated using the T1-weighted axial post contrast sequence.
  5. Some lesions may cross multiple exams (ie. an MRI of the head and an MRI of the neck). The images portions on each exam were then annotated. If, however, the complete lesion was visualized on either a neck or head exam, then the other exam was not annotated to avoid redundancy.
  6. Lesions were labeled separately.
  7. The volume of each annotated lesion was calculated and reported in cubic centimeters [cc] in the Annotation Metadata CSV.
  8. A “negative” annotation was created for any exam without findings.

At each time point:

  1. A seed point (kernel) was created for each segmented structure. The seed points for each segmentation are provided in a separate DICOM RTSTRUCT file.
  2. SNOMED-CT “Anatomic Region Sequence” and “Segmented Property Category Code Sequence” and codes were inserted for all segmented structures.
  3. “Tracking ID” and “Tracking UID” tags were inserted for each segmented structure to enable longitudinal lesion tracking.
  4. Imaging time point codes were inserted to help identify each annotation in the context of the clinical trial assessment protocol.
    1. “Clinical Trial Time Point ID” was used to encode time point type using one of the following strings as applicable: “pre-dose” or “post-chemotherapy”.
    2. Content Item in “Acquisition Context Sequence” was added containing "Time Point Type" using Concept Code Sequence (0040,A168) selected from:
      1. (255235001, SCT, “Pre-dose”)
      2. (262502001, SCT, "Post-chemotherapy")

Important supplementary information and sample code

  1. A spreadsheet containing key details about the annotations is available in the Data Access section below.
  2. A Jupyter notebook demonstrating how to use the NBIA Data Retriever Command-Line Interface application and the REST API to access these data can be found in the Additional Resources section below.


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titleData Access

Data Access

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(Download requires NBIA Data Retriever)

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activetrue
titleData Access

Data Access

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General restricted license access

Note to curators! Only use the appropriate macro for your collection above, or the text below in the case of NCTN trials.  It will need to be tailored with the correct NCT#.

This is a limited access data set. To request access please register an account on the NCTN Data Archive.  After logging in, use the "Request Data" link in the left side menu.  Follow the on screen instructions, and enter NCT00352534 when asked which trial you want to request.  In step 2 of the Create Request form, be sure to select “Imaging Data Requested”. Please contact NCINCTNDataArchive@mail.nih.gov for any questions about access requests.

Data TypeDownload all or Query/FilterLicense
Images, Segmentations, and Radiation Therapy Structures/Doses/Plans

ARAR0331 Annotations - Segmentations, Seed Points, and Negative Findings Assessments  (DICOM,

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0.

X

03 GB)

<< latter two items only if DICOM SEG/RTSTRUCT/RTDOSE/PLAN exist >>



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labelSearch
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urlhttps://wiki.cancerimagingarchive.net/download/attachments/163873624/ARAR0331_Tumor-Annotations-manifest_11-13-2023.tcia?api=v2
Tissue Slide Images (SVS, XX.X GB)



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labelSearch
urlhttps://nbia.cancerimagingarchive.net/nbia-search/?ImageModalityCriteria=RTSTRUCT&MinNumberOfStudiesCriteria=1&CollectionCriteria=ARAR0331&ThirdPartyCriteria=YES



(Download requires

Aspera plugin

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Clinical data (CSV


ARAR0331 Annotation Metadata (CSV, 830 KB)


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urlhttps://wiki.cancerimagingarchive.net/download/attachments/163873624/Metadata_Report_ARAR0331_2023_11_13.csv?api=v2



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Click the Versions tab for more info about data releases.

Additional Resources for this Dataset

Note to curators! Use this any time you are linking to NCI's IDC/GDC/PDC resources.  The links below are examples and will need to be tailored to point to the specific dataset (see parameters in URLS).

Nci_crdc additional resources

Note to curators! The link below is an example for NCTN trials and will need to be tailored to the proper URL for the corresponding data on the NCTN Data Archive.

Nctn additional resources

Note to curators! Below are examples for what to do with other external resources/links that don't fit into the above categories.

The following external resources have been made available by the data submitters.  These are not hosted or supported by TCIA, but may be useful to researchers utilizing this collection.

  • Software / Code on Github
  • Genomics data in DbGAP
  • Genomics data in Gene Expression Omnibus

Third Party Analyses of this Dataset

TCIA encourages the community to publish your analyses of our datasets. Below is a list of such third party analyses published using this Collection:

  • <add links to TCIA Analysis Result DOIs here>


Collections Used in this Third Party Analyses 

Below is a list of the Collections used in these analyses:

Source Data TypeDownloadLicense
Original ARAR0331 Images used to create Segmentations and Seed Points (DICOM, 11 GB)


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urlhttps://wiki.cancerimagingarchive.net/download/attachments/163873624/ARAR0331_SourceImages-SEGSandSeedpoints-manifest_11-13-2023.tcia?api=v2


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Original ARAR0331 Images used to create Negative Assessment reports (DICOM, 20.5 GB)


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urlhttps://wiki.cancerimagingarchive.net/download/attachments/163873624/ARAR0331_SourceImages-NegativeAssessments-manifest_11-13-2023.tcia?api=v2


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Localtab
titleDetailed Description

Detailed Description

Image Statistics

Radiology Image StatisticsPathology Image Statistics

Modalities

RTSTRUCTModalities

Number of Patients

108

Number of Studies

594

Number of Series

2193

Number of Images

2193

Images Size (GB)
<< Add any additional information that didn't fit or belong in the Summary section. >>
0.03



Localtab
titleCitations & Data Usage Policy

Citations & Data Usage Policy

Tcia limited license policy

Info
titleData Citation

DOI goes here. Create using Datacite with information from Collection Approval form

Info
titlePublication Citation

We ask on the proposal form if they have ONE traditional publication they'd like users to cite.

Info
titleAcknowledgement

Required acknowledgements only (ex:The CPTAC program requests that publications using data from this program...). If they just want to thank someone, that goes in the Acknowledgement section underneath the Summary.Rozenfeld, M., & Jordan, P. (2023). Annotations for Radiation Therapy, Amifostine, and Chemotherapy in Treating Young Patients With Newly Diagnosed Nasopharyngeal Cancer Collection (ARAR0331-Tumor-Annotations) (Version 1) [Data set]. The Cancer Imaging Archive. https://doi.org/10.25737/H65S-8F58

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 (Vol. 26, Issue 6, pp. 1045–1057). Springer Science and Business Media LLC.https://doi.org/10.1007/s10278-013-9622-7

Other Publications Using This Data

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


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titleVersions

Version

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1 (Current): Updated

yyyy

2023/

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dd

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Data TypeDownload all or Query/FilterLicense
Images, Segmentations, and Radiation Therapy Structures/Doses/Plans

ARAR0331 Annotations - Segmentations, Seed Points, and Negative Findings Assessments  (DICOM,

XX

0.

X

03 GB)

<< latter two items only if DICOM SEG/RTSTRUCT/RTDOSE/PLAN exist >>



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urlhttps://wiki.cancerimagingarchive.net/download/attachments/163873624/ARAR0331_Tumor-Annotations-manifest_11-13-2023.tcia?api=v2
tcia-button-generator



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labelSearch
urlhttps://nbia.cancerimagingarchive.net/nbia-search/?ImageModalityCriteria=RTSTRUCT&MinNumberOfStudiesCriteria=1&CollectionCriteria=ARAR0331&ThirdPartyCriteria=YES



(Download

requires the 

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ARAR0331 Annotation Metadata (CSV, 830 KB)


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restricted
button-
license

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Tissue Slide Images (SVS, XX.X
generator
urlhttps://wiki.cancerimagingarchive.net/download/attachments/163873624/Metadata_Report_ARAR0331_2023_11_13.csv?api=v2



Tcia cc by 4


Original ARAR0331 Images used to create Segmentations and Seed Points (DICOM, 11 GB)


Tcia button generator
Tcia button generator
labelSearch
urlhttps://wiki.cancerimagingarchive.net/download/attachments/163873624/ARAR0331_SourceImages-SEGSandSeedpoints-manifest_11-13-2023.tcia?api=v2


(Download requires NBIA Data Retriever)

Tcia cc by 4

Tcia restricted license

nctn_with_collab-license-only

Nctn_no_collab license only

Clinical data (CSV
Original ARAR0331 Images used to create Negative Assessment reports (DICOM, 20.5 GB)


Tcia button generator

Tcia cc by 4

Tcia restricted license

nctn_with_collab-license-only
urlhttps://wiki.cancerimagingarchive.net/download/attachments/163873624/ARAR0331_SourceImages-NegativeAssessments-manifest_11-13-2023.tcia?api=v2


(Download requires NBIA Data Retriever)

Nctn_no_collab license only

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