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APOLLO-5 - The Cancer Imaging Archive (TCIA)
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APOLLO-5


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The Cancer Imaging Archive

APOLLO-5 | Applied Proteogenomics OrganizationaL Learning and Outcomes

DOI: NA | Data Citation Required | Image Collection

Location Species Subjects Data Types Cancer Types Size Status Updated
Abdomen, Adrenal, Bile duct, Bladder, Brain, Breast, Chest, Chest-Abdomen-Pelvis, Colon, Endocrine, Esophagus, Gastrointestinal, Head, Head-Neck, Hip, Kidney, Liver, Leg, LSpine, Lung, , Ovary, Pancreas, Pelvis, Prostate, Rectum, Shoulder, Skin, Soft Tissue, Spinal Cord, Thymus, Thyroid, TSpine, Uterine corpus, and Whole body Human 437 MG, MR, NM, PT, CT, US, XA Breast Cancer, Bladder Urothelial Carcinoma, Cholangiocarcinoma, Colon adenocarcinoma, Cutaneous Melanoma, Endocrine Miscellaneous, Esophageal Carcinoma, Gastrointestinal Stromal Tumor, Head and Neck Squamous Cell Carcinoma, Kidney Chromophobe, Kidney Clear Cell Renal Cell Carcinoma, Kidney Renal Papillary Cell Carcinoma, Liver Hepatocellular Carcinoma, Lung Adenocarcinoma, Lung Other, Lung Squamous Cell Carcinoma, Major Salivary Gland, Mesothelioma, Miscellaneous, Neuroendocrine Tumors (all sites), Ovarian Cancer, Pancreatic adenocarcinoma, Pathologically Benign, Prostate Adenocarcinoma, Hematopoietic Cancers, Soft Tissue, Stomach Adenocarcinoma, Thymoma, Thyroid Carcinoma, Uterine Corpus Endometrial Carcinoma, Skin Cancer, Uterine Sarcoma 2.09TB Limited, Ongoing 2024/09/30

Summary

This collection contains subjects from the National Cancer Institute’s Applied Proteogenomics OrganizationaL Learning and Outcomes (APOLLO) network. The APOLLO network is a collaboration between NCI, the Department of Defense (DoD), and the Department of Veterans Affairs (VA) to incorporate proteogenomics into patient care as a way of looking beyond the genome, to the activity and expression of the proteins that the genome encodes. The emerging field of proteogenomics aims to better predict how patients will respond to therapy by screening their tumors for both genetic abnormalities and protein information, an approach that has been made possible in recent years due to advances in proteomic technology. Radiology and pathology images from APOLLO patients are being collected and made publicly available by The Cancer Imaging Archive to enable researchers to investigate cancer phenotypes that may correlate to corresponding proteomic, genomic, and clinical data.

Image data are being made available on a release schedule that is coordinated with the APOLLO program releases of proteomic and genomic data. Radiology imaging is collected from standard-of-care imaging performed on patients immediately before the pathological diagnosis, and from follow-up scans where available. For this reason, the radiology image data sets can be heterogeneous in terms of scanner modalities, manufacturers, and acquisition protocols. Pathology imaging is collected as part of the APOLLO qualification and laser capture microdissection (in some cases) workflow. Limited Access data is available only to members of the APOLLO network, and Publicly Available data may be under a limited publication embargo.

CollectionCancer TypeModalitiesSubjects

APOLLO-5-BLCA

Bladder CancerCT, MR2

APOLLO-5-BRCA

Breast CancerCT, MG, MR, NM, US72
APOLLO-5-CCRCCKidney Clear Cell Renal Cell CarcinomaCT. MR, NM, PT, US20
APOLLO-5-CHOLCholangiocarcinomaCT, MR, PT5
APOLLO-5-CMCutaneous MelanomaCT, MG, MR, NM, PT, US8
APOLLO-5-COADColon adenocarcinomaCT, MR, PT, US44
APOLLO-5-ENDOCRINE-MISCEndocrineCT, US1
APOLLO-5-ESCAEsophageal CarcinomaCT, PT3
APOLLO-5-GISTGastrointestinal Stromal TumorCT, PT, US5
APOLLO-5-HEME-OTHERHematopoietic CancersCT, PT2
APOLLO-5-HNSCCHead And Neck Squamous Cell CarcinomaCT, MR, NM, PT, US16
APOLLO-5-KICHKidney ChromophobeCT, MR2
APOLLO-5-KIRPKidney Renal Papillary Cell CarcinomaCT, MR, US5
APOLLO-5-LIHCLiver Hepatocellular CarcinomaCT, MR, NM, PT, US6
APOLLO-5-LSCCLung Squamous Cell CarcinomaCT, MR, PT48
APOLLO-5-LUADLung AdenocarcinomaCT, MR, PT69
APOLLO-5-LUNG-MISCLung OtherCT, PT6
APOLLO-5-MESOMesotheliomaCT, MR, NM, PT1
APOLLO-5-MISCMiscellaneousCT, MR, PT6
APOLLO-5-MSGMajor Salivary GlandCT, PT1
APOLLO-5-NETNeuroendocrine Tumors (all sites)CT, MR, NM, PT, US, XA21
APOLLO-5-NONCANCERPathologically BenignCT, MR, NM, PT5
APOLLO-5-OVOvarian CancerCT, MR, PT, US38
APOLLO-5-PAADPancreatic AdenocarcinomaCT, MR, PT, US6
APOLLO-5-PRADProstate AdenocarcinomaCT, PT, MR, US13
APOLLO-5-SARSoft TissueCT, MR, NM, PT, US11
APOLLO-5-SKIN-MISCSkin MiscellaneousCT, NM1
APOLLO-5-STADStomach AdenocarcinomaCT, PT1
APOLLO-5-THCAThyroid CarcinomaCT, NM, PT, US3
APOLLO-5-THYMThymomaCT, MR, PT2
APOLLO-5-UCECUterine Corpus Endometrial CarcinomaCT13
APOLLO-5-USUterine SarcomaCT, PT1

Data Access

This is a limited access data set that is currently only available to APOLLO investigators. If you are a member of this network and would like to request access, please fill out this PDF form.  Please email the completed form to the email address indicated on the form.  You will be notified with further information when it is received.

Version 1: Updated 2024/09/30

Title Data Type Format Access Points Subjects Studies Series Images License
Radiology Images MG, MR, NM, PT, CT, US, XA DICOM 437 5,369 35,067 3,873,238 TCIA Limited (contact Support)
Related Datasets
No related Analysis Results found: Submit your proposal! No related Collections found
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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:

Acknowledgement

The APOLLO Research Network require that publications using data from this program (1) cite all relevant publications and preprints describing the APOLLO data referenced in the manuscript; and (2) cite the relevant DOIs and/or study accession numbers for the data referenced in the manuscript. 

Acknowledgement

The APOLLO Research Network requests that publications using data from this program include the following statement: “Data used in this publication were generated by the Applied Proteogenomics OrganizationaL Learning and Outcomes (APOLLO) Research Network, a Federal Precision Oncology and Cancer Moonshot Program of the Department of Defense, Department of Veterans Affairs, and National Cancer Institute.”

Detailed Description

 

De-identification of DICOM dates

The resulting DICOM dates are meaningless yet preserve the relative temporal distance between studies for a patient

De-identification of dates uses the DICOM standard “Retain Longitudinal With Modified Dates Option” which allows dates to be retained as long as they are modified from the original date. Date and Date-Time fields in TCIA DICOM image headers are de-identified by normalizing to a base date of January 1, 1975 and then shifted by the number of days between the original Study Date and an “anchor date”.  The anchor date for APOLLO is the Date of Diagnosis.   The choice of ‘1975’ was arbitrary, but it allows one to ensure that the dates in de-identified DICOM files have been properly de-identified as anything not around that year would be suspect.

TCIA Study Date = 01/01/1975 + (Original Study Date – Date of Diagnosis).

For example, if the original Study Date was 03/29/2018 and the Date of Diagnosis was 03/27/2018 then the Days from Diagnosis would be +2 and the TCIA Study Date would become 01/03/1975.

This technique de-identifies the dates while preserving the longitudinal relationship between dates.  Therefore, a researcher won’t know the precise date the scan occurred, but if a follow up scan was performed 120 days later, that same 120 day difference between scans of a subject will exist in the TCIA images.  Dates that occur in DICOM tags other than Date or Date-Time fields are removed. An example of this would be a date entered into the Series Description field.  If the date is associated with a library for Code Meaning then that date is preserved as the date would be required to look up the meaning in the correct version of the library.  To show that the dates have been modified, the term “MODIFIED” is written into DICOM tag (0028,0303) “LongitudinalTemporalInformationModified”.

Original dates will be first normalized to 01 January, 1975 and then offset relative to the date of diagnosis. The CTP code for shifting the StudyDate is shown below:

<e en="T" t="00080020" n="StudyDate"> @dateinterval(StudyDate,diagnosisdate,PatientID,@NORMDATE)</e>

Insertion of computed “Days from Diagnosis” value

The inserted “Days from Diagnosis” value can be compared with similar values in the APOLLO clinical data to understand the clinical context of the imaging study

The number of days the study occurred relative to the date of diagnosis is calculated by the CTP software (using the diagnosis date in the CTP lookup table at the submission site) and automatically stored in the DICOM tag (0012,0052) Longitudinal Temporal Offset from Event with the associated tag (0012,0053) Longitudinal Temporal Event Type set to “Days from Diagnosis”. The days from diagnosis links the imaging data to the clinical data for a given subject. The CTP code for this is:

<e en="T" t="00120052" n="LongitudinalTemporalOffsetfromEvent">@always()@dateinterval(StudyDate,ddate,PatientID)</e>

<e en="T" t="00120053" n="LongitudinalTemporalEventType">@always()@param(@LTET)</e> (where LTET is defined as DIAGNOSIS)

Insertion of “Diagnosis Year”

It is important for cancer researchers to know the timeframe for which the cancer was diagnosed to relate the prescribed cancer treatment or staging to what was available at that time.

In order to relate the treatments that were available at the time of the diagnosis, the year that the primary diagnosis was made is recorded in a CTP owned group 13 private tag as follows.

<e en="T" t="00131051" n="DiagnosisYear">@always()@lookup(PatientID,diagnosisdate)</e>

In a separate stage of the pipeline the diagnosisdate is truncated to be just the year that the diagnosis was made.

<e en="T" t="00131051" n="DiagnosisYear">@truncate(DiagnosisYear,-4)</e>

The approximate StudyYear can be calculated by adding the days from diagnosis in tag LongitudinalTemporalOffsetfromEvent to the DiagnosisYear.

In order to use a normalized date function the private tags must also be de-identified at the site using a CTP script that encapsulates the TCIA Safe Private Tag Knowledge Base. With this approach, only the Safe Private Tags contained within the TCIA Private Tag Knowledge Base and encoded into the CTP script at the time the CTP script was created will be retained. If there are Private Tags that are known to be important but not part of the current Safe tags of the TCIA Private Tag Knowledge Base, then it is up to the submitting site to submit a Private Tag Dictionary of those tags to TCIA for consideration.

The normalized date workflow described above requires that diagnosis date be present and this workflow does not handle the example where there no diagnosis date is present.

Related Publications

Publications by the Dataset Authors

The authors recommended this paper as the best source of additional information about this dataset:

No publications by dataset authors were found.

Research Community Publications

TCIA maintains a list of publications that 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 TCIA’s Helpdesk.

Other Publications Using this Data

TCIA maintains a list of publications that 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 TCIA’s Helpdesk.