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Summary

This collection is a retrospective set of prostate MR studies. All studies included T2-weighted (T2W), proton density-weighted (PD-W), dynamic contrast enhanced (DCE), and diffusion-weighted (DW) imaging. The images were acquired on two different types of Siemens 3T MR scanners, the MAGNETOM Trio and Skyra. T2-weighted images were acquired using a turbo spin echo sequence and had a resolution of around 0.5 mm in plane and a slice thickness of 3.6 mm. The DCE time series was acquired using a 3-D turbo flash gradient echo sequence with a resolution of around 1.5 mm in-plane, a slice thickness of 4 mm and a temporal resolution of 3.5 s. The proton density weighted image was acquired prior to the DCE time series using the same sequence with different echo and repetition times and a different flip angle. Finally, the DWI series were acquired with a single-shot echo planar imaging sequence with a resolution of 2 mm in-plane and 3.6 mm slice thickness and with diffusion-encoding gradients in three directions. Three b-values were acquired (50, 400, and 800), and subsequently, the ADC map was calculated by the scanner software. All images were acquired without an endorectal coil.

Accessing the PROSTATEx Challenge Data Sets

The PROSTATEx Challenge ("SPIE-AAPM-NCI Prostate MR Classification Challenge”) focused on quantitative image analysis methods for the diagnostic classification of clinically significant prostate cancers and was held in conjunction with the 2017 SPIE Medical Imaging Symposium (see http://www.spie.org/PROSTATEx/).  PROSTATEx ran from November 21, 2016 to January 15, 2017.  The PROSTATEx-2 Challenge ("SPIE-AAPM-NCI Prostate MR Gleason Grade Group Challenge") is focused on the development of quantitative multi-parametric MRI biomarkers for the determination of Gleason Grade Group in prostate cancer and will be held in conjunction with the 2017 AAPM Annual Meeting (see http://www.aapm.org/GrandChallenge/PROSTATEx-2/default.asp).  PROSTATEx-2 runs from May 15, 2017 to June 23, 2017.

Acknowledgements

The prostate MR imaging was performed at the Radboud University Medical Centre (Radboudumc) in the Prostate MR Reference Center under supervision of prof. Dr. Barentsz. The Radboudumc is located in Nijmegen, The Netherlands. The dataset was collected and curated for research in computer aided diagnosis of prostate MR under supervision of Dr. Huisman, Radboudumc.

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.

Note: The following download links will download the entire collection. You can participate in PROSTATEx-2 at http://www.aapm.org/GrandChallenge/PROSTATEx-2/default.asp. You can also view historical info about the first PROSTATEx challenge in the Detailed Description section of this page.

Data TypeDownload all or Query/Filter

Download images (15.1 GB DICOM)

 

Click the Versions tab for more info about data releases.

Detailed Description

Collection Statistics

 

Modalities

MR

Number of Patients

346

Number of Studies

349

Number of Series

18,321

Number of Images

309,251

Images Size (GB)15.1

PROSTATEx-2 — SPIE-AAPM-NCI Prostate MR Gleason Grade Group Challenge (May 15, 2017 to August 3, 2017)

The American Association of Physicists in Medicine (AAPM), along with the SPIE (the international society for optics and photonics) and the National Cancer Institute (NCI), will conduct a part 2 “Grand Challenge” on the development of quantitative multi-parametric magnetic resonance imaging (MRI) biomarkers for the determination of Gleason Grade Group in prostate cancer. As part of the 2017 AAPM Annual Meeting, the PROSTATEx-2 Challenge will provide a unique opportunity for participants to compare their algorithms with those of others from academia, industry, and government in a structured, direct way using the same data sets.

A session at the 2017 AAPM Annual Meeting will focus on the PROSTATEx-2 Challenge; an individual from each of the two top-performing teams will receive a waiver of the meeting registration fee in order to present their methods during this session. Challenge participants are encouraged to submit their work for peer review to the AAPM’s scientific journal Medical Physics.

Release date of training set cases with truth: May 15, 2017
Release date of test set cases without truth: June 5, 2017
Submission date for participants’ test set Gleason Grade Group output: June 23, 2017
Challenge results released to participants: June 30, 2017
AAPM Annual Meeting: July 30 – August 3, 2017 (PROSTATEx-2 session: August 1)

To participate in PROSATEx-2 you must register at http://spiechallenges.cloudapp.net/competitions/7.

PROSTATEx Challenge (November 21, 2016 to February 16, 2017)

SPIE, along with the support of the American Association of Physicists in Medicine (AAPM) and the National Cancer Institute (NCI), conducted a “Grand Challenge” on quantitative image analysis methods for the diagnostic classification of clinically significant prostate lesions.  As part of the 2017 SPIE Medical Imaging Symposium, the PROSTATEx Challenge provided a unique opportunity for participants to compare their algorithms with those of others from academia, industry, and government in a structured, direct way using the same data sets.  For more details, go to http://www.spie.org/PROSTATEx/

  • Release date of training set cases with truth:  November 21, 2016
  • Release date of test set cases without truth:  December 12, 2016
  • Submission date for participants’ test set classification output:  January 16, 2017
  • Challenge results released to participants:  January 20, 2017
  • SPIE Medical Imaging Symposium:  February 13-16, 2017

The PROSTATEx Challenge ended in February 2017 but the training and test cohorts along with supplemental Ktrans images and lesion information can be obtained separately using the following options for download:

Data Type

Training Cohort

(204 subjects)

Test Cohort

(140 subjects)

Download images (DICOM)


Download Ktrans images (.mhd)

KTrans-Training-Files  KTrans-Training-Files

Download lesion information (.zip)

  

Download lesion reference thumbnails (.bmp)

The images come in two encodings. The acquired MR is provided in DICOM encoding. Additionally Ktrans images are provided. They come in mhd format. Ktrans is a key pharmacokinetic parameter computed from the available Dynamic contrast enhanced T1-weighted series. Each patient has one study with several DICOM images and one Ktrans image. The Ktrans image is encoded in two files ProstateX-[ProxID]-Ktrans.[mhd/zraw], where ProxID is the ProstateX patient identifier. The DICOM images comprise several Series each comprising several Instances. The DICOM files are documented in the ProstateX-Images.csv file. The columns in that file encode the following:

  • ProxID – ProstateX patient identifier.

  • Name – Series Description

  • Studydate – Study Date

  • fid – Finding ID

  • Pos – Scanner Coordinate position of the finding

  • WorldMatrix – Matrix describing image orientation and scaling

  • ijk – image col,row,slice coordinate of finding

  • ImageUID – Image Identifier

  • TopLevel

    • 0 - Series forms one image

    • 1 – A set of Series forms a 4D image (e.g. Dynamic MR)

    • NA – Series form one image, but is part of a Level 1 4D image

  • SpacingBetweenSlices – Scalar Spacing between slices

  • VoxelSpacing – Vector with x,y,z spacing scalars

  • Dim – Vector with 4D dimensions of the image

  • DCMSerDescr – The original DICOM Series Description

  • DCMSerUID – The DICOM Series UID

  • DCMSerNum – The DICOM Series Number

  • InstanceUIDList – DICOM Instances that make up this series

  • ImageUIDList – TopLevel-NA Images the make up this Toplevel 1 image

For example, to get the ADC image of Patient ProstateX-0123 do the following. After you imported the DICOM files into your environment, go to patient ProstateX-0123 and find the series with ADC in it. In this case it is ‘ep2d_diff_tra_DYNDIST_ADC’. It has SeriesNumber 8. The DICOM images in that series form the ADC image for this challenge. Image slice j at coordinate i,j contains a finding fid. See findings for more details.

Findings

The findings are documented in the ProstateX-Findings.csv table. Documentation for the columns in that table is as follows:

  • ProxID – ProstateX patient identifier

  • fid - Finding ID

  • pos - Scanner Coordinate position of the finding

  • ClinSig – Identifier available in training set that identifies whether this is a clinically significant finding. Either the biopsy GleasonScore was 7 or higher. Findings with a PIRADS score 2 were not biopsied and are not considered clinically significant. In our center the occurrence of clinically significant cancer in PIRADS 2 lesions is less than 5%.

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:

Data Citation

Geert Litjens, Oscar Debats, Jelle Barentsz, Nico Karssemeijer, and Henkjan Huisman. "ProstateX Challenge data", The Cancer Imaging Archive (2017). https://doi.org/10.7937/K9TCIA.2017.MURS5CL

Publication Citation

G. Litjens, O. Debats, J. Barentsz, N. Karssemeijer and H. Huisman. "Computer-aided detection of prostate cancer in MRI", IEEE Transactions on Medical Imaging 2014;33:1083-1092.

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. 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.


Version 1 (Current): Updated 2017/03/29

Data TypeDownload all or Query/Filter

Download images (15.1 GB DICOM)

 

 

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