This is a dataset with multiparametric prostate MRI applied in a test-retest setting, allowing to evaluate repeatability of the MRI-based measurements in the prostate. There is very limited data about the repeatability in mpMRI of the prostate, while such information is critical for establishing technical characteristics of mpMRI as imaging biomarker of prostate cancer. Data was provided by the Brigham and Women's Hospital team. Data collection was supported by U01 CA151261 (PI Fiona Fennessy). Preparation of data for public sharing was supported by U24 CA180918 (http://qiicr.org) (MPI Andrey Fedorov and Ron Kikinis).
This is a dataset with multiparametric prostate MRI applied in a test-retest setting, allowing to evaluate repeatability of the MRI-based measurements in the prostate. There is very limited data about the repeatability in mpMRI of the prostate, while such information is critical for establishing technical characteristics of mpMRI as imaging biomarker of prostate cancer.
Data was provided by the Brigham and Women's Hospital team. Data collection was supported by U01 CA151261 (PI Fiona Fennessy). Preparation of data for public sharing was supported by U24 CA180918 (http://qiicr.org) (MPI Andrey Fedorov and Ron Kikinis).
Type of cancer: Confirmed or suspected prostate cancer
Acquisition Protocol: Standard prostate mpMRI protocol implemented at Brigham and Women's Hospital was used in this study. For a given patient, we aimed to maintain similar protocol settings, and used the same scanner hardware and software configurations for both the baseline and repeat examinations, which were acquired within 2 weeks of time. Due to the scanner hardware upgrade in the middle of the study, 6 of the patients had baseline and repeat study performed on a GE Signa HDxt platform, software release 15.0_M4A_097.a, while the remaining 7 patients were scanned on a GE Discovery MR750w, software release DV24.0_R01_1344 (General Electric Healthcare, Milwaukee, WI). Transrectal coil within an air-filled balloon (Medrad Inc., Warrendale, PA) was used in all imaging studies. mpMRI protocol included T2-weighted, Diffusion Weighted (DW) (b-values of 0 and 1400 mm/s2) and Dynamic Contrast Enhanced (DCE) sequences. Detailed acquisition parameters are listed in Table 1 of . DWI Apparent Diffusion Coefficient (ADC) and DCE subtract maps (further referred to as SUB; computed as the difference between the phase corresponding to the contrast bolus arrival and the baseline phase) were generated using the scanner software.
The imaging data is accompanied by the following types of derived data:
- manual segmentations of the total prostate gland, peripheral zone of the prostate gland, suspected tumor and normal regions (where applicable). Segmentations were done by a radiologist with the expertise in prostate MRI
- volume measurements (for axial T2w images and ADC images) and mean ADC (for ADC images) corresponding to the segmented regions.
Both segmentations and segmentation-based measurements are stored as DICOM objects (DICOM Segmentation images and DICOM Structured Reports that follow DICOM SR TID 1500). For the details about data representation and tools available to convert and visualize the data see .
In the future we plan to augment this dataset with the additional MRI series (specifically, DCE and DWI), parametric maps obtained using that analysis (in DICOM), and potentially (pending IRB clearance) clinical data (demographics, PSA), pathology sampling data (biopsy Gleason score) and results of PI-RADS interpretation.
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.
This is a limited access data set. To request access, please contact firstname.lastname@example.org. Once access is granted, you can view and download these images on The Cancer Imaging Archive (TCIA) by logging in and selecting the QIN-Prostate-Repeatability collection.
Click the Versions tab for more info about data releases.
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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 email@example.com.
Please be sure to include the following citations in your work and acknowledge the award that supported collection and sharing of these data sets (U01 CA151261, PI Fiona Fennessy) if you use this data set:
Fedorov, A; Schwier, M; Clunie, D; Herz, C; Pieper, S; Kikinis, R; Tempany, C; Fennessy, F. (2018). Data From QIN-PROSTATE-Repeatability. The Cancer Imaging Archive. https://doi.org/10.7937/K9/TCIA.2018.MR1CKGND
Fedorov A, Vangel MG, Tempany CM, Fennessy FM. Multiparametric Magnetic Resonance Imaging of the Prostate: Repeatability of Volume and Apparent Diffusion Coefficient Quantification. Investigative Radiology. 52, 538–546 (2017). http://dx.doi.org/10.1097/RLI.0000000000000382
Fedorov A, Schwier M, Clunie D, Herz C, Pieper S, Kikinis R, Tempany C, Fennessy F. An annotated test-retest collection of prostate multiparametric MRI. Nature Scientific Data (2018) (in press)
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
Schwier M, van Griethuysen J, Vangel MG, Pieper S, Peled S, Tempany CM, Aerts HJ, Kikinis R, Fennessy FM, Fedorov A. Repeatability of Multiparametric Prostate MRI Radiomics Features. arXiv [cs.CV] (2018). at http://arxiv.org/abs/1807.06089.
Peled S, Vangel MG, Kikinis R, Tempany CM, Fennessy FM, Fedorov A. Selection of Fitting Model and Arterial Input Function for Repeatability in Dynamic Contrast-Enhanced Prostate MRI. Academic Radiology (2018) (in press).
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