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  • Fused Radiology-Pathology Prostate Dataset (Prostate Fused-MRI-Pathology)

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Summary

Excerpt

This is a fused rad-path prostate collection

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Data collection and analysis was supported by ....

collection comprises a total of 28 3 Tesla T1-weighted, T2-weighted, Diffusion weighted and Dynamic Contrast Enhanced prostate MRI along with accompanying digitized histopathology (H&Estained) images of corresponding radical prostatectomy specimens. The MRI scans also have a mapping of extent of prostate cancer on them [1]. Each surgically excised prostate specimen was originally sectioned and quartered resulting in 4 slides for each section. Each of these individual slides was digitized at 20x magnification using an Aperio slide scanner resulting in a set of 4 .svs images. Each of the 4 .svs images were then digitally stitched together to constitute a pseudo-whole mount section (.tiff) using the program in [2]. Annotations of cancer presence on the pseudo-whole mount sections were made by an expert pathologist. Slice correspondences were established between the individual T2w MRI and stitched pseudo-whole mount sections by the program in [3] and checked for accuracy by an expert pathologist and radiologist. Deformable co-registration [4] was employed to spatially co-registered the corresponding radiologic and histopathologic tissue sections to map disease extent onto the corresponding MRI scans.

Data collection and analysis was provided by Anant Madabhushi, PhD, Case Western Reserve University and Michael D. Feldman, MD, PhD, Hospital at the University of Pennsylvania.  This work was supported by NIH R01CA136535.

References

  1. Singanamalli, A. , Rusu, M. , Sparks, R. E., Shih, N. N., Ziober, A. , Wang, L. , Tomaszewski, J. , Rosen, M. , Feldman, M. and Madabhushi, A. (2016), Identifying in vivo DCE MRI markers associated with microvessel architecture and gleason grades of prostate cancer. J. Magn. Reson. Imaging, 43: 149-158. doi: 10.1002/jmri.24975 (PMID:26110513).
  2. Toth, R, Feldman, M, Yu, D, Tomaszewski, J, Madabhushi, A. “Histostitcher™: An Informatics Software Platform for Reconstructing Whole-Mount Prostate Histology using the Extensible Imaging Platform (XIP™) Framework,” Journal of Pathology Informatics, vol. 5, pg. 8, 2014 (PMID: 24843820, PMCID: PMC4023035).
  3. Xiao, G, Bloch, N, Chappelow, J, Genega, E, Rofsky, N, Lenkinsky, R, Tomaszewski, J, Feldman, M, Rosen, M, Madabhushi, A. “Determining Histology-MRI Slice Correspondences for Defining MRI-based Disease Signatures of Prostate Cancer,” Special Issue of Computerized Medical Imaging and Graphics on Whole Slide Microscopic Image Processing, vol. 35[7-8], pp. 568-78, 2011 (PMID: 21255974).
  4. Chappelow, J, Bloch, N., Rofsky, N, Genega, E, Lenkinski, R, DeWolf, W, Madabhushi, A.  “Elastic Registration of Multimodal Prostate MRI and Histology via Multi-Attribute Combined Mutual Information,” Medical Physics, vol. 38[4], pp. 2005-2018, 2011 (PMID: 21626933).

...


Localtab Group


Localtab
activetrue
titleData Access

Data

Access (Radiology)

Access 

Click the  Download button to save a ".tcia" manifest file to your computer, which you must open with the NBIA Data Retriever . Click the Search button to open our Data Portal, where you can browse the data collection and/or download a subset of its contents 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 option.

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

Annotated Whole Slide Pathology Images (76.8 GB)

Fused Rad-Path Matlab Files

Please note that Box has a 15GB download limit, so you will need to download images in batches.

Click the Versions tab for more info about data releases.

Data Access (Pathology)

 Browse the table below to view reconstructed, annotated whole slide pathology as well as fused Rad-Path matlab objects.

https://pathology.cancerimagingarchive.net/pathdata/

 

 


the following publications:

 

  1. Singanamalli, A. , Rusu, M. , Sparks, R. E., Shih, N. N., Ziober, A. , Wang, L. , Tomaszewski, J. , Rosen, M. , Feldman, M. and Madabhushi, A. (2016), Identifying in vivo DCE MRI markers associated with microvessel architecture and gleason grades of prostate cancer. J. Magn. Reson. Imaging, 43: 149-158. doi: 10.1002/jmri.24975 (PMID:26110513).
  2. Toth, R, Feldman, M, Yu, D, Tomaszewski, J, Madabhushi, A, “Histostitcher™: An Informatics Software Platform for Reconstructing Whole-Mount Prostate Histology using the Extensible Imaging Platform (XIP™) Framework,” Journal of Pathology Informatics, vol. 5, pg. 8, 2014 (PMID: 24843820, PMCID: PMC4023035).
  3. Xiao, G, Bloch, N, Chappelow, J, Genega, E, Rofsky, N, Lenkinsky, R, Tomaszewski, J, Feldman, M, Rosen, M, Madabhushi, A, “Determining Histology-MRI Slice Correspondences for Defining MRI-based Disease Signatures of Prostate Cancer,” Special Issue of Computerized Medical Imaging and Graphics on Whole Slide Microscopic Image Processing, vol. 35[7-8], pp. 568-78, 2011 (PMID: 21255974).
  4. Chappelow, J, Bloch, N., Rofsky, N, Genega, E, Lenkinski, R, DeWolf, W, Madabhushi, A,   “Elastic Registration of Multimodal Prostate MRI and Histology via Multi-Attribute Combined Mutual Information,” Medical Physics, vol. 38[4], pp. 2005-2018, 2011 (PMID: 21626933).

Pathology and Matlab Data

Reconstructed, annotated whole slide pathology as well as fused Rad-Path matlab objects are also available at https://pathology.cancerimagingarchive.net/pathdata/.

1

 

Localtab
titleDetailed Description

Detailed Description

Collection Statistics

 

Radiology Image Statistics

Pathology Image Statistics

Modalities

MRI

Pathology,
Path,
Matlab

Number of

Patients

Participants

28

 
16

Number of Studies

 

29

N/A

Number of Series

 
325N/A

Number of Images

 

32,508

114
Image Size (GB)
 
4.476.8

Supporting Documentation

The dataset data set is most fully described in detail in

 

Info
titleReferences


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:

Public collection license
Info
titleData Citation

Madabhushi, A., & Feldman, M. (2016). Fused Radiology-Pathology Prostate Dataset . The Cancer Imaging Archive. doi; 10.7937/K9/TCIA.2016.TLPMR1AM


Info
titlePublication Citation
  1. Singanamalli, A. , Rusu, M. , Sparks, R. E., Shih, N. N., Ziober, A. , Wang, L. , Tomaszewski, J. , Rosen, M. , Feldman, M. and Madabhushi, A. (2016), Identifying in vivo DCE MRI markers associated with microvessel architecture and gleason grades of prostate cancer. J. Magn. Reson. Imaging, 43: 149-158. doi: 10.1002/jmri.24975 
Info
titlePublication Citation
  1. (PMID:26110513).
  2. Toth, R, Feldman, M, Yu, D, Tomaszewski, J, Madabhushi, A, “Histostitcher™: An Informatics Software Platform for Reconstructing Whole-Mount Prostate Histology using the Extensible Imaging Platform (XIP™) Framework,” Journal of Pathology Informatics, vol. 5, pg. 8, 2014 (PMID: 24843820, PMCID: PMC4023035).
  3. Xiao, G, Bloch, N, Chappelow, J, Genega, E, Rofsky, N, Lenkinsky, R, Tomaszewski, J, Feldman, M, Rosen, M, Madabhushi, A, “Determining Histology-MRI Slice Correspondences for Defining MRI-based Disease Signatures of Prostate Cancer,” Special Issue of Computerized Medical Imaging and Graphics on Whole Slide Microscopic Image Processing, vol. 35[7-8], pp. 568-78, 2011 (PMID: 21255974). https://doi.org/10.1016/j.compmedimag.2010.12.003
  4. Chappelow, J, Bloch, N., Rofsky, N, Genega, E, Lenkinski, R, DeWolf, W, Madabhushi, A,   “Elastic Registration of Multimodal Prostate MRI and Histology via Multi-Attribute Combined Mutual Information,” Medical Physics, vol. 38[4], pp. 2005-2018, 2011 (PMID: 21626933).
 


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. 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 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 the TCIA Helpdesk.



Localtab
titleVersions

Version 1 (Current) Updated 11-30-2016

Data TypeDownload all or Query/Filter
Images (DICOM, 4.4 GB)
Annotated Whole Slide Pathology Images (76.8 GB)

Image Added    Image Added                   

Fused Rad-Path MATLAB Files