Summary

This is the first attempt of mapping the extent of Invasive Adenocarcinoma onto in vivo lung CT. The mappings constitute ground truth of disease and may be used to further investigate the imaging signatures of Invasive Adenocarcinoma in ground glass pulmonary nodules. Patient with small ground glass nodules with >2 histology slices per nodule were included. Patients with solid large nodules (>40mm), with <3 histology slices or with histology slices showing substantial artifacts were excluded from this study (see reference below for details). Data collection and analysis was provided by Case Western Reserve University. 

References



Data 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.

Data Type Download all or Query/Filter
Images (DICOM, 5.5 GB)

 

Annotated Whole Slide Pathology Images (TIF, 21.3 GB)
Clinical data (XLSX)

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Detailed Description

Collection Statistics

 Radiology Image Statistics

Pathology Image Statistics

Modalities

CT, Histology compartments mapped on CT (DICOM)

Pathology

Number of Participants

6

6

Number of Studies

6 6

Number of Series

52 N/A

Number of Images

11,210

25
Image Size (GB) 5.5 21.3

Supporting Documentation

Within the directory CT_Segmentations_and_annotations/CT_Segmentations/<ptID>/ there are five directories:

  1. BloodVessels (derived from CT)
  2. Nodule (derived from CT)
  3. MappedFromHistologyBloodVessels
  4. MappedFromHistologyInvasion
  5. MappedFromHistologyLesion

The data set is fully described in the following publications:

Rusu et al. Co-registration of pre-operative CT with ex vivo surgically excised ground glass nodules to define spatial extent of invasive adenocarcinoma on in vivo imaging: a proof-of-concept study. European Radiology (2018); PMCID:PMC5630490 DOI:10.1007/s00330-017-4813-0

Histology Data Description

There is one folder for each patient, with the same folder name as the TCIA ID. Each folder with TCIA ID name contains 2 folders:

  • “images”
    • Contains scanned histology images (in tiff format) pertinent to the TCIA ID Patient, e.g. LungFCP-01-0001_b1.tiff, LungFCP-01-0001_b2.tiff, etc
  • “annotations”
    • Contains the pathologist’s annotations, stored as tiff file with the same image size as the scanned histology files, with 0 where there is not label, and 255 where a region was annotated. It is possible to have multiple annotations for each file, e.g. for file LungFCP-01-0001\images\LungFCP-01-0001_b1.tiff the following regions are available:
      • LungFCP-01-0001_b1_annotation_00_R000G255B000.tiff
      • LungFCP-01-0001_b1_annotation_00_R255G000B000.tiff

A part of the filenames (LungFCP-01-0001_b1_annotation_00_RxxxGyyyBzzz) indicate the type of annotation:

  • Adenocarcinoma in Situ : R000G000B255, R001G000B255, R002G000B255
  • Invasive Adenocarcinoma: R000G255B000, R001G255B000, R002G255B000, R003G255B000, R004G255B000, R005G255B000, R006G255B000
  • Invasive Adenocarcinoma + Adenocarcinoma in Situ: R255G000B000

If multiple files are available for the same type of annotation, e.g. Invasive Adenocarcinoma, it indicates that the pathologists has annotated multiple regions

Description of the content of “FinalPublishedResults” folder

The folder “FinalPublishedResults” contains one folder for each patient. Within each patient folder, there are 3 subfolders: “CT”, ”Histology”, & ”Results_XX”. When expanded each patient folder  appears as depicted below.

  • LungFCP-01-0001
    • CT
    • Histology
    • Results_XX
  • LungFCP-01-0002
  • LungFCP-01-0003
  • LungFCP-01-0004
  • LungFCP-01-0005
  • LungFCP-01-0006

The folder “CT” contains the 3D CT volume saved as one mha file, the segmentation of the lesion obtained by majority voting for the three radiologist segmentations, and the segmentation of the blood vessels.

The folder “histology” has a similar content as the raw histology data, but a lower resolution, with some additional processing, e.g. applied gross rotation and flipping to correct for artifacts related to the mounting on the glass slide, and with additional annotations beside the lesion and in situ disease, e.g. blood vessels.

The folder Results contain the outcome of the registration of the histopathology images and the CT. All scripts used for generating these results are available at https://github.com/mirabelarusu/RadPathFusionLung

Please refer to the following publication for the methodological details:

Rusu M., Rajiah P., Gilkeson R., Yang M., Donatelli C., Thawani R., Jacono F.J., Linden P.,  Madabushi A. (2017) Co-registration of pre-operative CT with ex vivo surgically excised ground glass nodules to define spatial extent of invasive adenocarcinoma on in vivo imaging: a proof-of-concept study. European Radiology 27:10, 4209:4217. DOI: https://doi.org/10.1007/s00330-017-4813-0


Citations & Data Usage Policy 

Madabhushi, A., & Rusu, M. (2018). Fused Radiology-Pathology Lung Dataset. The Cancer Imaging Archive. https://doi.org/10.7937/K9/TCIA.2018.SMT36LPN


Rusu et al. Co-registration of pre-operative CT with ex vivo surgically excised ground glass nodules to define spatial extent of invasive adenocarcinoma on in vivo imaging: a proof-of-concept study. European Radiology (2018); PMCID:PMC5630490 DOI:10.1007/s00330-017-4813-0


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 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.


Version 1 (Current) Updated 07-30-2018

Data Type Download all or Query/Filter
Images (DICOM,  5.5 GB)

 

(Requires the NBIA Data Retriever .)

Annotated Whole Slide Pathology Images (TIF, 21.3 GB)
Clinical data (XLSX)