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
- All the program scripts that were used for generating the results and data in this paper have been made available at https://github.com/mirabelarusu/RadPathFusionLung
- This study is described in detail in the following publication:
- 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
Data Access
| Data Type | Download all or Query/Filter | License |
|---|---|---|
| CT Images and Histology compartments mapped on CT (DICOM, 5.5 GB) |
(Download requires the NBIA Data Retriever) | |
| Annotated Whole Slide Pathology Images (TIF, 21.3 GB) | (Download and apply the IBM-Aspera-Connect plugin to your browser to retrieve this faspex package) | |
| Clinical data (XLSX, 5 kB) |
Click the Versions tab for more info about data releases.
Additional Resources for this Dataset
The NCI Cancer Research Data Commons (CRDC) provides access to additional data and a cloud-based data science infrastructure that connects data sets with analytics tools to allow users to share, integrate, analyze, and visualize cancer research data.
- Imaging Data Commons (IDC) (Imaging Data)
The following external resources have been made available by the data submitters. These are not hosted or supported by TCIA, but may be useful to researchers utilizing this collection.
- Source code is publicly available on Github at https://github.com/mirabelarusu/RadPathFusionLung
Detailed Description
Collection Statistics | Radiology Image Statistics | Pathology Image Statistics |
|---|---|---|
Modalities | CT | Pathology |
Number of Participants | 6 | 6 |
Number of Studies | 36 | 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:
- BloodVessels (derived from CT)
- Nodule (derived from CT)
- MappedFromHistologyBloodVessels
- MappedFromHistologyInvasion
- 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
- 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:
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
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
Users must abide by the TCIA Data Usage Policy and Restrictions. Attribution should include references to the following citations:
Data Citation
Madabhushi, A., & Rusu, M. (2018). Fused Radiology-Pathology Lung (Lung-Fused-CT-Pathology) (Version 1) [Data set]. The Cancer Imaging Archive. https://doi.org/10.7937/k9/tcia.2018.smt36lpn
Publication Citation
Rusu, M., Rajiah, P., Gilkeson, R., Yang, M., Donatelli, C., Thawani, R., Jacono, F. J., Linden, P., & Madabhushi, A. (2018) 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 (Vol. 27, Issue 10, pp. 4209–4217). PMCID:PMC5630490 DOI: https://doi.org/10.1007/s00330-017-4813-0
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. DOI: https://doi.org/10.1007/s10278-013-9622-7
Additional Publication Resources
The Collection authors suggest the below will give context to this dataset:
- 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
Other Publications Using This Data
TCIA maintains a list of publications which leverage our data. If you have a publication you'd like to add, please contact TCIA's Helpdesk.
Version 1 (Current) Updated 2018/07/30
| 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) | (Download and apply the IBM-Aspera-Connect plugin to your browser to retrieve this faspex package) |
| Clinical data (XLSX) |