Submillimetric COVID-19 CT dataset

PaoloZaffino · February 16, 2021, 10:23am

Hi all,
I apologize if I’m posting in the wrong section (if so please remove/move this post).

We just released a free (non commercial use) dataset made of 62 submillimetric CT scans of COVID-19 positive patients.
Automatic lung tissue labeling and human-based clinical score are provided as well.
Maybe in this difficult historical period, this dataset can be useful for your research.

Here the article:

My 2 cents.

Paolo

Justin · February 19, 2021, 2:59pm

Dear Paolo,

That is great, thanks for your contribution.

Are there other clinical data such as survival outcomes, ICU admission or other (anonymized) data available as well?

Best,
Justin

rbumm · February 19, 2021, 7:39pm

Hi Paolo,

Thank you, this looks like an amazing source.

We recently developed a Lung CT Analyzer extension for 3D Slicer for COVID-19 assessments. It can be installed within Slicer from the extension manager.

The sources can be pull from here: GitHub - rbumm/SlicerLungCTAnalyzer: This is a 3D Slicer extension for segmentation and spatial reconstruction of infiltrated, collapsed, and emphysematous areas in chest CT examinations.

We will definitely check out your data, comments and ideas for the extension are always welcome !

Best regards

Rudolf Bumm, Chur, Switzerland

PaoloZaffino · February 22, 2021, 11:12am

Thanks @Justin !
We are trying to retrive these data, but I can not promise anything.

@rbumm I saw your extension…that’s really great!
The aim of our paper was to release high quality images (on internet a lot of people published png-like images…) alongside with some clinical data and a way to automatically get some labels from CTs.
Let me know if I can provide additional information (as already said we are trying to retrive additional clinical information).

Best,
Paolo

rbumm · February 22, 2021, 2:37pm

I would be very interested in how the community could help to enlarge the dataset.

PaoloZaffino · August 30, 2021, 8:46pm

@lassoan @jcfr do you think it would be interesting for the community to have an extension that, given a chest CT, automatically labels lungs tissues on basis of the intensity (healthy, ground-glass opacities, and consolidation)?
It can be used for pneumonia (COVID too).
The methodology is explained in the paper linked in the first post (it’s a GMM strategy basically).

We could call it “Lung density segmentation”.

lassoan · August 30, 2021, 11:47pm

Yes, sure, I expect that this would be useful. If you don’t want to create an entire new extension for this then it could be added to the LungCTAnalyzer or ChestImagingPlatform extensions.

rbumm · August 31, 2021, 8:47pm

This sounds interesting, the LungCTAnalyzer does that to some extent, and it would be great if you could add ideas or add functionality yourself.

PaoloZaffino · September 1, 2021, 9:15am

I submitted a pull request.

rbumm · September 7, 2021, 10:05am

I added a python script

github.com

rbumm/SlicerLungCTAnalyzer/blob/master/PythonScripts/processAllCTInDir.py

# Windows: Open slicer and enter the command to call this script (me) 
# exec(open(r"C:\Users\Yourname\Documents\MySlicerExtensions\LungCTAnalyzer\PythonScripts\processAllCTInDir.py").read())


"""
      ProcessAllCtInDir
      
      Purpose: 
      Run this script to search a directory for CT data sets according the 
      data structure suggested by @PaoloZaffino,   
      automatically run LungCTAnalyzer on them and save the results.
      
      Prerequisites:
      - Each CT data set needs to be placed in a subdirectory "Pat x" where x is an integer
      - input volumes need to be present in each dir and named as follows: 
              "CT.nrrd", "CT_followup.nrrd", "CT_followup2.nrrd", "CT_followup3.nrrd" 
      - lung masks need to be prepated in each dir with LungCTSegmenter and named:                                                                            
             "LungMasksCT.seg.nrrd","LungMasksCTFollowup.seg.nrrd","LungMasksCTFollowup2.seg.nrrd","LungMasksCTFollowup3.seg.nrrd"
      - Up to three follow up CT's are supported
      - results will be saved as CSV to "results.csv"

This file has been truncated. show original

on the LungCTAnalyzer GitHub that allows analyzing all of your 62 datasets in a row in ~60 minutes (gaming laptop).

As a prerequisite, lung masks have to be prepared once for every CT.

rbumm · September 7, 2021, 11:40am

My results of the initial CT’s of all 50 cases are summarized in this google spreadsheet:

Thresholds:
logic.setDefaultThresholds(-1050,-990,-650,-400,0,3000)

Without knowing any clinical details on the patients, LTCA predicts a severe clinical course (20-50% affected lung) in

D:/Patients5\45\CT.nrrd
D:/Patients5\46\CT.nrrd
D:/Patients5\7\CT.nrrd
D:/Patients\35\CT.nrrd
D:/Patients\33\CT.nrrd
D:/Patients\15\CT.nrrd
D:/Patients5\47\CT.nrrd
D:/Patients\40\CT.nrrd
D:/Patients\37\CT.nrrd
D:/Patients\3\CT.nrrd
D:/Patients\4\CT.nrrd
D:/Patients\12\CT.nrrd
D:/Patients\29\CT.nrrd

and a fatal one (> 50 % affected lung) in

D:/Patients\10\CT.nrrd
D:/Patients\14\CT.nrrd

PaoloZaffino · September 15, 2021, 12:31pm

Dear all,
today I updated our COVID-19 database.
Now it is made of 81 patients (in total 93 CTs since some patients have follow-up scan) and information about intensive care unit were added as well.

@rbumm @Justin

HTH,
Paolo.

rbumm · September 20, 2021, 12:38pm

Very interesting @PaoloZaffino - would it be possible to add mortality data too?
Thank you
Best regards
Rudolf

PaoloZaffino · September 20, 2021, 2:51pm

Not easy to get, but I’ll do my best.

Paolo