One of use cases would be developing machine learning algorithm analyzing X-ray, CT or MRI using radiology extension model.
I started to take the Neurohacking course in Coursera on every Saturday.
I plan to convert the sample data of this course into radiology CDM and apply the analysis on CDM, which I learn in the course.
Hi,
can you please clarify:
are we talking about CDM modification allowing us to put there images and reports
or
are we talking about the
@Dymshyts
I’m not sure that I understand correctly,
But what @SiHyung_No suggested is that storing path for the images and its informations, not image itself.
Image reports can be stored in the Note table after slight modification.
I’m sorry for the incomplete message posting, but you answered exactly what I wanted to know:)
Thanks
@yoon8302 had finished extracting waveform signals from ECG reports in PDF form . The new DB named ECG-ViEW III consists of 1 M of ECG reports and all the clinical information (demographic, condition, drug, selected measurement) in OMOP-CDM format. He will submit a manuscript on it soon. The DB will be opened to any researcher after acceptance of the manuscript. He also made a prototype of CDM extension model to contain the bio-signal waveform data.
Sorry for this TOO late reply. Extension models for radiology and bio-signals will be different each other. @yoon8302 will try to make a prototype for bio-signal CDM extension model, and he may want to submit it to our community.
Owing to the effort of @SiHyung_No , @mediblue , @NEONKID, the first sample data for radiology extension model is released.
This sample is consists of two tables
- Radiology_Occurrence: each row represents one radiologic procedure
- Radiology_Image: each row represents one image among the images from single radiologic procedure.
Samples:
Radiology_Ocurrence
Radiology_Image
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Friends:
As you model this out don’t forget we need to have normalized information as concepts in the concept table. If Dicom has it all, bring it on. If not, pick from SNOMED or so. If nothing helps propose a new controlled vocabulary.
We’re now figuring out which concepts we need to standardize. I’ve already picked RadLex ontology system from LOINC within OMOP concepts for standardized radiology procedure.
Definitely, we need to normalize all this information after completing the pilot model. Thank you for reminding again! 
@SCYou Thanks for leading this work. How do you do so much?
It would provide the basis of a lot of important research if the concepts required for DICOM CT Radiation Dose Structured Reports (RDSRs) were among the concepts you standardized. Here in the US, an estimated 3-5% of incident cancers are attributable to medical radiation and there is ample evidence that CT dosing is frequently too high relative to benchmarks and that there is very high unwarranted variability in CT dosing. Capturing the required data elements for RDSRs would allow the OHDSI community to document and address these important aspects of CT use. Having contributed to some of this research I am interested in being able to continue it with OHDSI partners…
These mature open source toolkits for getting data from DICOM (which uses RadLex) are designed to pull the elements for RDSRs among other useful tasks. PixelMed toolkit: http://www.pixelmed.com/dicomtoolkit.html and GROK: http://dose-grok.sourceforge.net/
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Thank you for providing such a precious information, @Andrew
Columns for radiation dosage and the unit exist without details in the pilot radiology extension model above. In order to standardize dosage and the units according to the various modality further, RDSR will be very helpful. Thank you again.
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I am curious to find out the status of this, is there any more recent work on Radiology_CDM? I am interested trying to deploy your current model and code on some test image data at my site, and possibly make extensions to it to fill gaps for our use cases for enabling image dataset discovery for multi-site collaboration in a federated learning setting without sharing data.
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Welcome back,@dlrubin It’s really exciting!
We’re now focusing on semantics of R-CDM, and trying to adopt RadLex LOINC as the standardized vocabulary for the radiology process.
It would be great if we work together on the use case for this. 
good idea.
Wonkwang University Hospital will be with you.
We can work this through together and release it on Athena eventually.
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Hi I know it has been a while since the last post, but I think this thread is the closest to what I am working on. I am a physicist in radiation oncology and am working on expanding the CDM to include radiation oncology specific data. In some ways radiation oncology is analogous to radiology, we too have MR and CT images. But we also have 3D dose distributions and target and normal tissue contours, and dose prescriptions. What would be a good place to start for building out the CDM to include the additional data? I’d love to join a group and start working on that.
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Hi! As I can see, it has been a while since the last time you had a discussion here. However, I would like to open this thread again. My name is Bea and I am currently working with the two tables from the radiology extension model (radiology_occurrence and radiology_image). After getting some materials to work with them I realised that the last version I could find date from 29th May 2019. I just wanted to ask if after this date it has been any other releases or if I am good to keep working with this last available version. If new updates have been done, would you mind to share some links here with the new information, please? I would really appreciate this help.
Thanks in advance! Looking forward to receive your reply!
Bea
Hi,
looks like this thread has not been active for a while. I’m starting an OMOP CDM implementation in our hospital and am particularly interested in integrating findings from Nuclear Medicine and Radiation Oncology.
Are there any other members actually active in this area ?
cheers
Thomas
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