Mayo Clinic, IBM Improving Aneurysm Detection

 
 
By Roy Mark  |  Posted 2010-01-28 Email Print this article Print
 
 
 
 
 
 
 

Combining advanced analytics technology developed by the Mayo Clinic and IBM's WebSphere Process Server to model and orchestrate the automated workflow, aneurysm detection is dramatically improving.

Using Mayo Clinic analytics technology with collaboration from IBM's Medical Imaging Informatics Innovation Center has proven a 95 percent accuracy rate in detecting aneurysms, compared with 70 percent for manual interpretation. The project has examined more than 15 million images from thousands of patients since the project began in early July. 

Traditionally, a patient suspected of having a brain aneurysm would undergo an invasive test using a catheter that injects dye into the body, a technique with risks of neurologic complications. To improve the process of detection using non-invasive magnetic resonance angiography imaging technology, Mayo Clinic and IBM worked to create so-called "automatic reads" that run detection algorithms immediately following a scan.

Once images are acquired, they are automatically routed to servers in the Mayo and IBM Medical Imaging Informatics Innovation Center located on the Mayo campus in Rochester, Minn. There, algorithms align and analyze images to locate and mark potential aneurysms -- even very small ones less than 5mm -- so specially trained radiologists can conduct a further and final analysis.

From the time an image is taken to the time it is ready to be read by a radiologist, there often is only a 10-minute window. In that brief time frame, the new workflow is able to identify images coming off the scanners and route those related to the head and brain through the special workflow, which then conducts automated aneurysm detection.

On average, this can be done in 3-5 minutes, improving efficiency and saving valuable radiologist's time, leading to a quicker diagnosis which is especially important in the case of a serious aneurysm.

The aneurysm detection system uses an algorithm developed by Mayo researchers that is executed on IBM WebSphere Process Server to model and orchestrate the automated workflow. Images are stored on IBM DB2 for Linux and Windows data service and workflow logic is run on IBM System x servers and IBM storage.

"Our joint work with Mayo Clinic on this project taps IBM's deep expertise in high performance computing and applies it to health analytics, enabling us to remove some of the time and efficiency barriers and making imaging an even more valuable preventative screening tool," Bill Rapp, IBM's CTO of Healthcare and Life Sciences and co-director of the Medical Imaging Informatics Innovation Center, said in a statement. "Enabling broad access to this capability via cloud delivery is the natural next step."

 
 
 
 
 
 
 
 
 
 
 

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