| Atherosclerosis, the blockage
of coronary arteries, together with its clinical manifestations, accounts
for approximately 540,000 myocardial infarctions and 515,000 deaths a year
in the United States. Researchers with NSF’s Bernard M. Gordon Center
for Subsurface Sensing and Imaging Systems (Gordon-CenSSIS), an Engineering
Research Center, are developing an innovative, non-invasive technique for
detecting coronary blockages. The new imaging technique uses an algorithm
developed by W. Clem Karl of Boston University and Homer Pien at Massachusetts
General Hospital, called the Model-Based Iterative Algebraic (MBIA) reconstruction
algorithm.
The current “gold standard”
for detecting coronary blockages is coronary angiography, an invasive and
expensive procedure that has an 8% complication rate. A non-invasive
detection method, computed tomography (CT), is used for high-risk patients
but is hindered by the presence of dense lesions of calcium in the walls
of the coronary arteries. The brightness of calcium in CT images
obscures the neighboring lumen, rendering at least one coronary segment
impossible to evaluate in 50% of patients older than 65.
The new technique appears
to be more accurate than computed tomography, and appears to significantly
mitigate the effects of calcium. The non-invasive nature of the MBIA
method, coupled with its high accuracy, makes it especially promising for
high-risk patients. The figure shows a comparison of results from
conventional blockage detection and the MBIA reconstruction technique.
Further development of MBIA—including
modeling, formulation, computational, and clinical developments—will continue
during the upcoming year. The Gordon-CenSSIS ERC and Massachusetts
General Hospital have jointly filed both domestic and world patent applications,
and are jointly pursuing external funding opportunities. A successful
demonstration of the approach is expected to have a significant impact
on the assessment of coronary blockages in high-risk patients. |
