Cynthia H. McCollough

A correlated noise reduction algorithm for dual-energy digital subtraction angiography.

It has long been recognized that the problems of motion artifacts in conventional time subtraction digital subtraction angiography (DSA) may be overcome using energy subtraction techniques. Of the variety of energy subtraction techniques investigated, non-k-edge dual-energy subtraction offers the best signal-to-noise ratio (SNR). However, this technique achieves only 55% of the temporal DSA SNR. Noise reduction techniques that average the noisier high-energy image produce various degrees of noise improvement while minimally affecting iodine contrast and resolution. A more significant improvement in dual-energy DSA iodine SNR, however, results when the correlated noise that exists in material specific images is appropriately cancelled. The correlated noise reduction (CNR) algorithm presented here follows directly from the dual-energy computed tomography work of Kalender who made explicit use of noise correlations in material specific images to reduce noise. The results are identical to those achieved using a linear version of the two-stage filtering process described by Macovski in which the selective image is filtered to reduce high-frequency noise and added to a weighted, high SNR, nonselective image which has been processed with a high-frequency bandpass filter. The dual-energy DSA CNR algorithm presented here combines selective tissue and iodine images to produce a significant increase in the iodine SNR while fully preserving iodine spatial resolution. Theoretical calculations predict a factor of 2-4 improvement in SNR compared to conventional dual-energy images. The improvement factor achieved is dependent upon the x-ray beam spectra and the size of blurring kernel used in the algorithm.(ABSTRACT TRUNCATED AT 250 WORDS)

Densitometric assessment of regional left ventricular systolic function during graded ischemia in the dog by use of dual-energy digital subtraction ventriculography

Densitometric analysis of images obtained by digital subtraction angiography (DSA) allows for more reproducible and less operator-dependent quantitation of ventricular function. Conventional DSA uses temporal subtraction but is limited by misregistration artifacts. Dual-energy digital subtraction angiography (DE-DSA) is immune to such misregistration artifacts. The ability of DE-DSA to quantitate changes in regional ventricular volume resulting from ischemia was tested. Densitometric analysis of both phase-matched and ejection fraction DE-DSA images was used to quantitate regional left ventricular systolic function during four levels of ischemia ranging from mild to severe in open-chest dogs (n = 10). DE-DSA left ventriculograms were obtained by means of central venous injections of iodinated contrast medium. Ischemia was graded according to percentage of systolic wall thickening as measured by sonomicrometry. Phase-matched end-systolic images were obtained at each of four levels of ischemia by subtracting an end-systolic control image from each end-systolic ischemic image. Ejection fraction images were obtained at the control level and at each level of ischemia by subtracting an end-systolic image from an end-diastolic image of the same cardiac cycle. The resulting wall motion difference signals represent the changes in regional ventricular volumes and were quantitated by densitometry. Densitometry was able to detect the effect of all levels of ischemia on regional function, even the mildest. Densitometric analysis of both phase-matched and ejection fraction DE-DSA images provides a sensitive technique for detecting and quantitating the changes in regional left ventricular systolic volume that occur with ischemia.