Evaluation of Encephaloduroarteriosynangiosis Efficacy Using Probabilistic Independent Component Analysis Applied to Dynamic Susceptibility Contrast Perfusion MRI

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In this prospective study, 13 patients underwent unilateral indirect cerebral revascularization and DSC-MR imaging before and after surgery. Conventional perfusion parameters (relative CBV, relative CBF, and TTP) and probabilistic independent components that reflect the relative contributions of DSC signals consistent with arterial, capillary, and venous hemodynamics were calculated and examined for significant changes after surgery. Before surgery, tissue within the affected hemisphere demonstrated a high probability for hemodynamics consistent with venous flow and a low probability for hemodynamics consistent with arterial flow, whereas the contralateral control hemisphere demonstrated the reverse. Consistent with symptomatic improvement, the probability for venous hemodynamics within the affected hemisphere decreased with time after surgery. The authors conclude that probabilistic independent component analysis yielded sensitive measurements of changes in local tissue perfusion that may be associated with newly formed vasculature after indirect cerebral revascularization surgery.

Abstract

Figure 1 from paper
Probabilistic independent component analysis of presurgical DSC-MR imaging of a patient undergoing EDAS. Probability maps of arterial (left) and venous (right) components are shown on an axial section. The respective time courses show a delayed response in the venous component. The color bar indicates local probability. Note the high probability for the venous component in the left hemispheric cortex, which is the symptomatic side.

BACKGROUND AND PURPOSE

Indirect cerebral revascularization has been successfully used for treatment in Moyamoya disease and symptomatic intracranial atherosclerosis. While angiographic neovascularization has been demonstrated after surgery, measurements of local tissue perfusion are scarce and may not reflect the reported successful clinical outcomes. We investigated probabilistic independent component analysis and conventional perfusion parameters from DSC-MR imaging to measure postsurgical changes in tissue perfusion.

MATERIALS AND METHODS

In this prospective study, 13 patients underwent unilateral indirect cerebral revascularization and DSC-MR imaging before and after surgery. Conventional perfusion parameters (relative cerebral blood volume, relative cerebral blood flow, and TTP) and probabilistic independent components that reflect the relative contributions of DSC signals consistent with arterial, capillary, and venous hemodynamics were calculated and examined for significant changes after surgery. Results were compared with postsurgical DSA studies to determine whether changes in tissue perfusion were due to postsurgical neovascularization.

RESULTS

Before surgery, tissue within the affected hemisphere demonstrated a high probability for hemodynamics consistent with venous flow and a low probability for hemodynamics consistent with arterial flow, whereas the contralateral control hemisphere demonstrated the reverse. Consistent with symptomatic improvement, the probability for venous hemodynamics within the affected hemisphere decreased with time after surgery (P = .002). No other perfusion parameters demonstrated this association. Postsurgical DSA revealed an association between an increased preoperative venous probability in the symptomatic hemisphere and neovascularization after surgery.

CONCLUSIONS

Probabilistic independent component analysis yielded sensitive measurements of changes in local tissue perfusion that may be associated with newly formed vasculature after indirect cerebral revascularization surgery.

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Evaluation of Encephaloduroarteriosynangiosis Efficacy Using Probabilistic Independent Component Analysis Applied to Dynamic Susceptibility Contrast Perfusion MRI
Jeffrey Ross
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