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

Abstract

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-MRI to measure post-surgical changes in tissue perfusion. Materials and Methods In this prospective study, thirteen patients underwent unilateral indirect cerebral revascularization and received DSC-MRI before and after surgery. Conventional perfusion parameters (rCBV, rCBF, 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 to post-surgical DSA studies to determine whether changes in tissue perfusion were due to post-surgical neovascularization. Results Prior to 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 = 0.002). No other perfusion parameters demonstrated this association. Post-surgical DSA revealed an association between an increased preoperative venous probability in the symptomatic hemisphere and neovascularization after surgery. Conclusion 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.

Noninvasive Assessment of Hemodynamic Stress Distribution after Indirect Revascularization for Pediatric Moyamoya Vasculopathy

“…Perfusion gradient redistribution through the newly formed pial circulation thus determines significant reduction of the hdSD. 3,7,15,21 Most interesting, hdSD at the last MR imaging evaluation and postoperative variations of hdSD obtained with DSC-PWI were related to postoperative outcome after controlling for age, sex, and the duration of clinical follow-up. These perfusion indices were significantly different in the 4 clinical outcome categories at the last follow-up point (average, 38.5 months after the operation).…”

“…[9][10][11] Hence, there has been an effort to find alternative methods for evaluating cerebral hemodynamics in patients with MM. [12][13][14][15] In 1996, Kashiwagi et al 12 proposed the ratio of mean CBF values in the lentiform nucleus (central CBF) and cortical MCA territories (cortical CBF) as an index of hemodynamic stress distribution (hdSD) using xenonenhanced CT. 12 More recently, Schubert et al 14 demonstrated that hdSD could be a more robust parameter than CBF alone for disease assessment in adults with MM. At present, no studies have evaluated the results of indirect revascularization in children with MM using the hdSD obtained with noninvasive PWI techniques.…”

Revealing hemodynamic heterogeneity of gliomas based on signal profile features of dynamic susceptibility contrast-enhanced MRI

“…Previously, the model free ICA has been applied successfully in brain functional mapping and functional connectivity studies using fMRI time course data for analyzing specific patterns of oscillation signals related to the resting state or task-invoked low-frequency brain activities (Calhoun et al, 2001; Griffanti et al, 2014). Separation of the mixed dynamic time course signals of DSC MRI into independent source signals provides a better measurement of spatiotemporal variations in local cerebral blood perfusion (Laiwalla et al, 2017). The present study suggests that the model-free pattern extracting methods, such as ICA, can be applied on DSC MRI data to characterize the brain tumor vasculature heterogeneity.…”

Methods to assess competence of indirect cerebral revascularization in children

“…Участие дисгемического механизма у данной категории больных осложняет течение заболевания. Худшие результаты реваскуляризации (классы В и С), вероятно, связа-ны со значительными кистозно-атрофическими изменениями мозговой ткани и с менее выраженной хронической недостаточностью мозгового кровообращения, хотя связь между тканевой перфузией и клиническим исходом остается неизвестной после ЭДАС при структурных изменениях мозга [14].…”