Prediction of the long-term efficacy of STA-MCA bypass by DSC-PI

Abstract

Superficial temporal artery-middle cerebral artery (STA-MCA) bypass [1,2] is an important and effective type of surgical revascularization that is widely used in the treatment of ischemic cerebral artery disease. However, a means of predicting its postoperative efficacy has not been established [3,4]. The present study analyzes the correlation between preoperative perfusion parameters (obtained using dynamic susceptibility contrast-enhanced perfusion imaging, DSC-PI) and postoperative long-term prognosis (using modified Rankin Scale, mRS scores). The preoperative perfusion parameters were defined by a combination of perfusion-weighted imaging and the Alberta Stroke Program Early Computerized Tomography Score (PWI-ASPECTS) and included cerebral blood flow (CBF)-ASPECTS, cerebral blood volume (CBV)-ASPECTS, mean transit time (MTT)-ASPECTS, and time to peak (TTP)-ASPECTS. Preoperative and postoperative scores were determined for 33 patients that received a unilateral STA-MCA bypass in order to discover the most reliable imaging predictive index as well as to define the threshold value for a favorable clinical outcome. The results showed that all of the PWI-ASPECTS scores were significantly negatively correlated with clinical prognosis. Receiver operating curve (ROC) analysis of the preoperative parameters in relation to long term prognosis showed the area under curve (AUC) was maximal for the CBF-ASPECTS score (P = 0.002). A preoperative score of less than six indicated a poor postoperative prognosis (sensitivity = 74.1%, specificity = 100%, AUC = 0.843). In conclusion, preoperative PWI-ASPECTS scores have been found useful as predictive indexes for the long-term prognosis of STA-MCA bypass patients, with higher scores indicating better postoperative long-term outcomes. As the most valuable prognostic indicator, the preoperative CBF-ASPECTS score has potential for use as a major index in screening and outcome prediction of patients under consideration for STA-MCA bypass surgery.

Crossed cerebellar diaschisis-related supratentorial hemodynamic and metabolic status measured by PET/MR in assessing postoperative prognosis in chronic ischemic cerebrovascular disease patients with bypass surgery

“…Fifty minutes after injection, the patients were placed into the PET/MR scanner in a supine position and instructed to remain calm with their eyes closed. 18 F-FDG PET images were acquired for 10 min. Attenuation correction was performed based on MR images, and the default attenuation correction sequence (Dixon MR sequences) was automatically prescribed and acquired as follows [19]: LAVA-Flex (GE Healthcare) axial acquisition, repetition time (TR) = 4 ms, echo time (TE) = 1.7 ms, slice thickness = 5.2 mm with a 2.6 mm overlap, 120 slices, pixel size = 1.95 × 2.93 mm, and acquisition time = 18 s. PET data were reconstructed into a 192 × 192 matrix, 35 cm field of view (FOV), and 2.78 mm slice thickness (voxel size 1.82 × 1.82 × 2.78 mm 3 ) using a time-of-flight, point spread function, ordered subset expectation maximization (TOF-PSF-OSEM) algorithm with 8 iterations, 32 subsets, and a 3 mm Gaussian filter [10].…”

“…First, two experienced doctors from the Department of Radiology and Nuclear Medicine blinded to the ASL-CBF findings visually determined CCD based on 18 F-FDG PET images following published criteria [22].…”

“…All images were preprocessed using SPM8 (Wellcome Department of Clinical Neurology, London, UK) [10]. 18 F-FDG-PET and ASL images were first spatially normalized to the MNI (Montreal Neurological Institute) space with a 3 × 3 × 3 mm 3 resolution using affine transformation and subsequent nonlinear warping. The 18 F-FDG-PET images were transformed into maps representing the radioactivity (kBq/ml), which was defined as the tissue concentration of radioactivity in each voxel normalized to the mean activity concentration.…”

“…Parameters, including voxel-wise asymmetry index (AI) values for CBF and metabolism, were calculated after the exclusion of the infarct area from the entire supratentorialaffected side. The AI used to detect left-right asymmetry in the 18 F-FDG PET and ASL-CBF data is based on the following equation:…”

“…Arterial spin labeling (ASL) sequences can be used to evaluate potentially reversible tissue ischemia. 18 F-FDG is widely used in the measurement of brain glucose metabolism. However, various physiological processes at different time points may change between imaging sessions.…”