21 research outputs found

    Absolute Cerebral Blood Flow Infarction Threshold for 3-Hour Ischemia Time Determined with CT Perfusion and <sup>18</sup>F-FFMZ-PET Imaging in a Porcine Model of Cerebral Ischemia

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    <div><p>CT Perfusion (CTP) derived cerebral blood flow (CBF) thresholds have been proposed as the optimal parameter for distinguishing the infarct core prior to reperfusion. Previous threshold-derivation studies have been limited by uncertainties introduced by infarct expansion between the acute phase of stroke and follow-up imaging, or DWI lesion reversibility. In this study a model is proposed for determining infarction CBF thresholds at 3hr ischemia time by comparing contemporaneously acquired CTP derived CBF maps to <sup>18</sup>F-FFMZ-PET imaging, with the objective of deriving a CBF threshold for infarction after 3 hours of ischemia. Endothelin-1 (ET-1) was injected into the brain of Duroc-Cross pigs (n = 11) through a burr hole in the skull. CTP images were acquired 10 and 30 minutes post ET-1 injection and then every 30 minutes for 150 minutes. 370 MBq of <sup>18</sup>F-FFMZ was injected ~120 minutes post ET-1 injection and PET images were acquired for 25 minutes starting ~155–180 minutes post ET-1 injection. CBF maps from each CTP acquisition were co-registered and converted into a median CBF map. The median CBF map was co-registered to blood volume maps for vessel exclusion, an average CT image for grey/white matter segmentation, and <sup>18</sup>F-FFMZ-PET images for infarct delineation. Logistic regression and ROC analysis were performed on infarcted and non-infarcted pixel CBF values for each animal that developed infarct. Six of the eleven animals developed infarction. The mean CBF value corresponding to the optimal operating point of the ROC curves for the 6 animals was 12.6 ± 2.8 mL·min<sup>-1</sup>·100g<sup>-1</sup> for infarction after 3 hours of ischemia. The porcine ET-1 model of cerebral ischemia is easier to implement then other large animal models of stroke, and performs similarly as long as CBF is monitored using CTP to prevent reperfusion.</p></div

    Average Relative CBF of Infarct ROIs.

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    <p>Average rCBF value from the infarct regions of the 6 animals at each time point. Error bars indicate standard error.</p

    Image Analysis Method.

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    <p>Infarct (pink) was identified on a PET image (top left) acquired 160-185min after ET-1 injection as pixels in the affected side ROI with signal below the infarction threshold derived from the contralateral ROI. Pixels with signal above this threshold were classified as non-infarct (yellow). The average image (top right) was used to segment out white matter. Blood vessels were identified on the BV map (bottom left) using a threshold derived from the affected side ROI (see text). Grey matter, vessel-less infarct and non-infarct ROIs were then superimposed onto the median CBF map (bottom right).</p

    ROC Curve with Optimal Operating Point.

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    <p>ROC curves plotted for each of the 6 animals. <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0158157#pone.0158157.t001" target="_blank">Table 1</a> lists the CBF threshold derived from the optimal operating point of the ROC curve for each animal, and the corresponding sensitivity, specificity, accuracy, and AUC.</p

    MEASURING COLLATERAL STATUS IN DIFFERENT VASCULAR BEDS

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    INTRODUCTION Collateral circulation in the brain is the most effective predictor of clinical outcome in acute ischemic stroke (AIS) patients [2]. Collaterals are vessels in the brain that reroute blood to the affected tissue during AIS. The only available methods of visualizing these vessels are invasive (CT Angiography, DSA) and are only effective if a major artery is occluded. Faber et al. (2010) showed that a correlation exists between collateral status in various body tissues, with the collateral status of the brain [1]. Here we describe a novel, non-invasive method for determining superficial palmar arch status (conduit collateral status), as well as micro vascular collateral status in the human hand.   METHODS The only non-invasive method for determination of the quality of blood flow in the hand is the modified allen’s test (MAT). The current techniques used in this test involve a high level of subjectivity and a low level of accuracy [3]. We improved this test by making the results quantitative, as well as focusing on specific regions of interest (ROI) in the hand. We developed an apparatus for the hand to be placed in, with a mounted research grade camera that would capture the duration of the test. The box was internally illuminated with optimized 740nm LEDs for detection of light intensity changes in the hand during the modified Allen’s test protocol. Our protocol was based upon removing blood from the hand using autonomous compressions, and recording the reperfusion of these vessels from a 1st artery release (radial or ulnar), followed by the 2nd artery release 15 seconds later. The camera recorded the intensity changes in the reflected radiation off the hand, which fluctuated as haemoglobin exited and re-entered the vessels in the hand. RESULTS Pilot data from 10 hands (5 healthy individuals) showed significant variance in both the rate of filling and the time to return to baseline. Our quickest rate of filling was 24 times larger than the slowest rate. Our analyses of the graphs, as well as controlling various confounding variables during assessment, suggest that these results are physiological and reflect differences in micro-vascular and conduit collateral status. DISCUSSION AND CONCLUSIONS This method reliably measures physiological differences in the collateral status of the human hand. These differences are shown in Figure 1, where two separate subjects have different arterial supply to the digits. In the future, we will be correlating hand collateral status with brain collateral status in stroke patients. If these correlations exist, a non-invasive pre-emptive tool would be made available to gain knowledge of brain collateral status before AIS occurs

    A longitudinal magnetic resonance imaging study of neurodegenerative and small vessel disease, and clinical cognitive trajectories in non demented patients with transient ischemic attack: the PREVENT study

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    Abstract Background Late-life cognitive decline, caused by progressive neuronal loss leading to brain atrophy years before symptoms are detected, is expected to double in Canada over the next two decades. Cognitive impairment in late life is attributed to vascular and lifestyle related risk factors in mid-life in a substantial proportion of cases (50%), thereby providing an opportunity for effective prevention of cognitive decline if incipient disease is detected earlier. Patients presenting with transient ischemic attack (TIA) commonly display some degree of cognitive impairment and are at a 4-fold increased risk of dementia. In the Predementia Neuroimaging of Transient Ischemic Attack (PREVENT) study, we will address what disease processes (i.e., Alzheimer’s vs. vascular disease) lead to neurodegeneration, brain atrophy, and cognitive decline, and whether imaging measurements of brain iron accumulation using quantitative susceptibility mapping predicts subsequent brain atrophy and cognitive decline. Methods A total of 440 subjects will be recruited for this study with 220 healthy subjects and 220 TIA patients. Early Alzheimer’s pathology will be determined by cerebrospinal fluid samples (including tau, a marker of neuronal injury, and amyloid β1–42) and by MR measurements of iron accumulation, a marker for Alzheimer’s-related neurodegeneration. Small vessel disease will be identified by changes in white matter lesion volume. Predictors of advanced rates of cerebral and hippocampal atrophy at 1 and 3 years will include in vivo Alzheimer’s disease pathology markers, and MRI measurements of brain iron accumulation and small vessel disease. Clinical and cognitive function will be assessed annually post-baseline for a period of 5-years using a clinical questionnaire and a battery of neuropsychological tests, respectively. Discussion The PREVENT study expects to demonstrate that TIA patients have increased early progressive rates of cerebral brain atrophy after TIA, before cognitive decline can be clinically detected. By developing and optimizing high-level machine learning models based on clinical data, image-based (quantitative susceptibility mapping, regional brain, and white matter lesion volumes) features, and cerebrospinal fluid biomarkers, PREVENT will provide a timely opportunity to identify individuals at greatest risk of late-life cognitive decline early in the course of disease, supporting future therapeutic strategies for the promotion of healthy aging

    Predicted Probability of Infarction vs. CBF.

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    <p>Predicted probability of infarction from logistic regression plotted against CBF for each animal. The average of the CBF values that corresponded to a 75% predicted probability of infarction was approximately 4.5 ± 2.6 mL·min<sup>-1</sup>·100g<sup>-1</sup>.</p

    Can CT perfusion accurately assess infarct core?

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    Abstract Background We sought to quantify CTP-derived infarct core applying previously published perfusion thresholds to multi-institutional CTP data to assess the margin of error for 25 mL and 70 mL critical volume thresholds using early DWI as a reference standard. Methods 60 patients with acute ischemic stroke undergoing CTP and DWI within 6 and 24 h of symptom onset, respectively, were retrospectively analyzed from 3 tertiary care centers. CTP-derived infarct core was calculated using published thresholds for absolute and relative CBF and CBV in addition to manual CBV tracing. Using DWI as the reference standard, performance of CTP-derived measures of infarct core was assessed using co-registered voxel-by-voxel analysis and total infarct volume comparison. Volumes of each CTP infarct core estimate were compared against DWI to determine the degree of infarct core over or underestimation at the critical volumes of 25 mL and 70 mL. Results Median core infarct volume was 10.8 mL. Mean CTP-derived infarct core volumes were similar to DWI for all CTP threshold methods to within ± 1 mL. CBV tracing demonstrated an overall significant core overestimation compared to DWI (p = 0.017). All CTP core volume estimations showed robust correlation with DWI (Pearson p-value < 0.001). As core volume increased, CTP demonstrated increased deviation from DWI. At the critical cut-offs of 25 mL and 70 mL, relative CBF demonstrated the best agreement with DWI for infarct core compared to the other CTP-derived measures of infarct core. Conclusion Our study demonstrates close approximation between multiple CTP-derived measures of infarct core and DWI infarct volume, Especially relative CBF
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