Dynamic Susceptibility Contrast Magnetic Resonance Research Articles

NIMG-23. A NOVEL APPROACH TO PERFUSION MRI STUDIES IN BRAIN TUMOR PATIENTS USING ENDOGENOUS DEOXYHEMOGLOBIN AS A CONTRAST AGENT: A PROOF-OF-CONCEPT STUDY

Abstract BACKGROUND Assessment of resting perfusion in brain tumors is clinically relevant and relies on dynamic susceptibility contrast magnetic resonance imaging using gadolinium contrast. Preliminary studies have introduced the use of controlled hemoglobin desaturation by means of a transient hypoxic stimulus during echo-planar imaging(EPI) as a surrogate for gadolinium for resting perfusion assessment in healthy subjects. In this proof of concept study, we investigated whether this approach is feasible in brain tumors and warrant further validation. METHODS A computer controlled gas blender was used to induce transient and standardized hypoxic stimulus in isocapnic conditions during EPI acquisition in a heterogenous cohort of tumor patients. The induced blood-oxygen-level-dependent(BOLD) signal changes determined by transit of a bolus of deoxygenated blood in the brain vasculature were used as a surrogate of gadolinium to calculate cerebral blood volume(CBV), cerebral blood flow(CBF) and mean transit time(MTT) using a global arterial input functions obtained through the BOLD signal measured over the middle cerebral artery as previously described by Poublanc et al. Perfusion parameters were calculated in the whole-brain voxel-by-voxel and in automatically segmented region of interest(ROI) using SPM, AFNI, Verbena softwares and MATLAB in-house written scripts. RESULTS Nine patients were included. MTT, rCBV, rCBF were calculated voxel-per-voxel. Obtained maps were overlayed on the co-registered T1 MRI scans and compared to T1CE and FLAIR to identify perfusion patterns in tumor ROIs (contrast enhancement, edema, necrosis). The deoxy-hemoglobin BOLD MRI perfusion were compared to clinical DSC-MRI when available and showed high qualitative agreement. CONCLUSION Transient and precise hemoglobin desaturation by controlled hypoxic gas modulation is safe and repeatable in brain tumor patients. The induced BOLD signal change allows measurement of resting perfusion, which qualitatively closely mimic gadolinium perfusion in different brain tumors. Deoxyhemoglobin-based perfusion warrant further quantitative validation against gadolinium in a larger cohort of heterogenous tumor patients.

Role of Contrast Perfusion Weighted Magnetic Resonance Imaging in Grading of Brain Tumors with Histopathological Correlation

Background: Traditional MRI sequences provide precise anatomical information about brain tumors. But these sequences can’t quantitatively evaluate vascular physiology, or capture tumor biology at the molecular level; which is important for tumor grading, therapeutic assessment, and prognostication. Furthermore, non-enhancing parts of the tumor affected brain, which generally indicates peri-tumoral brain edema with infiltrative tumor cells, is not visible on conventional MRI sequences. Perfusion weighted Magnetic Resonance Imaging (PW-MRI) techniques such as Dynamic Contrast Enhanced Magnetic Resonance Imaging (DCE-MRI) and Dynamic Susceptibility Contrast Magnetic Resonance Imaging (DSC-MRI) have shown promise as imaging biomarkers for glioma therapy, since these new sequences can also provide information about vascular hemodynamics. Our study was first prospective study from Himalayan belt of India, wherein we tried to assess the role of PW-MRI in the grading of brain tumors, with histopathological correlation. Aim and Objective: To compare tumor perfusion and histopathological tumor grading, in evaluation of brain tumor especially gliomas. Material and Method: 40 patients who were referred to Department of Radiodiagnosis for evaluation of brain tumor, and who gave informed consent, were included in this prospective study, done over a period of 18 months. All patients underwent MRI, followed by surgical resection. Observation and Result: In our study, diagnostic accuracy was 90% for mean rCBV (lesion) (cut off: 7 by ROC), mean rCBF (lesion) (cut off: 13.9 by ROC), and rCBF ratio (cut off: 2.9 by ROC); for differentiating benign versus malignant brain tumor. rCBF ratio was found to be best diagnostic parameter with sensitivity of 96%, specificity of 80%, positive predictive value of 89%, negative predictive value of 92%, diagnostic accuracy of 90%, area under ROC curve=0.909, and p value<0.001. Conclusion: We come to conclusion that high grade brain tumor display higher CBF, than do low grade brain tumor. Three parameters showed good diagnostic accuracy, which includes rCBF ratio, mean rCBF (lesion), and mean rCBV (lesion). These parameters can be used to predict the grade of the brain tumor, with good diagnostic accuracy.

Dynamic susceptibility contrast‑enhanced perfusion magnetic resonance imaging parameters for predicting MGMT promoter methylation and prognostic value in newly diagnosed patients with glioblastoma.

O6-methylguanine DNA methyltransferase (MGMT) promoter methylation is an important clinical biomarker of newly diagnosed glioblastoma. Previous radiological studies using dynamic susceptibility contrast (DSC) magnetic resonance imaging (MRI) perfusion have aimed to predict MGMT methylation status non-invasively in gliomas with radiological characteristics. The possibility of predicting MGMT methylation status using DSC-MRI perfusion with a radiological approach remains controversial. The present study aimed to evaluate the usefulness of MRI perfusion parameters as non-invasive markers to predict MGMT methylation status and prognosis in newly diagnosed glioblastoma patients. Thus, 50 patients with histologically confirmed primary glioblastoma, IDH-wildtype who underwent tumor resection at Osaka University Hospital (Suita, Japan) between January 2017 and January 2023 were included in this study. The mean cerebral blood volume (CBV) ratio (rCBV) and cerebral blood flow (CBF) ratio (rCBF) for tumors with MGMT methylation (mean rCBV:2.09 and mean rCBF:3.08) were significantly higher compared with those for tumors without MGMT methylation (mean rCBV:1.33 and mean rCBF:1.85; P<0.05). While patients with MGMT methylation had longer progression-free survival (PFS) compared with those without MGMT methylation (P<0.05), there was no significant difference in OS with or without MGMT methylation (P=0.06). By contrast, there was no association between MRI perfusion parameters and OS or PFS in patients with glioblastoma. Furthermore, the association between CBV, CBF, MGMT promotor methylation status, OS, and PFS were explored. There was no significant prognostic difference between low vascularity tumors (rCBV <1.3 or rCBF <1.8) with or without MGMT methylation. On the other hand, high vascularity tumors (rCBF ≥1.8) with MGMT promotor methylation were associated to longer OS and PFS compared with those without. However, there was no association between MGMT methylation status and OS or PFS in patients with high rCBV (rCBV ≥1.3). The present study indicated that CBV and CBF could be used to predict the MGMT methylation status in glioblastomas. However, the prognostic value of tumor vascularity and MGMT methylation status may be limited.

Relationships of Jugular Bulb Parameters with Cerebral Perfusion and Metabolism After Resuscitation from Cardiac Arrest: A Post-Hoc Analysis of Experimental Studies Using a Minipig Model.

Cerebral blood flow (CBF) decreases in the first few hours or days following resuscitation from cardiac arrest, increasing the risk of secondary cerebral injury. Using data from experimental studies performed in minipigs, we investigated the relationships of parameters derived from arterial and jugular bulb blood gas analyses and lactate levels (jugular bulb parameters), which have been used as indicators of cerebral perfusion and metabolism, with CBF and the cerebral lactate to creatine ratio measured with dynamic susceptibility contrast magnetic resonance imaging and proton magnetic resonance spectroscopy, respectively. We retrospectively analyzed 36 sets of the following data obtained during the initial hours following resuscitation from cardiac arrest: percent of measured CBF relative to that at the prearrest baseline (%CBF), cerebral lactate to creatine ratio, and jugular bulb parameters, including jugular bulb oxygen saturation, jugular bulb lactate, arterial-jugular bulb oxygen content difference, cerebral extraction of oxygen, jugular bulb-arterial lactate content difference, lactate oxygen index, estimated respiratory quotient, and arterial-jugular bulb hydrogen ion content difference. Linear mixed-effects models were constructed to examine the effects of each jugular bulb parameter on the %CBF and cerebral lactate to creatine ratio. The arterial-jugular bulb oxygen content difference (P = 0.047) and cerebral extraction of oxygen (P = 0.030) had a significant linear relationship with %CBF, but they explained only 12.0% (95% confidence interval [CI] 0.002-0.371) and 14.2% (95% CI 0.005-0.396) of the total %CBF variance, respectively. The arterial-jugular bulb hydrogen ion content difference had a significant linear relationship with cerebral lactate to creatine ratio (P = 0.037) but explained only 13.8% (95% CI 0.003-0.412) of the total variance in the cerebral lactate to creatine ratio. None of the other jugular bulb parameters were related to the %CBF or cerebral lactate to creatine ratio. In conclusion, none of the jugular bulb parameters appeared to provide sufficient information on cerebral perfusion and metabolism in this setting.

Perfusion parameter map generation from TOF-MRA in stroke using generative adversarial networks

PurposeTo generate perfusion parameter maps from Time-of-flight magnetic resonance angiography (TOF-MRA) images using artificial intelligence to provide an alternative to traditional perfusion imaging techniques. Materials and methodsThis retrospective study included a total of 272 patients with cerebrovascular diseases; 200 with acute stroke (from 2010 to 2018), and 72 with steno-occlusive disease (from 2011 to 2014). For each patient the TOF MRA image and the corresponding Dynamic susceptibility contrast magnetic resonance imaging (DSC-MRI) were retrieved from the datasets. The authors propose an adapted generative adversarial network (GAN) architecture, 3D pix2pix GAN, that generates common perfusion maps (CBF, CBV, MTT, TTP, Tmax) from TOF-MRA images. The performance was evaluated by the structural similarity index measure (SSIM). For a subset of 20 patients from the acute stroke dataset, the Dice coefficient was calculated to measure the overlap between the generated and real hypoperfused lesions with a time-to-maximum (Tmax) > 6 s. ResultsThe GAN model exhibited high visual overlap and performance for all perfusion maps in both datasets: acute stroke (mean SSIM 0.88–0.92, mean PSNR 28.48–30.89, mean MAE 0.02–0.04 and mean NRMSE 0.14–0.37) and steno-occlusive disease patients (mean SSIM 0.83–0.98, mean PSNR 23.62–38.21, mean MAE 0.01–0.05 and mean NRMSE 0.03–0.15). For the overlap analysis for lesions with Tmax>6 s, the median Dice coefficient was 0.49. ConclusionOur AI model can successfully generate perfusion parameter maps from TOF-MRA images, paving the way for a non-invasive alternative for assessing cerebral hemodynamics in cerebrovascular disease patients. This method could impact the stratification of patients with cerebrovascular diseases. Our results warrant more extensive refinement and validation of the method.

Cerebral hemodynamics as biomarkers for neuropathic pain in rats: a longitudinal study using a spinal nerve ligation model.

Neuropathic pain is one of the most challenging types of pain to diagnose and treat, a problem exacerbated by the lack of a quantitative biomarker. Recently, several clinical and preclinical studies have shown that neuropathic pain induces cerebral hemodynamic changes as a result of neuroplasticity in the brain. Our hypothesis in this study is that neuropathic pain leads to cerebral hemodynamic changes over postoperative time in a spinal nerve ligation (SNL) rat model, which has not been longitudinally explored previously. Furthermore, by identifying multiple regional hemodynamic features that are the most distinct between SNL and sham groups, where the sham group underwent only an incision without SNL, it may be possible to classify the SNL group regardless of when the onset of pain occurs. We investigate cerebral hemodynamic changes using dynamic susceptibility contrast magnetic resonance imaging in a rat model up to 28 days after ligating L5/L6 spinal nerves. We trained a linear support vector machine with relative cerebral blood volume data from different brain regions and found that the prediction model trained on the nucleus accumbens, motor cortex, pretectal area, and thalamus classified the SNL group and sham group at a 79.27% balanced accuracy, regardless of when the onset of pain occurred (SNL/sham: 60/45 data points). From the use of the SNL model without prior knowledge of the onset time of pain, the current findings highlight the potential of relative cerebral blood volume in the 4 highlighted brain regions as a biomarker for neuropathic pain.

Influence of arterial transit time delays on the differentiation between tumor progression and pseudoprogression in glioblastoma by arterial spin labeling magnetic resonance imaging.

Arterial spin labeling (ASL) and dynamic susceptibility contrast (DSC) magnetic resonance imaging (MRI) have shown potential for differentiating tumor progression from pseudoprogression. For pseudocontinuous ASL with a single postlabeling delay, the presence of delayed arterial transit times (ATTs) could affect the evaluation of ASL-MRI perfusion data. In this study, the influence of ATT artifacts on the perfusion assessment and differentiation between tumor progression and pseudoprogression were studied. This study comprised 66 adult patients (mean age 60 ± 13 years; 40 males) with a histologically confirmed glioblastoma who received postoperative radio (chemo)therapy. ASL-MRI and DSC-MRI scans were acquired at 3months postradiotherapy as part of the standard clinical routine. These scans were visually scored regarding (i) the severity of ATT artifacts (%) on the ASL-MRI scans only, scored by two neuroradiologists; (ii) perfusion of the enhancing tumor lesion; and (iii) radiological evaluation of tumor progression versus pseudoprogression by one neuroradiologist. The final outcome was based on combined clinical and radiological follow-up until 9months postradiotherapy. ATT artifacts were identified in all patients based on the mean scores of two raters. A significant difference between the radiological evaluation of ASL-MRI and DSC-MRI was observed only for ASL images with moderate ATT severity (30%-65%). The perfusion assessment showed ASL-MRI tending more towards hyperperfusion than DSC-MRI in the case of moderate ATT artifacts. In addition, there was a significant difference between the prediction of tumor progression with ASL-MRI and the final outcome in the case of severe ATT artifacts (McNemar test, p= 0.041). Despite using ASL imaging parameters close to the recommended settings, ATT artifacts frequently occur in patients with treated brain tumors. Those artifacts could hinder the radiological evaluation of ASL-MRI data and the detection of true disease progression, potentially affecting treatment decisions for patients with glioblastoma.

Macro- and microvascular contributions to cerebral structural alterations in patients with asymptomatic carotid artery stenosis

Atherosclerosis can underly internal carotid artery stenosis (ICAS), a major risk factor for ischemic stroke, as well as small vessel disease (SVD). This study aimed to investigate hemodynamics and structural alterations associated with SVD in ICAS patients. 28 patients with unilateral asymptomatic ICAS and 30 age-matched controls underwent structural (T1-/T2-weighted and diffusion tensor imaging [DTI]) and hemodynamic (pseudo-continuous arterial spin labeling and dynamic susceptibility contrast) magnetic resonance imaging. SVD-related alterations were assessed using free water (FW), FW-corrected DTI, and peak-width of skeletonized mean diffusivity (PSMD). Furthermore, cortical thickness, cerebral blood flow (CBF), and capillary transit time heterogeneity (CTH) were analyzed. Ipsilateral to the stenosis, cortical thickness was significantly decreased in the posterior dorsal cingulate cortex (p = 0.024) and temporal pole (p = 0.028). ICAS patients exhibited elevated PSMD (p = 0.005), FW (p < 0.001), and contralateral alterations in FW-corrected DTI metrics. We found significantly lateralized CBF (p = 0.011) and a tendency for lateralized CTH (p = 0.067) in the white matter (WM) related to ICAS. Elevated PSMD and FW may indicate a link between SVD and WM changes. Contralateral alterations were seen in FW-corrected DTI, whereas hemodynamic and cortical changes were mainly ipsilateral, suggesting SVD might influence global brain changes concurrent with ICAS-related hemodynamic alterations.

Comparison of computed tomography perfusion and magnetic resonance dynamic susceptibility contrast perfusion-weighted imaging in canine brain.

Brain perfusion allows for the evaluation of cerebral hemodynamics, particularly in brain infarcts and tumors. Computed tomography (CT) perfusion (CTP) provides reliable data; however, it has a limited scan field of view and radiation exposure. Magnetic resonance (MR) perfusion provides detailed imaging of small structures and a wide scan field of view. However, no study has compared CTP and MR perfusion and assessed the correlation between the perfusion parameters measured using CTP and MR perfusion. The aim of the present study was to assess the correlation and agreement of the cerebral perfusion derived from dynamic susceptibility contrast (DSC)-MRI and CTP in dogs. In this crossover design study, the cerebral blood volume (CBV), cerebral blood flow (CBF), mean transit time, and time to peak were measured in the temporal cerebral cortex, caudate nucleus, thalamus, piriform lobe, and hippocampus using CTP and DSC-MRI in six healthy beagle dogs and a dog with a pituitary tumor. On the color map of healthy beagles, blood vessels and the perivascular brain parenchyma appeared as red-green, indicating high perfusion, and the areas distant from the vessels appeared as green-blue, indicating low perfusion levels in CTP and DSC-MRI. CTP parameters were highest in the piriform lobe (CBF = 121.11 ± 12.78 mL/100 g/min and CBV = 8.70 ± 2.04 mL/100 g) and lowest in the thalamus (CBF = 63.75 ± 25.24 mL/100 g/min and CBV = 4.02 ± 0.55 mL/100 g). DSC-MRI parameters were also highest in the piriform lobe (CBF = 102.31 ± 14.73 mL/100 g/min and CBV = 3.17 ± 1.23 mL/100 g) and lowest in the thalamus (CBF = 37.73 ± 25.11 mL/100 g/min and CBV = 0.81 ± 0.44 mL/100 g) although there was no statistical correlation in the quantitative perfusion parameters between CTP and DSC-MRI. In a dog with a pituitary tumor, the color map of the tumor appeared as a red scale, indicating high perfusion and higher CBF and CBV on CTP (149 mL/100 g and 20 mL/100 g/min) and on DSC-MRI (116.3 mL/100 g and 15.32 mL/100 g/min) compared to those measured in healthy dogs. These findings indicate that DSC-MRI and CTP maps exhibit comparability and interchangeability in the assessment of canine brain perfusion.

Creation of a Simulated Sequence of Dynamic Susceptibility Contrast—Magnetic Resonance Imaging Brain Scans as a Tool to Verify the Quality of Methods for Diagnosing Diseases Affecting Brain Tissue Perfusion

DSC-MRI examination is one of the best methods of diagnosis for brain diseases. For this purpose, the so-called perfusion parameters are defined, of which the most used are CBF, CBV, and MTT. There are many approaches to determining these parameters, but regardless of the approach, there is a problem with the quality assessment of methods. To solve this problem, this article proposes virtual DSC-MRI brain examination, which consists of two steps. The first step is to create curves that are typical for DSC-MRI studies and characteristic of different brain regions, i.e., the gray and white matter, and blood vessels. Using perfusion descriptors, the curves are classified into three sets, which give us the model curves for each of the three regions. The curves corresponding to the perfusion of different regions of the brain in a suitable arrangement (consistent with human anatomy) form a model of the DSC-MRI examination. In the created model, one knows in advance the values of the complex perfusion parameters, as well as basic perfusion descriptors. The shown model study can be disturbed in a controlled manner—not only by adding noise, but also by determining the location of disturbances that are characteristic of specific brain diseases.

Deep Learning for Perfusion Cerebral Blood Flow (CBF) and Volume (CBV) Predictions and Diagnostics

Dynamic susceptibility contrast magnetic resonance perfusion (DSC-MRP) is a non-invasive imaging technique for hemodynamic measurements. Various perfusion parameters, such as cerebral blood volume (CBV) and cerebral blood flow (CBF), can be derived from DSC-MRP, hence this non-invasive imaging protocol is widely used clinically for the diagnosis and assessment of intracranial pathologies. Currently, most institutions use commercially available software to compute the perfusion parametric maps. However, these conventional methods often have limitations, such as being time-consuming and sensitive to user input, which can lead to inconsistent results; this highlights the need for a more robust and efficient approach like deep learning. Using the relative cerebral blood volume (rCBV) and relative cerebral blood flow (rCBF) perfusion maps generated by FDA-approved software, we trained a multistage deep learning model. The model, featuring a combination of a 1D convolutional neural network (CNN) and a 2D U-Net encoder-decoder network, processes each 4D MRP dataset by integrating temporal and spatial features of the brain for voxel-wise perfusion parameters prediction. An auxiliary model, with similar architecture, but trained with truncated datasets that had fewer time-points, was designed to explore the contribution of temporal features. Both qualitatively and quantitatively evaluated, deep learning-generated rCBV and rCBF maps showcased effective integration of temporal and spatial data, producing comprehensive predictions for the entire brain volume. Our deep learning model provides a robust and efficient approach for calculating perfusion parameters, demonstrating comparable performance to FDA-approved commercial software, and potentially mitigating the challenges inherent to traditional techniques.

Diagnostic Utility of Integration of Dynamic Contrast-Enhanced and Dynamic Susceptibility Contrast MR Perfusion Employing Split Bolus Technique in Differentiating High-Grade Glioma.

Background : Despite documented correlation between glioma grades and dynamic contrast-enhanced (DCE) magnetic resonance (MR) perfusion-derived parameters, and its inherent advantages over dynamic susceptibility contrast (DSC) perfusion, the former remains underutilized in clinical practice. Given the inherent spatial heterogeneity in high-grade diffuse glioma (HGG) and assessment of different perfusion parameters by DCE (extravascular extracellular space volume [Ve] and volume transfer constant in unit time [k-trans]) and DSC (rCBV), integration of the two into a protocol could provide a holistic assessment. Considering therapeutic and prognostic implications of differentiating WHO grade 3 from 4, we analyzed the two grades based on a combined DCE and DSC perfusion. Methods : Perfusion sequences were performed on 3-T MR. Cumulative dose of 0.1 mmol/kg of gadodiamide, split into two equal boluses, was administered with an interval of 6 minutes between the DCE and DSC sequences. DCE data were analyzed utilizing commercially available GenIQ software. Results : Of the 41 cases of diffuse gliomas analyzed, 24 were WHO grade III and 17 grade IV gliomas (2016 WHO classification). To differentiate grade III and IV gliomas, Ve cut-off value of 0.178 provided the best combination of sensitivity (88.24%) and specificity (87.50%; AUC: 0.920; p < 0.001). A relative cerebral blood volume (rCBV) of value 3.64 yielded a sensitivity of 70.59% and specificity of 62.50% ( p = 0.018). The k-trans value, although higher in grade III than in grade IV gliomas, did not reach statistical significance ( p = 0.108). Conclusion : Uniqueness of employed combined perfusion technique, treatment naïve patients at imaging, user-friendly postprocessing software utilization, and ability of Ve and rCBV to differentiate between grade III and IV gliomas ( p < 0.05) are the strengths of the present study, contributing to the existing literature and moving a step closer to achieving accurate MR perfusion-based glioma grading.

Assessment of the Effects of Sodium Nitroprusside Administered Via Intracranial Subdural Catheters on the Cerebral Blood Flow and Lactate Using Dynamic Susceptibility Contrast Magnetic Resonance Imaging and Proton Magnetic Resonance Spectroscopy in a Pig Cardiac Arrest Model.

Background Cerebral blood flow (CBF) is impaired in the early phase after return of spontaneous circulation. Sodium nitroprusside (SNP) administration via intracranial subdural catheters improves cerebral cortical microcirculation. We determined whether the SNP treatment improves CBF in the subcortical tissue and evaluated the effects of this treatment on cerebral lactate. Methods and Results Sixty minutes after return of spontaneous circulation following 14 minutes of untreated cardiac arrest, 14 minipigs randomly received 4 mg SNP or saline via intracranial subdural catheters. CBF was measured in regions of interest within the cerebrum and thalamus using dynamic susceptibility contrast-magnetic resonance imaging. After return of spontaneous circulation, CBF was expressed as a percentage of the baseline value. In the saline group, the %CBF in the regions of interest within the cerebrum remained at approximately 50% until 3.5 hours after return of spontaneous circulation, whereas %CBF in the thalamic regions of interest recovered to approximately 73% at this time point. The percentages of the baseline values in the cortical gray matter and subcortical white matter were higher in the SNP group (group effect P=0.026 and 0.025, respectively) but not in the thalamus. The cerebral lactate/creatine ratio measured using magnetic resonance spectroscopy increased over time in the saline group but not in the SNP group (group-time interaction P=0.035). The thalamic lactate/creatine ratio was similar in the 2 groups. Conclusions SNP administered via intracranial subdural catheters improved CBF not only in the cortical gray matter but also in the subcortical white matter. The CBF improvement by SNP was accompanied by a decrease in cerebral lactate.

Capillary dysfunction in healthy elderly APOE ε4 carriers with raised brain Aβ deposition.

Capillary dysfunction, characterized by disturbances in capillary blood flow distribution, might be an overlooked factor in the development of Alzheimer's disease (AD). This study investigated microvascular blood flow in preclinical and prodromal AD individuals. Using dynamic susceptibility contrast magnetic resonance imaging and positron emission tomography, we examined alterations in microvascular circulation and levels of Aβ deposition in two independent cohorts of APOE ε4 carriers. Capillary dysfunction was elevated in both prodromal and preclinical AD individuals compared to age-matched controls. Additionally, the prodromal group exhibited higher levels of capillary dysfunction compared to the preclinical group. These findings suggest that capillary dysfunction can be detected at the preclinical stage of AD and indicates a worsening of capillary dysfunction throughout the AD continuum. Understanding the interaction between capillary dysfunction and Aβ could provide insights into the relationship between cardiovascular risk factors and the development of AD. Alzheimer's disease (AD) is associated with disturbances in microvascular circulation. Capillary dysfunction can be detected in preclinical AD. As cognitive symptoms progress in prodromal AD, capillary dysfunction worsens. Capillary dysfunction may impede the clearance of beta-amyloid (Aβ). Capillary dysfunction might contribute to the development of AD.

Dynamic susceptibility contrast perfusion-weighted and diffusion-weighted magnetic resonance imaging findings in pilocytic astrocytoma and H3.3 and H3.1 variant diffuse midline glioma, H3K27-altered.

This study compared the dynamic susceptibility contrast (DSC) magnetic resonance imaging parameters and apparent diffusion coefficient (ADC) between pilocytic astrocytoma (PA) and diffuse midline glioma, H3K27-altered (DMG) variants. The normalized relative cerebral blood volume (nrCBV), normalized relative flow (nrCBF), percentile signal recovery (PSR), and normalized mean ADC (nADCmean) of 23 patients with midline PAs (median age, 13 years [range, 1-71 years]; 13 female patients) and 40 patients with DMG (8.5 years [1-35 years]; 19 female patients), including 35 patients with H3.3- and five patients with H3.1-mutant tumors, treated between January 2016 and May 2022 were statistically compared. DMG had a significantly lower nADCmean (median: 1.48 vs. 1.96; p = 0.00075) and lower PSR (0.97 vs. 1.23, p = 0.13) but higher nrCBV and nrCBF (1.66 vs. 1.17, p = 0.058, respectively, and 1.87 vs. 1.19, p = 0.028, respectively) than PA. The H3.3 variant had a lower nADCmean than the H3.1 variant (1.46 vs. 1.80, p = 0.10). DMG had lower ADC and PSR and higher rCBV and rCBF than PA. The H3.3 variant had a lower ADC than the H3.1 variant. Recognizing the differences and similarities in the DSC parameters and ADC between these tumors may help presurgical diagnosis.

Surgical outcomes following encephaloduroarteriosynangiosis in moyamoya disease associated with hyperhomocysteinemia.

This study investigated the effect of indirect revascularization surgery in adult patients with moyamoya disease (MMD) complicated with hyperhomocysteinemia (HHcy), and the effect of HHcy on the progression of adult MMD. A retrospective case-control study was conducted in patients with MMD, with or without HHcy (n=123). Postoperative collateral angiogenesis was evaluated using the Matsushima grading system and disease progression using the Suzuki staging system. Cerebral blood flow was evaluated before and after surgery using dynamic susceptibility contrast magnetic resonance imaging (DSC-MRI) and neurological function prognosis using the improved Rankin score (mRS). Univariate and multivariate logistic regression analyses were performed to determine risk factors for the clinical outcomes. There was no significant difference in the Suzuki stage composition ratios between the HHcy group and the non-HHcy group before and after surgery. Non-HHcy patients were more likely to grow new collateral circulating vessels after encephaloduroarteriosynangiosis (EDAS). Moreover, postoperative DSC-MRI indicated that the time to peak significantly improved. HHcy level may be a specific predictor of adverse clinical outcomes after EDAS in patients with MMD and a risk factor for poor collateral circulation and poor prognosis. Patients with MMD complicated with HHcy need to strictly control homocysteine levels before EDAS surgery.

Predictors of Stroke Outcomes in Conservatively Treated Patients With Moyamoya Disease: A Follow-up MRI Study.

Little is known about the association between stroke and imaging and clinical features in conservatively treated patients with moyamoya disease (MMD). To investigate independent risk factors for stroke in conservatively treated patients with MMD during a long-term follow-up. Prospective study. One hundred sixty conservatively managed patients with MMD (median age 46 years, 89 male). Time of flight, turbo inversion recovery magnitude T1WI, turbo spin echo (TSE) T2WI, echo-planar imaging DWI, T2-fluid attenuated inversion recovery, dynamic susceptibility contrast-magnetic resonance imaging, and pre- and post-contrast 3D TSE T1WI sequences at 3.0 Tesla. Patients were assessed at baseline and followed yearly. Ischemic and hemorrhagic stroke incidence rates were determined. Multiple demographic, clinical (modified Rankin score [mRS]), and cerebral imaging (cerebral blood volume [CBV] and concentric enhancement of arterial wall) factors at baseline were considered as potential predictors of stroke during the follow-up period. Univariable and multivariable Cox proportional hazards models to calculate the hazard ratios (HRs) and corresponding 95% confidence interval (CI) for stroke. Cumulative risk of stroke was estimated by the Kaplan-Meier product-limit method. A P value <0.05 was considered statistically significant. The median follow-up duration was 47 months. During the follow-up period, 18 (11.25%) patients experienced stroke events (13 [8.13%] ischemic, 5 [3.12%] hemorrhagic). Univariable analysis showed that 11 factors were significantly associated with stroke. After adjustment for clinical characteristics, multivariable analysis showed that mRS score ≥3 (HR, 1.99; 95% CI, 1.26-3.14), decreased CBV (HR, 5.31; 95% CI, 2.32-12.13), and concentric enhancement of the arterial wall (HR, 4.16; 95% CI, 1.55-11.15) were significantly associated with stroke. Decreased CBV, mRS score ≥ 3, and concentric enhancement of the arterial wall were significantly associated with increased incidence of stroke in conservatively treated MMD. 2 TECHNICAL EFFICACY: Stage 4.

Using carpet plots to analyze blood transit times in the brain during hypercapnic challenge magnetic resonance imaging.

Blood arrival time and blood transit time are useful metrics in characterizing hemodynamic behaviors in the brain. Functional magnetic resonance imaging in combination with a hypercapnic challenge has been proposed as a non-invasive imaging tool to determine blood arrival time and replace dynamic susceptibility contrast (DSC) magnetic resonance imaging, a current gold-standard imaging tool with the downsides of invasiveness and limited repeatability. Using a hypercapnic challenge, blood arrival times can be computed by cross-correlating the administered CO2 signal with the fMRI signal, which increases during elevated CO2 due to vasodilation. However, whole-brain transit times derived from this method can be significantly longer than the known cerebral transit time for healthy subjects (nearing 20s vs. the expected 5-6s). To address this unrealistic measurement, we here propose a novel carpet plot-based method to compute improved blood transit times derived from hypercapnic blood oxygen level dependent fMRI, demonstrating that the method reduces estimated blood transit times to an average of 5.32s. We also investigate the use of hypercapnic fMRI with cross-correlation to compute the venous blood arrival times in healthy subjects and compare the computed delay maps with DSC-MRI time to peak maps using the structural similarity index measure (SSIM). The strongest delay differences between the two methods, indicated by low structural similarity index measure, were found in areas of deep white matter and the periventricular region. SSIM measures throughout the remainder of the brain reflected a similar arrival sequence derived from the two methods despite the exaggerated spread of voxel delays computed using CO2 fMRI.

Image-to-image generative adversarial networks for synthesizing perfusion parameter maps from DSC-MR images in cerebrovascular disease.

Stroke is a major cause of death or disability. As imaging-based patient stratification improves acute stroke therapy, dynamic susceptibility contrast magnetic resonance imaging (DSC-MRI) is of major interest in image brain perfusion. However, expert-level perfusion maps require a manual or semi-manual post-processing by a medical expert making the procedure time-consuming and less-standardized. Modern machine learning methods such as generative adversarial networks (GANs) have the potential to automate the perfusion map generation on an expert level without manual validation. We propose a modified pix2pix GAN with a temporal component (temp-pix2pix-GAN) that generates perfusion maps in an end-to-end fashion. We train our model on perfusion maps infused with expert knowledge to encode it into the GANs. The performance was trained and evaluated using the structural similarity index measure (SSIM) on two datasets including patients with acute stroke and the steno-occlusive disease. Our temp-pix2pix architecture showed high performance on the acute stroke dataset for all perfusion maps (mean SSIM 0.92-0.99) and good performance on data including patients with the steno-occlusive disease (mean SSIM 0.84-0.99). While clinical validation is still necessary for future studies, our results mark an important step toward automated expert-level perfusion maps and thus fast patient stratification.

Comparative study between dynamic susceptibility contrast magnetic resonance imaging and arterial spin labelling perfusion in differentiating low-grade from high-grade brain tumours.

Our aim was to distinguish between low-grade and high-grade brain tumours on the basis of dynamic susceptibility contrast (DSC) magnetic resonance imaging (MRI) perfusion and arterial spin labelling (ASL) perfusion and to compare DSC and ASL techniques. Forty-one patients with brain tumours were evaluated by 3-Tesla MRI. Conventional and perfusion MRI imaging with a 3D pseudo-continuous ASL (PCASL) and DSC perfusion maps were evaluated. Three ROIs were placed to obtain cerebral blood value (CBV) and cerebral blood flow (CBF) in areas of maximum perfusion in brain tumour and normal grey matter. Histopathological diagnosis was considered as the reference. ROC analysis was performed to compare the diagnostic performance and to obtain a feasible cut-off value of perfusion parameters to differentiate low-grade and high-grade brain tumours. Normalised perfusion parameters with grey matter (rCBF or rCBV lesion/NGM) of malignant lesions were significantly higher than those of benign lesions in both DSC (normalised rCBF of 2.16 and normalised rCBV of 2.63) and ASL (normalised rCBF of 2.22) perfusion imaging. The normalised cut-off values of DSC (rCBF of 1.1 and rCBV of 1.4) and ASL (rCBF of 1.3) showed similar specificity and near similar sensitivity in distinguishing low-grade and high-grade brain tumours. Quantitative analysis of perfusion parameters obtained by both DSC and ASL perfusion techniques can be reliably used to distinguish low-grade and high-grade brain tumours. Normalisation of these values by grey matter gives us more reliable parameters, eliminating the different technical parameters involved in both the techniques.