Functional connectivity in resting-state networks relates to short-term global cognitive functioning in cardiac arrest survivors.

Long-term cognitive impairment is common in cardiac arrest survivors. Screening to identify patients at risk is recommended. Functional magnetic resonance brain imaging (fMRI) holds potential to contribute to prediction of cognitive outcomes. In this study, we investigated the possible value of early changes in resting-state networks for predicting short and long-term cognitive functioning of cardiac arrest survivors. We performed a prospective multicenter cohort study in cardiac arrest survivors in three Dutch hospitals. Resting-state fMRI scans were acquired within a month after cardiac arrest. We primarily focused on functional connectivity within the default-mode network (DMN) and salience network (SN), and additionally explored functional connectivity in seven other networks. Cognitive outcome was measured using the Montreal Cognitive Assessment (MoCA) during hospital admission and at 3 and 12 months, and by neuropsychological examination (NPE) at 12 months. We tested mixed effects models to evaluate the value of connectivity within the networks for predicting global cognitive outcomes at the three time points, and long-term cognitive outcomes in the memory, attention, and executive functioning domains. We included 80 patients (age 60 ± 11 years, 72 (90%) male). MoCA scores increased significantly between hospital admission and 3 months (ΔMoCAhospital-3M = 2.89, p < 0.01), but not between 3 and 12 months (ΔMoCA3M-12M = 0.38, p = 0.52). Connectivity within the DMN, SN, and dorsal attention network (DAN) was positively related to global cognitive functioning during hospital admission (ßDMN = 0.85, p = 0.03; ßSN = 1.48, p < 0.01; ßDAN = 0.96, p = 0.01), but not at 3 and 12 months. Network connectivity was also unrelated to long-term memory, attention, or executive functioning. Resting-state functional connectivity in the DMN, SN, and DAN measured in the first month after cardiac arrest is related to short-term global, but not long-term global or domain-specific cognitive performance of survivors. These results do not support the value of functional connectivity within these RSNs for prediction of long-term cognitive performance after cardiac arrest.

How to evaluate perfusion imaging in post-treatment glioma: a comparison of three different analysis methods.

INTRODUCTION: Dynamic susceptibility contrast (DSC) perfusion weighted (PW)-MRI can aid in differentiating treatment related abnormalities (TRA) from tumor progression (TP) in post-treatment glioma patients. Common methods, like the 'hot spot', or visual approach suffer from oversimplification and subjectivity. Using perfusion of the complete lesion potentially offers an objective and accurate alternative. This study aims to compare the diagnostic value and assess the subjectivity of these techniques. METHODS: 50 Glioma patients with enhancing lesions post-surgery and chemo-radiotherapy were retrospectively included. Outcome was determined by clinical/radiological follow-up or biopsy. Imaging analysis used the 'hot spot', volume of interest (VOI) and visual approach. Diagnostic accuracy was compared using receiving operator characteristics (ROC) curves for the VOI and 'hot spot' approach, visual assessment was analysed with contingency tables. Inter-operator agreement was determined with Cohens kappa and intra-class coefficient (ICC). RESULTS: 29 Patients suffered from TP, 21 had TRA. The visual assessment showed poor to substantial inter-operator agreement (κ = -0.72 - 0.68). Reliability of the 'hot spot' placement was excellent (ICC = 0.89), while reference placement was variable (ICC = 0.54). The area under the ROC (AUROC) of the mean- and maximum relative cerebral blood volume (rCBV) (VOI-analysis) were 0.82 and 0.72, while the rCBV-ratio ('hot spot' analysis) was 0.69. The VOI-analysis had a more balanced sensitivity and specificity compared to visual assessment. CONCLUSIONS: VOI analysis of DSC PW-MRI data holds greater diagnostic accuracy in single-moment differentiation of TP and TRA than 'hot spot' or visual analysis. This study underlines the subjectivity of visual placement and assessment.

Prevalence and 3-month follow-up of cerebrovascular MRI markers in hospitalized COVID-19 patients: the CORONIS study.

PURPOSE: To investigate the prevalence of cerebrovascular MRI markers in unselected patients hospitalized for COVID-19 (Coronavirus disease 2019), we compared these with healthy controls without previous SARS-CoV-2 infection or hospitalization and subsequently, investigated longitudinal (incidental) lesions in patients after three months. METHODS: CORONIS (CORONavirus and Ischemic Stroke) was an observational cohort study in adult hospitalized patients for COVID-19 and controls without COVID-19, conducted between April 2021 and September 2022. Brain MRI was performed shortly after discharge and after 3 months. Outcomes included recent ischemic (DWI-positive) lesions, previous infarction, microbleeds, white matter hyperintensities (WMH) and intracerebral hemorrhage and were analysed with logistic regression to adjust for confounders. RESULTS: 125 patients with COVID-19 and 47 controls underwent brain MRI a median of 41.5 days after symptom onset. DWI-positive lesions were found in one patient (1%) and in one (2%) control, both clinically silent. WMH were more prevalent in patients (78%) than in controls (62%) (adjusted OR: 2.95 [95% CI: 1.07-8.57]), other cerebrovascular MRI markers did not differ. Prevalence of markers in ICU vs. non-ICU patients was similar. After three months, five patients (5%) had new cerebrovascular lesions, including DWI-positive lesions (1 patient, 1.0%), cerebral infarction (2 patients, 2.0%) and microbleeds (3 patients, 3.1%). CONCLUSION: Overall, we found no higher prevalence of cerebrovascular markers in unselected hospitalized COVID-19 patients compared to controls. The few incident DWI-lesions were most likely to be explained by risk-factors of small vessel disease. In the general hospitalized COVID-19 population, COVID-19 shows limited impact on cerebrovascular MRI markers shortly after hospitalization.

Safety and efficacy of aspirin, unfractionated heparin, both, or neither during endovascular stroke treatment (MR CLEAN-MED): an open-label, multicentre, randomised controlled trial.

BACKGROUND: Aspirin and unfractionated heparin are often used during endovascular stroke treatment to improve reperfusion and outcomes. However, the effects and risks of anti-thrombotics for this indication are unknown. We therefore aimed to assess the safety and efficacy of intravenous aspirin, unfractionated heparin, both, or neither started during endovascular treatment in patients with ischaemic stroke. METHODS: We did an open-label, multicentre, randomised controlled trial with a 2 × 3 factorial design in 15 centres in the Netherlands. We enrolled adult patients (ie, ≥18 years) with ischaemic stroke due to an intracranial large-vessel occlusion in the anterior circulation in whom endovascular treatment could be initiated within 6 h of symptom onset. Eligible patients had a score of 2 or more on the National Institutes of Health Stroke Scale, and a CT or MRI ruling out intracranial haemorrhage. Randomisation was done using a web-based procedure with permuted blocks and stratified by centre. Patients were randomly assigned (1:1) to receive either periprocedural intravenous aspirin (300 mg bolus) or no aspirin, and randomly assigned (1:1:1) to receive moderate-dose unfractionated heparin (5000 IU bolus followed by 1250 IU/h for 6 h), low-dose unfractionated heparin (5000 IU bolus followed by 500 IU/h for 6 h), or no unfractionated heparin. The primary outcome was the score on the modified Rankin Scale at 90 days. Symptomatic intracranial haemorrhage was the main safety outcome. Analyses were based on intention to treat, and treatment effects were expressed as odds ratios (ORs) or common ORs, with adjustment for baseline prognostic factors. This trial is registered with the International Standard Randomised Controlled Trial Number, ISRCTN76741621. FINDINGS: Between Jan 22, 2018, and Jan 27, 2021, we randomly assigned 663 patients; of whom, 628 (95%) provided deferred consent or died before consent could be asked and were included in the modified intention-to-treat population. On Feb 4, 2021, after unblinding and analysis of the data, the trial steering committee permanently stopped patient recruitment and the trial was stopped for safety concerns. The risk of symptomatic intracranial haemorrhage was higher in patients allocated to receive aspirin than in those not receiving aspirin (43 [14%] of 310 vs 23 [7%] of 318; adjusted OR 1·95 [95% CI 1·13-3·35]) as well as in patients allocated to receive unfractionated heparin than in those not receiving unfractionated heparin (44 [13%] of 332 vs 22 [7%] of 296; 1·98 [1·14-3·46]). Both aspirin (adjusted common OR 0·91 [95% CI 0·69-1·21]) and unfractionated heparin (0·81 [0·61-1·08]) led to a non-significant shift towards worse modified Rankin Scale scores. INTERPRETATION: Periprocedural intravenous aspirin and unfractionated heparin during endovascular stroke treatment are both associated with an increased risk of symptomatic intracranial haemorrhage without evidence for a beneficial effect on functional outcome. FUNDING: The Collaboration for New Treatments of Acute Stroke consortium, the Brain Foundation Netherlands, the Ministry of Economic Affairs, Stryker, Medtronic, Cerenovus, and the Dutch Heart Foundation.

Free water corrected diffusion tensor imaging discriminates between good and poor outcomes of comatose patients after cardiac arrest.

OBJECTIVES: Approximately 50% of comatose patients after cardiac arrest never regain consciousness. Cerebral ischaemia may lead to cytotoxic and/or vasogenic oedema, which can be detected by diffusion tensor imaging (DTI). Here, we evaluate the potential value of free water corrected mean diffusivity (MD) and fractional anisotropy (FA) based on DTI, for the prediction of neurological recovery of comatose patients after cardiac arrest. METHODS: A total of 50 patients after cardiac arrest were included in this prospective cohort study in two Dutch hospitals. DTI was obtained 2-4 days after cardiac arrest. Outcome was assessed at 6 months, dichotomised as poor (cerebral performance category 3-5; n = 20) or good (n = 30) neurological outcome. We calculated the whole brain mean MD and FA and compared between patients with good and poor outcomes. In addition, we compared a preliminary prediction model based on clinical parameters with or without the addition of MD and FA. RESULTS: We found significant differences between patients with good and poor outcome of mean MD (good: 726 [702-740] × 10-6 mm2/s vs. poor: 663 [575-736] × 10-6 mm2/s; p = 0.01) and mean FA (0.30 ± 0.03 vs. 0.28 ± 0.03; p = 0.03). An exploratory prediction model combining clinical parameters, MD and FA increased the sensitivity for reliable prediction of poor outcome from 60 to 85%, compared to the model containing clinical parameters only, but confidence intervals are overlapping. CONCLUSIONS: Free water-corrected MD and FA discriminate between patients with good and poor outcomes after cardiac arrest and hold the potential to add to multimodal outcome prediction. KEY POINTS: • Whole brain mean MD and FA differ between patients with good and poor outcome after cardiac arrest. • Free water-corrected MD can better discriminate between patients with good and poor outcome than uncorrected MD. • A combination of free water-corrected MD (sensitive to grey matter abnormalities) and FA (sensitive to white matter abnormalities) holds potential to add to the prediction of outcome.

Long-term cognitive, psychosocial, and neurovascular complications of unilateral head and neck irradiation in young to middle-aged adults.

BACKGROUND: With a growing, younger population of head and neck cancer survivors, attention to long-term side-effects of prior, often radiotherapeutic, treatment is warranted. Therefore, we studied the long-term cognitive effects in young adult patients irradiated for head and neck neoplasms (HNN). METHODS: Young to middle-aged adults with HNN (aged 18-40 years) and treated with unilateral neck irradiation ≥ 5 years before inclusion underwent cardiovascular risk and neuropsychological assessments and answered validated questionnaires regarding subjective cognitive complaints, fatigue, depression, quality of life, and cancer-specific distress. Additionally, magnetic resonance imaging (MRI) of the brain was performed to assess white matter hyperintensities (WMH), infarctions, and atrophy. RESULTS: Twenty-nine patients (aged 24-61, 13 men) median 9.2 [7.3-12.9] years post-treatment were included. HNN patients performed worse in episodic memory (Z-score = -1.16 [-1.58-0.34], p < 0.001) and reported more fatigue symptoms (Z-score = 1.75 [1.21-2.00], p < 0.001) compared to normative data. Furthermore, patients had a high level of fear of tumor recurrence (13 patients [44.8%]) and a heightened speech handicap index (13 patients [44.8%]). Only a small number of neurovascular lesions were found (3 infarctions in 2 patients and 0.11 [0.00-0.40] mL WMH), unrelated to the irradiated side. Cognitive impairment was not associated with WMH, brain atrophy, fatigue, or subjective speech problems. CONCLUSIONS: HNN patients showed impairments in episodic memory and an increased level of fatigue ≥ 5 years after radiotherapy compared to normative data. Cognitive impairments could not be explained by WMH or brain atrophy on brain MRI or psychological factors. TRIAL REGISTRATION: Clinicaltrials.gov ( https://clinicaltrials.gov/ct2/show/NCT04257968 ).

Contrast-induced encephalopathy-neuroimaging findings and clinical relevance.

Contrast-induced encephalopathy (CIE) is a rare encephalopathic condition after the administration of a contrast agent. The diagnosis of CIE is challenging because of the heterogeneity and non-specificity of the clinical presentation. The clinical course is usually favorable with full recovery within 48-72 h in most patients, although comorbidity is of relevance and contributes to the clinical outcome. It is expected that the incidence of CIE is currently increasing, due to an increase in endovascular and diagnostic imaging procedures using iodinated contrast. It is important to include CIE in the differential diagnosis when patients deteriorate during, or immediately after, contrast administration, even when only a small amount of non-ionic contrast agent is used. When CIE is considered to be the most likely explanation for the clinical symptoms, it is advised to refrain from unnecessary additional contrast studies such as angiography or perfusion CT.

Prognosis After Cardiac Arrest: The Additional Value of DWI and FLAIR to EEG.

BACKGROUND: Despite application of the multimodal European Resuscitation Council and European Society of Intensive Care Medicine algorithm, neurological prognosis of patients who remain comatose after cardiac arrest remains uncertain in a large group of patients. In this study, we investigate the additional predictive value of visual and quantitative brain magnetic resonance imaging (MRI) to electroencephalography (EEG) for outcome estimation of comatose patients after cardiac arrest. METHODS: We performed a prospective multicenter cohort study in patients after cardiac arrest submitted in a comatose state to the intensive care unit of two Dutch hospitals. Continuous EEG was recorded during the first 3 days and MRI was performed at 3 ± 1 days after cardiac arrest. EEG at 24 h and ischemic damage in 21 predefined brain regions on diffusion weighted imaging and fluid-attenuated inversion recovery on a scale from 0 to 4 were related to outcome. Quantitative MRI analyses included mean apparent diffusion coefficient (ADC) and percentage of brain volume with ADC < 450 × 10-6 mm2/s, < 550 × 10-6 mm2/s, and < 650 × 10-6 mm2/s. Poor outcome was defined as a Cerebral Performance Category score of 3-5 at 6 months. RESULTS: We included 50 patients, of whom 20 (40%) demonstrated poor outcome. Visual EEG assessment correctly identified 3 (15%) with poor outcome and 15 (50%) with good outcome. Visual grading of MRI identified 13 (65%) with poor outcome and 25 (89%) with good outcome. ADC analysis identified 11 (55%) with poor outcome and 3 (11%) with good outcome. EEG and MRI combined could predict poor outcome in 16 (80%) patients at 100% specificity, and good outcome in 24 (80%) at 63% specificity. Ischemic damage was most prominent in the cortical gray matter (75% vs. 7%) and deep gray nuclei (45% vs. 3%) in patients with poor versus good outcome. CONCLUSIONS: Magnetic resonance imaging is complementary with EEG for the prediction of poor and good outcome of patients after cardiac arrest who are comatose at admission.

Performance of machine learning algorithms for glioma segmentation of brain MRI: a systematic literature review and meta-analysis.

OBJECTIVES: Different machine learning algorithms (MLAs) for automated segmentation of gliomas have been reported in the literature. Automated segmentation of different tumor characteristics can be of added value for the diagnostic work-up and treatment planning. The purpose of this study was to provide an overview and meta-analysis of different MLA methods. METHODS: A systematic literature review and meta-analysis was performed on the eligible studies describing the segmentation of gliomas. Meta-analysis of the performance was conducted on the reported dice similarity coefficient (DSC) score of both the aggregated results as two subgroups (i.e., high-grade and low-grade gliomas). This study was registered in PROSPERO prior to initiation (CRD42020191033). RESULTS: After the literature search (n = 734), 42 studies were included in the systematic literature review. Ten studies were eligible for inclusion in the meta-analysis. Overall, the MLAs from the included studies showed an overall DSC score of 0.84 (95% CI: 0.82-0.86). In addition, a DSC score of 0.83 (95% CI: 0.80-0.87) and 0.82 (95% CI: 0.78-0.87) was observed for the automated glioma segmentation of the high-grade and low-grade gliomas, respectively. However, heterogeneity was considerably high between included studies, and publication bias was observed. CONCLUSION: MLAs facilitating automated segmentation of gliomas show good accuracy, which is promising for future implementation in neuroradiology. However, before actual implementation, a few hurdles are yet to be overcome. It is crucial that quality guidelines are followed when reporting on MLAs, which includes validation on an external test set. KEY POINTS: • MLAs from the included studies showed an overall DSC score of 0.84 (95% CI: 0.82-0.86), indicating a good performance. • MLA performance was comparable when comparing the segmentation results of the high-grade gliomas and the low-grade gliomas. • For future studies using MLAs, it is crucial that quality guidelines are followed when reporting on MLAs, which includes validation on an external test set.

Deep learning-based reconstruction may improve non-contrast cerebral CT imaging compared to other current reconstruction algorithms.

OBJECTIVES: To evaluate image quality and reconstruction times of a commercial deep learning reconstruction algorithm (DLR) compared to hybrid-iterative reconstruction (Hybrid-IR) and model-based iterative reconstruction (MBIR) algorithms for cerebral non-contrast CT (NCCT). METHODS: Cerebral NCCT acquisitions of 50 consecutive patients were reconstructed using DLR, Hybrid-IR and MBIR with a clinical CT system. Image quality, in terms of six subjective characteristics (noise, sharpness, grey-white matter differentiation, artefacts, natural appearance and overall image quality), was scored by five observers. As objective metrics of image quality, the noise magnitude and signal-difference-to-noise ratio (SDNR) of the grey and white matter were calculated. Mean values for the image quality characteristics scored by the observers were estimated using a general linear model to account for multiple readers. The estimated means for the reconstruction methods were pairwise compared. Calculated measures were compared using paired t tests. RESULTS: For all image quality characteristics, DLR images were scored significantly higher than MBIR images. Compared to Hybrid-IR, perceived noise and grey-white matter differentiation were better with DLR, while no difference was detected for other image quality characteristics. Noise magnitude was lower for DLR compared to Hybrid-IR and MBIR (5.6, 6.4 and 6.2, respectively) and SDNR higher (2.4, 1.9 and 2.0, respectively). Reconstruction times were 27 s, 44 s and 176 s for Hybrid-IR, DLR and MBIR respectively. CONCLUSIONS: With a slight increase in reconstruction time, DLR results in lower noise and improved tissue differentiation compared to Hybrid-IR. Image quality of MBIR is significantly lower compared to DLR with much longer reconstruction times. KEY POINTS: • Deep learning reconstruction of cerebral non-contrast CT results in lower noise and improved tissue differentiation compared to hybrid-iterative reconstruction. • Deep learning reconstruction of cerebral non-contrast CT results in better image quality in all aspects evaluated compared to model-based iterative reconstruction. • Deep learning reconstruction only needs a slight increase in reconstruction time compared to hybrid-iterative reconstruction, while model-based iterative reconstruction requires considerably longer processing time.

High sensitivity and specificity of 4D-CTA in the detection of cranial arteriovenous shunts.

PURPOSE: In a prospective cohort study, we evaluated the diagnostic accuracy of time-resolved CT angiography (4D-CTA) compared to digital subtraction angiography (DSA) for detecting cranial arteriovenous shunts. MATERIAL AND METHODS: Patients were enrolled if a DSA had been ordered querying either a dural arteriovenous fistula (dAVF) or a cerebral arteriovenous malformation (bAVM). After enrolment, both a DSA and a 4D-CTA were performed. Both studies were evaluated using a standardized form. If a dAVF or bAVM was found, its classification, angioarchitectural details, and treatment options were recorded. RESULTS: Ninety-eight patients were enrolled and 76 full datasets were acquired. DSA demonstrated a shunting lesion in 28 out of 76 cases (prevalence 37%). 4D-CTA demonstrated all but two of these lesions (sensitivity of 93%) and produced one false positive (specificity of 98%). These numbers yielded a positive predictive value (PPV) of 96% and a negative predictive value (NPV) of 96%. Significant doubt regarding the 4D-CTA diagnosis was reported in 6.6% of all cases and both false-negative 4D-CTA results were characterized by such doubt. CONCLUSIONS: 4D-CTA has very high sensitivity and specificity for the detection of intracranial arteriovenous shunts. Based on these results, 4D-CTA may replace DSA imaging as a first modality in the diagnostic workup in a large number of patients suspected of a cranial dAVF or bAVM, especially if there is no doubt regarding the 4D-CTA diagnosis. KEY POINTS: • 4D-CTA was shown to have a high diagnostic accuracy and is an appropriate, less invasive replacement for DSA as a diagnostic tool for cranial arteriovenous shunts in the majority of suspected cases. • Doubt regarding the 4D-CTA result should prompt additional DSA imaging, as it is associated with false negatives. • False-positive 4D-CTA results are rare, but do exist.

Diagnostic accuracy of flat-panel computed tomography in assessing cerebral perfusion in comparison with perfusion computed tomography and perfusion magnetic resonance: a systematic review.

PURPOSE: Flat-panel computed tomography (FP-CT) is increasingly available in angiographic rooms and hybrid OR's. Considering its easy access, cerebral imaging using FP-CT is an appealing modality for intra-procedural applications. The purpose of this systematic review is to assess the diagnostic accuracy of FP-CT compared with perfusion computed tomography (CTP) and perfusion magnetic resonance (MRP) in cerebral perfusion imaging. METHODS: We performed a systematic literature search in the Cochrane Library, MEDLINE, Embase, and Web of Science up to June 2019 for studies directly comparing FP-CT with either CTP or MRP in vivo. Methodological quality was assessed using the QUADAS-2 tool. Data on diagnostic accuracy was extracted and pooled if possible. RESULTS: We found 11 studies comparing FP-CT with CTP and 5 studies comparing FP-CT with MRP. Most articles were pilot or feasibility studies, focusing on scanning and contrast protocols. All patients studied showed signs of cerebrovascular disease. Half of the studies were animal trials. Quality assessment showed unclear to high risks of bias and low concerns regarding applicability. Five studies reported on diagnostic accuracy; FP-CT shows good sensitivity (range 0.84-1.00) and moderate specificity (range 0.63-0.88) in detecting cerebral blood volume (CBV) lesions. CONCLUSIONS: Even though FP-CT provides similar CBV values and reconstructed blood volume maps as CTP in cerebrovascular disease, additional studies are required in order to reliably compare its diagnostic accuracy with cerebral perfusion imaging.

Presence of inflammatory proteins S100A8 and S100A9 in a giant intracranial aneurysm after flow diverter treatment.

We demonstrate the presence of S100A8 and S100A9 proteins in the wall and thrombosed lumen of an enlarged intracranial aneurysm after flow diverter treatment. These proteins have shown to play an important role in vascular inflammation and may serve as a biomarker and potential therapeutic target for intracranial aneurysms.

Brain CT perfusion improves intracranial vessel occlusion detection on CT angiography.

BACKGROUND AND PURPOSE: To evaluate whether brain CT perfusion (CTP) aids in the detection of intracranial vessel occlusion on CT angiography (CTA) in acute ischemic stroke. MATERIALS AND METHODS: Medical-ethical committee approval of our hospital was obtained and informed consent was waived. Patients suspected of acute ischemic stroke who underwent non-contrast CT(NCCT), CTA and whole-brain CTP in our center in the year 2015 were included. Three observers with different levels of experience evaluated the imaging data of 110 patients for the presence or absence of intracranial arterial vessel occlusion with two strategies. In the first strategy, only NCCT and CTA were available. In the second strategy, CTP maps were provided in addition to NCCT and CTA. Receiver-operating-characteristic (ROC) analysis was used for the evaluation of diagnostic accuracy. RESULTS: Overall, a brain perfusion deficit was scored present in 87-89% of the patients with an intracranial vessel occlusion, more frequently observed in the anterior than in the posterior circulation. Performance of intracranial vessel occlusion detection on CTA was significantly improved with the availability of CTP maps as compared to the first strategy (P=0.023), due to improved detection of distal and posterior circulation vessel occlusions (P-values of 0.032 and 0.003 respectively). No added value of CTP was found for intracranial proximal vessel occlusion detection, with already high accuracy based on NCCT and CTA alone. CONCLUSION: The performance of intracranial vessel occlusion detection on CTA was improved with the availability of brain CT perfusion maps due to the improved detection of distal and posterior circulation vessel occlusions.

Observer variability of reference tissue selection for relativecerebral blood volume measurements in glioma patients.

OBJECTIVES: To assess observer variability of different reference tissues used for relative CBV (rCBV) measurements in DSC-MRI of glioma patients. METHODS: In this retrospective study, three observers measured rCBV in DSC-MR images of 44 glioma patients on two occasions. rCBV is calculated by the CBV in the tumour hotspot/the CBV of a reference tissue at the contralateral side for normalization. One observer annotated the tumour hotspot that was kept constant for all measurements. All observers annotated eight reference tissues of normal white and grey matter. Observer variability was evaluated using the intraclass correlation coefficient (ICC), coefficient of variation (CV) and Bland-Altman analyses. RESULTS: For intra-observer, the ICC ranged from 0.50-0.97 (fair-excellent) for all reference tissues. The CV ranged from 5.1-22.1 % for all reference tissues and observers. For inter-observer, the ICC for all pairwise observer combinations ranged from 0.44-0.92 (poor-excellent). The CV ranged from 8.1-31.1 %. Centrum semiovale was the only reference tissue that showed excellent intra- and inter-observer agreement (ICC>0.85) and lowest CVs (<12.5 %). Bland-Altman analyses showed that mean differences for centrum semiovale were close to zero. CONCLUSION: Selecting contralateral centrum semiovale as reference tissue for rCBV provides the lowest observer variability. KEY POINTS: • Reference tissue selection for rCBV measurements adds variability to rCBV measurements. • rCBV measurements vary depending on the choice of reference tissue. • Observer variability of reference tissue selection varies between poor and excellent. • Centrum semiovale as reference tissue for rCBV provides the lowest observer variability.

Parkinson's Disease Diagnostic Observations (PADDO): study rationale and design of a prospective cohort study for early differentiation of parkinsonism.

BACKGROUND: Differentiation of Parkinson's disease (PD) from the various types of atypical parkinsonism (AP) such as multiple system atrophy (MSA), progressive supranuclear palsy (PSP), dementia with Lewy bodies (DLB), corticobasal syndrome (CBS) and vascular parkinsonism (VP), can be challenging, especially early in the disease course when symptoms overlap. A major unmet need in the diagnostic workup of these disorders is a diagnostic tool that differentiates the various disorders, preferably in the earliest disease stages when the clinical presentation is similar. Many diagnostic tests have been evaluated, but their added value was studied mostly in retrospective case-control studies that included patients with a straightforward clinical diagnosis. Here, we describe the design of a prospective cohort study in patients with parkinsonism in an early disease stage who have an uncertain clinical diagnosis. Our aim is to evaluate the diagnostic accuracy of (1) detailed clinical examination by a movement disorder specialist, (2) magnetic resonance imaging (MRI) techniques and (3) cerebrospinal fluid (CSF) biomarkers. METHODS/DESIGN: Patients with parkinsonism with an uncertain clinical diagnosis and a disease course less than three years will be recruited. Patients will undergo extensive neurological examination, brain MRI including conventional and advanced sequences, and a lumbar puncture. The diagnosis (including level of certainty) will be defined by a movement disorders expert, neuroradiologist and neurochemist based on clinical data, MRI results and CSF results, respectively. The clinical diagnosis after three years' follow-up will serve as the "gold standard" reference diagnosis, based on consensus criteria and as established by two movement disorder specialists (blinded to the test results). Diagnostic accuracy of individual instruments and added value of brain MRI and CSF analysis after evaluation by a movement disorder expert will be calculated, expressed as the change in percentage of individuals that are correctly diagnosed with PD or AP. DISCUSSION: This study will yield new insights into the diagnostic value of clinical evaluation by a movement disorder specialist, brain MRI and CSF analysis in discriminating PD from AP in early disease stages. The outcome has the potential to help clinicians in choosing the optimal diagnostic strategy for patients with an uncertain clinical diagnosis. TRIAL REGISTRATION: NCT01249768, registered November 26 2010.

Interleaving cerebral CT perfusion with neck CT angiography part I. Proof of concept and accuracy of cerebral perfusion values.

OBJECTIVES: We present a novel One-Step-Stroke protocol for wide-detector CT scanners that interleaves cerebral CTP with volumetric neck CTA (vCTA). We evaluate whether the resulting time gap in CTP affects the accuracy of CTP values. METHODS: Cerebral CTP maps were retrospectively obtained from 20 patients with suspicion of acute ischemic stroke and served as the reference standard. To simulate a 4 s gap for interleaving CTP with vCTA, we eliminated one acquisition at various time points of CTP starting from the bolus-arrival-time(BAT). Optimal timing of the vCTA was evaluated. At the time point with least errors, we evaluated elimination of a second time point (6 s gap). RESULTS: Mean absolute percentage errors of all perfusion values remained below 10 % in all patients when eliminating any one time point in the CTP sequence starting from the BAT. Acquiring the vCTA 2 s after reaching a threshold of 70HU resulted in the lowest errors (mean <3.0 %). Eliminating a second time point still resulted in mean errors <3.5 %. CBF/CBV showed no significant differences in perfusion values except MTT. However, the percentage errors were always below 10 % compared to the original protocol. CONCLUSION: Interleaving cerebral CTP with neck CTA is feasible with minor effects on the perfusion values. KEY POINTS: • Removing a single CTP acquisition has minor effects on calculated perfusion values • Calculated perfusion values errors depend on timing of skipping a CTP acquisition • Qualitative evaluation of CTP was not influenced by removing two time points • Neck CTA is optimally timed in the upslope of arterial enhancement.