Wojciech Ambrosius

Automatic model-guided segmentation of the human brain ventricular system from CT images.

RATIONALE AND OBJECTIVES Accurate segmentation of the brain ventricular system on computed tomographic (CT) imaging is useful in neurodiagnosis and neurosurgery. Manual segmentation is time consuming, usually not reproducible, and subjective. Because of image noise, low contrast between soft tissues, large interslice distance, large shape, and size variations of the ventricular system, no automatic method is presently available. The authors propose a model-guided method for the automated segmentation of the ventricular system. MATERIALS AND METHODS Fifty CT scans of patients with strokes at different sites were collected for this study. Given a brain CT image, its ventricular system was segmented in five steps: (1) a predefined volumetric model was registered (or deformed) onto the image; (2) according to the deformed model, eight regions of interest were automatically specified; (3) the intensity threshold of cerebrospinal fluid was calculated in a region of interest and used to segment all regions of cerebrospinal fluid from the entire brain volume; (4) each ventricle was segmented in its specified region of interest; and (5) intraventricular calcification regions were identified to refine the ventricular segmentation. RESULTS Compared to ground truths provided by experts, the segmentation results of this method achieved an average overlap ratio of 85% for the entire ventricular system. On a desktop personal computer with a dual-core central processing unit running at 2.13 GHz, about 10 seconds were required to analyze each data set. CONCLUSION Experiments with clinical CT images showed that the proposed method can generate acceptable results in the presence of image noise, large shape, and size variations of the ventricular system, and therefore it is potentially useful for the quantitative interpretation of CT images in neurodiagnosis and neurosurgery.

Automatic Segmentation of Cerebrospinal Fluid, White and Gray Matter in Unenhanced Computed Tomography Images

RATIONALE AND OBJECTIVES Although segmentation algorithms for cerebrospinal fluid (CSF), white matter (WM), and gray matter (GM) on unenhanced computed tomographic (CT) images exist, there is no complete research in this area. To take into account poor image contrast and intensity variability on CT scans, the aim of this study was to derive and validate a novel, automatic, adaptive, and robust algorithm. MATERIALS AND METHODS Unenhanced CT scans of normal subjects from two different centers were used. The algorithm developed uses adaptive thresholding, connectivity, and domain knowledge and is based on heuristics on the shape of CT histogram. The slope of the intensity histogram corresponding to the three-dimensional largest connected region in a variable CSF intensity range is tracked to determine the critical intensity, which serves as an initial classifier of CSF-WM. Thresholds of CSF, WM, and GM are then optimally derived to minimize classification overlap. Multiple, null, and erroneous classifications are resolved by applying domain knowledge. RESULTS The ground-truth regions with the minimal partial volume effect were used to evaluate segmentation results using the statistical markers. Average sensitivity, Dice index, and specificity, respectively, for the first center were 95.7%, 97.0%, and 98.6% for CSF; 96.1%, 97.3%, and 98.8% for WM; and 95.2%, 94.3%, and 92.8% for GM. The results were consistent for the second data center. CONCLUSIONS The algorithm automatically identifies CSF, WM, and GM on unenhanced CT images with high accuracy, is robust to data from different scanners, does not require any parameter setting, and takes about 5 minutes in MATLAB to process a 512 × 512 × 30 scan. The algorithm has potential use in research and clinical applications.

Anti-inflammatory cytokines in subclinical carotid atherosclerosis

Some studies have shown correlations between selected proinflammatory factors and carotid atherosclerosis. It has not been established whether anti-inflammatory cytokines are associated with carotid intima–media thickness (IMT), an ultrasound surrogate marker of atherosclerosis. Therefore, the authors studied the relationship between the carotid IMT and serum levels of interleukin (IL)-10 and transforming growth factor-β1 in 76 subjects. They discovered that lower IL-10 levels were associated with increased mean IMT in common carotid arteries.

The Early Effect of Carotid Artery Stenting on Antioxidant Capacity and Oxidative Stress in Patients with Carotid Artery Stenosis

The treatment of carotid artery stenosis is associated with the risk of complications, which may include stroke after carotid artery stenting (CAS) and myocardial infarction after carotid endarterectomy (CEA). The imbalance between prooxidative mechanisms and antioxidant capacity creates a milieu of factors, which may increase the risk of complications after endovascular procedures. We have examined 43 consecutive patients with carotid artery stenosis. Sera were analyzed for the activity of paraoxonase (PON) and arylesterase (ARE), sulfhydryl groups (SG), malondialdehyde (MDA), and conjugated dienes (CD) concentrations by means of spectrophotometric methods before and next day after CAS. We have found lowered PON (P = 0.0032), increase in ARE activity (P = 0.0058), and decrease in sulfhydryl groups concentration (P = 0.0267). No effect on absolute MDA and CD concentrations was observed. The degree of carotid artery stenosis correlated negatively with PON/ARE ratio after CAS (r S = −0.507, P = 0.0268). To conclude, CAS influences both enzymatic (differently, PON and ARE activity) and nonenzymatic antioxidant defense. Females are more susceptible to lipid peroxidation after CAS. PON/ARE ratio after CAS correlated with the degree of carotid artery stenosis. The changes (deltas) in ARE activity, SG, and MDA concentrations correlated with the severity of neurological deficit and disability.

Population-Based Stroke Atlas for Outcome Prediction: Method and Preliminary Results for Ischemic Stroke from CT

Background and Purpose Knowledge of outcome prediction is important in stroke management. We propose a lesion size and location-driven method for stroke outcome prediction using a Population-based Stroke Atlas (PSA) linking neurological parameters with neuroimaging in population. The PSA aggregates data from previously treated patients and applies them to currently treated patients. The PSA parameter distribution in the infarct region of a treated patient enables prediction. We introduce a method for PSA calculation, quantify its performance, and use it to illustrate ischemic stroke outcome prediction of modified Rankin Scale (mRS) and Barthel Index (BI). Methods The preliminary PSA was constructed from 128 ischemic stroke cases calculated for 8 variants (various data aggregation schemes) and 3 case selection variables (infarct volume, NIHSS at admission, and NIHSS at day 7), each in 4 ranges. Outcome prediction for 9 parameters (mRS at 7th, and mRS and BI at 30th, 90th, 180th, 360th day) was studied using a leave-one-out approach, requiring 589,824 PSA maps to be analyzed. Results Outcomes predicted for different PSA variants are statistically equivalent, so the simplest and most efficient variant aiming at parameter averaging is employed. This variant allows the PSA to be pre-calculated before prediction. The PSA constrained by infarct volume and NIHSS reduces the average prediction error (absolute difference between the predicted and actual values) by a fraction of 0.796; the use of 3 patient-specific variables further lowers it by 0.538. The PSA-based prediction error for mild and severe outcomes (mRS = [2]–[5]) is (0.5–0.7). Prediction takes about 8 seconds. Conclusions PSA-based prediction of individual and group mRS and BI scores over time is feasible, fast and simple, but its clinical usefulness requires further studies. The case selection operation improves PSA predictability. A multiplicity of PSAs can be computed independently for different datasets at various centers and easily merged, which enables building powerful PSAs over the community.

The Markers of Glutamate Metabolism in Peripheral Blood Mononuclear Cells and Neurological Complications in Lung Cancer Patients

Objective. To evaluate the involvement of glutamate metabolism in peripheral blood mononuclear cells (PBMC) in the development of neurological complications in lung cancer and during chemotherapy. Methods. The prospective study included 221 lung cancer patients treated with chemotherapeutics. Neurological status and cognitive functions were evaluated at baseline and after 6-month follow-up. Glutamate level, the activities of glutaminase- (GLS-) glutamate synthetizing enzyme, glutamate dehydrogenase (GDH), and glutamate decarboxylase catalyzing glutamate degradation were analyzed in PBMC and in sera of lung cancer patients by means of spectrophotometric and colorimetric methods. Results. Chemotherapy of lung neoplasms induced increase of glutamate content in PBMC and its concentration in serum increased the activity of GDH in PBMC and decreased activity of glutaminase in PBMC. The changes in glutamate metabolism markers were associated with initial manifestation of neurological deficit in lung cancer patients and with new symptoms, which appear as a complication of chemotherapy. Moreover, the analyzed parameters of glutamate control correlated with a spectrum of cognitive functions measures in lung cancer patients. Conclusion. We have demonstrated dysregulation in glutamate and glutamate metabolism controlling enzymes as promising indicators of risk for chemotherapy-induced neurological complications in lung cancer patients with particular emphasis on cognitive impairment.

Zastosowanie ultrasonografii przezczaszkowej typu duplex w diagnostyce chorób pozapiramidowych

Streszczenie Rutynowo stosowane metody obrazowania ukladu nerwowego, takie jak tomografia komputerowa i tomografia rezonansu magnetycznego, sluzą glownie do wykluczania wtornych przyczyn schorzen pozapiramidowych. Nie są jednak istotnie przydatne w wykrywaniu zmian w obrebie jąder podstawy i pnia mozgu, szczegolnie we wczesnym okresie wystąpienia objawow idiopatycznych postaci tych chorob. Ostatnio podjeto proby stosowania przezczaszkowej ultrasonografii metodą duplex w diagnostyce obrazowej jąder podstawy. Metoda ta, z powodzeniem wykorzystywana w chorobach naczyn mozgu, pozwala takze uwidocznic niektore struktury miązszowe mozgowia. W pracy przedstawiono najwazniejsze odkrycia dotyczące obserwowanych w badaniu ultrasonograficznym zaburzen określonych struktur, w szczegolności hiperechogeniczności w obrebie istoty czarnej towarzyszącej chorobie Parkinsona.

Predictive value of serum transthyretin for outcome in acute ischemic stroke

Introduction The impact of choroid plexus with its blood–cerebrospinal fluid barrier in the ischemic stroke pathology is poorly explored. Transthyretin (TTR) is a protein synthesized in liver and just in choroid plexus. Objectives The current study was designed to assess the prognostic value of serum TTR for functional outcome (at the time of hospital discharge) and long-term (one-year) overall mortality in ischemic stroke patients. Patients and methods We conducted a prospective observational study. Patients (n = 81) with acute (< 24 hours of symptoms onset) ischemic stroke consecutively admitted to Stroke Unit were included. An unfavorable outcome was defined as a modified Rankin Scale (mRS) score ≥ 3. The relationships between serum TTR levels and clinical outcome were analyzed using multivariate analysis. One-year mortality was analyzed by Kaplan–Meier survival curves stratified by mean value of TTR. Results Compared with patients with mRS <3, patients with an unfavorable outcome at hospital discharge had significantly lower TTR levels on admission (P < 0.0001). In non-survivals serum TTR levels were significantly lower compared with patients who survive one year of observation (P = 0.009). Using multivariate analysis, transthyretin emerged as an independent predictor for unfavorable outcome at the day of hospital discharge (adjusted odds ratio = 0.96; 95% CI: 0.9–0.99, P <0.05). A one-year mortality of patients with the lower TTR levels was significantly higher than in patients with TTR levels above mean value (P = 0.02). Conclusions Serum level of TTR at admission was a predictor of functional outcome after ischemic stroke and was also associated with one-year mortality in stroke survivals.

Mitochondrial Respiration in Intact Peripheral Blood Mononuclear Cells and Sirtuin 3 Activity in Patients with Movement Disorders

Objective Mitochondrial dysfunction is considered a unifying pathophysiological explanation for movement disorders. Sirtuin 3 (SIRT3) exhibits deacetylase activity and antioxidant properties. The aim of the study was to analyze the mitochondrial respiration in peripheral blood mononuclear cells (PBMCs) and the SIRT3 activity in patients with movement disorders. Methods Mitochondrial respiration was analyzed in intact PBMCs using the ROUTINE, LEAK, electron transfer system (ETS), and residual oxygen consumption (ROX) protocol by means of high-resolution respirometry. The SIRT3 expression and PBMC activity were measured using fluorometry. Ultrasound measurements of the echogenicity of the substantia nigra and the diameter of the 3rd ventricle were also performed. Results Patients with movement disorders exhibited a lower ROUTINE respiration than controls (P = 0.0237). Reduced oxygen fluxes in the LEAK (P = 0.033) and ROX (P = 0.0486) states were observed in patients with movement disorders compared with controls. Decreased ROUTINE respiration (P = 0.007) and oxygen flux in the LEAK state (P = 0.0203) were observed in patients with PD with substantia nigra hyperechogenicity compared with controls. Decreased SIRT 3 deacetylase activity was found in patients with movement disorders. Conclusion Impaired mitochondrial respiration in intact PBMCs was associated with inhibited SIRT3 activity and neurodegeneration measures evaluated using ultrasound in patients with PD.