Delay correction for the assessment of blood-brain barrier permeability using first-pass dynamic perfusion CT.

SUMMARY: Hemorrhagic transformation is a serious potential complication of ischemic stroke with damage to the BBB as one of the contributing mechanisms. BBB permeability measurements extracted from PCT by using the Patlak model can provide a valuable assessment of the extent of BBB damage. Unfortunately, Patlak assumptions require extended PCT acquisition, increasing the risk of motion artifacts. A necessary correction is presented for obtaining accurate BBB permeability measurements from first-pass PCT.

Blood-brain barrier permeability assessed by perfusion CT predicts symptomatic hemorrhagic transformation and malignant edema in acute ischemic stroke.

BACKGROUND AND PURPOSE: SHT and ME are feared complications in patients with acute ischemic stroke. They occur >10 times more frequently in tPA-treated versus placebo-treated patients. Our goal was to evaluate the sensitivity and specificity of admission BBBP measurements derived from PCT in predicting the development of SHT and ME in patients with acute ischemic stroke. MATERIALS AND METHODS: We retrospectively analyzed a dataset consisting of 32 consecutive patients with acute ischemic stroke with appropriate admission and follow-up imaging. We calculated admission BBBP by using delayed-acquisition PCT data and the Patlak model. Collateral flow was assessed on the admission CTA, while recanalization and reperfusion were assessed on the follow-up CTA and PCT, respectively. SHT and ME were defined according to ECASS III criteria. Clinical data were obtained from chart review. In our univariate and forward selection-based multivariate analysis for predictors of SHT and ME, we incorporated both clinical and imaging variables, including age, admission NIHSS score, admission blood glucose level, admission blood pressure, time from symptom onset to scanning, treatment type, admission PCT-defined infarct volume, admission BBBP, collateral flow, recanalization, and reperfusion. Optimal sensitivity and specificity for SHT and ME prediction were calculated by using ROC analysis. RESULTS: In our sample of 32 patients, 3 developed SHT and 3 developed ME. Of the 3 patients with SHT, 2 received IV tPA, while 1 received IA tPA and treatment with the Merci device; of the 3 patients with ME, 2 received IV tPA, while 1 received IA tPA and treatment with the Merci device. Admission BBBP measurements above the threshold were 100% sensitive and 79% specific in predicting SHT and ME. Furthermore, all patients with SHT and ME--and only those with SHT and ME--had admission BBBP measurements above the threshold, were older than 65 years of age, and received tPA. Admission BBBP, age, and tPA were the independent predictors of SHT and ME in our forward selection-based multivariate analysis. Of these 3 variables, only BBBP measurements and age were known before making the decision of administering tPA and thus are clinically meaningful. CONCLUSIONS: Admission BBBP, a pretreatment measurement, was 100% sensitive and 79% specific in predicting SHT and ME.

Dynamic perfusion-CT assessment of early changes in blood brain barrier permeability of acute ischaemic stroke patients.

BACKGROUND AND PURPOSE: Damage to the blood brain barrier (BBB) may lead to haemorrhagic transformation after ischaemic stroke. The purpose of this study was to evaluate the effect of patient characteristics and stroke severity on admission BBB permeability (BBBP) values measured with perfusion-CT (PCT) in acute ischaemic stroke patients. METHODS: We retrospectively identified 65 patients with proven ischaemic stroke admitted within 12 hours after symptom onset. Patients' charts were reviewed for demographic variables and vascular risk factors. The Patlak's model was applied to calculate BBBP values from the PCT data in the infarct core, penumbra and non-ischaemic tissue in the contralateral hemisphere. Mean BBBP values and their 95% confidence intervals (CI) were calculated in the different tissue types. Effects of demographic variables and risk factors on BBBP were analyzed using a multivariate, generalized estimating equations (GEE) model. RESULTS: BBBP values in the infarct core (mean [95%CI]: 2.48 [2.16-2.85]) and penumbra (2.48 [2.21-2.79]) were significantly higher than in non-ischaemic tissue (2.12 [1.88-2.39]). Multivariate analysis demonstrated that collateral filling has effect on BBBP. Less elevated BBBP values were associated with more than 50% collateral filling. CONCLUSIONS: BBBP values are increased in ischaemic brain tissue on the admission PCT scan of acute ischaemic stroke patients. Less abnormally elevated BBBP values were observed in patients with more than 50% collateral filling, possibly explaining why there is a relationship between more collateral filling and a lower incidence of haemorrhagic transformation.

Optimal duration of acquisition for dynamic perfusion CT assessment of blood-brain barrier permeability using the Patlak model.

BACKGROUND AND PURPOSE: A previous study demonstrated the need to use delayed acquisition rather than first-pass data for accurate blood-brain barrier permeability surface product (BBBP) calculation from perfusion CT (PCT) according to the Patlak model, but the optimal duration of the delayed acquisition has not been established. Our goal was to determine the optimal duration of the delayed PCT acquisition to obtain accurate BBBP measurements while minimizing potential motion artifacts and radiation dose. MATERIALS AND METHODS: We retrospectively identified 23 consecutive patients with acute ischemic anterior circulation stroke who underwent a PCT study with delayed acquisition. The Patlak model was applied for the full delayed acquisition (90-240 seconds) and also for truncated analysis windows (90-210, 90-180, 90-150, 90-120 seconds). Linear regression of Patlak plots was performed separately for the full and truncated analysis windows, and the slope of these regression lines was used to indicate BBBP. The full and truncated analysis windows were compared in terms of the resulting BBBP values and the quality of the Patlak fitting. RESULTS: BBBP values in the infarct and penumbra were similar for the full 90- to 240-second acquisition (95% confidence intervals for the infarct and penumbra: 1.62-2.47 and 1.75-2.41 mL x100 g(-1) x min(-1), respectively) and the 90- to 210-second analysis window (1.82-2.76 and 2.01-2.74 mL x 100 g(-1) x min(-1), respectively). BBBP values increased significantly with shorter acquisitions. The quality of the Patlak fit was excellent for the full 90- to 240-second and 90- to 210-second acquisitions, but it degraded with shorter acquisitions. CONCLUSIONS: The duration for the delayed PCT acquisition should be at least 210 seconds, because acquisitions shorter than 210 seconds lead to significantly overestimated BBBP values.

Quantification of blood flow from rotational angiography.

For assessment of cerebrovascular diseases, it is beneficial to obtain three-dimensional (3D) information on vessel morphology and hemodynamics. Rotational angiography is routinely used to determine the 3D geometry and we propose a method to exploit the same acquisition to determine the blood flow waveform and the mean volumetric flow rate. The method uses a model of contrast agent dispersion to determine the flow parameters from the spatial and temporal development of the contrast agent concentration, represented by a flow map. Furthermore, it also overcomes artifacts due to the rotation of the c-arm using a newly introduced reliability map. The method was validated on images from a computer simulation and from a phantom experiment. With a mean error of 11.0% for the mean volumetric flow rate and 15.3% for the blood flow waveform from the phantom experiments, we conclude that the method has the potential to give quantitative estimates of blood flow parameters during cerebrovascular interventions.

On the design of active contours for medical image segmentation. A Scheme for Classification and construction.

OBJECTIVES: To provide a comprehensive bottom-up categorization of model-based segmentation techniques that allows to select, implement, and apply well-suited active contour models for segmentation of medical images, where major challenges are the high variability in shape and appearance of objects, noise, artifacts, partial occlusions of objects, and the required reliability and correctness of results. METHODS: We consider the general purpose of segmentation, the dimension of images, the object representation within the model, image and contour influences, as well as the solution and the parameter selection of the model. Potentials and limits are characterized for all instances in each category providing essential information for the application of active contours to various purposes in medical image processing. Based on prolops surgery planning, we exemplify the use of the scheme to successfully design robust 3D-segmentation. RESULTS: The construction scheme allows to design robust segmentation methods, which, in particular, should avoid any gaps of dimension. Such gaps result from different image domains and value ranges with respect to the applied model domain and the dimension of relevant subsets for image influences, respectively. CONCLUSIONS: A general segmentation procedure with sufficient robustness for medical applications is still missing. It is shown that in almost every category, novel techniques are available to improve the initial snake model, which was introduced in 1987.

Computer-assisted quantification of axo-somatic boutons at the cell membrane of motoneurons.

This paper presents a system for computer-assisted quantification of axo-somatic boutons at motoneuron cell-surface membranes. Different immunohistochemical stains can be used to prepare tissue of the spinal cord. Based on micrographs displaying single neurons, a finite element balloon model has been applied to determine the exact location of the cell membrane. A synaptic profile is extracted next to the cell membrane and normalized with reference to the intracellular brightness. Furthermore, a manually selected reference cell is used to normalize settings of the microscope as well as variations in histochemical processing for each stain. Thereafter, staining, homogeneity, and allocation of boutons are determined automatically from the synaptic profiles. The system is evaluated by applying the coefficient of variation (Cv) to repeated measurements of a quantity. Based on 1856 motoneuronal images acquired from four animals with three stains, 93% of the images are analyzed correctly. The others were rejected, based on process protocols. Using only rabbit anti-synaptophysin as primary antibody, the correctness increases above 96%. Cv values are below 3%, 5%, and 6% for all measures with respect to stochastic optimization, cell positioning, and a large range of microscope settings, respectively. A sample size of about 100 is required to validate a significant reduction of staining in motoneurons below a hemi-section (Wilcoxon rank-sum test, alpha = 0.05, beta = 0.9). Our system yields statistically robust results from light micrographs. In future, it is hoped that this system will substitute for the expensive and time-consuming analysis of spinal cord injury at the ultra-structural level, such as by manual interpretation of nonoverlapping electron micrographs.