Iron-based biomarkers for personalizing pharmacological ascorbate therapy in glioblastoma: insights from a phase 2 clinical trial.

BACKGROUND: Pharmacological ascorbate (intravenous delivery reaching plasma concentrations ≈ 20 mM; P-AscH-) has emerged as a promising therapeutic strategy for glioblastoma. Recently, a single-arm phase 2 clinical trial demonstrated a significant increase in overall survival when P-AscH- was combined with temozolomide and radiotherapy. As P-AscH- relies on iron-dependent mechanisms, this study aimed to assess the predictive potential of both molecular and imaging-based iron-related markers to enhance the personalization of P-AscH- therapy in glioblastoma participants. METHODS: Participants (n = 55) with newly diagnosed glioblastoma were enrolled in a phase 2 clinical trial conducted at the University of Iowa (NCT02344355). Tumor samples obtained during surgical resection were processed and stained for transferrin receptor and ferritin heavy chain expression. A blinded pathologist performed pathological assessment. Quantitative susceptibility mapping (QSM) measures were obtained from pre-radiotherapy MRI scans following maximal safe surgical resection. Circulating blood iron panels were evaluated prior to therapy through the University of Iowa Diagnostic Laboratory. RESULTS: Through univariate analysis, a significant inverse association was observed between tumor transferrin receptor expression and overall and progression-free survival. QSM measures exhibited a significant, positive association with progression-free survival. Subjects were actively followed until disease progression and then were followed through chart review or clinical visits for overall survival. CONCLUSIONS: This study analyzes iron-related biomarkers in the context of P-AscH- therapy for glioblastoma. Integrating molecular, systemic, and imaging-based markers offers a multifaceted approach to tailoring treatment strategies, thereby contributing to improved patient outcomes and advancing the field of glioblastoma therapy.

HIGHLIGHTS: Pharmacological ascorbate shows significant promise to enhance glioblastoma clinical outcomes. Transferrin receptor and ferritin heavy chain expression represent potential molecular markers to predict pharmacological ascorbate treatment response. Quantitative Susceptibility Mapping is an MRI technique that can serve as a non-invasive marker of iron metabolism to evaluate progression-free survival. Systemic iron metabolic markers are readily available diagnostic tests that can potentially be used to prognosticate overall survival.

Magnetite nanoparticles as a kinetically favorable source of iron to enhance GBM response to chemoradiosensitization with pharmacological ascorbate.

Ferumoxytol (FMX) is an FDA-approved magnetite (Fe3O4) nanoparticle used to treat iron deficiency anemia that can also be used as an MR imaging agent in patients that can't receive gadolinium. Pharmacological ascorbate (P-AscH-; IV delivery; plasma levels ≈ 20 mM) has shown promise as an adjuvant to standard of care chemo-radiotherapy in glioblastoma (GBM). Since ascorbate toxicity mediated by H2O2 is enhanced by Fe redox cycling, the current study determined if ascorbate catalyzed the release of ferrous iron (Fe2+) from FMX for enhancing GBM responses to chemo-radiotherapy. Ascorbate interacted with Fe3O4 in FMX to produce redox-active Fe2+ while simultaneously generating increased H2O2 fluxes, that selectively enhanced GBM cell killing (relative to normal human astrocytes) as opposed to a more catalytically active Fe complex (EDTA-Fe3+) in an H2O2 - dependent manner. In vivo, FMX was able to improve GBM xenograft tumor control when combined with pharmacological ascorbate and chemoradiation in U251 tumors that were unresponsive to pharmacological ascorbate therapy. These data support the hypothesis that FMX combined with P-AscH- represents a novel combined modality therapeutic approach to enhance cancer cell selective chemoradiosentization in the management of glioblastoma.

Quantum chemical insight into the effects of the local electron environment on T2*-based MRI.

T2* relaxation is an intrinsic magnetic resonance imaging (MRI) parameter that is sensitive to local magnetic field inhomogeneities created by the deposition of endogenous paramagnetic material (e.g. iron). Recent studies suggest that T2* mapping is sensitive to iron oxidation state. In this study, we evaluate the spin state-dependence of T2* relaxation using T2* mapping. We experimentally tested this physical principle using a series of phantom experiments showing that T2* relaxation times are directly proportional to the spin magnetic moment of different transition metals along with their associated magnetic susceptibility. We previously showed that T2* relaxation time can detect the oxidation of Fe2+. In this paper, we demonstrate that T2* relaxation times are significantly longer for the diamagnetic, d10 metal Ga3+, compared to the paramagnetic, d5 metal Fe3+. We also show in a cell culture model that cells supplemented with Ga3+ (S = 0) have a significantly longer relaxation time compared to cells supplemented with Fe3+ (S = 5/2). These data support the hypothesis that dipole-dipole interactions between protons and electrons are driven by the strength of the electron spin magnetic moment in the surrounding environment giving rise to T2* relaxation.

Brain abnormalities in bipolar disorder detected by quantitative T1ρ mapping.

Abnormal metabolism has been reported in bipolar disorder, however, these studies have been limited to specific regions of the brain. To investigate whole-brain changes potentially associated with these processes, we applied a magnetic resonance imaging technique novel to psychiatric research, quantitative mapping of T1 relaxation in the rotating frame (T1ρ). This method is sensitive to proton chemical exchange, which is affected by pH, metabolite concentrations and cellular density with high spatial resolution relative to alternative techniques such as magnetic resonance spectroscopy and positron emission tomography. Study participants included 15 patients with bipolar I disorder in the euthymic state and 25 normal controls balanced for age and gender. T1ρ maps were generated and compared between the bipolar and control groups using voxel-wise and regional analyses. T1ρ values were found to be elevated in the cerebral white matter and cerebellum in the bipolar group. However, volumes of these areas were normal as measured by high-resolution T1- and T2-weighted magnetic resonance imaging. Interestingly, the cerebellar T1ρ abnormalities were normalized in participants receiving lithium treatment. These findings are consistent with metabolic or microstructural abnormalities in bipolar disorder and draw attention to roles of the cerebral white matter and cerebellum. This study highlights the potential utility of high-resolution T1ρ mapping in psychiatric research.

White matter integrity, as measured by diffusion tensor imaging, distinguishes between impaired and unimpaired older adult decision-makers: A preliminary investigation.

In the context of normal ageing, some individuals experience cognitive changes that affect their decision-making abilities. We investigated whether such cognitive changes could be related to the integrity of cortical white matter, as measured by diffusion tensor imaging (DTI). Participants were administered a well-validated laboratory decision-making task, and were subsequently grouped as either poor decision-makers (older-impaired, n = 9) or strong decision-makers (older-unimpaired, n = 7). Participants also underwent magnetic resonance imaging (MRI) that collected high-resolution structural images, including DTI of the brain. The key variable of interest to be contrasted between the groups was fractional anisotropy (FA), as calculated from the tensor images. We hypothesised that FA values would be lower (indicating poorer integrity of tracts) in the older-impaired participants. The results supported our hypothesis, indicating significant differences in FA values between the participant groups for the entire brain as well as several subregions. The results suggest that poorer decision-making abilities are associated with the integrity of cortical white matter across multiple regions of the brain, and support the call for additional research in this area.

Iterative active deformational methodology for tumor delineation: Evaluation across radiation treatment stage and volume.

PURPOSE: To introduce, implement, and assess an iterative modification to the active deformational image segmentation method as applied to cervical cancer tumors. MATERIALS AND METHODS: A comparison by Jaccard similarity (JS) between this active deformational method and manual segmentation was performed on tumors of various sizes across preradiation, 3 weeks postradiation, and 6 weeks postradiation using a General Linear Mixed Model across 121 studies from 52 patients with Stage IIB-IV cervical cancers. RESULTS: The deformable segmentation method produced promising levels of agreement including JS factors of 0.71+/-0.11 in the preradiation studies. The analysis illustrated a rate of improvement in JS with increasing tumor volume that differed between the preradiation and 6 weeks postradiation stage (P=0.0474). In the large preradiated tumors each additional cm3 of volume was associated with an increase or improvement in JS of 0.0008 (95% confidence interval [CI]: 0.0003, 0.0014). In the smaller postradiation tumors, each additional cm3 of volume was associated with a more robust improvement in JS of 0.0046 (95% CI: 0.0009, 0.0082). CONCLUSION: Agreement was strongly affected by tumor volume, and its performance was most impacted across volume in the later stages of radiation therapy. The deformation-based segmentation method appears to demonstrate utility for delineating cervical cancer tumors, particularly in the earliest stages of radiation treatment, where agreement is greatest.

Effects of olanzapine on cerebellar functional connectivity in schizophrenia measured by fMRI during a simple motor task.

BACKGROUND: According to current theories, schizophrenia results from altered connectivity in brain circuits for fundamental cognitive operations. Consequently, the poorly understood mechanisms of neuroleptic treatment may be explainable by altered functional interactions within such networks. The 'cognitive dysmetria' model hypothesizes that one key structure in these circuits is the cerebellum. To investigate the effects of olanzapine on cerebellar functional connectivity (CFC), a seed-voxel correlation analysis (SVCA) was used in a functional magnetic resonance imaging (fMRI) study of a simple finger-tapping task. METHODS: fMRI scans were obtained from six schizophrenic patients under both drug-free and olanzapine-treated conditions and from a matched control group of six healthy subjects at corresponding time points. SVCAs were performed for anatomically and functionally standardized seed voxels in the anterior cerebellum. SVCA results were then processed by three different randomization analyses. RESULTS: The analyses revealed that olanzapine caused widespread changes of CFC, including prominent changes in prefrontal cortex and mediodorsal thalamus. Significant changes in motor structures were found after subtractions within both groups and may thus indicate repetition effects rather than drug effects. Olanzapine 'normalized' the patients' CFC patterns for the right, but not for the left cerebellum. CONCLUSION: Even for a simple motor task, olanzapine affects functional interactions between the cerebellum and many non-motor brain regions, including elements of the 'cognitive dysmetria' circuit. Altogether, our findings suggest that olanzapine has a stronger differential effect on neural activity in prefrontal cortex and thalamus than in motor structures.

Pixel analysis of MR perfusion imaging in predicting radiation therapy outcome in cervical cancer.

The purpose of this study was to assess heterogeneity of tumor microcirculation determined by dynamic contrast-enhanced magnetic resonance (MR) imaging and its prognostic value for tumor radiosensitivity and long-term tumor control using pixel-by-pixel analysis of the dynamic contrast enhancement. Sixteen patients with advanced cervical cancer were examined with dynamic contrast-enhanced MR imaging at the time of radiation therapy. Pixel-by-pixel statistical analysis of the ratio of post- to precontrast relative signal intensity (RSI) values in the tumor region was performed to generate pixel RSI distributions of dynamic enhancement patterns. Histogram parameters were correlated with subsequent tumor control based on long-term cancer follow-up (median follow-up 4.6 years; range 3.8-5.2 years). The RSI distribution histograms showed a wide spectrum of heterogeneity in the dynamic enhancement pattern within the tumor. The quantity of low-enhancement regions (10th percentile RSI < 2.5) significantly predicted subsequent tumor recurrence (88% vs. 0%, P = 0.0004). Discriminant analysis based on both 10th percentile RSI and pixel number (reflective of tumor size) further improved the prediction rate (100% correct prediction of subsequent tumor control vs. recurrence). These preliminary results suggest that quantification of the extent of poor vascularity regions within the tumor may be useful in predicting long-term tumor control and treatment outcome in cervical cancer. J. Magn. Reson. Imaging 2000;12:1027-1033.

Cerebral cortex: a topographic segmentation method using magnetic resonance imaging.

Remarkable developments in magnetic resonance imaging (MRI) technology provide a broad range of potential applications to explore in vivo morphological characteristics of the human cerebral cortex. MR-based parcellation methods of the cerebral cortex may clarify the structural anomalies in specific brain subregions that reflect underlying neuropathological processes in brain illnesses. The present study describes detailed guidelines for the parcellation of the cerebral cortex into 41 subregions. Our method conserves the topographic uniqueness of individual brains and is based on our ability to visualize the three orthogonal planes, the triangulated gray matter isosurface and the three-dimensional (3D) rendered brain simultaneously. Based upon topographic landmarks of individual sulci, every subregion was manually segmented on a set of serial coronal or transaxial slices consecutively. The reliability study indicated that the cerebral cortex could be parcelled reliably; intraclass correlation coefficients for each subregion ranged from 0.60 to 0.99. The validity of the method is supported by the fact that gyral subdivisions are similar to regions delineated in functional imaging studies conducted in our center. Ultimately, this method will permit us to detect subtle morphometric impairments or to find abnormal patterns of functional activation in circumscribed cortical subregions. The description of a thorough map of regional structural and functional cortical abnormalities will provide further insight into the role that different subregions play in the pathophysiology of brain illnesses.

An MRI-based parcellation method for the temporal lobe.

The temporal lobe has long been a focus of attention with regard to the underlying pathology of several major psychiatric illnesses. Previous postmortem and imaging studies describing regional volume reductions or perfusion defects in temporal subregions have shown inconsistent findings, which are in part due to differences in the definition of the subregions and the methodology of measurement. The development of precise reproducible parcellation systems on magnetic resonance images may help improve uniformity of results in volumetric MR studies and unravel the complex activation patterns seen in functional neuroimaging studies. The present study describes detailed guidelines for the parcellation of the temporal neocortex. It parcels the entire temporal neocortex into 16 subregions: temporal pole, heschl's gyrus, planum temporale, planum polare, superior temporal gyrus (rostral and caudal), middle temporal gyrus (rostral, intermediate, and caudal), inferior temporal gyrus (rostral, intermediate, and caudal), occipitotemporal gyrus (rostral and caudal), and parahippocampal gyrus (rostral and caudal). Based upon topographic landmarks of individual sulci, every subregion was consecutively traced on a set of serial coronal slices. In spite of the huge variability of sulcal topography, the sulcal landmarks could be identified reliably due to the simultaneous display of three orthogonal (transaxial, coronal, and sagittal) planes, triangulated gray matter isosurface, and a 3-D-rendered image. The reliability study showed that the temporal neocortex could be parceled successfully and reliably; intraclass correlation coefficient for each subregion ranged from 0.62 to 0.99. Ultimately, this method will permit us to detect subtle morphometric impairments or to find abnormal patterns of functional activation in the temporal subregions that might reflect underlying neuropathological processes in psychiatric illnesses such as schizophrenia.

Visualization of subthalamic nuclei with cortex attenuated inversion recovery MR imaging.

There is a significant amount of interest in studying the thalamus because of its central location in the brain and its role as a gatekeeper to higher centers of cognition. Imaging and measuring of the individual subnuclei of the thalamus has proven extremely difficult in MR because of the contrast-to-noise (CNR) of the MR sequences used. This report describes a novel MR pulse sequence known as cortex attenuated inversion recovery (CAIR), which increases the CNR in images and allows the individual subnuclei of the thalamus to be visualized by selectively nulling the gray matter in the brain using an inversion recovery sequence with an inversion time of 700 ms at 1.5 T.

A new method for the in vivo volumetric measurement of the human hippocampus with high neuroanatomical accuracy.

Accurate and reproducible in vivo measurement of hippocampal volumes using magnetic resonance (MR) imaging is complicated by the morphological complexity of the structure. Additionally, separation of certain parts of the hippocampus from the adjacent brain structures on MR images is sometimes very difficult. These difficulties have led most investigators to either use arbitrary landmarks or to exclude certain parts of the structure from their measurements. Based on three-dimensional MR data, we have developed a reliable in vivo volumetric measurement of the human hippocampus. In contrast to most of the previously described volumetric MR-based methods, we aimed to sample the entire hippocampal formation using its true anatomical definition. This was accomplished by relying on the capacity of the BRAINS software to simultaneously visualize in multiple planes, to "telegraph" tracings or cursor position from one plane to another, and to simultaneously rely on multispectral data from three different image sets (T1, T2, and tissue classified). The methods for identifying boundaries and measuring the hippocampal volume are described. The method has excellent reliability, sensitivity, and specificity. The method may be of use in studies of structure-function relationships in neuropsychiatric disorders such as schizophrenia, temporal lobe epilepsy, and Alzheimer's disease. Future work will use these measurements as training data for a neural net-based technique to identify the anatomical boundaries automatically.

Human frontal cortex: an MRI-based parcellation method.

The frontal lobe is not a single anatomical and functional brain region. Several lines of research have demonstrated that particular subregions within the frontal lobe are associated with specific motor and cognitive functions in the human being. Our main purpose is to develop a magnetic resonance image (MRI)-based parcellation method of the frontal lobe that permits us to explore plausible abnormalities in functionally relevant frontal subregions in brain illnesses. We describe a procedure using MRI for subdividing the entire frontal cortex into 11 subregions: supplementary motor area (SMA), rostral anterior cingulate gyrus (r-ACiG), caudal anterior cingulate gyrus (c-ACiG), superior cingulate gyrus (SCiG), medial frontal cortex (MFC), straight gyrus (SG), orbitofrontal cortex (OFC), precentral gyrus (PCG), superior frontal gyrus (SFG), inferior frontal gyrus (IFG), and middle frontal gyrus (MFG). Our method posits to conserve the topographic uniqueness of individual brains and is based on our ability to visualize both the three-dimensional (3D) rendered brain and the three orthogonal planes simultaneously. The reliability study for gray matter volume and surface area of each subregion was performed on a set of 10 MR scans by two raters. The intraclass R coefficients for gray matter volume of each subregion ranged between 0.86 and 0.99. We describe here a reproducible and reliable topography-based parcellation method of the frontal lobe that will allow us to use new approaches to understand the role of particular frontal cortical subregions in schizophrenia and other brain illnesses.

MR microcirculation assessment in cervical cancer: correlations with histomorphological tumor markers and clinical outcome.

This article reviews the experience available to date on microcirculation assessment in cancer of the cervix including correlation studies of magnetic resonance (MR) microcirculatory parameters with histo-morphometric predictors and direct correlation with patient outcome. The data suggest that MR microcirculation parameters do not always correlate with histo-morphometric parameters, while there is evidence that MR parameters predict patients' treatment outcome. These observations raise the issue that perhaps the histo-morphometric parameters, accepted gold standards for tumor angiogenesis and prognostic factors, reflect anatomical information at a "static" single time point and may not always provide sufficient information on the "dynamic" microcirculation function of the tumor. MR microcirculation assessment reflects both anatomical and functional information and may provide this additional information on the "dynamic" angiogenic and metabolic status of a tumor. Therefore, assessment of tumor microcirculation may augment the individual risk profile in cervical cancer patients and has the potential to impact on therapy selection and treatment outcome.

Outcome of acute ischemic lesions evaluated by diffusion and perfusion MR imaging.

BACKGROUND AND PURPOSE: Diffusion and perfusion MR imaging have been reported to be valuable in the diagnosis of acute ischemia. Our purpose was to ascertain the value of these techniques in the prediction of ischemic injury and estimation of infarction size, as determined on follow-up examinations. METHODS: We studied 18 patients with acute ischemic stroke who underwent echo-planar perfusion and diffusion imaging within 72 hours of symptom onset. Quantitative volume measurements of ischemic lesions were derived from relative mean transit time (rMTT) maps, relative cerebral blood volume (rCBV) maps, and/or apparent diffusion coefficient (ADC) maps. Follow-up examinations were performed to verify clinical suspicion of infarction and to calculate the true infarction size. RESULTS: Twenty-five ischemic lesions were detected during the acute phase, and 14 of these were confirmed as infarcts on follow-up images. Both ADC and rMTT maps had a higher sensitivity (86%) than the rCBV map (79%), and the rCBV map had the highest specificity (91%) for detection of infarction as judged on follow-up images. The rMTT and ADC maps tended to overestimate infarction size (by 282% and 182%, respectively), whereas the rCBV map appeared to be more precise (117%). Significant differences were found between ADC and rMTT maps, and between rCBV and rMTT maps. CONCLUSION: Our data indicate that all three techniques are sensitive in detecting early ischemic injury within 72 hours of symptom onset but tend to overestimate the true infarction size. The best methods for detecting ischemic injury and for estimating infarction size appear to be the ADC map and the rCBV map, respectively, and the diffusion abnormality may indicate early changes of both reversible and irreversible ischemia.

Measurement of brain structures with artificial neural networks: two- and three-dimensional applications.

PURPOSE: To evaluate the ability of an artificial neural network (ANN) to identify brain structures. This ANN was applied to postprocessed magnetic resonance (MR) images to segment various brain structures in both two- and three-dimensional applications. MATERIALS AND METHODS: An ANN was designed that learned from experience to define the corpus callosum, whole brain, caudate, and putamen. Manual segmentation was used as a training set for the ANN. The ANN was trained on two-thirds of the manually segmented images and was tested on the remaining one-third. The reliability of the ANN was compared against manual segmentations by two technicians. RESULTS: The ANN was able to identify the brain structures as readily and as well as did the two technicians. Reliability of the ANN compared with the technicians was 0.96 for the corpus callosum, 0.95 for the whole brain, 0.86 (right) and 0.93 (left) for the caudate, and 0.71 (right) and 0.88 (left) for the putamen. CONCLUSION: The ANN was able to identify the structures used in this study as well as did the two technicians. The ANN could do this much more rapidly and without rater drift. Several other cortical and subcortical structures could also be readily identified with this method.

Quantitative in vivo measurement of gyrification in the human brain: changes associated with aging.

Clinical observation suggests that the aging process affects gyrification, with the brain appearing more 'atrophic' with increasing age. Empirical studies of tissue type indicate that gray matter volume decreases with age while cerebrospinal fluid increases. Quantitative changes in cortical surface characteristics such as sulcal and gyral shape have not been measured, however, due to difficulties in developing a method that separates abutting gyral crowns and opens up the sulci -- the 'problem of buried cortex'. We describe a quantitative method for measuring brain surface characteristics that is reliable and valid. This method is used to define the gyral and sulcal characteristics of atrophic and non-atrophic brains and to examine changes that occur with aging in a sample of 148 normal individuals from a broad age range. The shape of gyri and sulci change significantly over time, with the gyri becoming more sharply and steeply curved, while the sulci become more flattened and less curved. Cortical thickness also decreases over time. Cortical thinning progresses more rapidly in males than in females. The progression of these changes appears to be relatively stable during midlife and to begin to progress some time during the fourth decade. Measurements of sulcal and gyral shape may be useful in studying the mechanisms of both neurodevelopmental and neurodegenerative changes that occur during brain maturation and aging.

Improving tissue classification in MRI: a three-dimensional multispectral discriminant analysis method with automated training class selection.

PURPOSE: To improve the reliability, accuracy, and computational efficiency of tissue classification with multispectral sequences [T1, T2, and proton density (PD)], we developed an automated method for identifying training classes to be used in a discriminant function analysis. We compared it with a supervised operator-dependent method, evaluating its reliability and validity. We also developed a fuzzy (continuous) classification to correct for partial voluming. METHOD: Images were obtained on a 1.5 T GE Signa MR scanner using three pulse sequences that were co-registered. Training classes for the discriminant analysis were obtained in two ways. The operator-dependent method involved defining circular ROIs containing 5-15 voxels that represented "pure" samples of gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF), using a total of 150-300 voxels for each tissue type. The automated method involved selecting a large number of samples of brain tissue with sufficiently low variance and randomly placed throughout the brain ("plugs"), partitioning these samples into GM, WM, and CSF, and minimizing the amount of variance within each partition of samples to optimize its "purity." The purity of the plug was estimated by calculating the variance of 8 voxels in all modalities (T1, T2, and PD). We also compared "sharp" (discrete) measurements (which classified tissue only as GM, WM, or CSF) and "fuzzy" (continuous) measurements (which corrected for partial voluming by weighting the classification based on the mixture of tissue types in each voxel). RESULTS: Reliability was compared for the operator-dependent and automated methods as well as for the fuzzy versus sharp classification. The automated sharp classifications consistently had the highest interrater and intrarater reliability. Validity was assessed in three ways: reproducibility of measurements when the same individuals were scanned on multiple occasions, sensitivity of the method to detecting changes associated with aging, and agreement between the automated segmentation values and those produced through expert manual segmentation. The sharp automated classification emerged as slightly superior to the other three methods according to each of these validators. Its reproducibility index (intraclass r) was 0.97, 0.98, and 0.98 for total CSF, total GM, and total WM, respectively. Its correlations with age were 0.54, -0.61, and -0.53, respectively. Its percent agreement with the expert manually segmented tissue for the three tissue types was 93, 90, and 94%, respectively. CONCLUSION: Automated identification of training classes for discriminant analysis was clearly superior to a method that required operator intervention. A sharp (discrete) classification into three tissue types was also slightly superior to one that used "fuzzy" classification to produce continuous measurements to correct for partial voluming. This multispectral automated discriminant analysis method produces a computationally efficient, reliable, and valid method for classifying brain tissue into GM, WM, and CSF. It corrects some of the problems with reliability and computational inefficiency previously observed for operator-dependent approaches to segmentation.

Severe occlusive carotid artery disease: hemodynamic assessment by MR perfusion imaging in symptomatic patients.

BACKGROUND AND PURPOSE: Cerebral hemodynamic status has been reported to influence the occurrence and outcome of acute stroke. The purpose of this study was to assess hemodynamic compromise in symptomatic patients with severe occlusive disease of the carotid artery by the use of echo-planar perfusion imaging. METHODS: Spin-echo echo-planar perfusion imaging was performed in 11 patients (two had bilateral disease) with severe stenosis or occlusion of the carotid artery who had experienced either a recent transient ischemic attack or minor stroke. Relative cerebral blood volume (rCBV) maps and relative mean transit time (rMTT) maps were generated from the time-concentration curve. Findings on T2-weighted images, angiograms, rCBV maps, and rMTT maps were compared and assessed qualitatively and quantitatively. RESULTS: Although the abnormalities on T2-weighted images were absent, minimal, and/or unrelated to the degree of stenosis or collateral circulation, rMTT maps showed much larger and more distinct perfusion abnormalities along the vascular distribution of the affected vessels in all 13 vascular territories of the 11 patients. Despite obvious abnormalities on rMTT maps, none of the patients had evidence of decreased rCBV in the affected brain tissue (increased in three, normal in eight). A statistically significant difference in rMTT values was found between the affected and unaffected brain tissue, whereas no significant difference was seen in rCBV values. CONCLUSION: Echo-planar perfusion imaging is a noninvasive and rapid method for evaluating the hemodynamics in severe occlusive carotid artery disease and the compensatory vascular changes, and it may be useful in patient management.