T1-weighted Magnetic Resonance Imaging Data Research Articles

Support vector machine-based classification of neuroimages in Alzheimer's disease: direct comparison of FDG-PET, rCBF-SPECT and MRI data acquired from the same individuals.

Objective:To conduct the first support vector machine (SVM)-based study comparing the diagnostic accuracy of T1-weighted magnetic resonance imaging (T1-MRI), F-fluorodeoxyglucose-positron emission tomography (FDG-PET) and regional cerebral blood flow single-photon emission computed tomography (rCBF-SPECT) in Alzheimer’s disease (AD).Method:Brain T1-MRI, FDG-PET and rCBF-SPECT scans were acquired from a sample of mild AD patients (n=20) and healthy elderly controls (n=18). SVM-based diagnostic accuracy indices were calculated using whole-brain information and leave-one-out cross-validation.Results:The accuracy obtained using PET and SPECT data were similar. PET accuracy was 68∼71% and area under curve (AUC) 0.77∼0.81; SPECT accuracy was 68∼74% and AUC 0.75∼0.79, and both had better performance than analysis with T1-MRI data (accuracy of 58%, AUC 0.67). The addition of PET or SPECT to MRI produced higher accuracy indices (68∼74%; AUC: 0.74∼0.82) than T1-MRI alone, but these were not clearly superior to the isolated neurofunctional modalities.Conclusion:In line with previous evidence, FDG-PET and rCBF-SPECT more accurately identified patients with AD than T1-MRI, and the addition of either PET or SPECT to T1-MRI data yielded increased accuracy. The comparable SPECT and PET performances, directly demonstrated for the first time in the present study, support the view that rCBF-SPECT still has a role to play in AD diagnosis.

Compartmental sparse feature selection method for Alzheimer's disease identification.

For high-dimensional magnetic resonance imaging (MRI) data, many feature selection methods have been proposed to reduce feature dimension in the study of computer-aided Alzheimer's disease (AD) diagnosis. This paper presents a compartmental sparse feature selection method used for AD identification. Based on the derived atlas-based regions-of-interest (ROIs) of brain, the proposed method partitioned the T1-weighted MRI data into several compartments. It performs feature selection and classification compartmentally according to the local feature dimension estimation and local feature selection using sparse principal component analysis (SPCA) method followed with elastic-net logistic regression (ENLR) classifier. Experimental results showed that the proposed method improves the classification performance for small ROIs with high computational efficiency.

LONGITUDINAL EFFECT OF CLUSTERIN LEVELS ON CORTICAL THICKNESS IN THE AUSTRALIAN IMAGING BIOMARKERS LIFESTYLE (AIBL) STUDY OF AGING

Clusterin (Apolipoprotein J) is associated with Alzheimer's disease (AD) pathogenesis, and higher levels of clusterin are associated with increased cognitive decline in AD. We hypothesize that failure of clusterin chaperonic activity contributes to AD and hence could be a valuable therapeutics target for preclinical AD. In this study, we investigated the effect of clusterin levels on cortical grey matter thickness as assessed by Magnetic Resonance Imaging (MRI) data. The data of 87 (35 M) healthy subjects aged 68.8 (SD 5.9) years old from AIBL was used in this study. Neuropsychological classification of the included healthy participants remained unchanged during 36 months. Clusterin levels of each subject was measured at baseline, and at 18 and 36 months follow-ups using Mesoscale Discovery Platform. At each time point, subjects underwent a MRI. Cortical thickness was computed from the T1-weighted MRI data. We used a linear mixed effects model to model temporal reduction of cortical thickness, with respect to age, gender, apolipoprotein E ε4 allele status, baseline clusterin level. Clusterin levels are negatively associated with cortical thickness (p=0.026) at baseline. However, the significant interaction between time-point and clusterin levels (p=0.002) indicates that a higher clusterin level was associated with slower decline in cortical thickness.

Intrinsic functional connectivity alterations in progressive supranuclear palsy: Differential effects in frontal cortex, motor, and midbrain networks.

The topography of functional network changes in progressive supranuclear palsy can be mapped by intrinsic functional connectivity MRI. The objective of this study was to study functional connectivity and its clinical and behavioral correlates in dedicated networks comprising the cognition-related default mode and the motor and midbrain functional networks in patients with PSP. Whole-brain-based "resting-state" functional MRI and high-resolution T1-weighted magnetic resonance imaging data together with neuropsychological and video-oculographic data from 34 PSP patients (22 with Richardson subtype and 12 with parkinsonian subtype) and 35 matched healthy controls were subjected to network-based functional connectivity and voxel-based morphometry analysis. After correction for global patterns of brain atrophy, the group comparison between PSP patients and controls revealed significantly decreased functional connectivity (P < 0.05, corrected) in the prefrontal cortex, which was significantly correlated with cognitive performance (P = 0.006). Of note, midbrain network connectivity in PSP patients showed increased connectivity with the thalamus, on the one hand, whereas, on the other hand, lower functional connectivity within the midbrain was significantly correlated with vertical gaze impairment, as quantified by video-oculography (P = 0.004). PSP Richardson subtype showed significantly increased functional motor network connectivity with the medial prefrontal gyrus. PSP-associated neurodegeneration was attributed to both decreased and increased functional connectivity. Decreasing functional connectivity was associated with worse behavioral performance (ie, dementia severity and gaze palsy), whereas the pattern of increased functional connectivity may be a potential adaptive mechanism. © 2017 International Parkinson and Movement Disorder Society.

Age- and sex-related differences in masseter size and its role in oral functions

BackgroundThe masseter muscle plays a key structural and functional role in the stomatognathic system. Researchers’ cumulative evidence has suggested that the variation in the size of a person’s masseter muscle may be a critical factor related to individual differences in oral functions. However, researchers have not yet investigated systematically the effect of a person’s age and sex on masseter muscle size and the association of masseter muscle size with other clinical metrics, including masticatory performance (MP) and salivary flow rate (SFR). Using T1-weighted magnetic resonance imaging (MRI) data provides a noninvasive method for assessing masseter muscle volume (MMV). MethodsUsing T1-weighted MRI data, the authors developed a voxel-based method to assess MMV and investigated the associations among MMV, MP, and SFR. ResultsThe authors acquired T1-weighted MRI data from scans of the heads of 62 healthy adults and assessed MMV by means of using a voxel-based approach. The authors’ assessment results had acceptable rates of inter-rater and intrarater reliability. MMV was significantly lower in the older subgroup and in the female subgroup. In addition, the correlation for MMV was significantly positive with MP and stimulated SFR. ConclusionsThe study results revealed evidence that the authors’ voxel-based approach, which they designed on the basis of T1-weighted MRI data, would be a reliable method for quantifying MMV. Practical ImplicationsThe findings suggest that the variation in masseter muscle size may be a critical factor to assess individual differences in oral functions.

A unified Bayesian-based compensated magnetic resonance imaging.

Magnetic resonance (MR) images of higher quality is demanded for helping with more accurate and earlier diagnosis of different diseases. The overall quality of MR images is limited due to the existence of different degradation factors such as (1) MR aberrations due to intrinsic properties of the MR scanner, (2) magnetic field inhomogeneity, and (3) inherent MRI noise. Correcting each MRI degradation factor could be solely useful for the quality enhancement of MR imaging with a limited impact. Here, we propose a unified Bayesian based compensated MR imaging (CMRI) system which jointly corrects for the different aforementioned MR aberrations as well as MR noise and hence generates compensated MR (CMR) images with a higher quality. Testing the proposed CMRI system on both MR physical phantom as well as diffusion weighted and T2 weighted MR imaging data resulted in producing MR images with an overall higher quality that better represents different structures of tissue. The quantitative performance analysis shows a higher Signal to Noise (SNR) and Contrast to Noise (CNR) ratios as well as less Coefficient of Variation (CV) for reconstructed images using the proposed CMRI system compared to the Blind Deconvolution Compensation (BDC) method as state-of-the-art. As such, the proposed CMRI system has potential in improving MR image quality, which is important for accurate and consistent clinical interpretation.

Volumetric and shape analyses of subcortical structures in United States service members with mild traumatic brain injury.

Mild traumatic brain injury (mTBI) is a significant health concern. The majority who sustain mTBI recover, although ~20% continue to experience symptoms that can interfere with quality of life. Accordingly, there is a critical need to improve diagnosis, prognostic accuracy, and monitoring (recovery trajectory over time) of mTBI. Volumetric magnetic resonance imaging (MRI) has been successfully utilized to examine TBI. One promising improvement over standard volumetric approaches is to analyze high-dimensional shape characteristics of brain structures. In this study, subcortical shape and volume in 76 Service Members with mTBI was compared to 59 Service Members with orthopedic injury (OI) and 17 with post-traumatic stress disorder (PTSD) only. FreeSurfer was used to quantify structures from T1-weighted 3T MRI data. Radial distance (RD) and Jacobian determinant (JD) were defined vertex-wise on parametric mesh-representations of subcortical structures. Linear regression was used to model associations between morphometry (volume and shape), TBI status, and time since injury (TSI) correcting for age, sex, intracranial volume, and level of education. Volumetric data was not significantly different between the groups. JD was significantly increased in the accumbens and caudate and significantly reduced in the thalamus of mTBI participants. Additional significant associations were noted between RD of the amygdala and TSI. Positive trend-level associations between TSI and the amygdala and accumbens were observed, while a negative association was observed for third ventricle. Our findings may aid in the initial diagnosis of mTBI, provide biological targets for functional examination, and elucidate regions that may continue remodeling after injury.

MRI with and without a high-density EEG cap—what makes the difference?

Besides the benefit of combining electroencephalography (EEG) and magnetic resonance imaging (MRI), much effort has been spent to develop algorithms aimed at successfully cleaning the EEG data from MRI-related gradient and ballistocardiological artifacts. However, there are also studies showing a negative influence of the EEG on MRI data quality. Therefore, in the present study, we focused for the first time on the influence of the EEG on morphometric measurements of T1-weighted MRI data (voxel- and surfaced-based morphometry). Here, we demonstrate a strong influence of the EEG on cortical thickness, surface area, and volume as well as subcortical volumes due to local EEG-related inhomogeneities of the static magnetic (B0) and the gradient field (B1). In a second step, we analyzed the signal-to-noise ratios for both the anatomical and the functional data when recorded simultaneously with EEG and MRI and compared them to the ratios of the MRI data without simultaneous EEG measurements. These analyses revealed consistently lower signal-to-noise ratios for anatomical as well as functional MRI data during simultaneous EEG registration. In contrast, further analyses of T2*-weighted images provided reliable results independent of whether including the individuals' T1-weighted image with or without the EEG cap in the fMRI preprocessing stream. Based on our findings, we strongly recommend against using the structural images obtained during simultaneous EEG-MRI recordings for further anatomical data analysis.

In vivo mapping of hippocampal subfields in mesial temporal lobe epilepsy: Relation to histopathology

A particularly popular automated magnetic resonance imaging (MRI) hippocampal subfield mapping technique is the one described by Van Leemput et al. (2009: Hippocampus 19:549-557) that is currently distributed with FreeSurfer software. This method assesses the probabilistic locations of subfields based on a priori knowledge of subfield topology determined from high-field MRI. Many studies have applied this technique to conventionally acquired T1-weighted MRI data. In the present study, we investigated the relationship between this technique applied to conventional T1-weighted MRI data acquired at 3 T and postsurgical hippocampal histology in patients with medically intractable mesial temporal lobe epilepsy (mTLE) and hippocampal sclerosis (HS). Patients with mTLE (n = 82) exhibited significant volume loss of ipsilateral CA1, CA2-3, CA4-dentate gyrus (DG), subiculum, and fimbria relative to controls (n = 81). Histopathological analysis indicated that the most significant neuronal loss was observed in CA1, then CA4 and CA3, and more subtle neuronal loss in CA2, consistent with classical HS. Neuronal density of CA1 significantly correlated with MRI-determined volume of CA1, and increasingly so with CA2-3 and CA4-DG. Patients with increased HS based on histopathology had greater volume loss of the ipsilateral hippocampal regions on MRI. We conclude by suggesting that whilst time efficient and fully reproducible when applied to conventional single acquisition sequences, the use of the automated subfield technique described here may necessitate the application to multiacquisition high-resolution MR sequences for accurate delineation of hippocampal subfields.

Differences in Neuromuscular Control and Quadriceps Morphology Between Potential Copers and Noncopers Following Anterior Cruciate Ligament Injury

Prospective cross-sectional study. To compare knee muscle morphology and voluntary neuromuscular control in individuals who sustained an anterior cruciate ligament (ACL) injury and were identified as being capable of avoiding surgery (potential copers) and those who were recommended for surgery (noncopers), within 6 months of injury. Quadriceps atrophy and poor neuromuscular control have been found in noncopers. However, the reasons why some noncopers may be able to avoid surgery remain elusive. Twenty participants (10 ACL-deficient noncopers and 10 ACL-deficient potential copers) were included in this study. Axial spin-echo, T1-weighted magnetic resonance imaging data of the lower extremities were captured. The volume and maximum cross-sectional area (CSA) of each muscle of the quadriceps and hamstrings were calculated following digital reconstruction. In addition, voluntary neuromuscular control was evaluated using an established target-matching task that required participants to produce static isometric loads across the knee joint. Electromyography was acquired from 5 muscles as participants performed the target-matching task. Circular statistics were used to calculate a specificity index to describe how well focused each muscle was activated toward its primary direction of muscle action. The ACL-deficient limb was then compared to the uninvolved limb of the noncopers and potential copers. The vasti (vastus medialis and vastus intermedius) of the involved limb of the noncopers were significantly smaller (P<.031) in comparison to those of their uninvolved limb. The potential copers' vastus lateralis maximum CSA (P = .047), total quadriceps muscle volume (P = .020) and maximum CSA (P = .015), and quadriceps-hamstring ratio volume (P = .021) and maximum CSA (P = .007) demonstrated quadriceps atrophy. However, only the ACL-deficient limb of the older (mean ± SD age, 27.4 ± 11.4 versus 19.9 ± 3.3 years; P = .032) and lower-activity-level (3.3 ± 0.5 versus 3.6 ± 0.5; P = .098) noncoper group demonstrated reduced rectus femoris (P = .057) and lateral hamstring (P = .064) neuromuscular control in comparison to their uninvolved limb. These findings suggest that quadriceps and hamstring muscle function, rather than muscle size, may be an important factor in the varied response early after ACL injury.

Particle Swarm Optimization Applied to EEG Source Localization of Somatosensory Evoked Potentials

One of the most important steps in presurgical diagnosis of medically intractable epilepsy is to find the precise location of the epileptogenic foci. Electroencephalography (EEG) is a noninvasive tool commonly used at epilepsy surgery centers for presurgical diagnosis. In this paper, a modified particle swarm optimization (MPSO) method is used to solve the EEG source localization problem. The method is applied to noninvasive EEG recording of somatosensory evoked potentials (SEPs) for a healthy subject. A 1 mm hexahedra finite element volume conductor model of the subject's head was generated using T1-weighted magnetic resonance imaging data. Special consideration was made to accurately model the skull and cerebrospinal fluid. An exhaustive search pattern and the MPSO method were then applied to the peak of the averaged SEP data and both identified the same region of the somatosensory cortex as the location of the SEP source. A clinical expert independently identified the expected source location, further corroborating the source analysis methods. The MPSO converged to the global minima with significantly lower computational complexity compared to the exhaustive search method that required almost 3700 times more evaluations.

Reduced Cingulate Gyrus Volume Associated with Enhanced Cortisol Awakening Response in Young Healthy Adults Reporting Childhood Trauma

BackgroundPreclinical studies have demonstrated the relationship between stress-induced increased cortisol levels and atrophy of specific brain regions, however, this association has been less revealed in clinical samples. The aim of the present study was to investigate the changes and associations of the hypothalamic-pituitary-adrenal (HPA) axis activity and gray matter volumes in young healthy adults with self-reported childhood trauma exposures.MethodsTwenty four healthy adults with childhood trauma and 24 age- and gender-matched individuals without childhood trauma were recruited. Each participant collected salivary samples in the morning at four time points: immediately upon awakening, 30, 45, and 60 min after awakening for the assessment of cortisol awakening response (CAR). The 3D T1-weighted magnetic resonance imaging data were obtained on a Philips 3.0 Tesla scanner. Voxel-based morphometry analyses were conducted to compare the gray matter volume between two groups. Correlations of gray matter volume changes with severity of childhood trauma and CAR data were further analyzed.ResultsAdults with self-reported childhood trauma showed an enhanced CAR and decreased gray matter volume in the right middle cingulate gyrus. Moreover, a significant association was observed between salivary cortisol secretions after awaking and the right middle cingulate gyrus volume reduction in subjects with childhood trauma.ConclusionsThe present research outcomes suggest that childhood trauma is associated with hyperactivity of the HPA axis and decreased gray matter volume in the right middle cingulate gyrus, which may represent the vulnerability for developing psychosis after childhood trauma experiences. In addition, this study demonstrates that gray matter loss in the cingulate gyrus is related to increased cortisol levels.

Ventricular Enlargement and its Clinical Correlates in the Imaging Cohort From the ADCS MCI Donepezil/Vitamin E Study

We analyzed the baseline and 3-year T1-weighted magnetic resonance imaging data of 110 amnestic mild cognitive impairment (MCI) participants with minimal hippocampal atrophy at baseline from the Alzheimer's Disease Cooperative Study group MCI Donepezil/Vitamin E trial. Forty-six subjects converted to Alzheimer disease (AD) (MCIc), whereas 64 remained stable (MCInc). We used the radial distance technique to examine the differences in lateral ventricle shape and size between MCIc and MCInc and the associations between ventricular enlargement and cognitive decline. MCIc group had significantly larger frontal and right body/occipital horns relative to MCInc at baseline and significantly larger bilateral frontal, body/occipital, and left temporal horns at follow-up. Global cognitive decline measured with AD Assessment scale cognitive subscale and Mini-Mental State Examination and decline in activities of daily living (ADL) were associated with posterior lateral ventricle enlargement. Decline in AD Assessment scale cognitive subscale and ADL were associated with left temporal and decline in Mini-Mental State Examination with right temporal horn enlargement. After correction for baseline hippocampal volume, decline in ADL showed a significant association with right frontal horn enlargement. Executive decline was associated with right frontal and left temporal horn enlargement.

Widespread reductions in gray matter volume in depression

Abnormalities in functional limbic–anterior cingulate–prefrontal circuits associated with emotional reactivity, evaluation and regulation have been implicated in the pathophysiology of major depressive disorder (MDD). However, existing knowledge about structural alterations in depression is equivocal and based on cohorts of limited sample size. This study used voxel-based morphometry (VBM) and surface-based cortical thickness to investigate the structure of these circuits in a large and well-characterized patient cohort with MDD.Non-geriatric MDD outpatients (n = 102) and age- and gender-matched healthy control participants (n = 34) provided T1-weighted magnetic resonance imaging data during their baseline visit as part of the International Study to Predict Optimized Treatment for Depression. Whole-brain VBM volumetric and surface-based cortical thickness assessments were performed voxel-wise and compared (at p < 0.05 corrected for multiple comparisons) between the MDD and control groups.MDD participants had reduced gray matter volume in the anterior cingulate cortex, regions of the prefrontal circuits, including dorsolateral and dorsomedial prefrontal cortices, and lateral and medial orbitofrontal cortices, but not in limbic regions. Additional reductions were observed cortically in the posterior temporal and parieto-occipital cortices and, subcortically in the basal ganglia and cerebellum. Focal cortical thinning in the medial orbitofrontal cortex was also observed for the MDD group. These alterations in volume and cortical thickness were not associated with severity of depressive symptoms.The findings demonstrate that widespread gray matter structural abnormalities are present in a well-powered study of patients with depression. The patterns of gray matter loss correspond to the same brain functional network regions that were previously established to be abnormal in MDD, which may support an underlying structural abnormality for these circuits.

Comparing Hippocampal Atrophy in Alzheimer’s Dementia and Dementia with Lewy Bodies

Background/Aims: Dementia with Lewy bodies (DLB) and Alzheimer’s disease (AD) are the two most common neurodegenerative dementias. During the early stages, clinical distinction between them is often challenging. Our objective is to compare hippocampal atrophy patterns in mild AD and mild DLB. We hypothesized that DLB subjects have milder hippocampal atrophy relative to AD subjects. Methods: We analyzed the T1-weighted magnetic resonance imaging data from 113 subjects: 55 AD, 16 DLB and 42 cognitively normal elderly (normal controls, NC). Using the hippocampal radial distance technique and multiple linear regression, we analyzed the effect of clinical diagnosis on hippocampal radial distance, while adjusting for gender and age. Three-dimensional statistical maps were adjusted for multiple comparisons using permutation-based statistics with a threshold of p < 0.01. Results: Compared to NC, AD exhibited significantly greater atrophy in the cornu ammonis (CA)1, CA2–3 and subicular regions bilaterally while DLB showed left-predominant atrophy in the CA1 region and subiculum. Compared directly, AD and DLB did not reveal statistically significant differences. Conclusion: Hippocampal atrophy, while present in mildly impaired DLB subjects, is less severe than atrophy seen in mildly impaired AD subjects, when compared to NC. Both groups show predominant atrophy of the CA1 subfield and subiculum.

Three-Dimensional Computational Modeling of Subject-Specific Cerebrospinal Fluid Flow in the Subarachnoid Space

This study aims at investigating three-dimensional subject-specific cerebrospinal fluid (CSF) dynamics in the inferior cranial space, the superior spinal subarachnoid space (SAS), and the fourth cerebral ventricle using a combination of a finite-volume computational fluid dynamics (CFD) approach and magnetic resonance imaging (MRI) experiments. An anatomically accurate 3D model of the entire SAS of a healthy volunteer was reconstructed from high resolution T2 weighted MRI data. Subject-specific pulsatile velocity boundary conditions were imposed at planes in the pontine cistern, cerebellomedullary cistern, and in the spinal subarachnoid space. Velocimetric MRI was used to measure the velocity field at these boundaries. A constant pressure boundary condition was imposed at the interface between the aqueduct of Sylvius and the fourth ventricle. The morphology of the SAS with its complex trabecula structures was taken into account through a novel porous media model with anisotropic permeability. The governing equations were solved using finite-volume CFD. We observed a total pressure variation from -42 Pa to 40 Pa within one cardiac cycle in the investigated domain. Maximum CSF velocities of about 15 cms occurred in the inferior section of the aqueduct, 14 cms in the left foramen of Luschka, and 9 cms in the foramen of Magendie. Flow velocities in the right foramen of Luschka were found to be significantly lower than in the left, indicating three-dimensional brain asymmetries. The flow in the cerebellomedullary cistern was found to be relatively diffusive with a peak Reynolds number (Re)=72, while the flow in the pontine cistern was primarily convective with a peak Re=386. The net volumetric flow rate in the spinal canal was found to be negligible despite CSF oscillation with substantial amplitude with a maximum volumetric flow rate of 109 mlmin. The observed transient flow patterns indicate a compliant behavior of the cranial subarachnoid space. Still, the estimated deformations were small owing to the large parenchymal surface. We have integrated anatomic and velocimetric MRI data with computational fluid dynamics incorporating the porous SAS morphology for the subject-specific reconstruction of cerebrospinal fluid flow in the subarachnoid space. This model can be used as a basis for the development of computational tools, e.g., for the optimization of intrathecal drug delivery and computer-aided evaluation of cerebral pathologies such as syrinx development in syringomelia.

Increased rates of white matter hyperintensities in late‐onset bipolar disorder

Magnetic resonance imaging (MRI) studies have reported an increased frequency of white matter hyperintensities (WMH) in association with late-onset (LO) depression, and this has supported the notion that vascular-related mechanisms may be implicated in the pathophysiology of LO mood disorders. Recent clinical studies have also suggested a link between LO bipolar disorder (LO-BD) and cerebrovascular risk factors, but this has been little investigated with neuroimaging techniques. In order to ascertain whether there could be a specific association between WMH and LO-BD, we directly compared WMH rates between LO-BD subjects (illness onset >or= 60 years), early-onset BD subjects (EO-BD, illness onset <60 years), and elderly healthy volunteers. T2-weighted MRI data were acquired in LO-BD subjects (n = 10, age = 73.60 +/- 4.09), EO-BD patients (n = 49, age = 67.78 +/- 4.44), and healthy subjects (n = 24, age = 69.00 +/- 7.22). WMH rates were assessed using the Scheltens scale. There was a greater prevalence of WMH in LO-BD patients relative to the two other groups in the deep parietal region (p = 0.018) and basal ganglia (p < 0.045). When between-group comparisons of mean WMH scores were conducted taking account of age differences (ANCOVA), there were more severe scores in LO-BD patients relative to the two other groups in deep frontal and parietal regions, as well as in the putamen (p < 0.05). Our results provide empirical support to the proposed link between vascular risk factors and LO-BD. If extended in future studies with larger samples, these findings may help to clarify the pathophysiological distinctions between bipolar disorder emerging at early and late stages of life.

Adaptive Model Initialization and Deformation for Automatic Segmentation of T1-Weighted Brain MRI Data

A fully automatic, two-step, T1-weighted brain magnetic resonance imaging (MRI) segmentation method is presented. A preliminary mask of parenchyma is first estimated through adaptive image intensity analysis and mathematical morphological operations. It serves as the initial model and probability reference for a level-set algorithm in the second step, which finalizes the segmentation based on both image intensity and geometric information. The Dice coefficient and Euclidean distance between boundaries of automatic results and the corresponding references are reported for both phantom and clinical MR data. For the 28 patient scans acquired at our institution, the average Dice coefficient was 98.2% and the mean Euclidean surface distance measure was 0.074 mm. The entire segmentation for either a simulated or a clinical image volume finishes within 2 min on a modern PC system. The accuracy and speed of this technique allow us to automatically create patient-specific finite element models within the operating room on a timely basis for application in image-guided updating of preoperative scans.

Sequential Visualization of Brain and Fiber Tract Deformation during Intracranial Surgery with Three-dimensional Ultrasound: An Approach to Evaluate the Effect of Brain Shift

We present a technique that allows intraoperative display of brain shift and its effects on fiber tracts. Three patients had intracranial lesions (one malignant glioma, one metastasis, and one cavernoma) in contact with either the corticospinal or the geniculostriate tract that were removed microneurosurgically. Preoperatively, magnetic resonance diffusion-weighted imaging (DWI) was performed to visualize the fiber tract at risk. DWI data were fused with those obtained from anatomic T1-weighted magnetic resonance imaging. A single-rack three-dimensional ultrasound neuronavigation system, which simultaneously displays the MRI scan and the corresponding ultrasound image, was used intraoperatively for 1) navigation; 2) definition of fixed and potentially shifting ultrasound landmarks near the fiber tract; and 3) sequential image updating at different steps of resection. The result was time-dependent brain deformation data. With a standard personal computer equipped with standard image software, the brain shift-associated fiber tract deformation was assessed by use of sequential landmark registration. After surgery, DWI was performed to confirm the predicted fiber tract deformation. The lesions were removed without morbidity. Comparison of three-dimensional ultrasound with DWI and T1-weighted magnetic resonance imaging data allowed us to define fixed and potentially shifting landmarks close to the respective fiber tract. Postoperative DWI confirmed that the actual fiber tract position at the conclusion of surgery corresponded to the sonographically predicted fiber tract position. By definition and sequential intraoperative registration of ultrasound landmarks near the fiber tract, brain shift-associated deformation of a tract that is not visible sonographically can be assessed correctly. This approach seems to help identify and avoid eloquent brain areas during intracranial surgery.

Interactive 3-dimensional segmentation of MRI data in personal computer environment

We describe a method of interactive three-dimensional segmentation and visualization for anatomical magnetic resonance imaging (MRI) data in a personal computer environment. The visual feedback necessary during 3-D segmentation was provided by a ray casting algorithm, which was designed to allow users to interactively decide the visualization quality depending on the task-requirement. Structures such as gray matter, white matter, and facial skin from T1-weighted high-resolution MRI data were segmented and later visualized with surface rendering. Personal computers with central processing unit (CPU) speeds of 266, 400, and 700 MHz, were used for the implementation. The 3-D visualization upon each execution of the segmentation operation was achieved in the order of 2 s with a 700 MHz CPU. Our results suggest that 3-D volume segmentation with semi real-time visual feedback could be effectively implemented in a PC environment without the need for dedicated graphics processing hardware.