ABSTRACT
The mammalian striatum is comprised of intermingled tissue compartments, matrix and striosome. Though indistinguishable by routine histological techniques, matrix and striosome have distinct embryologic origins, afferent/efferent connections, surface protein expression, intra-striatal location, susceptibilities to injury, and functional roles in a range of animal behaviors. Distinguishing the compartments previously required post-mortem tissue and/or genetic manipulation; we aimed to identify matrix/striosome non-invasively in living humans. We used diffusion MRI (probabilistic tractography) to identify human striatal voxels with connectivity biased towards matrix-favoring or striosome-favoring regions (determined by prior animal tract-tracing studies). Segmented striatal compartments replicated the topological segregation and somatotopic organization identified in animal matrix/striosome studies. Of brain regions mapped in prior studies, our human brain data confirmed 93% of the compartment-selective structural connectivity demonstrated in animals. Test-retest assessment on repeat scans found a voxel classification error rate of 0.14%. Fractional anisotropy was significantly higher in matrix-like voxels, while mean diffusivity did not differ between the compartments. As mapped by the Talairach human brain atlas, 460 regions were significantly biased towards either matrix or striosome. Our method allows the study of striatal compartments in human health and disease, in vivo, for the first time.
Subject(s)
Corpus Striatum/anatomy & histology , Corpus Striatum/diagnostic imaging , Diffusion Tensor Imaging/methods , Adolescent , Adult , Aged , Female , Humans , Male , Middle Aged , Young AdultABSTRACT
Diffusion MRI-based probabilistic tractography is a powerful tool for non-invasively investigating normal brain architecture and alterations in structural connectivity associated with disease states. Both voxelwise and region-of-interest methods of analysis are capable of integrating population differences in tract amplitude (streamline count or density), given proper alignment of the tracts of interest. However, quantification of tract differences (between groups, or longitudinally within individuals) has been hampered by two related features of white matter. First, it is unknown to what extent healthy individuals differ in the precise location of white matter tracts, and to what extent experimental factors influence perceived tract location. Second, white matter lacks the gross neuroanatomical features (e.g., gyri, histological subtyping) that make parcellation of grey matter plausible - determining where tracts "should" lie within larger white matter structures is difficult. Accurately quantifying tractographic connectivity between individuals is thus inherently linked to the difficulty of identifying and aligning precise tract location. Tractography is often utilized to study neurological diseases in which the precise structural and connectivity abnormalities are unknown, underscoring the importance of accounting for individual differences in tract location when evaluating the strength of structural connectivity. We set out to quantify spatial variance in tracts aligned through a standard, whole-brain registration method, and to assess the impact of location mismatch on groupwise assessments of tract amplitude. We then developed a method for tract alignment that enhances the existing standard whole brain registration, and then tested whether this method improved the reliability of groupwise contrasts. Specifically, we conducted seed-based probabilistic diffusion tractography from primary motor, supplementary motor, and visual cortices, projecting through the corpus callosum. Streamline counts decreased rapidly with movement from the tract center (-35% per millimeter); tract misalignment of a few millimeters caused substantial compromise of amplitude comparisons. Alignment of tracts "peak-to-peak" is essential for accurate amplitude comparisons. However, for all transcallosal tracts registered through the whole-brain method, the mean separation distance between an individual subject's tract and the average tract (3.2â¯mm) precluded accurate comparison: at this separation, tract amplitudes were reduced by 74% from peak value. In contrast, alignment of subcortical tracts (thalamo-putaminal, pallido-rubral) was substantially better than alignment for cortical tracts; whole-brain registration was sufficient for these subcortical tracts. We demonstrated that location mismatches in cortical tractography were sufficient to produce false positive and false negative amplitude estimates in both groupwise and longitudinal comparisons. We then showed that our new tract alignment method substantially reduced location mismatch and improved both reliability and statistical power of subsequent quantitative comparisons.
Subject(s)
Cerebral Cortex/diagnostic imaging , Corpus Callosum/diagnostic imaging , Diffusion Tensor Imaging/methods , Image Processing, Computer-Assisted/methods , White Matter/diagnostic imaging , Adolescent , Adult , Aged , Diffusion Tensor Imaging/standards , Female , Humans , Image Processing, Computer-Assisted/standards , Male , Middle Aged , Probability , Young AdultABSTRACT
BACKGROUND: The measurement of brain perfusion may provide valuable information for assessment and treatment of newborns with hypoxic-ischemic encephalopathy (HIE). While arterial spin labeled perfusion (ASL) magnetic resonance imaging (MRI) provides noninvasive and direct measurements of regional cerebral blood flow (CBF) values, it is logistically challenging to obtain. Near-infrared spectroscopy (NIRS) might be an alternative, as it permits noninvasive and continuous monitoring of cerebral hemodynamics and oxygenation at the bedside. OBJECTIVE: The purpose of this study is to determine the correlation between measurements of brain perfusion by NIRS and by MRI in term newborns with HIE treated with hypothermia. DESIGN/METHODS: In this prospective cohort study, ASL-MRI and NIRS performed during hypothermia were used to assess brain perfusion in these newborns. Regional cerebral blood flow (CBF) values, measured from 1-2 MRI scans for each patient, were compared to mixed venous saturation values (SctO2) recorded by NIRS just before and after each MRI. Analysis included groupings into moderate versus severe HIE based on their initial background pattern of amplitude-integrated electroencephalogram. RESULTS: Twelve concomitant recordings were obtained of seven neonates. Strong correlation was found between SctO2 and CBF in asphyxiated newborns with severe HIE (r=0.88; p value=0.0085). Moreover, newborns with severe HIE had lower CBF (likely lower oxygen supply) and extracted less oxygen (likely lower oxygen demand or utilization) when comparing SctO2 and CBF to those with moderate HIE. CONCLUSIONS: NIRS is an effective bedside tool to monitor and understand brain perfusion changes in term asphyxiated newborns, which in conjunction with precise measurements of CBF obtained by MRI at particular times, may help tailor neuroprotective strategies in term newborns with HIE.
Subject(s)
Asphyxia Neonatorum/diagnosis , Asphyxia Neonatorum/therapy , Cerebrovascular Circulation/physiology , Functional Neuroimaging/methods , Hypothermia, Induced/methods , Hypoxia-Ischemia, Brain/diagnosis , Hypoxia-Ischemia, Brain/therapy , Magnetic Resonance Imaging/methods , Spectroscopy, Near-Infrared/methods , Cohort Studies , Electroencephalography , Female , Humans , Image Processing, Computer-Assisted , Infant, Newborn , Male , Oxygen/blood , Oxygen Consumption/physiology , Perfusion , Prospective Studies , Reproducibility of ResultsABSTRACT
OBJECTIVE: The quantitative interpretation of hip cartilage magnetic resonance imaging (MRI) has been limited by the difficulty of identifying and delineating the cartilage in a three-dimensional (3D) dataset, thereby reducing its routine usage. In this paper a solution is suggested by unfolding the cartilage to planar two-dimensional (2D) maps on which both morphology and biochemical degeneration patterns can be investigated across the entire hip joint. DESIGN: Morphological TrueFISP and biochemical delayed gadolinium enhanced MRI of cartilage (dGEMRIC) hip images were acquired isotropically for 15 symptomatic subjects with mild or no radiographic osteoarthritis (OA). A multi-template based label fusion technique was used to automatically segment the cartilage tissue, followed by a geometric projection algorithm to generate the planar maps. The segmentation performance was investigated through a leave-one-out study, for two different fusion methods and as a function of the number of utilized templates. RESULTS: For each of the generated planar maps, various patterns could be seen, indicating areas of healthy and degenerated cartilage. Dice coefficients for cartilage segmentation varied from 0.76 with four templates to 0.82 with 14 templates. Regional analysis suggests even higher segmentation performance in the superior half of the cartilage. CONCLUSIONS: The proposed technique is the first of its kind to provide planar maps that enable straightforward quantitative assessment of hip cartilage morphology and dGEMRIC values. This technique may have important clinical applications for patient selection for hip preservation surgery, as well as for epidemiological studies of cartilage degeneration patterns. It is also shown that 10-15 templates are sufficient for accurate segmentation in this application.
Subject(s)
Cartilage Diseases/pathology , Cartilage, Articular/pathology , Hip Joint/pathology , Imaging, Three-Dimensional/methods , Osteoarthritis, Hip/pathology , Adolescent , Adult , Cartilage Diseases/etiology , Female , Gadolinium , Humans , Image Processing, Computer-Assisted/methods , Magnetic Resonance Imaging , Male , Middle Aged , Osteoarthritis, Hip/complications , Retrospective Studies , Severity of Illness Index , Young AdultABSTRACT
Neurologic impairment is a major complication of complex congenital heart disease (CHD). A growing body of evidence suggests that neurologic dysfunction may be present in a significant proportion of this high-risk population in the early newborn period prior to surgical interventions. We recently provided the first evidence that brain growth impairment in fetuses with complex CHD has its origins in utero. Here, we extend these observations by characterizing global and regional brain development in fetuses with hypoplastic left heart syndrome (HLHS), one of the most severe forms of CHD. Using advanced magnetic resonance imaging techniques, we compared in vivo brain growth in 18 fetuses with HLHS and 30 control fetuses from 25.4-37.0 weeks of gestation. Our findings demonstrate a progressive third trimester fall-off in cortical gray and white matter volumes (P < 0.001), and subcortical gray matter (P < 0.05) in fetuses with HLHS. Significant delays in cortical gyrification were also evident in HLHS fetuses (P < 0.001). In the HLHS fetus, local cortical folding delays were detected as early as 25 weeks in the frontal, parietal, calcarine, temporal, and collateral regions and appear to precede volumetric brain growth disturbances, which may be an early marker of elevated risk for third trimester brain growth failure.
Subject(s)
Cerebral Cortex/abnormalities , Fetus/abnormalities , Hypoplastic Left Heart Syndrome/pathology , Female , Humans , Magnetic Resonance Imaging , Male , PregnancyABSTRACT
BACKGROUND AND PURPOSE: Little is known about microstructural development of cerebellar white matter in vivo. This study aimed to investigate developmental changes of the cerebellar peduncles in second- and third-trimester healthy fetuses using motion-corrected DTI and tractography. MATERIALS AND METHODS: 3T data of 81 healthy fetuses were reviewed. Structural imaging consisted of multiplanar T2-single-shot sequences; DTI consisted of a series of 12-direction diffusion. A robust motion-tracked section-to-volume registration algorithm reconstructed images. ROI-based deterministic tractography was performed using anatomic landmarks described in postnatal tractography. Asymmetry was evaluated qualitatively with a perceived difference of >25% between sides. Linear regression evaluated gestational age as a predictor of tract volume, ADC, and fractional anisotropy. RESULTS: Twenty-four cases were excluded due to low-quality reconstructions. Fifty-eight fetuses with a median gestational age of 30.6 weeks (interquartile range, 7 weeks) were analyzed. The superior cerebellar peduncle was identified in 39 subjects (69%), and it was symmetric in 15 (38%). The middle cerebellar peduncle was identified in all subjects and appeared symmetric; in 13 subjects (22%), two distinct subcomponents were identified. The inferior cerebellar peduncle was not found in any subject. There was a significant increase in volume for the superior cerebellar peduncle and middle cerebellar peduncle (both, P < .05), an increase in fractional anisotropy (both, P < .001), and a decrease in ADC (both, P < .001) with gestational age. The middle cerebellar peduncle had higher volume (P < .001) and fractional anisotropy (P = .002) and lower ADC (P < .001) than the superior cerebellar peduncle after controlling for gestational age. CONCLUSIONS: A robust motion-tracked section-to-volume registration algorithm enabled deterministic tractography of the superior cerebellar peduncle and middle cerebellar peduncle in vivo and allowed characterization of developmental changes.
Subject(s)
Algorithms , Cerebellum/embryology , Diffusion Tensor Imaging/methods , Image Processing, Computer-Assisted/methods , Neurogenesis , Female , Fetus , Humans , Male , Neurogenesis/physiology , Pregnancy , Pregnancy Trimester, Third , Retrospective StudiesABSTRACT
BACKGROUND AND PURPOSE: Brain MRI of newborns with congenital heart disease show signs of immaturity relative to healthy controls. Our aim was to determine whether the semiquantitative fetal total maturation score can detect abnormalities in brain maturation in fetuses with congenital heart disease in the second and third trimesters. MATERIALS AND METHODS: We analyzed data from a prospective study of fetuses with and without congenital heart disease who underwent fetal MR imaging at 25-35 weeks' gestation. Two independent neuroradiologists blinded to the clinical data reviewed and scored all images using the fetal total maturation score. Interrater reliability was evaluated by the intraclass correlation coefficient using the individual reader scores, which were also used to calculate an average score for each subject. Comparisons of the average and individual reader scores between affected and control fetuses and relationships with clinical variables were evaluated using multivariable linear regression. RESULTS: Data from 69 subjects (48 cardiac, 21 controls) were included. High concordance was observed between readers with an intraclass correlation coefficient of 0.98 (95% CI, 0.97-0.99). The affected group had significantly lower fetal total maturation scores than the control group (ß-estimate, -0.9 [95% CI, -1.5 to -0.4], P = .002), adjusting for gestational age and sex. Averaged fetal total maturation, germinal matrix, myelination, and superior temporal sulcus scores were significantly delayed in fetuses with congenital heart disease versus controls (P < .05 for each). The fetal total maturation score was not significantly associated with any cardiac, anatomic, or physiologic variables. CONCLUSIONS: The fetal total maturation score is sensitive to differences in brain maturation between fetuses with isolated congenital heart disease and healthy controls.
Subject(s)
Brain/abnormalities , Brain/embryology , Fetus/diagnostic imaging , Fetus/embryology , Heart Defects, Congenital/complications , Adult , Brain/diagnostic imaging , Female , Humans , Image Interpretation, Computer-Assisted/methods , Infant, Newborn , Magnetic Resonance Imaging/methods , Male , Pregnancy , Prenatal Diagnosis/methods , Prospective Studies , Reproducibility of ResultsABSTRACT
The major goal of the evaluation in presurgical epilepsy diagnosis for medically intractable patients is the precise reconstruction of the epileptogenic foci, preferably with non-invasive methods. This paper evaluates whether surface electroencephalography (EEG) source analysis based on a 1 mm anisotropic finite element (FE) head model can provide additional guidance for presurgical epilepsy diagnosis and whether it is practically feasible in daily routine. A 1 mm hexahedra FE volume conductor model of the patient's head with special focus on accurately modeling the compartments skull, cerebrospinal fluid (CSF) and the anisotropic conducting brain tissues was constructed using non-linearly co-registered T1-, T2- and diffusion-tensor-magnetic resonance imaging data. The electrodes of intra-cranial EEG (iEEG) measurements were extracted from a co-registered computed tomography image. Goal function scan (GFS), minimum norm least squares (MNLS), standardized low resolution electromagnetic tomography (sLORETA) and spatio-temporal current dipole modeling inverse methods were then applied to the peak of the averaged ictal discharges EEG data. MNLS and sLORETA pointed to a single center of activity. Moving and rotating single dipole fits resulted in an explained variance of more than 97%. The non-invasive EEG source analysis methods localized at the border of the lesion and at the border of the iEEG electrodes which mainly received ictal discharges. Source orientation was towards the epileptogenic tissue. For the reconstructed superficial source, brain conductivity anisotropy and the lesion conductivity had only a minor influence, whereas a correct modeling of the highly conducting CSF compartment and the anisotropic skull was found to be important. The proposed FE forward modeling approach strongly simplifies meshing and reduces run-time (37 ms for one forward computation in the model with 3.1 million unknowns), corroborating the practical feasibility of the approach.
Subject(s)
Brain Mapping/methods , Brain/physiopathology , Diagnosis, Computer-Assisted/methods , Electroencephalography/methods , Epilepsy/diagnosis , Epilepsy/physiopathology , Models, Neurological , Child , Computer Simulation , Finite Element Analysis , Humans , Male , Reproducibility of Results , Sensitivity and SpecificityABSTRACT
In the human brain, the morphology of cortical gyri and sulci is complex and variable among individuals, and it may reflect pathological functioning with specific abnormalities observed in certain developmental and neuropsychiatric disorders. Since cortical folding occurs early during brain development, these structural abnormalities might be present long before the appearance of functional symptoms. So far, the precise mechanisms responsible for such alteration in the convolution pattern during intra-uterine or post-natal development are still poorly understood. Here we compared anatomical and functional brain development in vivo among 45 premature newborns who experienced different intra-uterine environments: 22 normal singletons, 12 twins and 11 newborns with intrauterine growth restriction (IUGR). Using magnetic resonance imaging (MRI) and dedicated post-processing tools, we investigated early disturbances in cortical formation at birth, over the developmental period critical for the emergence of convolutions (26-36 weeks of gestational age), and defined early 'endophenotypes' of sulcal development. We demonstrated that twins have a delayed but harmonious maturation, with reduced surface and sulcation index compared to singletons, whereas the gyrification of IUGR newborns is discordant to the normal developmental trajectory, with a more pronounced reduction of surface in relation to the sulcation index compared to normal newborns. Furthermore, we showed that these structural measurements of the brain at birth are predictors of infants' outcome at term equivalent age, for MRI-based cerebral volumes and neurobehavioural development evaluated with the assessment of preterm infant's behaviour (APIB).
Subject(s)
Cerebral Cortex/anatomy & histology , Image Processing, Computer-Assisted , Infant, Premature , Magnetic Resonance Imaging , Cerebral Cortex/pathology , Child Development , Female , Fetal Growth Retardation/pathology , Follow-Up Studies , Humans , Infant Behavior/physiology , Infant, Newborn , Infant, Very Low Birth Weight , Linear Models , Male , Neuropsychological Tests , Pregnancy , TwinsABSTRACT
The dynamical structure of the brain's electrical signals contains valuable information about its physiology. Here we combine techniques for nonlinear dynamical analysis and manifold identification to reveal complex and recurrent dynamics in interictal epileptiform discharges (IEDs). Our results suggest that recurrent IEDs exhibit some consistent dynamics, which may only last briefly, and so individual IED dynamics may need to be considered in order to understand their genesis. This could potentially serve to constrain the dynamics of the inverse source localization problem.
ABSTRACT
OBJECTIVE: To investigate the relationship between magnetic resonance imaging regional lesion burden and cognitive performance in multiple sclerosis (MS) over a 4-year follow-up period. DESIGN: Twenty-eight patients with MS underwent magnetic resonance imaging and took the Brief, Repeatable Battery of Neuropsychological Tests in Multiple Sclerosis at baseline, 1-year, and 4-year follow-up. An automated 3-dimensional lesion detection method was used to identify MS lesions within anatomical regions on proton density T2-weighted images. The relationship between magnetic resonance imaging regional lesion volumes and the Brief, Repeatable Battery of Neuropsychological Tests in Multiple Sclerosis results was examined using regression analyses. RESULTS: At all time points, frontal lesion volume represented the greatest proportion of total lesion volume, and the percentage of white matter classified as lesion was also highest in frontal and parietal regions. On neuropsychological testing, when compared with age- and educational level-matched control subjects, patients with MS showed significant impairment on tests of sustained attention, processing speed, and verbal memory (P<.001). Performance on these measures was negatively correlated with MS lesion volume in frontal and parietal regions at baseline, 1-year, and 4-year follow-up (R = -0.55 to -0.73, P<.001). CONCLUSIONS: Multiple sclerosis lesions show a propensity for frontal and parietal white matter. Lesion burden in these areas was strongly associated with performance on tasks requiring sustained complex attention and working verbal memory. This relationship was consistent over a 4-year period, suggesting that disruption of frontoparietal subcortical networks may underlie the pattern of neuropsychological impairment seen in many patients with MS.
Subject(s)
Cognition Disorders/diagnosis , Cognition Disorders/etiology , Magnetic Resonance Imaging , Multiple Sclerosis/complications , Multiple Sclerosis/diagnosis , Adult , Depression/diagnosis , Depression/etiology , Disability Evaluation , Female , Frontal Lobe/pathology , Humans , Male , Middle Aged , Multiple Sclerosis/physiopathology , Neural Pathways/physiopathology , Neuropsychological Tests , Parietal Lobe/pathology , Regression Analysis , Severity of Illness IndexABSTRACT
BACKGROUND: Recent investigations using MRI suggest that older persons with mobility impairment have a greater volume of abnormal cerebral white matter compared with persons with normal mobility, thus raising the possibility that those with impairment have lesions in areas critical for the control of mobility. OBJECTIVE: To utilize automated image analysis methods to localize the specific regions of abnormal white matter that distinguish subjects with lower mobility from subjects with higher mobility. METHODS: Tissue classification was performed on subjects' dual-echo long repetition time spin-echo MRI using computer algorithms operating on intensity criteria integrated with anatomic information. Statistical analysis of group differences was obtained after spatially normalizing each brain to a standard reference brain. RESULTS: Four discrete periventricular regions, including bilaterally symmetric frontal and bilateral occipitoparietal regions, were identified as being sensitive (frontal) or specific (occipitoparietal) in discriminating the subjects with lower mobility from subjects with higher mobility. The symmetry of these lesions in individual subjects suggested pathology other than arteriolar infarction. CONCLUSIONS: These results suggest that damage to discrete frontal and occipitoparietal periventricular white matter locations may be associated with a mobility disorder of aging.
Subject(s)
Brain/pathology , Movement Disorders/pathology , Aged , Aged, 80 and over , Female , Gait/physiology , Humans , Male , Movement Disorders/physiopathology , Predictive Value of Tests , Sensitivity and SpecificityABSTRACT
OBJECTIVE: To investigate the relationship between white matter abnormalities and impairment of gait and balance in older persons. METHODS: Quantitative MRI was used to evaluate the brain tissue compartments of 28 older individuals separated into normal and impaired groups on the basis of mobility performance testing using the Short Physical Performance Battery. In addition, individuals were tested on six indices of gait and balance. For imaging data, segmentation of intracranial volume into four tissue classes was performed using template-driven segmentation, in which signal-intensity-based statistical tissue classification is refined using a digital brain atlas as anatomic template. RESULTS: Both decreased white matter volume, which was age-related, and increased white matter signal abnormalities, which were not age-related, were observed in the mobility-impaired group compared with the control subjects. The average volume of white matter signal abnormalities for impaired individuals was nearly double that of control subjects. CONCLUSIONS: This cross-sectional study suggests that decreased white matter volume is age-related, whereas increased white matter signal abnormalities are most likely to occur as a result of disease. Both of these changes are independently associated with impaired mobility in older persons and therefore likely to be additive factors of motor disability.
Subject(s)
Brain/pathology , Movement Disorders/pathology , Aged , Aged, 80 and over , Female , Gait/physiology , Humans , Magnetic Resonance Imaging , Male , Movement Disorders/physiopathology , Postural Balance/physiologyABSTRACT
RATIONALE AND OBJECTIVES: To improve the conspicuity of bladder tumors in a virtual environment, we developed an algorithm for color mapping the thickness of the bladder wall. The purpose of this study was to demonstrate the feasibility of this algorithm as a component of virtual CT cystoscopy. METHODS: Five subjects with a history of superficial transitional-cell carcinoma of the bladder underwent helical CT scanning after insufflation of the bladder with air. Source images were transformed into three-dimensional models, and the thickness of the bladder wall was demarcated by using a new computer algorithm and a fixed color scale. Results were compared with those obtained by conventional cystoscopy. RESULTS: Three tumors, one site of benign wall thickening, and normal wall thickness were correctly identified by using axial source images and virtual cystoscopy with color mapping. CONCLUSIONS: Color mapping of bladder wall thickness is feasible and demonstrates both normal and thickened urothelium. Its value in identification of small or sessile tumors will require further trials.
Subject(s)
Carcinoma, Transitional Cell/diagnostic imaging , Cystoscopy/methods , Tomography, X-Ray Computed , Urinary Bladder Neoplasms/diagnostic imaging , Aged , Algorithms , Color , Feasibility Studies , Female , Humans , Image Processing, Computer-Assisted , Male , Middle AgedABSTRACT
In this report we evaluate an image registration technique that can improve the information content of intraoperative image data by deformable matching of preoperative images. In this study, pretreatment 1.5 tesla (T) magnetic resonance (MR) images of the prostate are registered with 0.5 T intraoperative images. The method involves rigid and nonrigid registration using biomechanical finite element modeling. Preoperative 1.5 T MR imaging is conducted with the patient supine, using an endorectal coil, while intraoperatively, the patient is in the lithotomy position with a rectal obturator in place. We have previously observed that these changes in patient position and rectal filling produce a shape change in the prostate. The registration of 1.5 T preoperative images depicting the prostate substructure [namely central gland (CG) and peripheral zone (PZ)] to 0.5 T intraoperative MR images using this method can facilitate the segmentation of the substructure of the gland for radiation treatment planning. After creating and validating a dataset of manually segmented glands from images obtained in ten sequential MR-guided brachytherapy cases, we conducted a set of experiments to assess our hypothesis that the proposed registration system can significantly improve the quality of matching of the total gland (TG), CG, and PZ. The results showed that the method statistically-significantly improves the quality of match (compared to rigid registration), raising the Dice similarity coefficient (DSC) from prematched coefficients of 0.81, 0.78, and 0.59 for TG, CG, and PZ, respectively, to 0.94, 0.86, and 0.76. A point-based measure of registration agreement was also improved by the deformable registration. CG and PZ volumes are not changed by the registration, indicating that the method maintains the biomechanical topology of the prostate. Although this strategy was tested for MRI-guided brachytherapy, the preliminary results from these experiments suggest that it may be applied to other settings such as transrectal ultrasound-guided therapy, where the integration of preoperative MRI may have a significant impact upon treatment planning and guidance.
Subject(s)
Image Processing, Computer-Assisted , Prostatic Neoplasms/pathology , Prostatic Neoplasms/surgery , Biophysical Phenomena , Biophysics , Brachytherapy/methods , Humans , Magnetic Resonance Imaging/methods , Male , Prostate/pathology , Reproducibility of ResultsABSTRACT
OBJECTIVE: A major shortcoming of image-guided navigational systems is the use of preoperatively acquired image data, which does not account for intraoperative changes in brain morphology. The occurrence of these surgically induced volumetric deformations ("brain shift") has been well established. Maximal measurements for surface and midline shifts have been reported. There has been no detailed analysis, however, of the changes that occur during surgery. The use of intraoperative magnetic resonance imaging provides a unique opportunity to obtain serial image data and characterize the time course of brain deformations during surgery. METHODS: The vertically open intraoperative magnetic resonance imaging system (SignaSP, 0.5 T; GE Medical Systems, Milwaukee, WI) permits access to the surgical field and allows multiple intraoperative image updates without the need to move the patient. We developed volumetric display software (the 3D Slicer) that allows quantitative analysis of the degree and direction of brain shift. For 25 patients, four or more intraoperative volumetric image acquisitions were extensively evaluated. RESULTS: Serial acquisitions allow comprehensive sequential descriptions of the direction and magnitude of intraoperative deformations. Brain shift occurs at various surgical stages and in different regions. Surface shift occurs throughout surgery and is mainly attributable to gravity. Subsurface shift occurs during resection and involves collapse of the resection cavity and intraparenchymal changes that are difficult to model. CONCLUSION: Brain shift is a continuous dynamic process that evolves differently in distinct brain regions. Therefore, only serial imaging or continuous data acquisition can provide consistently accurate image guidance. Furthermore, only serial intraoperative magnetic resonance imaging provides an accurate basis for the computational analysis of brain deformations, which might lead to an understanding and eventual simulation of brain shift for intraoperative guidance.
Subject(s)
Brain Diseases/surgery , Image Processing, Computer-Assisted/instrumentation , Imaging, Three-Dimensional/instrumentation , Intraoperative Complications/diagnosis , Magnetic Resonance Imaging/instrumentation , Stereotaxic Techniques/instrumentation , User-Computer Interface , Adult , Brain/pathology , Brain/surgery , Brain Diseases/diagnosis , Brain Neoplasms/diagnosis , Brain Neoplasms/surgery , Equipment Design , Female , Frontal Lobe/pathology , Frontal Lobe/surgery , Humans , Intraoperative Complications/surgery , Male , Numerical Analysis, Computer-Assisted , Oligodendroglioma/diagnosis , Oligodendroglioma/surgery , Parietal Lobe/pathology , Parietal Lobe/surgery , SoftwareABSTRACT
The watershed transform has interesting properties that make it useful for many different image segmentation applications: it is simple and intuitive, can be parallelized, and always produces a complete division of the image. However, when applied to medical image analysis, it has important drawbacks (oversegmentation, sensitivity to noise, poor detection of thin or low signal to noise ratio structures). We present an improvement to the watershed transform that enables the introduction of prior information in its calculation. We propose to introduce this information via the use of a previous probability calculation. Furthermore, we introduce a method to combine the watershed transform and atlas registration, through the use of markers. We have applied our new algorithm to two challenging applications: knee cartilage and gray matter/white matter segmentation in MR images. Numerical validation of the results is provided, demonstrating the strength of the algorithm for medical image segmentation.
Subject(s)
Algorithms , Brain/anatomy & histology , Cartilage/anatomy & histology , Image Enhancement/methods , Image Interpretation, Computer-Assisted/methods , Imaging, Three-Dimensional/methods , Models, Biological , Subtraction Technique , Computer Simulation , Knee Joint/anatomy & histology , Magnetic Resonance Imaging/methods , Models, Statistical , Pattern Recognition, Automated , Reproducibility of Results , Sensitivity and Specificity , Signal Processing, Computer-AssistedABSTRACT
We present a new algorithm for the nonrigid registration of three-dimensional magnetic resonance (MR) intraoperative image sequences showing brain shift. The algorithm tracks key surfaces of objects (cortical surface and the lateral ventricles) in the image sequence using a deformable surface matching algorithm. The volumetric deformation field of the objects is then inferred from the displacements at the boundary surfaces using a linear elastic biomechanical finite-element model. Two experiments on synthetic image sequences are presented, as well as an initial experiment on intraoperative MR images showing brain shift. The results of the registration algorithm show a good correlation of the internal brain structures after deformation, and a good capability of measuring surface as well as subsurface shift. We measured distances between landmarks in the deformed initial image and the corresponding landmarks in the target scan. Cortical surface shifts of up to 10 mm and subsurface shifts of up to 6 mm were recovered with an accuracy of 1 mm or less and 3 mm or less respectively.
Subject(s)
Brain/physiology , Imaging, Three-Dimensional/methods , Magnetic Resonance Imaging/methods , Models, Neurological , Algorithms , Anisotropy , Elasticity , Finite Element Analysis , Humans , Intraoperative Period/methods , Models, Theoretical , Phantoms, Imaging , Reproducibility of Results , Sensitivity and SpecificityABSTRACT
A novel image segmentation algorithm was developed to allow the automatic segmentation of both normal and abnormal anatomy from medical images. The new algorithm is a form of spatially varying statistical classification, in which an explicit anatomical template is used to moderate the segmentation obtained by statistical classification. The algorithm consists of an iterated sequence of spatially varying classification and nonlinear registration, which forms an adaptive, template moderated (ATM), spatially varying statistical classification (SVC). Classification methods and nonlinear registration methods are often complementary, both in the tasks where they succeed and in the tasks where they fail. By integrating these approaches the new algorithm avoids many of the disadvantages of each approach alone while exploiting the combination. The ATM SVC algorithm was applied to several segmentation problems, involving different image contrast mechanisms and different locations in the body. Segmentation and validation experiments were carried out for problems involving the quantification of normal anatomy (MRI of brains of neonates) and pathology of various types (MRI of patients with multiple sclerosis, MRI of patients with brain tumors, MRI of patients with damaged knee cartilage). In each case, the ATM SVC algorithm provided a better segmentation than statistical classification or elastic matching alone.
Subject(s)
Image Processing, Computer-Assisted , Magnetic Resonance Imaging , Algorithms , Brain/anatomy & histology , Brain/pathology , Brain Neoplasms/pathology , Cartilage, Articular/injuries , Cartilage, Articular/pathology , Humans , Image Processing, Computer-Assisted/methods , Infant, Newborn , Knee Joint/pathology , Multiple Sclerosis/pathologyABSTRACT
New medical imaging modalities offering multi-valued data, such as phase contrast MRA and diffusion tensor MRI, require general representations for the development of automated algorithms. In this paper we propose a unified framework for the registration of medical volumetric multi-valued data using local matching. The paper extends the usual concept of similarity between two pieces of data to be matched, commonly used with scalar (intensity) data, to the general tensor case. Our approach to registration is based on a multiresolution scheme, where the deformation field estimated in a coarser level is propagated to provide an initial deformation in the next finer one. In each level, local matching of areas with a high degree of local structure and subsequent interpolation are performed. Consequently, we provide an algorithm to assess the amount of structure in generic multi-valued data by means of gradient and correlation computations. The interpolation step is carried out by means of the Kriging estimator, which provides a novel framework for the interpolation of sparse vector fields in medical applications. The feasibility of the approach is illustrated by results on synthetic and clinical data.