Machine Learning in Differentiating Gliomas from Primary CNS Lymphomas: A Systematic Review, Reporting Quality, and Risk of Bias Assessment.

BACKGROUND: Differentiating gliomas and primary CNS lymphoma represents a diagnostic challenge with important therapeutic ramifications. Biopsy is the preferred method of diagnosis, while MR imaging in conjunction with machine learning has shown promising results in differentiating these tumors. PURPOSE: Our aim was to evaluate the quality of reporting and risk of bias, assess data bases with which the machine learning classification algorithms were developed, the algorithms themselves, and their performance. DATA SOURCES: Ovid EMBASE, Ovid MEDLINE, Cochrane Central Register of Controlled Trials, and the Web of Science Core Collection were searched according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. STUDY SELECTION: From 11,727 studies, 23 peer-reviewed studies used machine learning to differentiate primary CNS lymphoma from gliomas in 2276 patients. DATA ANALYSIS: Characteristics of data sets and machine learning algorithms were extracted. A meta-analysis on a subset of studies was performed. Reporting quality and risk of bias were assessed using the Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) and Prediction Model Study Risk Of Bias Assessment Tool. DATA SYNTHESIS: The highest area under the receiver operating characteristic curve (0.961) and accuracy (91.2%) in external validation were achieved by logistic regression and support vector machines models using conventional radiomic features. Meta-analysis of machine learning classifiers using these features yielded a mean area under the receiver operating characteristic curve of 0.944 (95% CI, 0.898-0.99). The median TRIPOD score was 51.7%. The risk of bias was high for 16 studies. LIMITATIONS: Exclusion of abstracts decreased the sensitivity in evaluating all published studies. Meta-analysis had high heterogeneity. CONCLUSIONS: Machine learning-based methods of differentiating primary CNS lymphoma from gliomas have shown great potential, but most studies lack large, balanced data sets and external validation. Assessment of the studies identified multiple deficiencies in reporting quality and risk of bias. These factors reduce the generalizability and reproducibility of the findings.

Scientific Collaboration across Time and Space: Bibliometric Analysis of the American Journal of Neuroradiology, 1980-2018.

BACKGROUND AND PURPOSE: Scientific collaboration is traditionally acknowledged through coauthorship. Studies on this topic are few in the neuroimaging literature. This study is a bibliometric analysis of the American Journal of Neuroradiology (AJNR) between 1980 and 2018, with the primary aim of evaluating changes in article collaboration. MATERIALS AND METHODS: Full bibliographic records from 1980 to 2018 were retrieved. Yearly metrics calculated included the number of articles published, the average number of authors, and the average number of affiliations per article. The levels of evidence of 160 random articles were determined. Geographic characteristics of author affiliations were analyzed. Changes across time were evaluated using linear regression, while Spearman rank-order correlation was used to determine relationships between level of evidence and time, number of authors, and number of affiliations. RESULTS: There was a steady linear growth in the number of articles (R 2 = 0.70, P < 1e-10) from 1980 to 2018. There were clear linear increases in the average number of authors (R 2 = 0.91, P < 1e-15) and affiliations (R 2 = 0.90, P < 1e-15) per article. There was a significant correlation between level of evidence and time period (Spearman ρ = -0.42, P < 1e-7), indicating that articles trended toward better methodologic quality or strength of results over time. A significant correlation existed between the level of evidence and the number of authors (Spearman ρ = -0.39, P < 1e-6). There were linear increases in the average number of different geographic locales of authors per article by country/region (R 2 = 0.80, P < 1e-13), state/province (R 2 = 0.88, P < 1e-15), and locality/city/town (R 2 = 0.86, P < 1e-15). CONCLUSIONS: From 1980 to 2018, as the quantity of articles published in the AJNR increased, their level of evidence improved, while an increasing number of authors with different affiliations and from different geographic locales collaborated on these articles.

AUGMENTED INLINE-BASED NAVIGATION FOR STEREOTACTIC IMAGE GUIDED NEUROSURGERY.

Image-guided neurosurgery requires navigation in 3D using a computer-assisted surgery system that tracks surgical tools in realtime and displays their positions with respect to the preoperatively acquired images (e.g. CT, MRI, fMRI etc.) A key problem in image guided procedures is the need to navigate to specific locations highlighted in the images, such as image-derived functional areas, that have no obvious corresponding anatomical landmarks - we refer to such locations as virtual landmarks. To address these issues, we contribute a novel interactive visualization technique to provide improved feedback to surgeons - Augmented inline visualization. Based on the results of an expert evaluation, we found neurosurgeons to be 30% more accurate when using our augmented inline representation.

LIGHT-SENSITIVE VISUALIZATION OF MULTIMODAL DATA FOR NEUROSURGICAL APPLICATIONS.

We present a technique for enhancing multimodal visualizations for image-guided neurosurgery in the presence of adverse lighting conditions. In the surgical environment, images used for real time navigation are displayed in suboptimal conditions due to the varying lighting conditions. Our approach actively monitors the incoming light on the display and appropriately enhances the visualization based on the change in light. Based on the results of a user study to evaluate our approach, we found that our enhanced visualization techniques were mostly preferred over regular visualizations.

Constrained non-rigid registration for use in image-guided adaptive radiotherapy.

A constrained non-rigid registration (CNRR) algorithm for use in prostate image-guided adaptive radiotherapy is presented in a coherent mathematical framework. The registration algorithm is based on a global rigid transformation combined with a series of local injective non-rigid multi-resolution cubic B-spline Free Form Deformation (FFD) transformations. The control points of the FFD are used to non-rigidly constrain the transformation to the prostate, rectum, and bladder. As well, the control points are used to rigidly constrain the transformation to the estimated position of the pelvis, left femur, and right femur. The algorithm was tested with both 3D conformal radiotherapy (3DCRT) and intensity-modulated radiotherapy (IMRT) dose plan data sets. The 3DCRT dose plan set consisted of 10 fan-beam CT (FBCT) treatment-day images acquired from four different patients. The IMRT dose plan set consisted of 32 cone-beam CT (CBCT) treatment-day images acquired from 4 different patients. The CNRR was tested with different combinations of anatomical constraints and each test significantly outperformed both rigid and non-rigid registration at aligning constrained bones and critical organs. The CNRR results were used to adapt the dose plans to account for patient positioning errors as well as inter-day bone motion and intrinsic organ deformation. Each adapted dose plan improved performance by lowering radiation distribution to the rectum and bladder while increasing or maintaining radiation distribution to the prostate.

DTI abnormalities in anterior corpus callosum of rats with spike-wave epilepsy.

OBJECTIVE: Absence epilepsy is a common seizure disorder in children which can produce chronic psychosocial sequelae. Human patients and rat absence models show bilateral spike-wave discharges (SWD) in cortical regions. We employed diffusion tensor imaging (DTI) in rat absence models to detect abnormalities in white matter pathways connecting regions of seizure activity. METHODS: We studied Wistar albino Glaxo rats of Rijswijk (WAG/Rij), genetic absence epilepsy rats of Strasbourg (GAERS), and corresponding nonepileptic control strains. Ex vivo DTI was performed at 9.4 T with diffusion gradients applied in 16 orientations. We compared fractional anisotropy (FA), perpendicular (lambda(perpendicular)) and parallel (lambda(||)) diffusivity between groups using t-maps and region of interest (ROI) measurements. RESULTS: Adult epileptic WAG/Rij rats exhibited a localized decrease in FA in the anterior corpus callosum. This area was confirmed by tractography to interconnect somatosensory cortex regions most intensely involved in seizures. This FA decrease was not present in young WAG/Rij rats before onset of SWD. GAERS, which have more severe SWD than WAG/Rij, exhibited even more pronounced callosal FA decreases. Reduced FA in the epileptic animals originated from an increased lambda(perpendicular) with no significant changes in lambda(||). INTERPRETATION: Reduced FA with increased lambda(perpendicular) suggests that chronic seizures cause reduction in myelin or decreased axon fiber density in white matter pathways connecting regions of seizure activity. These DTI abnormalities may improve the understanding of chronic neurological difficulties in children suffering with absence epilepsy, and may also serve as a noninvasive biomarker for monitoring beneficial effects of treatment.

Improving the Reliability of Shape Comparison by Perturbation.

Shape comparison is a key scenario in morphometric study, where registration is often involved and found to be unreliable: different registrations can lead to different shape differences. This paper proposes a generic scheme applicable to most registration methods, to reduce this unreliability. It perturbs the registration processes by feeding them with resampled shape groups, and then aggregates the results to yield the final result. This scheme can be simplified for pair-wise registration methods to reduce the computation. Experiments are conducted on both synthetic and biomedical shapes using different registration methods, which demonstrate its effectiveness.

A constrained non-rigid registration algorithm for use in prostate image-guided radiotherapy.

A constrained non-rigid registration (CNRR) algorithm for use in updating prostate external beam image-guided radiotherapy treatment plans is presented in this paper. The developed algorithm is based on a multi-resolution cubic B-spline FFD transformation and has been tested and verified using 3D CT images from 10 sets of real patient data acquired from 4 different patients on different treatment days. The registration can be constrained to any combination of the prostate, rectum, bladder, pelvis, left femur, and right femur. The CNRR was tested with 5 different combinations of constraints and each test significantly outperformed both rigid and non-rigid registration at aligning constrained bones and critical organs. The CNRR was then used to update the treatment plans to account for articulated, rigid bone motion and non-rigid organ deformation. Each updated treatment plan outperformed the original treatment plan by increasing radiation dosage to the prostate and lowering radiation dosage to the rectum and bladder.

Using perturbation theory to compute the morphological similarity of diffusion tensors.

Computing the morphological similarity of diffusion tensors (DTs) at neighboring voxels within a DT image, or at corresponding locations across different DT images, is a fundamental and ubiquitous operation in the postprocessing of DT images. The morphological similarity of DTs typically has been computed using either the principal directions (PDs) of DTs (i.e., the direction along which water molecules diffuse preferentially) or their tensor elements. Although comparing PDs allows the similarity of one morphological feature of DTs to be visualized directly in eigenspace, this method takes into account only a single eigenvector, and it is therefore sensitive to the presence of noise in the images that can introduce error intothe estimation of that vector. Although comparing tensor elements, rather than PDs, is comparatively more robust to the effects of noise, the individual elements of a given tensor do not directly reflect the diffusion properties of water molecules. We propose a measure for computing the morphological similarity of DTs that uses both their eigenvalues and eigenvectors, and that also accounts for the noise levels present in DT images. Our measure presupposes that DTs in a homogeneous region within or across DT images are random perturbations of one another in the presence of noise. The similarity values that are computed using our method are smooth (in the sense that small changes in eigenvalues and eigenvectors cause only small changes in similarity), and they are symmetric when differences in eigenvalues and eigenvectors are also symmetric. In addition, our method does not presuppose that the corresponding eigenvectors across two DTs have been identified accurately, an assumption that is problematic in the presence of noise. Because we compute the similarity between DTs using their eigenspace components, our similarity measure relates directly to both the magnitude and the direction of the diffusion of water molecules. The favorable performance characteristics of our measure offer the prospect of substantially improving additional postprocessing operations that are commonly performed on DTI datasets, such as image segmentation, fiber tracking, noise filtering, and spatial normalization.

TRACKING ORGAN OVERLAP FOR A CONSTRAINED NON-RIGID REGISTRATION ALGORITHM.

This paper tracks organ (prostate, rectum, bladder) overlap in a constrained non-rigid registration (NRR) algorithm to register computed tomographic (CT) images used in external beam prostate radiotherapy. The local motion of the organs is described by a hierarchical multi-resolution FFD based on cubic B-splines. Registration is achieved by minimizing a cost function which is a combination of three functions representing the overlap of the critical organs, image similarity and smoothness of the transformation. The constrained NRR algorithm generated better registration results when compared to an unconstrained NRR algorithm.

A new method for quantification of spatial and temporal parameters of endocardial motion: evaluation of experimental infarction using magnetic resonance imaging.

BACKGROUND: With the development of high-resolution myocardial imaging there has evolved a need for automated techniques that can accurately quantify regional function. OBJECTIVE: To develop a new method for quantification of spatial and temporal parameters of endocardial motion. DESIGN: Magnetic resonance images were analyzed using a unique, shape-based approach that tracks endocardial surface motion at defined points through the cardiac cycle by minimizing the bending energy. SETTING: Animal instrumentation was performed in the Nuclear Cardiology Experimental Research Laboratory at Yale University, New Haven, Connecticut. Magnetic resonance imaging was performed at the Yale New Haven Hospital Center. ANIMALS: Eight mongrel canines were used. INTERVENTIONS: Electrocardiograph-gated gradient-echo magnetic resonance images were obtained before and after occlusion of the left anterior descending coronary. Thirty-two points along automatically defined endocardial contours were tracked. Average displacements and cumulative path lengths were computed from end-diastole for each point over the entire cardiac cycle. The average cumulative path length was computed for each of four quarters of systole for the normal, border and infarct zones. Shape-based parameters of systolic motion were compared with the centreline approach. Infarct zone was defined by postmortem histochemical staining. MAIN RESULTS: Displacement and cumulative path length over the cardiac cycle decreased significantly in the infarct and border zones (P<0.05), but did not change in the normal zone (P was not significant). Temporal changes in motion were observed in all zones. Displacement measured using the shape-based algorithm was more consistent than cumulative path length when compared with systolic motion measured using the centreline method. CONCLUSIONS: An automated, shape-based approach permits quantitative evaluation of both spatial and temporal parameters of regional endocardial motion from high-resolution electrocardiograph-gated images. Analysis of endocardial motion and cumulative motion over the entire cardiac cycle discriminated infarcted from normal and border regions.

Automated measurement of latent morphological features in the human corpus callosum.

Our objective was to develop a novel factor-based analysis of the morphology of the corpus callosum and assess its applicability to the study of normal development, intelligence, and other subject characteristics. The contour of the corpus callosum was defined in the midsagittal planes of the MRI scans of 325 subjects, 6 to 88 years of age. The contours were coregistered, rescaled, and resampled to 50 points that were then entered into a principal components analysis with varimax rotation. The analysis yielded 8 factors for the contours of 138 healthy subjects. A second analysis of contours from 187 subjects in a patient group extracted 8 similar factors. Correlations of factor scores with conventional measures of callosum shape supported the construct validity of the assignment of morphological features to each of the factors. Correlations of factor scores with age, sex, handedness, ventricular volume, and IQ demonstrated the predictive validity of the factor structure and helped to define the neural correlates of these subject characteristics. We conclude that factor-based measures capture latent morphological features of the corpus callosum that are reliable and valid. Future studies will determine whether these novel measures are more closely related to neurobiologically important features of the corpus than are conventional measures of callosum size and shape.

Gender differences in cognitive and neural correlates of remembrance of emotional words.

Studies suggest that men and women have important differences in specific cognitive functions. Men show superior spatial memory and women demonstrate superior verbal memory, and women rely on emotional content to a greater degree in the processing of information. In spite of extensive research in neural correlates of human cognition, little is known about possible gender differences or the role of emotional content in the mediation of cognition. Two sets of lists of word pairs were developed, one with neutral (e.g., school-grocery) and the other with emotional (e.g., mutilate-beat) content. Male and female subjects were asked to rate emotions related to the words on several dimensions (e.g., nervous, fearful, happy). In a second experiment, men and women underwent positron emission tomographic (PET) measurement of brain blood flow during retrieval of word pairs. Words in the "emotional" category were rated more highly on the emotional dimensions, and women rated them as having more emotional impact than did the men. During retrieval of emotional words (but not neutral words) there was a different pattern of activation among the women compared with the men, with greater activation in bilateral posterior hippocampus and cerebellum, and decreased activity in medial prefrontal cortex, which are brain areas previously implicated in emotion. There were no significant differences in retrieval of emotional versus neutral words, or in differences in memory performance between men and women. The findings suggest differences in cognitive appraisal and involvement of a broader network of brain regions mediating emotion during remembrance of emotional words in women compared with men.

Regional brain volume abnormalities and long-term cognitive outcome in preterm infants.

CONTEXT: Preterm infants have a high prevalence of long-term cognitive and behavioral disturbances. However, it is not known whether the stresses associated with premature birth disrupt regionally specific brain maturation or whether abnormalities in brain structure contribute to cognitive deficits. OBJECTIVE: To determine whether regional brain volumes differ between term and preterm children and to examine the association of regional brain volumes in prematurely born children with long-term cognitive outcomes. DESIGN AND SETTING: Case-control study conducted in 1998 and 1999 at 2 US university medical schools. PARTICIPANTS: A consecutive sample of 25 eight-year-old preterm children recruited from a longitudinal follow-up study of preterm infants and 39 term control children who were recruited from the community and who were comparable with the preterm children in age, sex, maternal education, and minority status. MAIN OUTCOME MEASURES: Volumes of cortical subdivisions, ventricular system, cerebellum, basal ganglia, corpus callosum, amygdala, and hippocampus, derived from structural magnetic resonance imaging scans and compared between preterm and term children; correlations of regional brain volumes with cognitive measures (at age 8 years) and perinatal variables among preterm children. RESULTS: Regional cortical volumes were significantly smaller in the preterm children, most prominently in sensorimotor regions (difference: left, 14.6%; right, 14.3% [P<.001 for both]) but also in premotor (left, 11.2%; right, 12.6% [P<.001 for both]), midtemporal (left, 7.4% [P =.01]; right, 10.2% [P<.001]), parieto-occipital (left, 7.9% [P =.01]; right, 7.4% [P =.005]), and subgenual (left, 8.9% [P =.03]; right, 11.7% [P =.01]) cortices. Preterm children's brain volumes were significantly larger (by 105. 7%-271.6%) in the occipital and temporal horns of the ventricles (P<. 001 for all) and smaller in the cerebellum (6.7%; P =.02), basal ganglia (11.4%-13.8%; P

Physical model-based non-rigid registration incorporating statistical shape information.

This paper describes two new atlas-based methods of 2D single modality non-rigid registration using the combined power of physical and statistical shape models. The transformations are constrained to be consistent with the physical properties of deformable elastic solids in the first method and those of viscous fluids in the second, to maintain smoothness and continuity. A Bayesian formulation, based on each physical model, an intensity similarity measure, and statistical shape information embedded in corresponding boundary points, is employed to derive more accurate and robust approaches to non-rigid registration. A dense set of forces arises from the intensity similarity measure to accommodate complex anatomical details. A sparse set of forces constrains consistency with statistical shape models derived from a training set. A number of experiments were performed on both synthetic and real medical images of the brain and heart to evaluate the approaches. It is shown that statistical boundary shape information significantly augments and improves physical model-based non-rigid registration and the two methods we present each have advantages under different conditions.

Temporal lobe volume in panic disorder--a quantitative magnetic resonance imaging study.

Although previous studies have used magnetic resonance imaging (MRI) to demonstrate qualitative abnormalities of the temporal lobes in patients with panic disorder, no study to date has applied quantitative volumetric methods to evaluate brain changes in panic disorder. The purpose of this study was to measure the volume of the temporal lobe and the hippocampus in patients with panic disorder and healthy control subjects using quantitative MRI measures. The volume of the temporal lobe, hippocampus and whole brain was measured in 13 patients with panic disorder and 14 healthy subjects. The mean volume of the left and right temporal lobes was significantly smaller in panic disorder compared to healthy subjects (16770+/-909 mm(3) vs. 18343+/-1740 mm(3)). This result was significant after controlling for differences in whole brain volume. There was no significant difference in volume of the hippocampus between patients and control subjects. These findings are consistent with smaller temporal lobe volume in panic disorder despite normal hippocampal volume.

Hippocampal volume reduction in major depression.

OBJECTIVE: Elevated levels of glucocorticoids in depression have been hypothesized to be associated with damage to the hippocampus, a brain area involved in learning and memory. The purpose of this study was to measure hippocampal volume in patients with depression. METHOD: Magnetic resonance imaging was used to measure the volume of the hippocampus in 16 patients with major depression in remission and 16 case-matched nondepressed comparison subjects. RESULTS: Patients with depression had a statistically significant 19% smaller left hippocampal volume than comparison subjects, without smaller volumes of comparison regions (amygdala, caudate, frontal lobe, and temporal lobe) or whole brain volume. The findings were significant after brain size, alcohol exposure, age, and education were controlled for. CONCLUSIONS: These findings are consistent with smaller left hippocampal volume in depression.

Kinetic modeling of benzodiazepine receptor binding with PET and high specific activity [(11)C]Iomazenil in healthy human subjects.

Quantitation of the PET benzodiazepine receptor antagonist, [(11)C]Iomazenil, using low specific activity radioligand was recently described. The purpose of this study was to quantitate benzodiazepine receptor binding in human subjects using PET and high specific activity [(11)C]Iomazenil. Six healthy human subjects underwent PET imaging following a bolus injection of high specific activity (>100 Ci/mmol) [(11)C]iomazenil. Arterial samples were collected at multiple time points after injection for measurement of unmetabolized total and nonprotein-bound parent compound in plasma. Time activity curves of radioligand concentration in brain and plasma were analyzed using two and three compartment model. Kinetic rate constants of transfer of radioligand between plasma, nonspecifically bound brain tissue, and specifically bound brain tissue compartments were fitted to the model. Values for fitted kinetic rate constants were used in the calculation of measures of benzodiazepine receptor binding, including binding potential (the ratio of receptor density to affinity), and product of BP and the fraction of free nonprotein-bound parent compound (V(3)'). Use of the three compartment model improved the goodness of fit in comparison to the two compartment model. Values for kinetic rate constants and measures of benzodiazepine receptor binding, including BP and V(3)', were similar to results obtained with the SPECT radioligand [(123)I]iomazenil, and a prior report with low specific activity [(11)C]Iomazenil. Kinetic modeling using the three compartment model with PET and high specific activity [(11)C]Iomazenil provides a reliable measure of benzodiazepine receptor binding. Synapse 35:68-77, 2000. Published 2000 Wiley-Liss, Inc.

Neural correlates of memories of childhood sexual abuse in women with and without posttraumatic stress disorder.

OBJECTIVE: Childhood sexual abuse is very common in our society, but little is known about the long-term effects of abuse on brain function. The purpose of this study was to measure neural correlates of memories of childhood abuse in sexually abused women with and without the diagnosis of posttraumatic stress disorder (PTSD). METHOD: Twenty-two women with a history of childhood sexual abuse underwent injection of [15O]H2O, followed by positron emission tomography imaging of the brain while they listened to neutral and traumatic (personalized childhood sexual abuse events) scripts. Brain blood flow during exposure to traumatic and neutral scripts was compared for sexually abused women with and without PTSD. RESULTS: Memories of childhood sexual abuse were associated with greater increases in blood flow in portions of anterior prefrontal cortex (superior and middle frontal gyri-areas 6 and 9), posterior cingulate (area 31), and motor cortex in sexually abused women with PTSD than in sexually abused women without PTSD. Abuse memories were associated with alterations in blood flow in medial prefrontal cortex, with decreased blood flow in subcallosal gyrus (area 25), and a failure of activation in anterior cingulate (area 32). There was also decreased blood flow in right hippocampus, fusiform/inferior temporal gyrus, supramarginal gyrus, and visual association cortex in women with PTSD relative to women without PTSD. CONCLUSIONS: These findings implicate dysfunction of medial prefrontal cortex (subcallosal gyrus and anterior cingulate), hippocampus, and visual association cortex in pathological memories of childhood abuse in women with PTSD. Increased activation in posterior cingulate and motor cortex was seen in women with PTSD. Dysfunction in these brain areas may underlie PTSD symptoms provoked by traumatic reminders in subjects with PTSD.

Quantitation of benzodiazepine receptor binding with PET [11C]iomazenil and SPECT [123I]iomazenil: preliminary results of a direct comparison in healthy human subjects.

Although positron emission tomography (PET) and single photon emission computed tomography (SPECT) are increasingly used for quantitation of neuroreceptor binding, almost no studies to date have involved a direct comparison of the two. One study found a high level of agreement between the two techniques, although there was a systematic 30% increase in measures of benzodiazepine receptor binding in SPECT compared with PET. The purpose of the current study was to directly compare quantitation of benzodiazepine receptor binding in the same human subjects using PET and SPECT with high specific activity [11C]iomazenil and [123I]iomazenil, respectively. All subjects were administered a single bolus of high specific activity iomazenil labeled with 11C or 123I followed by dynamic PET or SPECT imaging of the brain. Arterial blood samples were obtained for measurement of metabolite-corrected radioligand in plasma. Compartmental modeling was used to fit values for kinetic rate constants of transfer of radioligand between plasma and brain compartments. These values were used for calculation of binding potential (BP = Bmax/Kd) and product of BP and the fraction of free non-protein-bound parent compound (V3'). Mean values for V3' in PET and SPECT were as follows: temporal cortex 23+/-5 and 22+/-3 ml/g, frontal cortex23+/-6 and 22+/-3 ml/g, occipital cortex 28+/-3 and 31+/-5 ml/g, and striatum 4+/-4 and 7+/-4 ml/g. These preliminary findings indicate that PET and SPECT provide comparable results in quantitation of neuroreceptor binding in the human brain.