scholarly journals 11C-Diprenorphine Binding in Huntington's Disease: A Comparison of Region of Interest Analysis with Statistical Parametric Mapping

1997 ◽  
Vol 17 (9) ◽  
pp. 943-949 ◽  
Author(s):  
Robert A. Weeks ◽  
Vincent J. Cunningham ◽  
Paola Piccini ◽  
Simon Waters ◽  
Anita E. Harding ◽  
...  
Keyword(s):  
Spectral Analysis ◽  
Statistical Parametric Mapping ◽  
Region Of Interest ◽  
Emission Tomography ◽  
Z Score ◽  
Parametric Images ◽  
Positron Emission ◽  
Opioid Binding ◽  
Static Images ◽  
Analytical Approaches

We compare region of interest (ROI) analytical approaches with statistical parametric mapping (SPM) of 11C-diprenorphine positron emission tomography findings in five patients with Huntington's disease (HD) and nine age-matched controls. The ROI were placed on caudate, putamen, and an occipital reference area. Ratios of striatal–occipital uptake from averaged static images centered at 60 minutes showed a mean 20% reduction in caudate ( P = 0.034) and 15% reduction in putamen ( P = 0.095) receptor binding in the HD patients. Dynamic data from caudate and putamen ROI, together with a plasma tracer input function, were analyzed using spectral analysis to give regional impulse response functions. Regional data at 60 minutes after impulse showed a mean 29% decrease in caudate ( P = 0.006) and 23% decrease in putamen ( P = 0.029) opioid binding in the HD cohort. Parametric images of tracer binding also were produced with spectral analysis on a voxel basis. The images of the unit impulse response function at 60 minutes showed a mean 31 % decrease in caudate ( P = 0.005) and a 26% decrease in putamen binding ( P = 0.011) in HD. The voxel-based parametric images were transformed into standard stereotactic space, and a between-group comparison (patient versus controls) was performed with SPM. This approach revealed symmetrical decreases in caudate (peak 40% decrease, z score = 4.38) and putamen opioid binding (peak 24% decrease, z score = 4.686) with additional nonhypothesized changes in cingulate, prefrontal, and thalamic areas. The significance and precision of changes measured with spectral analysis applied to dynamic data sets were superior to ROI-based ratio analysis on static images. The SPM replicated the striatal reductions in opioid binding in HD and detected additional nonpredicted changes. This study suggests that SPM is a valid alternative to conventional ROI analytical approaches for determining binding changes with positron emission tomography and may have advantages over region-based analyses in exploratory studies.

Neural Mechanism of Propofol Anesthesia in Severe Depression

2003 ◽  
Vol 98 (5) ◽  
pp. 1101-1111 ◽  
Author(s):  
Kenichi Ogawa ◽  
Takeshi Uema ◽  
Nobutaka Motohashi ◽  
Masami Nishikawa ◽  
Harumasa Takano ◽  
...  
Keyword(s):  
Positron Emission Tomography ◽  
Blood Flow ◽  
Cerebral Blood Flow ◽  
Statistical Parametric Mapping ◽  
Severe Depression ◽  
Dose Effect ◽  
Emission Tomography ◽  
Association Cortex ◽  
Depressed Patients ◽  
Positron Emission

Background The precise neural mechanisms of propofol anesthesia in humans are still unknown. The authors examined the acute effects of propofol on regional cerebral blood flow (rCBF) using positron emission tomography in patients with severe depression. Methods In six severely depressed patients (mean age, 55.0 yr) scheduled for electroconvulsive therapy, anesthetic levels were monitored by electroencephalography, and rCBF was serially quantified in the awake, sedated, and anesthetized states. The authors used high-resolution positron emission tomography with 15O-labeled water and statistical parametric mapping 99 for imaging and analysis of the data. Results Global cerebral blood flow showed sharp decreases from the awake level during the administration of propofol, decreasing 26.8% in the sedated state and 54.4% in the anesthetized state. Moreover, a dose effect was seen in both parietal cortices and the left lateral prefrontal region with larger regions of relative decrease in rCBF at higher propofol doses. At the higher dose, the values of rCBF in the pulvinar nucleus of the thalamus, the pontine tegmentum, and the cerebellar cortex were also affected. Meanwhile, there were few changes of relative rCBF in the basal frontal lobes during both sedated and anesthetized states. Conclusions As in earlier studies using normal subjects, pronounced suppression in rCBF in the brain stem reticular formation, the thalamus, and the parietal association cortex occurred even in severely depressed patients. However, previously reported decreases in rCBF in the basal frontal lobe were absent in depressed patients.

Tracer kinetic model of regional pulmonary function using positron emission tomography

2002 ◽  
Vol 93 (3) ◽  
pp. 1104-1114 ◽  
Author(s):  
Gaetano G. Galletti ◽  
José G. Venegas
Keyword(s):  
Positron Emission Tomography ◽  
Pulmonary Function ◽  
Goodness Of Fit ◽  
Molecular Nitrogen ◽  
Region Of Interest ◽  
Emission Tomography ◽  
Gas Content ◽  
Pulmonary Vasculature ◽  
Model Parameters ◽  
Positron Emission

To determine the spatial distributions of pulmonary perfusion, shunt, and ventilation, we developed a compartmental model of regional 13N-labeled molecular nitrogen (13NN) kinetics measured from positron emission tomography (PET) images. The model features a compartment for right heart and pulmonary vasculature and two compartments for each region of interest: 1) aerated alveolar units and 2) alveolar units with no gas content (shunting). The model was tested on PET data from normal animals (dogs and sheep) and from animals with experimentally injured lungs simulating acute respiratory distress syndrome. The analysis yielded estimates of regional perfusion, shunt fraction, and specific ventilation with excellent goodness-of-fit to the data ( R 2 > 0.99). Model parameters were estimated to within 10% accuracy in the presence of exaggerated levels of experimental noise by using a Monte Carlo sensitivity analysis. Main advantages of the present model are that 1) it separates intraregional blood flow to aerated alveolar units from that shunting across nonaerated units and 2) it accounts and corrects for intraregional tracer removal by shunting blood when estimating ventilation from subsequent washout of tracer. The model was thus found to provide estimates of regional parameters of pulmonary function in sizes of lung regions that could potentially approach the intrinsic resolution for PET images of 13NN in lung (∼7.0 mm for a multiring PET camera).

scholarly journals Comparison of Lesion Detection and Quantification in MAP Reconstruction with Gaussian and Non-Gaussian Priors

2006 ◽  
Vol 2006 ◽  
pp. 1-10 ◽  
Author(s):  
Jinyi Qi
Keyword(s):  
Region Of Interest ◽  
Lesion Detection ◽  
Emission Tomography ◽  
Reconstruction Methods ◽  
Positron Emission ◽  
Hotelling Observer ◽  
Sharp Edges ◽  
Gaussian Prior ◽  
Non Gaussian ◽  
Detection And Quantification

Statistical image reconstruction methods based on maximum a posteriori (MAP) principle have been developed for emission tomography. The prior distribution of the unknown image plays an important role in MAP reconstruction. The most commonly used prior are Gaussian priors, whose logarithm has a quadratic form. Gaussian priors are relatively easy to analyze. It has been shown that the effect of a Gaussian prior can be approximated by linear filtering a maximum likelihood (ML) reconstruction. As a result, sharp edges in reconstructed images are not preserved. To preserve sharp transitions, non-Gaussian priors have been proposed. However, their effect on clinical tasks is less obvious. In this paper, we compare MAP reconstruction with Gaussian and non-Gaussian priors for lesion detection and region of interest quantification using computer simulation. We evaluate three representative priors: Gaussian prior, Huber prior, and Geman-McClure prior. We simulate imaging a prostate tumor using positron emission tomography (PET). The detectability of a known tumor in either a fixed background or a random background is measured using a channelized Hotelling observer. The bias-variance tradeoff curves are calculated for quantification of the total tumor activity. The results show that for the detection and quantification tasks, the Gaussian prior is as effective as non-Gaussian priors.

scholarly journals CROSS-REFERENCE MAXIMUM LIKELIHOOD ESTIMATE RECONSTRUCTION FOR POSITRON EMISSION TOMOGRAPHY

2001 ◽  
Vol 13 (04) ◽  
pp. 190-198 ◽  
Author(s):  
CHUNG-MING CHEN ◽  
HENRY HORNG-SHING LU ◽  
YUN-PAI HSU
Keyword(s):  
Maximum Likelihood ◽  
Maximum Likelihood Estimate ◽  
Region Of Interest ◽  
Likelihood Estimate ◽  
Emission Tomography ◽  
Estimation Errors ◽  
Structure Information ◽  
Positron Emission ◽  
Monte Carlo Studies ◽  
Cross Reference

Maximum likelihood estimate (MLE) is a widely used approach for PET image reconstruction. However, it has been shown that reconstructing emission tomography based on MLE without regularization would result in noise and edge artifacts. In the attempt to regularize the maximum likelihood estimate, we propose a new and efficient method in this paper to incorporate the correlated but possibly incomplete structure information which may be derived from expertise, PET systems or other imaging modalities. A mean estimate smoothing the MLE locally within each region of interest is derived according to the boundaries provided by the structure information. Since the boundaries may not be correct, a penalized MLE using the mean estimate is sought. The resulting reconstruction is called a cross-reference maximum likelihood estimate (CRMLE). The CRMLE can be obtained through a modified EM algorithm, which is computation and storage efficient. By borrowing the strength from the correct portion of boundary information, the CRMLE is able to extract the useful information to improve reconstruction for different kinds of incomplete and incorrect boundaries in Monte Carlo studies. The proposed CRMLE algorithm not only reduces the estimation errors, but also preserves the correct boundaries. The penalty parameters can be selected through human interactions or automatically data-driven methods, such as the generalized cross validation method.

scholarly journals Medial Orbitofrontal Cortex Is Associated with Fatigue Sensation

2010 ◽  
Vol 2010 ◽  
pp. 1-5 ◽  
Author(s):  
Seiki Tajima ◽  
Shigeyuki Yamamoto ◽  
Masaaki Tanaka ◽  
Yosky Kataoka ◽  
Masao Iwase ◽  
...  
Keyword(s):  
Positron Emission Tomography ◽  
Orbitofrontal Cortex ◽  
Brain Region ◽  
Statistical Parametric Mapping ◽  
Brain Regions ◽  
Mapping Method ◽  
Emission Tomography ◽  
Neural Basis ◽  
Positron Emission ◽  
The Brain

Fatigue is an indispensable bioalarm to avoid exhaustive state caused by overwork or stresses. It is necessary to elucidate the neural mechanism of fatigue sensation for managing fatigue properly. We performedH2O  15positron emission tomography scans to indicate neural activations while subjects were performing 35-min fatigue-inducing task trials twice. During the positron emission tomography experiment, subjects performed advanced trail-making tests, touching the target circles in sequence located on the display of a touch-panel screen. In order to identify the brain regions associated with fatigue sensation, correlation analysis was performed using statistical parametric mapping method. The brain region exhibiting a positive correlation in activity with subjective sensation of fatigue, measured immediately after each positron emission tomography scan, was located in medial orbitofrontal cortex (Brodmann's area 10/11). Hence, the medial orbitofrontal cortex is a brain region associated with mental fatigue sensation. Our findings provide a new perspective on the neural basis of fatigue.

scholarly journals Linearized Reference Tissue Parametric Imaging Methods: Application to [11C]DASB Positron Emission Tomography Studies of the Serotonin Transporter in Human Brain

2003 ◽  
Vol 23 (9) ◽  
pp. 1096-1112 ◽  
Author(s):  
Masanori Ichise ◽  
Jeih-San Liow ◽  
Jian-Qiang Lu ◽  
Akihiro Takano ◽  
Kendra Model ◽  
...  
Keyword(s):  
Positron Emission Tomography ◽  
Human Brain ◽  
Positron Emission Tomography Imaging ◽  
Emission Tomography ◽  
Binding Potential ◽  
Parametric Imaging ◽  
Reference Tissue ◽  
Parametric Images ◽  
Positron Emission ◽  
Tissue Models

The authors developed and applied two new linearized reference tissue models for parametric images of binding potential ( BP) and relative delivery ( R1) for [11C]DASB positron emission tomography imaging of serotonin transporters in human brain. The original multilinear reference tissue model (MRTMO) was modified (MRTM) and used to estimate a clearance rate ( k′2) from the cerebellum (reference). Then, the number of parameters was reduced from three (MRTM) to two (MRTM2) by fixing k′2. The resulting BP and R1 estimates were compared with the corresponding nonlinear reference tissue models, SRTM and SRTM2, and one-tissue kinetic analysis (1TKA), for simulated and actual [11C]DASB data. MRTM gave k′2 estimates with little bias (<1%) and small variability (<6%). MRTM2 was effectively identical to SRTM2 and 1TKA, reducing BP bias markedly over MRTMO from 12–70% to 1–4% at the expense of somewhat increased variability. MRTM2 substantially reduced BP variability by a factor of two or three over MRTM or SRTM. MRTM2, SRTM2, and 1TKA had R1 bias <0.3% and variability at least a factor of two lower than MRTM or SRTM. MRTM2 allowed rapid generation of parametric images with the noise reductions consistent with the simulations. Rapid parametric imaging by MRTM2 should be a useful method for human [11C]DASB positron emission tomography studies.

scholarly journals A 18F-fluorodeoxyglucose MicroPET Imaging Study to Assess Changes in Brain Glucose Metabolism in a Rat Model of Surgery-induced Latent Pain Sensitization

2011 ◽  
Vol 115 (5) ◽  
pp. 1072-1083 ◽  
Author(s):  
Asunción Romero ◽  
Santiago Rojas ◽  
David Cabañero ◽  
Juan D. Gispert ◽  
José R. Herance ◽  
...  
Keyword(s):  
Positron Emission Tomography ◽  
Rat Model ◽  
Brain Metabolism ◽  
Statistical Parametric Mapping ◽  
Imaging Study ◽  
Emission Tomography ◽  
Posterior Cortex ◽  
Fdg Uptake ◽  
Positron Emission ◽  
Pain Sensitization

Background Neuroplastic changes involved in latent pain sensitization after surgery are poorly defined. We assessed temporal changes in glucose brain metabolism in a postoperative rat model using positron emission tomography. We also investigated brain metabolism after naloxone administration. Methods Rats were given remifentanil anesthetic and underwent a plantar incision, with 1 mg/kg of (-)-naloxone subcutaneously administered on postoperative days 20 and 21. Using the von Frey test, mechanical thresholds were measured pre- and postoperatively at different time points in awake animals during F-fluorodeoxyglucose (F-FDG) uptake. Brain images were also obtained the day before mechanical testing, using a positron emission tomography R4 scanner (Concorde Microsystems, Siemens, Knoxville, TN). Differences in brain activity were assessed utilizing a statistical parametric mapping. Results Surgery induced minor changes in F-FDG uptake in the cerebellum, hippocampus, and posterior cortex, which extended to the thalamus, hypothalamus, and brainstem on days 6 and 7. Changes were still present on day 21. Maximal postoperative hypersensitivity was observed on day 2. The administration of (-)-naloxone on day 21 induced significant hypersensitivity, greatly enhancing the effect on F-FDG uptake. In sham-operated rats, naloxone induced changes limited to the striatum and the cerebellum. Nonnociceptive stimulation with von Frey filaments had no effect on F-FDG uptake. Conclusions Surgery, remifentanil, and their combination induced long-lasting and significant metabolic changes in the pain brain matrix, with a positive correlation with hypersensitivity after naloxone. Changes in brain F-FDG precipitated by naloxone suggest that surgery under remifentanil anesthetic induces the greatest neuroplastic brain adaptations in opioid-related pathways involved in nociceptive processing and long-lasting pain sensitization.

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