Positron Emission Tomography Slices Research Articles

New method of using a convolutional neural network for 2D intraprostatic tumor segmentation from PET images

PurposeA new method of using a convolutional neural network (CNN) to perform automatic tumor segmentation from two-dimensional transaxial slices of positron emission tomography (PET) images of high-risk primary prostate cancer patients is introduced.MethodsWe compare three different methods including (1) usual image segmentation with a CNN whose continuous output is converted to binary labels with a constant threshold, (2) our new technique of choosing separate thresholds for each image PET slice with a CNN to label the pixels directly from the PET slices, and (3) the combination of the two former methods based on using the second CNN to choose the optimal thresholds to convert the output of the first CNN. The CNNs are trained and tested multiple times by using a data set of 864 slices from the PET images of 78 prostate cancer patients.ResultsAccording to our results, the Dice scores computed from the predictions of the second method are statistically higher than those of the typical image segmentation (p-value<0.002).ConclusionThe new method of choosing unique thresholds to convert the pixels of the PET slices directly into binary tumor masks is not only faster and more computationally efficient but also yields better results.

AW-SDRLSE: Adaptive Weighting and Scalable Distance Regularized Level Set Evolution for Lymphoma Segmentation on PET Images.

Accurate lymphoma segmentation on Positron Emission Tomography (PET) images is of great importance for medical diagnoses, such as for distinguishing benign and malignant. To this end, this paper proposes an adaptive weighting and scalable distance regularized level set evolution (AW-SDRLSE) method for delineating lymphoma boundaries on 2D PET slices. There are three important characteristics with respect to AW-SDRLSE: 1) A scalable distance regularization term is proposed and a parameter q can control the contour's convergence rate and precision in theory. 2) A novel dynamic annular mask is proposed to calculate mean intensities of local interior and exterior regions and further define the region energy term. 3) As the level set method is sensitive to parameters, we thus propose an adaptive weighting strategy for the length and area energy terms using local region intensity and boundary direction information. AW-SDRLSE is evaluated on 90 cases of real PET data with a mean Dice coefficient of 0.8796. Comparative results demonstrate the accuracy and robustness of AW-SDRLSE as well as its performance advantages as compared with related level set methods. In addition, experimental results indicate that AW-SDRLSE can be a fine segmentation method for improving the lymphoma segmentation results obtained by deep learning (DL) methods significantly.

Fully 3D Active Surface with Machine Learning for PET Image Segmentation.

In order to tackle three-dimensional tumor volume reconstruction from Positron Emission Tomography (PET) images, most of the existing algorithms rely on the segmentation of independent PET slices. To exploit cross-slice information, typically overlooked in these 2D implementations, I present an algorithm capable of achieving the volume reconstruction directly in 3D, by leveraging an active surface algorithm. The evolution of such surface performs the segmentation of the whole stack of slices simultaneously and can handle changes in topology. Furthermore, no artificial stop condition is required, as the active surface will naturally converge to a stable topology. In addition, I include a machine learning component to enhance the accuracy of the segmentation process. The latter consists of a forcing term based on classification results from a discriminant analysis algorithm, which is included directly in the mathematical formulation of the energy function driving surface evolution. It is worth noting that the training of such a component requires minimal data compared to more involved deep learning methods. Only eight patients (i.e., two lung, four head and neck, and two brain cancers) were used for training and testing the machine learning component, while fifty patients (i.e., 10 lung, 25 head and neck, and 15 brain cancers) were used to test the full 3D reconstruction algorithm. Performance evaluation is based on the same dataset of patients discussed in my previous work, where the segmentation was performed using the 2D active contour. The results confirm that the active surface algorithm is superior to the active contour algorithm, outperforming the earlier approach on all the investigated anatomical districts with a dice similarity coefficient of 90.47 ± 2.36% for lung cancer, 88.30 ± 2.89% for head and neck cancer, and 90.29 ± 2.52% for brain cancer. Based on the reported results, it can be claimed that the migration into a 3D system yielded a practical benefit justifying the effort to rewrite an existing 2D system for PET imaging segmentation.

Can Na18F PET/CT bone scans help when deciding if early intervention is needed in patients being treated with a TSF attached to the tibia: insights from 41 patients

PurposeTo demonstrate the usefulness of positron emission tomography (PET)/computed tomography (CT) bone scans for gaining insight into healing bone status earlier than CT or X-ray alone.MethodsForty-one prospective patients being treated with a Taylor Spatial Frame were recruited. We registered data obtained from successive static CT scans for each patient, to align the broken bone. Radionuclide uptake was calculated over a spherical volume of interest (VOI). For all voxels in the VOI, histograms and cumulative distribution functions of the CT and PET data were used to assess the type and progress of new bone growth and radionuclide uptake. The radionuclide uptake difference per day between the PET/CT scans was displayed in a scatter plot. Superimposing CT and PET slice data and observing the spatiotemporal uptake of 18F− in the region of healing bone by a time-sequenced movie allowed qualitative evaluation.ResultsNumerical evaluation, particularly the shape and distribution of Hounsfield Units and radionuclide uptake in the graphs, combined with visual evaluation and the movies enabled the identification of six patients needing intervention as well as those not requiring intervention. Every revised patient proceeded to a successful treatment conclusion.ConclusionNumerical and visual evaluation based on all the voxels in the VOI may aid the orthopedic surgeon to assess a patient’s progression to recovery. By identifying slow or insufficient progress at an early stage and observing the uptake of 18F− in specific regions of bone, it might be possible to shorten the recovery time and avoid unnecessary late complications.

Development of a new fully three-dimensional methodology for tumours delineation in functional images

Delineation of tumours in Positron Emission Tomography (PET) plays a crucial role in accurate diagnosis and radiotherapy treatment planning. In this context, it is of outmost importance to devise efficient and operator-independent segmentation algorithms capable of reconstructing the tumour three-dimensional (3D) shape. In previous work, we proposed a system for 3D tumour delineation on PET data (expressed in terms of Standardized Uptake Value - SUV), based on a two-step approach. Step 1 identified the slice enclosing the maximum SUV and generated a rough contour surrounding it. Such contour was then used to initialize step 2, where the 3D shape of the tumour was obtained by separately segmenting 2D PET slices, leveraging the slice-by-slice marching approach. Additionally, we combined active contours and machine learning components to improve performance. Despite its success, the slice marching approach poses unnecessary limitations that are naturally removed by performing the segmentation directly in 3D. In this paper, we migrate our system into 3D. In particular, the segmentation in step 2 is now performed by evolving an active surface directly in the 3D space. The key points of such an advancement are that it performs the shape reconstruction on the whole stack of slices simultaneously, naturally leveraging cross-slice information that could not be exploited before. Additionally, it does not require any specific stopping condition, as the active surface naturally reaches a stable topology once convergence is achieved.Performance of this fully 3D approach is evaluated on the same dataset discussed in our previous work, which comprises fifty PET scans of lung, head and neck, and brain tumours. The results have confirmed that a benefit is indeed achieved in practice for all investigated anatomical districts, both quantitatively, through a set of commonly used quality indicators (dice similarity coefficient >87.66%, Hausdorff distance < 1.48 voxel and Mahalanobis distance < 0.82 voxel), and qualitatively in terms of Likert score (>3 in 54% of the tumours).

Multiscale Mask R-CNN–Based Lung Tumor Detection Using PET Imaging

Positron emission tomography (PET) imaging serves as one of the most competent methods for the diagnosis of various malignancies, such as lung tumor. However, with an elevation in the utilization of PET scan, radiologists are overburdened considerably. Consequently, a new approach of “computer-aided diagnosis” is being contemplated to curtail the heavy workloads. In this article, we propose a multiscale Mask Region–Based Convolutional Neural Network (Mask R-CNN)–based method that uses PET imaging for the detection of lung tumor. First, we produced 3 models of Mask R-CNN for lung tumor candidate detection. These 3 models were generated by fine-tuning the Mask R-CNN using certain training data that consisted of images from 3 different scales. Each of the training data set included 594 slices with lung tumor. These 3 models of Mask R-CNN models were then integrated using weighted voting strategy to diminish the false-positive outcomes. A total of 134 PET slices were employed as test set in this experiment. The precision, recall, and F score values of our proposed method were 0.90, 1, and 0.95, respectively. Experimental results exhibited strong conviction about the effectiveness of this method in detecting lung tumors, along with the capability of identifying a healthy chest pattern and reducing incorrect identification of tumors to a large extent.

253. An accurate and operator independent method for biological tumour volume segmentation

Purpose The aim of this paper is to develop an operator independent method for biological tumour volume (BTV) delineation from Positron Emission Tomography (PET) images. BTV delineation is challenging because of the low spatial resolution and high noise level in PET images. In addition, BTV varies substantially depending on the method used to segment. Manual delineation is widely-used, but it is strongly user dependent. Methods The proposed method starts with the automatic identification of the PET slice with maximum Standardized Uptake Value (SUV). Then, a user- independent mask is obtained by a rough pre-segmentation step and it is used to perform the local active contour segmentation on the next slices. When the proposed method finds a slice where the mean SUV on the interior of the delineation contour is greater or equal than the mean SUV on the exterior of the delineation contour, the segmentation is automatically stopped. The algorithm is evaluated on four datasets of synthetic lesions considering different ratios between lesion and background radioactivity concentrations. In this way, the actual lesion volumes are known and the segmentation algorithm is evaluated under different contrast ratio scenarios. In addition, BTVs of 25 patient studies have been manually delineated and compared to the proposed method in order to assess its applicability in a clinical environment. Results In phantom experiments, dice similarity coefficient (DSC) rate and true positive volume fraction (TPVF) rate greater than 90% were observed in synthetic lesions with a diameter greater than 17 mm. In clinical cases, TPVF and DSC were 91.00 ± 7.33% and 85.98 ± 3.40%, respectively. Conclusion Our method produces accurate segmentation results in phantom studies. In addition, it is feasible in clinical context and shows good accuracy in realistic conditions, reducing any user interaction.

SPNsim: A database of simulated solitary pulmonary nodule PET/CT images facilitating computer aided diagnosis

The aim of the present work was to design and develop a database of simulated solitary pulmonary nodules (SPN) in pairs of computed tomography (CT) and positron emission tomography (PET) images, using Monte Carlo (MC) simulation methods. We have developed an SPN image modeling pipeline to feed the database entitled SPNsim. The database is web-accessible and it is contains two subsets of simulated PET/CT SPN images. The first subset is currently composed of 1000 cases containing pairs of the transaxial CT and the corresponding PET slice with various types of simulated SPNs, presented as individual records. The second subset contains pairs of the transaxial CT and the corresponding PET slice of simulated SPNs, presenting cases of graded difficulty in diagnosis. The users of the database will have the ability to set queries in order to retrieve cases with certain characteristics, as well as characterized image sets. All images are freely available and may be downloaded from the website. SPNsim provides a useful reference data set for training and evaluation of computer aided detection (CAD) and diagnosis (CADx) systems focusing on SPN.

A method for accurate spatial registration of PET images and histopathology slices.

BackgroundAccurate alignment between histopathology slices and positron emission tomography (PET) images is important for radiopharmaceutical validation studies. Limited data is available on the registration accuracy that can be achieved between PET and histopathology slices acquired under routine pathology conditions where slices may be non-parallel, non-contiguously cut and of standard block size. The purpose of this study was to demonstrate a method for aligning PET images and histopathology slices acquired from patients with laryngeal cancer and to assess the registration accuracy obtained under these conditions.MethodsSix subjects with laryngeal cancer underwent a 64Cu-copper-II-diacetyl-bis(N4-methylthiosemicarbazone) (64Cu-ATSM) PET computed tomography (CT) scan prior to total laryngectomy. Sea urchin spines were inserted into the pathology specimen to act as fiducial markers. The specimen was fixed in formalin, as per standard histopathology operating procedures, and was then CT scanned and cut into millimetre-thick tissue slices. A subset of the tissue slices that included both tumour and fiducial markers was taken and embedded in paraffin blocks. Subsequently, microtome sectioning and haematoxylin and eosin staining were performed to produce 5-μm-thick tissue sections for microscopic digitisation. A series of rigid registration procedures was performed between the different imaging modalities (PET; in vivo CT—i.e. the CT component of the PET-CT; ex vivo CT; histology slices) with the ex vivo CT serving as the reference image. In vivo and ex vivo CTs were registered using landmark-based registration. Histopathology and ex vivo CT images were aligned using the sea urchin spines with additional anatomical landmarks where available. Registration errors were estimated using a leave-one-out strategy for in vivo to ex vivo CT and were estimated from the RMS landmark accuracy for histopathology to ex vivo CT.ResultsThe mean ± SD accuracy for registration of the in vivo to ex vivo CT images was 2.66 ± 0.66 mm, and the accuracy for registration of histopathology to ex vivo CT was 0.86 ± 0.41 mm. Estimating the PET to in vivo CT registration accuracy to equal the PET-CT alignment accuracy of 1 mm resulted in an overall average registration error between PET and histopathology slices of 3.0 ± 0.7 mm.ConclusionsWe have developed a registration method to align PET images and histopathology slices with an accuracy comparable to the spatial resolution of the PET images.

VALIDATION OF [18F]-SODIUM FLUORIDE AS A MARKER OF ACTIVE CALCIFICATION AND HIGH-RISK CAROTID PLAQUE: A SUB-STUDY OF THE CANADIAN ATHEROSCLEROSIS IMAGING NETWORK (CAIN-2)

[18F]-sodium fluoride (NaF) positron emission tomography (PET) uptake may serve as an imaging-derived biomarker of active calcification. It is postulated that NaF binds to hydroxyapatite molecules that are expressed in regions with active calcification. We aimed to: 1. Validate NaF uptake imaged with PET/CT, as a direct marker of active calcification within carotid plaque, as determined by its association with intraplaque expression of hydroxyapatite; and 2. Determine whether NaF uptake is related to cerebrovascular events. Eleven patients (69 ± 5 years, 3 females) scheduled for carotid endarterectomy were prospectively recruited. Patients underwent NaF PET and contrast-enhanced CTA imaging of carotid vasculature. The bifurcation of the common carotid was used as a reference point; maximum NaF uptake normalized to blood (tissue to blood ratio - TBR) was measured at every PET slice extending 2 cm above and below the bifurcation. Following endarterectomy, excised carotid plaque was fixed, sectioned and stained with Goldner’s Trichrome (marker of hydroxyapatite expression). An electronic algorithm was applied to quantify hydroxyapatite expression on whole-slide digitized images. Using the distance from the bifurcation, pathology was aligned with CTA and co-registered with PET. To determine the relationship between NaF uptake and cerebrovascular events, bilateral carotid plaque was classified as either symptomatic (associated with cerebrovascular events) or clinically silent, asymptomatic plaque. Carotid endarterectomy was performed in 11 patients; one patient received a 2nd carotid endarterectomy due to bilateral disease. Two patients were excluded (intolerance to CT contrast agent and PET/CT misalignment). Staining was available for 8 excised plaques. NaF uptake was related to intraplaque hydroxyapatite expression (r=0.45, p<0.001) (Figure 1). NaF uptake was greater at the side of carotid endarterectomy (endarterectomy: 3.73±1.1 TBR vs. contralateral: 2.82±0.6 TBR, p=0.030). Symptomatic carotid plaque had evidence for greater NaF uptake (symptomatic plaque: 3.75±1.1 TBR vs. asymptomatic plaque: 2.79±0.6 TBR p=0.04) NaF uptake imaged with PET/CT is related to intraplaque expression of hydroxyapatite, which is expressed in regions with active calcific activity. NaF uptake was greater in plaque that was scheduled for endarterectomy, as well as symptomatic plaque associated with cerebrovascular events. NaF PET/CT may serve as a novel biomarker of active calcification and enable identification of high-risk patients. Larger outcome based follow-up studies are underway.

18F]-sodium fluoride PET/CT is an imaging-derived biomarker of hydroxyapatite expression in carotid plaque: sub-study of the Canadian Atherosclerosis Imaging Network (CAIN-2)

Background: It has been hypothesized that [18F]-sodium fluoride (NaF) uptake imaged with positron emission tomography (PET) binds to hydroxyapatite molecules expressed in regions with active calcification. Therefore, we aimed to validate NaF as a marker of hydroxyapatite expression in high-risk carotid plaque. Methods: Eleven patients (69 ± 5 years, 3 female) scheduled for carotid endarterectomy were prospectively recruited for NaF PET/CT. One patient received a second contralateral endarterectomy; two patients were excluded (intolerance to contrast media and PET/CT misalignment). The bifurcation of the common carotid was used as the reference point; NaF uptake (tissue to blood ratio - TBR) was measured at every PET slice extending 2 cm above and below the bifurcation. Excised plaque was immunostained with Goldner’s Trichrome and whole-slide digitized images were used to quantify hydroxyapatite expression. Pathology was co-registered with PET. Results: NaF uptake was related to the extent of hydroxyapatite expression (r=0.45, p&lt;0.001). Upon classifying bilateral plaque for symptomatology, symptomatic plaque was associated with cerebrovascular events (3.75±1.1 TBR, n=9) and had greater NaF uptake than clinically silent asymptomatic plaque (2.79±0.6 TBR, n=11) (p=0.04). Conclusion: NaF uptake is related to hydroxyapatite expression and is increased in plaque associated with cerebrovascular events. NaF may serve as a novel biomarker of active calcification and plaque vulnerability.

Noninvasive Multimodality Imaging of the Tumor Microenvironment: Registered Dynamic Magnetic Resonance Imaging and Positron Emission Tomography Studies of a Preclinical Tumor Model of Tumor Hypoxia

In vivo knowledge of the spatial distribution of viable, necrotic, and hypoxic areas can provide prognostic information about the risk of developing metastases and regional radiation sensitivity and may be used potentially for localized dose escalation in radiation treatment. In this study, multimodality in vivo magnetic resonance imaging (MRI) and positron emission tomography (PET) imaging using stereotactic fiduciary markers in the Dunning R3327AT prostate tumor were performed, focusing on the relationship between dynamic contrast-enhanced (DCE) MRI using Magnevist (Gd-DTPA) and dynamic 18F-fluoromisonidazole (18F-Fmiso) PET. The noninvasive measurements were verified using tumor tissue sections stained for hematoxylin/eosin and pimonidazole. To further validate the relationship between 18F-Fmiso and pimonidazole uptake, 18F digital autoradiography was performed on a selected tumor and compared with the corresponding pimonidazole-stained slices. The comparison of Akep values (kep = rate constant of movement of Gd-DTPA between the interstitial space and plasma and A = amplitude in the two-compartment model (Hoffmann U, Brix G, Knopp MV, Hess T and Lorenz WJ (1995). Magn Reson Med 33, 506– 514) derived from DCE-MRI studies and from early 18F-Fmiso uptake PET studies showed that tumor vasculature is a major determinant of early 18F-Fmiso uptake. A negative correlation between the spatial map of Akep and the slope map of late (last 1 hour of the dynamic PET scan) 18F-Fmiso uptake was observed. The relationships between DCE-MRI and hematoxylin/eosin slices and between 18F-Fmiso PET and pimonidazole slices confirm the validity of MRI/PET measurements to image the tumor microenvironment and to identify regions of tumor necrosis, hypoxia, and well-perfused tissue.

Comparison of Different Techniques for Stereotactic Positron Emission Tomography Imaging

Background and Purpose: The aim of this study was to evaluate three different techniques used for stereotactic positron emission tomography (PET) image definition: (1) PET imaging with external stereotactic radioactive markers, (2) PET imaging without external stereotactic markers and subsequent coregistration with stereotactically defined imaging modality such as computed tomography (CT) or magnetic resonance imaging (MRI), (3) PET/CT imaging with utilization of external nonradioactive markers. Materials and Methods:Special head phantom that could be fixed in the Leksell stereotactic frame was used. The phantom was filled with fluorodeoxyglucose (¹⁸F-FDG) in water solution at an activity concentration of 17.5 kBq/ml simulating counts from standard brain. A spherically shaped glass test vessel (inner diameter 46 mm and wall thickness 3 mm) positioned in the head phantom was filled with FDG water solution at an activity concentration of 52.5 kBq/ml corresponding to pathologic lesion during PET imaging. Leksell stereotactic MRI indicator box was filled with FDG water solution at an activity concentration of 3.1 MBq/ml. The phantom was then stereotactically investigated on PET, PET/CT, CT and MRI. Deviations between stereotactic X, Y, Z PET coordinates of the center of the spherical vessel (simulating pathological lesion) were determined in the treatment planning system according to reference image and represented inaccuracy in stereotactic PET image definition for each of three tested methods of stereotactic PET definition. Results:Total spatial inaccuracy for stereotactic PET image definition based on radioactive fiducials was 1.7 and 0.7 mm for 3.4- and 2.0-mm PET slices, respectively. Total spatial PET image definition inaccuracy based on PET/CT imaging and stereotactic definition using nonradioactive CT fiducials was 0.7 mm. Total spatial PET image definition inaccuracy based on coregistration was 0.5 and 0.9 mm for coregistration with MRI and CT, respectively. Conclusion: All three evaluated stereotactic PET image definition techniques indicated very good accuracy in this phantom study entirely accepted by clinical requirements for functional imaging. The most convenient stereotactic PET image definition technique seemed to be PET image coregistration either on CT or MRI. In this situation, PET imaging can be done independently on frame application (for example few days before stereotactic frame application or even in a different centre) and then coregistered with stereotactically performed CT or MRI during the stereotactic procedure. However, detailed patient study has to be performed to test image coregistration inaccuracy on real clinical data.

Prediction of antidepressant effects of sleep deprivation by metabolic rates in the ventral anterior cingulate and medial prefrontal cortex.

Sleep deprivation has been shown to have an antidepressant benefit in a subgroup of depressed patients. Functional imaging studies by the authors and others have suggested that patients with elevated metabolic rates in the anterior cingulate gyrus at baseline are more likely to respond to either sleep deprivation or antidepressant medications than patients with normal metabolic rates. The authors extend their earlier work in a larger group of patients and explore additional brain areas with statistical probability mapping. Thirty-six patients with unipolar depression and 26 normal volunteers were studied with positron emission tomography before and after sleep deprivation. Response to sleep deprivation was defined as a 40% or larger decrease in total scores on the Hamilton Depression Rating Scale. One-third of the depressed patients had a significant response to sleep deprivation. Responders had higher relative metabolic rates in the medial prefrontal cortex, ventral anterior cingulate, and posterior subcallosal gyrus at baseline than depressed patients who did not respond to sleep deprivation and normal volunteers. Lower Hamilton depression scores correlated significantly with lower metabolic rates in the left medial prefrontal cortex. After sleep deprivation, significant decreases in metabolic rates occurred in the medial prefrontal cortex and frontal pole in the patients who responded positively to sleep deprivation. High pretreatment metabolic rates and decreases in metabolic rates after treatment in the medial prefrontal cortex may characterize a subgroup of depressed patients who improve following sleep deprivation and, perhaps, other antidepressant treatments.

Frontal and temporal cortex function in schizophrenia during a memory task

Several previous studies with both cerebral blood flow and positron emission tomography (PET) have found diminished functional activity in the lateral frontal and temporal cortex in schizophrenia. This study examined these same brain regions using PET with 18-F-deoxyglucose (FDG) in a completely new cohort of 19 patients with schizophrenia (mean age = 37.7, SD = 14.7) and 25 healthy matched controls (mean age 36.5, SD = 13.2). Subjects were scanned with our new high-resolution (4.2-4.5 nun FWHM) scanner. Patients were off all psychoactive medications a minimum of 2 weeks. All subjects were screened by history, psychiatric interview, physical exam, and laboratory testing. Controls with a history of mental illness in a first-degree relative were excLuded. During the FDG uptake period, all subjects performed a modified version of the California Verbal Learning Test (CVLT). This task was chosen as it is thought to involve: (1) the frontal lobe, important in short-term memory and executive functions; including those involved in developing strategies for learning; and (2) the temporal lobe, important in long-term memory storage. The lateral cortex was measured using our stereotaxic atlas method with boxes placed in the superior, middle, and inferior gyrus of both the frontal and temporal lobe for both left and right hemisphere on three PET slices (41%, 34%, and 28% of brain height). Values were expressed in mean relative metabolic rate for the region of interest (box metabolic rate/whole slice metabolic rate) in order to correct for generalized effects and allow inferences about regionally specific brain areas. Preliminary results from a repeated-measures ANOVA indicate that while glucose metabolism in the lateral frontal lobe is significantly lower in the schizophrenics compared to the controls, it did not differ in the lateral temporal lobe (Group × Lobe interaction, F = 5.17, p = 0.028). Further, in the schizophrenic group, lower glucose metabolism in the frontal lobe was significantly correlated with higher BPRS Positive Symptom Composite Scores (r = 0.68, p < 0.01). These results extend our previous work and indicate that frontal lobe dysfunction is an important contributor to the pathophysiology of schizophrenia.

A new technique for pet slice orientation and MRI‐PET coregistration

AbstractWe report and validate a technique for magnetic resonace imaging (MRI) positron emission tomography (PET) coregistration and the optimization of PET slice orientation that enhances and complements existing techniques. The technique depends on an external fiducial system and on software that models the relationship of the PET gantry with respect to a three‐dimensional (3D) MR reconstruction of each subject's brain anatomy. The technique offers the possibility of using individual neuroanatomical information to plan PET activation studies. Estimated 3D errors average 3 mm in [15O]H2O PET activation studies. In‐plane interinjection movement averages less than 1 mm. The resulting MRI‐PET coregistration provides a basis for bringing neuroanatomical information to bear on a number of issues critical for the interpretation of functional imaging studies. © 1995 Wiley‐Liss, Inc.

PET determination of regional cerebral glucose metabolism in alcohol-dependent men and healthy controls using 11C-glucose.

Regional brain glucose metabolism was determined in 9 male alcohol-dependent inpatients and 12 male healthy controls. All the patients were socially impaired by the alcohol abuse. All the subjects had abstained from alcohol and drugs for more than four weeks before entering the study. Brain glucose metabolism was determined by positron emission tomography (PET) with 11C-glucose as the tracer. Regions of interest were drawn on displayed computed tomographic (CT) images of the brain. Regions were transferred to corresponding PET slices, allowing the determination of regional glucose metabolism. In the healthy volunteers there was a reduction in glucose metabolism with age. In 11 of the 19 brain regions examined, the alcoholics had a 20% to 30% lower glucose metabolism than the controls. This was true for both cortical and subcortical structures. The distribution of relative regional metabolic rates indicated that parietal cortical areas were most affected. Atrophic changes as shown by CT were not correlated to the reduced metabolism in the alcohol-dependent patients.