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This is a front end electronic design for a PET camera with 8 arrays of position sensitive detectors. Each array has 16 BGO blocks (each block is composed of 49 crystals). The design goals are component and space reduction. Each PMT has its fast amplifier and triggered integrator. Nine flash ADCs serve an array of 27 PMTs and 784 crystals. The fast signals from one or more PMT clusters are summed. The fast summed signals are thresholded and sent to a programmable logic to determines the probable scintillation zone (4 blocks) and to turn on the associated 9 PMT integrators. After integration, the logic also drives a set of ultra-fast analog switches to connect the flash ADC set to the PMT integration channels in the scintillation zone. The 9 ADC outputs (integrated pulses with good photon statistics) are latched and compared. The comparator result determines which block in the zone is firing and the appropriate 4 ADCs are selected and bused into a position decoder. The decoder outputs the image-slice address and the crystal address. The circuit is pipelined and driven by a 250 MHz master clock.

A prototype PET camera has been designed and is being constructed to test the concept, and develop the engineering design and production methodology for a variable field PET camera. The long term goal of the design is to develop a lower cost, high resolution PET camera. The camera has eight detector heads which form a closely packed octagon detector ring with an average diameter of 44cm for brain/breast and animal model imaging. The heads can be translated radially to a maximum ring diameter of 70cm for whole body imaging. In the larger diameter modes, the camera rotates 45 [degrees] during imaging. The camera heads can be set to intermediate positions to fit the camera to the subject size to maximize detection sensitivity and sampling uniformity. Special design features for imaging the breast and the axillary metastases have been incorporated. The detector design implemented is the quadrant sharing photomultiplier (PMT) design using circular 19mm PMT. The BGO detector pitch size is 2.7x2.7mm. The prototype camera images 27 slices simultaneously with an axial field of view (FOV) of 39mm. The prototype's limited axial FOV, which is appropriate for testing the camera concept, would be expanded in a next-generation clinical camera implementation. Preliminary simulation studies have been performed to evaluate the resolution, sensitivity, and sampling uniformity.

Background: Altered gray matter (GM) volumes and functional connectivity (FC) happens in attention-deficit/hyperactivity disorder (ADHD) patients and the intelligence quotient (IQ) of ADHD patients is generally lower than healthy subjects, while few studies have focused on the association among the three.Purpose: To investigate the abnormal changes of GM volumes and FC in ADHD patients compared with typically-developing control (TD-C), as well as the association between the changes and IQ.Study Type: Case control.Population: 36 ADHD patients and 36 TD-C, aged 8-17.Field Strength/sequence: 3.0T/single shot echo planar imaging (EPI).Assessment: Preprocessing of fMRI data and seed-based FC calculation using DPABI4.0, and VBM was performed by CAT12.Statistical Tests: Comparison between groups of smoothed GM volumes was performed using two-sample t-test within SPM 12, age and total intracranial volume (TIV) were returned as covariates. Comparison between groups of FCs was performed using a two-sample t-test within RESTplus; age was returned as a covariate. False discovery rate (FDR)-corrected and P < 0.05 was considered statistically significant.Results: Compared with TD-C, reduced GM volumes occurred in the left superior frontal gyrus (t = -3.61, P < 0.001), right middle frontal gyrus (t = -3.97, P < 0.001), left middle cingulum (t = -3.93, P < 0.001), and left cuneus (t = -4.42, P < 0.001). Decreased FC was found between the left precuneus and left middle cingulum (t = -5.86, P < 0.001), left middle temporal gyrus, and left superior frontal gyrus (t = -5.67, P < 0.001), as well as left medial superior frontal gyrus and left superior frontal gyrus (t = -6.73, P < 0.001).Data Conclusion: The results confirmed that FCs between the regions with declined GM volumes and others were altered in ADHD patients. We speculated that abnormal changes of GM volume and FC maybe used as an imaging metric of ADHD.Level Of Evidence: 2 Technical Efficacy: Stage 4 J. Magn. Reson. Imaging 2020;51:719-726. [ABSTRACT FROM AUTHOR]

Introduction: Abdominal adipose tissue (AT) mass has adverse effects on the brain. This study aimed to investigate the effect of glucose uptake by abdominal AT on brain aging., Methods: Three-hundred twenty-five participants underwent total-body positron emission tomography scan. Brain age was estimated in an independent test set (n = 98) using a support vector regression model that was built using a training set (n = 227). Effects of abdominal subcutaneous and visceral AT (SAT/VAT) glucose uptake on brain age delta were evaluated using linear regression., Results: Higher VAT glucose uptake was linked to negative brain age delta across all subgroups. Higher SAT glucose uptake was associated with negative brain age delta in lean individuals. In contrast, increased SAT glucose uptake demonstrated positive trends with brain age delta in female and overweight/obese participants., Discussion: Increased glucose uptake of the abdominal VAT has positive influences on the brain, while SAT may not have such influences, except for lean individuals., Highlights: Higher glucose uptake of the visceral adipose tissue was linked to decelerated brain aging. Higher glucose uptake of the subcutaneous adipose tissue (SAT) was associated with negative brain age delta in lean individuals. Faster brain aging was associated with increased glucose uptake of the SAT in female and overweight and obese individuals., (© 2024 The Author(s). Alzheimer's & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer's Association.)

Objectives: This study utilizes [ 99m Tc]-methylene diphosphate (MDP) single photon emission computed tomography (SPECT) images as a reference standard to evaluate whether the integration of radiomics features from computed tomography (CT) and machine learning algorithms can identify microscopic early bone metastases. Additionally, we also determine the optimal machine learning approach., Materials and Methods: We retrospectively studied 63 patients with early bone metastasis from July 2020 to March 2023. The ITK-SNAP software was used to delineate early bone metastases and normal bone tissue in SPECT images of each patient, which were then registered onto CT images to outline the volume of interest (VOI). The VOI includes 63 early bone metastasis volumes and 63 normal bone tissue volumes. 126 VOIs were randomly distributed in a 7:3 ratio between the training and testing groups, and 944 radiomics features were extracted from every VOI. We established 20 machine learning models using 5 feature selection algorithms and 4 classification methods. Evaluate the performance of the model using the area under the receiver operating characteristic curve (AUC)., Results: Most machine learning models demonstrated outstanding discriminative capacity, with AUCs higher than 0.70. Notably, the K-Nearest Neighbors (KNN) classifier exhibited significant performance improvement compared to the other four classifiers. Specifically, the model constructed utilizing eXtreme Gradient Boosting (XGBoost) feature selection method integrated with KNN classifier achieved the maximum AUC, which is 0.989 in the training set and 0.975 in the testing set., Conclusions: Radiomics features integrated with machine learning methods can identify early bone metastases that are not visible on CT images. In our analysis, KNN is considered the optimal classification method., (© 2024. The Author(s), under exclusive licence to International Skeletal Society (ISS).)

Rationale and Objectives: Primary open-angle glaucoma (POAG) is accompanied with gray matter (GM) changes across the brain. However, causal relationships of the GM changes have not been fully understood. Our aim was to investigate the causality of GM progressive changes in POAG using Granger causality (GC) analysis and structural MRI., Materials and Methods: Structural MRI from 20 healthy controls and 30 POAG patients with elevated intraocular pressure (IOP) were collected. We performed voxel-wise GM volume comparisons between control and POAG groups, and between control and four POAG subgroups (categorized by IOP). Then, we sequenced the structural MRI data of all POAG patients and conducted both voxel-wise and region of interest (ROI)-wise GC analysis to investigate the causality of GM volume changes in POAG brain., Results: Compared to healthy controls, reduced GM volumes across the brain were found, GM volume enlargements in the thalamus, caudate nucleus and cuneus were also observed in POAG brain (false discovery rate (FDR) corrected at q< 0.05). As IOP elevated, the reductions of GM volume were more severe in the cerebellum and frontal lobe. GC analysis revealed that the bilateral cerebellum, visual cortices, and the frontal regions served independently as primary hubs of the directional causal network, and projected causal effects to the parietal and temporal regions of the brain (FDR corrected at q<0.05)., Conclusion: POAG exhibits progressive GM alterations across the brain, with oculomotor regions and visual cortices as independent primary hubs. The current results may deepen our understanding of neuropathology of POAG., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.)