CT-Less Whole-Body Bone Segmentation of PET Images Using a Multimodal Deep Learning Network.

In bone cancer imaging, positron emission tomography (PET) is ideal for the diagnosis and staging of bone cancers due to its high sensitivity to malignant tumors. The diagnosis of bone cancer requires tumor analysis and localization, where accurate and automated wholebody bone segmentation (WBBS) is often needed. Current WBBS for PET imaging is based on paired Computed Tomography (CT) images.

Deep learning-aided respiratory motion compensation in PET/CT: addressing motion induced resolution loss, attenuation correction artifacts and PET-CT misalignment.

Purpose: Respiratory motion (RM) significantly impacts image quality in thoracoabdominal PET/CT imaging. This study introduces a unified data-driven respiratory motion correction (uRMC) method, utilizing deep learning neural networks, to solve all the major issues caused by RM, i.e.

Cross-Attention for Improved Motion Correction in Brain PET.

Head movement during long scan sessions degrades the quality of reconstruction in positron emission tomography (PET) and introduces artifacts, which limits clinical diagnosis and treatment. Recent deep learning-based motion correction work utilized raw PET list-mode data and hardware motion tracking (HMT) to learn head motion in a supervised manner. However, motion prediction results were not robust to testing subjects outside the training data domain.

Fast Reconstruction for Deep Learning PET Head Motion Correction.

Head motion correction is an essential component of brain PET imaging, in which even motion of small magnitude can greatly degrade image quality and introduce artifacts. Building upon previous work, we propose a new head motion correction framework taking fast reconstructions as input. The main characteristics of the proposed method are: (i) the adoption of a high-resolution short-frame fast reconstruction workflow; (ii) the development of a novel encoder for PET data representation extraction; and (iii) the implementation of data augmentation techniques.

EEG microstates analysis after TMS in patients with subacute stroke during the resting state.

To investigate whether intermittent theta burst stimulation over the cerebellum induces changes in resting-state electroencephalography microstates in patients with subacute stroke and its correlation with cognitive and emotional function. Twenty-four stroke patients and 17 healthy controls were included in this study. Patients and healthy controls were assessed at baseline, including resting-state electroencephalography and neuropsychological scales.

MULTI-TASK DEEP LEARNING AND UNCERTAINTY ESTIMATION FOR PET HEAD MOTION CORRECTION.

Head motion occurring during brain positron emission tomography images acquisition leads to a decrease in image quality and induces quantification errors. We have previously introduced a Deep Learning Head Motion Correction (DL-HMC) method based on supervised learning of gold-standard Polaris Vicra motion tracking device and showed the potential of this method. In this study, we upgrade our network to a multi-task architecture in order to include image appearance prediction in the learning process.

Nomograms for the prediction of decannulation in patients with neurological injury: a study based on clinical practice.

Background: Rational prediction of the probability of decannulation in tracheotomy patients is of great importance to clinicians and patients' families. This study aimed to develop a prediction model for decannulation in tracheotomized patients with neurological injury using routine clinical data and blood tests.

Methods: We developed a prediction model based on 186 tracheotomized patients, and data were collected from January 2018 to March 2021.

Markerless head motion tracking and event-by-event correction in brain PET.

Head motion correction (MC) is an essential process in brain positron emission tomography (PET) imaging. We have used the Polaris Vicra, an optical hardware-based motion tracking (HMT) device, for PET head MC. However, this requires attachment of a marker to the subject's head.

The regional pattern of age-related synaptic loss in the human brain differs from gray matter volume loss: in vivo PET measurement with [C]UCB-J.

Purpose: Aging is a major societal concern due to age-related functional losses. Synapses are crucial components of neural circuits, and synaptic density could be a sensitive biomarker to evaluate brain function. [C]UCB-J is a positron emission tomography (PET) ligand targeting synaptic vesicle glycoprotein 2A (SV2A), which can be used to evaluate brain synaptic density in vivo.

Framing protocol optimization in oncological Patlak parametric imaging with uKinetics.

Purpose: Total-body PET imaging with ultra-high sensitivity makes high-temporal-resolution framing protocols possible for the first time, which allows to capture rapid tracer dynamic changes. However, whether protocols with higher number of temporal frames can justify the efficacy with substantially added computation burden for clinical application remains unclear. We have developed a kinetic modeling software package (uKinetics) with the advantage of practical, fast, and automatic workflow for dynamic total-body studies.

Principal component analysis of synaptic density measured with [C]UCB-J PET in early Alzheimer's disease.

Background: Synaptic loss is considered an early pathological event and major structural correlate of cognitive impairment in Alzheimer's disease (AD). We used principal component analysis (PCA) to identify regional patterns of covariance in synaptic density using [C]UCB-J PET and assessed the association between principal components (PC) subject scores with cognitive performance.

Methods: [C]UCB-J binding was measured in 45 amyloid + participants with AD and 19 amyloid- cognitively normal participants aged 55-85.

Deep learning-based attenuation map generation with simultaneously reconstructed PET activity and attenuation and low-dose application.

. In PET/CT imaging, CT is used for positron emission tomography (PET) attenuation correction (AC). CT artifacts or misalignment between PET and CT can cause AC artifacts and quantification errors in PET.

Supervised Deep Learning for Head Motion Correction in PET.

Head movement is a major limitation in brain positron emission tomography (PET) imaging, which results in image artifacts and quantification errors. Head motion correction plays a critical role in quantitative image analysis and diagnosis of nervous system diseases. However, to date, there is no approach that can track head motion continuously without using an external device.

Deep learning-based attenuation correction for whole-body PET - a multi-tracer study with F-FDG, Ga-DOTATATE, and F-Fluciclovine.

Unlabelled: A novel deep learning (DL)-based attenuation correction (AC) framework was applied to clinical whole-body oncology studies using F-FDG,  Ga-DOTATATE, and F-Fluciclovine. The framework used activity (λ-MLAA) and attenuation (µ-MLAA) maps estimated by the maximum likelihood reconstruction of activity and attenuation (MLAA) algorithm as inputs to a modified U-net neural network with a novel imaging physics-based loss function to learn a CT-derived attenuation map (µ-CT).

Methods: Clinical whole-body PET/CT datasets of F-FDG (N = 113),  Ga-DOTATATE (N = 76), and F-Fluciclovine (N = 90) were used to train and test tracer-specific neural networks.

Adaptive data-driven motion detection and optimized correction for brain PET.

Head motion during PET scans causes image quality degradation, decreased concentration in regions with high uptake and incorrect outcome measures from kinetic analysis of dynamic datasets. Previously, we proposed a data-driven method, center of tracer distribution (COD), to detect head motion without an external motion tracking device. There, motion was detected using one dimension of the COD trace with a semiautomatic detection algorithm, requiring multiple user defined parameters and manual intervention.

Assessment of transient dopamine responses to smoked cannabis.

Background: Dopaminergic mechanisms that may underlie cannabis' reinforcing effects are not well elucidated in humans. This positron emission tomography (PET) imaging study used the dopamine D receptor antagonist [C]raclopride and kinetic modelling testing for transient changes in radiotracer uptake to assess the striatal dopamine response to smoked cannabis in a preliminary sample.

Methods: PET emission data were acquired from regular cannabis users (n = 14; 7 M/7 F; 19-32 years old) over 90 min immediately after [C]raclopride administration (584 ± 95 MBq) as bolus followed by constant infusion (K = 105 min).

Generation of parametric K images for FDG PET using two 5-min scans.

Purpose: The net uptake rate constant (K ) derived from dynamic imaging is considered the gold standard quantification index for FDG PET. In this study, we investigated the feasibility and assessed the clinical usefulness of generating K images for FDG PET using only two 5-min scans with population-based input function (PBIF).

Methods: Using a Siemens Biograph mCT, 10 subjects with solid lung nodules underwent a single-bed dynamic FDG PET scan and 13 subjects (five healthy and eight cancer patients) underwent a whole-body dynamic FDG PET scan in continuous-bed-motion mode.

Partial volume correction analysis for C-UCB-J PET studies of Alzheimer's disease.

Purpose: C-UCB-J PET imaging, targeting synaptic vesicle glycoprotein 2A (SV2A), has been shown to be a useful indicator of synaptic density in Alzheimer's disease (AD). For SV2A imaging, a decrease in apparent tracer uptake is often due to the combination of gray-matter (GM) atrophy and SV2A decrease in the remaining tissue. Our aim is to reveal the true SV2A change by performing partial volume correction (PVC).

Automatic Inter-Frame Patient Motion Correction for Dynamic Cardiac PET Using Deep Learning.

Patient motion during dynamic PET imaging can induce errors in myocardial blood flow (MBF) estimation. Motion correction for dynamic cardiac PET is challenging because the rapid tracer kinetics of 82Rb leads to substantial tracer distribution change across different dynamic frames over time, which can cause difficulties for image registration-based motion correction, particularly for early dynamic frames. In this paper, we developed an automatic deep learning-based motion correction (DeepMC) method for dynamic cardiac PET.

Association of Aβ deposition and regional synaptic density in early Alzheimer's disease: a PET imaging study with [C]UCB-J.

Background: Attempts to associate amyloid-β (Aβ) pathogenesis with synaptic loss in Alzheimer's disease (AD) have thus far been limited to small numbers of postmortem studies. Aβ plaque burden is not well-correlated with indices of clinical severity or neurodegeneration-at least in the dementia stage-as deposition of Aβ reaches a ceiling. In this study, we examined in vivo the association between fibrillar Aβ deposition and synaptic density in early AD using positron emission tomography (PET).

Reduced synaptic vesicle protein 2A binding in temporal lobe epilepsy: A [ C]UCB-J positron emission tomography study.

Objective: In this positron emission tomography (PET) study with [ C]UCB-J, we evaluated synaptic vesicle glycoprotein 2A (SV2A) binding, which is decreased in resected brain tissues from epilepsy patients, in subjects with temporal lobe epilepsy (TLE) and compared the regional binding pattern to [ F]fluorodeoxyglucose (FDG) uptake.

Methods: Twelve TLE subjects and 12 control subjects were examined. Regional [ C]UCB-J binding potential (BP ) values were estimated using the centrum semiovale as a reference region.

Human adult and adolescent biodistribution and dosimetry of the synaptic vesicle glycoprotein 2A radioligand C-UCB-J.

Unlabelled: The ability to quantify synaptic density in vivo in human adults and adolescents is of vital importance to understanding neuropsychiatric disorders. Here, we performed whole-body scans to determine organ radiation dosimetry of C-UCB-J in humans.

Methods: Dynamic whole-body PET scans were performed in four healthy adults after injection of C-UCB-J.