Motion Correction Research Articles

Content-aware motion correction for multi-shot imaging

Content-aware motion correction for multi-shot imaging

Dissociable effects of urgency and evidence accumulation during reaching revealed by dynamic multisensory integration.

When making perceptual decisions, humans combine information across sensory modalities dependent on their respective uncertainties. However, it remains unknown how the brain integrates multisensory feedback during movement, and which factors besides sensory uncertainty influence sensory contributions. We performed two reaching experiments on healthy adults to investigate whether movement corrections to combined visual and mechanical perturbations scale with visual uncertainty. To describe the dynamics of multimodal feedback responses, we further varied movement time and visual feedback duration during the movement. The results of our first experiment show that the contribution of visual feedback decreased with uncertainty. Additionally, we observed a transient phase during which visual feedback responses were stronger during faster movements. In a follow-up experiment, we found that the contribution of vision increased more quickly during slow movements when we presented the visual feedback for a longer time. Muscle activity corresponding to these visual responses exhibited modulations with sensory uncertainty and movement speed ca. 100ms following the onset of the visual feedback. Using an optimal feedback control model, we show that the increased response to visual feedback during fast movements can be explained by an urgency-dependent increase in control gains. Further, the fact that a longer viewing duration increased the visual contributions suggests that the brain accumulates sensory information over time to estimate the state of the arm during reaching. Our results provide additional evidence concerning the link between reaching control and decision-making, both of which appear to be influenced by sensory evidence accumulation and response urgency.Significance statement The time-course of multisensory integration during movement, along with the factors influencing this process, still requires further investigation. Here, we tested how visual uncertainty, movement speed, and visual feedback duration influence reach corrections to combined visual and mechanical perturbations. Using an optimal feedback control model, we illustrate that the time-course of multimodal corrections follows the predictions of a Kalman filter which continuously weighs sensory feedback and internal predictions according to their reliability. Importantly, we further show that changes in movement speed led to urgency-dependent modulations of control gains. Our results corroborate previous research linking motor control and decision-making by highlighting that multisensory feedback responses depend on sensory evidence accumulation and response urgency in a similar way as decision-making processes.

COMPLEX PHYSICAL THERAPY OF PATIENTS WITH ADHESIVE CAPSULITIS

Adhesive capsulitis is predominantly an idiopathic condition and is more common in patients with metabolic disorders. PS contracture can be of varying degrees of severity, depending on the pathology of the PS with which we are dealing. This condition greatly aff ects work capacity and quality of life due to the presence of pain, discomfort and limitation of daily life activities. Prolonged pain syndrome can provoke sleep disorders and depression. Disruption of normal sleep, pain and depression form a pathological closed circle and contribute to the maintenance of the pathological process in the locus morbi.The development of a comprehensive program of physical therapy for patients with adhesive capsulitis with the use of modern means of recovery, which will reduce the risk of the disease re-emerging, and will also contribute to the faster recovery of the functional capacity of the musculoskeletal system of the patients.The objective of the study. The develop and practically substantiate a comprehensive program of therapy for patients with adhesive capsulitis using physical therapy.Materials and Research Methods. The study is based on a comprehensive therapeutic approach for 36 patients diagnosed with adhesive capsulitis in the acute phase of the condition. The assessed parameters included X-ray and computed tomography results, evaluation of range of motion in the shoulder joint, joint- muscle apparatus, and analysis of pain intensity indicators.Conclusions. To improve the condition of patients and optimize the process of treatment and rehabilitation of patients with adhesive capsulitis of the shoulder joint in the acute period, it is advisable to use with the diff erentiation of means of therapeutic intervention according to the diagnosis of the international classifi cation of functioning, optimization of physiotherapeutic means and special means of physical therapy allowed to shorten the terms of treatment and recovery of patients with adhesive capsulitis. It was determined that the best combination of means of therapeutic intervention for patients with adhesive capsulitis is the use of a complex of ideomotor exercises to create the patient’s idea of correct movement; correct positioning of the limb during sleep, everyday and professional activity; passive exercises to increase the volume of painless movements (bending, external rotation); restorationof the pattern of typical motor actions and optimization of physiotherapeutic means due to the use of shock wave and TENS therapy signifi cantly improved the eff ectiveness of their recovery in the short-term and long-term stages of the acute period of rehabilitation.

Motion and magnetic field inhomogeneity correction techniques for chemical exchange saturation transfer (CEST) MRI: A contemporary review.

Chemical exchange saturation transfer (CEST) magnetic resonance imaging (MRI) has emerged as a powerful imaging technique sensitive to tissue molecular composition, pH, and metabolic processes in situ. CEST MRI uniquely probes the physical exchange of protons between water and specific molecules within tissues, providing a window into physiological phenomena that remain invisible to standard MRI. However, given the very low concentration (millimolar range) of CEST compounds, the effects measured are generally only on the order of a few percent of the water signal. Consequently, a few critical challenges, including correction of motion artifacts and magnetic field (B0 and B1 +) inhomogeneities, have to be addressed in order to unlock the full potential of CEST MRI. Motion, whether from patient movement or inherent physiological pulsations, can distort the CEST signal, hindering accurate quantification. B0 and B1 + inhomogeneities, arising from scanner hardware imperfections, further complicate data interpretation by introducing spurious variations in the signal intensity. Without proper correction of these confounding factors, reliable analysis and clinical translation of CEST MRI remain challenging. Motion correction methods aim to compensate for patient movement during (prospective) or after (retrospective) image acquisition, reducing artifacts and preserving data quality. Similarly, B0 and B1 + inhomogeneity correction techniques enhance the spatial and spectral accuracy of CEST MRI. This paper aims to provide a comprehensive review of the current landscape of motion and magnetic field inhomogeneity correction methods in CEST MRI. The methods discussed apply to saturation transfer (ST) MRI in general, including semisolid magnetization transfer contrast (MTC) and relayed nuclear Overhauser enhancement (rNOE) studies.

Long-term optical imaging of the spinal cord in awake behaving mice.

Advances in optical imaging and fluorescent biosensors enable study of the spatiotemporal and long-term neural dynamics in the brain of awake animals. However, methodological difficulties and fibrosis limit similar advances in the spinal cord. Here, to overcome these obstacles, we combined in vivo application of fluoropolymer membranes that inhibit fibrosis, a redesigned implantable spinal imaging chamber and improved motion correction methods that together permit imaging of the spinal cord in awake behaving mice, for months to over a year. We demonstrated a robust ability to monitor axons, identified a spinal cord somatotopic map, performed months-long imaging in freely moving mice, conducted Ca2+ imaging of neural dynamics in behaving mice responding to pain-provoking stimuli and observed persistent microglial changes after nerve injury. The ability to couple in vivo imaging and behavior at the spinal cord level will drive insights not previously possible at a key location for somatosensory transmission to the brain.

Development of quantitative PET/MR imaging for measurements of hepatic portal vein input function: a phantom study

BackgroundAccurate pharmacokinetic modelling in PET necessitates measurements of an input function, which ideally is acquired non-invasively from image data. For hepatic pharmacokinetic modelling two input functions need to be considered, to account for the blood supply from the hepatic artery and portal vein. Image-derived measurements at the portal vein are challenging due to its small size and image artifacts caused by respiratory motion. In this work we seek to demonstrate, using phantom experiments, how a dedicated PET/MR protocol can tackle these challenges and potentially provide input function measurements of the portal vein in a clinical setup.MethodsA custom 3D printed PET/MR phantom was constructed to mimic the liver and portal vein. PET/MR acquisitions were made with emulated respiratory motion. The PET/MR imaging protocol consisted of high-resolution anatomical MR imaging of the portal vein, followed by a PET acquisition in parallel to a dedicated motion-tracking MR sequence. Motion tracking and deformation information were extracted from PET data and subsequently used in PET reconstruction to produce dynamic series of motion-free PET images. Anatomical MR images were used post PET reconstruction for partial volume correction of the input function measurements.ResultsReconstruction of dynamic PET data with motion-compensation provided nearly motion-free series of PET frame data, suitable for image derived input function measurements of the portal vein. After partial volume correction, the individual input function measurements were within a 16.1% error range from the true activity in the portal vein compartment at the time of PET acquisition.ConclusionThe proposed protocol demonstrates clinically feasible PET/MR imaging of the liver for pharmacokinetic studies with accurate quantification of the portal vein input function, including correction for respiratory motion and partial volume effects.

Adaptive optical correction for in vivo two-photon fluorescence microscopy with neural fields.

Adaptive optics (AO) restore ideal imaging performance in complex samples by measuring and correcting optical aberrations, but often require custom-built microscopes with carefully aligned wavefront sensing/shaping devices and can be susceptible to sample motion. Here we describe NeAT, a computational framework using neural fields for AO two-photon fluorescence microscopy. NeAT estimates wavefront aberration and recovers sample structure from a 3D image stack without requiring external datasets for training. Incorporating motion correction in learning and correcting conjugation errors commonly found in commercial microscopes, NeAT is designed for deployment in biological laboratories for in vivo imaging. We validate NeAT's performance using a custom-built microscope with a wavefront sensor under varying signal-to-noise ratios, aberration, and motion conditions. With a commercial microscope, we demonstrate real-time aberration correction for in vivo morphological and functional imaging in the living mouse brain, with NeAT improving signal and accuracy of glutamate and calcium imaging of synapses and neurons.

Cardiac motion correction with a deep learning network for perfusion defect assessment in SPECT myocardial perfusion imaging

BackgroundIn myocardial perfusion imaging (MPI) with SPECT ungated studies are used for evaluation of perfusion defects despite motion blur. We investigate the potential benefit of motion correction using a deep-learning (DL) network for evaluating perfusion defects. MethodsWe employed a DL network for cardiac motion correction in ECG-gated SPECT-MPI images, wherein the image data from different cardiac phases are combined with respect to a reference gate to reduce motion blur. For training the DL network 197 cases were used. Given the variability of gated images during the cardiac cycle, we investigated the detectability of perfusion defects in two distinct reference gates. To assess perfusion defect detection, we performed receiver-operating-characteristic (ROC) analyses on the motion-corrected images using a separate test dataset of clinical 194 subjects, in which studies were created from actual patient data with inserted simulated-lesions as ground truth. The reconstructed images were assessed by the quantitative-perfusion SPECT (QPS) software. We also evaluated the performance on reduced-count studies (by two and four folds). ResultsThe quantitative results, measured by area-under-the-ROC curve (AUC), demonstrated that DL motion correction improves the detectability of perfusion defects significantly on both standard- and reduced-count studies, and that the detectability can vary with reference cardiac phases. A joint assessment from two reference-phases achieved AUC=0.841 on the quarter-count data, higher than with ungated full-count data (AUC=0.795, p-value=0.0054). ConclusionsDL motion correction can benefit assessment of perfusion defects in standard- and reduced-count SPECT-MPI studies. It can also be beneficial to evaluate perfusion images over multiple cardiac phases.

Effects of List-Mode-Based Intraframe Motion Correction in Dynamic Brain PET Imaging.

Motion is unavoidable in dynamic [18F]-MK6240 Positron Emission Tomography (PET) imaging, especially in Alzheimer's disease (AD) research requiring long scan duration. To understand how motion correction affects quantitative analysis, we investigated two approaches: II-MC, which corrects for both inter-frame and intra-frame motion, and IO-MC, which only corrects for inter-frame motion. These methods were applied to 83 scans from 34 subjects, and we calculated distribution volume ratios (DVR) using the multilinear reference tissue model with two parameters (MRTM2) in tau-rich brain regions. Most of the studies yielded similar DVR results for both II-MC and IO-MC. However, in one scan of an AD subject, the inferior temporal region showed 14% higher DVR with II-MC compared to IO-MC. This difference was reasonable given the AD diagnosis, although similar results were not observed in other regions. Although discrepancies between IO-MC and II-MC results were rare, they underscore the importance of incorporating intra-frame motion correction for more accurate and dependable PET quantitation, particularly in the context of dynamic imaging. These findings suggest that while the overall impact of intra-frame motion correction may be subtle, it can improve the reliability of longitudinal PET data, ultimately enhancing our understanding of tau protein distribution in AD pathology.

Anticipatory postural adjustment deficits in children with developmental coordination disorder during a self-induced prehension task while standing on one leg

Effective postural control is essential for motor skill development, yet the specific nature of anticipatory control in children with Developmental Coordination Disorder (DCD) remains poorly understood for complex or dynamic stability tasks. This study investigated anticipatory postural adjustments (APA) during a self-initiated dynamic stability task. The Can Placement Task (CPT)—a self-initiated dynamic stability task—was performed by 23 children with DCD and 30 typically developing (TD) children aged 9–12 years. The task involved standing on one leg while also repositioning a can on the floor. Center of pressure (COP) movement was recorded by two force platforms during the five phases of the movement. The ground reaction force measured external support during both descent to pick up the can and ascent after replacing the can. The study used a mixed-design approach with group (DCD, TD) as a between-subject factor and condition (can position close or far) and phase of movement as within-subject. Distinct movement control characteristics were shown for children with DCD including a greater range of COP movement and higher COP velocity in the anterior-posterior direction prior to movement initiation compared with TD. The DCD group also relied more on external support during both the downward and upward phases of the CPT and needed more trials to complete the task. Only two significant interaction effects involving Group and the within-subject factors emerged. Children with DCD swayed significantly more at specific phases of the task, especially when coming up and restoring balance, and did not adapt COP velocity as a function of reaching distance. Dynamic control of posture in children with DCD is impaired as they struggle to generate the effective APAs necessary to maintain dynamic stability which leads to greater reliance on external support and more corrective movements. The CPT provides a valuable assessment of posture and dynamic balance control during a complex prehension movement performed on one leg; the task highlights distinct movement patterns between children with and without DCD.

Multistream Adaptive Attention-Enhanced Graph Convolutional Networks for Youth Fencing Footwork Training.

The popularity of fencing and intense sports competition has burdened adolescents with excessive training, harming their immature bodies. Traditional training methods fail to provide timely movement corrections and personalized plans, leading to ineffective exercises. This paper aims to use artificial intelligence technology to reduce ineffective exercises and alleviate the training burden. We propose an action recognition algorithm based on the characteristics of adolescent athletes. This algorithm uses multimodal input data to comprehensively extract action information. Each modality is processed by the same network structure, utilizing attention mechanisms and adaptive graph structures. A multibranch feature fusion method is used to determine the final action category. We gathered the fencing footwork data set 2.0. Our model achieved 93.3% accuracy, with the highest precision at 95.8% and the highest F1-Score at 94.5% across all categories. It effectively recognized actions of adolescents with different heights and speeds, outperforming traditional methods. Our artificial intelligence-based training solution improves training efficiency and reduces the training burden on adolescents.

Fast inter-frame motion correction in contrast-free ultrasound quantitative microvasculature imaging using deep learning

Contrast-free ultrasound quantitative microvasculature imaging shows promise in several applications, including the assessment of benign and malignant lesions. However, motion represents one of the major challenges in imaging tumor microvessels in organs that are prone to physiological motions. This study aims at addressing potential microvessel image degradation in in vivo human thyroid due to its proximity to carotid artery. The pulsation of the carotid artery induces inter-frame motion that significantly degrades microvasculature images, resulting in diagnostic errors. The main objective of this study is to reduce inter-frame motion artifacts in high-frame-rate ultrasound imaging to achieve a more accurate visualization of tumor microvessel features. We propose a low-complex deep learning network comprising depth-wise separable convolutional layers and hybrid adaptive and squeeze-and-excite attention mechanisms to correct inter-frame motion in high-frame-rate images. Rigorous validation using phantom and in-vivo data with simulated inter-frame motion indicates average improvements of 35% in Pearson correlation coefficients (PCCs) between motion corrected and reference data with respect to that of motion corrupted data. Further, reconstruction of microvasculature images using motion-corrected frames demonstrates PCC improvement from 31 to 35%. Another thorough validation using in-vivo thyroid data with physiological inter-frame motion demonstrates average improvement of 20% in PCC and 40% in mean inter-frame correlation. Finally, comparison with the conventional image registration method indicates the suitability of proposed network for real-time inter-frame motion correction with 5000 times reduction in motion corrected frame prediction latency.

Application of 3D Motion Graphic Design Technology of Object Simulation Human Body in Sports Teaching

In the current era, the rapid development of computer technology has brought unprecedented opportunities for innovation in physical education teaching. The introduction of computer technology not only improves the efficiency of physical education teaching but also provides more accurate and scientific means for sports training. In response to this trend, this paper proposes an innovative human body model design method and explores in detail the key implementation techniques of computer simulation of 3D motion maps, aiming to further optimize and improve the quality of physical education teaching. The design of human body models plays a crucial role in physical education teaching and training, as it can help students and teachers better understand the mechanisms and principles of human movement. By introducing computer technology, this paper can construct a more precise, dynamic, and realistic human body model that conforms to the actual motion situation. This model can simulate various movement states of the human body, providing students with an intuitive and vivid learning experience. In the classroom, teachers can use projection or virtual reality devices to display 3D motion models, allowing students to intuitively see the details and changes of motion movements, deepening their understanding of the essentials of the movements. Teachers can demonstrate different movements in real time by operating models, and explain the technical points and precautions of each movement. Students can observe the motion trajectory and posture changes of the model from multiple perspectives to improve learning efficiency. The system generates personalized feedback reports based on students’ movement data, pointing out the problems and improvement directions that students have during the exercise process. Teachers can provide more accurate guidance to students based on these feedbacks, helping them correct incorrect movements and improve their skill levels.

Significant impact of a novel whole heart motion correction algorithm on cardiac computed tomography and aortic valve calcium scores

Abstract Introduction A new whole-heart motion-correction algorithm has been available in cardiac computed tomography (CT), and it has already revealed the higher diagnostic accuracy of significant coronary artery stenosis in cases with higher heart rate at the CT scan. Recently, aortic valve calcium scores (AVCS) are often measured for the decision-making of surgical treatment of aortic valve stenosis. However, the measurement of AVCS of the aortic valve has potential risks of motion artifact of the aortic valve. Therefore, we would like to know the clinical impact of a new whole-heart motion correction algorithm for accurately measuring aortic valve AVCS without motion artifacts. Purpose The purpose of this study is to evaluate the impact of a new whole-heart motion-correction algorithm on non-contrast cardiac CT images and the AVCS in trans-catheter aortic valve regurgitation (TAVR) candidates with severe aortic valve stenosis. Materials and methods Forty-two consecutive TAVR candidates (83 ± 7 years old, 21 males) who underwent ECG-gated CT using 256-row detector CT from November 2023 to February 2024 at our hospital were analyzed. The best phase non-contrast cardiac images were automatically selected, and they were reconstructed with both the standard (STD) algorithm and the new whole-heart motion-correction algorithm. AVCS was calculated using semi-automatic commercially available software. The aortic valve's image noise was also measured. Results Non-contrast best cardiac phase images were successfully reconstructed using the new motion correction algorithm in 36 patients (86%). The best cardiac phase was mainly the diastolic phase in 29 patients (81%). The overall Agatston score and calcified volume of the aortic valve in SSF2 were 1779 ± 896, and 1403 ± 689, respectively, and they were lower than 2195 ± 1132 and 1656 ± 851 of STD (all P < 0.01). Conclusion The new whole-heart motion-correction algorithm worked in almost all TAVR candidates, and revealed lower AVCS and shows a potential for increasing AVCS accuracy.

Prospective 3D Fat Navigator (FatNav) motion correction for 7T Terra MRI.

Ultra-high field (7T) MRI allows scans at sub-millimetre resolution with exquisite signal-to-noise ratio (SNR). As 7T MRI becomes more widely used clinically, the challenge of patient motion must be overcome. Retrospective motion correction is used successfully for some protocols, but for acquisitions such as slice-by-slice scans only prospective motion correction can deliver the full potential of 7T MRI. We report the first implementation of prospective 3D Fat Navigator ("FatNav") motion correction for the Siemens 7T Terra MRI. We implemented a modular Sequence Building Block for FatNav and embedded it into the vendor's gradient-recalled echo (GRE) sequence. We modified the reconstruction pipeline to reconstruct FatNav images online, coregistering them and sending motion updates to the host sequence online. We tested five registration algorithms for performance and accuracy on synthetic FatNav data. We implemented the best three of these in our sequence and tested them online. We acquired T1 and T2* weighted brain images of healthy volunteers correcting every other image for motion to visualise the effectiveness of online motion correction. Data were acquired with and without head immobilisation. We also tested performance while correcting every measurement for motion. Our implementation uses a 1.23 s 3D FatNav acquisition module and delivers motion updates in less than 3s, which is sufficient for motion updates every few k-space lines in typical scans. Corrected images are crisper with fewer visible motion artefacts. This improved sharpness is reflected quantitatively by an increase in the variance of the image Laplacian which is 1.59 x better for corrected vs uncorrected images. Profiles across the cerebral falx are 33% steeper for corrected vs uncorrected images. Prospective FatNav improves GRE image quality in the brain. Our modular Sequence Building Block provides a simple method to integrate motion correction in 7T MRI pulse sequences.

Measurement variability of blood-brain barrier permeability using dynamic contrast-enhanced magnetic resonance imaging.

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is used to quantify the blood-brain barrier (BBB) permeability-surface area product. Serial measurements can indicate changes in BBB health, of interest to the study of normal physiology, neurological disease, and the effect of therapeutics. We performed a scan-rescan study to inform both sample size calculation for future studies and an appropriate reference change value for patient care. The final dataset included 28 healthy individuals (mean age 53.0 years, 82% female) scanned twice with mean interval 9.9 weeks. DCE-MRI was performed at 3T using a 3D gradient echo sequence with whole brain coverage, T1 mapping using variable flip angles, and a 16-min dynamic sequence with a 3.2-s time resolution. Segmentation of white and grey matter (WM/GM) was performed using a 3D magnetization-prepared gradient echo image. The influx constant Ki was calculated using the Patlak method. The primary outcome was the within-subject coefficient of variation (CV) of Ki in both WM and GM. Ki values followed biological expectations in relation to known GM/WM differences in cerebral blood volume (CBV) and consequently vascular surface area. Subject-derived arterial input functions showed marked within-subject variability which were significantly reduced by using a venous input function (CV of area under the curve 46 vs. 12%, p < 0.001). Use of the venous input function significantly improved the CV of Ki in both WM (30 vs. 59%, p < 0.001) and GM (21 vs. 53%, p < 0.001). Further improvement was obtained using motion correction, scaling the venous input function by the artery, and using the median rather than the mean of individual voxel data. The final method gave CV of 27% and 17% in WM and GM, respectively. No further improvement was obtained by replacing the subject-derived input function by one standard population input function. CV of Ki was shown to be highly sensitive to dynamic sequence duration, with shorter measurement periods giving marked deterioration especially in WM. In conclusion, measurement variability of 3D brain DCE-MRI is sensitive to analysis method and a large precision improvement is obtained using a venous input function.

Home-based guidance training system with interactive visual feedback using kinect on stroke survivors with moderate to severe motor impairment

The home-based training approach benefits stroke survivors by providing them with an increased amount of training time and greater feasibility in terms of their training schedule, particularly for those with severe motor impairment. Computer-guided training systems provide visual feedback with correct movement patterns during home-based training. This study aimed to investigate the improvement in motor performance among stroke survivors with moderate to severe motor impairment after 800 min of training using a home-based guidance training system with interactive visual feedback. Twelve patients with moderate to severe stroke underwent home-based training, totaling 800 min (20–40 min per session, with a frequency of 3 sessions per week). The home-based guidance training system uses Kinect to reconstruct the 3D human body skeletal model and provides real-time motor feedback during training. The training exercises consisted of six core exercises and eleven optional exercises, including joint exercises, balance control, and coordination. Pre-training and post-training assessments were conducted using the Fugl-Meyer Assessment-Upper Limb (FMA-UE), Fugl-Meyer Assessment-Lower Limb (FMA-LE), Functional Ambulation Categories (FAC), Berg Balance Scale (BBS), Barthel Index (BI), Modified Ashworth Scale (MAS), as well as kinematic data of joint angles and center of mass (COM). The results indicated that motor training led to the attainment of the upper limit of functional range of motion (FROM) in hip abduction, shoulder flexion, and shoulder abduction. However, there was no improvement in the active range of motion (AROM) in the upper extremity (U/E) and lower extremity (L/E) joints, reaching the level of the older healthy population. Significant improvements were observed in both left/right and superior/inferior displacements, as well as body sway in the mediolateral axis of the COM, after 800 min of training. In conclusion, the home-based guidance system using Kinect aids in improving joint kinematics performance at the level of FROM and balance control, accompanied by increased mediolateral body sway of the COM for stroke survivors with moderate to severe stroke. Additionally, spasticity was reduced in both the upper and lower extremities after 800 min of home-based training.

High-resolution motion compensation for brain PET imaging using real-time electromagnetic motion tracking.

Substantial improvements in spatial resolution in brain positron emission tomography (PET) scanners have greatly reduced partial volume effect, making head movement the main source of image blur. To achieve high-resolution PET neuroimaging, precise real-time estimation of both head position and orientation is essential for accurate motion compensation. A high-resolution electromagnetic motion tracking (EMMT) system with an event-by-event motion correction is developed for PET-CTscanners. EMMT is comprised of a source, an array of sensors, and a readout electronic unit (REU). The source acts as a transmitter and emits an EM dipole field. It is placed in close proximity to the sensor array and detects changes in EM flux density due to sensor movement. The REU digitizes signals from each sensor and captures precise rotational and translational movements in real time. Tracked motion in the EMMT coordinate system is synchronized with the PET list-mode data and transformed into the scanner coordinate system by locating paired positions in both systems. The optimal rigid motion is estimated using singular value decomposition. The rigid motion and depth-of-interaction (DOI) parallax effect are corrected by event-by-event rebinning of mispositioned lines-of-response (LORs). We integrated the EMMT with our recently developed ultra-high resolution Prism-PET prototype brain scanner and a commercial Siemens Biograph mCT PET-CT scanner. We assessed the imaging performance of the Prism-PET/EMMT system using multi-frame motion of point sources and phantoms. The mCT/EMMT system was validated using a set of point sources attached to both a mannequin head and a human volunteer, for simulating multiframe and continuous motions, respectively. Additionally, a human subject for [18F]MK6240 PET imaging wasincluded. The tracking accuracy of the Prism-PET/EMMT system was quantified as a root-mean-square (RMS) error of 0.49 for 100 axial rotations, and an RMS error of 0.15 mm for 100 mm translations.The percent difference (%diff) in average full width at half maximum (FWHM) of point source between motion-corrected and static images, within a motion range of and 10 mm from the center of the scanner's field-of-view (FOV), was 3.9%. The measured recovery coefficients of the 2.5-mm diameter sphere in the activity-filled partial volume correction phantom were 23.9%, 70.8%, and 74.0% for the phantom with multi-frame motion, with motion and motion compensation, and without motion, respectively. In the mCT/EMMT system, the %diff in average FWHM of point sources between motion-corrected and static images, within a motion range of and 10 mm from the center of the FOV, was 14%. Applying motion correction to the [18F]MK6240 PET imaging reduced the motion-induced spill-in artifact in the lateral ventricle region, lowering its standardized uptake value ratio (SUVR) from 0.70 to 0.34. The proposed EMMT system is a cost-effective, high frame-rate, and none-line-of-sight alternative to infrared camera-based tracking systems and is capable of achieving high rotational and translational tracking accuracies for mitigating motion-induced blur in high-resolution brain dedicated PETscanners.

Early childhood family threat and longitudinal amygdala-mPFC circuit development: Examining cortical thickness and gray matter-white matter contrast

Early threat-associated cortical thinning may be interpreted as accelerated cortical development. However, non-adaptive processes may show similar macrostructural changes. Examining cortical thickness (CT) together with grey/white-matter contrast (GWC), a proxy for intracortical myelination, may enhance the interpretation of CT findings. In this prospective study, we examined associations between early life family-related threat (harsh parenting, family conflict, and neighborhood safety) and CT and GWC development from late childhood to middle adolescence. MRI was acquired from 4200 children (2069 boys) from the Generation R study at ages 8, 10 and 14 years (in total 6114 scans), of whom 1697 children had >1 scans. Linear mixed effect models were used to examine family factor-by-age interactions on amygdala volume, caudal and rostral anterior cingulate (ACC) and medial orbitofrontal cortex (mOFC) CT and GWC. A neighborhood safety-by-age-interaction was found for rostral ACC GWC, suggesting less developmental change in children from unsafe neighborhoods. Moreover, after more stringent correction for motion, family conflict was associated with greater developmental change in CT but less developmental change in GWC. Results suggest that early threat may blunt ACC GWC development. Our results, therefore, do not provide evidence for accelerated threat-associated structural development of the amygdala-mPFC circuit between ages 8–14 years.

Feasibility of submillimeter functional quantitative susceptibility mapping using 3D echo planar imaging at 7 T.

Quantitative susceptibility mapping (QSM) is a tool for mapping tissue susceptibility. Using QSM for functional brain mapping, it is possible to directly quantify blood-oxygen-level-dependent (BOLD) susceptibility changes. This study presents a submillimeter functional QSM (fQSM) approach compared to BOLD fMRI from data acquired with 3D gradient-echo echo planar imaging (EPI) at ultra-high field. Complex EPI data were acquired in nine healthy subjects with varying temporal and spatial resolutions and used for BOLD fMRI and for fQSM. Right-hand finger tapping experiments were performed as well as one measurement with intentional subject movement. Susceptibility maps were computed using 3D path-based unwrapping, the variable-kernel sophisticated harmonic artifact reduction for phase data, and the streaking artifact reduction for QSM algorithm. Functional data analysis included general linear modeling and computation of z-scores. Submillimeter data were denoised using NOise reduction with DIstribution Corrected (NORDIC), which improved z-scores in the motor cortex for fQSM and fMRI. An expected increase in BOLD fMRI signal and corresponding decrease in magnetic susceptibility was observed in sensorimotor areas during active periods. For all experiments, fQSM showed smaller activation regions compared with fMRI. The percentage of high negative t-values localized in the cortex was higher for fQSM (52%) than for positive or negative t-values for fMRI (45%). For the scans with intentional motion, movement exceeded the size of a voxel, but paradigm dependent signal evolution could be recovered using motion correction. In conclusion, this study demonstrates the feasibility of submillimeter whole-brain fQSM with voxel volume of 0.53 μL. In comparison to traditional BOLD fMRI, fQSM provided improved localization of brain activation within the cortex, especially in submillimeter 3D EPI sequences.