Sub-millimeter Resolution Research Articles

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.

Laminar fMRI in the locked-in stage of amyotrophic lateral sclerosis shows preserved activity in layer Vb of primary motor cortex

Amyotrophic lateral sclerosis (ALS) affects the cerebral cortex layer-dependently, most notably by the foremost targeting of upper motor neurons (UMNs) sited in layer Vb. Previous studies have shown a retained ability of paralysed patients to activate cortical motor networks, even in late-stage ALS. However, it is currently unknown whether such activation reflects a retained capacity to process sensorimotor inputs or if it is a result of actual motor output. Given the distinct function of individual cortical layers, layer-specific functional measurements may provide insight to this question. In this study, using submillimetre resolution laminar fMRI, we assessed the layer-dependent activation associated with attempted (motor) and passive (somatosensory) movements in a locked-in stage ALS patient. We found robust activation in both superficial and deep layers of primary motor cortex (M1). The peak activation in deep layers was localised to layer Vb. These findings demonstrate preserved activity in deep output layers of M1, possibly reflecting a retained ability to engage surviving UMNs despite years of paralysis. Our study underscores the capacity of laminar fMRI to discern subtle cortical activity and elucidates a promising pathway for probing in vivo human ALS pathology with unprecedented resolution.

Utilizing acrylic acid polymer hydrogel for 3-D quality assurance in CyberKnife radiotherapy

Dosimetry tools play a crucial role in radiotherapy as they are essential for recording and validating intricate 3-D dose distributions. This research introduces and examines a novel acrylic acid polymer hydrogel (ACAPHG) dosimeter composition designed for 3-D dose verification and quality assurance in the context of radiotherapy treatment. A phantom made of an 80 mm diameter cylindrical glass container was utilized. The phantom contained the hydrogel, which served as the medium for radiation exposure. The water equivalent hydrogel within the phantom was subjected to irradiation by a CyberKnife robotic radiotherapy system. An optical computed tomography (OCT) scanner with sub-millimeter resolution was used to obtain imaging data. The dose distribution of a CyberKnife robotic SRS/SBRT treatment plan for a brain cancer patient was compared to that of the hydrogel's OCT scan using 2-D and 3-D gamma analysis with a criterion of 3% dose difference and 3 mm distance-to-agreement. A gamma pass rate of 94.1% for the 2-D gamma analysis and a pass rate of 99% for the 3-D gamma analysis were calculated within the region at which the treatment planning system data drops to 20% of the maximum dose. The use of the ACAPHG dosimeter in conjunction with the described setup suggests that it has the potential to offer an accurate 3-D verification of complex dose distributions in SRS/SBRT radiotherapy treatments. By employing the ACAPHG dosimeter and utilizing OCT scanning, this dosimeter enables the assessment and validation of intricate dose distributions in these advanced radiotherapy treatments.

Method for co-registration of high-resolution specimen PET-CT with histopathology to improve insight into radiotracer distributions

BackgroundAs the spatial resolution of positron emission tomography (PET) scanners improves, understanding of radiotracer distributions in tissues at high resolutions is important. Hence, we propose a method for co-registration of high-resolution ex vivo specimen PET images, combined with computed tomography (CT) images, and the corresponding specimen histopathology.MethodsWe applied our co-registration method to breast cancer (BCa) specimens of patients who were preoperatively injected with 0.8 MBq/kg [18\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$^{18}$$\\end{document}F]fluorodeoxyglucose ([18F]FDG). The method has two components. First, we used an image acquisition scheme that minimises and tracks tissue deformation: (1) We acquired sub-millimetre (micro)-PET-CT images of ±2 mm-thick lamellas of the fresh specimens, enclosed in tissue cassettes. (2) We acquired micro-CT images of the same lamellas after formalin fixation to visualise tissue deformation. (3) We obtained 1 hematoxylin and eosin (H&E) stained histopathology section per lamella of which we captured a digital whole slide image (WSI). Second, we developed an automatic co-registration algorithm to improve the alignment between the micro-PET-CT images and WSIs, guided by the micro-CT of the fixated lamellas. To estimate the spatial co-registration error, we calculated the distance between corresponding microcalcifications in the micro-CTs and WSIs. The co-registered images allowed to study standardised uptake values (SUVs) of different breast tissues, as identified on the WSIs by a pathologist.ResultsWe imaged 22 BCa specimens, 13 cases of invasive carcinoma of no special type (NST), 6 of invasive lobular carcinoma (ILC), and 3 of ductal carcinoma in situ (DCIS). While the cassette framework minimised tissue deformation, the best alignment between the micro-PET-CT images and WSIs was achieved after deformable co-registration. We found an overall average co-registration error of 0.74 ± 0.17 mm between the micro-PET images and WSIs. (Pre)malignant tissue (including NST, ILC, and DCIS) generally showed higher SUVs than healthy tissue (including healthy glandular, connective, and adipose tissue). As expected, inflamed tissue and skin also showed high uptake.ConclusionsWe developed a method to co-register micro-PET-CT images of surgical specimens and WSIs with an accuracy comparable to the spatial resolution of the micro-PET images. While currently, we only applied this method to BCa specimens, we believe this method is applicable to a wide range of specimens and radiotracers, providing insight into distributions of (new) radiotracers in human malignancies at a sub-millimetre resolution.

Highfield imaging of the subgenual anterior cingulate cortex in uni- and bipolar depression.

The subgenual Anterior Cingulate Cortex (sgACC), as a part of the Anterior Cingulate Cortex and the limbic system plays a crucial role in mood regulation. Previous structural and functional brain imaging studies of the sgACC have revealed alterations of Gray Matter (GM) volumes and Blood Oxygenation Level Dependent signals (BOLD) in patients with Major Depressive Disorder (MDD) and Bipolar Disorder (BD), suggesting potential biomarker traits for affective disorders. In this study we investigated the gray matter volume of the sgACC in 3 different patient groups: 40 MDD patients, of which 20 were medicated (MDDm) and 20 were unmedicated (MDDu), and 21 medicated BD patients, and compared them with 23 healthy volunteers. We examined GM volume alteration using high-resolution 7T Magnetic Resonance Imaging (MRI) which produced quantitative maps of the spin-lattice relaxation time (T1). T1 maps provide high contrast between gray and white matter, and at 7 Tesla voxels with submillimeter resolution can be acquired in a reasonable scan time. We developed a semi-automatic segmentation protocol based on refined landmarks derived from previous volumetric studies using quantitative T1 maps as raw input data for automatic tissue segmentation of GM, WM and CSF (cerebrospinal fluid) tissue. The sgACC ROI was then superimposed on these tissue probability maps and traced manually by two independent raters (F.B., M.M.) following our semi-automatic segmentation protocol. Interrater reliability was calculated on a subset of 10 brain scans for each hemisphere, showing an Intra-Class Correlation coefficient (ICC) r = 0.96 for left sgACC and r = 0.84 for right sgACC respectively. In summary, we have developed a reproducible and reliable semi-automatic segmentation protocol to measure gray matter volume in the sgACC. Based on previous findings from meta-analyses on morphometric studies of the sgACC, we hypothesized that patients with MDD would have lower gray matter sgACC volumes compared to healthy subjects. Post-hoc analysis revealed smaller subgenual volumes for the left hemisphere in both the medicated (MDDm) and non-medicated (MDDu) group versus healthy controls (p = .001, p = .008) respectively. For the right hemisphere, the (MDDu) and BD group exhibited significantly lower subgenual volumes than healthy controls (p < .001, p = .004) respectively. To our knowledge, this is the first morphometric MRI study using T1 maps obtained in high-resolution 7 Tesla MRI to compare MDD and BD patients with healthy controls.

Deep learning constrained compressed sensing reconstruction improves high-resolution three-dimensional (3D) T2-weighted turbo spin echo magnetic resonance imaging (MRI) of the lumbar spine

We sought to assess the image quality of three-dimensional (3D) T2-weighted (T2w) turbo spin echo (TSE) sequences with deep learning (DL)-constrained compressed sensing (CS) reconstruction relative to a reference two-dimensional (2D) T2w TSE sequence for routine clinical lumbar spine MRI. Fifty-three patients underwent imaging of the lumbar spine with a sagittal 2D T2w TSE sequence and with two CS-accelerated 3D T2w TSE sequences (voxel size of 0.4×0.4×0.5 mm) with CS factors of 7 and 11. The CS-accelerated sequences were reconstructed with iterative reconstruction with wavelet transformation (conventional CS) and secondly with a DL-constrained CS reconstruction (named CS-AI). Two readers graded image quality, based on 8 metrics (overall image quality, presence of image noise, presence of motion artifacts, delineation/conspicuity and clarity of anatomical structures such as the spinal cord, cauda equine nerve roots, cerebrospinal fluid (CSF), intervertebral disc, and bone marrow and intervertebral foramen) using Likert scales. Overall inter-readout agreement was substantial (Krippendorff's α=0.724, 95% confidence interval [CI]: 0.692-0.755). The CS7-AI and CS11-AI sequences were comparable or better than the 2D sequence in all 8 metrics (p < 0.001-p > 0.99). The CS7 and CS11 sequences were comparable or better than the 2D sequence in only 5 and 3 of the 8 metrics, respectively (p < 0.001-p > 0.99). A DL-constrained CS reconstruction significantly improves the quality of accelerated high-resolution 3D T2w TSE imaging of the lumbar spine. Thus, high-quality imaging in a submillimeter resolution in all three imaging planes can be achieved without compromising the image quality as compared with standard 2D T2w TSE imaging.

Design and validation of a high-speed hyperspectral laparoscopic imaging system.

Minimally invasive surgery (MIS) has shown vast improvement over open surgery by reducing post-operative stays, intraoperative blood loss, and infection rates. However, in spite of these improvements, there are still prevalent issues surrounding MIS that may be addressed through hyperspectral imaging (HSI). We present a laparoscopic HSI system to further advance the field of MIS. We present an imaging system that integrates high-speed HSI technology with a clinical laparoscopic setup and validate the system's accuracy and functionality. Different configurations that cover the visible (VIS) to near-infrared (NIR) range of electromagnetism are assessed by gauging the spectral fidelity and spatial resolution of each hyperspectral camera. Standard Spectralon reflectance tiles were used to provide ground truth spectral footprints to compare with those acquired by our system using the root mean squared error (RMSE). Demosaicing techniques were investigated and used to measure and improve spatial resolution, which was assessed with a USAF resolution test target. A perception-based image quality evaluator was used to assess the demosaicing techniques we developed. Two configurations of the system were developed for evaluation. The functionality of the system was investigated in a phantom study and by imaging ex vivo tissues. Multiple configurations of our system were tested, each covering different spectral ranges, including VIS (460 to 600nm), red/NIR (RNIR) (610 to 850nm), and NIR (665 to 950nm). Each configuration is capable of achieving real-time imaging speeds of up to 20 frames per second. RMSE values of , , and 3.47% were achieved for the VIS, RNIR, and NIR systems, respectively. We obtained sub-millimeter resolution using our demosaicing techniques. We developed and validated a high-speed hyperspectral laparoscopic imaging system. The HSI system can be used as an intraoperative imaging tool for tissue classification during laparoscopic surgery.

Evaluating the effect of denoising submillimeter auditory fMRI data with NORDIC

Abstract Functional magnetic resonance imaging (fMRI) has emerged as an essential tool for exploring human brain function. Submillimeter fMRI, in particular, has emerged as a tool to study mesoscopic computations. The inherently low signal-to-noise ratio (SNR) at submillimeter resolutions warrants the use of denoising approaches tailored at reducing thermal noise—the dominant contributing noise component in high-resolution fMRI. NOise Reduction with DIstribution Corrected Principal Component Analysis (NORDIC PCA) is one of such approaches, and has been benchmarked against other approaches in several applications. Here, we investigate the effects that two versions of NORDIC denoising have on auditory submillimeter data. While investigating auditory functional responses poses unique challenges, we anticipated NORDIC to have a positive impact on the data on the basis of previous applications. Our results show that NORDIC denoising improves the detection sensitivity and the reliability of estimates in submillimeter auditory fMRI data. These effects can be explained by the reduction of the noise-induced signal variability. However, we did observe a reduction in the average response amplitude (percent signal change) within regions of interest, which may suggest that a portion of the signal of interest, which could not be distinguished from general i.i.d. noise, was also removed. We conclude that, while evaluating the effects of the signal reduction induced by NORDIC may be necessary for each application, using NORDIC in high-resolution auditory fMRI studies may be advantageous because of the large reduction in variability of the estimated responses.

Recurrent inhibition refines mental templates to optimize perceptual decisions.

Translating sensory inputs to perceptual decisions relies on building internal representations of features critical for solving complex tasks. Yet, we still lack a mechanistic account of how the brain forms these mental templates of task-relevant features to optimize decision-making. Here, we provide evidence for recurrent inhibition: an experience-dependent plasticity mechanism that refines mental templates by enhancing γ-aminobutyric acid (GABA)-mediated (GABAergic) inhibition and recurrent processing in superficial visual cortex layers. We combine ultrahigh-field (7 T) functional magnetic resonance imaging at submillimeter resolution with magnetic resonance spectroscopy to investigate the fine-scale functional and neurochemical plasticity mechanisms for optimized perceptual decisions. We demonstrate that GABAergic inhibition increases following training on a visual (i.e., fine orientation) discrimination task, enhancing the discriminability of orientation representations in superficial visual cortex layers that are known to support recurrent processing. Modeling functional and neurochemical plasticity interactions reveals that recurrent inhibitory processing optimizes brain computations for perpetual decisions and adaptive behavior.

Lesion phenotyping based on magnetic susceptibility in pediatric multiple sclerosis.

Pediatric multiple sclerosis (MS) displays different pathological features compared to adult MS, which can be studied in vivo by assessing tissue magnetic susceptibility with 3T-MRI. We aimed to assess different white matter lesions (WMLs) phenotypes in pediatric MS patients using quantitative susceptibility mapping (QSM) and susceptibility mapping weighted imaging (SMWI) over 12 months. Eleven pediatric MS patients [female: 63.6%; mean ± standard deviation (SD) age and disease duration: 16.3 ± 2.2 and 2.4 ± 1.5; median (range) Expanded Disability Status Scale (EDSS) 1 (0-2)] underwent 3 Tesla-MRI exams and EDSS assessments at baseline and after 1 year. QSM and SMWI were obtained using 3-dimensional (3D)-segmented echo-planar-imaging with submillimetric spatial resolution. WMLs were classified according to their QSM appearance and SMWI was used to identify QSM hyperintensities ascribable to veins. Total brain volumes at baseline and follow-up were computed using high-resolution 3D T1-weighted images. Mean ± SD paramagnetic rim lesions (PRLs) prevalence was 7.0% ± 9.0. Fifty-four percent (6/11) of patients exhibited at least one PRL, with one patient exhibiting ≥ 4 PRLs. All patients showed QSM-iso-/hypo-intense lesions, which represented a mean ± SD of 65.8% ± 22.7 of total WMLs. QSM-hyperintense WMLs showed a positive correlation with total brain volume reduction at follow-up (r = 0.705; p = .02). No lesion was classified as different between baseline and follow-up. Chronic compartmentalized inflammation seems to occur early in pediatric MS patients with short disease duration. A high prevalence of iso-/hypo-intense lesions was found, which could account for the higher remyelination potential in pediatric MS.

Hyperpolarized Water for Coronary Artery Angiography and Whole-Heart Myocardial Perfusion Quantification.

Purpose: Water freely diffuses across cell membranes, making it suitable for measuring absolute tissue perfusion. In this study, we introduce an imaging method for conducting coronary artery angiography and quantifying myocardial perfusion across the entire heart using hyperpolarized water. Methods:1H was hyperpolarized using dissolution dynamic nuclear polarization (dDNP) with UV-generated radicals. Submillimeter resolution coronary artery images were acquired as 2D projections using a spoiled GRE (SPGRE) sequence gated on diastole. Dynamic perfusion images were obtained with a multi-slice SPGRE with diastole gating, covering the entire heart. Perfusion values were analyzed through histograms, and the most frequent estimated perfusion value (the mode of the distribution), was compared with the average values for 15O water PET from the literature. Results: A liquid state polarization of 10% at the time of the injection and a 30 s T1 in D2O TRIS buffer were measured. Both coronary artery and dynamic perfusion images exhibited good quality. The main and small coronary artery branches were well resolved. The most frequent estimated perfusion value is around 0.6 mL/g/min, which is lower than the average values obtained from the literature for 15O-water PET (around 1.1 and 1.5 mL/g/min). Conclusions: The study successfully demonstrated the feasibility of achieving high-resolution, motion-free coronary artery angiography and 3D whole-heart quantitative myocardial perfusion using hyperpolarized water.

Position-Sensitive Silicon Photomultiplier Arrays with Large-Area and Sub-Millimeter Resolution.

Silicon photomultipliers (SiPMs) are solid-state single-photon-sensitive detectors that show excellent performance in a wide range of applications. In FBK (Trento, Italy), we developed a position-sensitive SiPM technology, called "linearly graded" (LG-SiPM), which is based on an avalanche-current weighted-partitioning approach. It shows position reconstruction resolution below 250 μm on an 8 × 8 mm2 device area with four readout channels and minimal distortions. A recent development in terms of LG-SIPM is a larger chip version (10 × 10 mm2) based on FBK NUV-HD technology (near-ultraviolet sensitive), with a peak photon detection efficiency at 420 nm. Such a large-area detector with position sensitivity is very interesting in applications like MR-compatible PET, high-energy physics experiments, and readout of time-projection chambers, gamma and beta cameras, or scintillating fibers, with a reduced number of channels. These SiPMs were characterized in terms of noise, photon detection efficiency, and position resolution. We also developed tiles of 2 × 2 and 3 × 3 LG-SiPMs, reaching very large sensitive areas of 20 × 20 mm2 and 30 × 30 mm2. We implemented a "smart-channel" configuration, which allowed us to have just six output channels for the 2 × 2 elements and eight channels for the 3 × 3 element tiles, preserving a position resolution below 0.5 mm. These kinds of detectors provide a great advantage in compact and low-power applications by maintaining position sensitivity over large areas with a small number of channels.

Mapping short association fibre connectivity up to V3 in the human brain in vivo.

Short association fibres (SAF) are the most abundant fibre pathways in the human white matter. Until recently, SAF could not be mapped comprehensively in vivo because diffusion weighted magnetic resonance imaging with sufficiently high spatial resolution needed to map these thin and short pathways was not possible. Recent developments in acquisition hardware and sequences allowed us to create a dedicated in vivo method for mapping the SAF based on sub-millimetre spatial resolution diffusion weighted tractography, which we validated in the human primary (V1) and secondary (V2) visual cortex against the expected SAF retinotopic order. Here, we extended our original study to assess the feasibility of the method to map SAF in higher cortical areas by including SAF up to V3. Our results reproduced the expected retinotopic order of SAF in the V2-V3 and V1-V3 stream, demonstrating greater robustness to the shorter V1-V2 and V2-V3 than the longer V1-V3 connections. The demonstrated ability of the method to map higher-order SAF connectivity patterns in vivo is an important step towards its application across the brain.

Detecting antimony(III) on-site using novel gel-based techniques: Colorimetric diffusive equilibrium in thin films for two-dimensional imaging and surface-enhanced Raman scattering for sensitive quantification

Antimony (Sb) pollution has raised increasing public concerns and its rapid on-site screening is central for the risk assessment. Herein, we proposed two gel-based methods based on colorimetric diffusive equilibrium in thin films (DET) and surface-enhanced Raman scattering (SERS), for two-dimensional imaging and sensitive detection of Sb(III) by revisiting the phenylfluorone (PhF) complexation reaction. PhF was well dispersed in the polyvinyl alcohol (PVA) hydrogel and reacted with Sb(III) in the DET gel to form a strong PhF-Sb(III) complex. The distribution of Sb(III) was easily visualized at a submillimeter resolution using computer imaging densitometry, with a detection limit (LOD) of ∼100 nmol L−1. Field application in the Sb mine area reveals limited dissolved Sb(III) penetrating the redox barrier below the sediment-water interface by 20 mm in rivers and tailing pond sediments. To improve the detection sensitivity and apply the principle to trace Sb quantification, a SERS platform was established by anchoring PhF on the hydrogel-stabilized Ag nanoparticles via C–O–Ag bonding to specifically detect Raman-inactive Sb(III). Benefiting from the high SERS activity of PhF and enrichment ability of hydrogel, Sb(III) was quantified with a LOD of 1.2–10.7 nmol L−1 depending on the sample volume. The coexisting ions at a 100-fold higher concentration than Sb(III) resulted in only 3.3–10.4 % variation in SERS intensity, indicating a negligible interference on the SERS platform. The platform exhibited a RSD of 6.6–13.1 % and acceptable recoveries for various environmental matrices, highlighting its promise in on-site application.

Optical frequency domain reflectometry-based high-performance distributed sensing empowered by a data and physics-driven neural network

Optical frequency domain reflectometry (OFDR) based distributed strain sensors are the preferred choice for achieving accurate strain measurements over extensive sensing ranges while maintaining exceptional spatial resolution. However, the simultaneous realization of high spatial resolution, high strain resolution, large strain range, and an extended sensing range presents an exceedingly challenging endeavor. In this study, we introduce and experimentally demonstrate a data and physics-driven neural network-empowered OFDR system designed to attain high-performance distributed sensing. In our experiments, we successfully maintained an impressive sensing resolution of sub-microstrain (0.91 με) alongside a sharp spatial resolution of sub-millimeter (0.857 mm) across a 140-m sensing range. To the best of our knowledge, this marks the inaugural experimental demonstration of OFDR-based distributed sensing, combining sub-millimeter spatial resolution and sub-με strain resolution across a lengthy sensing range over a hundred meters. This pioneering work unveils new pathways for the development of ultra-high-performance optical fiber sensing systems, paving the way for the next generation of intelligent systems tailored for diverse smart industrial applications.

A calorimetric evaluation method for beam targets with IR imaging: Implementation for the negative ion source BATMAN Upgrade

A comprehensive calorimetric evaluation method is presented for the beam target installed in the testbed BATMAN Upgrade (BUG). BUG hosts the prototype RF-driven negative ion source for the ITER Neutral Beam Heating System. In nominal conditions BUG features an array of negative ion beamlets (5 horizontal × 14 vertical) with 20 mm spacing among them. Each beamlet is accelerated electrostatically up to a maximum of 45 kV and transports currents in the range from 0.01 to 0.05 A. BUG has two beam targets at different distances from the beam acceleration system. The furthest (2.08 m downstream) is a water-cooled diagnostic CW-calorimeter, which can measure the heat flux distribution of the beam with a resolution of 20 × 20 mm² over a surface of 600 (H) × 800 (V) mm² and water calorimetry. The closest (0.86 m downstream) beam target with sub-millimetric resolution consists of a (376 × 142 × 20 mm³) tile made of a composite anisotropic material with carbon fibers oriented in the thickness direction (1D-CFC). It can only be exposed to beams for limited time, therefore it is retractable. Infrared (IR) imaging of beam targets yields time-resolved high-resolution spatial temperature footprints. A simple algorithm is proposed to reconstruct the heat flux at the front of a beam target, from the IR footprints at the rear. The reconstructed heat flux profiles are lower and broader due to heat conduction effects in the beam target. A correction algorithm is proposed through simulation-based inference of 2D axisymmetrical FEM simulations that reduces the power and shape fit errors over an order of magnitude, to a few percent. The calorimetric evaluation method is applied to experimental shots and two advanced heat flux distribution analysis are shown. The most relevant error sources are discussed and quantified to assess systematic errors. Finally, the method is validated in BUG comparing total beam power estimations with the two calorimetric diagnostics from the CW-calorimeter, showing good agreement.

Test Platform for Developing New Optical Position Tracking Technology towards Improved Head Motion Correction in Magnetic Resonance Imaging.

Optical tracking of head pose via fiducial markers has been proven to enable effective correction of motion artifacts in the brain during magnetic resonance imaging but remains difficult to implement in the clinic due to lengthy calibration and set up times. Advances in deep learning for markerless head pose estimation have yet to be applied to this problem because of the sub-millimetre spatial resolution required for motion correction. In the present work, two optical tracking systems are described for the development and training of a neural network: one marker-based system (a testing platform for measuring ground truth head pose) with high tracking fidelity to act as the training labels, and one markerless deep-learning-based system using images of the markerless head as input to the network. The markerless system has the potential to overcome issues of marker occlusion, insufficient rigid attachment of the marker, lengthy calibration times, and unequal performance across degrees of freedom (DOF), all of which hamper the adoption of marker-based solutions in the clinic. Detail is provided on the development of a custom moiré-enhanced fiducial marker for use as ground truth and on the calibration procedure for both optical tracking systems. Additionally, the development of a synthetic head pose dataset is described for the proof of concept and initial pre-training of a simple convolutional neural network. Results indicate that the ground truth system has been sufficiently calibrated and can track head pose with an error of <1 mm and <1°. Tracking data of a healthy, adult participant are shown. Pre-training results show that the average root-mean-squared error across the 6 DOF is 0.13 and 0.36 (mm or degrees) on a head model included and excluded from the training dataset, respectively. Overall, this work indicates excellent feasibility of the deep-learning-based approach and will enable future work in training and testing on a real dataset in the MRI environment.

Corrosion detection and localisation utilising a novel thin film guided wave sensor sparse array

Detecting and pinpointing corrosion-related damage in infrastructure poses significant financial and technical difficulties. It is simply not feasible to manually inspect all infrastructure for corrosion. Permanently installed systems can monitor critical failure points without the need for manual scanning but these are not always known. Ultrasonic guided wave technology can be used for full system coverage, however, there is a trade-off between range and resolution. This has found a place for long distance monitoring of significant defects, however high- resolution systems require too dense a network to be feasible to install, cost and maintain. This research seeks a middle ground between these two options by employing machine learning and a scalable setup of easy to install, printed detection sensors. A flexible array of printed thin film sensors is placed around two identical mild steel pipes, each 0.5m long with a 6 mm wall thickness and 115 mm outer diameter. Corrosion is then induced artificially in one sample. Two transmit transducers on the top and bottom of the pipes are used to emit an ultrasonic, circumferential guided wave. The transmitted waveform was then received on all sensors throughout the array for data collection. Through machine learning and a search algorithm, sub-millimetre resolution is achieved, detecting millimetre-scale corrosion and localisation to the nearest detection sensor. Crucially, the system maintains scalability for large-scale asset inspection. This technology shows promise in addressing inspection challenges, including Corrosion Under Pipe Supports (CUPS) and Corrosion Under Insulation (CUI). It offers a potential solution to the costly problem of infrastructure damage detection and localisation while retaining scalability and a low-profile design philosophy.

Virtual cylindrical PET for efficient DOI image reconstruction with sub-millimetre resolution

Objective. Image reconstruction in high resolution, narrow bore PET scanners with depth of interaction (DOI) capability presents a substantial computational challenge due to the very high sampling in detector and image space. The aim of this study is to evaluate the use of a virtual cylinder in reducing the number of lines of response (LOR) for DOI-based reconstruction in high resolution PET systems while maintaining uniform sub-millimetre spatial resolution. Approach. Virtual geometry was investigated using the awake animal mousePET as a high resolution test case. Using GEANT4 Application for Tomographic Emission (GATE), we simulated the physical scanner and three virtual cylinder implementations with detector size 0.74 mm, 0.47 mm and 0.36 mm (vPET1, vPET2 and vPET3, respectively). The virtual cylinder condenses physical LORs stemming from various crystal pairs and DOI combinations, and which intersect a single virtual detector pair, into a single virtual LOR. Quantitative comparisons of the point spread function (PSF) at various positions within the field of view (FOV) were compared for reconstructions based on the vPET implementations and the physical scanner. We also assessed the impact of the anisotropic PSFs by reconstructing images of a micro Derenzo phantom. Main results. All virtual cylinder implementations achieved LOR data compression of at least 50% for DOI PET reconstruction. PSF anisotropy in radial and tangential profiles was chiefly influenced by DOI resolution and only marginally by virtual detector size. Spatial degradation introduced by virtual cylinders was most prominent in the axial profile. All virtual cylinders achieved sub-millimetre volumetric resolution across the FOV when 6-bin DOI reconstructions (3.3 mm DOI resolution) were performed. Using vPET2 with 6 DOI bins yielded nearly identical reconstructions to the non-virtual case in the transaxial plane, with an LOR compression factor of 86%. Resolution modelling significantly reduced the effects of the asymmetric PSF arising from the non-cylindrical geometry of mousePET. Significance. Narrow bore and high resolution PET scanners require detectors with DOI capability, leading to computationally demanding reconstructions due to the large number of LORs. In this study, we show that DOI PET reconstruction with 50%–86% LOR compression is possible using virtual cylinders while maintaining sub-millimetre spatial resolution throughout the FOV. The methodology and analysis can be extended to other scanners with DOI capability intended for high resolution PET imaging.

On the influence of the vascular architecture on Gradient Echo and Spin Echo BOLD fMRI signals across cortical depth: a simulation approach based on realistic 3D vascular networks.

GE-BOLD contrast stands out as the predominant technique in functional MRI experiments for its high sensitivity and straightforward implementation. GE-BOLD exhibits rather similar sensitivity to vessels independent of their size at submillimeter resolution studies like those examining cortical columns and laminae. However, the presence of nonspecific macrovascular contributions poses a challenge to accurately isolate neuronal activity. SE-BOLD increases specificity towards small vessels, thereby enhancing its specificity to neuronal activity, due to the effective suppression of extravascular contributions caused by macrovessels with its refocusing pulse. However, even SE-BOLD measurements may not completely remove these macrovascular contributions. By simulating hemodynamic signals across cortical depth, we gain insights into vascular contributions to the laminar BOLD signal. In this study, we employed four realistic 3D vascular models to simulate oxygen saturation states in various vascular compartments, aiming to characterize both intravascular and extravascular contributions to GE and SE signals, and corresponding BOLD signal changes, across cortical depth at 7T. Simulations suggest that SE-BOLD cannot completely reduce the macrovascular contribution near the pial surface. Simulations also show that both the specificity and signal amplitude of BOLD signals at 7T depend on the spatial arrangement of large vessels throughout cortical depth and on the pial surface.