Parametric Mapping Research Articles

Constrained alternating minimization for parameter mapping (CAMP)

ObjectiveTo improve image quality in highly accelerated parameter mapping by incorporating a linear constraint that relates consecutive images. ApproachIn multi-echo T1 or T2 mapping, scan time is often shortened by acquiring undersampled but complementary measures of k-space at each TE or TI. However, residual undersampling artifacts from the individual images can then degrade the quality of the final parameter maps.In this work, a new reconstruction method, dubbed Constrained Alternating Minimization for Parameter mapping (CAMP), is introduced. This method simultaneously extracts T2 or T1* maps in addition to an image for each TE or TI from accelerated datasets, leveraging the constraints of the decay to improve the reconstructed image quality. The model enforces exponential decay through a linear constraint, resulting in a biconvex objective function that lends itself to alternating minimization. The method was tested in four in vivo volunteer experiments and validated in phantom studies and healthy subjects, using T2 and T1 mapping, with accelerations of up to 12. Main resultsCAMP is demonstrated for accelerated radial and Cartesian acquisitions in T2 and T1 mapping. The method is even applied to generate an entire T2 weighted image series from a single TSE dataset, despite the blockwise k-space sampling at each echo time. Experimental undersampled phantom and in vivo results processed with CAMP exhibit reduced artifacts without introducing bias. SignificanceFor a wide array of applications, CAMP linearizes the model cost function without sacrificing model accuracy so that the well-conditioned and highly efficient reconstruction algorithm improves the image quality of accelerated parameter maps.

Mapping of Water and Soil Quality Parameters in the Gampaha-Ihalagama East and Eldeniya East Grama Niladhari Divisions, Sri Lanka

Water and soil are important natural resources, and the study of their distribution is of great interest. The Grama Niladhari Divisions, Ihalagama-East and Eldeniya-East, located in the Gampaha district, are selected as the study areas, and this is done as a pilot study. Different water and soil quality parameters are investigated followed by the construction of contour maps. As water quality parameters, pH, conductivity, phosphate content, nitrate content, and Ca2+ hardness were determined, and as soil quality parameters, pH, nitrate, organic matter, water-soluble Na+ and K+, extractable Na+ and K+, and water-soluble Ca2+ ion contents were determined. The pH of water samples lies within the range of 4.41 - 7.11 and 3.79 – 7.18 in the Ihalagama-East and Eldeniya East divisions, respectively. Almost all the samples have acidic pH values, with some falling below the lower limit of the WHO guidelines for safe drinking water (6.5 - 8.5). Conductivity values vary from 52.0 - 277.0 µS/cm and between 54.0 – 403.0 µS/cm, respectively, which is below the WHO permissible level of 1500 µS/cm. The phosphate content varies from 1.374 - 3.986 mg/L in Ihalagama-East and water-soluble phosphate was not detected in Eldeniya-East, indicating a very low range and suggesting that the water samples are less contaminated with phosphate-containing substances. Considerably high values in the range of 1.24 - 279.00 mg/L for Ihalagama-east and 59.5 mg/L - 168.0 mg/L for Eldeniya-East, are obtained for the nitrate content where most of them are beyond the safe level of drinking water, 50 mg/L. The soil pH in all the samples falls within the acidic range, varying from 2.99 - 6.73 in Ihalagama-East and 3.07 – 6.68 in Eldeniya-East. Most of the soil samples contain high nitrate contents, indicating significant contamination. The percentage soil organic matter content varies between 0.60% and 13.27% in both areas. Many fertile agricultural soils typically have an organic matter content ranging from 3% - 6% revealing that most of the samples are beyond the standard levels. The distribution of water-soluble and extractable cations does not exhibit a wide range. According to the findings, though two Grama Niladhari Divisions are selected, they also display a huge variation. This reveals the importance of mapping to address contaminations, effects of natural disasters which lead to changes in the studied water and soil quality parameters.

Application of Instrumented Indentation Test and Neural Networks to determine the constitutive model of in-situ austenitic stainless steel components

Over the last few decades, Instrumented Indentation Test (IIT) has evolved into a versatile and convenient method for assessing the mechanical properties of metals. Unlike conventional hardness tests, IIT allows for incremental control of the indenter based on depth or force, enabling the measurement of not only hardness but also tensile properties, fracture toughness, and welding residual stress. Two crucial measures in IIT are the reaction force (F) exerted by the tested material on the indenter and the depth of the indenter (D). Evaluation of the mentioned properties from F–D curves typically involves complex analytical formulas that restricts the application of IIT to a limited group of materials. Moreover, for soft materials, such as austenitic stainless steel SS304L, with excessive pile-up/sink-in behaviors, conducting IIT becomes challenging due to improper evaluation of the imprint depth. In this work, we propose a systematic procedure for replacing complex analytical evaluations of IIT and expensive physical measurements. The proposed approach is based on the well-known potential of Neural Networks (NN) for data-driven modeling. We carried out physical IIT and tensile tests on samples prepared from SS304L. In addition, we generated multiple configurations of material properties and simulated the corresponding number of IITs using Finite Element Method (FEM). The information provided by the physical tests and simulated data from FEM are integrated into an NN, to produce a parametric mapping that can predict the parameters of a constitutive model based on any given F–D curve. Our physical and numerical experiments successfully demonstrate the potential of the proposed approach.

Integrating Demographics and Imaging Features for Various Stages of Dementia Classification: Feed Forward Neural Network Multi-Class Approach.

MRI magnetization-prepared rapid acquisition (MPRAGE) is an easily available imaging modality for dementia diagnosis. Previous studies suggested that volumetric analysis plays a crucial role in various stages of dementia classification. In this study, volumetry, radiomics and demographics were integrated as inputs to develop an artificial intelligence model for various stages, including Alzheimer's disease (AD), mild cognitive decline (MCI) and cognitive normal (CN) dementia classifications. The Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset was separated into training and testing groups, and the Open Access Series of Imaging Studies (OASIS) dataset was used as the second testing group. The MRI MPRAGE image was reoriented via statistical parametric mapping (SPM12). Freesurfer was employed for brain segmentation, and 45 regional brain volumes were retrieved. The 3D Slicer software was employed for 107 radiomics feature extractions from within the whole brain. Data on patient demographics were collected from the datasets. The feed-forward neural network (FFNN) and the other most common artificial intelligence algorithms, including support vector machine (SVM), ensemble classifier (EC) and decision tree (DT), were used to build the models using various features. The integration of brain regional volumes, radiomics and patient demographics attained the highest overall accuracy at 76.57% and 73.14% in ADNI and OASIS testing, respectively. The subclass accuracies in MCI, AD and CN were 78.29%, 89.71% and 85.14%, respectively, in ADNI testing, as well as 74.86%, 88% and 83.43% in OASIS testing. Balanced sensitivity and specificity were obtained for all subclass classifications in MCI, AD and CN. The FFNN yielded good overall accuracy for MCI, AD and CN categorization, with balanced subclass accuracy, sensitivity and specificity. The proposed FFNN model is simple, and it may support the triage of patients for further confirmation of the diagnosis.

Systematic review of cardiovascular magnetic resonance imaging T1 and T2 mapping in patients with Takotsubo syndrome

BackgroundCurrent imaging advancements quantify the use of cardiovascular magnetic resonance (CMR) derived T1 and T2 tissue characterization as robust indicators for cardiomyopathies, but limited literature exists on its clinical application in Takotsubo syndrome (TTS). This systematic review evaluated the T1 and T2 parametric mapping to delineate the current diagnostic and prognostic CMR imaging outcomes in TTS. MethodsA comprehensive literature search until October 2023 was performed on ScienceDirect, PubMed, Web of Science, and Cochrane Library by two independent reviewers adhering to the PRISMA framework. The Newcastle-Ottawa Scale (NOS) was used to evaluate the methodological quality of studies. ResultsOut of 198 results, 8 studies were included in this qualitative synthesis, accounting for a total population of 399 subjects (TTS = 201, controls = 175, acute myocarditis = 14, and acute regional myocardial oedema without infarction = 9). Approximately 50.4 % were TTS patients aged between 61 and 73 years, whereof, females (n = 181, 90.0 %) and apical variants (n = 180, 89.6 %) were significantly higher, and emotional stressor (n = 42; 20.9 %) was more prevalent than physical (n = 27; 13.4 %). The NOS identified 62.5 % of studies as moderate and 37.5 % as high quality. Parametric tissue mapping revealed significantly prolonged T1 and T2 relaxation times at 1.5T and 3T respectively in TTS (1053–1164 msec, 1292–1438 msec; and 56–67 msec, 60–90 msec) with higher extracellular volume (ECV) fraction (29–36 %), compared to healthy subjects (944–1211 msec, 1189–1251 msec; and 46–54 msec, 32–68 msec; 23–29 %) and myocarditis (1058 msec, 60 msec). Other significant myocardial abnormalities included increased left ventricular (LV) end-systolic and diastolic volume and reduced global longitudinal strain. Overall, myocardial oedema, altered LV mass and strain, and worse LV systolic function, with higher native T1, T2, and ECV values were consistent. ConclusionsFuture research with substantially larger clinical trials is vital to explore the CMR imaging findings in diverse TTS patient cohorts and correlate the T1 and T2 mapping outcomes with demographic/clinical covariates. CMR is a valuable imaging tool for TTS diagnosis and prognostication. T1 and T2 parametric mapping facilitates the quantification of oedema, inflammation, and myocardial injury in Takotsubo.

The biomechanical influence of transtibial Bone-Anchored limbs during walking

Individuals with unilateral transtibial amputation (TTA) using socket prostheses demonstrate asymmetric joint biomechanics during walking, which increases the risk of secondary comorbidities (e.g., low back pain (LBP), osteoarthritis (OA)). Bone-anchored limbs are an alternative to socket prostheses, yet it remains unknown how they influence multi-joint loading. Our objective was to determine the influence of bone-anchored limb use on multi-joint biomechanics during walking. Motion capture data (kinematics, ground reaction forces) were collected during overground walking from ten participants with unilateral TTA prior to (using socket prostheses) and 12-months after bone-anchored limb implantation. Within this year, each participant completed a rehabilitation protocol that guided progression of loading based on patient pain response and optimized biomechanics. Musculoskeletal models were developed at each testing timepoint (baseline or 12-months after implantation) and used to calculate joint kinematics, internal joint moments, and joint reaction forces (JRFs). Analyses were performed during three stance periods on each limb. The between-limb normalized symmetry index (NSI) was calculated for joint moments and JRF impulses. Discrete (range of motion (ROM), impulse NSI) dependent variables were compared before and after implantation using paired t-tests with Bonferroni-Holm corrections while continuous (ensemble averages of kinematics, moments, JRFs) were compared using statistical parametric mapping (p < 0.05). When using a bone-anchored limb, frontal plane pelvic (residual: pre = 9.6 ± 3.3°, post = 6.3 ± 2.5°, p = 0.004; intact: pre = 10.2 ± 3.9°, post = 7.9 ± 2.6°, p = 0.006) and lumbar (residual: pre = 15.9 ± 7.0°, post = 10.6 ± 2.5°, p = 0.024, intact: pre = 17.1 ± 7.0°, post = 11.4 ± 2.8°, p = 0.014) ROM was reduced compared to socket prosthesis use. The intact limb hip extension moment impulse increased (pre = -11.0 ± 3.6 Nm*s/kg, post = -16.5 ± 4.4 Nm*s/kg, p = 0.005) and sagittal plane hip moment impulse symmetry improved (flexion: pre = 23.1 ± 16.0 %, post = -3.9 ± 19.5 %, p = 0.004, extension: pre = 29.2 ± 20.3 %, post = 8.7 ± 22.9 %, p = 0.049). Residual limb knee extension moment impulse decreased compared to baseline (pre = 15.7 ± 10.8 Nm*s/kg, post = 7.8 ± 3.9 Nm*s/kg, p = 0.030). These results indicate that bone-anchored limb implantation alters multi-joint biomechanics, which may impact LBP or OA risk factors in the TTA population longitudinally.

Conversion of single-energy CT to parametric maps of dual-energy CT using convolutional neural network.

We propose a deep learning (DL) multitask learning framework using convolutional neural network for a direct conversion of single-energy CT (SECT) to 3 different parametric maps of dual-energy CT (DECT): virtual-monochromatic image (VMI), effective atomic number (EAN), and relative electron density (RED). We propose VMI-Net for conversion of SECT to 70, 120, and 200 keV VMIs. In addition, EAN-Net and RED-Net were also developed to convert SECT to EAN and RED. We trained and validated our model using 67 patients collected between 2019 and 2020. Single-layer CT images with 120 kVp acquired by the DECT (IQon spectral CT; Philips Healthcare, Amsterdam, Netherlands) were used as input, while the VMIs, EAN, and RED acquired by the same device were used as target. The performance of the DL framework was evaluated by absolute difference (AD) and relative difference (RD). The VMI-Net converted 120 kVp SECT to the VMIs with AD of 9.02 Hounsfield Unit, and RD of 0.41% compared to the ground truth VMIs. The ADs of the converted EAN and RED were 0.29 and 0.96, respectively, while the RDs were 1.99% and 0.50% for the converted EAN and RED, respectively. SECT images were directly converted to the 3 parametric maps of DECT (ie, VMIs, EAN, and RED). By using this model, one can generate the parametric information from SECT images without DECT device. Our model can help investigate the parametric information from SECT retrospectively. DL framework enables converting SECT to various high-quality parametric maps of DECT.

Suitability Study of Biofuel Blend for Light Commercial Vehicle Application under Real-World Transient Operating Conditions

&lt;div&gt;Driving schedule of every vehicle involves transient operation in the form of changing engine speed and load conditions, which are relatively unchanged during steady-state conditions. As well, the results from transient conditions are more likely to reflect the reality. So, the current research article is focused on analyzing the biofuel-like lemon peel oil (LPO) behavior under real-world transient conditions with fuel injection parameter MAP developed from steady-state experiments. At first, engine parameters and response MAPs are developed by using a response surface methodology (RSM)-based multi-objective optimization technique. Then, the vehicle model has been developed by incorporating real-world transient operating conditions. Finally, the developed injection parameters and response MAPs are embedded in the vehicle model to analyze the biofuel behavior under transient operating conditions. The results obtained for diesel-fueled light commercial vehicle (LCV) have shown better fuel economy than LPO biofuel with their developed fuel injection parameter MAP. The maximum BTE obtained was 29.7% for diesel and 29.5% for LPO at 2100 rpm and 20 Nm torque. The mean HC emissions were identified as 0.02046 g/km for diesel and 0.03488 g/km for LPO fuel over the modified Indian driving cycle (MIDC). Except for NOx emission, LPO biofuel exhibited diesel-like performance and emission characteristics under the MIDC.&lt;/div&gt;

The Impacts of Sunlight on the Lichen Scots Pine Forest Community

The habitat of the lichen Scots pine forest is currently one of the communities that requires attention and active protection due to its rapid disappearance. In our study, we identified factors that can be modified to preserve this habitat. The primary focus of our research was on the significance of tree height and sunlight in fostering the development of a lichen-rich layer within the lichen Scots pine forest. Additionally, we investigated the environmental factors influencing the presence of specific species of lichens and bryophytes, including those that form communities and those that displace species characteristic of the lichen Scots pine forest community. Our study was conducted in Bory Tucholskie National Park (N-W Poland) using 20 experimental sites and 248 point-frame plots from spring 2021 to winter 2022. Fieldwork involved species surveys, measurements of photosynthetic activity in lichens and bryophytes, and collection of environmental data. Through parametric testing, modeling, and mapping, our main findings confirmed that light availability, influenced by tree height, is a critical factor in maintaining a well-preserved lichen-rich layer and facilitating habitat reintroduction.

The relationship between manual ability, dystonia and choreoathetosis severity and upper limb movement patterns during reaching and grasping in children and young adults with dyskinetic cerebral palsy

IntroductionImpaired upper limb movements are a key feature in dyskinetic cerebral palsy (CP). However, information on how specific movement patterns relate to manual ability, performance and underlying movement disorders is lacking. Insight in these associations may contribute to targeted upper limb management in dyskinetic CP. This study aimed to explore associations between deviant upper limb movement patterns and (1) manual ability, (2) severity of dystonia/choreoathetosis, and (3) movement time/trajectory deviation during reaching and grasping. Participants/methodsParticipants underwent three-dimensional upper limb analysis during reaching forwards (RF), reaching sideways (RS) and reach-and-grasp vertical (RGV) as well as clinical assessment. Canonical correlation and regression analysis with statistical parametric mapping were used to explore associations between clinical/performance parameters and movement patterns (mean and variability). ResultsThirty individuals with dyskinetic CP participated (mean age 16±5 y; 20 girls). Lower manual ability was related to higher variability in wrist flexion/extension during RF and RS early in the reaching cycle (p < 0.05). Higher dystonia severity was associated with higher mean wrist flexion (40–82 % of the reaching cycle; p = 0.004) and higher variability in wrist flexion/extension (31–75 %; p < 0.001) and deviation (2–14 %; p = 0.007/60–73 %; p = 0.006) during RF. Choreoathetosis severity was associated with higher elbow pro/supination variability (12–19 %; p = 0.009) during RGV. Trajectory deviation was associated with wrist and elbow movement variability (p < 0.05). ConclusionCurrent novel analysis of upper limb movement patterns and respective timings allows to detect joint angles and periods in the movement cycle wherein associations with clinical parameters occur. These associations are not present at each joint level, nor during the full movement cycle. This knowledge should be considered for individualized treatment strategies.

The Significance of Parametric Mapping in Advanced Cardiac Imaging.

Cardiac magnetic resonance imaging has witnessed a transformative shift with the integration of parametric mapping techniques, such as T1 and T2 mapping and extracellular volume fraction. These techniques play a crucial role in advancing our understanding of cardiac function and structure, providing unique insights into myocardial tissue properties. Native T1 mapping is particularly valuable, correlating with histopathological fibrosis and serving as a marker for various cardiac pathologies. Extracellular volume fraction, an early indicator of myocardial remodeling, predicts adverse outcomes in heart failure. Elevated T2 relaxation time in cardiac MRI indicates myocardial edema, enabling noninvasive and early detection in conditions like myocarditis. These techniques offer precise insights into myocardial properties, enhancing the accuracy of diagnosis and prognosis across a spectrum of cardiac conditions, including myocardial infarction, autoimmune diseases, myocarditis, and sarcoidosis. Emphasizing the significance of these techniques in myocardial tissue analysis, the review provides a comprehensive overview of their applications and contributions to our understanding of cardiac diseases.

Tidal turbine hydrofoil design and optimization based on deep learning

The optimal design of hydrofoils is critical to improve the hydrodynamic performance of the tidal turbine. However, the global optimization of hydrofoils is limited by the high dimensionality of the design space, which requires extensive computational fluid dynamics simulations. This paper proposes an interactive framework for hydrofoil design and optimization based on deep learning. Generative adversarial networks are used to parameterize the hydrofoil design, which automatically learns representations from existing hydrofoils and controls new hydrofoil generation using fewer variables to reduce optimization dimensions. Moreover, the surrogate model based on convolutional neural networks is constructed, which realizes the mapping of hydrofoil design and operating parameters to hydrodynamic performance parameters. The framework can generate a large number of smooth and realistic hydrofoils with three design variables and quickly predict the performance, enabling effective optimization design of hydrofoils. The results show that the optimized hydrofoil shapes have larger lift-to-drag ratios than those of the common hydrofoils. Furthermore, the optimized hydrofoil is applied to the design of 3D horizontal axis tidal turbine blades. The simulation results show that the framework is effective and stable, which can facilitate the design of tidal turbine rotors and provide hydrofoils with higher power coefficients.

Conversion map from quantitative parameter mapping to myelin water fraction: comparison with R1·R2* and myelin water fraction in white matter.

To clarify the relationship between myelin water fraction (MWF) and R1⋅R2* and to develop a method to calculate MWF directly from parameters derived from QPM, i.e., MWF converted from QPM (MWFQPM). Subjects were 12 healthy volunteers. On a 3T MR scanner, dataset was acquired using spoiled gradient-echo sequence for QPM. MWF and R1⋅R2* maps were derived from the multi-gradient-echo (mGRE) dataset. Volume-of-interest (VOI) analysis using the JHU-white matter (WM) atlas was performed. All the data in the 48 WM regions measured VOI were plotted, and quadratic polynomial approximations of each region were derived from the relationship between R1·R2* and the two-pool model-MWF. The R1·R2* map was converted to MWFQPM map. MWF atlas template was generated using converted to MWF from R1·R2* per WM region. The mean MWF and R1·R2* values for the 48 WM regions were 11.96 ± 6.63%, and 19.94 ± 4.59s-2, respectively. A non-linear relationship in 48 regions of the WM between MWF and R1·R2* values was observed by quadratic polynomial approximation (R2 ≥ 0.963, P < 0.0001). MWFQPM map improved image quality compared to the mGRE-MWF map. Myelin water atlas template derived from MWFQPM may be generated with combined multiple WM regions.

Efficacy of hinged and carbon fiber ankle-foot orthoses in children with unilateral spastic cerebral palsy and drop-foot gait pattern.

In children with unilateral spastic cerebral palsy (USCP), ankle-foot orthoses (AFOs) are widely used to correct common gait deviations such as a drop-foot pattern. Most studies on this topic have investigated specific time points while omitting other parts of the gait cycle. This study investigated the separate effects of prefabricated carbon fiber AFOs and custom-made hinged AFOs compared with barefoot walking in children with USCP with a drop-foot gait pattern using statistical parametric mapping. Retrospective, cross-sectional, repeated measures study. Twenty ambulatory children (9.9 ± 2.5 years) with USCP and a drop-foot gait pattern were included. Kinematics, kinetics, and spatiotemporal parameters assessed during 3-dimensional gait analysis were compared between barefoot and AFO walking. Statistical parametric mapping was used to compare joint angles and moment waveforms. Kinematics, kinetics and spatiotemporal parameters assessed during 3-dimensional gait analysis were compared between barefoot and AFO walking for each AFO type but not between the 2 AFO types. Compared with barefoot walking, there was a steeper sole angle at initial contact, corresponding to a heel strike pattern, and an increased ankle dorsiflexion in swing with the use of both AFOs. The ankle plantar flexion moment during loading response increased. Ankle power generation during pre-swing decreased in the carbon fiber AFO group when walking with AFOs. Both AFOs were beneficial for improving a drop-foot gait pattern in these small patient groups and can, therefore, be recommended to treat this gait deviation in patients with unilateral cerebral palsy. However, the reduction in ankle power generation during push-off and additional goals targeted by AFOs, such as correction of structural or flexible foot deformities, should be considered for prescription.

Mapping of Forest Structural Parameters in Tianshan Mountain Using Bayesian-Random Forest Model, Synthetic Aperture Radar Sentinel-1A, and Sentinel-2 Imagery

The assessment of forest structural parameters is crucial for understanding carbon storage, habitat suitability, and timber stock. However, the labor-intensive and expensive nature of field measurements, coupled with inadequate sample sizes for large-scale modeling, poses challenges. To address the forest structure parameters in the Western Tianshan Mountains, this study used UAV-LiDAR to gather extensive sample data. This approach was enhanced by integrating Sentinel satellite and topographic data and using a Bayesian-Random Forest model to estimate forest canopy height, average height, density, and aboveground biomass (AGB). Validation against independent LiDAR-derived samples confirmed the model’s high accuracy, with coefficients of determination (R2) and root mean square errors (RMSE) indicating strong predictive performance (R2 = 0.63, RMSE = 5.06 m for canopy height; R2 = 0.64, RMSE = 2.88 m for average height; R2 = 0.68, RMSE = 62.84 for density; and R2 = 0.59, RMSE = 29.71 Mg/ha for AGB). Notably, the crucial factors include DEM, Sentinel-1 (VH and VV backscatter in dB), and Sentinel-2 (B6, B8A, and B11 bands). These factors contribute significantly to the modeling of forest structure. This technology aims to expedite and economize forest surveys while augmenting the range of forest parameters, especially in remote and rugged terrains. Using a wealth of UAV-LiDAR data, this outcome surpasses its counterparts’ by providing essential insights for exploring climate change effects on Central Asian forests, facilitating precise carbon stock quantification, and enhancing knowledge of forest ecosystems.

Quantitative accuracy of lung function measurement using parametric response mapping: A virtual imaging study.

Parametric response mapping (PRM) is a voxel-based quantitative CT imaging biomarker that measures the severity of chronic obstructive pulmonary disease (COPD) by analyzing both inspiratory and expiratory CT scans. Although PRM-derived measurements have been shown to predict disease severity and phenotyping, their quantitative accuracy is impacted by the variability of scanner settings and patient conditions. The aim of this study was to evaluate the variability of PRM-based measurements due to the changes in the scanner types and configurations. We developed 10 human chest models with emphysema and air-trapping at end-inspiration and end-expiration states. These models were virtually imaged using a scanner-specific CT simulator (DukeSim) to create CT images at different acquisition settings for energy-integrating and photon-counting CT systems. The CT images were used to estimate PRM maps. The quantified measurements were compared with ground truth values to evaluate the deviations in the measurements. Results showed that PRM measurements varied with scanner type and configurations. The emphysema volume was overestimated by 3 ± 9.5 % (mean ± standard deviation) of the lung volume, and the functional small airway disease (fSAD) volume was underestimated by 7.5±19 % of the lung volume. PRM measurements were more accurate and precise when the acquired settings were photon-counting CT, higher dose, smoother kernel, and larger pixel size. This study demonstrates the development and utility of virtual imaging tools for systematic assessment of a quantitative biomarker accuracy.

Brain 18 F-FDG PET reveals cortico-subcortical hypermetabolic dysfunction in juvenile neuropsychiatric systemic lupus erythematosus

BackgroundIn juvenile systemic lupus erythematosus (j-SLE) with neuropsychiatric (NP) symptoms, there is a lack of diagnostic biomarkers. Thus, we study whether PET-FDG may identify any metabolic dysfunction in j-NPSLE.MethodsA total of 19 18FDG-PET exams were consecutively performed using PET-MRI system in 11 non-sedated patients presenting with j-NPSLE (11-18y) for less than 18 months (m) and without any significant lesion at MRI. Psychiatric symptoms were scored from 0 (none) to 3 (severe) at PET time. PET images were visually analyzed and voxel-based analyses of cerebral glucose metabolism were performed using statistical parametric mapping (spm) with an age-matched control group, at threshold set > 50 voxels using both p < 0.001 uncorrected (unc.) and p < 0.05 corrected family wise error (FWE).ResultsPatients exhibited mainly psychiatric symptoms, with diffuse inflammatory j-NPSLE. First PET (n = 11) was performed at a mean of 15y of age, second/third PET (n = 7/n = 1) 6 to 19 m later. PET individual analysis detected focal bilateral anomalies in 13/19 exams visually but 19/19 using spm (unc.), mostly hypermetabolic areas (18/19). A total of 15% of hypermetabolic areas identified by spm had been missed visually. PET group analysis (n = 19) did not identify any hypometabolic area, but a large bilateral cortico-subcortical hypermetabolic pattern including, by statistical decreasing order (unc.), thalamus, subthalamic brainstem, cerebellum (vermis and cortex), basal ganglia, visual, temporal and frontal cortices. Mostly the subcortical hypermetabolism survived to FWE analysis, being most intense and extensive (51% of total volume) in thalamus and subthalamus brainstem. Hypermetabolism was strictly subcortical in the most severe NP subgroup (n = 8, scores 2–3) whereas it also extended to cerebral cortex, mostly visual, in the less severe subgroup (n = 11, scores 0–1), but difference was not significant. Longitudinal visual analysis was inconclusive due to clinical heterogeneity.Conclusionsj-NPSLE patients showed a robust bilateral cortico-subcortical hypermetabolic network, focused subcortically, particularly in thalamus, proportionally to psychiatric features severity. Further studies with larger, but homogeneous, cohorts are needed to determine the sensitivity and specificity of this dysfunctional pattern as a potential biomarker in diffuse inflammatory j-NPSLE with normal brain MRI.

Innovative Design and Development of Personalized Ankle-Foot Orthoses for Survivors of Stroke With Equinovarus Foot: Protocol for a Feasibility and Comparative Trial.

Ankle-foot orthoses (AFOs) are vital in gait rehabilitation for patients with stroke. However, many conventional AFO designs may not offer the required precision for optimized patient outcomes. With the advent of 3D scanning and printing technology, there is potential for more individualized AFO solutions, aiming to enhance the rehabilitative process. This nonrandomized trial seeks to introduce and validate a novel system for AFO design tailored to patients with stroke. By leveraging the capabilities of 3D scanning and bespoke software solutions, the aim is to produce orthoses that might surpass conventional designs in terms of biomechanical effectiveness and patient satisfaction. A distinctive 3D scanner, complemented by specialized software, will be developed to accurately capture the biomechanical data of leg movements during gait in patients with stroke. The acquired data will subsequently guide the creation of patient-specific AFO designs. These personalized orthoses will be provided to participants, and their efficacy will be compared with traditional AFO models. The qualitative dimensions of this experience will be evaluated using the Quebec User Evaluation of Satisfaction With Assistive Technology (QUEST) assessment tool. Feedback from health care professionals and the participants will be considered throughout the trial to ensure a rounded understanding of the system's implications. Spatial-temporal parameters will be statistically compared using paired t tests to determine significant differences between walking with the personalized orthosis, the existing orthosis, and barefoot conditions. Significant differences will be identified based on P values, with P<.05 indicating statistical significance. The Statistical Parametric Mapping method will be applied to graphically compare kinematic and kinetic data across the entire gait cycle. QUEST responses will undergo statistical analysis to evaluate patient satisfaction, with scores ranging from 1 (not satisfied) to 5 (very satisfied). Satisfaction scores will be presented as mean and SD values. Significant variations in satisfaction levels between the personalized and existing orthosis will be assessed using a Wilcoxon signed rank test. The anticipation is that the AFOs crafted through this innovative system will either match or outperform existing orthoses in use, with higher patient satisfaction rates. Embracing the synergy of technology and biomechanics may hold the key to revolutionizing orthotic design, with the potential to set new standards in patient-centered orthotic solutions. However, as with all innovations, a balanced approach, considering both the technological possibilities and individual patient needs, will be paramount to achieving optimal outcomes. PRR1-10.2196/52365.

Relaxation Along a Fictitious Field, continuous wave T1rho, adiabatic T1rho and adiabatic T2rho imaging of human gliomas at 3T: A feasibility study.

In pre-clinical models of brain gliomas, Relaxation Along a Fictitious Field in second rotating frame (TRAFF2), continues wave T1rho (T1ρcw), adiabatic T1rho (T1ρadiab), and adiabatic T2rho (T2ρadiab) relaxation time mappings have demonstrated potential to non-invasively characterize brain gliomas. Our aim was to evaluate the feasibility and potential of 4 different spin lock methods at 3T to characterize primary brain glioma. 22 patients (26-72 years) with suspected primary glioma. T1ρcw was performed using pulse peak amplitude of 500Hz and pulse train durations of 40 and 80 ms while the corresponding values for T1ρadiab, T2ρadiab, TRAFF2 were 500/500/500Hz and 48 and 96, 64 and 112, 45 and 90 ms, respectively. The parametric maps were calculated using a monoexponential model. Molecular profiles were evaluated from tissue specimens obtained during the resection. The lesion regions-of-interest were segmented from high intensity FLAIR using automatic segmentation with manual refinement. Statistical descriptors from the voxel intensity values inside each lesion and radiomic features (Pyrad MRC package) were calculated. From extracted radiomics, mRMRe R package version 2.1.0 was used to select 3 features in each modality for statistical comparisons. Of the 22 patients, 10 were found to have IDH-mutant gliomas and of those 5 patients had 1p/19q codeletion group comparisons. Following correction for effects of age and gender, at least one statistical descriptor was able to differentiate between IDH and 1p/19q codeletion status for all the parametric maps. In the radiomic analysis, corner-edge detector features with Harris-Stephens filtered signal showed significant group differences in IDH and 1p/19q codeletion groups. Spin lock imaging at 3T of human glioma was feasible and various qualitative parameters derived from the parametric maps were found to have potential to differentiate IDH and 1p19q codeletion status. Future larger prospective clinical trials are warranted to evaluate these methods further.

Biceps femoris long head muscle and aponeurosis geometry in males with and without a history of hamstring strain injury.

Hamstring strain injuries (HSIs) commonly affect the proximal biceps femoris long head (BFlh) musculotendinous junction. Biomechanical modeling suggests narrow proximal BFlh aponeuroses and large muscle-to-aponeurosis width ratios increase localized tissue strains and presumably risk of HSI. This study aimed to determine if BFlh muscle and proximal aponeurosis geometry differed between limbs with and without a history of HSI. Twenty-six recreationally active males with (n = 13) and without (n = 13) a history of unilateral HSI in the last 24 months underwent magnetic resonance imaging of both thighs. BFlh muscle and proximal aponeurosis cross-sectional areas, length, volume, and interface area between muscle and aponeurosis were extracted. Previously injured limbs were compared to uninjured contralateral and control limbs for discrete variables and ratios, and along the relative length of tissues using statistical parametric mapping. Previously injured limbs displayed significantly smaller muscle-to-aponeurosis volume ratios (p = 0.029, Wilcoxon effect size (ES) = 0.43) and larger proximal BFlh aponeurosis volumes (p = 0.019, ES = 0.46) than control limbs with no history of HSI. No significant differences were found between previously injured and uninjured contralateral limbs for any outcome measure (p = 0.216-1.000, ES = 0.01-0.36). Aponeurosis geometry differed between limbs with and without a history of HSI. The significantly larger BFlh proximal aponeuroses and smaller muscle-to-aponeurosis volume ratios in previously injured limbs could alter the strain experienced in muscle adjacent to the musculotendinous junction during active lengthening. Future research is required to determine if geometric differences influence the risk of re-injury and whether they can be altered via targeted training.