1,720,975 research outputs found
Reliability of quantitative magnetic susceptibility imaging metrics for cerebral cortex and major subcortical structures
No full textBackground and purposeSusceptibility estimates derived from quantitative susceptibility mapping (QSM) images for the cerebral cortex and major subcortical structures are variably reported in brain magnetic resonance imaging (MRI) studies, as average of all (mu all), absolute (mu abs), or positive- (mu p) and negative-only (mu n) susceptibility values using a region of interest (ROI) approach. This pilot study presents a reliability analysis of currently used ROI-QSM metrics and an alternative ROI-based approach to obtain voxel-weighted ROI-QSM metrics (mu wp and mu wn).Background and purposeSusceptibility estimates derived from quantitative susceptibility mapping (QSM) images for the cerebral cortex and major subcortical structures are variably reported in brain magnetic resonance imaging (MRI) studies, as average of all (mu all), absolute (mu abs), or positive- (mu p) and negative-only (mu n) susceptibility values using a region of interest (ROI) approach. This pilot study presents a reliability analysis of currently used ROI-QSM metrics and an alternative ROI-based approach to obtain voxel-weighted ROI-QSM metrics (mu wp and mu wn).MethodsTen healthy subjects underwent repeated (test-retest) 3-dimensional multi-echo gradient-echo (3DMEGE) 3 Tesla MRI measurements. Complex-valued 3DMEGE images were acquired and reconstructed with slice thicknesses of 1 and 2 mm (3DMEGE1, 3DMEGE2) along with 3DT1-weighted isometric (voxel 1 mm3) images for independent registration and ROI segmentation. Agreement, consistency, and reproducibility of ROI-QSM metrics were assessed through Bland-Altman analysis, intraclass correlation coefficient, and interscan and intersubject coefficient of variation (CoV).MethodsTen healthy subjects underwent repeated (test-retest) 3-dimensional multi-echo gradient-echo (3DMEGE) 3 Tesla MRI measurements. Complex-valued 3DMEGE images were acquired and reconstructed with slice thicknesses of 1 and 2 mm (3DMEGE1, 3DMEGE2) along with 3DT1-weighted isometric (voxel 1 mm3) images for independent registration and ROI segmentation. Agreement, consistency, and reproducibility of ROI-QSM metrics were assessed through Bland-Altman analysis, intraclass correlation coefficient, and interscan and intersubject coefficient of variation (CoV).ResultsAll ROI-QSM metrics exhibited good to excellent consistency and test-retest agreement with no proportional bias. Interscan CoV was higher for mu all in comparison to the other metrics where it was below 15%, in both 3DMEGE1 and 3DMEGE2 datasets. Intersubject CoV for mu all and mu abs exceeded 50% in all ROIs.ConclusionsAmong the evaluated ROI-QSM metrics, mu all and mu abs estimates were less reliable, whereas separating positive and negative values (using mu p,mu n,mu wp,mu wn) improved the reproducibility within, and the comparability between, subjects, even when reducing the slice thickness.These preliminary findings may offer valuable insights toward standardizing ROI-QSM metrics across different patient cohorts and imaging settings in future clinical MRI studies
Automated Design of Efficient Supports in FDM 3D Printing of Anatomical Phantoms
No full textRecent improvements in image segmentation techniques enabled the (semi)automatic extraction of biostructures surfaces from 3D medical imaging data. The diffusion of 3D printing technologies promoted their introduction in the medical field, giving rise to several applications, such as the development of 3D-printed anatomical imaging phantoms. These devices provide controlled experimental environments for the improvement of medical imaging techniques, as they mimic the morphological and physiological features of different body parts. However, to obtain a 3D printable model from medical imaging data, different post-processing steps are needed, which require a considerable effort. Supports generation is often a critical task, as it requires to find the minimum amount of support structures necessary to hold a part in place during the printing process. This is particularly difficult for complex anthropomorphic models, for which a high printing level of detail, along with a reasonable number of internal supports, is usually needed. In this paper, an automatic method for the design of efficient support structures is proposed, which is suitable for 3D printing of complex anatomical phantoms, even with non-professional FDM 3D printers. A custom design software was developed, which places paraboloid-shaped shells to support all and only the critical points of the 3D model. This provided different advantages over support generation by means of common slicing software, allowing a reduction of material waste and printing times, along with an easier and faster dissolution of soluble supports for the clean-up of phantoms empty volumes
StepBrain: A 3-Dimensionally Printed Multicompartmental Anthropomorphic Brain Phantom to Simulate PET Activity Distributions
No full textAn innovative multicompartmental anatomic brain phantom (StepBrain) is described to simulate the in vivo tracer uptake of gray matter, white matter, and striatum, overcoming the limitations of currently available phantoms. Methods: StepBrain was created by exploiting the potential of fused deposition modeling 3-dimensional printing to replicate the real anatomy of the brain compartments, as modeled through ad hoc processing of healthy-volunteer MR images. Results: A realistic simulation of 18F-FDG PET brain studies, using target activity to obtain the real concentration ratios, was obtained, and the results of postprocessing with partial-volume effect correction tools developed for human PET studies confirmed the accuracy of these methods in recovering the target activity concentrations. Conclusion: StepBrain compartments (gray matter, white matter, and striatum) can be simultaneously filled, achieving different concentration ratios and allowing the simulation of different (e.g., amyloid, tau, or 6-fluoro-l-dopa) tracer distributions, with a potentially valuable role for multicenter PET harmonization studies
A Combined Use of Radiomics and Connectomics to Classify Sex and Age in Healthy Subjects: The New “Radioconnectomics” Paradigm
No full textA low-cost open-architecture taste delivery system for gustatory fMRI and BCI experiments
No full textBackground: Tasting is a complex process involving chemosensory perception and cognitive evaluation. Different experimental designs and solution delivery approaches may in part explain the variability reported in literature. These technical aspects certainly limit the development of taste-related brain computer interface devices. New Method: We propose a novel modular, scalable and low-cost device for rapid injection of small volumes of taste solutions during fMRI experiments that gathers the possibility to flexibly increase the number of channels, allowing complex multi-dimensional taste experiments. We provide the full description of the hardware and software architecture and illustrate the application of the working prototype in single-subject event-related fMRI experiments by showing the BOLD responses to basic taste qualities and to five intensities of tastes during the course of perception. Results: The device is shown to be effective in activating multiple clusters within the gustatory pathway and a precise time-resolved event-related analysis is shown to be possible by the impulsive nature of the induced perception. Comparison with Existing Method(s): This gustometer represents the first implementation of a low-cost, easily replicable and portable device that is suitable for all kinds of fMRI taste experiments. Its scalability will boost the experimental design of more complex multi-dimensional fMRI studies of the human taste pathway. Conclusions: The gustometer represents a valid open-architecture alternative to other available devices and its spread and development may contribute to an increased standardization of experimental designs in human fMRI studies of taste perception and pave the way to the development of novel taste-related BCIs
A Comparison of Denoising Algorithms for Effective Edge Detection in X-Ray Fluoroscopy
No full textX-ray fluoroscopy provides various diagnosis and is widely used in interventional radiology. However, the low-dose involved in fluoroscopy generates an intense Poisson-distributed quantum noise. Object recognition and tracking help in many fluoroscopic applications. Edge-detection is essential, but common derivative operators require noise suppression to provide reliable results. Moreover, homoscedasticity of noise is generally assumed, but is not the case of fluoroscopic images. However, the Anscombe transform can stabilize the quantum noise variance. This study presents a comparison of two denoising algorithms to evaluate their performance in edge-detection for real fluoroscopic sequences. VBM4D is one of best video-processing method for Additive White Gaussian Noise (AWGN), while Noise Variance Conditioned Average (NVCA) is a recent, real-time, algorithm specifically tailored for fluoroscopy. Some real fluoroscopic sequences screening the motion of lumbar spine were processed. Noise parameters were estimated using image sequences of a static scene: the relationship between the luminance and the noise variance was obtained. Generalised Anscombe transform and its inverse were applied to use the VBM4D algorithm. Edge-detection was performed by means of the Sobel operator. The Anscombe transform resulted able to stabilise the noise variance and consequently allow the use of algorithms designed for AWGN. The results show that both approaches provide effective identification of object contours (i.e. vertebral bodies). Despite of its simplicity the NVCA algorithm shows better performances than VBM4D on delineation of boundaries of examined spine fluoroscopic scenes. Furthermore, the NVCA algorithm can be realized in hardware and can offer real-time fluoroscopic processing
Quantitative performance comparison of derivative operators for intervertebral kinematics analysis
No full textComparison of derivative operators via quantitative performance analysis is rarely addressed in medical imaging. Indeed, the main application of such operators is the extraction of edges and, since there is no unequivocal definition of edges, the common trend is to identify the best performing operator based on a qualitative match between the extracted edges and the fickle human perception of object boundaries. This study presents an objective comparison of four first-order derivative operators through quantitative analysis of results yielded in a specific task, i.e. a spine kinematics application. Such application is based on a template matching method, which estimates common kinematic parameters of intervertebral segments from an X-ray fluoroscopy sequence of spine motion, by operating on the image derivatives of each frame. Therefore, differences in image derivatives, computed via different derivative operators, may lead to differences in estimated parameters of intervertebral kinematics. The comparison presented in this study focused on the trajectory of the instantaneous center of rotation (ICR) of an intervertebral segment, as it is particularly sensitive even to very small differences in displacements and velocities. Therefore, a quantitative analysis of the discrepancies between the ICR trajectories, obtained with each of the four considered derivative operators, was carried out by defining quantitative measures. The results showed detectable differences in the obtained ICR trajectories, thus highlighting the need for quantitative analysis of derivative operator performances in applications aimed at providing quantitative results. However, the significance level of such differences for clinical applications should be further assessed, but, currently, it is not possible, as there is no consensus and sufficient data on kinematic parameters features associated with specific spinal pathologies
A polynomial regression-based approach to estimate relaxation rate maps suitable for multiparametric segmentation of clinical brain MRI studies in multiple sclerosis
No full textRelaxation parameter maps (RPMs) calculated from spin-echo data have provided a basis for the segmentation of normal brain tissues and white matter lesions in multiple sclerosis (MS) MRI studies. However, Conventional Spin-Echo (CSE) sequences, once the core of clinical MRI studies, have been largely replaced by faster ones, which do not allow the calculation a-posteriori of RPMs from clinical studies. Aim of the study was to develop and validate a method to estimate RPMs (pseudo-RPMs) from routine clinical MRI protocols (including 3D-Gradient Echo T1w, FLAIR and fast-T2w sequences), suitable for fully automatic multiparametric segmentation of normal-appearing and pathological brain tissues in MS
Validity of Wearable Inertial Sensors for Gait Analysis: A Systematic Review
Full text linkBackground/Objectives: Gait analysis, traditionally performed with lab-based optical motion capture systems, offers high accuracy but is costly and impractical for real-world use. Wearable technologies, especially inertial measurement units (IMUs), enable portable and accessible assessments outside the lab, though challenges with sensor placement, signal selection, and algorithm design can affect accuracy. This systematic review aims to bridge the benchmarking gap between IMU-based and traditional systems, validating the use of wearable inertial systems for gait analysis. Methods: This review examined English studies between 2012 and 2023, retrieved from the Scopus database, comparing wearable sensors to optical motion capture systems, focusing on IMU body placement, gait parameters, and validation metrics. Exclusion criteria for the search included conference papers, reviews, unavailable papers, studies without wearable inertial sensors for gait analysis, and those not involving agreement studies or optical motion capture systems. Results: From an initial pool of 479 articles, 32 were selected for full-text screening. Among them, the lower body resulted in the most common site for single IMU placement (in 22 studies), while the most frequently used multi-sensor configuration involved IMU positioning on the lower back, shanks, feet, and thighs (10 studies). Regarding gait parameters, 11 studies out of the 32 included studies focused on spatial-temporal parameters, 12 on joint kinematics, 2 on gait events, and the remainder on a combination of parameters. In terms of validation metrics, 24 studies employed correlation coefficients as the primary measure, while 7 studies used a combination of error metrics, correlation coefficients, and Bland–Altman analysis. Validation metrics revealed that IMUs exhibited good to moderate agreement with optical motion capture systems for kinematic measures. In contrast, spatiotemporal parameters demonstrated greater variability, with agreement ranging from moderate to poor. Conclusions: This review highlighted the transformative potential of wearable IMUs in advancing gait analysis beyond the constraints of traditional laboratory-based systems
Quantitative susceptibility mapping for investigating brain iron deposits in amyotrophic lateral sclerosis: correlations with clinical phenotype and disease progression
No full textObjective: Perturbation of iron homeostasis is a potential key mechanism involved in neurodegeneration across many neurological disorders, including amyotrophic lateral sclerosis (ALS). We hypothesized that changes in quantitative susceptibility mapping (QSM) could capture perturbations in brain iron concentration in subgroups of ALS patients stratified by clinical phenotype and disease progression. Method: We enrolled 38 ALS patients (23 males–mean age: 58.7 ± 9.8), screened by clinical (ALS functional rating scale-revised, ALSFRS-R) and neuropsychological scales. Patients were a posteriori classified as fast (n = 16) or slow (n = 22) progressors. Two subgroups were also considered: pyramidal (or upper motor neuron+, UMN+) patients (n = 18), and patients with other phenotypes (n = 20). Results: Comparing fast vs. slow progressors, significant differences in iron deposits were observed in the left (p = 0.028) and right amygdala (p = 0.022), and in susceptibility distribution on the right hippocampus (p = 0.0011). Comparing UMN+ vs. other phenotypes, significant susceptibility differences emerged in the left thalamus (p = 0.0014) and right amygdala (p = 0.001). QSM changes were associated with baseline ALSFRS-R (rho = 0.36, p = 0.026) in the left paracentral cortex, and iron concentration with UMN score (rho = 0.35, p = 0.034). Moreover, the Edinburgh Cognitive and Behavioral ALS Screen (ECAS) was associated with iron deposits in the left thalamus (rho=−0.46, p = 0.0041). Conclusions: We confirmed that QSM alterations in extra-motor areas and subcortical regions may be distinctive hallmarks of neurodegeneration in pure/dominant UMN phenotypes of ALS. Moreover, we showed that QSM could be a valuable tool to differentiate patients with different progression rates and phenotypes, suggesting that QSM may support a prognostically useful early stratification of ALS patients
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