Phantom Scans Research Articles

Artifact suppression in readout-segmented consistentK-tspace EPSI (RS-COKE) for fast 1 H spectroscopic imagingat7 T.

Fast proton (1 H) MRSI is an important diagnostic tool for clinical investigations, providing metabolic and spatial information. MRSI at 7T benefits from increased SNR and improved separation of peaks but requires larger spectral widths. RS-COKE (Readout-Segmented Consistent K-t space Epsi) is an echo planar spectroscopic imaging (Epsi) variant capable to support the spectral width required for human brain metabolites spectra at 7T. However, mismatches between readout segments lead to artifacts, particularly when subcutaneous lipid signals are not suppressed. In this study, these mismatches and their effects are analyzed and reduced. The following corrections to the data were performed: i) frequency-dependent phase corrections; ii) k-space trajectory corrections, derived from short reference scans; and iii) smoothing of data at segment transitions to mitigate the effect of residual mismatches. The improvement was evaluated by performing single-slice RS-COKE on a head-shaped phantom with a "lipid" layer and healthy subjects, using varying resolutions and durations ranging from 4.1 × 4.7 × 15 mm3 in 5:46 min to 3.1 × 3.3 × 15 mm3 in 13:07 min. Artifacts arising from the readout-segmented acquisition were substantially reduced, thus providing high-quality spectroscopic imaging in phantom and human scans. LCModel fitting of the human data resulted in a relative Cramer-Rao lower bounds within 6% for NAA, Cr, and Cho images in the majority of the voxels. Using the new reference scans and reconstruction steps, RS-COKE was able to deliver fast 1 H MRSI at 7T, overcoming the spectral width limitation of standard EPSI at this field strength.

A novel dual-energy cone beam computed tomography device for assessment of jaw bone density

<h3>Objective</h3> To evaluate a novel dual-energy cone beam computed tomography (DE-CBCT) device for jaw bone density assessment. <h3>Study Design</h3> An ongoing clinical trial has enrolled 19 subjects with a target enrollment of 24 subjects. All subjects were 21 years and older and required a maxillofacial CT scan for standard-of-care diagnosis. Each subject received 2 examinations: one with a 64-slice multi-detector CT (MDCT) scanner and the second with the experimental DE-CBCT device (RCT720, Ray Co. Seoul, Korea). Asynchronous scanning of a custom hydroxyapatite phantom (concentrations of 0.8, 1.0 and 1.2 g/cc) provided calibration for bone density measurement. DICOM data from both CT examinations were imported into a custom version of OnDemand software<i>.</i> Calibration curves were generated from the MDCT and DE-CBCT scans of the hydroxyapatite phantoms. The MDCT and DE-CBCT scans of study subjects were superimposed and custom tools allowed calculation of bone density within a specified region of interest (ROI). Concordance between the MDCT- and DE-CBCT-derived bone densities was examined. <h3>Results</h3> In our preliminary assessments of data from current subjects, the mean calculated bone density in all the ROIs measured was 0.51 ± 0.27 g/cc for MDCT imaging and 0.50 ± 0.32 for DE-CBCT imaging. The range of the calculated bone densities was 0.06 to 1.1 g/cc for MDCT and 0.04 to 1.3 g/cc for DE-CBCT. Overall, there was strong correlation between bone densities calculated from MDCT scans with those calculated from DE-CBCT scans (r = 0.96, p <0.0001). Bland-Altman analysis identified a bias of 0.01 ± 0.1, and 95% limits of agreement range was -0.19 to 0.21. <h3>Conclusion</h3> The RCT720, a newly-developed DE-CBCT device, produced measurement of bone density equivalent to MDCT and overcomes the inaccuracies of bone density assessment using conventional CBCT scans. <b>Statement of Ethical Review</b> Human/Animal subjects were used and this study was approved by an institutional ethics panel

Global multi-center and multi-modal magnetic resonance imaging study of obsessive-compulsive disorder: Harmonization and monitoring of protocols in healthy volunteers and phantoms.

We describe the harmonized MRI acquisition and quality assessment of an ongoing global OCD study, with the aim to translate representative, well-powered neuroimaging findings in neuropsychiatric research to worldwide populations. We report on T1-weighted structural MRI, resting-state functional MRI, and multi-shell diffusion-weighted imaging of 140 healthy participants (28 per site), two traveling controls, and regular phantom scans. Human image quality measures (IQMs) and outcome measures showed smaller within-site variation than between-site variation. Outcome measures were less variable than IQMs, especially for the traveling controls. Phantom IQMs were stable regarding geometry, SNR, and mean diffusivity, while fMRI fluctuation was more variable between sites. Variation in IQMs persists, even for an a priori harmonized data acquisition protocol, but after pre-processing they have less of an impact on the outcome measures. Continuous monitoring IQMs per site is valuable to detect potential artifacts and outliers. The inclusion of both cases and healthy participants at each site remains mandatory.

Mapping of magnetic resonance imaging's transverse relaxation time at low signal-to-noise ratio using Bloch simulations and principal component analysis image denoising.

High-resolution mapping of magnetic resonance imaging (MRI)'s transverse relaxation time (T2 ) can benefit many clinical applications by offering improved anatomic details, enhancing the ability to probe tissues' microarchitecture, and facilitating the identification of early pathology. Increasing spatial resolutions, however, decreases data's signal-to-noise ratio (SNR), particularly at clinical scan times. This impairs imaging quality, and the accuracy of subsequent radiological interpretation. Recently, principal component analysis (PCA) was employed for denoising diffusion-weighted MR images and was shown to be effective for improving parameter estimation in multiexponential relaxometry. This study combines the Marchenko-Pastur PCA (MP-PCA) signal model with the echo modulation curve (EMC) algorithm for denoising multiecho spin-echo (MESE) MRI data and improving the precision of EMC-generated single T2 relaxation maps. The denoising technique was validated on simulations, phantom scans, and in vivo brain and knee data. MESE scans were performed on a 3-T Siemens scanner. The acquired images were denoised using the MP-PCA algorithm and were then provided as input for the EMC T2 -fitting algorithm. Quantitative analysis of the denoising quality included comparing the standard deviation and coefficient of variation of T2 values, along with gold standard SNR estimation of the phantom scans. The presented denoising technique shows an increase in T2 maps' precision and SNR, while successfully preserving the morphological features of the tissue. Employing MP-PCA denoising as a preprocessing step decreases the noise-related variability of T2 maps produced by the EMC algorithm and thus increases their precision. The proposed method can be useful for a wide range of clinical applications by facilitating earlier detection of pathologies and improving the accuracy of patients' follow-up.

Nonlinearly scaled prior image-controlled frequency split for high-frequency metal artifact reduction in computed tomography.

This paper introduces a new approach for the dedicated reduction of high-frequency metal artifacts, which applies a nonlinear scaling (NLS) transfer function on the high-frequency projection domain to reduce artifacts, while preserving edge information and anatomic detail by incorporating prior image information. An NLS function is applied to suppress high-frequency streak artifacts, but to restrict the correction to metal projections only, scaling is performed in the sinogram domain. Anatomic information should be preserved and is excluded from scaling by incorporating a prior image from tissue classification. The corrected high-frequency sinogram is reconstructed and combined with the low-frequency component of a normalized metal artifact reduction (NMAR) image. Scans of different anthropomorphic phantoms were acquired (unilateral hip, bilateral hip, dental implants, and embolization coil). Multiple regions of interest (ROIs) were drawn around the metal implants and hounsfield unit (HU) deviations were analyzed. Clinical data sets including single image slices of dental fillings, a bilateral hip implant, spinal fixation screws, and an aneurysm coil were reconstructed and assessed. The prior image-controlled NLS can remove streak artifacts while preserving anatomic detail within the bone and soft tissue. The qualitative analysis of clinical cases showed a tremendous enhancement within dental fillings and neuro coils, and a significant enhancement within spinal screws or hip implants. The phantom scan measurements support this observation. In all phantom setups, the NLS-corrected result showed lowest HU derivation and the best visualization of thedata. The prior image-controlled NLS provides a method to reduce high-frequency streaks in metal-corrupted computed tomography (CT)data.

Valuasi Nilai Noise dan Uniformity Citra CT Scan Sebelum dan Setelah Kalibrasi Harian

Computed Tomography (CT) imaging technique is digital imaging that requires the optimal performance of the CT system to produce good image quality so that radiologists can interpret images appropriately and diagnoses can be accurate. The frequency of use of CT equipment will affect the system's accuracy during the image formation process. To ensure optimal performance of the CT scan system, it is necessary to perform routine quality assurance procedures called quality control (QC). Daily calibration is one of the QC actions needed to ensure that the parameters on the CT Scan system function according to specifications. The benefit of QC is to anticipate the malfunction of CT as early as possible so that can do that system maintenance and repairs immediately to meet operational tolerance limits and maintain optimal CT image quality. This study aims to determine the effect of daily calibration on noise and uniformity of CT images to ensure optimal image quality. Phantom scans are performed before and after calibration of CT Scans with Head and Abdomen protocols. The noise is obtained from the measurement of Standard Deviation (SD) in the central area of the phantom image, while the uniformity value of the CT number is obtained from calculating the mean difference in the central area of the phantom image with the average mean in the 12 o'clock area, 3, 6, and 9. Decreased SD value after calibration; in the Head protocol, there is a decrease of 0.01 HU. In the Abdominal protocol, there is a decrease of 0.81 HU. A reduction in the value of SD after calibration indicates a decrease in CT image noise, which means better image quality after calibration. In the uniformity value of CT number, scanning with the Head and Abdomen protocols after calibration decreased by 0.258 HU and 1.56 HU, and still, within the tolerance limit of the CT system, this shows calibration can improve image quality. Keywords: Calibration, Quality Control, Noise, Uniformity

Correction of Bowtie filter induced scatter signals based on air scan data and object scan data

In a cone beam CT system, a bowtie filter brings in additional scatter signals with respect to object induced scatter signals, which can degrade image quality and sometimes result in artifacts. This work aims to improve the image quality of CT scans by analyzing the contribution of bowtie filter induced scatter signals and removing them from projection data. Air calibration is a very useful preprocessing step to eliminate the response variations of detector pixels. Bowtie filter induced scattered x-ray signals of air scans are recorded in air calibration tables and therefore considered as a part of primary signals. However, scattered X-rays behave differently in scanned objects compared to primary x-rays. The difference should be corrected to eliminate the impact of bowtie filter induced scatter signals. A kernel based correction algorithm based on air scan data, named bowtie filter scatter correction algorithm, is applied to estimate and to eliminate the bowtie filter induced scatter signals in object scans. The scatter signals of air scans can be measured with air scans or retrieved from air calibration tables of a CT system, and can be used as input of the correction algorithm to estimate the change of scatter signals caused by the scanned objects in the scan field. Based on the assumption that the scatter signals in the projection data scanned with narrow collimation can be neglected, the difference signals between narrow and broad collimations can be used to estimate bowtie filter induced scatter signals for air scans with the correction of extra-focal radiations (EFRs). The calculated bowtie filter induced scatter signals have been compared with the results of Monte Carlo simulations, and the parameters of correction algorithm have been determined by fitting the measured scatter signal curves of phantom scans with calculated curves. Projection data have been reconstructed using Filtered BackProjection (FBP) method with and without bowtie filter correction to check whether the image quality is improved. Scatter signals can be well approximated with the bowtie filter scatter correction algorithm together with an existing object scatter correction algorithm. After removing the bowtie filter induced scatter signals, the dark bands in reconstructed images in the regions near the edges of scanned objects can be mostly eliminated. The difference signals of air scan data between narrow and broad collimations can be used to estimate the bowtie filter induced scatter for air scans. The proposed bowtie filter scatter correction algorithm using air scan data can be applied to estimate and to remove most of the bowtie filter induced scatter signals in object scans.

Increased brain volumetric measurement precision from multi-site 3D T1-weighted 3 T magnetic resonance imaging by correcting geometric distortions

PurposeMagnetic resonance imaging (MRI) scanner-specific geometric distortions may contribute to scanner induced variability and decrease volumetric measurement precision for multi-site studies. The purpose of this study was to determine whether geometric distortion correction increases the precision of brain volumetric measurements in a multi-site multi-scanner study. MethodsGeometric distortion variation was quantified over a one-year period at 10 sites using the distortion fields estimated from monthly 3D T1-weighted MRI geometrical phantom scans. The variability of volume and distance measurements were quantified using synthetic volumes and a standard quantitative MRI (qMRI) phantom. The effects of geometric distortion corrections on MRI derived volumetric measurements of the human brain were assessed in two subjects scanned on each of the 10 MRI scanners and in 150 subjects with cerebrovascaular disease (CVD) acquired across imaging sites. ResultsGeometric distortions were found to vary substantially between different MRI scanners but were relatively stable on each scanner over a one-year interval. Geometric distortions varied spatially, increasing in severity with distance from the magnet isocenter. In measurements made with the qMRI phantom, the geometric distortion correction decreased the standard deviation of volumetric assessments by 35% and distance measurements by 42%. The average coefficient of variance decreased by 16% in gray matter and white matter volume estimates in the two subjects scanned on the 10 MRI scanners. ConclusionGeometric distortion correction using an up-to-date correction field is recommended to increase precision in volumetric measurements made from MRI images.

Cross-calibration journal of same make and model (Hologic Horizon Wi) installed on Mobile container in different scanner environment

Purpose: ISCD Official positions (2019) has provided appropriate guidance to multiple DXA scanner institutions wishing to offer patients flexibility and convenience, and clearly define good clinical practice requirements to attain it. NHG Diagnostics has launched the project for our DXA machine installed on mobile containers to ensure that our results are comparable with the cross-calibration assessment methodology as described by ISCD Official position (2019). Methods: Atop from the methodology described by ISCD's Official Position, the possible variations within the scanner's environment installed within the mobile container and the choice of tool used for the assessment will be explored (Stage 1: Pretest) & the assessment journal (Stage 2: Cross-calibration journal). Hologic Horizon Wi DXA Machine (S/N 301900M) is identified to be the index scanner, and Hologic Horizon Wi DXA Machine (S/N 304277M) is identified to be the additional scanner during the test. Stage 1: As NHGD has the existing DXA Machine installed within a mobile container with UPS running while tapping on various power source, we have reviewed our QC plots for 6 months (from March 2021 to Sept 2021). When determining the choice of tool, we have performed 10x phantom scans without repositioning at various deployment locations. The %CV and Percentage difference in mean BMD are calculated. Stage 2: The chosen choice of tool will be scanned once daily throughout 20 different days on two machines, operated by a radiographer who has completed the precision assessment. Due to vast distance between the two machines, we have planned and sourced out for courier in transporting the phantom in a shockproof case from one location to another. Once the scan of the day was completed, the scan will be analyzed and the values will be recorded. At the end of the project, the mean BMD will be calculated and the percentage difference between two machines is required to be within 0.5%. If the mean BMD difference is greater than 0.5%, the machine is required to be recalibrated and Stage 2 will be repeated. Results: Stage 1: Spine Phantom (SN #10122) was chosen to be the choice of tool for the cross-calibration assessment due to its lightweight and lower %CV (%CV: 0.09-0.18%) compared to Spine phantom (SN #13684) (%CV: 0.29-0.47%). The 6-month QC Plot Review indicated that the %CV for individual deployment location and average deployment location are less significant and mostly similar. Hologic Horizon Wi DXA Machine (S/N 304277M) has the highest %CV at 0.35% and averaged 0.32% across different locations. Hologic Horizon Wi DXA Machine (S/N 301900M) has the highest %CV at 0.33% and averaged 0.24% across different locations. Stage 2: At the end of the 20 days’ period, the data points were recorded and tabulated. The mean BMD is observed to be 0.890 g/cm2 and 0.888 g/cm2 respectively on Hologic Horizon Wi (S/N 304277M) and Hologic Horizon Wi (S/N 301900M), with a percentage difference of 0.29%. Conclusion: The above additional scanner (Hologic Horizon Wi (S/N 304277M)) which is of good working order within NHGD is observed to be cross calibrated to the index scanner (Hologic Horizon Wi DXA Machine (S/N 301900M)). The data obtained from both machines can be compared with each other when having multi scan site deployment with convenience.

Evaluation of brass alloy density as tissue equivalence bolus using electron density phantom and optical density method

The brass mesh bolus alloy has been shown to be a promising substitute for tissue-equivalent bolus to increase the surface dose during breast cancer radiotherapy treatment. This study is aimed to evaluate the brass alloy density in order to better understand the brass qualities as a bolus in radiotherapy. The mass density of brass alloy determined in this work are using solid approaches, i) traditional density method, ii) Computed Tomography (CT) number using electron density phantom and CT scan and iii) mean pixel value via ImageJ software. According to ANOVA F (2,6) 2.982, p0.126, there was no statistically significant difference between the groups. As a result, all methods for calculating the density of brass alloy are valid. The X2 test of CT number of brass plug to breast substitute in electron density phantom indicates no association. Density analysis using computed tomography and an electron density phantom, as well as the traditional density method and Image J analysis, were all shown to be acceptable methods for estimating the density of the brass alloy. Considering this, brass alloy can be considered as a potential substitute for tissue-equivalent bolus with further extensive of research in conjunction to CT number.

Ultra-High-Resolution Coronary CT Angiography With Photon-Counting Detector CT: Feasibility and Image Characterization.

The aim of this study was to evaluate the feasibility and quality of ultra-high-resolution coronary computed tomography angiography (CCTA) with dual-source photon-counting detector CT (PCD-CT) in patients with a high coronary calcium load, including an analysis of the optimal reconstruction kernel and matrix size. In this institutional review board-approved study, 20 patients (6 women; mean age, 79 ± 10 years; mean body mass index, 25.6 ± 4.3 kg/m 2 ) undergoing PCD-CCTA in the ultra-high-resolution mode were included. Ultra-high-resolution CCTA was acquired in an electrocardiography-gated dual-source spiral mode at a tube voltage of 120 kV and collimation of 120 × 0.2 mm. The field of view (FOV) and matrix sizes were adjusted to the resolution properties of the individual reconstruction kernels using a FOV of 200 × 200 mm 2 or 150 × 150 mm 2 and a matrix size of 512 × 512 pixels or 1024 × 1024 pixels, respectively. Images were reconstructed using vascular kernels of 8 sharpness levels (Bv40, Bv44, Bv56, Bv60, Bv64, Bv72, Bv80, and Bv89), using quantum iterative reconstruction (QIR) at a strength level of 4, and a slice thickness of 0.2 mm. Images with the Bv40 kernel, QIR at a strength level of 4, and a slice thickness of 0.6 mm served as the reference. Image noise, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), vessel sharpness, and blooming artifacts were quantified. For subjective image quality, 2 blinded readers evaluated image noise and delineation of coronary artery plaques and the adjacent vessel lumen using a 5-point discrete visual scale. A phantom scan served to characterize image noise texture by calculating the noise power spectrum for every reconstruction kernel. Maximum spatial frequency (f peak ) gradually shifted to higher values for reconstructions with the Bv40 to Bv64 kernel (0.15 to 0.56 mm -1 ), but not for reconstructions with the Bv72 to Bv89 kernel. Ultra-high-resolution CCTA was feasible in all patients (median calcium score, 479). In patients, reconstructions with the Bv40 kernel and a slice thickness of 0.6 mm showed largest blooming artifacts (55.2% ± 9.8%) and lowest vessel sharpness (477.1 ± 73.6 ΔHU/mm) while achieving highest SNR (27.4 ± 5.6) and CNR (32.9 ± 6.6) and lowest noise (17.1 ± 2.2 HU). Considering reconstructions with a slice thickness of 0.2 mm, image noise, SNR, CNR, vessel sharpness, and blooming artifacts significantly differed across kernels (all P 's < 0.001). With higher kernel sharpness, SNR and CNR continuously decreased, whereas image noise and vessel sharpness increased, with highest sharpness for the Bv89 kernel (2383.4 ± 787.1 ΔHU/mm). Blooming artifacts continuously decreased for reconstructions with the Bv40 (slice thickness, 0.2 mm; 52.8% ± 9.2%) to the Bv72 kernel (39.7% ± 9.1%). Subjective noise was perceived by both readers in agreement with the objective measurements. Considering delineation of coronary artery plaques and the adjacent vessel lumen, reconstructions with the Bv64 and Bv72 kernel (for both, median score of 5) were favored by the readers providing an excellent anatomic delineation of plaque characteristics and vessel lumen. Ultra-high-resolution CCTA with PCD-CT is feasible and enables the visualization of calcified coronaries with an excellent image quality, high sharpness, and reduced blooming. Coronary plaque characterization and delineation of the adjacent vessel lumen are possible with an optimal quality using Bv64 kernel, a FOV of 200 × 200 mm 2 , and a matrix size of 512 × 512 pixels.

Estimations of the weather effects on brain functions using functional MRI: A cautionary note.

The influences of environmental factors such as weather on the human brain are still largely unknown. A few neuroimaging studies have demonstrated seasonal effects, but were limited by their cross‐sectional design or sample sizes. Most importantly, the stability of the MRI scanner has not been taken into account, which may also be affected by environments. In the current study, we analyzed longitudinal resting‐state functional MRI (fMRI) data from eight individuals, where they were scanned over months to years. We applied machine learning regression to use different resting‐state parameters, including the amplitude of low‐frequency fluctuations (ALFF), regional homogeneity (ReHo), and functional connectivity matrix, to predict different weather and environmental parameters. For careful control, the raw EPI and the anatomical images were also used for predictions. We first found that daylight length and air temperatures could be reliably predicted with cross‐validation using the resting‐state parameters. However, similar prediction accuracies could also be achieved by using one frame of EPI image, and even higher accuracies could be achieved by using the segmented or raw anatomical images. Finally, the signals outside of the brain in the anatomical images and signals in phantom scans could also achieve higher prediction accuracies, suggesting that the predictability may be due to the baseline signals of the MRI scanner. After all, we did not identify detectable influences of weather on brain functions other than the influences on the baseline signals of MRI scanners. The results highlight the difficulty of studying long‐term effects using MRI.

Tracking of rigid head motion during MRI using anEEG system.

PurposeTo demonstrate a novel method for tracking of head movements during MRI using electroencephalography (EEG) hardware for recording signals induced by native imaging gradients.Theory and MethodsGradient switching during simultaneous EEG–fMRI induces distortions in EEG signals, which depend on subject head position and orientation. When EEG electrodes are interconnected with high‐impedance carbon wire loops, the induced voltages are linear combinations of the temporal gradient waveform derivatives. We introduce head tracking based on these signals (CapTrack) involving 3 steps: (1) phantom scanning is used to characterize the target sequence and a fast calibration sequence; (2) a linear relation between changes of induced signals and head pose is established using the calibration sequence; and (3) induced signals recorded during target sequence scanning are used for tracking and retrospective correction of head movement without prolonging the scan time of the target sequence. Performance of CapTrack is compared directly to interleaved navigators.ResultsHead‐pose tracking at 27.5 Hz during echo planar imaging (EPI) was demonstrated with close resemblance to rigid body alignment (mean absolute difference: [0.14 0.38 0.15]‐mm translation, [0.30 0.27 0.22]‐degree rotation). Retrospective correction of 3D gradient‐echo imaging shows an increase of average edge strength of 12%/−0.39% for instructed/uninstructed motion with CapTrack pose estimates, with a tracking interval of 1561 ms and high similarity to interleaved navigator estimates (mean absolute difference: [0.13 0.33 0.12] mm, [0.28 0.15 0.22] degrees).ConclusionMotion can be estimated from recordings of gradient switching with little or no sequence modification, optionally in real time at low computational burden and synchronized to image acquisition, using EEG equipment already found at many research institutions.

Empirical scatter correction: CBCT scatter artifact reduction without prior information.

The image quality of cone beam CT (CBCT) scans severely suffers from scattered radiation if no countermeasures are taken. Scatter artifacts may induce cupping and streak artifacts and lead to a reduced image contrast and wrong CT values of the reconstructed volumes. Established software-based approaches for a correction of scattered radiation typically rely on prior knowledge of the CT system, scan parameters, the scanned object, or all of theaforementioned. This study proposes a simple and effective postprocessing software-based correction method of scatter artifacts in CBCT scans without specific priorknowledge. We propose the empirical scatter correction (ESC), which generates scatter-like basis images from each projection image by convolution operations. A linear combination of these basis images is subtracted from the original projection image. The logarithm is taken and an FDK reconstruction is performed. The coefficients needed for the linear combination are determined automatically by a downhill simplex algorithm such that the resulting reconstructed images show no scatter artifacts. We demonstrate the potential of ESC by correcting simulated volumes with Monte Carlo scatter artifacts, a head phantom scan performed on our table-top CBCT, and a pelvis scan from a Varian Edge CBCTscanner. ESC is able to improve the image quality of CBCT scans, which is shown on the basis of our simulations and on measured data. For a simulated head CT, the CT value difference to the scatter-free reference image was as low as -6 HU after using ESC, whereas the uncorrected data deviated by more than -200 HU from the reference data. Simulations of thorax and abdomen CT scans show that although scatter artifacts are not fully removed, anatomical features which were hard to discover prior to the correction become clearly visible and better segmentable with ESC. Similar results are obtained in the phantom measurement, where a comparison to a slit scan of our head phantom shows only small differences. The CT values in soft tissue are improved in this measurement, as well. In soft tissue areas with severe scatter artifacts, the CT values agree well with those of the slit scan (difference to slit scan: 35HU corrected and -289 HU uncorrected). Scatter artifacts in measured patient data can also be reduced using the proposed ESC. The results are comparable to those achieved with designated correction algorithms installed on the Varian Edge CBCT system. ESC allows to reduce artifacts caused by patient scatter solely based on the projectiondata.

166Holmium\u201399mTechnetium dual-isotope imaging: scatter compensation and automatic healthy-liver segmentation for 166Holmium radioembolization dosimetry

BackgroundPartition modeling allows personalized activity calculation for holmium-166 (166Ho) radioembolization. However, it requires the definition of tumor and non-tumorous liver, by segmentation and registration of a separately acquired CT, which is time-consuming and prone to error. A protocol including 166Ho-scout, for treatment simulation, and technetium-99m (99mTc) stannous phytate for healthy-liver delineation was proposed. This study assessed the accuracy of automatic healthy-liver segmentation using 99mTc images derived from a phantom experiment. In addition, together with data from a patient study, the effect of different 99mTc activities on the 166Ho-scout images was investigated. To reproduce a typical scout procedure, the liver compartment, including two tumors, of an anthropomorphic phantom was filled with 250 MBq of 166Ho-chloride, with a tumor to non-tumorous liver activity concentration ratio of 10. Eight SPECT/CT scans were acquired, with varying levels of 99mTc added to the non-tumorous liver compartment (ranging from 25 to 126 MBq). For comparison, forty-two scans were performed in presence of only 99mTc from 8 to 240 MBq. 99mTc image quality was assessed by cold-sphere (tumor) contrast recovery coefficients. Automatic healthy-liver segmentation, obtained by thresholding 99mTc images, was evaluated by recovered volume and Sørensen–Dice index. The impact of 99mTc on 166Ho images and the role of the downscatter correction were evaluated on phantom scans and twenty-six patients’ scans by considering the reconstructed 166Ho count density in the healthy-liver.ResultsAll 99mTc image reconstructions were found to be independent of the 166Ho activity present during the acquisition. In addition, cold-sphere contrast recovery coefficients were independent of 99mTc activity. The segmented healthy-liver volume was recovered fully, independent of 99mTc activity as well. The reconstructed 166Ho count density was not influenced by 99mTc activity, as long as an adequate downscatter correction was applied.ConclusionThe 99mTc image reconstructions of the phantom scans all performed equally well for the purpose of automatic healthy-liver segmentation, for activities down to 8 MBq. Furthermore, 99mTc could be injected up to at least 126 MBq without compromising 166Ho image quality.Clinical trials The clinical study mentioned is registered with Clinicaltrials.gov (NCT02067988) on February 20, 2014.

Low dose protocol for high resolution CT thorax: influence of matrix size and tube voltage on image quality and radiation dose

Background: High-resolution CT (HRCT) thorax has increase demand due to its advantage in diagnosing chronic respiratory diseases. The feasibility of matrix size with different tube voltage in the HRCT protocol of thorax is unknown. Therefore, this study aimed to compare the effect of matrix sizes and tube voltage on image quality and radiation dose on adult HRCT thorax. Methods: A Phantom experiment was performed, followed by a patient scan. For phantom and patient scan, a total of six protocols with two tube voltage settings, 120 kVp and 100 kVp, with a combination of three matrix sizes, 512, 768, and 1024 were used. In this study, 180 adult patients who had HRCT thorax scan were considered. Dose data was collected, and quantitative image analysis was performed by drawing region of interests on the acquired phantom and patient images. Qualitative image analysis was performed independently by two blinded radiologists. Results: The dose report of the phantom experiment revealed that the 100kVp with selected matrix size delivered 15.64% and 15.62% less radiation dose in terms of volumetric computed tomography dose index (CTDIvol) and dose length product (DLP), respectively, compared to 120kVp settings with selected matrix sizes. Similarly, for the patient population, the CTDIvol and DLP difference noted for 120kVp and 100kVp with different matrix sizes was statistically significant (p&lt;0.001). For quantitative image quality, the difference noted was also statistically significant among two kVp settings. The mean score for subjective image assessment was greater than 4.5 for diagnostic acceptability and streak artefacts. Conclusion: The result suggests that the 100 kVp with 512 X 512 matrix size is preferable in the HRCT Lung to achieve the optimal diagnostic image quality with a reduction of almost 40% of the dose to the patients compared to 120 kVp techniques.

Development of a mobile low-field MRI scanner

Magnetic resonance imaging (MRI) allows important visualization of the brain and central nervous system anatomy and organization. However, unlike electroencephalography (EEG) or functional near infrared spectroscopy, which can be brought to a patient or study participant, MRI remains a hospital or center-based modality. Low magnetic field strength MRI systems, however, offer the potential to extend beyond these traditional hospital and imaging center boundaries. Here we describe the development of a modified cargo van that incorporates a removable low-field permanent magnet MRI system and demonstrate its proof-of-concept. Using phantom scans and in vivo T2-weighted neuroimaging data, we show no significant differences with respect to geometric distortion, signal-to-noise ratio, or tissue segmentation outcomes in data acquired in the mobile system compared to a similar static system in a laboratory setting. These encouraging results show, for the first time, MRI that can be performed at a participant’s home, community center, school, etc. Breaking traditional barriers of access, this mobile approach may enable imaging of patients and participants who have mobility challenges, live long distances from imaging centers, or are otherwise unable to travel to an imaging center or hospital.

3D Image-Guided Robotic System for Bone Fracture Reduction

To overcome possible drawbacks of bone fracture reduction such as risks of malrotation, radiation exposure, as well as laborious traction, image-guided robotic surgery systems have been proposed. However, the use of optical tracking systems (OTS) creates inherent line-of-sight problems that cause frequent interruptions during surgery. We propose an OTS-free image-guided bone fracture reduction system utilizing a Stewart robot platform to solve the problem of conventional OTS-based robotic systems. The system applies inverse kinematics to compute the relative positions between the broken bone fragments. Each fragment is pre-operatively registered in the robotic system with a semi-automatic image-based registration method using an attachable jig designed for the proposed platform. This approach is particularly effective when the image features are not clearly detected in the fluoroscopic images. The accuracy of the proposed system was evaluated via pre- and post-operative computed tomography (CT) scans of femoral phantoms. Ex-vivo experiments were also performed on caprine legs to assess the clinical feasibility. In the phantom and ex-vivo experiments, the mean rotational errors of the reduction were 1.79&#x00B0; and 1.76&#x00B0;, respectively. The mean time for the reduction was approximately 3 min. This letter proposes a new method to compute the relative positions between the bone fragments using inverse kinematics and semi-automatic robot-patient registration without requiring a C-arm and an OTS. The OTS-free robotic surgery system has the potential advantages to enhance the accuracy of fracture reduction and reduce the surgery time and radiation exposure.

CT Reconstruction Kernels and the Effect of Pre- and Post-Processing on the Reproducibility of Handcrafted Radiomic Features.

Handcrafted radiomics features (HRFs) are quantitative features extracted from medical images to decode biological information to improve clinical decision making. Despite the potential of the field, limitations have been identified. The most important identified limitation, currently, is the sensitivity of HRF to variations in image acquisition and reconstruction parameters. In this study, we investigated the use of Reconstruction Kernel Normalization (RKN) and ComBat harmonization to improve the reproducibility of HRFs across scans acquired with different reconstruction kernels. A set of phantom scans (n = 28) acquired on five different scanner models was analyzed. HRFs were extracted from the original scans, and scans were harmonized using the RKN method. ComBat harmonization was applied on both sets of HRFs. The reproducibility of HRFs was assessed using the concordance correlation coefficient. The difference in the number of reproducible HRFs in each scenario was assessed using McNemar’s test. The majority of HRFs were found to be sensitive to variations in the reconstruction kernels, and only six HRFs were found to be robust with respect to variations in reconstruction kernels. The use of RKN resulted in a significant increment in the number of reproducible HRFs in 19 out of the 67 investigated scenarios (28.4%), while the ComBat technique resulted in a significant increment in 36 (53.7%) scenarios. The combination of methods resulted in a significant increment in 53 (79.1%) scenarios compared to the HRFs extracted from original images. Since the benefit of applying the harmonization methods depended on the data being harmonized, reproducibility analysis is recommended before performing radiomics analysis. For future radiomics studies incorporating images acquired with similar image acquisition and reconstruction parameters, except for the reconstruction kernels, we recommend the systematic use of the pre- and post-processing approaches (respectively, RKN and ComBat).

Self-navigated prospective motion correction for 3D-EPI acquisition.

Although 3D EPI is more susceptible to motion artifacts than 2D EPI, it presents some benefits for functional MRI, including the absence of spin-history artifacts, greater potential for parallel imaging acceleration, and better functional sensitivity in high-resolution imaging. Here we present a self-navigated 3D-EPI sequence suitable for prospective motion-corrected functional MRI without additional hardware or pulses. For each volume acquisition, the first 24 of the 52 partitions being acquired are accumulated to a new feedback block that was added to the image reconstruction pipeline. After zero-filling the remaining partitions, the feedback block constructs a volumetric self-navigator (vSNav), co-registers it to the reference vSNav acquired during the first volume acquisition, and sends motion estimates to the sequence. The sequence then updates its FOV and acquires subsequent partitions with the adjusted FOV, until the next update is received. The sequence was validated without and with intentional motion in phantom and in vivo on a 3T Skyra. For phantom scans, the FOV was updated 0.704 s after acquisition of the vSNav partitions, and for in vivo scans after 0.768 s. Both phantom and in vivo data demonstrated stable motion estimates in the absence of motion. For in vivo acquisitions, prospective head-pose estimates using the vSNav's and retrospective estimates with FLIRT (FMRIB's Linear Image Registration Tool) agreed to within 0.23 mm (< 10% of the slice thickness) and 0.14° in all directions. Depending when motion occurs during a volume acquisition, the proposed method fully corrects the FOV and recovers image quality within one volume acquisition.