Large Voxel Research Articles

Deep learning for high-resolution dose prediction in high dose rate brachytherapy for breast cancer treatment

Objective. Monte Carlo (MC) simulations are the benchmark for accurate radiotherapy dose calculations, notably in patient-specific high dose rate brachytherapy (HDR BT), in cases where considering tissue heterogeneities is critical. However, the lengthy computational time limits the practical application of MC simulations. Prior research used deep learning (DL) for dose prediction as an alternative to MC simulations. While accurate dose predictions akin to MC were attained, graphics processing unit limitations constrained these predictions to large voxels of 3 mm × 3 mm × 3 mm. This study aimed to enable dose predictions as accurate as MC simulations in 1 mm × 1 mm × 1 mm voxels within a clinically acceptable timeframe. Approach. Computed tomography scans of 98 breast cancer patients treated with Iridium-192-based HDR BT were used: 70 for training, 14 for validation, and 14 for testing. A new cropping strategy based on the distance to the seed was devised to reduce the volume size, enabling efficient training of 3D DL models using 1 mm × 1 mm × 1 mm dose grids. Additionally, novel DL architecture with layer-level fusion were proposed to predict MC simulated dose to medium-in-medium (D m,m ). These architectures fuse information from TG-43 dose to water-in-water (D w,w ) with patient tissue composition at the layer-level. Different inputs describing patient body composition were investigated. Main results. The proposed approach demonstrated state-of-the-art performance, on par with the MC D m,m maps, but 300 times faster. The mean absolute percent error for dosimetric indices between the MC and DL-predicted complete treatment plans was 0.17% ± 0.15% for the planning target volume V 100, 0.30% ± 0.32% for the skin D 2cc , 0.82% ± 0.79% for the lung D 2cc , 0.34% ± 0.29% for the chest wall D 2cc and 1.08% ± 0.98% for the heart D 2cc . Significance. Unlike the time-consuming MC simulations, the proposed novel strategy efficiently converts TG-43 D w,w maps into precise D m,m maps at high resolution, enabling clinical integration.

Repeatability of Lac+ measurements in healthy human brain at 3 T.

In vivo quantification of lactate has numerous applications in studying the pathology of both cerebral and musculoskeletal systems. Due to its low concentration (~0.5-1 mM), and overlap with lipid signals, traditional 1H MR spectra acquired in vivo using a small voxel and short echo time often result in an inadequate signal to detect and resolve the lactate peak, especially in healthy human volunteers. In this study, using a semi-LASER acquisition with long echo time (TE= 288 ms) and large voxel size (80 × 70 × 20 mm3), we clearly visualize the combined signal of lactate and threonine. Therefore, we call the signal at 1.33 ppm Lac+ and quantify Lac+ concentration from water suppressed spectra in healthy human brains in vivo. Four participants (22-37 years old; mean age = 28 ± 5.4; three male, one female) were scanned on four separate days, and on each day four measurements were taken. Intra-day values are calculated for each participant by comparing the four measurements on a single day. Inter-day values were calculated using the mean intra-day measurements. The mean intra-participant Lac+ concentration, standard deviation (SD), and coefficient of variation (CV) ranged from 0.49 to 0.61 mM, 0.02 to 0.07 mM, and 4% to 13%, respectively, across four volunteers. The inter-participant Lac+ concentration, SD, and CV was 0.53 mM, ±0.06 mM, and 11%. Repeatability is shown in Lac+ measurement in healthy human brain using a long echo time semi-LASER sequence with a large voxel in about 3.5 min at 3 T.

Effect of MRI acquisition parameters on accuracy and precision of phase-contrast measurements in a small-lumen vessel phantom

BackgroundPhase-contrast magnetic resonance imaging (PC-MRI) quantifies blood flow and velocity noninvasively. Challenges arise in neurovascular disorders due to small vessels. We evaluated the impact of voxel size, number of signal averages (NSA), and velocity encoding (VENC) on PC-MRI measurement accuracy and precision in a small-lumen vessel phantom.MethodsWe constructed an in vitro model with a constant flow rate using a 2.2-mm inner diameter plastic tube. A reservoir with a weight scale and timer was used as standard reference. Gradient-echo T1 weighted PC-MRI sequence was performed on a 3-T scanner with varying voxel size (2.5, 5.0, 7.5 mm3), NSA (1, 2, 3), and VENC (200, 300, 400 cm/s). We repeated measurements nine times per setting, calculating mean flow rate, maximum velocity, and least detectable difference (LDD).ResultsPC-MRI flow measurements were higher than standard reference values (mean ranging from 7.3 to 9.5 mL/s compared with 6.6 mL/s). Decreased voxel size improved accuracy, reducing flow rate measurements from 9.5 to 7.3 mL/s. The LDD for flow rate and velocity varied between 1 and 5%. The LDD for flow rate decreased with increased voxel size and NSA (p = 0.033 and 0.042). The LDD for velocity decreased with increased voxel size (p < 10-16). No change was observed when VENC varied.ConclusionsPC-MRI overestimated flow. However, it has high precision in a small-vessel phantom with constant flow rate. Improved accuracy was obtained with increasing spatial resolution (smaller voxels). Improved precision was obtained with increasing signal-to-noise ratio (larger voxels and/or higher NSA).Relevance statementPhase-contrast MRI is clinically used in large vessels. To further investigate the possibility of using phase-contrast MRI for smaller intracranial vessels in neurovascular disorders, we need to understand how acquisition parameters affect phase-contrast MRI-measured flow rate and velocity in small vessels.Key points• PC-MRI measures flow and velocity in a small lumen phantom with high precision but overestimates flow rate.• The precision of PC-MRI measurements matches the precision of standard reference for flow rate measurements.• Optimizing PC-MRI settings can enhance accuracy and precision in flow rate and velocity measurements.Graphical

Predicted effects of image acquisition and analysis conditions on DTMRI tractography-based muscle architecture estimates.

To quantify the effects of the intrinsic signal pattern, image acquisition conditions, and data analysis conditions on diffusion-tensor MRI (DTMRI) tractography-based muscle architecture estimates using a sampling-reconstruction assessment framework. Numerical models of muscles were constructed with realistic architectural properties. DTMRI signals were computed at signal-to-noise ratio (SNR) of 24-96 and common voxel sizes. Fiber tracking was performed, and the results were compared with the known architectural properties. SNR exerted the most significant impact on the outcome. The outcome variables approached asymptotes at SNR ≈ 54. Large in-plane voxel dimensions reduced the similarity between reconstructed fibers and the known architectural properties. Higher order polynomials helped reconstruct fibers with more complicated geometry but overfit noise for less complex geometries. The intrinsic fiber curvature also affected the robustness of polynomial smoothing to SNR. Other conditions, such as the fiber dimensionality, voxel aspect ratio, and slice thickness, did not affect the outcomes. SNR ≥ 54 is recommended for accurate muscle architecture characterization using DTMRI. Averaged across all simulated conditions, the greatest percent errors under SNR = 54 were -5.6% and -4.0% for the pennation angle and fiber-tract length estimates, respectively. For fiber tracts with intermediate intrinsic curvature, the greatest percent error for the curvature estimate was 9.8% for SNR = 54. Smaller in-plane voxel size (≤1.5 mm) is preferred to minimize the estimation error in architectural properties. If necessary, slice thickness may be adjusted within typical ranges to achieve sufficient SNR when slices are aligned near the fiber direction. Third-order polynomial fitting is appropriate for smoothing fiber tracts.

Numerical investigation reveals challenges in measuring the contrast recovery coefficients in PET

Objective. Contrast recovery coefficient (CRC) is essential for image quality (IQ) assessment in positron emission tomography (PET), typically measured according to the National Electrical Manufacturers Association (NEMA) NU 2 standard. This study quantifies systematic uncertainties of the CRC measurement by a numerical investigation of the effects from scanner-independent parameters like voxel size, region-of-interest (ROI) misplacement, and sphere position on the underlying image grid. Approach. CRC measurements with 2D and 3D ROIs were performed on computer-generated images of a NEMA IQ-like phantom, using voxel sizes of 1–4 mm for sphere diameters of 5–40 mm—first in absence of noise and blurring, then with simulated spatial resolution and image noise with varying noise levels. The systematic uncertainties of the CRC measurement were quantified from above variations of scanner-independent parameters. Subsampled experimental images of a NEMA IQ phantom were additionally used to investigate the impact of ROI misplacement at different noise levels. Main results. In absence of noise and blurring, systematic uncertainties were up to 28.8% and 31.0% with 2D and 3D ROIs, respectively, for the 10 mm sphere, with the highest impact from ROI misplacement. In all cases, smaller spheres showed higher uncertainties with larger voxels. Contrary to prior assumptions, the use of 3D ROIs did not exhibit less susceptibility for parameter changes. Experimental and computer-generated images both demonstrated considerable variations on individual CRC measurements when background coefficient-of-variation exceeded 20%, despite negligible effects on mean CRC. Significance. This study underscores the effect of scanner-independent parameters on reliability, reproducibility, and comparability of CRC measurements. Our findings highlight the trade-off between the benefits of smaller voxel sizes and noise-induced CRC fluctuations, which is not considered in the current version of the NEMA IQ standards. The results furthermore warrant adjustments to the standard to accommodate the advances in sensitivity and spatial resolution of current-generation PET scanners.

Analysis of very large voxel datasets

Analysis of very large voxel datasets

Efficiency enhancements of a Monte Carlo beamlet based treatment planning process: implementation and parameter study

Objective. The computational effort to perform beamlet calculation, plan optimization and final dose calculation of a treatment planning process (TPP) generating intensity modulated treatment plans is enormous, especially if Monte Carlo (MC) simulations are used for dose calculation. The goal of this work is to improve the computational efficiency of a fully MC based TPP for static and dynamic photon, electron and mixed photon-electron treatment techniques by implementing multiple methods and studying the influence of their parameters. Approach. A framework is implemented calculating MC beamlets efficiently in parallel on each available CPU core. The user can specify the desired statistical uncertainty of the beamlets, a fractional sparse dose threshold to save beamlets in a sparse format and minimal distances to the PTV surface from which 2 × 2 × 2 = 8 (medium) or even 4 × 4 × 4 = 64 (large) voxels are merged. The compromise between final plan quality and computational efficiency of beamlet calculation and optimization is studied for several parameter values to find a reasonable trade-off. For this purpose, four clinical and one academic case are considered with different treatment techniques. Main results. Setting the statistical uncertainty to 5% (photon beamlets) and 15% (electron beamlets), the fractional sparse dose threshold relative to the maximal beamlet dose to 0.1% and minimal distances for medium and large voxels to the PTV to 1 cm and 2 cm, respectively, does not lead to substantial degradation in final plan quality compared to using 2.5% (photon beamlets) and 5% (electron beamlets) statistical uncertainty and no sparse format nor voxel merging. Only OAR sparing is slightly degraded. Furthermore, computation times are reduced by about 58% (photon beamlets), 88% (electron beamlets) and 96% (optimization). Significance. Several methods are implemented improving computational efficiency of beamlet calculation and plan optimization of a fully MC based TPP without substantial degradation in final plan quality.

Consistency of frontal cortex metabolites quantified by magnetic resonance spectroscopy within overlapping small and large voxels

Single voxel magnetic resonance spectroscopy (MRS) quantifies metabolites within a specified volume of interest. MRS voxels are constrained to rectangular prism shapes. Therefore, they must define a small voxel contained within the anatomy of interest or include not of interest neighbouring tissue. When studying cortical regions without clearly demarcated boundaries, e.g. the dorsolateral prefrontal cortex (DLPFC), it is unclear how representative a larger voxel is of a smaller volume within it. To determine if a large voxel is representative of a small voxel placed within it, this study quantified total N-Acetylaspartate (tNAA), choline, glutamate, Glx (glutamate and glutamine combined), myo-inositol, and creatine in two overlapping MRS voxels in the DLPFC, a large (30×30x30 mm) and small (15×15x15 mm) voxel. Signal-to-noise ratio (SNR) and tissue type factors were specifically investigated. With water-referencing, only myo-inositol was significantly correlated between the two voxels, while all metabolites showed significant correlations with creatine-referencing. SNR had a minimal effect on the correspondence between voxels, while tissue type showed substantial influence. This study demonstrates substantial variability of metabolite estimates within the DLPFC. It suggests that when small anatomical structures are of interest, it may be valuable to spend additional acquisition time to obtain specific, localized data.

Increased brain 1H-MRS glutamate and lactate signals following maximal aerobic capacity exercise in young healthy males: an exploratory study.

Physical exercise involves increased neuronal activity of many brain structures, but 1H-MRS investigations on the effects of human brain glutamate (Glu) concentrations on acute exercise have been sparse. Previous studies consistently found increases in brain lactate (Lac) concentrations following graded exercise up to 85% of the predicted maximal heart rate. However, the reported effects on brain concentrations of glutamine and glutamate were not consistent. This study aimed to determine the effect of acute intense graded maximal exercise on 1H-MRS signals related to concentrations of Glu, glutamate+glutamine (Glx), and Lac. Young adult males were randomly divided into two groups and subjected to 1H-MRS when resting (NE) or shortly after cessation of the intense graded exercise intended to pass the anaerobic threshold (E). 1H-MRS spectra were acquired from the large voxel encompassing the occipito-parietal cortex only once. Estimates of Glu, Glx, and Lac concentrations were calculated in institutional units by normalizing to a spectroscopic signal originating from creatine-containing compounds (Cr). Concentrations of Glu, Glx, and Lac were respectively 11%, 12.6%, and 48.5% higher in E than in NE (p < 0.001). The increased brain Lac signal in the exercising group indicated that in our experiment, vigorous exercise resulted in passing the anaerobic threshold and lactate apparently entered the brain. Concomitantly glutamate-related resonance signals from the vicinity of the occipito-parietal cortex were significantly increased; physiological mechanisms underlying these phenomena require further study. Future studies should evaluate whether the normalization rate of these concentrations is a marker of general physical fitness.

Identification of l-Tryptophan by down-field 1 H MRS: A precursor for brain NAD+ and serotonin syntheses.

To explore the presence of new resonances beyond 9.4ppm from the human brain, down-field proton MRS was performed in vivo in the human brain on 6 healthy volunteers at 7 T. To maximize the SNR, a large voxel was placed within the brain to cover the maximal area in such a way that sinus cavities were avoided. A spectrally selective 90° E-BURP pulse with an excitation bandwidth of 2ppm was used to probe the spectral chemical shift range between 9.1 and 10.5ppm. The E-BURP pulse was integrated with PRESS spatial localization to obtain non-water-suppressed proton MR spectra from the desired spectral region. In the down-field proton MRS obtained from all of the volunteers scanned, we identified a new peak consistently resonating at 10.1ppm. Protons associated with this resonance are in cross-relaxation with the bulk water, as demonstrated by the water saturation and deuterium exchange experiments. Based on the chemical shift, this new peak was identified as the indole (-NH) proton of l-tryptophan (l-TRP) and was further confirmed from phantom experiments on l-TRP. These promising preliminary results potentially pave the way to investigate the role of cerebral metabolism of l-TRP in healthy and disease conditions.

Implications of 3D Forest Stand Reconstruction Methods for Radiative Transfer Modeling: A Case Study in the Temperate Deciduous Forest

AbstractThis study investigated the implications of different assumptions of 3D forest stand reconstructions for the accuracy and efficiency of radiative transfer (RT) modeling based on two highly detailed 3D stand representations: 3D‐explicit and voxel‐based. The discrete anisotropic radiative transfer (DART) model was used for RT simulations. The 3D‐explicit and voxel‐based 3D forest scenes were used as structural inputs for the DART model, respectively. Using the 3D‐explicit RT simulation as the benchmark, the accuracy and efficiency of the voxel‐based RT simulation were evaluated under multiple simulation conditions. The results showed that for voxel‐based RT simulations: with voxel sizes 0.1, 1, and 10 m and in blue, green, red, and near‐infrared wavebands, the normalized deviations of simulated directional reflectance exceeded the 5% tolerance limit in 89% viewing directions; with voxel sizes 0.2, 1, and 10 m, the normalized deviations of simulated spectral albedo exceeded the 5% tolerance limit in 90.5% wavelengths; for simulated spectral albedo in blue, green, red, and near‐infrared wavebands and fraction of absorbed photosynthetically active radiation, the normalized deviations exceeded the 5% tolerance limit in 65.3% voxel sizes and spatial resolutions. The two major causes for differences in the 3D‐explicit versus voxel‐based RT simulations were: (a) the difference between light interaction in spatially explicit objects and in turbid medium, and (b) the structural difference of 3D contours between voxel‐based and 3D‐explicit models. However, voxel‐based RT simulations were substantially more computationally efficient than 3D‐explicit RT simulations in large voxel sizes (≥1 m) and coarse spatial resolutions (≥1 m).

Differences in neurometabolites and transcranial magnetic stimulation motor maps in children with attention-deficit/hyperactivity disorder.

Background:Although much is known about cognitive dysfunction in attention-deficit/hyperactivity disorder (ADHD), few studies have examined the pathophysiology of disordered motor circuitry. We explored differences in neurometabolite levels and transcranial magnetic stimulation (TMS)–derived corticomotor representations among children with ADHD and typically developing children.Methods:We used magnetic resonance spectroscopy (MRS) protocols to measure excitatory (glutamate + glutamine [Glx]) and inhibitory (γ-aminobutyric acid [GABA]) neurometabolite levels in the dominant primary motor cortex (M1) and the supplementary motor area (SMA) in children with ADHD and typically developing children. We used robotic neuronavigated TMS to measure corticospinal excitability and create corticomotor maps.Results:We collected data from 26 medication-free children with ADHD (aged 7–16 years) and 25 typically developing children (11–16 years). Children with ADHD had lower M1 Glx (p = 0.044, d = 0.6); their mean resting motor threshold was lower (p = 0.029, d = 0.8); their map area was smaller (p = 0.044, d = 0.7); and their hotspot density was higher (p = 0.008, d = 0.9). M1 GABA levels were associated with motor map area (p = 0.036).Limitations: Some TMS data were lost because the threshold of some children exceeded 100% of the machine output. The relatively large MRS voxel required to obtain sufficient signal-to-noise ratio and reliably measure GABA levels encompassed tissue beyond the M1, making this measure less anatomically specific.Conclusion:The neurochemistry and neurophysiology of key nodes in the motor network may be altered in children with ADHD, and the differences appear to be related to each other. These findings suggest potentially novel neuropharmacological and neuromodulatory targets for ADHD.

Relationship between fine aggregate size and the air void system of six mortars: I. Air void content and diameter distribution

Precisely determining the characteristics of the air void system in cement-based materials is important in material design and freeze-thaw durability evaluation. X-ray computed tomography (XCT) has been used to characterize air void systems, since it is able to measure the 3D spatial arrangement of the voids. Though the factors influencing air void formation and arrangement have been well-studied, the role of fine aggregate size and gradation has mainly been ignored. In this paper, six mortars were prepared with varying sand size distributions and their air void system quantitatively characterized via XCT. The role of sand size distribution and blended proportions were combined via calculation of the fine aggregate specific surface area (SSA). A linear relationship between SSA and global air void volume fraction was observed, with increasing air void volume fraction as SSA increased (and sand size decreased). The 2D circle diameter distribution was derived from 2D analysis of each XCT slice and the 3D sphere diameter distribution was derived from 3D analysis of the stacked 3D XCT microstructure. The distributions for 2D and 3D were calculated from each other using stereological methods and compared with the original experimental results. All three methods used were in reasonable agreement. The air void size distributions obtained via high resolution (small voxel size, small scan volume) and low resolution (large voxel size, large scan volume) XCT scans compared favorably in a compatible air void size range, which illustrates how the problems of differing XCT resolutions can be resolved.

Rat Brain Global Ischemia-Induced Diffusion Changes Revisited: Biophysical Modeling of the Water and NAA MR "Diffusion Signal".

To assess changes in intracellular diffusion as a mechanism for the reduction in water ADC that accompanies brain injury. Using NAA as a marker of neuronal cytoplasmic diffusion, NAA diffusion was measured before and after global ischemia (immediately postmortem) in the female Sprague-Dawley rat. Diffusion-weighted PRESS spectra, with diffusion encoding in a single direction, were acquired from large voxels of rat brain gray matter in vivo and postischemia employing either pairs of pulsed half-sine-shaped gradients (in vivo and postischemia, bmax = 19 ms/μm2 ) or sinusoidal oscillating gradients (in vivo only) with frequencies of 99.2-250 Hz. A 2D randomly oriented cylinder (neurite) model gave estimates of longitudinal and transverse diffusivities (DL and DT , respectively). In this model, DL represents the "free" diffusivity of NAA, whereas DT reflects highly restricted diffusion. Using oscillating gradients, the frequency dependence of DT [DT (ω)] gave estimates of the cylinder (axon/dendrite) radius. A 10% decrease in DL,NAA followed global ischemia, dropping from 0.391 ± 0.012μm2 /ms to 0.350 ± 0.009μm2 /ms. Modeling DT,NAA (ω) provided an estimate of the neurite radius of 1.0± 0.6μm. Whereas the increase in apparent intraneuronal viscosity suggested by changes in DL,NAA may contribute to the overall reduction in water ADC associated with brain injury, it is not sufficient to be the sole explanation. Estimates of neurite radius based on DT (ω) were consistent with literature values.

Quality Control for 4D Flow MR Imaging.

In recent years, 4D flow MRI has become increasingly important in clinical applications for the blood vessels in the whole body, heart, and cerebrospinal fluid. 4D flow MRI has advantages over 2D cine phase-contrast (PC) MRI in that any targeted area of interest can be analyzed post-hoc, but there are some factors to be considered, such as ensuring measurement accuracy, a long imaging time and post-processing complexity, and interobserver variability.Due to the partial volume phenomenon caused by low spatial and temporal resolutions, the accuracy of flow measurement in 4D flow MRI is reduced. For spatial resolution, it is recommended to include at least four voxels in the vessel of interest, and if possible, six voxels. In large vessels such as the aorta, large voxels can be secured and SNR can be maintained, but in small cerebral vessels, SNR is reduced, resulting in reduced accuracy. A temporal resolution of less than 40 ms is recommended. The velocity-to-noise ratio (VNR) of low-velocity blood flow is low, resulting in poor measurement accuracy. The use of dual velocity encoding (VENC) or multi-VENC is recommended to avoid velocity wrap around and to increase VNR. In order to maintain sufficient spatio-temporal resolution, a longer imaging time is required, leading to potential patient movement during examination and a corresponding decrease in measurement accuracy.For the clinical application of new technologies, including various acceleration techniques, in vitro and in vivo accuracy verification based on existing accuracy-validated 2D cine PC MRI and 4D flow MRI, as well as accuracy verification on the conservation of mass' principle, should be performed, and intraobserver repeatability, interobserver reproducibility, and test-retest reproducibility should be checked.

Errors in the Estimation of Leaf Area Density From Aerial LiDAR Data: Influence of Statistical Sampling and Heterogeneity

In this study, several approaches were evaluated for estimation of the 3-D distribution of leaf area from aerial light detection and ranging (LiDAR) data. Two general leaf area density (LAD) inversion methods were evaluated against “synthetic” LiDAR data for a range of grid resolutions and canopy architectures: 1) inversion based on cumulative transmission of LiDAR pulses through the volume of interest (i.e., the cumulative distribution function (CDF) of transmission, or Beer’s law), and 2) inversion based on the probability density function (PDF) of beam propagation distance within the volume of interest (i.e., probability distribution fitting). Results indicated that the Beer’s law-based method consistently outperformed the PDF-based methods. In a homogeneous canopy, the average error in LAD estimation using the Beer’s law approach decreased exponentially as the number of voxel statistical samples <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${N_{v}}$ </tex-math></inline-formula> (i.e., laser pulses reaching the voxel) was increased. The normalized error also decreased exponentially as leaf area index of the voxel LAI <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><i>v</i></sub> increased. Heterogeneity increased the magnitude of errors in LAD inversion, with errors tending to increase as vegetation density increased, but plant spacing had a negligible impact. For sufficiently dense heterogeneous canopies, there was an optimal voxel size that balanced errors due to poor statistical sampling (small voxels) and errors due to crown-scale heterogeneity that violated the turbid medium assumption (large voxels). This optimum, if present, occurred at around <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${N_{v}=40}$ </tex-math></inline-formula> or a voxel width of 2 m regardless of canopy geometry. Sub-crown-scale clumping had a minimal effect on average errors in estimated LAD for the tree geometries explored in this work.

Diagnostic Accuracy of CBCT for the Detection of Accessory Mental Foramina Using Different Devices and Imaging Modalities

This study investigated the diagnostic accuracy of CBCT for detection of accessory mental foramina (AMFs) in dry mandibles using two different devices and three different CBCT imaging modalities. A total of 40 dry mandibles (20 per group) were selected to generate corresponding CBCT images, each with three different CBCT imaging modalities (high, standard, and low doses), using ProMax 3D Mid (Planmeca) and Veraview X800 (J. Morita). The presence, count (n), location, and diameter of the AMFs were measured on both dry mandibles and CBCT scans. The Veraview X800 with different imaging modalities showed the highest accuracy (97.5%), while the ProMax 3D Mid in low-dose imaging modality exhibited the lowest accuracy (93.8%). The most common AMF sites on dry mandibles were anterior-cranial and posterior-cranial, while anterior-cranial was the most frequent on CBCT scans. As for AMF diameter, the mean mesiodistal and vertical diameters on dry mandibles were 1.89 mm and 1.47 mm, respectively, which were greater or equal to the values obtained from CBCT scans. The overall diagnostic accuracy for assessing AMFs exhibited good results, but some caution is warranted when using a low-dose imaging modality with a large voxel size (400 μm).

Topography of hippocampal connectivity with sensorimotor cortex revealed by optimizing smoothing kernel and voxel size.

Studies of the hippocampus use smaller voxel sizes and smoothing kernels than cortical activation studies, typically using a multivoxel seed with specified radius for connectivity analysis. This study identified optimal processing parameters for evaluating hippocampal connectivity with sensorimotor cortex (SMC), comparing effectiveness by varying parameters during both activation and connectivity analysis. Using both 3mm and 4mm isovoxels, smoothing kernels of 0-10mm were evaluated on the amplitude and extent of motor activation and hippocampal connectivity with SMC. Psychophysiological interactions (PPI) identified hippocampal connectivity with SMC during volitional movements, and connectivity effects from multivoxel seeds were compared with alternate methods; a structural seed represented the mean connectivity map from all voxels within a region, whereas a functional seed represented the regional voxel with maximal SMC connectivity. With few exceptions, the same parameters were optimal for activation and connectivity. Larger isovoxels showed larger activation volumes in both SMC and the hippocampus; connectivity volumes from structural seeds were also larger, except from the posterior hippocampus. Regardless of voxel size, the 10mm smoothing kernel generated larger activation and connectivity volumes from structural seeds, as well as larger beta estimates at connectivity maxima; structural seeds also produced larger connectivity volumes than multivoxel seeds. Functional seeds showed lesser effects from voxel size and smoothing kernels. Optimal parameters revealed topography in structural seed connectivity along both the longitudinal axis and mediolateral axis of the hippocampus. These results indicate larger voxels and smoothing kernels can improve sensitivity for detecting both cortical activation and hippocampal connectivity.

Whole-Heart High-Resolution Late Gadolinium Enhancement: Techniques and Clinical Applications.

In cardiovascular magnetic resonance, late gadolinium enhancement (LGE) has become the cornerstone of myocardial tissue characterization. It is widely used in clinical routine to diagnose and characterize the myocardial tissue in a wide range of ischemic and nonischemic cardiomyopathies. The recent growing interest in imaging left atrial fibrosis has led to the development of novel whole‐heart high‐resolution late gadolinium enhancement (HR‐LGE) techniques. Indeed, conventional LGE is acquired in multiple breath‐holds with limited spatial resolution: ~1.4–1.8 mm in plane and 6–8 mm slice thickness, according to the Society for Cardiovascular Magnetic Resonance standardized guidelines. Such large voxel size prevents its use in thin structures such as the atrial or right ventricular walls. Whole‐heart 3D HR‐LGE images are acquired in free breathing to increase the spatial resolution (up to 1.3 × 1.3 × 1.3 mm3) and offer a better detection and depiction of focal atrial fibrosis. The downside of this increased resolution is the extended scan time of around 10 min, which hampers the spread of HR‐LGE in clinical practice. Initially introduced for atrial fibrosis imaging, HR‐LGE interest has evolved to be a tool to detect small scars in the ventricles and guide ablation procedures. Indeed, the detection of scars, nonvisible with conventional LGE, can be crucial in the diagnosis of myocardial infarction with nonobstructed coronary arteries, in the detection of the arrhythmogenic substrate triggering ventricular arrhythmia, and improve the confidence of clinicians in the challenging diagnoses such as the arrhythmogenic right ventricular cardiomyopathy. HR‐LGE also offers a precise visualization of left ventricular scar morphology that is particularly useful in planning ablation procedures and guiding them through the fusion of HR‐LGE images with electroanatomical mapping systems. In this narrative review, we attempt to summarize the technical particularities of whole‐heart HR‐LGE acquisition and provide an overview of its clinical applications with a particular focus on the ventricles.Evidence Level2Technical Efficacy Stage2

Dimensional measurement accuracy of 3-dimensional models from cone beam computed tomography using different voxel sizes

To compare the geometric accuracy and measurement reliability of 3-dimensional (3D) reconstructed models of the mandible created from cone beam computed tomography (CBCT) images obtained with 0.2-mm and 0.4-mm voxel sizes with the reference standard model and compare the accuracy of the CBCT-based models to each other. The reference standard 3D model of a dry human mandible was obtained using a white light scanner. The mandible was scanned with CBCT 10 times at each voxel size. The models created from the CBCT data were compared with the reference standard by using a point-based rigid registration algorithm where the distance differences between the superimposed CBCT models and the reference standard model were recorded. The measurements derived from the 2 CBCT-based scans were also compared. Mean deviations from the reference standard for 0.2-mm and 0.4-mm voxel scans were 0.4342 mm and 0.4580 mm, respectively (P ≥ .16). The CBCT scans with both 0.2-mm and 0.4-mm voxels produced good measurement reliability and did not significantly differ from each other (P ≥ .20). CBCT scans with 0.2-mm and 0.4-mm voxel sizes delivered similarly accurate models. Larger voxels can be used to minimize radiation exposure.