Small Voxel Research Articles

Rapid submillimeter QSM and R2* mapping using interleaved multishot 3D-EPI at 7 and 3 Tesla.

To explore the high signal-to-noise ratio (SNR) efficiency of interleaved multishot 3D-EPI with standard image reconstruction for fast and robust high-resolution whole-brain quantitative susceptibility (QSM) and mapping at 7 and 3T. Single- and multi-TE segmented 3D-EPI is combined with conventional CAIPIRINHA undersampling for up to 72-fold effective gradient echo (GRE) imaging acceleration. Across multiple averages, scan parameters are varied (e.g., dual-polarity frequency-encoding) to additionally correct for -induced artifacts, geometric distortions and motion retrospectively. A comparison to established GRE protocols is made. Resolutions range from 1.4 mm isotropic (1 multi-TE average in 36 s) up to 0.4 mm isotropic (2 single-TE averages in approximately 6 min) with whole-head coverage. Only 1-4 averages are needed for sufficient SNR with 3D-EPI, depending on resolution and field strength. Fast scanning and small voxels together with retrospective corrections result in substantially reduced image artifacts, which improves susceptibility and mapping. Additionally, much finer details are obtained in susceptibility-weighted image projections through significantly reduced partial voluming. Using interleaved multishot 3D-EPI, single-TE and multi-TE data can readily be acquired 10 times faster than with conventional, accelerated GRE imaging. Even 0.4 mm isotropic whole-head QSM within 6 min becomes feasible at 7T. At 3T, motion-robust 0.8 mm isotropic whole-brain QSM and mapping with no apparent distortion in less than 7 min becomes clinically feasible. Stronger gradient systems may allow for even higher effective acceleration rates through larger EPI factors while maintaining optimal contrast.

A voxel-based 3D indoor model to support 3D pedestrian evacuation simulations

Three-dimensional (3D) indoor models enable realistic simulation of pedestrian evacuations in 3D space. However, existing indoor models do not fully identify navigable spaces located above/below physical components (e.g., chairs, stairs, desks), and the connections between these spaces and their navigable surfaces remain underexplored. These limitations hinder the accurate modelling of 3D pedestrian motions during evacuations. To address the shortcomings, we present novel automatic approaches to create a voxel-based 3D indoor model. First, based on different types of 3D motions, indoor spaces are automatically identified as freely navigable spaces, navigable spaces under conditions and non-navigable spaces. Then, navigable surfaces are identified to simulate moving above/below in 3D space. Vertical links are identified to connect the spaces and surfaces at different heights. A 3D pathfinding approach is subsequently developed to validate the model’s effectiveness. Finally, we evaluate the created model’s accuracy, robustness and efficiency across different voxel sizes. The primary findings are: 1) as voxel size increases, accuracy decreases, robustness changes and efficiency improves; 2) with very small voxel sizes, identification becomes challenging, while larger voxel sizes prevent some spaces and vertical links from being identified; and 3) indoor spaces with complex geometries require more time for identification. Our key contributions are: 1) an approach for automatically identifying indoor spaces for 3D motions; 2) two approaches for automatically identifying navigable surfaces and vertical links; and 3) a 3D pathfinding approach considering distinct 3D motion costs. This work advances 3D modelling to facilitate more realistic evacuation simulations.

Accuracy of measurements on CBCT-generated digital models using different exposure parameters (in vitro study).

Dental imaging comprises a wide range of techniques and modalities, each with different diagnostic features influenced by numerous parameters, all of which contribute to the precision and effectiveness of dental evaluations and treatments. This study examined the dimensional reproducibility of arch measurements from CBCT scans with different voxel sizes and exposure parameters compared to a reference model from Extra-oral scanners (EOS) and how these parameters affected digital matching and diagnostic image quality. A diagnostic observational study of arch dimensions, including inter-canine, inter-premolar, intermolar, arch width and arch length, was conducted on digital models (DMs) created from 65 CBCT scans of a full dentate epoxy maxillary model. The measurements obtained from EOS scans served as the control for the study. Normality was tested with the Shapiro-Wilk test, comparisons used the Kruskal-Wallis test with Bonferroni-adjusted pairwise comparisons for significant results, and data were analysed using IBM SPSS (Version 26.0), with significance set at p < .05. Significant deviations were revealed among study groups, with group I (smallest voxel size) consistently displaying the lowest values, mean (SD) deviation was reported as 0.01 (0.006) and group IV (lowest kV value) exhibiting the highest deviations, mean (SD) deviation of 0.16 (0.17). Combining a small voxel size (0.12 mm) with high milliampere (8 mA) and kilovoltage (90 kV) settings in CBCT ensured detailed anatomical visualization and accurate linear measurements, crucial for precise dental assessments, and emphasizing the necessity for strict control over CBCT parameters in dental applications.

Relative profile measurements in 1.5T MR-linacs: investigation of central axis deviations

Objective. In 1.5 T MR-linacs, the absorbed dose central axis (CAX) deviates from the beam's CAX due to inherent profile asymmetry. In addition, a measured CAX deviation may be biased due to potential lateral (to the beam) effective point of measurement (EPOML) shifts of the detector employed. By investigating CAX deviations, the scope of this study is to determine a set ofEPOMLshifts for profile measurements in 1.5 T MR-linacs.Approach. The Semiflex 3D ion chamber and microDiamond detector (PTW, Germany) were considered in the experimental study while three more detectors were included in the Monte Carlo (MC) study. CAX deviations in the crossline and inline profiles were calculated based on inflection points of the 10×10 cm2field, at five centers. In MC simulations, the experimental setup was reproduced. A small water voxel was simulated to calculate CAX deviation without the impact of the detector-specificEPOMLshift.Main results. All measurements were consistent among the five centers. MC-based and experimental measurements were in agreement within uncertainties. Placing the microDiamond in the vertical orientation does not appear to affect the detector'sEPOML, which is on its central longitudinal axis. For the Semiflex 3D in the crossline direction, the CAX deviation was 2.3 mm, i.e. 1 mm larger than the ones measured using the microDiamond and simulated considering the ideal water detector. Thus, anEPOMLshift of 1 mm is recommended for crossline profile measurements under both Semiflex 3D orientations. For the inline profile, anEPOMLshift of -0.5 mm was determined only for the parallel configuration. In the MC study, CAX deviations were found detector- and orientation-dependent. The dead volume is responsible for theEPOMLshift only in the inline profile and under the parallel orientation.Significance. This work contributes to data availability on the correction or mitigation of the magnetic field-induced changes in the detectors' response.

Comparison of Measurement and Prognostic Power of SUV Between High-Definition and Standard PET Imaging in Non-Small Cell Lung Cancer Patients.

This study aimed to evaluate the measurement and prognostic ability of the SUVmax of whole-body tumors (SUVmaxwb) in non-small cell lung cancer (NSCLC) patients, comparing high-definition (HD) PET imaging with standard-definition (SD) PET imaging. Methods: The study included 242 consecutive NSCLC patients who underwent baseline 18F-FDG PET/CT from April 2018 to January 2021. Two imaging techniques were used: HD PET (using ordered-subsets expectation maximization with point-spread function modeling and time-of-flight techniques and smaller voxels) and SD PET (with ordered-subsets expectation maximization and time-of-flight techniques). SUVmaxwb was determined by measuring all the tumor lesions in the whole body, and tumor-to-background ratio (TBR) was calculated using the background SUVmean of various body parts. Results: The patient cohort had an average age of 68.3 y, with 59.1% being female. During a median follow-up of 29.6 mo, 83 deaths occurred. SUVmaxwb was significantly higher in HD PET than SD PET, with respective medians of 17.4 and 11.8. The TBR of 1,125 tumoral lesions was also higher in HD PET. Univariate Cox regression analysis showed that SUVmaxwb from both HD and SD PET were significantly associated with overall survival. However, after adjusting for TNM (tumor, node, metastasis) stage, only SUVmaxwb from SD PET remained significantly associated with survival. Conclusion: HD PET imaging in NSCLC patients yields higher SUVmaxwb and TBR, enhancing tumor visibility. Despite this, its prognostic value is less significant than SD PET after adjusting clinical TNM stage. Thus, consideration should be given to using HD PET reconstruction to increase tumor visibility, and SD PET is recommended for NSCLC patient prognostication and therapeutic evaluation, as well as for the classification of lung nodules.

T1-mapping characterization of two tumor types

T1 mapping is a quantitative method to characterize tissues with magnetic resonance imaging in a quick and efficient manner. It utilizes the relaxation rate of protons to depict the underlying structures within the imaging frame. While T1-mapping techniques are used with some frequency in areas such as cardiac imaging, their application for understanding malignancies and identifying tumor structures has yet to be thoroughly investigated. Utilizing a saturation recovery method to acquire T1 maps for two different tumor models has revealed that longitudinal relaxation mapping is sensitive enough to distinguish between normal and malignant tissue. This is seen even with decreased signal/noise ratios using small voxel sizes to obtain high-resolution images. In both tumor models, it was revealed that relaxation mapping recorded significantly different relaxation values between regions encapsulating the tumor, muscle, kidney, or spleen, as well as between the cell lines themselves. This indicates a potential future application of relaxation mapping as a method to fingerprint various stages of tumor development and may prove a useful measure to identify micro-metastases.

Whole‐brain deuterium metabolic imaging via concentric ring trajectory readout enables assessment of regional variations in neuronal glucose metabolism

Whole‐brain deuterium metabolic imaging via concentric ring trajectory readout enables assessment of regional variations in neuronal glucose metabolism

Intraductal magnetic resonance imaging of cholangiocarcinoma -a practical possibility.

Intraductal T2 mapping based on a catheter receiver is proposed as a method of visualizing the extent of intraductal and periductal cholangiocarcinoma (CCA). Compared to external receivers, internal receivers provide locally enhanced signal-to-noise ratios by virtue of their lower field-of-view for body noise, allowing smaller voxels and higher resolution. However, inherent radial sensitivity variation and segmentation for patient safety both distort image brightness. We discuss simulated T2 weighted images and T2 maps, and in vitro images obtained using a thin film catheter receiver of a freshly resected liver specimen containing a polypoid intraductal tumor from a patient with CCA. T2 mapping provides a simple method of compensating non-uniform signal reception patterns of catheter receivers, allowing the visualization of tumor extent without contrast enhancement and potentially quantitative tissue characterization. Potential advantages and disadvantages of in vivo intraductal imaging are considered.

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.

Porosity prediction in laser-based powder bed fusion of polyamide 12 using infrared thermography and machine learning

Achieving precise control in laser-based powder bed fusion of polymers is crucial for ensuring the structural integrity of aerospace and automotive components. Closed-loop feedback control systems using process monitoring techniques, such as infrared thermography, have the potential to provide reliable production by controlling the temperature of the melt. However, challenges arise from complex interactions among variables, such as part geometry, scan strategy, and laser parameters, affecting the melted polymer's temperatures and subsequent particle fusion. Thus, the correlation between thermal signals and resulting part density still needs to be clarified. In this work, a machine learning algorithm is trained to predict local porosity or, rather, solidity based on thermal and temporal features extracted from the melt's temperature-time profile. This enables statistical techniques to assess the contribution of the melt's thermal and temporal features in the decision-making process for evaluating porosity, along with the influence of voxel size and configuration. The in-situ process signature is measured using infrared thermography, and the porosity is analyzed by X-ray micro-computed tomography. The 2D thermal data is first converted into voxel information and then stitched with the 3D mircoCT data in a second step. The resulting 3D thermal features and porosity matrices are downsampled and utilized to train a machine learning algorithm (lightGBM). Models with high prediction accuracy are achieved using a small voxel size to avoid over-homogenizing features and by utilizing thermal signals from adjacent voxels to determine porosity in a volume element. The highest predictor for resulting porosity is the peak temperature of the melt during laser exposure. Interlayer effects, such as sufficient reheating of subsurface layers, are the second-highest indicator for dense parts. Furthermore, the model's performance is also affected by intra-layer effects, including the peak temperature of adjacent voxels and the cooling behavior after laser exposure. This research has several implications for industry, as it enables the detection of process defects based on in-situ process monitoring data without post-process material testing. Moreover, identifying thermal signal ranges that lead to the highest porosity can reduce the number of experiments needed for material qualification processes.

Accuracy of cone-beam computed tomography in imaging the components of the periodontal phenotype.

The components and dimensions of the periodontal and peri-implant phenotype have a high relevance in contemporary dental research and should be taken into consideration in the decision-making process in the management of a variety of clinical scenarios to optimize the outcomes of therapy. Various assessment methods for quantifying and classifying the phenotypical dimensions have emerged and developed in recent decades. Nevertheless, the use of cone-beam computed tomography (CBCT) scans remains the most commonly used approach worldwide. However, the accuracy to adequately imaging and measuring the dimensions of the hard and soft tissue components around teeth may represent a significant challenge in different clinical scenarios due to factors such as the age of the patient and motion during the scan, presence of metallic artifacts causing streaks and gray-value distortion, overlapping of soft tissue structures, machine performance, file processing, and small voxel size among others. These factors pose a particular challenge when tiny structures are under investigation, for example, the buccal/lingual bony or soft tissue layer of lower/upper incisors. Therefore, this review addresses the underlying technical information of the use of CBCT scans, and suggests some recommendations on the utilization of this method of assessment to optimally use it despite its' system-inherent limitations.

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

Phantom study and clinical application of total-body 18F-FDG PET/CT imaging: How to use small voxel imaging better?

BackgroundConventional PET/CT imaging reconstruction is typically performed using voxel size of 3.0–4.0 mm in three axes. It is hypothesized that a smaller voxel sizes could improve the accuracy of small lesion detection. This study aims to explore the advantages and conditions of small voxel imaging on clinical application.MethodsBoth NEMA IQ phantom and 30 patients with an injected dose of 3.7 MBq/kg were scanned using a total-body PET/CT (uEXPLORER). Images were reconstructed using matrices of 192 × 192, 512 × 512, and 1024 × 1024 with scanning duration of 3 min, 5 min, 8 min, and 10 min, respectively.ResultsIn the phantom study, the contrast recovery coefficient reached the maximum in matrix group of 512 × 512, and background variability increased as voxel size decreased. In the clinical study, SUVmax, SD, and TLR increased, while SNR decreased as the voxel size decreased. When the scanning duration increased, SNR increased, while SUVmax, SD, and TLR decreased. The SUVmean was more reluctant to the changes in imaging matrix and scanning duration. The mean subjective scores for all 512 × 512 groups and 1024 × 1024 groups (scanning duration ≥ 8 min) were over three points. One false-positive lesion was found in groups of 512 × 512 with scanning duration of 3 min, 1024 × 1024 with 3 min and 5 min, respectively. Meanwhile, the false-negative lesions found in group of 192 × 192 with duration of 3 min and 5 min, 512 × 512 with 3 min and 1024 × 1024 with 3 min and 5 min were 5, 4, 1, 4, and 1, respectively. The reconstruction time and storage space occupation were significantly increased as the imaging matrix increased.ConclusionsPET/CT imaging with smaller voxel can improve SUVmax and TLR of lesions, which is advantageous for the diagnosis of small or hypometabolic lesions if with sufficient counts. With an 18F-FDG injection dose of 3.7 MBq/kg, uEXPLORER PET/CT imaging using matrix of 512 × 512 with 5 min or 1024 × 1024 with 8 min can meet the image requirements for clinical use.

Utilization of Imaging Modalities in the Diagnosis of Melanoma: A Scoping Review.

Melanomas arise de novo or in the context of a precursor lesion. Lesions typically grow radially and then undergo a vertical growth phase proceeding to local invasion and metastasis. This review describes the utility of different imaging modalities in diagnosis and melanocytic lesion monitoring. A literature search was performed in November 2023 utilizing EMBASE, Medline, and PubMed. The PRISMA diagram demonstrates the review process. Reflectance confocal microscopy (RCM) utilizes near-infrared light to help diagnose dermatologic lesions. RCMwas found to demonstrate nearly two times the positive predictive value compared to dermoscopy. The introduction of the Berlin Ultrasound (US) Morphology Criteria permitted a 65-80% improvement in diagnostic sensitivity. US with fine-needle aspiration cytology (FNAC) accurately predicts the necessity for sentinel lymph node biopsy and lymphadenectomy, sparing patients with metastasis and prompting biopsy for equivocal lesions. Single-photon emission computed tomography/computed tomography (SPECT/CT) is an adjunctive tool to anatomically and functionally assess lymphatic invasion. SPECT/CT improves the detection of sentinel nodes while decreasing operating time and improving cosmetic outcomes. 18F-fluorodeoxyglucose(18F-FDG) positron emission tomography/computed tomography (PET/CT) with small voxel reconstruction demonstrated increased specificity and sensitivity for detecting in-transit metastases of melanomas, specifically in the limbs. Dermoscopy allows providers to cost-effectively recognize common lesion patterns. Multiphoton microscopy assigns a weight-based score based on malignant features. Optical coherence angiography captures images of vessels to help diagnose equivocal lesions. Utilization of imaging techniques may increase diagnostic accuracy, reduce unnecessary procedures, and help guide treatment plans. Additional research is needed to further characterize the utility of these techniques in order to improve the diagnosis and treatment of melanomas.

A cryogenic tune and match circuit for magnetic resonance microscopy at 15.2T

Background and SignificanceAchievable signal to noise ratios (SNR) in magnetic resonance microscopy images are limited by acquisition times and the decreasing number of spins in smaller voxels. A common method of enhancing SNR is to cool the RF receiver coil. Significant SNR gains are realized only when the Johnson noise generated within the RF hardware is large compared to the electromagnetic noise produced by the sample. Cryogenic cooling of imaging probes is in common use in high field systems, but it is difficult to insulate a sample from the extreme temperatures involved and in practice imaging cryoprobes have been limited to surface or partial volume designs only. In order to use a solenoid in which the windings were not directly cooled and in close proximity to the sample, we designed a chamber to cool only the tune and match circuitry and show experimentally it is possible to achieve much of the theoretically available SNR gain. MethodsA microcoil circuit consisting of two tuning capacitors, one fixed capacitor, and SMB coaxial cable was designed to resonate at 650 MHz for imaging on a Bruker 15.2 T scanner. Sample noise increases with the sample diameter, so surface loops and solenoids of varying diameters were tested on the bench to determine the largest diameter coil that demonstrated significant SNR gains from cooling. A liquid N2 cryochamber was designed to cool the tune and match circuit, coaxial cable, and connectors, while leaving the RF coil in ambient air. As the cryochamber was filled with liquid N2, quality factors were measured on the bench while monitoring the coil's surface temperature. Improvements of SNR on images of ionic solutions were demonstrated via cooling the tune and match circuit in the magnet bore. ResultsAt 650 MHz, loops and solenoids < 3 mm in diameter showed significant improvements in quality factor on the bench. The resistance of the variable capacitors and the coaxial cable were measured to be 45% and 32% of room temperature values near the Larmor frequency. Images obtained with a 2 turn, 3 mm diameter loop with the matching circuit at room temperature and then cooled with liquid nitrogen demonstrated SNR improvements of a factor of 2. ConclusionsBy cooling the tune and match circuit and leaving the surface loop in ambient air, SNR was improved by a factor of 2. The results are significant because it allows for more space to insulate the sample from the extreme temperatures used in imaging cryoprobes.

A Variational Autoencoder Cascade Generative Adversarial Network for Scalable 3D Object Generation and Reconstruction

Generative Adversarial Networks (GANs) for 3D volume generation and reconstruction, such as shape generation, visualization, automated design, real-time simulation, and research applications, are receiving increased amounts of attention in various fields. However, challenges such as limited training data, high computational costs, and mode collapse issues persist. We propose combining a Variational Autoencoder (VAE) and a GAN to uncover enhanced 3D structures and introduce a stable and scalable progressive growth approach for generating and reconstructing intricate voxel-based 3D shapes. The cascade-structured network involves a generator and discriminator, starting with small voxel sizes and incrementally adding layers, while subsequently supervising the discriminator with ground-truth labels in each newly added layer to model a broader voxel space. Our method enhances the convergence speed and improves the quality of the generated 3D models through stable growth, thereby facilitating an accurate representation of intricate voxel-level details. Through comparative experiments with existing methods, we demonstrate the effectiveness of our approach in evaluating voxel quality, variations, and diversity. The generated models exhibit improved accuracy in 3D evaluation metrics and visual quality, making them valuable across various fields, including virtual reality, the metaverse, and gaming.

Haralick texture analysis for microdosimetry: characterization of Monte Carlo generated 3D specific energy distributions

Objective. Explore the application of Haralick textural analysis to 3D distributions of specific energy (energy imparted per unit mass) scored in cell-scale targets considering varying mean specific energy (absorbed dose), target volume, and incident spectrum. Approach. Monte Carlo simulations are used to generate specific energy distributions in cell-scale water voxels ((1 μm)3–(15 μm)3) irradiated by photon sources (mean energies: 0.02–2 MeV) to varying mean specific energies (10–400 mGy). Five Haralick features (homogeneity, contrast, entropy, correlation, local homogeneity) are calculated using an implementation of Haralick analysis designed to reduce sensitivity to grey level quantization and are interpreted using fundamental radiation physics. Main results. Haralick measures quantify differences in 3D specific energy distributions observed with varying voxel volume, absorbed dose magnitude, and source spectrum. For example, specific energy distributions in small (1–3 μm) voxels with low magnitudes of absorbed dose (10 mGy) have relatively high measures of homogeneity and local homogeneity and relatively low measures of contrast and entropy (all relative to measures for larger voxels), reflecting the many voxels with zero specific energy in an otherwise sporadic distribution. With increasing target size, energy is shared across more target voxels, and trends in Haralick measures, such as decreasing homogeneity and increasing contrast and entropy, reflect characteristics of each 3D specific energy distribution. Specific energy distributions for sources of differing mean energy are characterized by Haralick measures, e.g. contrast generally decreases with increasing source energy, correlation and homogeneity are often (not always) higher for higher energy sources. Significance. Haralick texture analysis successfully quantifies spatial trends in 3D specific energy distributions characteristic of radiation source, target size, and absorbed dose magnitude, thus offering new avenues to quantify microdosimetric data beyond first order histogram features. Promising future directions include investigations of multiscale tissue models, targeted radiation therapy techniques, and biological response to radiation.

Cone-Beam Computed Tomography Accuracy for Morphological and Morphometric Evaluation of Mandibular Condyles Using Small FOV and Small Voxel Size

&#x0D; The objective of this study is to evaluate the accuracy of cone beam computed tomography (CBCT) in determining and visualizing the morphology and morphometry of the mandibular condyle. Narrative reviews with article searches were carried out through NCBI's PubMed database and Scopus from September 2021–October 2021, with the inclusion criteria articles published in 2011–2021. The temporomandibular joint (TMJ) has a crucial role and is closely related to the masticatory system. The diagnosis of temporomandibular disorder (TMD) is not easy and is complex enough to require a comprehensive clinical and radiographic examination. Pathological changes such as erosion of the condyle, fracture, ankylosis, dislocation, and osteophyte can be well seen using CBCT imaging. CBCT images obtained with smaller field of view (FOV) have smaller a voxel size and a higher image resolution. FOV or scan volume refers to the anatomical area that will be included in the data volume or the area of the patient that will be irradiated. The dimension of FOV depends on the detector size and shape, the beam projection geometry, and the ability to collimate the beam. Voxel size is an important component of image quality, related to both the pixel size and the image matrix. Selection of small FOV and small voxel size is recommended because they provide better visualization and detail for the evaluation of morphology and morphometry of the condyle, especially the detection of erosion and defects on the condyle surface.

Deep learning synthesis of cone-beam computed tomography from zero echo time magnetic resonance imaging

Cone-beam computed tomography (CBCT) produces high-resolution of hard tissue even in small voxel size, but the process is associated with radiation exposure and poor soft tissue imaging. Thus, we synthesized a CBCT image from the magnetic resonance imaging (MRI), using deep learning and to assess its clinical accuracy. We collected patients who underwent both CBCT and MRI simultaneously in our institution (Seoul). MRI data were registered with CBCT data, and both data were prepared into 512 slices of axial, sagittal, and coronal sections. A deep learning-based synthesis model was trained and the output data were evaluated by comparing the original and synthetic CBCT (syCBCT). According to expert evaluation, syCBCT images showed better performance in terms of artifacts and noise criteria but had poor resolution compared to the original CBCT images. In syCBCT, hard tissue showed better clarity with significantly different MAE and SSIM. This study result would be a basis for replacing CBCT with non-radiation imaging that would be helpful for patients planning to undergo both MRI and CBCT.

Improved sensitivity and microvascular weighting of 3T laminar fMRI with GE-BOLD using NORDIC and phase regression

IntroductionFunctional MRI with spatial resolution in the submillimeter domain enables measurements of activation across cortical layers in humans. This is valuable as different types of cortical computations, e.g., feedforward versus feedback related activity, take place in different cortical layers. Laminar fMRI studies have almost exclusively employed 7T scanners to overcome the reduced signal stability associated with small voxels. However, such systems are relatively rare and only a subset of those are clinically approved. In the present study, we examined if the feasibility of laminar fMRI at 3T could be improved by use of NORDIC denoising and phase regression. Methods5 healthy subjects were scanned on a Siemens MAGNETOM Prisma 3T scanner. To assess across-session reliability, each subject was scanned in 3–8 sessions on 3–4 consecutive days. A 3D gradient echo EPI (GE-EPI) sequence was used for BOLD acquisitions (voxel size 0.82 mm isotopic, TR = 2.2 s) using a block design finger tapping paradigm. NORDIC denoising was applied to the magnitude and phase time series to overcome limitations in temporal signal-to-noise ratio (tSNR) and the denoised phase time series were subsequently used to correct for large vein contamination through phase regression. Results and conclusionNORDIC denoising resulted in tSNR values comparable to or higher than commonly observed at 7T. Layer-dependent activation profiles could thus be extracted robustly, within and across sessions, from regions of interest located in the hand knob of the primary motor cortex (M1). Phase regression led to substantially reduced superficial bias in obtained layer profiles, although residual macrovascular contribution remained. We believe the present results support an improved feasibility of laminar fMRI at 3T.