Virtual blebbistatin: A robust and rapid software approach to motion artifact removal in optical mapping of cardiomyocytes.

Fluorescent reporters of cardiac electrophysiology provide valuable information on heart cell and tissue function. However, motion artifacts caused by cardiac muscle contraction interfere with accurate measurement of fluorescence signals. Although drugs such as blebbistatin can be applied to stop cardiac tissue from contracting by uncoupling calcium-contraction, their usage prevents the study of excitation-contraction coupling and, as we show, impacts cellular structure. We therefore developed a robust method to remove motion computationally from images of contracting cardiac muscle and to map fluorescent reporters of cardiac electrophysiological activity onto images of undeformed tissue. When validated on cardiomyocytes derived from human induced pluripotent stem cells (iPSCs), in both monolayers and engineered tissues, the method enabled efficient and robust reduction of motion artifact. As with pharmacologic approaches using blebbistatin for motion removal, our algorithm improved the accuracy of optical mapping, as demonstrated by spatial maps of calcium transient decay. However, unlike pharmacologic motion removal, our computational approach allowed direct analysis of calcium-contraction coupling. Results revealed calcium-contraction coupling to be more uniform across cells within engineered tissues than across cells in monolayer culture. The algorithm shows promise as a robust and accurate tool for optical mapping studies of excitation-contraction coupling in heart tissue.

Novel inductively coupled ear-bars (ICEs) to enhance restored fMRI signal from susceptibility compensation in rats.

Functional magnetic resonance imaging faces inherent challenges when applied to deep-brain areas in rodents, e.g. entorhinal cortex, due to the signal loss near the ear cavities induced by susceptibility artifacts and reduced sensitivity induced by the long distance from the surface array coil. Given the pivotal roles of deep brain regions in various diseases, optimized imaging techniques are needed. To mitigate susceptibility-induced signal losses, we introduced baby cream into the middle ear. To enhance the detection sensitivity of deep brain regions, we implemented inductively coupled ear-bars, resulting in approximately a 2-fold increase in sensitivity in entorhinal cortex. Notably, the inductively coupled ear-bar can be seamlessly integrated as an add-on device, without necessitating modifications to the scanner interface. To underscore the versatility of inductively coupled ear-bars, we conducted echo-planner imaging-based task functional magnetic resonance imaging in rats modeling Alzheimer's disease. As a proof of concept, we also demonstrated resting-state-functional magnetic resonance imaging connectivity maps originating from the left entorhinal cortex-a central hub for memory and navigation networks-to amygdala hippocampal area, Insular Cortex, Prelimbic Systems, Cingulate Cortex, Secondary Visual Cortex, and Motor Cortex. This work demonstrates an optimized procedure for acquiring large-scale networks emanating from a previously challenging seed region by conventional magnetic resonance imaging detectors, thereby facilitating improved observation of functional magnetic resonance imaging outcomes.

Uncovering eco-friendly design in the ancient bronze goose-and-fish lamp: an unnoticeable gap boosts ventilation.

The bronze goose-and-fish lamp exhibited in the national museum of China is a 2,000-y-old artifact once used for indoor lighting by nobility in the Western Han dynasty (206 BCE TO 25 CE). The beauty of this national treasure arises from its elegant shape vividly showing a goose catching fish with beautiful colors painted over the whole body. Beyond the artistic and historical value, what enchants people most is the eco-design concept of this oil-burning lamp. It is widely believed that the smoke generated by burning animal oil can flow into the goose belly through its long neck, then be absorbed by prefilled water in the belly, hence mitigating indoor air pollution. Although different mechanistic hypotheses such as natural convection and even the siphon effect have been proposed to qualitatively rationalize the above-claimed pollution mitigation function, due to the absence of a true scientific analysis, the definitive mechanism remains a mystery. By rigorous modeling of the nonisothermal fluid flow coupled with convection-diffusion of pollutant within and out of the lamp, we discover that it is the unnoticeable gap between goose body and lamp tray (i.e., an intrinsic feature of the multicompartmental design) that can offer definitive ventilation in the lamp. The ventilation is facilitated by natural convection due to oil burning. Adequate ventilation plays a key role in enabling pollution mitigation, as it allows pollutant to reach the goose belly, travel over and be absorbed by the water.

Stem cell-derived cardiomyocyte heterogeneity confounds electrophysiological insights.

Human induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs) offer potential as an in vitro model for studying drug cardiotoxicity and patient-specific cardiovascular disease. The inherent electrophysiological heterogeneity of these cells limits the depth of insights that can be drawn from well-designed experiments. In this review, we provide our perspective on some sources and the consequences of iPSC-CM heterogeneity. We demonstrate the extent of heterogeneity in the literature and explain how such heterogeneity is exacerbated by patch-clamp experimental artifacts in the manual and automated set-up. Finally, we discuss how this heterogeneity, caused by both intrinsic and extrinsic factors, limits our ability to build digital twins of patient-derived cardiomyocytes.

Expanding the clinical application of OPM-MEG using an effective automatic suppression method for the dental brace metal artifact.

Optically pumped magnetometer magnetoencephalography (OPM-MEG) holds significant promise for clinical functional brain imaging due to its superior spatiotemporal resolution. However, effectively suppressing metallic artifacts, particularly from devices such as orthodontic braces and vagal nerve stimulators remains a major challenge, hindering the wider clinical application of wearable OPM-MEG devices. A comprehensive analysis of metal artifact characteristics from time, frequency, and time-frequency perspectives was conducted for the first time using an OPM-MEG device in clinical medicine. This study focused on patients with metal orthodontics, examining the modulation of metal artifacts by breath and head movement, the incomplete regular sub-Gaussian distribution, and the high absolute power ratio in the 0.5-8 Hz band. The existing metal artifact suppression algorithms applied to SQUID-MEG, such as fast independent component analysis (FastICA), information maximization (Infomax), and algorithms for multiple unknown signal extraction (AMUSE), exhibit limited efficacy. Consequently, this study introduced the second-order blind identification (SOBI) algorithm, which utilized multiple time delays for the component separation of OPM-MEG measurement signals. We modified the time delays of the SOBI method to improve its efficacy in separating artifact components, particularly those in the ultralow frequency range. This approach employs the frequency-domain absolute power ratio, root mean square (RMS) value, and mutual information methods to automate the artifact component screening process. The effectiveness of this method was validated through simulation experiments involving four subjects in both resting and evoked experiments. In addition, the proposed method was also validated by the actual OPM-MEG evoked experiments of three subjects. Comparative analyses were conducted against the FastICA, Infomax, and AMUSE algorithms. Evaluation metrics included normalized mean square error, normalized delta band power error, RMS error, and signal-to-noise ratio, demonstrating that the proposed method provides optimal suppression of metal artifacts. This advancement holds promise for enhancing data quality and expanding the clinical applications of OPM-MEG.

Prevalence of TERT Promoter Mutations in Orbital Solitary Fibrous Tumors.

The orbital manifestation of a solitary fibrous tumor (SFT) is exceptionally rare and poses specific challenges in diagnosis and treatment. Its rather exceptional behavior among all SFTs comprises a high tendency towards local recurrence, but it rarely culminates in metastatic disease. This raises the question of prognostic factors in orbital SFTs (oSFTs). Telomerase reverse transcriptase (TERT)-promoter mutations have previously been linked to an unfavorable prognosis in SFTs of other locations. We analyzed the prevalence of TERT promoter mutations of SFTs in the orbital compartment. We performed a retrospective, descriptive clinico-histopathological analysis of nine cases of oSFTs between the years of 2017 and 2021. A TERT promoter mutation was present in one case, which was classified with intermediate metastatic risk. Local recurrence or progress occurred in six cases after primary resection; no distant metastases were reported. Multimodal imaging repeatedly showed particular morphologic patterns, including tubular vascular structures and ADC reduction. The prevalence of the TERT promoter mutation in oSFT was 11%, which is similar to the prevalence of extra-meningeal SFTs of the head and neck and lower than that in other extra-meningeal compartments. In the present study, the TERT promoter mutation in oSFT manifested in a case with an unfavorable prognosis, comprising aggressive local tumor growth, local recurrence, and eye loss.

Diffusion MRI head motion correction methods are highly accurate but impacted by denoising and sampling scheme.

Head motion correction is particularly challenging in diffusion-weighted MRI (dMRI) scans due to the dramatic changes in image contrast at different gradient strengths and directions. Head motion correction is typically performed using a Gaussian Process model implemented in FSL's Eddy. Recently, the 3dSHORE-based SHORELine method was introduced that does not require shell-based acquisitions, but it has not been previously benchmarked. Here we perform a comprehensive evaluation of both methods on realistic simulations of a software fiber phantom that provides known ground-truth head motion. We demonstrate that both methods perform remarkably well, but that performance can be impacted by sampling scheme and the extent of head motion and the denoising strategy applied before head motion correction. Furthermore, we find Eddy benefits from denoising the data first with MP-PCA. In sum, we provide the most extensive known benchmarking of dMRI head motion correction, together with extensive simulation data and a reproducible workflow. PRACTITIONER POINTS: Both Eddy and SHORELine head motion correction methods performed quite well on a large variety of simulated data. Denoising with MP-PCA can improve head motion correction performance when Eddy is used. SHORELine effectively corrects motion in non-shelled diffusion spectrum imaging data.

Toward accurate and fast velocity quantification with 3D ultrashort TE phase-contrast imaging.

PURPOSE: Traditional phase-contrast MRI is affected by displacement artifacts caused by non-synchronized spatial- and velocity-encoding time points. The resulting inaccurate velocity maps can affect the accuracy of derived hemodynamic parameters. This study proposes and characterizes a 3D radial phase-contrast UTE (PC-UTE) sequence to reduce displacement artifacts. Furthermore, it investigates the displacement of a standard Cartesian flow sequence by utilizing a displacement-free synchronized-single-point-imaging MR sequence (SYNC-SPI) that requires clinically prohibitively long acquisition times. METHODS: 3D flow data was acquired at 3T at three different constant flow rates and varying spatial resolutions in a stenotic aorta phantom using the proposed PC-UTE, a Cartesian flow sequence, and a SYNC-SPI sequence as reference. Expected displacement artifacts were calculated from gradient timing waveforms and compared to displacement values measured in the in vitro flow experiments. RESULTS: The PC-UTE sequence reduces displacement and intravoxel dephasing, leading to decreased geometric distortions and signal cancellations in magnitude images, and more spatially accurate velocity quantification compared to the Cartesian flow acquisitions; errors increase with velocity and higher spatial resolution. CONCLUSION: PC-UTE MRI can measure velocity vector fields with greater accuracy than Cartesian acquisitions (although pulsatile fields were not studied) and shorter scan times than SYNC-SPI. As such, this approach is superior to traditional Cartesian 3D and 4D flow MRI when spatial misrepresentations cannot be tolerated, for example, when computational fluid dynamics simulations are compared to or combined with in vitro or in vivo measurements, or regional parameters such as wall shear stress are of interest.

Rapid motion estimation and correction using self-encoded FID navigators in 3D radial MRI.

PURPOSE: To develop a self-navigated motion compensation strategy for 3D radial MRI that can compensate for continuous head motion by measuring rigid body motion parameters with high temporal resolution from the central k-space acquisition point (self-encoded FID navigator) in each radial spoke. METHODS: A forward model was created from low-resolution calibration data to simulate the effect of relative motion between the coil sensitivity profiles and the underlying object on the self-encoded FID navigator signal. Trajectory deviations were included in the model as low spatial-order field variations. Three volunteers were imaged at 3 T using a modified 3D gradient-echo sequence acquired with a Kooshball trajectory while performing abrupt and continuous head motion. Rigid body-motion parameters were estimated from the central k-space signal of each spoke using a least-squares fitting algorithm. The accuracy of self-navigated motion parameters was assessed relative to an established external tracking system. Quantitative image quality metrics were computed for images with and without retrospective correction using external and self-navigated motion measurements. RESULTS: Self-encoded FID navigators achieved mean absolute errors of 0.69 ± 0.82 mm and 0.73 ± 0.87° relative to external tracking for maximum motion amplitudes of 12 mm and 10°. Retrospective correction of the 3D radial data resulted in substantially improved image quality for both abrupt and continuous motion paradigms, comparable to external tracking results. CONCLUSIONS: Accurate rigid body motion parameters can be rapidly obtained from self-encoded FID navigator signals in 3D radial MRI to continuously correct for head movements. This approach is suitable for robust neuroanatomical imaging in subjects that exhibit patterns of large and frequent motion.

Effects of prospective motion correction on perivascular spaces at 7T MRI evaluated using motion artifact simulation.

PURPOSE: The effectiveness of prospective motion correction (PMC) is often evaluated by comparing artifacts in images acquired with and without PMC (NoPMC). However, such an approach is not applicable in clinical setting due to unavailability of NoPMC images. We aim to develop a simulation approach for demonstrating the ability of fat-navigator-based PMC in improving perivascular space (PVS) visibility in T2-weighted MRI. METHODS: MRI datasets from two earlier studies were used for motion artifact simulation and evaluating PMC, including T2-weighted NoPMC and PMC images. To simulate motion artifacts, k-space data at motion-perturbed positions were calculated from artifact-free images using nonuniform Fourier transform and misplaced onto the Cartesian grid before inverse Fourier transform. The simulation's ability to reproduce motion-induced blurring, ringing, and ghosting artifacts was evaluated using sharpness at lateral ventricle/white matter boundary, ringing artifact magnitude in the Fourier spectrum, and background noise, respectively. PVS volume fraction in white matter was employed to reflect its visibility. RESULTS: In simulation, sharpness, PVS volume fraction, and background noise exhibited significant negative correlations with motion score. Significant correlations were found in sharpness, ringing artifact magnitude, and PVS volume fraction between simulated and real NoPMC images (p ≤ 0.006). In contrast, such correlations were reduced and nonsignificant between simulated and real PMC images (p ≥ 0.48), suggesting reduction of motion effects with PMC. CONCLUSIONS: The proposed simulation approach is an effective tool to study the effects of motion and PMC on PVS visibility. PMC may reduce the systematic bias of PVS volume fraction caused by motion artifacts.

Comprehensive assessment of nonuniform image quality: Application to imaging near metal.

PURPOSE: Comprehensive assessment of image quality requires accounting for spatial variations in (i) intensity artifact, (ii) geometric distortion, (iii) signal-to-noise ratio (SNR), and (iv) spatial resolution, among other factors. This work presents an ensemble of methods to meet this need, from phantom design to image analysis, and applies it to the scenario of imaging near metal. METHODS: A modular phantom design employing a gyroid lattice is developed to enable the co-registered volumetric quantitation of image quality near a metallic hip implant. A method for measuring spatial resolution by means of local point spread function (PSF) estimation is presented and the relative fitness of gyroid and cubic lattices is examined. Intensity artifact, geometric distortion, and SNR maps are also computed. Results are demonstrated with 2D-FSE and MAVRIC-SL scan protocols on a 3T MRI scanner. RESULTS: The spatial resolution method demonstrates a worst-case error of 0.17 pixels for measuring in-plane blurring up to 3 pixels (full width at half maximum). The gyroid outperforms a cubic lattice design for the local PSF estimation task. The phantom supports four configurations toggling the presence/absence of both metal and structure with good spatial correspondence for co-registered analysis of the four quality factors. The marginal scan time to evaluate one scan protocol amounts to five repetitions. The phantom design can be fabricated in 2 days at negligible material cost. CONCLUSION: The phantom and associated analysis methods can elucidate complex image quality trade-offs involving intensity artifact, geometric distortion, SNR, and spatial resolution. The ensemble of methods is suitable for benchmarking imaging performance near metal.

Motion-robust free-running volumetric cardiovascular MRI.

PURPOSE: To present and assess an outlier mitigation method that makes free-running volumetric cardiovascular MRI (CMR) more robust to motion. METHODS: The proposed method, called compressive recovery with outlier rejection (CORe), models outliers in the measured data as an additive auxiliary variable. We enforce MR physics-guided group sparsity on the auxiliary variable, and jointly estimate it along with the image using an iterative algorithm. For evaluation, CORe is first compared to traditional compressed sensing (CS), robust regression (RR), and an existing outlier rejection method using two simulation studies. Then, CORe is compared to CS using seven three-dimensional (3D) cine, 12 rest four-dimensional (4D) flow, and eight stress 4D flow imaging datasets. RESULTS: Our simulation studies show that CORe outperforms CS, RR, and the existing outlier rejection method in terms of normalized mean square error and structural similarity index across 55 different realizations. The expert reader evaluation of 3D cine images demonstrates that CORe is more effective in suppressing artifacts while maintaining or improving image sharpness. Finally, 4D flow images show that CORe yields more reliable and consistent flow measurements, especially in the presence of involuntary subject motion or exercise stress. CONCLUSION: An outlier rejection method is presented and tested using simulated and measured data. This method can help suppress motion artifacts in a wide range of free-running CMR applications.

Smart forecasting of artifacts in contrast-enhanced breast MRI before contrast agent administration.

OBJECTIVES: To evaluate whether artifacts on contrast-enhanced (CE) breast MRI maximum intensity projections (MIPs) might already be forecast before gadolinium-based contrast agent (GBCA) administration during an ongoing examination by analyzing the unenhanced T1-weighted images acquired before the GBCA injection. MATERIALS AND METHODS: This IRB-approved retrospective analysis consisted of n = 2884 breast CE MRI examinations after intravenous administration of GBCA, acquired with n = 4 different MRI devices at different field strengths (1.5 T/3 T) during clinical routine. CE-derived subtraction MIPs were used to conduct a multi-class multi-reader evaluation of the presence and severity of artifacts with three independent readers. An ensemble classifier (EC) of five DenseNet models was used to predict artifacts for the post-contrast subtraction MIPs, giving as the input source only the pre-contrast T1-weighted sequence. Thus, the acquisition directly preceded the GBCA injection. The area under ROC (AuROC) and diagnostics accuracy scores were used to assess the performance of the neural network in an independent holdout test set (n = 285). RESULTS: After majority voting, potentially significant artifacts were detected in 53.6% (n = 1521) of all breast MRI examinations (age 49.6 ± 12.6 years). In the holdout test set (mean age 49.7 ± 11.8 years), at a specificity level of 89%, the EC could forecast around one-third of artifacts (sensitivity 31%) before GBCA administration, with an AuROC = 0.66. CONCLUSION: This study demonstrates the capability of a neural network to forecast the occurrence of artifacts on CE subtraction data before the GBCA administration. If confirmed in larger studies, this might enable a workflow-blended approach to prevent breast MRI artifacts by implementing in-scan personalized predictive algorithms. CLINICAL RELEVANCE STATEMENT: Some artifacts in contrast-enhanced breast MRI maximum intensity projections might be predictable before gadolinium-based contrast agent injection using a neural network. KEY POINTS: • Potentially significant artifacts can be observed in a relevant proportion of breast MRI subtraction sequences after gadolinium-based contrast agent administration (GBCA). • Forecasting the occurrence of such artifacts in subtraction maximum intensity projections before GBCA administration for individual patients was feasible at 89% specificity, which allowed correctly predicting one in three future artifacts. • Further research is necessary to investigate the clinical value of such smart personalized imaging approaches.

Reducing clustering of readouts in non-Cartesian cine magnetic resonance imaging.

BACKGROUND: Non-Cartesian magnetic resonance imaging trajectories at golden angle increments have the advantage of allowing motion correction and gating using intermediate real-time reconstructions. However, when the acquired data are cardiac binned for cine imaging, trajectories can cluster together at certain heart rates (HR) causing image artifacts. Here, we demonstrate an approach to reduce clustering by inserting additional angular increments within the trajectory, and optimizing them while still allowing for intermediate reconstructions. METHODS: Three acquisition models were simulated under constant and variable HR: golden angle (Mtrd), random additional angles (Mrnd), and optimized additional angles (Mopt). The standard deviations of trajectory angular differences (STAD) were compared through their interquartile ranges (IQR) and the Kolmogorov-Smirnov test (significance level: p = 0.05). Agreement between an image reconstructed with uniform sampling and images from Mtrd, Mrnd, and Mopt was analyzed using the structural similarity index measure (SSIM). Mtrd and Mopt were compared in three adults at high, low, and no HR variability. RESULTS: STADs from Mtrd were significantly different (p < 0.05) from Mopt and Mrnd. STAD (IQR × 10-2 rad) showed that Mopt (0.5) and Mrnd (0.5) reduced clustering relative to Mtrd (1.9) at constant HR. For variable HR, Mopt (0.5) and Mrnd (0.5) outperformed Mtrd (0.9). The SSIM (IQR) showed that Mopt (0.011) produced the best image quality, followed by Mrnd (0.014), and Mtrd (0.030). Mopt outperformed Mtrd at reduced HR variability in in-vivo studies. At high HR variability, both models performed well. CONCLUSION: This approach reduces clustering in k-space and improves image quality.

Arterial transit artifact as a short-term prognostic indicator in acute ischemic stroke.

BACKGROUND: Arterial transit artifact (ATA) observed on arterial spin labeling (ASL) was recently suggested to be associated with improved functional outcomes following acute ischemic stroke (AIS). AIS is a heterogeneous disease with diverse pathogenic mechanisms depending on the stroke subtype. This study aimed to investigate the association between ATA and 3-month functional outcomes in AIS patients according to etiology subtypes. METHODS: Consecutive patients with AIS were included. All patients underwent ASL MRI with postlabeling delay (PLD) of 1.5 and 2.5 s. ATA was assessed from the ASL images of both PLDs. Stroke etiologic subtypes were determined according to the modified TOAST (Trial of ORG 10172 in Acute Stroke Treatment) classification. Short-term functional outcomes were evaluated using the 3-month modified Rankin scale (mRS). Log-binomial regression was applied to analyze the association between ATA and functional outcomes at 3 months after stroke. RESULTS: Ninety-eight AIS patients (62.73 ± 13.05 years; 68 men) were finally included. ATA was detected in forty-six patients and most frequently seen in the large-artery atherosclerosis (LAA) subtype (35/46). The ATA group exhibited a lower percentage of patients with mRS > 2 compared to the group without ATA (36.5% vs. 19.6%; P < 0.001). ATA was independently associated with better 3-month clinical outcomes (adjusted risk ratio, 0.35[95% CI, 0.16-0.74]) in the multivariate log-binomial regression model. After stratification by TOAST subtypes, a significant association was found between ATA and better outcomes in the LAA subtype (adjusted risk ratio, 0.20[ 95% CI, 0.05-0.72]) but not in cardioembolism and small artery occlusion (SVO) subtype. CONCLUSION: ATA is associated with better outcomes at 3 months in patients with AIS, especially in the LAA subtype, but this association attenuated in the cardioembolism and SVO subtypes.

Toxicologic Pathology Forum Opinion: Apoptosis/Single Cell Necrosis as a Possible Procedural Effect in Primate Brain Following Ice-Cold Saline Perfusion.

Nonclinical studies of test articles (TAs) in nonhuman primates are often designed to assess both biodistribution and toxicity. For this purpose, studies commonly use intravenous perfusion of ice-cold (2°C-8°C) saline to facilitate measurements of TA-associated nucleic acids and proteins, after which tissues undergo later fixation by immersion for histological processing and microscopic evaluation. Intriguingly, minimal apoptosis/single cell necrosis (A/SCN) of randomly distributed neural cells is evident in the cerebral cortex and less often the hippocampus in animals from all groups, including vehicle-treated controls. Affected cells exhibit end-stage features such as cytoplasmic hypereosinophilia, nuclear condensation or fragmentation, and shape distortions, so their lineage(s) generally cannot be defined; classical apoptotic bodies are exceedingly rare. In addition, A/SCN is not accompanied by glial reactions, leukocyte infiltration/inflammation, or other parenchymal changes. The severity is minimal in controls but may be slightly exacerbated (to mild) by TA that accumulate in neural cells. One plausible hypothesis explaining this A/SCN exacerbation is that cold shock (perhaps complicated by concurrent tissue acidity and hypoxia) drives still-viable but TA-stressed cells to launch a self-directed death program. Taken together, these observations indicate that A/SCN in brain processed by cold saline perfusion with delayed immersion fixation represents a procedural artifact and not a TA-related lesion.

EtOH-LN cryoembedding workflow to minimize freezing artifact in frozen tissues: A pilot study in preparing tissues compatible with mass spectrometry-based spatial proteomics application.

Coolant-assisted liquid nitrogen (LN) flash freezing of frozen tissues has been widely adopted to preserve tissue morphology for histopathological annotations in mass spectrometry-based spatial proteomics techniques. However, existing coolants pose health risks upon inhalation and are expensive. To overcome this challenge, we present our pilot study by introducing the EtOH-LN workflow, which demonstrates the feasibility of using 95 % ethanol as a safer and easily accessible alternative to existing coolants for LN-based cryoembedding of frozen tissues. Our study reveals that both the EtOH-LN and LN-only cryoembedding workflows exhibit significantly reduced freezing artifacts compared to cryoembedding in cryostat (p < 0.005), while EtOH-LN (SD = 0.56) generates more consistent results compared to LN-only (SD = 1.29). We have modified a previously reported morphology restoration method to incorporate the EtOH-LN workflow, which successfully restored the tissue architecture from freezing artifacts (p < 0.05). Additional studies are required to validate the impact of the EtOH-LN workflow on the molecular profiles of tissues.

Metal implant segmentation in CT images based on diffusion model.

BACKGROUND: Computed tomography (CT) is widely in clinics and is affected by metal implants. Metal segmentation is crucial for metal artifact correction, and the common threshold method often fails to accurately segment metals. PURPOSE: This study aims to segment metal implants in CT images using a diffusion model and further validate it with clinical artifact images and phantom images of known size. METHODS: A retrospective study was conducted on 100 patients who received radiation therapy without metal artifacts, and simulated artifact data were generated using publicly available mask data. The study utilized 11,280 slices for training and verification, and 2,820 slices for testing. Metal mask segmentation was performed using DiffSeg, a diffusion model incorporating conditional dynamic coding and a global frequency parser (GFParser). Conditional dynamic coding fuses the current segmentation mask and prior images at multiple scales, while GFParser helps eliminate high-frequency noise in the mask. Clinical artifact images and phantom images are also used for model validation. RESULTS: Compared with the ground truth, the accuracy of DiffSeg for metal segmentation of simulated data was 97.89% and that of DSC was 95.45%. The mask shape obtained by threshold segmentation covered the ground truth and DSCs were 82.92% and 84.19% for threshold segmentation based on 2500 HU and 3000 HU. Evaluation metrics and visualization results show that DiffSeg performs better than other classical deep learning networks, especially for clinical CT, artifact data, and phantom data. CONCLUSION: DiffSeg efficiently and robustly segments metal masks in artifact data with conditional dynamic coding and GFParser. Future work will involve embedding the metal segmentation model in metal artifact reduction to improve the reduction effect.

Artifact suppression for breast specimen imaging in micro CBCT using deep learning.

BACKGROUND: Cone-beam computed tomography (CBCT) has been introduced for breast-specimen imaging to identify a free resection margin of abnormal tissues in breast conservation. As well-known, typical micro CT consumes long acquisition and computation times. One simple solution to reduce the acquisition scan time is to decrease of the number of projections, but this method generates streak artifacts on breast specimen images. Furthermore, the presence of a metallic-needle marker on a breast specimen causes metal artifacts that are prominently visible in the images. In this work, we propose a deep learning-based approach for suppressing both streak and metal artifacts in CBCT. METHODS: In this work, sinogram datasets acquired from CBCT and a small number of projections containing metal objects were used. The sinogram was first modified by removing metal objects and up sampling in the angular direction. Then, the modified sinogram was initialized by linear interpolation and synthesized by a modified neural network model based on a U-Net structure. To obtain the reconstructed images, the synthesized sinogram was reconstructed using the traditional filtered backprojection (FBP) approach. The remaining residual artifacts on the images were further handled by another neural network model, ResU-Net. The corresponding denoised image was combined with the extracted metal objects in the same data positions to produce the final results. RESULTS: The image quality of the reconstructed images from the proposed method was improved better than the images from the conventional FBP, iterative reconstruction (IR), sinogram with linear interpolation, denoise with ResU-Net, sinogram with U-Net. The proposed method yielded 3.6 times higher contrast-to-noise ratio, 1.3 times higher peak signal-to-noise ratio, and 1.4 times higher structural similarity index (SSIM) than the traditional technique. Soft tissues around the marker on the images showed good improvement, and the mainly severe artifacts on the images were significantly reduced and regulated by the proposed. CONCLUSIONS: Our proposed method performs well reducing streak and metal artifacts in the CBCT reconstructed images, thus improving the overall breast specimen images. This would be beneficial for clinical use.

The role of conventionality and design in children's function judgments about malfunctioning artifacts.

This study investigated the individual influences of conventionality and designer's intent on function judgments of possibly malfunctioning artifacts. Children aged 4 and 5 years and 6 to 8 years were presented with stories about an artifact with two equally plausible functions, one labeled as either conventional or designed. Subsequently, a character attempted to use the artifact for the cued function, which resulted in either malfunction or successful use. The children's task was to identify the real function of the artifact. When the use attempt succeeded, 4- and 5-year-olds preferred conventional functions to the alternative (but did not show a clear preference between design functions and the alternative), and 6- to 8-year-olds preferred conventional and designed functions to the alternative. In case of malfunction, children's choices were at chance, where the effect of either conventional or design cues was less salient. This contrasts with a baseline condition where children avoided the malfunctioning alternatives. Presenting additional cues about an artifact's function can affect function judgments in cases of malfunction.