Volumetric Imaging Research Articles

Volumetric Imaging From Raman Perspective: Review and Prospect

AbstractVolumetric imaging, which supports quantitative and comprehensive assessment of a 3D sample from an entire volume, has attracted tremendous attention in biomedical research. Fluorescence imaging techniques, such as optical sectioning and light sheet microscopy, enable to reconstruct the 3D distribution of chemicals within a sample. However, current methods rely on exogenous labels, from which considerable perturbation may be introduced in living systems. Raman imaging offers a feasible solution to visualize components in biological samples in a label‐free manner. Besides, the integration of Raman microscopy with 3D approaches will benefit the research of biomedical samples on novel devices, which is dominated by the strongly enhanced spatial resolution, imaging speed, and overall field of view as well as complemented more details of samples. In this overview, recent achievements in 3D visualization of biological samples from the Raman perspective, are explored including scanning mechanism, light sheet, tomography strategy, compressive sensing, holography, and tissue clearing. Importantly, these platforms are compatible with biomedical research, thus allowing the imaging of chemical constituents and the distribution of samples in a whole volume. As a unique volumetric imaging tool for biological discovery, these methods may provide a strategy to accelerate new discoveries across diverse fields of research.

Evaluation of Volumetric Magnetic Resonance Imaging in Determining the Indication for Total Neoadjuvant Therapy in Rectal Cancer.

This study aims to evaluate the relationship between volumetric measurements of residual tumor via magnetic resonance imaging (MRI) and pathologic complete response (pCR) in rectal cancer patients undergoing neoadjuvant chemoradiotherapy (nCRT). Patients with locally advanced rectal cancer who had pelvic MRI for clinical staging and completed nCRT followed by radical resection were included. Two experienced radiologists measured tumor volume on MRI obtained before and after nCRT. We compared the pre- and post-CRT tumor volume and measured tumor volume reduction rates. The median value of tumor volume reduction rate in all patients was 64.7% (min-max - 81.1-98.1%). When the relationship between tumor volume and tumor regression grade (TRG) after nCRT was assessed, it was found that 18 of 21 (86%) patients with a good response (TRG 1) had a post-CRT tumor volume of ≤ 8 cm3 (p = 0.001). While 9 of 10 patients with pCR after nCRT had a tumor volume of ≤ 8 cm3, one patient had pCR despite having a tumor volume greater than 8 cm3 (p = 0.015). The correlation between post-nCRT residual tumor volume and pCR underscores the potential of volumetric MRI as a predictive tool in tailoring rectal cancer treatment. For patients with residual tumor volumes greater than 8 cm3, extending neoadjuvant chemotherapy as part of TNT may enhance the likelihood of achieving pCR. This approach advocates for a more personalized treatment strategy, potentially optimizing outcomes for rectal cancer patients.

Impact of hydrothermal aging on microstructure transformation in Poly(L‐lactide) nonwovens under tension in condition close to a living organism

AbstractThe analysis of mechanical properties and structure of bioresorbable polymer nonwoven materials is an important area of research in the medical industry, the properties and structure of which directly affect the processes of cellular activity. In this work, the processes of reorganization of the fibrous microstructure of poly(l‐lactide) nonwoven materials under uniaxial tension in a water environment were investigated. The study which included volumetric ultrasound imaging, mechanical testing, differential scanning calorimetry, X‐ray diffraction, and melting rate measurements was the first attempt to identify correlations between the mechanical behavior of fibrous meshes and changes in the supramolecular structure of the polymer during 3 months of hydrothermal aging T = 37°C. An increase in crystallinity by 4%, a shift of glass transition temperature by 4°C, and a 2 times increase in melt flow rate under hydrolysis were indicated degradation of the amorphous phase. Local degradation of the amorphous phase of fibers led to the formation of surface cracks, an increase in the number of microcracks during hydrothermal aging resulted in a decrease in the mobility of fibers in the volume of the nonwoven material and a decrease in the elasticity of the entire nonwoven material, which was revealed using the volume ultrasound imaging and optical microphotographs.

BIOM-43. SOMATICTP53, PIK3R1, NF1 ORTERT MUTATIONS ARE ASSOCIATED WITH INFERIOR CLINICAL OUTCOME IN H3K27M-ALTERED DIFFUSE MIDLINE GLIOMA: AN INTERNATIONAL, MULTI-INSTITUTIONAL STUDY

Abstract BACKGROUND H3K27-altered diffuse midline gliomas (DMGs) have poor prognosis with no standard of care therapy beyond radiation (RT). While RT prolongs survival, not all patients respond. Molecular biomarkers can be a strategy to predict RT response and thus patient outcomes. METHODS We performed a retrospective analysis of patients with biopsy-proven H3K27M-altered DMG between 2013-2023 from six US medical centers and the DMG Center in Zurich. Patients with tumor genomic sequencing and completion of RT were eligible. Genomic alterations were evaluated for somatic mutations, fusions, and chromosomal instability. Cox proportional hazard models were used to evaluate associations between genomic alterations and survival. Multivariate analysis included all significant variables at P <0.1 in initial analysis, including age at diagnosis, tumor location, TP53 and PIK3R1 alterations. RESULTS 297 patients (135 female; median age 8.3 years; range 0.2-71.4 years) were included. Median progression-free survival (PFS) and overall survival (OS) was 7.6 months (95%CI: 6.9-8.6) and 14.0 months (95%CI: 12.9-15.7). In univariate analysis, TP53 or PIK3R1 status correlated with shorter OS (TP53-mutant 12.5 vs. TP53-wildtype 17.5 months; HR=1.5; 95%CI: (1.1-2.0), P= 0.005); (PIK3R1-mutant 12.6 vs. 14.5 months; HR=1.9, 95%CI: (1.1-3.4), P = 0.03). Multivariate analysis corroborated TP53-mutant status with poorer OS (HR=1.5; 95%CI: (1.2-2.0), P= 0.003). Subgroup univariate analysis of pontine DMG patients showed poorer OS with TP53, NF1, or TERT mutations (TP53-mutant 11.9 vs. 15.2 months; HR= 1.6; 95%CI: (1.1-2.3), P= 0.02); (NF1-mutant 8.4 vs. 13.6 months; HR= 2.3; 95%CI: (1.1-5.0), P=0.03); (TERT 8.5 vs. 13.6 months; HR= 2.5; 95%CI: (1.1-5.7), P= 0.03). Subsequent multivariate analysis corroborated the association of TERT mutations with poorer OS in pontine DMG (HR=2.5; 95%CI:1.05, 5.9, P= 0.03). CONCLUSIONS This is the largest cohort of H3K27M-altered DMG patients with volumetric imaging analysis ongoing. Taken together, our data suggests these genetic alterations can risk-stratify patients for RT and future investigations of radiosensitizers targeting these alterations may improve survival.

Three-dimensional random-access confocal microscopy with 3D remote focusing system.

Understanding biological activities in cells or deep tissues requires high-speed three-dimensional (3D) imaging. Substantial progress has been made with the emergence of 3D random-access microscopy. However, current solutions for fast 3D random-access imaging remain complex and costly. Herein we propose a simple, cost-effective, and fast 3D random-access confocal microscopy with remote focusing system. Our system shows isotropic response times across the x, y, and z axes, with a 34-fold improvement in axial response time over traditional piezo stages. We demonstrate its volumetric imaging performance with fluorescent particles and live cells. Furthermore, we validate the 3D random-access imaging capability of this system by continuously monitoring the signals in three different planes, showing a refresh rate of 500 Hz on two different positions in 3D. The simplicity, versatility, and affordability of our system promise widespread applications in research and industry.

Stereo slit-scanning tomography of the anterior segment of the human eye

We demonstrate a new tomographic imaging device for 2D cross-sectional and 3D volumetric images of the anterior eye segment. The optical system combines optical sectioning with a stereoscopic camera setup to determine the true spatial location of the ocular structures. Moreover, we propose a calibration procedure to estimate the triangulation function that links the stereo camera pixel indices with the eye-referenced 3D spatial coordinates. The proposed instrument will image the entire anterior chamber and contiguous structures, including the corneal limbus, sclera and eyelids. Furthermore, the system can obtain corneal topography. Finally, we studied the repeatability of the instrument and its agreement with a commercial Scheimpflug imaging tomographer in a group of healthy subjects.

Full-view volumetric photoacoustic imaging using a hemispheric transducer array combined with an acoustic reflector

Full-view volumetric photoacoustic imaging using a hemispheric transducer array combined with an acoustic reflector

ReNeu: A Pivotal, Phase IIb Trial of Mirdametinib in Adults and Children With Symptomatic Neurofibromatosis Type 1-Associated Plexiform Neurofibroma.

Pharmacologic therapies for neurofibromatosis type 1-associated plexiform neurofibromas (NF1-PNs) are limited; currently, none are US Food and Drug Administration-approved for adults. ReNeu is an open-label, multicenter, pivotal, phase IIb trial of mirdametinib in 58 adults (≥18 years of age) and 56 children (2 to 17 years of age) with NF1-PN causing significant morbidities. Patients received mirdametinib capsules or tablets for oral suspension (2 mg/m2 twice daily, maximum 4 mg twice daily), regardless of food intake, in 3 weeks on/1 week off 28-day cycles. The primary end point was confirmed objective response rate (ORR; proportion of patients with a ≥20% reduction of target PN volume from baseline on consecutive scans during the 24-cycle treatment phase) assessed by blinded independent central review (BICR) of volumetric magnetic resonance imaging. Twenty-four of 58 adults (41%) and 29 of 56 children (52%) had a BICR-confirmed objective response during the 24-cycle treatment phase; in addition, two adults and one child had confirmed responses during long-term follow-up. Median (range) target PN volumetric best response was -41% (-90 to 13) in adults and -42% (-91 to 48) in children. Both cohorts reported significant and clinically meaningful improvement in patient- or parent proxy-reported outcome measures of worst tumor pain severity, pain interference, and health-related quality of life (HRQOL) that began early and were sustained during treatment. The most commonly reported treatment-related adverse events were dermatitis acneiform, diarrhea, and nausea in adults and dermatitis acneiform, diarrhea, and paronychia in children. In ReNeu, the largest multicenter NF1-PN trial reported to date, mirdametinib treatment demonstrated significant confirmed ORRs by BICR, deep and durable PN volume reductions, and early, sustained, and clinically meaningful improvement in pain and HRQOL. Mirdametinib was well-tolerated in adults and children.

Fast and light-efficient remote focusing for volumetric voltage imaging

Voltage imaging holds great potential for biomedical research by enabling noninvasive recording of the electrical activity of excitable cells such as neurons or cardiomyocytes. Camera-based detection can record from hundreds of cells in parallel, but imaging entire volumes is limited by the need to focus through the sample at high speeds. Remote focusing techniques can remedy this drawback, but have so far been either too slow or light-inefficient. Here, we introduce flipped image remote focusing, a remote focusing method that doubles the light efficiency compared to conventional beamsplitter-based techniques and enables high-speed volumetric voltage imaging at 500 volumes/s. We show the potential of our approach by combining it with light sheet imaging in the zebrafish spinal cord to record from >100 spontaneously active neurons in parallel.

Attack-Defending Contrastive Learning for Volumetric Medical Image Zero-Watermarking

Zero-watermarking is an emerging distortion-free copyright protection method for volumetric medical images. However, achieving both robustness against various malicious attacks and distinguishability between individual images remains challenging. In this paper, we propose a novel attack-defending contrastive learning zero-watermarking scheme (ADCL-ZW) to tackle the above challenge using deep learning-based representations. In our approach, we design an attack-defending data enrichment mechanism to enhance the watermarking robustness by generating a large number of image samples under various watermarking attacks. Subsequently, features for both watermarking distinguishability and robustness are enhanced through application of a contrastive loss. In particular, we implement a dual-stream Siamese network architecture to effectively handle both signal attacks and geometric attacks in order to enhance the wartermarking performance. Experimental results demonstrate that ADCL-ZW achieves stronger watermarking robustness and a better tradeoff between watermarking robustness and distinguishability compared with state-of-the art zero-watermarking methods. One of the highlighted metrics the false negative rate of ADCL-ZW achieves 0.01 when a fixed false positive rate is set to 1%, which is more than 13.3 times better than the benchmark methods.

Long-Axial-Range Double-Helix Point Spread Functions for 3D Volumetric Super-Resolution Imaging.

Single-molecule localization microscopy (SMLM) is a powerful tool for observing structures beyond the diffraction limit of light. Combining SMLM with engineered point spread functions (PSFs) enables 3D imaging over an extended axial range, as has been demonstrated for super-resolution imaging of various cellular structures. However, super-resolving structures in 3D in thick samples, such as whole mammalian cells, remains challenging as it typically requires acquisition and postprocessing stitching of multiple slices to cover the entire sample volume or more complex analysis of the data. Here, we demonstrate how the imaging and analysis workflows can be simplified by 3D single-molecule super-resolution imaging with long-axial-range double-helix (DH)-PSFs. First, we experimentally benchmark the localization precisions of short- and long-axial-range DH-PSFs at different signal-to-background ratios by imaging fluorescent beads. The performance of the DH-PSFs in terms of achievable resolution and imaging speed was then quantified for 3D single-molecule super-resolution imaging of mammalian cells by DNA-PAINT imaging of nuclear lamina protein lamin B1 in U-2 OS cells. Furthermore, we demonstrate how the use of a deep-learning-based algorithm allows the localization of dense emitters, drastically improving the achievable imaging speed and resolution. Our data demonstrate that using long-axial-range DH-PSFs offers stitching-free, 3D super-resolution imaging of whole mammalian cells, simplifying the experimental and analysis procedures for obtaining volumetric nanoscale structural information.

Efficient and Accurate Semi-Automatic Neuron Tracing with Extended Reality.

Neuron tracing, alternately referred to as neuron reconstruction, is the procedure for extracting the digital representation of the three-dimensional neuronal morphology from stacks of microscopic images. Achieving accurate neuron tracing is critical for profiling the neuroanatomical structure at single-cell level and analyzing the neuronal circuits and projections at whole-brain scale. However, the process often demands substantial human involvement and represents a nontrivial task. Conventional solutions towards neuron tracing often contend with challenges such as non-intuitive user interactions, suboptimal data generation throughput, and ambiguous visualization. In this paper, we introduce a novel method that leverages the power of extended reality (XR) for intuitive and progressive semi-automatic neuron tracing in real time. In our method, we have defined a set of interactors for controllable and efficient interactions for neuron tracing in an immersive environment. We have also developed a GPU-accelerated automatic tracing algorithm that can generate updated neuron reconstruction in real time. In addition, we have built a visualizer for fast and improved visual experience, particularly when working with both volumetric images and 3D objects. Our method has been successfully implemented with one virtual reality (VR) headset and one augmented reality (AR) headset with satisfying results achieved. We also conducted two user studies and proved the effectiveness of the interactors and the efficiency of our method in comparison with other approaches for neuron tracing.

A calibration-informed deep learning model for three-dimensional particle reconstruction of volumetric particle image velocimetry

Accurately reconstructing three-dimensional particle fields is essential in fluid velocity measurement research. This study addresses the limitations of current three-dimensional (3D) particle reconstruction methods, such as computational efficiency, precision at high particle density, and particle morphology issues, by introducing a calibration-informed deep learning model named the calibrated pixel to voxel convolutional neural network (CPV-CNN) for 3D Particle Reconstruction. This innovative neural network framework employs a unique Gaussian attention mechanism that bridges pixels and voxels, enabling the mapping of pixel features from two-dimensional (2D) particle images to 3D voxel features. This approach eliminates the need for an initial particle field for particle reconstruction, while significantly enhancing reconstruction efficiency. Additionally, the neural network incorporates camera calibration parameters and the physical coordinates of the reconstructed domain, thereby improving the model's generalization capability and flexibility. Numerical experiments demonstrate that CPV-CNN delivers superior results in terms of accuracy, generalization, and robustness in 3D particle reconstruction. The reconstructed particles exhibit favorable morphology, without the elongation issues commonly observed with conventional methods. This achievement illustrates a practical particle reconstruction algorithm based on artificial intelligence (AI) techniques and represents an important step toward developing an end-to-end AI-based particle reconstruction method in the future.

A computationally efficient queue-based algorithm for simulating volume-controlled drainage under the influence of gravity on volumetric images of porous materials

Simulating non-wetting fluid invasion in volumetric images of porous materials is of broad interest in applications as diverse as electrochemical devices and CO2 sequestration. Among available methods, image-based algorithms offer much lower computational cost compared to direct numerical simulations. Recent work has extended image-based methods to incorporate more physics such as gravity and volume-controlled invasion. The present work combines these two developments to develop an image-based invasion percolation algorithm that incorporates the effect of gravity. Additionally, the presented algorithm was developed using a priority queue algorithm to drastically reduce the computational cost of the simulation. The priority queue-based method was validated against previous image-based methods both with and without the effect of gravity, showing identical results. It was also shown that the new method provides a speedup of 20X over the previous image-based methods. Finally, comparison with experimental results at three Bond numbers showed that the model can predict the real invasion process with a high accuracy with and without gravitational effects.

Recognition of autism in subcortical brain volumetric images using autoencoding-based region selection method and Siamese Convolutional Neural Network

Recognition of autism in subcortical brain volumetric images using autoencoding-based region selection method and Siamese Convolutional Neural Network

Ultrafast 3D synthetic aperture imaging with Hadamard-encoded aperiodic interval codes and aperiodic sparse arrays with separate transmitters and receivers

3D synthetic aperture (SA) imaging of volumes can be obtained using sparse 2D ultrasound arrays. However, even with just 256 elements, the volumetric imaging rate can be relatively slow due to having to transmit on each element in succession. Hadamard Aperiodic Interval (HAPI) codes can be used to image the full SA dataset in one extended transmit to speed up the synthetic aperture imaging, but their long nature produces large deadzones if the same elements are used as both transmitters and receivers. In this simulation study, we use a 2D Costas sparse array with separate transmitters and receivers to remedy the deadzone problem, and use it with the HAPI-coded imaging scheme to obtain fully transmit-receive focused, wide field-of-view 3D volumes with high-resolution and high SNR at ultrafast volumetric imaging rates of more than 500 volumes per second, almost nine times faster than non-coded SA imaging with the same imaging parameters. We show similar PSF performance compared to non-coded SA, and a 26 dB improvement in SNR with order-256 HAPI codes. We also present cyst simulations showing similar contrast for the HAPI-coded SA method compared to non-coded SA in the context of no noise, and improved contrast in the context of noise.

Hyperspectral unmixing for Raman spectroscopy via physics-constrained autoencoders

Raman spectroscopy is widely used across scientific domains to characterize the chemical composition of samples in a nondestructive, label-free manner. Many applications entail the unmixing of signals from mixtures of molecular species to identify the individual components present and their proportions, yet conventional methods for chemometrics often struggle with complex mixture scenarios encountered in practice. Here, we develop hyperspectral unmixing algorithms based on autoencoder neural networks, and we systematically validate them using both synthetic and experimental benchmark datasets created in-house. Our results demonstrate that unmixing autoencoders provide improved accuracy, robustness, and efficiency compared to standard unmixing methods. We also showcase the applicability of autoencoders to complex biological settings by showing improved biochemical characterization of volumetric Raman imaging data from a monocytic cell.

Phosphorylated tau protein serum levels increase over time in patients with chronic heart failure

Abstract Background/Introduction Amongst various potential biomarkers associated with cognitive deficits, phosphorylated Tau (pTau) appears to link brain and cardiac abnormalities through a systemic tauopathy pathway. Purpose A recent report on the potential importance of myocardial pTau in chronic heart failure (HF) prompted the here described longitudinal quantification of circulating pTau serum levels in patients with HF. We hypothesized that serum pTau accumulates in HF and is associated with markers of myocardial dysfunction. Methods Eligible patients within the prospective, investigator-initiated, monocentric follow-up study Cognition.Matters-HF were older than 18 years, suffered from stable chronic HF and were free from major neurological or psychiatric disorders. Beyond the cardiological assessment including transthoracic echocardiography and six minute walking distance (6-MWD), investigations at baseline, 1 year and 3 years comprised extensive, domain-specific psychological testing and volumetric brain magnetic resonance imaging. Serum pTau was measured using the pTau181 advantage kit. Results Serum samples were available from 78 patients. Mean age was 63±10 years and 87% were men. Serum pTau longitudinally increased from a median of 1.05 (quartiles 0.26, 1.21) pg/ml at baseline to 1.84 (1.36, 3.60) pg/ml after 3 years (p<0.001). During that time period, LVEF, NT-proBNP, 6-MWD and the hippocampal volume remained unaltered, whereas global brain volume and cortical thickness shrank age-appropriately. Cognitive testing revealed that domain-specific T-scores within 36 months remained stable for attentional intensity and executive functioning, and even improved for memory. When we entered baseline values of age and above-mentioned cardiac, brain-volumetric, and cognitive parameters into a multivariable regression model predicting log-transformed pTau, only age (β=0.34), NT-proBNP (β=0.24) and GBV (β=0.26) were independently associated with pTau serum levels (R2=0.18). Consistently, at 36 months, the same predictors were selected by the model (R2=0.29): age (β=0.41), NT-proBNP (β=0.43), and global brain volume (β=0.26). Moreover, higher baseline pTau (β=0.23) and lower 6-MWD (β=-0.39) independently predicted ΔpTau with an explained variance (R2) of 0.24. Conclusions We observed a prominent increase of serum pTau over time, which was predicted by prevalent myocardial dysfunction. Moreover, absolute NT-proBNP levels were independently associated with absolute pTau serum levels, along with age and global brain volume. Mechanistically, phosphorylation of cardiac tau is thought to destabilize its interaction with microtubules causing microtubule detyronisation and increased myocardial stiffness through enhancing the mechanical resistance of contracting cardiomyocytes. The etiological role of pTau in the development of HF and the potential of serum pTau as a novel biomarker of chronic HF warrants further studies.

Highly demarcated structural alterations in the brain and impaired social incentive learning in Tbx1 heterozygous mice.

Copy number variants (CNVs) are robustly associated with psychiatric disorders and changes in brain structures. However, because CNVs contain many genes, the precise gene-phenotype relationship remains unclear. Although various volumetric alterations in the brains of 22q11.2 CNV carriers have been identified in humans and mouse models, it is unknown how each gene encoded in the 22q11.2 region contributes to structural alterations, associated mental illnesses, and their dimensions. Our previous studies identified Tbx1, a T-box family transcription factor encoded in the 22q11.2 CNV, as a driver gene for social interaction and communication, spatial and working memory, and cognitive flexibility. However, it remains unclear how TBX1 impacts the volumes of various brain regions and their functionally linked behavioral dimensions. In this study, we used volumetric magnetic resonance imaging analysis to comprehensively evaluate brain region volumes and behavioral alterations relevant to affected structures in congenic Tbx1 heterozygous mice. Our data showed that the volumes of the anterior and posterior portions of the amygdaloid complex and its surrounding cortical regions were most robustly reduced in Tbx1 heterozygous mice. In an amygdala-dependent task, Tbx1 heterozygous mice were impaired in their ability to learn the incentive value of a social partner. The volumes of the primary and secondary auditory cortexes were increased, and acoustic, but not non-acoustic, sensorimotor gating was impaired in Tbx1 heterozygous mice. Our findings identify the brain's regional volume alterations and their relevant behavioral dimensions associated with Tbx1 heterozygosity.

Modern Methods of Fluorescence Nanoscopy in Biology

Optical microscopy has undergone significant changes in recent decades due to the breaking of the diffraction limit of optical resolution and the development of high-resolution imaging techniques, which are collectively known as fluorescence nanoscopy. These techniques allow researchers to observe biological structures and processes at a nanoscale level of detail, revealing previously hidden features and aiding in answering fundamental biological questions. Among the advanced methods of fluorescent nanoscopy are: STED (Stimulated Emission Depletion Microscopy), STORM (STochastic Optical Reconstruction Microscopy), PALM (Photo-activated Localization Microscopy), TIRF (Total Internal Reflection Fluorescence), SIM (Structured Illumination Microscopy), MINFLUX (Minimal Photon Fluxes), PAINT (Points Accumulation for Imaging in Nanoscale Topography) и RESOLFT (REversible Saturable Optical Fluorescence Transitions) and others. In addition, most of these methods make it possible to obtain volumetric (3D) images of the objects under study. In this review, we will look at the principles of these methods, their advantages and disadvantages, and their application in biological researches.