High-resolution 3D Imaging Research Articles

EDTP enhances and protects the fluorescent signal of GFP in cleared and expanded tissues

Advanced 3D high-resolution imaging techniques are essential for investigating biological challenges, such as neural circuit analysis and tumor microenvironment in intact tissues. However, the fluorescence signal emitted by endogenous fluorescent proteins in cleared or expanded biological samples gradually diminishes with repeated irradiation and prolonged imaging, compromising its ability to accurately depict the underlying scientific problem. We have developed a strategy to preserve fluorescence in cleared and expanded tissue samples during prolonged high-resolution three-dimensional imaging. We evaluated various compounds at different concentrations to determine their ability to enhance fluorescence intensity and resistance to photobleaching while maintaining the structural integrity of the tissue. Specifically, we investigated the impact of EDTP utilization on GFP, as it has been observed to significantly improve fluorescence intensity, resistance to photobleaching, and maintain fluorescence during extended room temperature storage. This breakthrough will facilitate extended hydrophilic and hydrogel-based clearing and expansion methods for achieving long-term high-resolution 3D imaging of cleared biological tissues by effectively safeguarding fluorescent proteins within the tissue.

Internalisation of immunoglobulin light chains by cardiomyocytes in AL amyloidosis: what can biopsies tell us?

Background Cardiac involvement in systemic light chain amyloidosis (AL) leads to chronic heart failure and is a major prognosis factor. Severe cellular defects are provoked in cardiac cells by tissue-deposited amyloid fibrils of misfolded free immunoglobulin light chains (LCs) and their prefibrillar oligomeric precursors. Objective Understanding the molecular mechanisms behind cardiac cell cytotoxicity is necessary to progress in therapy and to improve patient management. One key question is how extracellularly deposited molecules exert their toxic action inside cardiac cells. Here we searched for direct evidence of amyloid LC uptake by cardiomyocytes in patient biopsies. Methods We immunolocalized LCs in cardiac biopsies from four AL cardiac amyloidosis patients and analysed histopathological images by high resolution confocal microscopy and 3D image reconstruction. Results We show, for the first time directly in patient tissue, the presence of LCs inside cardiomyocytes, and report their proximity to nuclei and to caveolin-3-rich areas. Our observations point to macropinocytosis as a probable mechanism of LC uptake. Conclusions Internalisation of LCs occurs in patient cardiomyocytes. This event could have important consequences for the pathogenesis of the cardiac disease by enabling interactions between amyloid molecules and cellular organelles inducing specific signalling pathways, and might bring new insight regarding treatment.

Supramolecular self-assembling hydrogel based on imidazole/d-sorbitol deep eutectic solvent for tissue clearance

Embedding and tissue clearing with high refractive index reagents are essential for 3D tissue imaging. However, the current liquid-based clearing condition and dye environment suffer from solvent evaporation and photo-bleaching, causing difficulties in maintain the tissue optical and fluorescent features. In traditional embedding technique, paraffin is highly astigmatic and paraffin-tissue complex is opaque; CLARITY series of gel-type tissue transparency methods usually achieve cross-linking of tissue and gel network first, and then active or passive degreasing by using SDS, TritonX-100 and so on, and finally, the tissue achieves a transparent state by refractive index matching. Based on high permeability of deep eutectic solvents (DES) and the optical transparency potential of polyols, this study developed a DES self-assembled hydrogel-based copolymer to embed mouse tissue for clearing and imaging prepared with imidazole and d-sorbitol. In addition to preserving the high optic transparency of the tissue, the DES hydrogel system is compatible with multiple fluorescence labeling, particularly lipophilic dyes. This DES hydrogel system provides a unique opportunity for simultaneous tissue embedding and clearing. The self-assembled hydrogel achieves 3D imaging at a solid state, and 2D images can be obtained through slicing after 3D imaging of complete organs. Due to its temperature dependent hydrogel properties, the hydrogel-tissue complex achieves gel-sol transition and allows tissue reuse. This transparent and hydrogel condition provides a friendly tissue and cellular environment to facilitate high resolution 3D imaging, preservation, transfer, and sharing among laboratories to investigate the morphologies of interest in experimental and clinical conditions.

High-Resolution Magnetic Resonance Neurography at 7T: A Pilot Study of Hand Innervation.

The emergence of 7T clinical MRI technology has sparked our interest in its ability to discern the complex structures of the hand. Our primary objective was to assess the sensory and motor nerve structures of the hand, specifically nerves and Pacinian corpuscles, with the dual purpose of aiding diagnostic endeavors and supporting reconstructive surgical procedures. Ethical approval was obtained to carry out 7T MRI scans on a cohort of volunteers. Four volunteers assumed a prone position, with their hands (N = 8) positioned in a "superman" posture. To immobilize and maintain the hand in a strictly horizontal position, it was affixed to a plastic plate. Passive B0 shimming was implemented. Once high-resolution 3D images had been acquired using a multi-transmit head coil, advanced post-processing techniques were used to meticulously delineate the nerve fiber networks and mechanoreceptors. Across all participants, digital nerves were consistently located on the phalanges area, on average, between 2.5 and 3.5 mm beneath the skin, except within flexion folds where the nerve was approximately 1.8 mm from the surface. On the phalanges area, the mean distance from digital nerves to joints was approximately 1.5 mm. The nerves of the fingers were closer to the bone than to the surface of the skin. Furthermore, Pacinian corpuscles exhibited a notable clustering primarily within the metacarpal zone, situated on the palmar aspect. Our study yielded promising results, successfully reconstructing and meticulously describing the anatomy of nerve fibers spanning from the carpus to the digital nerve division, alongside the identification of Pacinian corpuscles, in four healthy volunteers (eight hands).

Segmentation and Multi-Timepoint Tracking of 3D Cancer Organoids from Optical Coherence Tomography Images Using Deep Neural Networks.

Recent years have ushered in a transformative era in in vitro modeling with the advent of organoids, three-dimensional structures derived from stem cells or patient tumor cells. Still, fully harnessing the potential of organoids requires advanced imaging technologies and analytical tools to quantitatively monitor organoid growth. Optical coherence tomography (OCT) is a promising imaging modality for organoid analysis due to its high-resolution, label-free, non-destructive, and real-time 3D imaging capabilities, but accurately identifying and quantifying organoids in OCT images remain challenging due to various factors. Here, we propose an automatic deep learning-based pipeline with convolutional neural networks that synergistically includes optimized preprocessing steps, the implementation of a state-of-the-art deep learning model, and ad-hoc postprocessing methods, showcasing good generalizability and tracking capabilities over an extended period of 13 days. The proposed tracking algorithm thoroughly documents organoid evolution, utilizing reference volumes, a dual branch analysis, key attribute evaluation, and probability scoring for match identification. The proposed comprehensive approach enables the accurate tracking of organoid growth and morphological changes over time, advancing organoid analysis and serving as a solid foundation for future studies for drug screening and tumor drug sensitivity detection based on organoids.

Advancements in Dental Imaging: A Technological Renaissance in Diagnosis and Treatment Planning

Dental imaging technology has undergone significant advancements in recent years, offering dentists unprecedented tools for accurate diagnosis and treatment planning. This article provides a comprehensive overview of the latest innovations in dental imaging and their clinical applications. Cone Beam Computed Tomography (CBCT) has revolutionized imaging by providing high-resolution 3D images with minimal radiation exposure. Its versatility in applications, from implant planning to TMJ analysis, makes it an indispensable tool in modern dentistry. Studies have shown its effectiveness in detecting root fractures and periapical lesions, enhancing diagnostic precision. Digital Radiography has replaced traditional film-based systems, offering benefits like reduced radiation doses and faster image acquisition. Its superior diagnostic capabilities in detecting caries and periodontal conditions enable early intervention and preventive strategies, improving patient outcomes. Intraoral Scanners have transformed impression-taking, eliminating the need for messy materials and improving patient comfort. Their accuracy in capturing detailed intraoral structures ensures precise fit and aesthetics in crown and bridge restorations, enhancing overall treatment quality. Optical Coherence Tomography (OCT) has gained attention for its non-invasive, high-resolution imaging of dental tissues. Its utility in detecting early caries lesions, evaluating periodontal tissues, and assessing adhesive interfaces in restorations supports conservative treatment approaches and long-term restoration success. Artificial Intelligence (AI) algorithms are being integrated into dental imaging, enhancing diagnostic capabilities and streamlining workflow. AI’s role in image analysis, risk assessment, and treatment planning opens avenues for personalized dentistry and predictive outcomes, ultimately improving patient care. In conclusion, the rapid advancements in dental imaging technologies have transformed dental diagnostics and treatment planning. Integrating these innovations into clinical practice not only improves diagnostic accuracy and treatment outcomes but also enhances patient experience and satisfaction. Continued research and technological advancements promise further enhancements in dental imaging capabilities, paving the way for optimized patient care in the future.

TOBE-Costas arrays for fast high-resolution 3D power Doppler imaging.

2D sparse arrays and row-column arrays are both alternatives to 2D fully-addressed arrays with lower channel counts. Row-column arrays have recently demonstrated fast 3D structural and flow imaging but commonly suffer from high grating lobes or require multiplexing to achieve better quality. 2D sparse arrays enable full-volume acquisitions for each to transmit event, but plane-wave transmissions with them usually lack quality in terms of uniformity of wavefronts. Here, we propose a novel architecture that combines both types of these arrays in one aperture, enabling imaging using row-column or sparse arrays alone or a hybrid imaging scheme where the row-column array is used in transmission and a 2D sparse array in reception. This hybrid imaging scheme can potentially solve the shortcomings of each of these approaches. The sparse array layout chosen is a Costas array, characterized by having only one element per row and column, facilitating its integration with row-column (TOBE) arrays. We simulate images acquired with TOBE-Costas arrays using the hybrid imaging scheme and compare them to row-column and sparse spiral arrays of equivalent aperture size (128λ×128λ at 7.5 MHz) in ultrafast plane-wave imaging of point targets and 3D power Doppler imaging of synthetic flow phantoms. Our simulation results show that TOBE-Costas arrays exhibit superior resolution and lower side lobe levels compared to plane-wave compounding with row-column arrays. Compared to density-tapered spiral arrays, they provide a larger field of view and finer resolution.

Super-resolution of biomedical volumes with 2D supervision.

Volumetric biomedical microscopy has the potential to increase the diagnostic information extracted from clinical tissue specimens and improve the diagnostic accuracy of both human pathologists and computational pathology models. Unfortunately, barriers to integrating 3-dimensional (3D) volumetric microscopy into clinical medicine include long imaging times, poor depth/z-axis resolution, and an insufficient amount of high-quality volumetric data. Leveraging the abundance of high-resolution 2D microscopy data, we introduce masked slice diffusion for super-resolution (MSDSR), which exploits the inherent equivalence in the data-generating distribution across all spatial dimensions of biological specimens. This intrinsic characteristic allows for super-resolution models trained on high-resolution images from one plane (e.g., XY) to effectively generalize to others (XZ, YZ), overcoming the traditional dependency on orientation. We focus on the application of MSDSR to stimulated Raman histology (SRH), an optical imaging modality for biological specimen analysis and intraoperative diagnosis, characterized by its rapid acquisition of high-resolution 2D images but slow and costly optical z-sectioning. To evaluate MSDSR's efficacy, we introduce a new performance metric, SliceFID, and demonstrate MSDSR's superior performance over baseline models through extensive evaluations. Our findings reveal that MSDSR not only significantly enhances the quality and resolution of 3D volumetric data, but also addresses major obstacles hindering the broader application of 3D volumetric microscopy in clinical diagnostics and biomedical research.

A modular framework for multi-scale tissue imaging and neuronal segmentation.

The development of robust tools for segmenting cellular and sub-cellular neuronal structures lags behind the massive production of high-resolution 3D images of neurons in brain tissue. The challenges are principally related to high neuronal density and low signal-to-noise characteristics in thick samples, as well as the heterogeneity of data acquired with different imaging methods. To address this issue, we design a framework which includes sample preparation for high resolution imaging and image analysis. Specifically, we set up a method for labeling thick samples and develop SENPAI, a scalable algorithm for segmenting neurons at cellular and sub-cellular scales in conventional and super-resolution STimulated Emission Depletion (STED) microscopy images of brain tissues. Further, we propose a validation paradigm for testing segmentation performance when a manual ground-truth may not exhaustively describe neuronal arborization. We show that SENPAI provides accurate multi-scale segmentation, from entire neurons down to spines, outperforming state-of-the-art tools. The framework will empower image processing of complex neuronal circuitries.

Airborne single-photon LiDAR towards a small-sized and low-power payload

Single-photon light detection and ranging (LiDAR) has played an important role in areas ranging from target identification and 3D imaging to remote sensing. Its high sensitivity provides the feasibility of lightweight LiDAR systems for the resource-limited airborne and spaceborne platforms. Here, we design and demonstrate an airborne single-photon LiDAR towards the compact, small-sized, and low-power payload. To reduce the system size, we utilize small telescopes with an optical aperture of 47 mm and develop the sub-pixel scanning approach to enhance the imaging resolution. With the fine scanning mirrors, we validate the super-resolution ability in the ground experiment by surpassing the system’s resolution by 2.5 times and achieve high-resolution 3D imaging in the airborne experiment. To realize low-power LiDAR, we employ photon-efficient computational algorithms and high-quality single-photon avalanche diode (SPAD) arrays. This enables us to reconstruct images from noisy data even under challenging conditions of two signal photons per pixel. Using the airborne single-photon LiDAR system, we demonstrate 3D imaging during daytime over a large area for remote sensing applications and show the capability to reveal the detailed features of various landforms and objects.

High Spatial Resolution 2D Imaging of Current Density and Pressure for Graphene Devices under High Pressure Using Nitrogen-Vacancy Centers in Diamond.

Current density imaging is helpful for discovering interesting electronic phenomena and understanding carrier dynamics, and by combining pressure distributions, several pressure-induced novel physics may be comprehended. In this work, noninvasive, high-resolution two-dimensional images of the current density and pressure gradient for graphene ribbon and hBN-graphene-hBN devices are explored using nitrogen-vacancy (NV) centers in diamond under high pressure. The two-dimensional vector current density is reconstructed by the vector magnetic field mapped by the near-surface NV center layer in the diamond. The current density images accurately and clearly reproduce the complicated structure and current flow of graphene under high pressure. Additionally, the spatial distribution of the pressure is simultaneously mapped, rationalizing the nonuniformity of the current density under high pressure. The current method opens a significant new avenue to investigate electronic transport and conductance variations in two-dimensional materials and electrical devices under high pressure as well as for nondestructive evaluation of semiconductor circuits.

Acto3D: an open-source user-friendly volume rendering software for high-resolution 3D fluorescence imaging in biology.

Advances in fluorescence microscopy and tissue-clearing have revolutionised 3D imaging of fluorescently labelled tissues, organs and embryos. However, the complexity and high cost of existing software and computing solutions limit their widespread adoption, especially by researchers with limited resources. Here, we present Acto3D, an open-source software, designed to streamline the generation and analysis of high-resolution 3D images of targets labelled with multiple fluorescent probes. Acto3D provides an intuitive interface for easy 3D data import and visualisation. Although Acto3D offers straightforward 3D viewing, it performs all computations explicitly, giving users detailed control over the displayed images. Leveraging an integrated graphics processing unit, Acto3D deploys all pixel data to system memory, reducing visualisation latency. This approach facilitates accurate image reconstruction and efficient data processing in 3D, eliminating the need for expensive high-performance computers and dedicated graphics processing units. We have also introduced a method for efficiently extracting lumen structures in 3D. We have validated Acto3D by imaging mouse embryonic structures and by performing 3D reconstruction of pharyngeal arch arteries while preserving fluorescence information. Acto3D is a cost-effective and efficient platform for biological research.

New non-local mean methods for MRI denoising based on global self-similarity between values

Magnetic resonance imaging (MRI) is a non-invasive medical imaging technique that provides high-resolution 3D images and valuable insights into human tissue conditions. Even at present, the refinement of denoising methods for MRI remains a crucial concern for improving the quality of the images. This study aims to improve the prefiltered rotationally invariant non-local principal component analysis (PRI-NL-PCA) algorithm. We relaxed the original restrictions using particle swarm optimization to determine optimal parameters for the PCA part of the original algorithm. In addition, we adjusted the prefiltered rotationally invariant non-local mean (PRI-NLM) part by traversing the signal intensities of voxels instead of their spatial positions to reduce duplicate calculations and expand the search volume to the whole image when estimating voxels’ signal intensities. The new method demonstrated superior denoising performance compared to the original approach. Moreover, in most cases, the new algorithm ran faster. Furthermore, our proposed method can also be applied to process Gaussian noise in natural images and has the potential to enhance other NLM-based denoising algorithms.

Active Dual Line-Laser Scanning for Depth Imaging of Piled Agricultural Commodities for Itemized Processing Lines.

The accurate depth imaging of piled products provides essential perception for the automated selection of individual objects that require itemized food processing, such as fish, crabs, or fruit. Traditional depth imaging techniques, such as Time-of-Flight and stereoscopy, lack the necessary depth resolution for imaging small items, such as food commodities. Although structured light methods such as laser triangulation have high depth resolution, they depend on conveyor motion for depth scanning. This manuscript introduces an active dual line-laser scanning system for depth imaging static piled items, such as a pile of crabs on a table, eliminating the need for conveyor motion to generate high-resolution 3D images. This advancement benefits robotic perception for loading individual items from a pile for itemized food processing. Leveraging a unique geometrical configuration and laser redundancy, the dual-laser strategy overcomes occlusions while reconstructing a large field of view (FOV) from a long working distance. We achieved a depth reconstruction MSE of 0.3 mm and an STD of 0.5 mm on a symmetrical pyramid stage. The proposed system demonstrates that laser scanners can produce depth maps of complex items, such as piled Chesapeake Blue Crab and White Button mushrooms. This technology enables 3D perception for automated processing lines and offers broad applicability for quality inspection, sorting, and handling of piled products.

X-Ray-Based 3D Histopathology of the Kidney Using Cryogenic Contrast-Enhanced MicroCT.

The kidney's microstructure, which comprises a highly convoluted tubular and vascular network, can only be partially revealed using classical 2D histology. Considering that the kidney's microstructure is closely related to its function and is often affected by pathologies, there is a need for powerful and high-resolution 3D imaging techniques to visualize the microstructure. Here, we present how cryogenic contrast-enhanced microCT (cryo-CECT) allowed 3D visualization of glomeruli, tubuli, and vasculature. By comparing different contrast-enhancing staining agents and freezing protocols, we found that the preferred sample preparation protocol was the combination of staining with 1:2 hafnium(IV)-substituted Wells-Dawson polyoxometalate and freezing by submersion in isopentane at -78°C. This optimized protocol showed to be highly sensitive, allowing to detect small pathology-induced microstructural changes in a mouse model of mild trauma-related acute kidney injury after thorax trauma and hemorrhagic shock. In summary, we demonstrated that cryo-CECT is an effective 3D histopathological tool that allows to enhance our understanding of kidney tissue microstructure and their related function.

Abstract 2593: Spatial multi-omics profiling of tumor cell phenotypes in primary cutaneous melanoma at single-cell resolution

Abstract Primary cutaneous melanomas develop in stages from melanoma precursor cells that may progress to melanoma in situ (MIS) and eventually to invasive disease. Molecular changes, such as tumor cell state switches from melanocytic to undifferentiated and neural-crest-like phenotypes, have been associated with the development of melanoma metastases and therapeutic resistance. However, it is unknown whether cell states or gene expression changes enriched in advanced tumors exist at the premalignant stage and if they can elicit tumor-infiltrating lymphocytes (TILs). To address this gap, we analyzed a cohort of clinical samples from 43 patients with primary cutaneous melanoma using whole-slide cyclic multiplex immunofluorescence imaging (CyCIF), morphology-guided micro-regional RNA sequencing, and high-resolution 3D imaging. Each specimen contained multiple histologically-distinct regions representing a progression axis from normal to precursor to melanoma in situ to invasion. Subsequently, we examined the molecular profiles of both atypical melanocytes and tumor cells, and the gene expression and tumor microenvironmental (TME) changes that occurred during these progression stages. We identified major intra- and inter-specimen heterogeneity in the tumor intrinsic and extrinsic features across progression stages. Multiple tumor samples contained regions where publicly available gene signatures linked to both melanocytic and undifferentiated cell phenotypes were enriched. CyCIF analysis confirmed that various tumor cell phenotypes can coexist in close proximity to each other in early-stage untreated melanomas, and that the majority of undifferentiated tumor cells were located within regions of dermal invasion. Moreover, the cellular neighborhoods around undifferentiated tumor cells had a higher proportion of CD8+ T cells and cells of myeloid lineage compared to the neighborhoods around melanocytic tumor cell phenotypes. When assessing the localization and abundance of various tumor cell phenotypes, the levels of spatial and regional heterogeneity increased proportionally along normal to premalignant to malignant progression. Furthermore, the regional entropy of tumor cell phenotypes decreased along tumor depth in the majority (63%) of the samples, and even the melanoma in situ regions showed varying levels of spatial heterogeneity. Our in-depth multimodal molecular analyses highlight the presence of spatial heterogeneity among tumor cell phenotypes as well as the organization of early-stage primary melanomas, and are suggestive of tumor cell adaptation to the local environment. Citation Format: Tuulia Vallius, Edward Novikov, Ajit Nirmal Johnson, Shi Yingxiao, Roxanne Pelletier, Shishir Pant, Zoltan Maliga, Alyce Chen, Clarence Yapp, Sabrina Chan, Christine Lian, George F. Murphy, Sandro Santagata, Peter Sorger. Spatial multi-omics profiling of tumor cell phenotypes in primary cutaneous melanoma at single-cell resolution [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2593.

Abstract 4179: Magnetic resonance imaging and bioluminescence imaging for evaluating tumor burden in orthotopic glioblastoma

Abstract Accurate monitoring of orthotopic tumors in oncological research is critical. While conventional surgical exposure method or imaging methods such as bioluminescence imaging (BLI), ultrasound imaging (US) and computed tomography (CT) have different advantages and limitations. Magnetic Resonance Imaging (MRI) offers a non-invasive modality with high sensitivity. This study compares BLI and MRI in tracking tumor progression, focusing on the human glioblastoma multiforme (GBM) orthotopic xenograft mouse model. To establish the GBM model, human glioblastoma cells U87 MG-luc, expressing firefly luciferase, were intracranially implanted in female BALB/c nude mice. In-life tumor growth was assessed longitudinally every 3-4 days using BLI (IVIS Lumina S5, PerkinElmer, US) and MRI (Bruker BioSpec 117/16, 11.7T ultra-high field scanner, Germany) with a T2-weighted sequence. Mice were randomized into two groups (n=8) based on the MRI-derived tumor volume and BLI signal on the 3rd day post inoculation. One day after grouping, each cohort received specific treatments: one with the standard vehicle control and the other with Temozolomide (TMZ) (10mg/kg, 5 days/week, oral gavage). This treatment lasted until day 21, after which whole brains were removed and tumors excised from surrounding normal tissue and weighed. The results from both BLI and MRI showed that the control group exhibited consistent tumor growth, while TMZ treatment significantly inhibited tumor growth by day 21. However, some differences were observed, particularly for small tumor size, with more accurate measurement with MRI compared to BLI. By day 7 (3 days post treatment), MRI indicated a Tumor Growth Inhibition (TGI) of 32.63%, whereas BLI indicated a 5.04% increase in the TMZ-treated group compared to the control group. From day 11 onwards, both methods demonstrated a TGI exceeding 70% with TMZ treatment. Moreover, there was a pronounced difference in tumor weight correlations: MRI assessments showed a strong correlation (R2=0.9967) with extracted tumor weights, whereas in contrast to BLI showed a weaker correlation (R2=0.5371). The lower correlation for BLI, could be explained by the hypoxia and necrosis commonly observed in larger tumors or after treatment leading to decrease of ATP and reduction of bioluminescence. BLI offers rapid 2D imaging but lacks precision in determining location and depth of GBM tumor. Moreover, it requires luciferase engineered cell lines. In contrast, MRI provides high-resolution 3D imaging without genetic modifications, providing precise anatomical evaluations. Our study highlights the advantages of MRI over BLI for longitudinal monitoring of orthotopic GBM models. MRI imaging modality opens the possibility to use more clinically relevant patient derived xenograft (PDX) models of GBM in an orthotopic manner, improving the clinical transability to evaluate new GBM treatment modalities. Citation Format: Mingrui Guo, Ruisong Su, Jeff W H Chor, Zheyan Zhang, Mandy Tan, Xing Qi Teo, Haosheng Feng, Kuan J. Lee, Li Hua, Longyun Zhang, Jie Cai, Guanping Mao, Jingjing Wang, Keefe Chng, Weiping Han, Colin Guo. Magnetic resonance imaging and bioluminescence imaging for evaluating tumor burden in orthotopic glioblastoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4179.

CUS3D: A New Comprehensive Urban-Scale Semantic-Segmentation 3D Benchmark Dataset

With the continuous advancement of the construction of smart cities, the availability of large-scale and semantically enriched datasets is essential for enhancing the machine’s ability to understand urban scenes. Mesh data have a distinct advantage over point cloud data for large-scale scenes, as they can provide inherent geometric topology information and consume less memory space. However, existing publicly available large-scale scene mesh datasets are limited in scale and semantic richness and do not cover a wide range of urban semantic information. The development of 3D semantic segmentation algorithms depends on the availability of datasets. Moreover, existing large-scale 3D datasets lack various types of official annotation data, which hinders the widespread applicability of benchmark applications and may cause label errors during data conversion. To address these issues, we present a comprehensive urban-scale semantic segmentation benchmark dataset. It is suitable for various research pursuits on semantic segmentation methodologies. This dataset contains finely annotated point cloud and mesh data types for 3D, as well as high-resolution original 2D images with detailed 2D semantic annotations. It is constructed from a 3D reconstruction of 10,840 UVA aerial images and spans a vast area of approximately 2.85 square kilometers that covers both urban and rural scenes. The dataset is composed of 152,298,756 3D points and 289,404,088 triangles. Each 3D point, triangular mesh, and the original 2D image in the dataset are carefully labeled with one of the ten semantic categories. Six typical 3D semantic segmentation methods were compared on the CUS3D dataset, with KPConv demonstrating the highest overall performance. The mIoU is 59.72%, OA is 89.42%, and mAcc is 97.88%. Furthermore, the experimental results on the impact of color information on semantic segmentation suggest that incorporating both coordinate and color features can enhance the performance of semantic segmentation. The current limitations of the CUS3D dataset, particularly in class imbalance, will be the primary target for future dataset enhancements.

Fresnel incoherent compressive holography toward 3D videography via dual-channel simultaneous phase-shifting interferometry.

Fresnel incoherent correlation holography (FINCH) enables high-resolution 3D imaging of objects from several 2D holograms under incoherent light and has many attractive applications in motionless 3D fluorescence imaging. However, FINCH has difficulty implementing 3D imaging of dynamic scenes since multiple phase-shifting holograms need to be recorded for removing the bias term and twin image in the reconstructed scene, which requires the object to remain static during this progress. Here, we propose a dual-channel Fresnel noncoherent compressive holography method. First, a pair of holograms with π phase shifts obtained in a single shot are used for removing the bias term noise. Then, a physic-driven compressive sensing (CS) algorithm is used to achieve twin-image-free reconstruction. In addition, we analyze the reconstruction effect and suitability of the CS algorithm and two-step phase-shift filtering algorithm for objects with different complexities. The experimental results show that the proposed method can record hologram videos of 3D dynamic objects and scenes without sacrificing the imaging field of view or resolution. Moreover, the system refocuses images at arbitrary depth positions via computation, hence providing a new method for fast high-throughput incoherent 3D imaging.

Microneedles: A novel clinical technology for evaluating skin characteristics.

Current methods for evaluating efficacy of cosmetics have limitations because they cannot accurately measure changes in the dermis. Skin sampling using microneedles allows identification of skin-type biomarkers, monitoring treatment for skin inflammatory diseases, and evaluating efficacy of anti-aging and anti-pigmentation products. Two studies were conducted: First, 20 participants received anti-aging treatment; second, 20 participants received anti-pigmentation treatment. Non-invasive devices measured skin aging (using high-resolution 3D-imaging in the anti-aging study) or pigmentation (using spectrophotometry in the anti-pigmentation study) at weeks 0 and 4, and adverse skin reactions were monitored. Skin samples were collected with biocompatible microneedle patches. Changes in expression of biomarkers for skin aging and pigmentation were analyzed using qRT-PCR. No adverse events were reported. In the anti-aging study, after 4 weeks, skin roughness significantly improved in 17 out of 20 participants. qRT-PCR showed significantly increased expression of skin-aging related biomarkers: PINK1 in 16/20 participants, COL1A1 in 17/20 participants, and MSN in 16/20 participants. In the anti-pigmentation study, after 4 weeks, skin lightness significantly improved in 16/20 participants. qRT-PCR showed significantly increased expression of skin-pigmentation-related biomarkers: SOD1 in 15/20 participants and Vitamin D Receptor (VDR) in 15/20 participants. No significant change in TFAP2A was observed. Skin sampling and mRNA analysis for biomarkers provides a novel, objective, quantitative method for measuring changes in the dermis and evaluating the efficacy of cosmetics. This approach complements existing evaluation methods and has potential application in assessing the effectiveness of medical devices, medications, cosmeceuticals, healthy foods, and beauty devices.