3D Image Analysis Research Articles

Central Amygdala Astrocyte Plasticity Underlies GABAergic Dysregulation in Ethanol Dependence.

Dependence is a hallmark of alcohol use disorder characterized by excessive alcohol intake and withdrawal symptoms. The central nucleus of the amygdala (CeA) is a key brain structure underlying the synaptic and behavioral consequences of ethanol dependence. While accumulating evidence suggests that astrocytes regulate synaptic transmission and behavior, there is a limited understanding of the role astrocytes play in ethanol dependence. The present study used a combination of viral labeling, super resolution confocal microscopy, 3D image analysis, and slice electrophysiology to determine the effects of chronic intermittent ethanol (CIE) exposure on astrocyte plasticity in the CeA. During withdrawal from CIE exposure, we observed increased GABA transmission, an upregulation in astrocytic GAT3 levels, and an increased proximity of astrocyte processes near CeA synapses. Furthermore, GAT3 levels and synaptic proximity were positively associated with voluntary ethanol drinking in dependent rats. Slice electrophysiology confirmed that the upregulation in astrocytic GAT3 levels was functional, as CIE exposure unmasked a GAT3-sensitive tonic GABA current in the CeA. A causal role for astrocytic GAT3 in ethanol dependence was assessed using viral-mediated GAT3 overexpression and knockdown approaches. However, GAT3 knockdown or overexpression had no effect on somatic withdrawal symptoms, dependence-escalated ethanol intake, aversion-resistant drinking, or post-dependent ethanol drinking in male or female rats. Moreover, intra-CeA pharmacological inhibition of GAT3 also did not alter dependent ethanol drinking. Together, these findings indicate that ethanol dependence induces GABAergic dysregulation and astrocyte plasticity in the CeA. However, astrocytic GAT3 does not appear necessary for the drinking related phenotypes associated with dependence.

Geometric deep learning for enhanced quantitative analysis of microstructures in X-ray computed tomography data

Quantitative microstructural analysis of XCT 3D images is key for quality assurance of materials and components. In this paper we implement a Graph Convolutional Neural Network (GCNN) architecture to segment a complex Al-Si Metal Matrix composite XCT volume (3D image). We train the model on a synthetic dataset and we assess its performance on both synthetic and experimental, manually-labeled, datasets. Our simple GCNN shows a comparable performance, measured via the Dice score, to more standard machine learning methods, but uses a greatly reduced number of parameters (less than 1/10 of parameters), features low training time, and needs little hardware resources. Our GCNN thus achieves a cost-effective reliable segmentation.

Establishment and evaluation of a 3D quantitative analysis method for dental plaque based on an intraoral scanner technique.

Quantitative dental plaque evaluation is necessary for clinical and scientific work. The present study aimed to examine the reliability of a 3D image analysis method by digitally analyzing the color 3D images obtained from an intraoral scanner (IOS) and then detecting and quantifying the plaque information and comparing it with the clinical examination results. A total of 140 teeth from five subjects with a standard dentition were enrolled. Plaque examination was performed at two different time points: after 24 h without oral hygiene (T1), and after habitual brushing (T2). At each time point, the Quigley-Hein Plaque Index (PI) of each tooth surface was recorded separately, followed by color 3D images obtained using an IOS, and image analysis and calculation using Geomagic Wrap 2021 software. The percentage of plaque staining area calculated from the 3D image analysis correlated well with the PI recorded during the clinical examination: the Spearman correlation coefficients were 0.9136 and 0.9061 (P < 0.001) for all tooth surfaces at T1 and T2, respectively. The measurements of the three investigators were in good agreement, with intraclass correlation coefficients of 0.989 and 0.992 (P < 0.001) for the vestibular and lingual surfaces at T1, respectively, and 0.964 and 0.983 (P < 0.001) for the vestibular and lingual surfaces at T2, respectively. In the present study, a digital 3D evaluation system of dental plaque suitable for research and clinical practice was initially developed and its reliability demonstrated.

Influence of surface finishing on the outcome of a 3-point bending test in polymer-based dental composits assessed by qualitative and quantitative fractography

ObjectivesThe aim of the study was to evaluate the influence of surface finishing in three polymer-based composits (composits) on the result of a 3-point bending test using quantitative and qualitative fractography as well as microstructural characteristics. Materials and methods270 rectangular specimens (n = 30) of three composits were prepared, stored and tested according to NIST No. 4877. Prior testing, the samples were subjected to three surface treatments: 1) no treatment, to preserve the oxygen inhibition layer, 2) with FEPA P1200 (ANSI equivalent grit 600) SiC paper abraded surface, and 3) polished surface. A three-point bending testing was employed, followed by quantitative (assessment of reason for failure and fracture pattern) and qualitative (fracture mirror measurements) fractography, 3D and 2D surface imaging, surface roughness, reliability and Fe-SEM analysis. The mirror radius that runs in the direction of constant stress was used to calculate the mirror constant (A) using Orr's equation. Uni- and multifactorial ANOVA, Tukey's post hoc test, and Weibull analysis was performed for statistical analysis. ResultsSurface finishing has less influence on the fracture pattern, reliability and mechanical parameters and has no influence on the mirror constant. The amount of inorganic filler has a direct impact on flexural strength and modulus, while the ranking of materials was independent of surface treatment. Failures initiated by volume defects were the most common failure mode (77.0%) with surface defects accounting for 14.9% (edge) and 7.7% (corner). Polishing resulted in lower peak-to valley height compared to no treatment, both 3–4 times lower compared to the 600 grit treatment. The increase in roughness within the analyzed range did not lead to an increase in surface-related failures. ConclusionsThe clear dominance of volume defects in all examined materials as a cause of material fracture reduces the impact of roughness on the measured properties. This insight was only possible using qualitative and quantitative research fractography.

Skeletal muscle myosin heavy chain expression and 3D capillary network changes in streptozotocin-induced diabetic female mice.

It is not well-understood how type 1 diabetes (T1DM) affects skeletal muscle histological phenotype, particularly capillarisation. This study aimed to analyze skeletal muscle myosin heavy chain (MyHC) fibre type changes and 3D capillary network characteristics in experimental T1DM mice. Female C57BL/6J-OlaHsd mice were categorized into streptozotocin (STZ)-induced diabetic (n = 12) and age-matched non-diabetic controls (n =12). The muscle fibre phenotype of the soleus, gluteus maximus, and gastrocnemius muscles were characterized based on the expression of MyHC isoforms, while capillaries of the gluteus maximus were assessed with immunofluorescence staining, confocal laser microscopy and 3D image analysis. STZ-induced diabetic mice exhibited elevated glucose levels, reduced body weight, and prolonged thermal latency, verifying the T1DM phenotype. In both T1DM and non-diabetic mice, the gluteus maximus and gastrocnemius muscles predominantly expressed fast-twitch type 2b fibers, with no significant differences noted. However, the soleus muscle in non-diabetic mice had a greater proportion of type 2a fibers and comparable type 1 fiber densities (26.2 ± 14.6% vs 21.9 ± 13.5%) relative to diabetic mice. T1DM mice showed reduced fiber diameters (P = 0.026), and the 3D capillary network analysis indicated a higher capillary length per muscle volume in the gluteus maximus of diabetic mice compared to controls (P < 0.05). Overall, T1DM induced significant changes in the skeletal muscle, including shifts in MyHC fibre types, decreased fibre diameters, and increased relative capillarisation, possibly due to muscle fibre atrophy. Our findings emphasize the superior detail provided by the 3D analytical method for characterizing skeletal muscle capillary architecture, highlighting caution in interpreting 2D data for capillary changes in T1DM.

Spatiotemporal mapping of renal innervation and impact of in utero fetal denervation on kidney development

Proper kidney function is intricately linked to cardiovascular health. To help maintain homeostasis, the kidney is innervated by peripheral nerves which play significant roles in the regulation of renal function. Our lab has recently established that peripheral neurons composed of both sympathetic and sensory fibers innervate the kidney concomitantly during arterial differentiation, following guidance cues released by renal stromal cells. Yet, it remains unknown whether renal nerves actively direct organogenesis as they establish neuroeffector junctions to begin mediating physiology. In this study, we hypothesize that renal nerves release spatially and temporally important signaling factors which regulate kidney development. To test this hypothesis, we genetically ablated renal nerves in utero utilizing a whole animal Ntrk1 knockout (TrkA) which is required for neuronal survival. Using 3D light-sheet imaging and IMARIS analysis on wild-type ( TrkA+/+) (n=6), heterozygous ( TrkA+/-) (n=6), and mutant ( TrkA−/−) (n=6) mice, we assessed morphology and number of renal structures in at P0. We found total glomeruli number was decreased (P1-way Anova &lt;0.001) and glomeruli diameter was increased (P1-way Anova &lt;0.001) in heterozygous TrkA+/- and further in mutant TrkA−/− denervated kidneys compared to TrkA+/+ wild-type kidneys at P0. Using immunofluorescence (IF) on kidney section, we observed that proximal tubule diameter was increased (PT-test &lt; 0.0001) in mutant TrkA−/− denervated kidneys compared to TrkA+/+ wild-type kidneys at P0. These data suggest that renal nerves are poised to impact nephron morphology and/or function during kidney development. We further established that renal nerves traffcked Synapsin 1+ vesicles showing that they establish neuro-effector junctions with developing kidney structures like glomeruli and tubules suggesting potential cellular crosstalk important for development. Future efforts will aim to conditionally delete sensory or sympathetic renal nerves independently and investigate the developmental and resulting functional phenotypes. Taken together our findings will significantly bridge the gap in knowledge concerning the establishment of renal innervation and the role of nerves in kidney development and disease. O'Brien Lab Startup Fund, R01DK121014 (O'Brien, PI). This is the full abstract presented at the American Physiology Summit 2024 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.

Controlled Mechanical Property Gradients Within a Digital Light Processing Printed Hydrogel-Composite Osteochondral Scaffold.

Tissue engineered scaffolds are needed to support physiological loads and emulate the micrometer-scale strain gradients within tissues that guide cell mechanobiological responses. We designed and fabricated micro-truss structures to possess spatially varying geometry and controlled stiffness gradients. Using a custom projection microstereolithography (μSLA) system, using digital light projection (DLP), and photopolymerizable poly(ethylene glycol) diacrylate (PEGDA) hydrogel monomers, three designs with feature sizes < 200μm were formed: (1) uniform structure with 1MPa structural modulus ( ) designed to match equilibrium modulus of healthy articular cartilage, (2) = 1MPa gradient structure designed to vary strain with depth, and (3) osteochondral bilayer with distinct cartilage ( = 1MPa) and bone ( = 7MPa) layers. Finite element models (FEM) guided design and predicted the local mechanical environment. Empty trusses and poly(ethylene glycol) norbornene hydrogel-infilled composite trusses were compressed during X-ray microscopy (XRM) imaging to evaluate regional stiffnesses. Our designs achieved target moduli for cartilage and bone while maintaining 68-81% porosity. Combined XRM imaging and compression of empty and hydrogel-infilled micro-truss structures revealed regional stiffnesses that were accurately predicted by FEM. In the infilling hydrogel, FEM demonstrated the stress-shielding effect of reinforcing structures while predicting strain distributions. Composite scaffolds made from stiff μSLA-printed polymers support physiological load levels and enable controlled mechanical property gradients which may improve in vivo outcomes for osteochondral defect tissue regeneration. Advanced 3D imaging and FE analysis provide insights into the local mechanical environment surrounding cells in composite scaffolds.

Sonographically-guided Parasacrum Infrapiriformis Drainage of Deep Pelvic Abscesses: An Anatomical Safety Study Using SYNAPSE VINCENT.

Deep pelvic abscesses are surrounded by the pelvic bones, bladder, gynecological organs, intestinal tract, and nerve and vascular systems, and are approached by various routes for drainage. The transgluteal approach is often performed under computed tomography guidance; however, if ultrasonography can be used to confirm the approach, it is considered more effective because it reduces radiation exposure and allows for real-time puncture under sonographic and fluoroscopic guidance. This retrospective study was conducted at Tobata Kyoritsu Hospital (Fukuoka, Japan) between April 1, 2021, and December 31, 2022. Sonographically guided transgluteal drainage with fluoroscopy was performed in five consecutive cases of deep pelvic abscesses using a 3D image analysis system (SYNAPSE VINCENT) to study the anatomy for safe puncture. Three patients had postoperative abscesses from colorectal cancer, one caused by perforation of the appendicitis, and one caused by sigmoid diverticulitis. The average drainage duration was 11 days (SD = 6.7). No complications, such as bleeding or nerve damage, were observed. We constructed a 3D image of the puncture route of the trans greater sciatic foramen using SYNAPSE VINCENT to objectively comprehend the anatomy and puncture route. The ideal transgluteal approach is to insert the catheter as close to the sacrum as possible at the level of the infrapiriformis. The parasacrum infrapiriformis approach can be performed safely and easily using ultrasound guidance and fluoroscopy.

Concrete structure assembly technology based on 3D intelligent image analysis

AbstractAt present, there is no standard practice for temporary connection of component installation. How to make temporary connections to components more efficient and accurate is the key to the construction of cast‐in‐place connection parts in concrete prefabricated buildings. In order to improve the assembly technology of concrete structures, this paper combines three‐dimensional intelligent image analysis technology for simulation, analyzes and compares several common electronic image stabilization algorithms, discusses the video image stabilization technology based on gray projection method in detail, and gives experimental results. Moreover, this paper analyzes and compares common moving target tracking algorithms, such as feature‐based tracking, region matching‐based tracking, dynamic contour‐based tracking, and 3D model‐based tracking. In addition, this paper studies the target tracking algorithm based on the Camshift algorithm, and constructs the assembly model of the intelligent concrete structure with the support of the algorithm. Through experimental verification, it is known that the performance distribution of the concrete structure assembly model based on 3D intelligent image analysis in experimental evaluation is between [81, 89], the experimental study shows that the concrete structure assembly model based on 3D intelligent image analysis can effectively improve the assembly effect of concrete structure.

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.

B-ultrasound-assisted gluteal fat grafting in Asians: A prospective study of quantitative results from three-dimensional imaging and B-ultrasound analysis

BackgroundThe increasing number of fatalities caused by gluteal fat grafting is concerning; thus, there is a need to determine ways to obtain the ideal aesthetic effect while ensuring a safe operation. In this study, three-dimensional (3D) measurements combined with B-ultrasound were used to evaluate the effect of gluteal fat augmentation in Asians, whose safety and effectiveness were confirmed using quantitative data. MethodsThirty-five consecutive female patients were evaluated in this prospective clinical study. All patients underwent B-ultrasound-assisted gluteal fat augmentation on the subcutaneous plane alone. 3D imaging and B-ultrasound analysis of the adipose tissue thickness in the gluteal region were performed preoperatively and at 1 week, 3 months and 6 months post-operatively. ResultsThe waist circumference of the patients decreased, gluteal circumference and length of the gluteal crease increased and average waist-to-hip ratio improved from 0.78 to 0.74. At 3 months and 6 months post-operatively, the adipose tissue thickness decreased by 5.1% and 15.1%, respectively. The fat retention rates calculated using 3D imaging measurements at 3 months and 6 months post-operatively were 77.9% and 64.7%, respectively. According to the BODY-Q scale scores, patients reported a high level of satisfaction post-operatively. ConclusionsB-ultrasound guidance can effectively prevent the occurrence of fatal fat embolism during gluteal fat grafting and maximise the augmentation effect. The quantitative data obtained using 3D measurements and B-ultrasound confirmed the safety and effectiveness of fat injections for gluteal augmentation under B-ultrasound guidance.

Automated Derivation of Vine Objects and Ecosystem Structures Using UAS-Based Data Acquisition, 3D Point Cloud Analysis, and OBIA

This study delves into the analysis of a vineyard in Carinthia, Austria, focusing on the automated derivation of ecosystem structures of individual vine parameters, including vine heights, leaf area index (LAI), leaf surface area (LSA), and the geographic positioning of single plants. For the derivation of these parameters, intricate segmentation processes and nuanced UAS-based data acquisition techniques are necessary. The detection of single vines was based on 3D point cloud data, generated at a phenological stage in which the plants were in the absence of foliage. The mean distance from derived vine locations to reference measurements taken with a GNSS device was 10.7 cm, with a root mean square error (RMSE) of 1.07. Vine height derivation from a normalized digital surface model (nDSM) using photogrammetric data showcased a strong correlation (R2 = 0.83) with real-world measurements. Vines underwent automated classification through an object-based image analysis (OBIA) framework. This process enabled the computation of ecosystem structures at the individual plant level post-segmentation. Consequently, it delivered comprehensive canopy characteristics rapidly, surpassing the speed of manual measurements. With the use of uncrewed aerial systems (UAS) equipped with optical sensors, dense 3D point clouds were computed for the derivation of canopy-related ecosystem structures of vines. While LAI and LSA computations await validation, they underscore the technical feasibility of obtaining precise geometric and morphological datasets from UAS-collected data paired with 3D point cloud analysis and object-based image analysis.

Advancing preclinical drug evaluation through automated 3D imaging for high-throughput screening with kidney organoids

High-throughput drug screening is crucial for advancing healthcare through drug discovery. However, a significant limitation arises from available in vitro models using conventional 2D cell culture, which lack the proper phenotypes and architectures observed in three-dimensional (3D) tissues. Recent advancements in stem cell biology have facilitated the generation of organoids—3D tissue constructs that mimic human organs in vitro. Kidney organoids, derived from human pluripotent stem cells, represent a significant breakthrough in disease representation. They encompass major kidney cell types organized within distinct nephron segments, surrounded by stroma and endothelial cells. This tissue allows for the assessment of structural alterations such as nephron loss, a characteristic of chronic kidney disease. Despite these advantages, the complexity of 3D structures has hindered the use of organoids for large-scale drug screening, and the drug screening pipelines utilizing these complex in vitro models remain to be established for high-throughput screening. In this study, we address the technical limitations of kidney organoids through fully automated 3D imaging, aided by a machine-learning approach for automatic profiling of nephron segment-specific epithelial morphometry. Kidney organoids were exposed to the nephrotoxic agent cisplatin to model severe acute kidney injury. An U.S. Food and Drug Administration (FDA)-approved drug library was tested for therapeutic and nephrotoxicity screening. The fully automated pipeline of 3D image acquisition and analysis identified nephrotoxic or therapeutic drugs during cisplatin chemotherapy. The nephrotoxic potential of these drugs aligned with previous in vivo and human reports. Additionally, Imatinib, a tyrosine kinase inhibitor used in hematological malignancies, was identified as a potential preventive therapy for cisplatin-induced kidney injury. Our proof-of-concept report demonstrates that the automated screening process, using 3D morphometric assays with kidney organoids, enables high-throughput screening for nephrotoxicity and therapeutic assessment in 3D tissue constructs.

Evaluation of Individual and Crystal Population Dissolution Rates by Time-Resolved X-ray Microtomography.

The intrinsic dissolution rate (IDR) is an important parameter in pharmaceutical science that measures the rate at which a pure crystalline active pharmaceutical ingredient dissolves in the absence of diffusion limitations. Traditional IDR measurement techniques do not capture the complex interplay between particle morphology, fluid flow, and dissolution dynamics. The dissolution rate of individual particles can differ from the population average because of factors such as particle size, surface roughness, or exposure of individual crystal facets to the dissolution medium. The aim of this work was to apply time-resolved X-ray microtomography imaging and simultaneously measure the individual dissolution characteristics of a large population of crystalline particles placed in a packed bed perfused by the dissolution medium. Using NaCl crystals in three different size fractions as a model, time-resolved microtomography made it possible to visualize the dissolution process in a custom-built flow cell. Subsequent 3D image analysis was used to evaluate changes in the shape, size, and surface area of individual particles by tracking them as they are dissolved. Information about the particle population statistics and intrabatch variability provided a deeper insight into the dissolution process that can complement established IDR measurements.

Evolution of pore structure and reactive transport parameters during acid leaching of sandstone uranium ore

The changes in the micro-scale pore structure during the acid leaching of sandstone uranium ore significantly affect its reactive transport parameters, which, in turn, directly influence the leaching efficiency of uranium. Consequently, understanding and managing the dynamic evolution of the pore structure of sandstone at micro-scale during acid leaching is beneficial for enhancing the leaching efficiency of uranium. This paper employs a dynamic continuous water-rock reaction experiment on sandstone uranium ore to simulate the in-situ acid leaching process. Additionally, X-ray micro-computed tomography (μCT) scanning was utilized to produce three-dimensional (3D) images at various leaching stages. Subsequently, image processing techniques were employed to characterize and parameterize the pore structure within these images. The results revealed that, during the leaching process, mineral dissolution led to an increase in the interconnected pores, while there was a decrease in the isolated pores. Nonetheless, at the leading edge of the sandstone uranium ore, detachment of mineral grains occurred during the leaching process along the direction of fluid flow. The migration of mineral grains resulted in a reduction of interconnected pores and an increase in the isolated pores. The analysis of 3D images indicated that porosity, permeability, the percentage of connected pore area and the reactive surface area exhibited similar variation trends throughout the leaching process. Furthermore, the permeability, the percentage of connected pore area and the reactive surface area displayed a positive correlation with porosity. The study holds valuable insights to develop a deeper understanding of the evolutionary patterns regarding the pore structure during the in-situ acid leaching of sandstone uranium ore.

Functional Acetabular Component Positioning During Direct Anterior Approach Hip Arthroplasty Using a Novel Three-Dimensional Virtual Mesh Imaging System With Fluoroscopy

BackgroundOptimal position of total hip arthroplasty (THA) components is critical for joint mechanics and stability. Acetabular component positioning during supine surgery in direct anterior approach (DAA) THA may be different in the standing position postoperatively, which traditional fluoroscopy is unable to predict. A novel 3-dimensional (3D) image analysis technology (IAT) that uses artificial intelligence to measure the tilt and rotation of the pelvis has enabled prediction of component positioning from supine to standing. The purpose of this study was to compare intraoperative fluoroscopy, non–3D-IAT, and 3D-IAT with postoperative standing radiographs to assess the accuracy of component positioning. MethodsFrom 2022 to 2023, 30 consecutive patients (86.6% women, mean age 59 [range, 55 to 67]) undergoing primary DAA THA with the use of the 3D-IAT were identified. A separate cohort of 148 patients from 2020 to 2021 (85% women, mean age 65 [range, 55 to 69]) who underwent DAA THA with non–3D-IAT was used for comparison. Leg length discrepancy (LLD), cup anteversion, and inclination were manually measured on intraoperative fluoroscopic images and digitally measured using IAT. Follow-up evaluation occurred at 1 month with standing pelvis radiographs measured using Ein Bild Röntgen Analyze–Cup software. Measurements were compared via Wilcoxon signed rank tests where P ≤ .05 indicates significantly different measurements. ResultsMedian LLD, inclination, and anteversion measurements via non–3D-IAT and fluoroscopy were significantly different compared to postoperative standing radiographs (P < .001). The 3D-IAT more accurately predicted LLD, abduction, and anteversion, with values not significantly different from postoperative standing measurements (P = .23, P = .93, and P = .36, respectively). ConclusionsThe use of the 3D-IAT during DAA THA allowed for the more accurate prediction of acetabular component position in the standing position postoperatively.

Abstract 4249: Establishment and analysis of patient-derived high-grade serous ovarian cancer organoids for disease modeling and drug testing

Abstract Purpose: Ovarian cancer is the most lethal gynecologic cancer. Majority of ovarian cancers belong to the subgroup of high-grade serous ovarian cancer (HGSC). Its standard treatment is surgery and chemotherapy with platinum and taxane-based compounds, for which almost all patients become resistant. We have established a panel of patient derived 3-dimensional (3D) HGSC long-term tumor organoid cultures for personalized disease modeling, drug screening and evaluation of the efficiency of potential new treatments to be used in preclinical research. Methods: Tumor tissues or ascites from &amp;gt; 30 HGSC tumors were set up as long-term 3D organoid cultures (PDOs). RNA and whole genome sequencing was performed from the original tumors and from PDOs. Pluripotency and proliferation were assessed via high-throughput immunofluorescent detection of PAX8 and Ki67. Resistance towards standard treatment and response to additional selected drugs and drug combinations were evaluated in cell death and proliferation assays. Imaging and image-based quantifications were performed under 3D setup. PDOs were set up for in vivo drug testing in immunodeficient NOD/Shi-scid/IL-2Rgnull (NOG) mice. Summary: A set of HGSC PDOs of different longitudinal, prospective, and multiregional samples has been established representing the three evolutionary states of HGSC: evolving, maintaining and adaptive state. They are ready to be used as rational and effective models for studying drug interventions. Supportively, results of preclinical studies with PI3K inhibitor Alpelisib matched the published patient responses. Tumor evolutionary analysis based on data of longitudinal, prospective, and multiregional collected samples suggest further targetable pathways that can mediate chemotherapy resistance and pinpoint potential targets for drug intervention. Conclusion: Inhibition of these pathways with simultaneous targeting of other cellular functions, such as lysosomal-mediated cell death, may be highly effective alternative treatment option. 3D imaging and efficient image analysis are necessary tools to understand tumor organoid biology and drug responses to assist development and pre-clinical evaluation of new treatments. This study is a part of the DECIDER project (https://www.deciderproject.eu/, NCT04846933). Citation Format: Tuula Kallunki, Anna R. Lauridsen, Aikaterini Skorda, Alexandra Lahtinen, Marie L. Bay, Benita Rasmussen, Kaisa Huhtinen, Taru Muranen, Jaana Oikkonen, Johanna Hynninen, Sampsa Hautaniemi. Establishment and analysis of patient-derived high-grade serous ovarian cancer organoids for disease modeling and drug testing [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 4249.

Automatic multi-view pose estimation in focused cardiac ultrasound

Focused cardiac ultrasound (FoCUS) is a valuable point-of-care method for evaluating cardiovascular structures and function, but its scope is limited by equipment and operator’s experience, resulting in primarily qualitative 2D exams. This study presents a novel framework to automatically estimate the 3D spatial relationship between standard FoCUS views. The proposed framework uses a multi-view U-Net-like fully convolutional neural network to regress line-based heatmaps representing the most likely areas of intersection between input images. The lines that best fit the regressed heatmaps are then extracted, and a system of nonlinear equations based on the intersection between view triplets is created and solved to determine the relative 3D pose between all input images. The feasibility and accuracy of the proposed pipeline were validated using a novel realistic in silico FoCUS dataset, demonstrating promising results. Interestingly, as shown in preliminary experiments, the estimation of the 2D images’ relative poses enables the application of 3D image analysis methods and paves the way for 3D quantitative assessments in FoCUS examinations.

Emphasis of Cyclic Loading on the Fracture Mechanism and Residual Fracture Toughness of High-Performance Concrete Considering the Morphological Properties of Aggregate

This research investigates the fatigue behaviour and fracture mechanics of high-performance concrete (HPC), including various compositions such as HPC with basalt aggregates (HPC-B), HPC with gravel (HPC-G), and high-strength coarse mortar (CM) under static and cyclic tensile loading within the special priority program SPP 2020. The study aims to integrate fracture mechanics into structural analysis to enhance design guidelines for slender cross-sections and safety-related high-performance structural components. The experimental investigations reveal HPC-B’s remarkable superiority, displaying its higher compressive strength, modulus of elasticity, and tensile strength compared to HPC-G and CM. A modified disk-shaped compact tension (MDCT) based on ASTM standards, aided by digital image correlation (DIC) unveils fracture behaviour, emphasizing fracture energy as a crucial parameter. HPC-B exhibits improved crack resistance and notch sensitivity reduction attributed to crushed basalt aggregates and an enhanced interfacial transition zone (ITZ). The research scrutinizes factors like material characterization, aggregate morphology, stress levels, and the displacement rate on crack formation. High-cycle fatigue tests show HPC-B’s superior performance, and the post-fatigue analysis reveals enhanced residual fracture toughness attributed to nano-level structural changes, stress redistribution and aggregate-matrix interaction. A 3D image analysis via Computed Tomography (CT) scans captures mesostructural crack propagation and provide quantitative insights. This research marks a significant shift from conventional aggregate-focused approaches and introduces a novel approach by integrating excess paste theory and mesoscale analysis, highlighting the critical role of aggregate choice in material characterization and mesoscale design in enhancing the structural efficiency of HPC. Furthermore, the study advances the understanding of HPC fatigue behaviour, emphasizing the interplay of aggregate types and morphologies and their dynamic response to cyclic loading, offering valuable insights for optimizing design guidelines and fostering innovation in structural engineering.

Advancing the understanding of pupil size variation in occupational safety and health: A systematic review and evaluation of open-source methodologies

Pupil size can be used as an important biomarker for occupational risks. In recent years, there has been an increase in the development of open-source tools dedicated to obtaining and measuring pupil diameter. However, it remains undetermined determined whether these tools are suitable for use in occupational settings. This study explores the significance of pupil size variation as a biomarker for occupational risks and evaluates existing open-source methods for potential use in both research and occupational settings, with the goal of to prevent occupational accidents and improve the health and performance of workers. To this end, a two-phase systematic literature review was conducted in the Web of Science™, ScienceDirect®, and Scopus® databases. For the relevance of monitoring pupil size variation in occupational settings, 15 articles were included. The articles were divided into three groups: mental workload, occupational stress, and mental fatigue. In most cases, pupil dilation increased with workload enhancement and with higher levels of stress. Regarding fatigue, it was noted that an increase in this condition corresponded with a decrease in pupil size. With respect to the open-source methodologies, 16 articles were identified, which were categorized into two groups: algorithms and software. Convolutional neural networks (CNN)11CNN: Deep learning models adept at processing large datasets for 2D image analysis. These CNNs, by convolving images with filters, excel at extracting features and achieving high accuracy in image recognition and detection tasks (Chauhan et al., 2018). have exhibited superior performance among the various algorithmic approaches studied. Building on this insight, and considering the evaluations of software options, MEYE emerges as the premier open-source system for deployment in occupational settings due to its compatibility with a standard computer webcam. This feature positions MEYE as a particularly practical tool for workers in stable environments, like those of developers and administrators.