3D Image Analysis Research Articles

MORPHOLOGICAL ANALYSIS OF 3D MR IMAGES OF PF JOINTS IN ASYMPTOMATIC SUBJECTS

Understanding the pathogenesis of patellofemoral osteoarthritis (PFOA) will be enhanced by elucidating the onset and progression in asymptomatic PFOA. Demonstrating of the cartilage defect of 3D MR images, obtained from a cohort population, in order from the smallest to the largest, can mimic the morphological progression process of PFOA. The purpose of this study was to clarify the frequency, classification, and morphological progression process of PFOA by observing MRI 3D images in a cohort population of subjects without a history of visiting hospitals for knee disease. The subjects were 561 at 30–79 years old who were registered in the Kanagawa Knee Study. The main exclusion criteria were those who have a past history of consecutive visits to the hospital for more than 3 months for knee symptoms. We obtained 3D MR images of the PF joints using 3D image analysis system volume analyzer (SYNAPSE 3D, Fujifilm Corporation, Tokyo). The cartilage defects were classified as medial and lateral type. MR images of the PF joints were displayed with cartilage area ratios of the patella and presented in order of highest to lowest, separated into the medial and lateral type. Of the 561 subjects, cartilage defects were detected on 3D images of the patella in 37 subjects (6.6%). Medial lesion was detected in 26 subjects (4.6%) and lateral lesion in 11 subjects (2.0%), showing that medial lesion was significantly more frequent (p=0.01). For the medial type, the patellar cartilage defect was located in the center of the medial facet, expanded to the surrounding area, and further distally and medially. 3D MR images of the patellofemoral joint showed the cartilage defect of the patella expanded along with the medial ridge of the femoral trochlea. For the lateral type, the patellar cartilage defect was located in the center of the lateral facet, expanded to the surrounding area, and further distally and laterally. 3D MR images of the patellofemoral joint showed the cartilage defect of the patella expanded along with the lateral ridge of the femoral trochlea (Fig. 1). According to 3D MR images, the frequency of the patella cartilage defect was 6.6% in 561 asymptomatic subjects. Patellar cartilage defects occurred more frequently on the medial facet than on the lateral facet. The patellar cartilage defect occurred at the center of each facet and expanded along with each side of the ridge of the femoral trochlea. Fujifilm Corporation and Japan Society for the Promotion of Science Grant JP22K09349 I Sekiya received a research grant from Fujifilm Corporation including lending of the analysis software used in this study. Kimiko Takanashi is to be thanked for technical assistance. CORRESPONDENCE ADDRESS: sekiya.arm@tmd.ac.jp

Optoaccoustic Tomography – good news for microcirculatory research

Tomographic imaging is a well established technology in preventive medicine and biomedical research, although not without limitations and concerns. Optoacoustic tomography (OAT) is a recent development that bridges optical and sonographic techniques to solve spatial resolution in deep-tissue imaging. In addition to safety advantages, OAT allows multiple wavelength readings for natural thermoelastic chromophores. In this study, we explore Multi Spectral Optoacoustic Tomography (MSOT) capacities to simultaneously acquire three independent chromophores – deoxygenated haemoglobin (Hb), oxygenated haemoglobin (HbO2), and melanin, from healthy human volunteers, with maximal molar extinction of HbO2 at 950 nm, Hb at 750 nm and melanin at 680 nm. Later we demonstrate how image stability during acquisition is fundamental for optimal resolution, precision and consistency of high throughout MSOT data collection. From recorded scans, a workflow is layered for data evaluation. With the MSOT dedicated software results were extracted from 3D image analysis of deep (15 mm3) vessels. The possibilities offered by this new system, specially in vascular pathophysiology, are immense and can be extended beyond current knowledge.

Three-dimensional morphometric analysis of human kidney nephron structures in health and disease

Background and Hypothesis: Chronic kidney disease (CKD) is very common and affects as many as 37 million people in the United States. Diabetes and hypertension are the most common causes of CKD. The pathogenesis of CKD is not fully elucidated. Morphological changes such as glomerulosclerosis and tubular atrophy are commonly observed with advanced disease. However, it is unclear if such changes occur at earlier stages of disease, a time when therapeutic interventions are likely to have the most benefit. Measurements of glomerular, vascular and tubular dimensions have been typically derived from thin section, but a pipeline for acquiring these morphometric measurements in 3-dimentions have not been performed. Using enhanced tissue clearing, confocal 3D imaging and volumetric segmentation and analysis, we aimed at developing an approach to measure the dimensions of various structures within the human kidney. Our overarching hypothesis is that such approach could allow the detection of morphometric changes in early disease. 
 Experimental Design or Project Methods: Kidney tissue were used either from donor nephrectomies or stored frozen biopsies from Biobank Biopsy Cohort of Indiana (BBCI). Enhanced tissue clearing and staining for nuclei, endothelium and proximal tubules were performed. Optical sectioning and 3D Imaging was done using confocal microscopy. Volume rendering, segmentation and analysis were done using the Imaris Software (Bitplane). Various built in and customized segmentation approaches were used.
 Results: Volumes spanning 200 µm in thickness encompassing entire glomeruli and tubules were obtained. 3D Rendering of these volumes allowed visualization and enabled 3D segmentation. Dimensions of entire human glomeruli (maximum and minimum diameters, glomerular volumes and cellular densities), tubules and vessels were defined in control and samples with diabetic kidney disease.
 Conclusion and Potential Impact: Our studies established an approach for accurate measurements of the dimensions of nephronal structures preserved in their 3D environment within tissue. We also established the feasibility of this approach in comparing changes with disease vs. control. Such methodology will open up a new line of investigations to better understand the pathogenesis of CKD, particularly at its early stages.

Clinical Research of Orthopedic Trauma Based on Computer 3D Image Analysis.

In order to improve the clinical research effect of orthopedic trauma, this paper applies computer 3D image analysis technology to the clinical research of orthopedic trauma and proposes the BOS technology based on FFT phase extraction. The background image in this technique is a “cosine blob” background image. Moreover, this technology uses the FFT phase extraction method to process this background image to extract the image point displacement. The BOS technology based on FFT phase extraction does not need to select a diagnostic window. Finally, this paper combines computer 3D image analysis technology to build an intelligent system. According to the experimental research results, the clinical analysis system of orthopedic trauma based on computer 3D image analysis proposed in this paper can play an important role in the clinical diagnosis and treatment of orthopedic trauma and improve the diagnosis and treatment effect of orthopedic trauma.

Commentary: Beware of Optical Illusion of the Alar Base in Unilateral Cleft Lip Nasal Deformity.

Sir: We would like to congratulate the authors on an important study that clarifies dogma regarding the unilateral cleft lip nasal deformity.1 A common misperception is that the cleft-side alar base is displaced lateral, and that correction requires medial advancement (Fig. 1A). Just as we have, the authors provide objective evidence of the reverse2: relative to facial midline, the non-cleft alar base is displaced laterally and needs to be centralized (Fig. 1B). Mulliken has proposed that surrounding regional contours may lead to optical illusions of alar base position.3 We feel that the misperception may be due to human cognitive tendencies to reference the more natural appearing non-cleft side when explaining the less-familiar cleft-side contours. Regardless, a clear understanding of the deformity is critical to improving treatment and avoiding iatrogenic anomalies.Fig. 1.: A, Optical illusion. In the absence of facial regions outside the nasolabial region it may seem that correction of the deformity involves downward rotation of the medial lip philtrum and medial advancement of the lateral lip and alar base. B, Context. Facial features and reference lines make the actual displacements readily perceived. The non-cleft alar base and columella need to be centralized, and the cleft alar base needs to be advanced anteriorly. If the lateral lip and alar base were advanced medially, it would produce further imbalance, aggravate the nasal twist, and introduce iatrogenic deformity. Modified with permission from Plast Reconstr Surg 2020:145;185–199.Sakamoto et al analyzed a large sample of photographs and suggested that the cleft alar base is displaced medial relative to age-matched controls.1 Their findings differed from ours in that we found the cleft alar base to be retruded, but normal in medial-lateral position.2 Although they attributed the discrepancy to their larger sample size,1 there are several other explanations to consider. First, whereas our study examined standardized 3D images, they used 2D photographs that involve considerable error from lens distortions, parallax, and uncontrolled head rotation. The appearance of depth from a retruded cleft alar base on 2D images could be extrapolated as variation in medial-lateral position, and error from parallax may be magnified when images are tilted to normalize head position. Second, whereas we measured alar base position using calibrated images with accuracy to within 1 mm, they normalized dimensions on non-standardized photographs using inter-endocantion distance expressed as ratios. These ratios don’t account for the fact that the inter-endocanthion distance widens with increasing cleft severity.2 The findings that Sakamoto et al report may therefore simply be a changing denominator rather than true alteration of cleft alar base position. Although further analysis of well-controlled 3D images would be helpful, the medial position of cleft alar base relative to controls that they report is minimal and may not be of clinical relevance. Most figures depicting unilateral cleft lip nasal deformity crop out facial features beyond the nasolabial region and some research studies advocate that doing so reduces bias when rating esthetic outcomes.4 We are glad to see that Figure 4 in Sakamoto’s article1 is identical to Figure 1 in ours.2 The midline and the endocanthion verticals illustrate the medial-lateral displacements, whereas the alar base horizontals illustrate the relative vertical disparities. Visualization of the whole face allows balance to be judged, and the reference lines guide us to correct perceptions (Fig. 1). We propose that those references should be standard and caution against future research that crops out non-nasolabial regions without providing a mechanism to judge balance. Finally, based on Sakamoto’s,1 Fisher’s,5 and our2 studies, we propose that centralizing the columella and rebalancing the nasal base elements should be the fundamental principle in the correction of the unilateral cleft lip nasal deformity. DISCLOSURE The authors have no financial interest to declare in relation to the content of this article.

Abstract P158: Phenotypic analysis of myeloid cells in a 3D image-based repolarization assay with tumor spheroids

Abstract Background The immunosuppressive tumor microenvironment (TME) involves multiple cell types and a better understanding of the interplay between these cells could potentially unleash the full potential of many different types of immunotherapies. Tumor infiltrating myeloid cells have both cancer-restraining and cancer-promoting functions. Therefore, to further increase the biological relevance of in vitro platform, we incorporated the myeloid cell compartment into 3D co-cultures of tumor cells and T cells to measure the effects of immune-modulators. Using our proprietary image analysis software and machine learning, a set of morphological features was identified that allowed discrimination between undifferentiated monocytes, M1 and M2 macrophages, and dendritic cells. In addition, the phenotypic profiles of the myeloid cells could be analyzed in the presence of the tumor supernatants or in co-cultures with tumor cells. This assay allows a better understanding of the suppressive tumor microenvironment including multiple cell types and is suitable to test different cancer immunotherapies. Materials and Methods Different myeloid cell populations were generated from healthy PBMCs. Polarized M1 and M2 macrophages, DCs, and undifferentiated monocytes were then co-cultured with tumor conditioned media, spheroids derived from different cancer cell lines, or colorectal cancer organoids (CRC), growing in protein hydrogel in 384 well-plates for 1-7 days. In addition, purified T cells were also incorporated in these cultures. The cellular interactions were visualized using high-content microscopy and OMiner® software, which was trained to identify phenotypic profiles of different myeloid cell populations in 3D, was used to quantify their similarity to the defined subsets upon treatment. Results Myeloid cell populations were classified according to their phenotypic features identified by 3D image analysis, which verified the repolarization of M2 macrophages by their shift into phenotypic space of the M1 type macrophages upon treatment with CSF1r inhibitor or STING agonist. Repolarization was confirmed with an increased similarity score towards M1 macrophages upon treatment. This approach was further used to reveal the different effects of tumor cells and their immunosuppressive TME on myeloid cell phenotypes, showing that each tumor differently influenced the repolarization of the myeloid cells. In addition, triple co-cultures with T cells revealed the suppressive effect of tumor associated myeloid cells on the proliferation and infiltration of T cells. Conclusions The phenotypic analysis of different myeloid cells in 3D co-cultures could be visualized and quantified elucidating the bi-directional interplay between tumor and immune cells, and the functional reprograming of the suppressive tumor associated population towards an M1 phenotype induced by drug candidates. This advanced platform for testing cancer immunotherapies combines the ability to examine the complexity of the TME with the robustness of a high-throughput screening platform. Citation Format: Gera Goverse, Nataliia Beztsinna, Benjamin Visser, Tomas Veenendaal, Marjan van de Merbel, Emma Spanjaard, Ashgard Weterings, Kuan Yan, Leo Price, Lidia Daszkiewicz. Phenotypic analysis of myeloid cells in a 3D image-based repolarization assay with tumor spheroids [abstract]. In: Proceedings of the AACR-NCI-EORTC Virtual International Conference on Molecular Targets and Cancer Therapeutics; 2021 Oct 7-10. Philadelphia (PA): AACR; Mol Cancer Ther 2021;20(12 Suppl):Abstract nr P158.

2D and 3D techniques to assess the structure and porosity of Oxisols and their correlations with other soil properties

Structure and porous geometry are dynamic soil parameters that control several soil processes and functions. This study details the differences in the structure of typical Oxisols regarding the clay amount, biological activity, and mineralogy. Combining 2D and 3D image analysis can provide detailed information about the soil structure and porous system. The objectives of this study were: (i) to describe the soil microstructure and degree of microaggregation; (ii) to quantify porosity, soil pore types, and soil pore size distribution using 2D and 3D techniques; and (iii) to better understand the relationship between the porous system and the biological, chemical, mineralogical, and physical properties of the soil. The study considered four Oxisols: Xantic Kandiustox (P1), Rhodic Haplustox (P2), Anionic Acrustox (P3), and Typic Hapludox (P4). The results showed that all Oxisols have some degree of microaggregation. The Rhodic Haplustox (P2) had the most pronounced degree of microaggregation, which reflects the greater biological activity and gibbsite/kaolinite ratio, and lower hematite/(hematite + goethite) ratio compared to the other Oxisols. The pore types found by 2D analysis were complex pores in P1 and P2 and rounded pores in P3 and P4. The 3D analysis showed that P2 and P3 have a more connected porous system compared to the other Oxisols, evidenced by the lower value of the Euler number. The best connectivity values of the porous system were congruent to improved saturated hydraulic conductivity measured in a separate sample set.

Secondary porosity prediction in complex carbonate reefs using 3D CT scan image analysis and machine learning

Development and preservation of carbonate porosity and permeability are critical to characterizing reservoirs. However, secondary porosity, such as vugs and fractures, are difficult to identify and require collection of expensive wireline tools or core sampling. Wireline logs and cores have traditionally been used to identify the presence of secondary porosity but fail to quantify the contribution to total reservoir porosity. Additionally, advanced wireline logs and core are not readily available for most wells. Dual energy CT scans were collected on whole core from the A-1 Carbonate and Brown Niagaran formations drawn from six wells in northern Michigan. 3D analysis techniques were applied to identify and isolate secondary porosity features. A series of machine learning and data analytics techniques were applied to the dataset to predict secondary porosity features on basic wireline logs. The predictive model successfully predicted secondary porosity with high confidence.

The Method of Pose Judgment of Potential Motion Damage in 3D Image Analysis.

Objective This work aimed to study the posture judgment method of 3D image analysis of potential motion damage. Methods The motion damage collection was implemented by the 3D image analysis method, and 3D image data were adopted to identify the motion damage data. Moreover, 3D image acquisition technology was adopted to analyze the model of potential motion damage and analyze the simulation judgment result of potential motion damage. Specifically, it included simulation parameters, motion damage posture collection effect, damage detection speed at the collection point, damage accuracy, and damage degree. Results (1) The analysis of the damage monitoring speed at multiple collection points of the athletes in the sports environment confirmed that the range of changes in different time periods was different, and the changes showed a fast to slow to fast trend. (2) The 3D image analysis had high accuracy in analyzing the posture of potential motion damage, which rationalized the evolution of injuries. (3) The degree of motion damage under a 3D image changed from rising to gradual, which was in line with the theoretical results (all p < 0.05). Conclusion 3D image analysis can collect a high degree of small-sample-size data, then perform specific analysis, judgment, and summary, and finally, obtain objective and reasonable data. It greatly reduced the risk of potential motion damage for athletes and also improved the efficiency of injury recognition. Moreover, it reduced the chances of blind prevention and error prevention by athletes, thereby avoiding waste of resources. The simulation test confirmed the advantages of 3D image data collection in the sports environment, and it was solved that the current athletes cannot accurately and timely judge the potential motion damage. It also met the instability needs of the movement personnel of the acquisition system in the changing sports environment and provided a reliable guarantee for the safety and health of the sport personnel.

Evaluation of the Risk of Recurrence in Patients with Local Advanced Rectal Tumours by Different Radiomic Analysis Approaches.

The word radiomics, like all domains of type omics, assumes the existence of a large amount of data. Using artificial intelligence, in particular, different machine learning techniques, is a necessary step for better data exploitation. Classically, researchers in this field of radiomics have used conventional machine learning techniques (random forest, for example). More recently, deep learning, a subdomain of machine learning, has emerged. Its applications are increasing, and the results obtained so far have demonstrated their remarkable effectiveness. Several previous studies have explored the potential applications of radiomics in colorectal cancer. These potential applications can be grouped into several categories like evaluation of the reproducibility of texture data, prediction of response to treatment, prediction of the occurrence of metastases, and prediction of survival. Few studies, however, have explored the potential of radiomics in predicting recurrence-free survival. In this study, we evaluated and compared six conventional learning models and a deep learning model, based on MRI textural analysis of patients with locally advanced rectal tumours, correlated with the risk of recidivism; in traditional learning, we compared 2D image analysis models vs. 3D image analysis models, models based on a textural analysis of the tumour versus models taking into account the peritumoural environment in addition to the tumour itself. In deep learning, we built a 16-layer convolutional neural network model, driven by a 2D MRI image database comprising both the native images and the bounding box corresponding to each image.

Optical coherence tomography-angiography in diabetic retinopathy diagnosis and monitoring

Optical coherence tomography-angiography is a modern noninvasive method of 3D imaging and quantitative analysis of the retinal and choroidal microvasculature. It allows detecting manifestation and progression of diabetic retinopathy, planning treatment and evaluating its results.Optical coherence tomography angiography expands our understanding of microvascular changes in retinal vascular plexuses at different disease stages and deepens the understanding of its pathogenesis.

Microscopic estimation of swelling and shrinkage of hemp concrete in response to relative humidity variations

The use of bio-based building materials such as hemp concrete has increased considerably in France in the last few years, due to its hygrothermal and acoustic advantages. Hemp concrete is hygroscopic and very sensitive to relative humidity. This property is responsible for dimensional variations and therefore the degradation of the material. To evaluate these dimensional variations, 2D and 3D imaging techniques can be used. For 3D tools, significant research and financial investments are required. This study is based on the analysis of the 2D microstructure of both hemp concrete and hemp shiv aggregates, in order to understand and estimate these dimensional variations for sorption and desorption cycles. First, the interaction between the different constituents of these bio-based materials was performed using scanning electron microscopy (SEM). Then, a new experimental optical setup was investigated to quantify the hemp shiv and hemp concrete swelling and shrinking by analyzing variations in their microstructure at different relative humidity levels. The quantification is calculated by 2D image analysis function of the fibers direction. Finally, digital image correlation (DIC) was performed to allow better estimation of the hemp concrete swelling. The findings of this study underline the real influence of relative humidity on the hemp concrete, that present a hysteretic swelling due to the porous structure and hygroscopic behavior of this material. The resulting dimensional variations should have to be seriously taken into account when modeling the hygrothermal behavior of this material.

A parallel attention-augmented bilinear network for early magnetic resonance imaging-based diagnosis of Alzheimer's disease.

Structural magnetic resonance imaging (sMRI) can capture the spatial patterns of brain atrophy in Alzheimer's disease (AD) and incipient dementia. Recently, many sMRI‐based deep learning methods have been developed for AD diagnosis. Some of these methods utilize neural networks to extract high‐level representations on the basis of handcrafted features, while others attempt to learn useful features from brain regions proposed by a separate module. However, these methods require considerable manual engineering. Their stepwise training procedures would introduce cascading errors. Here, we propose the parallel attention‐augmented bilinear network, a novel deep learning framework for AD diagnosis. Based on a 3D convolutional neural network, the framework directly learns both global and local features from sMRI scans without any prior knowledge. The framework is lightweight and suitable for end‐to‐end training. We evaluate the framework on two public datasets (ADNI‐1 and ADNI‐2) containing 1,340 subjects. On both the AD classification and mild cognitive impairment conversion prediction tasks, our framework achieves competitive results. Furthermore, we generate heat maps that highlight discriminative areas for visual interpretation. Experiments demonstrate the effectiveness of the proposed framework when medical priors are unavailable or the computing resources are limited. The proposed framework is general for 3D medical image analysis with both efficiency and interpretability.

High-Resolution 3D Crop Reconstruction and Automatic Analysis of Phenotyping Index Using Machine Learning

Beyond the use of 2D images, the analysis of 3D images is also necessary for analyzing the phenomics of crop plants. In this study, we configured a system and implemented an algorithm for the 3D image reconstruction of red pepper plant (Capsicum annuum L.), as well as its automatic analysis. A Kinect v2 with a depth sensor and a high-resolution RGB camera were used to obtain more accurate reconstructed 3D images. The reconstructed 3D images were compared with conventional reconstructed images, and the data of the reconstructed images were analyzed with respect to their directly measured features and accuracy, such as leaf number, width, and plant height. Several algorithms for image extraction and segmentation were applied for automatic analysis. The results showed that the proposed method showed an error of about 5 mm or less when reconstructing and analyzing 3D images, and was suitable for phenotypic analysis. The images and analysis algorithms obtained by the 3D reconstruction method are expected to be applied to various image processing studies.

Preparation and Characterization of corn husk nanocellulose coating on electrospun polyamide 6

At present, electrospinning technology is a versatile and simple method for generating nano-scale membranes, and it provides attractive solutions in solving environmental problems and many energy problems. However, such films generally have low mechanical properties which limit their use in industry. Nanocellulose with excellent mechanical properties, high specific surface area, and renewable nature is an ideal green reinforcing material. In this paper, the cellulose nanocrystals (CNC) coatings on electrospun polyamide 6 (PA6) were prepared via coating method and explored as potential high-performance reinforced materials. The extraction of CNC and the performance of the composite membranes were studied by calculating the yield, scanning electron microscopy, 3D imaging, mechanical testing, and thermogravimetric analysis. Results show that the yield of CNC is impacted by various factors among which acid concentration is the most important. The CNC/PA6 composite film shows lower porosity and higher surface roughness than the pure PA6 membrane. With the increase of CNC concentration, lower porosity and higher surface roughness are obtained. With CNC coatings, tensile strength and Young s modulus of PA6 increase dramatically, while the tensile strain decreases obviously. The Young s modulus of the composite film has been increased by 250%. The composite membranes reveal high mechanical strength and low porosity, which can be applied infiltration and packaging.

Pore Volume Compressibility of Unconsolidated Sand Reservoirs: Insights Gained Using Laboratory-Created Sand Pack Analogs

Pore volume compressibility is a fundamental driver of production for unconsolidated sand reservoirs. Prediction of compressibility is desirable when direct measurements on core are not available. Many characteristics of reservoir sands change simultaneously. For this reason, the controls on compressibility are difficult to isolate and interpret. We present the results of compaction experiments using laboratory-created, unconsolidated sands. In these analog sands, we change one textural or mineralogical parameter at a time to investigate the influence of that parameter on the measured compaction properties. Initially, simple quartz grain packs of varying grain sizes were used. Subsequently, additional parameters were investigated, including grain packing, angularity, sorting, feldspar content, ductile grain content, small volumes of dispersed clay, and initial sample preconditioning at stress. Multiple samples of each type were created and tested. This allowed the testing to be halted at several intermediate stresses and the samples to be examined using 2D and 3D imaging and image analysis techniques. For monomineralic quartz sand packs, grain size is a principal control on compressibility. As mean size increases from 150 to 450 μm, peak compressibility increases from 6 to 24 microsips. The depletion stress at which peak compressibility occurs decreases from 8,000 to 2,500 psi. Increasing grain angularity also increases compressibility but with smaller effect. For 150-μm quartz sands, increasing the angularity resulted in an increase in compressibility from 6 microsips for round quartz to 10 microsips for angular quartz and decreased the depletion stress required to achieve peak compressibility from 8,000 to 7,000 psi. As sorting varies from well to moderately poorly sorted, compressibility decreases, and the curve broadens as a function of depletion stress. Adding small volumes of feldspar (or other minerals that cleave) increases the compressibility more than the change resulting from changes in grain size, illustrating the importance of framework grain composition. Adding similar volumes of ductile grains results in a similar increase in compressibility to that observed for feldspar. However, when the size of the ductile grains is larger than that of the associated quartz (e.g., locally derived rip-up clasts), the increase in compressibility is significantly larger. To validate the experimental work, we compare the results of uniaxial pore volume compressibility tests on laboratory-created sands with measurements made on subsurface samples of similar texture and mineralogy. Both the shape of the compressibility curves as well as the magnitude of the compressibility are successfully reproduced. We conclude that laboratory-created sands can provide reasonable proxies for estimating the compressibility of subsurface reservoirs when intact subsurface samples are not available for measurement (e.g., only percussion sidewall samples are acquired) as long as mineralogy and texture are known.

Advanced Light Sheet Microscopy and 3D Image Analyses of Kidney Injury, Glomerulosclerosis, and Fibrosis in a Mouse Model of Diabetic Kidney Disease

Advanced Light Sheet Microscopy and 3D Image Analyses of Kidney Injury, Glomerulosclerosis, and Fibrosis in a Mouse Model of Diabetic Kidney Disease

Agreement Between A 2-Dimensional Digital Image-Based 3-Compartment Body Composition Model and Dual Energy X-Ray Absorptiometry for The Estimation of Relative Adiposity

The purpose of this study was to compare relative adiposity (%Fat) derived from a 2-dimensional image-based 3-component (3C) model (%Fat3C-IMAGE) and dual-energy X-ray absorptiometry (DXA) (%FatDXA) against a 5-component (5C) laboratory criterion (%Fat5C). 57 participants were included (63.2% male, 84.2% White/Caucasian, 22.5±4.7 yrs., 23.9±2.8 kg/m2). For each participant, body mass and standing height were measured to the nearest 0.1 kg and 0.1 cm, respectively. A digital image of each participant was taken using a 9.7 inch, 16g iPad Air 2 and analyzed using a commercially available application (version 1.1.2, made Health and Fitness, USA) for the estimation of body volume (BV) and inclusion in %Fat3C-IMAGE . %Fat3C-IMAGE and %Fat5C included measures of total body water derived from bioimpedance spectroscopy. The criterion %Fat5C included BV estimates derived from underwater weighing and bone mineral content measures via DXA. %FatDXA estimates were calculated from a whole-body DXA scan. A standardized mean effect size (ES) assessed the magnitude of differences between models with values of 0.2, 0.5, and 0.8 for small, moderate, and large differences, respectively. Data are presented as mean ± standard deviation. A strong correlation (r = 0.94, p <.001) and small mean difference (ES = 0.24, p <.001) was observed between %Fat3C-IMAGE (19.20±5.80) and %Fat5C (17.69±6.20) whereas a strong correlation (r = 0.87, p <.001) and moderate-large mean difference (ES = 0.70, p <.001) was observed between %FatDXA (22.01±6.81) and %Fat5C. Furthermore, %Fat3C-IMAGE (SEE = 2.20 %Fat, TE= 2.6) exhibited smaller SEE and TE than %FatDXA (SEE = 3.14 %Fat, TE = 5.5). The 3C image-based model performed slightly better in our sample of young adults than the DXA 3C model. Thus, the 2D image analysis program provides an accurate and non-invasive estimate of %Fat within a 3C model in young adults. Compared to DXA, the 3C image-based model allows for a more cost-effective and portable method of body composition assessment, potentially increasing accessibility to multi-component methods.

In-situ 3D fouling visualization of membrane distillation treating industrial textile wastewater by optical coherence tomography imaging

Membrane fouling, which is caused by the deposition of particles on the membrane surface or pores, reduces system performance in membrane distillation (MD) applications, resulting in increased operational costs, poor recovery, and system failure. Optical Coherence Tomography enables in-situ foulant monitoring in both 2D and 3D, however, the 2D images can only determine fouling layer thickness in severe fouling. Therefore, in this study, an advanced 3D imaging analysis technique using intensity range filters was proposed to quantify fouling layer formation during MD through the use of a single 3D image. This approach not only reduces computational power requirements, but also successfully separated the fouling layer from the membrane at the microscale. Thus, the thickness, fouling index, and fouling layer coverage can be evaluated in real time. To test this approach, Polyvinylidene fluoride (C-PVDF) and polytetrafluoroethylene (C-PTFE) membranes were used to treat a feed consisting of industrial textile wastewater. Thin and disperse foulants was observed on the C-PTFE, with a 22 µm thick fouling layer which could not be observed using 2D images after 24 h. Moreover, the C-PTFE demonstrated better antifouling ability than the C-PVDF as demonstrated by its lower fouling index, which was also supported by surface energy characterization. This work demonstrates the significant potential of 3D imagery in the long-term monitoring of membrane fouling process to improve membrane antifouling performance in MD applications, which can lead to lowered operational costs and improved system stability.

Depth resolution of transmission ERDA for H in Al under nuclear-elastically enhanced recoiling of H by 8 MeV He

Using stacked samples of Al foil and H-containing resin film, we have carried out elastic recoil detection analysis with transmission layout (T-ERDA) to investigate the depth resolution in the measurements of H distribution in Al. For narrow and wide acceptance conditions of the detector, the depth resolutions of 1.5–4.9 μm at several depths in Al of 50 and 80 μm thicknesses have been determined for incidence of 8 MeV 4He. While the main factor to degrade the depth resolution is the energy straggling of recoil H for narrow acceptance conditions, it is the extended low-energy side of the H spectrum for wide acceptance conditions. The knowledge obtained in this work is useful for analysis of 3D images of H distribution measured by T-ERDA, for example, future analysis of minerals or natural glass samples to determine abundances and distributions of water or OH in the samples.