Emerging methods for genome-scale metabolic modeling of microbial communities.

Genome-scale metabolic models (GEMs) are consolidating as platforms for studying mixed microbial populations, by combining biological data and knowledge with mathematical rigor. However, deploying these models to answer research questions can be challenging due to the increasing number of available computational tools, the lack of universal standards, and their inherent limitations. Here, we present a comprehensive overview of foundational concepts for building and evaluating genome-scale models of microbial communities. We then compare tools in terms of requirements, capabilities, and applications. Next, we highlight the current pitfalls and open challenges to consider when adopting existing tools and developing new ones. Our compendium can be relevant for the expanding community of modelers, both at the entry and experienced levels.

Grey Wolf Optimizer with Behavior Considerations and Dimensional Learning in Three-Dimensional Tooth Model Reconstruction.

Three-dimensional registration with the affine transform is one of the most important steps in 3D reconstruction. In this paper, the modified grey wolf optimizer with behavior considerations and dimensional learning (BCDL-GWO) algorithm as a registration method is introduced. To refine the 3D registration result, we incorporate the iterative closet point (ICP). The BCDL-GWO with ICP method is implemented on the scanned commercial orthodontic tooth and regular tooth models. Since this is a registration from multi-views of optical images, the hierarchical structure is implemented. According to the results for both models, the proposed algorithm produces high-quality 3D visualization images with the smallest mean squared error of about 7.2186 and 7.3999 µm2, respectively. Our results are compared with the statistical randomization-based particle swarm optimization (SR-PSO). The results show that the BCDL-GWO with ICP is better than those from the SR-PSO. However, the computational complexities of both methods are similar.

The Precision, Inter-Rater Reliability, and Accuracy of a Handheld Scanner Equipped with a Light Detection and Ranging Sensor in Measuring Parts of the Body-A Preliminary Validation Study.

BACKGROUND: Anthropometric measurements play a crucial role in medico-legal practices. Actually, several scanning technologies are employed in post-mortem investigations for forensic anthropological measurements. This study aims to evaluate the precision, inter-rater reliability, and accuracy of a handheld scanner in measuring various body parts. METHODS: Three independent raters measured seven longitudinal distances using an iPad Pro equipped with a LiDAR sensor and specific software. These measurements were statistically compared to manual measurements conducted by an operator using a laser level and a meterstick (considered the gold standard). RESULTS: The Friedman test revealed minimal intra-rater variability in digital measurements. Inter-rater variability analysis yielded an ICC = 1, signifying high agreement among the three independent raters. Additionally, the accuracy of digital measurements displayed errors below 1.5%. CONCLUSIONS: Preliminary findings demonstrate that the pairing of LiDAR technology with the Polycam app (ver. 3.2.11) and subsequent digital measurements with the MeshLab software (ver. 2022.02) exhibits high precision, inter-rater agreement, and accuracy. Handheld scanners show potential in forensic anthropology due to their simplicity, affordability, and portability. However, further validation studies under real-world conditions are essential to establish the reliability and effectiveness of handheld scanners in medico-legal settings.

Deep learning-based workflow for hip joint morphometric parameter measurement from CT images.

Objective.Precise hip joint morphometry measurement from CT images is crucial for successful preoperative arthroplasty planning and biomechanical simulations. Although deep learning approaches have been applied to clinical bone surgery planning, there is still a lack of relevant research on quantifying hip joint morphometric parameters from CT images.Approach.This paper proposes a deep learning workflow for CT-based hip morphometry measurement. For the first step, a coarse-to-fine deep learning model is designed for accurate reconstruction of the hip geometry (3D bone models and key landmark points). Based on the geometric models, a robust measurement method is developed to calculate a full set of morphometric parameters, including the acetabular anteversion and inclination, the femoral neck shaft angle and the inclination, etc. Our methods were validated on two datasets with different imaging protocol parameters and further compared with the conventional 2D x-ray-based measurement method.Main results. The proposed method yields high bone segmentation accuracies (Dice coefficients of 98.18% and 97.85%, respectively) and low landmark prediction errors (1.55 mm and 1.65 mm) on both datasets. The automated measurements agree well with the radiologists' manual measurements (Pearson correlation coefficients between 0.47 and 0.99 and intraclass correlation coefficients between 0.46 and 0.98). This method provides more accurate measurements than the conventional 2D x-ray-based measurement method, reducing the error of acetabular cup size from over 2 mm to less than 1 mm. Moreover, our morphometry measurement method is robust against the error of the previous bone segmentation step. As we tested different deep learning methods for the prerequisite bone segmentation, our method produced consistent final measurement results, with only a 0.37 mm maximum inter-method difference in the cup size.Significance. This study proposes a deep learning approach with improved robustness and accuracy for pelvis arthroplasty planning.

Development of biodegradable customized tibial scaffold with advanced architected materials utilizing additive manufacturing.

In the last decade, the development of customized biodegradable scaffolds and implants has attracted increased scientific interest due to the fact that additive manufacturing technologies allow for the rapid production of implants with high geometric complexity constructed via commercial biodegradable polymers. In this study, innovative designs of tibial scaffold in form of bone-brick configuration were developed to fill the bone gap utilizing advanced architected materials and bio-inspired diffusion canals. The architected materials and canals provide high porosity, as well as a high surface area to volume ratio in the scaffold facilitating that way in the tissue regeneration process and in withstanding the applied external loads. The cellular structures applied in this work were the Schwarz Diamond (SD) and a hybrid SD&FCC hybrid cellular material, which is a completely new architected material that derived from the combination of SD and Face Centered Cubic (FCC) structures. These designs were additively manufactured utilizing two biodegradable materials namely Polylactic acid (PLA) and Polycaprolactone (PCL), using the Fused Filament Fabrication (FFF) technique, in order to avoid the surgery, for the scaffold's removal after the bone regeneration. Furthermore, the additively manufactured scaffolds were examined in terms of compatibility and assembly with the bone's physical model, as well as, in terms of mechanical behavior under realistic static loads. In addition, non-linear finite element models (FEMs) were developed based on the experimental data to accurately simulate the mechanical response of the examined scaffolds. The Finite Element Analysis (FEA) results were compared with the experimental response and afterwards the stress concentration regions were observed and identified. Τhe proposed design of scaffold with SD&FCC lattice structure made of PLA material with a relative density of 20% revealed the best overall performance, showing that it is the most suitable candidate for further investigation (in-vivo test, clinical trials, etc.) and commercialization.

Evaluation and Calibration of CBCT Reconstruction Models.

PURPOSE: This study proposes a method for improving the accuracy of three-dimensional (3D) models generated through cone-beam computed tomography (CBCT). METHODS: A 3D cuboid model fitted with a »-scale dentition on its top surface was constructed to simulate an alveolar bone with teeth. A physical specimen of the model was printed and the distance between its opposite sides was measured using a vernier caliper. The physical model was light-scanned, and the surface data of the generated 3D model were corrected by calibrating the distance between opposite sides against the vernier caliper measurements. The physical model was also scanned using CBCT to reconstruct a second 3D model. The overall deviation between the two models and the distance deviation in each direction of the cuboid and dentition were quantified and statistically analyzed. RESULTS: The overall deviation between the reconstructed CBCT model and the calibrated structured light-scanned model was 0.098 ± 0.001 mm. Following calibration, the overall deviation was 0.010 ± 0.006 mm. A one-way variance analysis suggested that the overall deviations' differences were not statistically significant (P < 0.05). CONCLUSION: This study lays a solid foundation for accurate dental implantation.

Preoperative 3D reconstruction and fluorescent indocyanine green for laparoscopic duodenum preserving pancreatic head resection: A case report.

BACKGROUND: Duodenum-preserving pancreatic head resection (DPPHR) is the choice of surgery for benign or low-grade malignant tumors of the pancreatic head. Laparoscopic DPPHR (LDPPHR) procedure can be improved by preoperative 3D model reconstruction and the use of intravenous indocyanine green fluorescent before surgery for real-time navigation with fluorescent display to guide the surgical dissection and prevention of from injury to vessels and biliary tract. CASE SUMMARY: Here we report the successful short- and long-term outcomes after one year following LDPPHR for a 60-year lady who had an uneventful recovery and was discharged home one week after the surgery. CONCLUSION: There was no bile leakage or pancreatic leakage or delayed gastric emptying. The histopathology report showed multiple cysts in the pancreatic head and localized pancreatic intraepithelial tumor lesions. The resected margin was free of tumor.

The anterior talofibular ligament: A thin-slice three-dimensional magnetic resonance imaging study.

PURPOSE: The aim of this study was to provide an accurate and improved understanding of anterior talofibular ligament (ATFL) anatomy, and to determine the exact positioning and diameter of the bony tunnel during ATFL repair and/or reconstruction surgery. METHOD: A total of 58 healthy asymptomatic volunteers were examined, wherein 38 underwent bilateral ankle 3D MRI, and 20 underwent unilateral ankle 3D MRI (10 left and 10 right ankles). Data from a total of 96 MRI datasets were collected. The MRI data from these cases were exported into Mimics to enable reconstruction of 3D ATFL models. The resulting image quality was evaluated using a 5-point subjective scoring system. In addition, the length, width, thickness, and positioning of each ATFL and the area of the ATFL footprints were identified within the 3D model using Mimics and SolidWorks. RESULTS: The image quality score was 4.48 ± 0.50. The ATFL formed one (65.6%), two (31.3%), or three (3.1%) bundles forms. The footprint area was 31.25 ± 6.29 mm2 on the fibular side, and 17.48 ± 4.49 mm2 on the talar side. CONCLUSION: Thin-slice 3D MRI aids in the reconstruction of the 3D ATFL model, and it provides reference for the accurate anatomy of the area and location of the ATFL. This technology will facilitate diagnosis of ATFL injuries and choice of surgical methods. LEVEL OF EVIDENCE: level IV.

Model reconstruction and morphological observation of internal carotid artery siphon and ophthalmic artery in non-arteritic anterior ischemic optic neuropathy patients / 中华眼底病杂志

Objective:To observe the morphological characteristics of internal carotid artery (ICA) siphon and ophthalmic artery (OA) in patients with non-arteritic anterior ischemic optic neuropathy (NAION) based on CT angiography (CTA) three-dimensional reconstruction of ICA siphon and OA models.Methods:A retrospective cohort study. From January 2017 to January 2019, 26 patients with 31 eyes (NAION group) who were diagnosed with NAION by ophthalmic examination at Beijing Friendship Hospital, Capital Medical Universitywere included in the study. Among them, there were 11 males with 13 eyes, and 15 females with 18 eyes; the age was 67.52±6.30 years old. Nineteen eyes of 19 non-affected contralateral eyes were selected as the contralateral eye group. Among them, there were 9 males with 9 eyes and 10 females with 10 eyes; the age was 65.95±5.66 years old. Twenty-six eyes of 26 age- and sex-matched subjects with normal fundus examination during the same period were selected as the normal control group. All subjects underwent best corrected visual acuity (BCVA), intraocular pressure, fundus photography and CTA examination. The data obtained from CT scans were reconstructed by 3D model, and the anatomical morphology of ICA siphon was divided into U-shape, V-shape, C-shape and S-shape; the diameter of ICA siphon portion and the diameter at the beginning of OA were measured. One-way analysis of variance was used to compare the diameter of the OA at the beginning of the OA and the diameter of the ICA siphon between the three groups of eyes.Results:The diameters at the beginning of OA in the NAION group, the contralateral eye group, and the normal control group were 1.17±0.20, 1.34±0.17, and 1.39±0.15 mm, respectively, and the differences among the three groups were statistically significant ( F=12.325, P<0.05); there was no significant difference between the contralateral eye group and the normal control group ( P=0.310). In the NAION group, the anatomical morphology of the ICA siphon was U-shaped and V-shaped in 20 (64.52%) and 8 (25.81%) eyes respectively, and S and C-shaped in 3 eyes (9.67%); in the contralateral eye group, in the control group, the ICA siphon shape of the eyes examined was U-shaped and V-shaped, and S-shaped and C-shaped were rare. The diameters of the ICA siphons in the NAION group, the contralateral eye group, and the normal control group were 3.50±0.69, 3.22±0.59, and 3.55±0.54 mm, respectively. There was no significant difference between the three groups ( F=1.860, P=0.163). Conclusion:U-shaped and V-shaped ICA siphons are more common in NAION-affected eyes; the diameter of the starting point of OA is significantly reduced.

Fruit Detection and Pose Estimation for Grape Cluster-Harvesting Robot Using Binocular Imagery Based on Deep Neural Networks.

Reliable and robust fruit-detection algorithms in nonstructural environments are essential for the efficient use of harvesting robots. The pose of fruits is crucial to guide robots to approach target fruits for collision-free picking. To achieve accurate picking, this study investigates an approach to detect fruit and estimate its pose. First, the state-of-the-art mask region convolutional neural network (Mask R-CNN) is deployed to segment binocular images to output the mask image of the target fruit. Next, a grape point cloud extracted from the images was filtered and denoised to obtain an accurate grape point cloud. Finally, the accurate grape point cloud was used with the RANSAC algorithm for grape cylinder model fitting, and the axis of the cylinder model was used to estimate the pose of the grape. A dataset was acquired in a vineyard to evaluate the performance of the proposed approach in a nonstructural environment. The fruit detection results of 210 test images show that the average precision, recall, and intersection over union (IOU) are 89.53, 95.33, and 82.00%, respectively. The detection and point cloud segmentation for each grape took approximately 1.7 s. The demonstrated performance of the developed method indicates that it can be applied to grape-harvesting robots.

A novel no-sensors 3D model reconstruction from monocular video frames for a dynamic environment.

Occlusion awareness is one of the most challenging problems in several fields such as multimedia, remote sensing, computer vision, and computer graphics. Realistic interaction applications are suffering from dealing with occlusion and collision problems in a dynamic environment. Creating dense 3D reconstruction methods is the best solution to solve this issue. However, these methods have poor performance in practical applications due to the absence of accurate depth, camera pose, and object motion.This paper proposes a new framework that builds a full 3D model reconstruction that overcomes the occlusion problem in a complex dynamic scene without using sensors' data. Popular devices such as a monocular camera are used to generate a suitable model for video streaming applications. The main objective is to create a smooth and accurate 3D point-cloud for a dynamic environment using cumulative information of a sequence of RGB video frames. The framework is composed of two main phases. The first uses an unsupervised learning technique to predict scene depth, camera pose, and objects' motion from RGB monocular videos. The second generates a frame-wise point cloud fusion to reconstruct a 3D model based on a video frame sequence. Several evaluation metrics are measured: Localization error, RMSE, and fitness between ground truth (KITTI's sparse LiDAR points) and predicted point-cloud. Moreover, we compared the framework with different widely used state-of-the-art evaluation methods such as MRE and Chamfer Distance. Experimental results showed that the proposed framework surpassed the other methods and proved to be a powerful candidate in 3D model reconstruction.

Reconstruction and optimization of the 3D geometric anatomy structure model for subject-specific human knee joint based on CT and MRI images.

BACKGROUND: Nowadays, the total knee arthroplasty (TKA) technique plays an important role in surgical treatment for patients with severe knee osteoarthritis (OA). However, there are still several key issues such as promotion of osteotomy accuracy and prosthesis matching degree that need to be addressed. OBJECTIVE: It is significant to construct an accurate three-dimensional (3D) geometric anatomy structure model of subject-specific human knee joint with major bone and soft tissue structures, which greatly contributes to obtaining personalized osteotomy guide plate and suitable size of prosthesis. METHODS: Considering different soft tissue structures, magnetic resonance imaging (MRI) scanning sequences involving two-dimensional (2D) spin echo (SE) sequence T1 weighted image (T1WI) and 3D SE sequence T2 weighted image (T2WI) fat suppression (FS) are selected. A 3D modeling methodology based on computed tomography (CT) and two sets of MRI images is proposed. RESULTS: According to the proposed methods of image segmentation and 3D model registration, a novel 3D knee joint model with high accuracy is finally constructed. Furthermore, remeshing is used to optimize the established model by adjusting the relevant parameters. CONCLUSIONS: The modeling results demonstrate that reconstruction and optimization model of 3D knee joint can clearly and accurately reflect the key characteristics, including anatomical structure and geometric morphology for each component.

High-Quality Genome-Scale Models From Error-Prone, Long-Read Assemblies.

Advances in nanopore-based sequencing techniques have enabled rapid characterization of genomes and transcriptomes. An emerging application of this sequencing technology is point-of-care characterization of pathogenic bacteria. However, genome assessments alone are unable to provide a complete understanding of the pathogenic phenotype. Genome-scale metabolic reconstruction and analysis is a bottom-up Systems Biology technique that has elucidated the phenotypic nuances of antimicrobial resistant (AMR) bacteria and other human pathogens. Combining these genome-scale models (GEMs) with point-of-care nanopore sequencing is a promising strategy for combating the emerging health challenge of AMR pathogens. However, the sequencing errors inherent to the nanopore technique may negatively affect the quality, and therefore the utility, of GEMs reconstructed from nanopore assemblies. Here we describe and validate a workflow for rapid construction of GEMs from nanopore (MinION) derived assemblies. Benchmarking the pipeline against a high-quality reference GEM of Escherichia coli K-12 resulted in nanopore-derived models that were >99% complete even at sequencing depths of less than 10× coverage. Applying the pipeline to clinical isolates of pathogenic bacteria resulted in strain-specific GEMs that identified canonical AMR genome content and enabled simulations of strain-specific microbial growth. Additionally, we show that treating the sequencing run as a mock metagenome did not degrade the quality of models derived from metagenome assemblies. Taken together, this study demonstrates that combining nanopore sequencing with GEM construction pipelines enables rapid, in situ characterization of microbial metabolism.

In vivo deformation of the spine canal before and after surgical corrections of severe and rigid kyphoscoliosis.

BACKGROUND: Ponte osteotomy and posterior vertebral column resection (PVCR) are two popular surgical techniques in treatment of severe and rigid kyphoscoliosis. However, quantitative effects of the two surgeries on spinal cord deformation are unclear. This information is critical for improvement of the treatment methods that can maximally correct the spinal deformity and prevent neurological complications. METHODS: Ten patients with severe kyphoscoliosis were investigated. X-ray and CT images of full spine of all patients were acquired before and 6-24 months after surgical treatment using either Ponte osteotomy or PVCR. A 3D model of the spine was constructed for each patient using the CT images that included the spinal canal between T2 and L2 vertebrae. The spinal canal length (SCL) was determined at 5 locations on the cross section of the canal: anterior, posterior, left, right (concave or convex side) and centre positions. The perpendicular distances between the T2 and L2 vertebrae, COBB angles and patient reported outcome measures before and after operations were determined. RESULTS: For patients treated with Ponte osteotomy, the SCLs were elongated by 12.7 ± 9.5 mm (5.4 ± 3.9%) at the concave side and 3.2 ± 6.8 mm (1.3 ± 2.8%) at the convex side. The COBB angle was corrected by 55.8% and the T2-L2 distance was increased by 66.1 ± 12.0 mm (68.4 ± 15.9%). For patients treated using PVCR, the SCLs were shortened by -5.5 ± 5.3 mm (-2.3 ± 2.2%) at the concave side and -14.0 ± 6.6 mm (-5.2 ± 2.6%) at the convex side. The COBB angle was corrected by 60.0% and the T2-L2 distance was increased by 41.5 ± 12.4 mm (32.1 ± 23.0%). The patient reported outcome scores were improved using both surgeries (p < 0.05). CONCLUSION: Ponte and PVCR surgeries caused significant changes of the SCL in scoliosis patients in different ways. The Ponte osteotomy mainly caused elongation of the SCL at concave side and the PVCR caused compression of the SCL at the convex side. Both surgeries partially improved the spinal deformity. The data provide insights for development of new surgical techniques that integrates the advantages of both Ponte and PVCR osteotomies to maximally correct the spine deformity and prevent neurological complications. THE TRANSLATIONAL POTENTIAL OF THIS ARTICLE: The methodology and the data presented in this paper could be instrumental for development of computer assisted surgical techniques that can maximally correct the spinal deformity and minimize the effect on the spinal cord in scoliosis patients.

Micro-Computed Tomography to Assess the Processing Quality of the Additive Manufacturing of Spiral Microcoils.

Additive manufactured polymers and metallized microstructures are widely used in the production of electronic components. However, such three-dimensional printed metallized electrical components inevitably have processing errors that affect their performance. It is vital to understand defects' effects on the performance of the final product. In this study, we simulated micro-computed tomography (CT) data. A spiral cavity is printed by stereolithography and spiral inductors with different numbers of turns are fabricated by injecting Gallium Indium liquid metal (EGaIn). Through the theoretical simulation of the spiral inductor and the characterization of the electrical performance, we found that the relative error in the simulation of 2.5-turn, 4.5-turn, and 6.5-turn spiral inductors is +30.6%, +13%, and +6%, respectively, compared with the experimental data. The CT data are obtained by a CT scanning microcoil and a reconstruction model with real structural features is established based on the data. The results show that the relative error between the reconstructed model with real defects and the experimental data is +10.4%, -3.7%, and -1.5%, respectively, which is closer to the experimental data. According to the CT data simulation that provides a more accurate theoretical prediction, the actual effect of a defect on the final product can be assessed. The difference between the experimental results and the theoretical simulation can be inferred from the reconstruction model.

The Reconstruction of a Bronze Battle Axe and Comparison of Inflicted Damage Injuries Using Neutron Tomography, Manufacturing Modeling, and X-ray Microtomography Data.

A massive bronze battle axe from the Abashevo archaeological culture was studied using neutron tomography and manufacturing modeling from production molds. Detailed structural data were acquired to simulate and model possible injuries and wounds caused by this battle axe. We report the results of neutron tomography experiments on the bronze battle axe, as well as manufactured plastic and virtual models of the traumas obtained at different strike angles from this axe. The reconstructed 3D models of the battle axe, plastic imprint model, and real wound and trauma traces on the bones of the ancient peoples of the Abashevo archaeological culture were obtained. Skulls with traces of injuries originate from archaeological excavations of the Pepkino burial mound of the Abashevo culture in the Volga region. The reconstruction and identification of the injuries and type of weapon on the restored skulls were performed. The complementary use of 3D visualization methods allowed us to make some assumptions on the cause of death of the people of the Abashevo culture and possible intra-tribal conflict in this cultural society. The obtained structural and anthropological data can be used to develop new concepts and methods for the archaeology of conflict.

Experimental study of the effect of typical halides on pyrolysis of ammonium nitrate using model reconstruction.

The energetic material ammonium nitrate (AN) is used as an industrial raw material; however, it presents a pyrolysis and explosion hazard during transportation and storage, especially when mixed with impurities. To study the effects of typical halides on the thermal decomposition kinetics of AN, a series of precision thermogravimetric analysis experiments at four heating rates were carried out in a nitrogen atmosphere. Based on derivative thermogravimetric analysis, the addition of sodium halides was found to change the kinetic reaction mechanism of AN pyrolysis. The activation energies were obtained using the isoconversional method, and the pre-exponential factor was derived from the kinetic compensation effect. Models of the kinetic reaction mechanism were reliably reconstructed by combining composite kinetic data processing methods, namely, model-free method, model-fitting method, and parameter simulation. A comprehensive analysis showed that the addition of sodium halides shifts the kinetic mechanism of the pyrolysis of AN toward different dominant reaction models (such as reaction order models, power law models, or phase boundary control models) than those of the original reaction model. The results are helpful as a reference and provide guidance for the determination of AN pyrolysis behavior and the simulation of parameters.

Ultra-low-dose multiphase CT angiography derived from CT perfusion data in patients with middle cerebral artery stenosis.

PURPOSE: Computed tomography (CT) perfusion (CTP) source images contain both brain perfusion and cerebrovascular information, and may allow a dynamic assessment of collaterals. The purpose of the study was to compare the image quality and the collaterals identified on multiphase CT angiography (CTA) derived from CTP datasets (hereafter called CTPA) reconstructed with iterative model reconstruction (IMR) algorithm in patients with middle cerebral artery (MCA) steno-occlusion with those of routine CTA. METHODS: Consecutive patients with a unilateral MCA steno-occlusion underwent non-contrast CT (NCCT), CTP, and CTA. CTPA images were reconstructed from CTP datasets. The vascular attenuation, image noise, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) of routine CTA and CTPA were measured and analyzed by Student's t test. Subjective image quality and collaterals were scored and compared using the Wilcoxon signed-rank test. RESULTS: Fifty-eight patients (mean age 61.7 years, 78% males, median National Institutes of Health Stroke Scale score = 12) were included. The effective radiation dose of CTP was 1.28 mSv. The vascular attenuation, SNR, CNR, and the image quality of CTPA were considerably higher than that of CTA (all, p < 0.001). Collaterals were rated higher on CTPA compared with CTA (1.79 ± 0.64 vs. 1.22 ± 0.84, p < 0.001). Fifty-three percent of patients with poor collaterals assessed on single-phase CTA had good collaterals on CTPA. CONCLUSION: CTPA derived from CTP datasets reconstructed with IMR algorithm offers image quality comparable to routine CTA and provides time-resolved evaluation of collaterals in patients with MCA ischemic disease.

Feasibility of assessment of chronic sinusitis using iterative model reconstruction combined with 256-slice iCT low-dose scan / 中国医学影像技术

Objective: To explore the feasibility of iterative model reconstruction (IMR) combined with 256-slice iCT low-dose scan in assessment of chronic sinusitis. Methods: Twenty patients with clinically diagnosed chronic sinusitis were examined with conventional dose CT scan and low-dose CT scan. According to dose right index (DRI) and reconstruction algorithms, CT data were divided into SD-FBP group, LD-IMR-L1 group, LD-IMR-L2 group and LD-IMR-L3 group. The volume CT dose index (CTDIvol), dose-length product (DLP) and the effective dose (ED) were recorded under different scanning schemes. The objective noise value of images were measured. The differences of image noise, artifacts and displaying of anatomical structures of ostiomeatal complex and lesions were analyzed. Results: SD-FBP group, LD-IMR-L3 group, LD-IMR-L2 group and LD-IMR-L1 group were in a descending order of image noise values. No significant difference of average noise value between LD-IMR-L3 group and SD-FBP group was found(P>0.05). The noise value of LD-IMR-L2 group and LD-IMR-L1 group were higher than that of SD-FBP group (both P0.05), which would both satisfy diagnostic requirements. The displaying of anatomical details was better in SD-FBP group groups than that in LD-IMR, but the scores in LD-IMR groups were all above 3 points and able to satisfy diagnostic requirements. CTDIvol, DLP and ED in LD-IMR groups reduced by 89.20%, 89.37% and 89.36% compared with those in SD-FBP group, respectively. Conclusion: IMR low-dose sinus CT can satisfy the requirements of displaying important bone structures of ostiomeatal complex and diagnosing chronic sinusitis with reduced ED.

Numerical Reconstruction Model and Simulation Study of Concrete Based on Damaged Partition Theory and CT Number.

The applicability of mesoscopic models plays an important role in studying the mesoscopic mechanical properties of concrete. In this study, the computerized tomography (CT) test of concrete under uniaxial compression conditions is conducted using a portable dynamic loading equipment developed by Xi'an University of Technology and a medical Marconi M8000 spiral CT scanner. On the basis of damage partition theory, a probabilistic statistical method for determining threshold values is proposed, and a CT test images is obtained and divided into aggregate, hardened cement and hole-crack areas. A 'structural random numerical concrete model' is also established on the basis of the coordinates of each pixel unit in CT images. Uniaxial static compression and tensile numerical simulation tests are conducted. Results show that the structural random numerical concrete model can not only reflect the microscopic composition of concrete but also the interfacial transition zone (ITZ) between aggregate and mortar. The ITZ thickness is approximately 0.04 mm, which is close to the real concrete sample ITZ thickness (approximately 10-50 µm). In the two tests, the specimen damage starts from the initial defects, and the damage crack expands through the weaker ITZ around the aggregate. No matter under the action of static tension or compression load, the damage cracks of the sample almost never pass through the aggregate. Most of the many cracks in uniaxial compression are shear cracks. However, many cracks form at the beginning of uniaxial tension, and only one main crack, which is roughly perpendicular to the loading direction, exists in the end.