3D exploration of gene expression in chicken embryos through combined RNA fluorescence in situ hybridization, immunofluorescence, and clearing.

BACKGROUND: Fine characterization of gene expression patterns is crucial to understand many aspects of embryonic development. The chicken embryo is a well-established and valuable animal model for developmental biology. The period spanning from the third to sixth embryonic days (E3 to E6) is critical for many organ developments. Hybridization chain reaction RNA fluorescent in situ hybridization (HCR RNA-FISH) enables multiplex RNA detection in thick samples including embryos of various animal models. However, its use is limited by tissue opacity. RESULTS: We optimized HCR RNA-FISH protocol to efficiently label RNAs in whole mount chicken embryos from E3.5 to E5.5 and adapted it to ethyl cinnamate (ECi) tissue clearing. We show that light sheet imaging of HCR RNA-FISH after ECi clearing allows RNA expression analysis within embryonic tissues with good sensitivity and spatial resolution. Finally, whole mount immunofluorescence can be performed after HCR RNA-FISH enabling as exemplified to assay complex spatial relationships between axons and their environment or to monitor GFP electroporated neurons. CONCLUSIONS: We could extend the use of HCR RNA-FISH to older chick embryos by optimizing HCR RNA-FISH and combining it with tissue clearing and 3D imaging. The integration of immunostaining makes possible to combine gene expression with classical cell markers, to correlate expressions with morphological differentiation and to depict gene expressions in gain or loss of function contexts. Altogether, this combined procedure further extends the potential of HCR RNA-FISH technique for chicken embryology.

Dome versus single-cut osteotomies for correction of long bone deformities-technical considerations.

Corrective osteotomy allows to improve joint loading, pain and function. In complex deformities, the biggest challenge is to define the optimal surgical solution, while considering anatomical, technical and biomechanical factors. While the single-cut osteotomy (SCOT) and focal dome osteotomy (FDO) are well-established treatment options, their mathematical relationship remain largely unclear. The aim of the study was (1) to describe the close mathematical relationship between the SCOT and FDO and (2) to analyze and introduce a novel technique-the stepped FDO-as a modification of the classic FDO. The mathematical background and relationship of SCOT and FDO are described for the example of a femoral deformity correction and visualized using a 3D surface model taking into account the benefits for the clinical application. The novel modifications of the stepped FDO are introduced and its technical and clinical feasibility demonstrated. Both, SCOT and FDO, rely on the same deformity axis that defines the rotation axis k for a 3D deformity correction. To achieve the desired correction using a SCOT, the resulting cutting plane is perpendicular to k, while using a FDO will result in a cylindrical cut with a central axis parallel to k. The SCOT and FDO demonstrate a strong mathematical relation, as both methods rely on the same deformity axis, however, resulting in different cutting planes. These characteristics enable a complementary use when defining the optimal type of osteotomy. This understanding enables a more versatile planning approach when considering factors as the surgical approach, biomechanical characteristics of fixation or soft tissue conditions. The newly introduced stepped FDO facilitates an exact reduction of the bone fragments and potentially expands the clinical applicability of the FDO.

3D Tortuosity computation as a shape descriptor and its application to brain structure analysis.

In this study, we propose a novel method for quantifying tortuosity in 3D voxelized objects. As a shape characteristic, tortuosity has been widely recognized as a valuable feature in image analysis, particularly in the field of medical imaging. Our proposed method extends the two-dimensional approach of the Slope Chain Code (SCC) which creates a one-dimensional representation of curves. The utility of 3D tortuosity ( τ 3 D ) as a shape descriptor was investigated by characterizing brain structures. The results of the τ 3 D computation on the central sulcus and the main lobes revealed significant differences between Alzheimer's disease (AD) patients and control subjects, suggesting its potential as a biomarker for AD. We found a p < 0.05 for the left central sulcus and the four brain lobes.

Estimating body volumes and surface areas of animals from cross-sections.

Background: Body mass and surface area are among the most important biological properties, but such information is lacking for some extant organisms and most extinct species. Numerous methods have been developed for body size estimation of animals for this reason. There are two main categories of mass-estimating approaches: extant-scaling approaches and volumetric-density approaches. Extant-scaling approaches determine the relationships between linear skeletal measurements and body mass using regression equations. Volumetric-density approaches, on the other hand, are all based on models. The models are of various types, including physical models, 2D images, and 3D virtual reconstructions. Once the models are constructed, their volumes are acquired using Archimedes' Principle, math formulae, or 3D software. Then densities are assigned to convert volumes to masses. The acquisition of surface area is similar to volume estimation by changing math formulae or software commands. This article presents a new 2D volumetric-density approach called the cross-sectional method (CSM). Methods: The CSM integrates biological cross-sections to estimate volume and surface area accurately. It requires a side view or dorsal/ventral view image, a series of cross-sectional silhouettes and some measurements to perform the calculation. To evaluate the performance of the CSM, two other 2D volumetric-density approaches (Graphic Double Integration (GDI) and Paleomass) are compared with it. Results: The CSM produces very accurate results, with average error rates around 0.20% in volume and 1.21% in area respectively. It has higher accuracy than GDI or Paleomass in estimating the volumes and areas of irregular-shaped biological structures. Discussion: Most previous 2D volumetric-density approaches assume an elliptical or superelliptical approximation of animal cross-sections. Such an approximation does not always have good performance. The CSM processes the true profiles directly rather than approximating and can deal with any shape. It can process objects that have gradually changing cross-sections. This study also suggests that more attention should be paid to the careful acquisition of cross-sections of animals in 2D volumetric-density approaches, otherwise serious errors may be introduced during the estimations. Combined with 2D modeling techniques, the CSM can be considered as an alternative to 3D modeling under certain conditions. It can reduce the complexity of making reconstructions while ensuring the reliability of the results.

Specific pelvic shape in patients with developmental dysplasia of the hip on 3D morphometric homologous model analysis.

PURPOSE: To clarify the morphological factors of the pelvis in patients with developmental dysplasia of the hip (DDH), three-dimensional (3D) pelvic morphology was analyzed using a template-fitting technique. METHODS: Three-dimensional pelvic data of 50 patients with DDH (DDH group) and 3D pelvic data of 50 patients without obvious pelvic deformity (Normal group) were used. All patients were female. A template model was created by averaging the normal pelvises into a symmetrical and isotropic mesh. Next, 100 homologous models were generated by fitting the pelvic data of each group of patients to the template model. Principal component analysis was performed on the coordinates of each vertex (15,235 vertices) of the pelvic homologous model. In addition, a receiver-operating characteristic (ROC) curve was calculated from the sensitivity of DDH positivity for each principal component, and principal components for which the area under the curve was significantly large were extracted (p<0.05). Finally, which components of the pelvic morphology frequently seen in DDH patients are related to these extracted principal components was evaluated. RESULTS: The first, third, and sixth principal components showed significantly larger areas under the ROC curves. The morphology indicated by the first principal component was associated with a decrease in coxal inclination in both the coronal and horizontal planes. The third principal component was related to the sacral inclination in the sagittal plane. The sixth principal component was associated with narrowing of the superior part of the pelvis. CONCLUSION: The most important factor in the difference between normal and DDH pelvises was the change in the coxal angle in both the coronal and horizontal planes. That is, in the anterior and superior views, the normal pelvis is a triangle, whereas in DDH, it was more like a quadrilateral.

Natural scenes reveal diverse representations of 2D and 3D body pose in the human brain.

Human pose, defined as the spatial relationships between body parts, carries instrumental information supporting the understanding of motion and action of a person. A substantial body of previous work has identified cortical areas responsive to images of bodies and different body parts. However, the neural basis underlying the visual perception of body part relationships has received less attention. To broaden our understanding of body perception, we analyzed high-resolution fMRI responses to a wide range of poses from over 4,000 complex natural scenes. Using ground-truth annotations and an application of three-dimensional (3D) pose reconstruction algorithms, we compared similarity patterns of cortical activity with similarity patterns built from human pose models with different levels of depth availability and viewpoint dependency. Targeting the challenge of explaining variance in complex natural image responses with interpretable models, we achieved statistically significant correlations between pose models and cortical activity patterns (though performance levels are substantially lower than the noise ceiling). We found that the 3D view-independent pose model, compared with two-dimensional models, better captures the activation from distinct cortical areas, including the right posterior superior temporal sulcus (pSTS). These areas, together with other pose-selective regions in the LOTC, form a broader, distributed cortical network with greater view-tolerance in more anterior patches. We interpret these findings in light of the computational complexity of natural body images, the wide range of visual tasks supported by pose structures, and possible shared principles for view-invariant processing between articulated objects and ordinary, rigid objects.

The cytoarchitectonic landscape revealed by deep learning method facilitated precise positioning in mouse neocortex.

Neocortex is a complex structure with different cortical sublayers and regions. However, the precise positioning of cortical regions can be challenging due to the absence of distinct landmarks without special preparation. To address this challenge, we developed a cytoarchitectonic landmark identification pipeline. The fluorescence micro-optical sectioning tomography method was employed to image the whole mouse brain stained by general fluorescent nucleotide dye. A fast 3D convolution network was subsequently utilized to segment neuronal somas in entire neocortex. By approach, the cortical cytoarchitectonic profile and the neuronal morphology were analyzed in 3D, eliminating the influence of section angle. And the distribution maps were generated that visualized the number of neurons across diverse morphological types, revealing the cytoarchitectonic landscape which characterizes the landmarks of cortical regions, especially the typical signal pattern of barrel cortex. Furthermore, the cortical regions of various ages were aligned using the generated cytoarchitectonic landmarks suggesting the structural changes of barrel cortex during the aging process. Moreover, we observed the spatiotemporally gradient distributions of spindly neurons, concentrated in the deep layer of primary visual area, with their proportion decreased over time. These findings could improve structural understanding of neocortex, paving the way for further exploration with this method.

Intraoral scanner-based monitoring of tooth wear in young adults: 36-month results.

OBJECTIVES: The study continues our longitudinal observation of wear aiming to further monitoring of progression and lesion morphology and to identify relationships with assumed aetiological factors. MATERIALS AND METHODS: Molars (FDI #36 or #46) of 74 participants (23.8 ± 2.2 years) were scanned (Trios 3, 3Shape) at the third follow-up (T3; observation period 1,111 ± 10 days). Data sets from T3, T2 (24-month follow-up) and T1 (12-month follow-up) were superimposed with baseline in a 3D analysis software (GOM Inspect). Wear was quantified as maximum vertical tissue loss (µm; median, 95% CI) in various occlusal areas (4/5 cusps and 2 ridges). Morphologies were classified into cupping (C), facet (F), and combined cupping-facet (CF). Aetiological factors were assessed with questionnaires. RESULTS: Wear increased at T3 significantly at low rates in all areas of the occlusal surface (median between 7.0 (4.0;10.5) and 9.5 (6.0;15.0) µm). There was a clear trend for higher loss values in males, but no association with other factors such as nutrition. C and CF showed significantly higher loss values than F. Areas without initial wear developed F first, which either persisted or developed into C and CF. CONCLUSIONS: Wear continued at low rates with C/CF morphology and sex as significant factors. Cupped lesions seem to develop from facets and thus may not be a valid diagnostic criterion for erosive tooth wear. CLINICAL RELEVANCE: Wear is a cumulative process that apparently follows complex mechanisms that cannot be conceptualized in simplified terms; C and CF may be indicators for higher progression rates.

Chondrosarcoma evaluation using hematein-based x-ray staining and high-resolution 3D micro-CT: a feasibility study.

BACKGROUND: Chondrosarcomas are rare malignant bone tumors diagnosed by analyzing radiological images and histology of tissue biopsies and evaluating features such as matrix calcification, cortical destruction, trabecular penetration, and tumor cell entrapment. METHODS: We retrospectively analyzed 16 cartilaginous tumor tissue samples from three patients (51-, 54-, and 70-year-old) diagnosed with a dedifferentiated chondrosarcoma at the femur, a moderately differentiated chondrosarcoma in the pelvis, and a predominantly moderately differentiated chondrosarcoma at the scapula, respectively. We combined a hematein-based x-ray staining with high-resolution three-dimensional (3D) microscopic x-ray computed tomography (micro-CT) for nondestructive 3D tumor assessment and tumor margin evaluation. RESULTS: We detected trabecular entrapment on 3D micro-CT images and followed bone destruction throughout the volume. In addition to staining cell nuclei, hematein-based staining also improved the visualization of the tumor matrix, allowing for the distinction between the tumor and the bone marrow cavity. The hematein-based staining did not interfere with further conventional histology. There was a 5.97 ± 7.17% difference between the relative tumor area measured using micro-CT and histopathology (p = 0.806) (Pearson correlation coefficient r = 0.92, p = 0.009). Signal intensity in the tumor matrix (4.85 ± 2.94) was significantly higher in the stained samples compared to the unstained counterparts (1.92 ± 0.11, p = 0.002). CONCLUSIONS: Using nondestructive 3D micro-CT, the simultaneous visualization of radiological and histopathological features is feasible. RELEVANCE STATEMENT: 3D micro-CT data supports modern radiological and histopathological investigations of human bone tumor specimens. It has the potential for being an integrative part of clinical preoperative diagnostics. KEY POINTS: • Matrix calcifications are a relevant diagnostic feature of bone tumors. • Micro-CT detects all clinically diagnostic relevant features of x-ray-stained chondrosarcoma. • Micro-CT has the potential to be an integrative part of clinical diagnostics.

[Comparative evaluation of the accuracy of 3D TMJ analysis performed by different methods of processing computed tomograms]. / Sravnitel'naya otsenka tochnosti 3D-analiza elementov visochno-nizhnechelyustnogo sustava, vypolnennogo raznymi sposobami obrabotki komp'yuternykh tomogramm.

OBJECTIVE: The aim of this study. Comparison of the accuracy of segmentation of TMJ elements in different ways and assessment of the suitability of the data obtained for the diagnosis of TMJ dysfunction. MATERIALS AND METHODS: To study the segmentation of the bone elements of the TMJ (articular fossa, head of the LF), 60 computed tomograms of the maxillofacial region of patients were randomly selected in various ways (archival material). In group 1, the results of CT processing by AI diagnostics algorithms (Russia) were collected; in group 2, the results of CT processing based on the semi-automatic segmentation method in the Avantis3D program. The results of CT processing by Avantis3D AI algorithms (Russia) with different probability modes - 0.4 and 0.9, respectively, were selected for the third and fourth groups. Visually, the coincidence of the contours of the LF heads and articular pits isolated using different methods with their contours on all possible sections of the original CT itself was evaluated. The time spent on TMJ segmentation according to CT data was determined and compared using the methods described above. RESULTS: Of the 240 objects, only 7.5% of the cases showed a slight discrepancy between the contours of the original CT in group b1, which was the lowest of all. A slight discrepancy in the TMJ contours to be corrected is characteristic of the semi-automatic method of segmentation by optical density was detected in 50.4% (group 2). The largest percentage of significant errors not subject to correction was noted in the first group, which made it impossible to perform a full 3D analysis of the TMJ, and the smallest in the second and fourth. The magnitude of the error in determining the width of the articular gap in different groups is comparable to the size of one voxel per CT. When segmentation is carried out using AI, the difference between segmented objects is close to zero values. The average time spent on TMJ segmentation in group 1 was 10.2±1.23 seconds, in group 2 - 12.6±1.87 seconds, in groups 3 and 4 - 0.46±0.12 seconds and 0.46±0.13 seconds, respectively. CONCLUSION: The developed automated method for segmenting TMJ elements using AI is obviously more suitable for practical work, since it requires minimal time, and is almost as accurate as other methods under consideration.

Sodium quantification in skeletal muscle: comparison between Cartesian gradient-echo and radial ultra-short echo time 23Na MRI techniques.

BACKGROUND: Clinical magnetic resonance imaging (MRI) studies often use Cartesian gradient-echo (GRE) sequences with ~2-ms echo times (TEs) to monitor apparent total sodium concentration (aTSC). We compared Cartesian GRE and ultra-short echo time three-dimensional (3D) radial-readout sequences for measuring skeletal muscle aTSC. METHODS: We retrospectively evaluated 211 datasets from 112 volunteers aged 62.3 ± 12.1 years (mean ± standard deviation), acquired at 3 T from the lower leg. For 23Na MRI acquisitions, we used a two-dimensional Cartesian GRE sequence and a density-adapted 3D radial readout sequence with cuboid field-of-view (DA-3D-RAD-C). We calibrated the 23Na MR signal using reference tubes either with or without agarose and subsequently performed a relaxation correction. Additionally, we employed a six-echo 1H GRE sequence and a multi-echo spin-echo sequence to calculate proton density fat fraction (PDFF) and water T2. Paired Wilcoxon signed-rank test, Cohen dz for paired samples, and Spearman correlation were used. RESULTS: Relaxation correction effectively reduced the differences in muscle aTSC between the two acquisition and calibration methods (DA-3D-RAD-C using NaCl/agarose references: 20.05 versus 19.14 mM; dz = 0.395; Cartesian GRE using NaCl/agarose references: 19.50 versus 18.82 mM; dz = 0.427). Both aTSC of the DA-3D-RAD-C and Cartesian GRE acquisitions showed a small but significant correlation with PDFF as well as with water T2. CONCLUSIONS: Different 23Na MRI acquisition and calibration approaches affect aTSC values. Applying relaxation correction is advised to minimize the impact of sequence parameters on quantification, and considering additional fat correction is advisable for patients with increased fat fractions. RELEVANCE STATEMENT: This study highlights relaxation correction's role in improving sodium MRI accuracy, paving the way for better disease assessment and comparability of measured sodium signal in patients. KEY POINTS: • Differences in MRI acquisition methods hamper the comparability of sodium MRI measurements. • Measured sodium values depend on used MRI sequences and calibration method. • Relaxation correction during postprocessing mitigates these discrepancies. • Thus, relaxation correction enhances accuracy of sodium MRI, aiding its clinical use.

Svetlana a supervised segmentation classifier for Napari.

We present Svetlana (SuperVised sEgmenTation cLAssifier for NapAri), an open-source Napari plugin dedicated to the manual or automatic classification of segmentation results. A few recent software tools have made it possible to automatically segment complex 2D and 3D objects such as cells in biology with unrivaled performance. However, the subsequent analysis of the results is oftentimes inaccessible to non-specialists. The Svetlana plugin aims at going one step further, by allowing end-users to label the segmented objects and to pick, train and run arbitrary neural network classifiers. The resulting network can then be used for the quantitative analysis of biophysical phenoma. We showcase its performance through challenging problems in 2D and 3D and provide a comprehensive discussion on its strengths and limits.

Nasal Morphology in a Young Adult Middle-Eastern Population: A Stereophotogrammetric Analysis.

AIM: This study aimed to describe gender-specific three-dimensional morphology of the soft-tissue nose in Lebanese young adults and to explore the associations between nasal morphology with age and body mass index (BMI). MATERIALS AND METHODS: Three-dimensional photographs were captured for 176 young healthy Lebanese adults (75 males and 101 females) aged 18.1-37.68 years. Linear and angular nasal measurements were computed and compared between genders, in addition to other established norms. Associations with age and BMI were also assessed. RESULTS: All linear measurements were greater in males than in females, and only the nasolabial angle was significantly larger in females by 2.97 degrees on average. Most of the measurements were found to be larger than the Caucasian norms. A few significant correlations were found between the measurements and age or BMI. CONCLUSION: This study is the first to present the sex-specific norms for nasal morphology in the Lebanese population and highlights the presence of gender dimorphism in the majority of measurements. Additional studies are needed to validate our data and expand the associations with age and BMI. CLINICAL SIGNIFICANCE: The data offered in this study could help enhance the accuracy of facial reconstructive surgery and aid in personalized treatment planning for both medical and cosmetic nasal interventions. How to cite this article: Saadeh M, Shamseddine L, Fayyad-Kazan H, et al. Nasal Morphology in a Young Adult Middle-Eastern Population: A Stereophotogrammetric Analysis. J Contemp Dent Pract 2024;25(3):199-206.

STORM Super-Resolution Visualization of Self-Assembled γPFD Chaperone Ultrastructures in Methanocaldococcus jannaschii.

Gamma-prefoldin (γPFD), a unique chaperone found in the extremely thermophilic methanogen Methanocaldococcus jannaschii, self-assembles into filaments in vitro, which so far have been observed using transmission electron microscopy and cryo-electron microscopy. Utilizing three-dimensional stochastic optical reconstruction microscopy (3D-STORM), here we achieve ∼20 nm resolution by precisely locating individual fluorescent molecules, hence resolving γPFD ultrastructure both in vitro and in vivo. Through CF647 NHS ester labeling, we first demonstrate the accurate visualization of filaments and bundles with purified γPFD. Next, by implementing immunofluorescence labeling after creating a 3xFLAG-tagged γPFD strain, we successfully visualize γPFD in M. jannaschii cells. Through 3D-STORM and two-color STORM imaging with DNA, we show the widespread distribution of filamentous γPFD structures within the cell. These findings provide valuable insights into the structure and localization of γPFD, opening up possibilities for studying intriguing nanoscale components not only in archaea but also in other microorganisms.

Breast Glandular and Ductal Volume Changes during the Menstrual Cycle: A Study in 48 Breasts Using Ultralow-Frequency Transmitted Ultrasound Tomography/Volography.

The aim of this study was to show for the first time that low-frequency 3D-transmitted ultrasound tomography (3D UT, volography) can differentiate breast tissue types using tissue properties, accurately measure glandular and ductal volumes in vivo, and measure variation over time. Data were collected for 400 QT breast scans on 24 women (ages 18-71), including four (4) postmenopausal subjects, 6-10 times over 2+ months of observation. The date of onset of menopause was noted, and the cases were further subdivided into three (3) classes: pre-, post-, and peri-menopausal. The ducts and glands were segmented using breast speed of sound, attenuation, and reflectivity images and followed over several menstrual cycles. The coefficient of variation (CoV) for glandular tissue in premenopausal women was significantly larger than for postmenopausal women, whereas this is not true for the ductal CoV. The glandular standard deviation (SD) is significantly larger in premenopausal women vs. postmenopausal women, whereas this is not true for ductal tissue. We conclude that ducts do not appreciably change over the menstrual cycle in either pre- or post-menopausal subjects, whereas glands change significantly over the cycle in pre-menopausal women, and 3D UT can differentiate ducts from glands in vivo.

Lumbar and Thoracic Vertebrae Segmentation in CT Scans Using a 3D Multi-Object Localization and Segmentation CNN.

Radiation treatment of cancers like prostate or cervix cancer requires considering nearby bone structures like vertebrae. In this work, we present and validate a novel automated method for the 3D segmentation of individual lumbar and thoracic vertebra in computed tomography (CT) scans. It is based on a single, low-complexity convolutional neural network (CNN) architecture which works well even if little application-specific training data are available. It is based on volume patch-based processing, enabling the handling of arbitrary scan sizes. For each patch, it performs segmentation and an estimation of up to three vertebrae center locations in one step, which enables utilizing an advanced post-processing scheme to achieve high segmentation accuracy, as required for clinical use. Overall, 1763 vertebrae were used for the performance assessment. On 26 CT scans acquired for standard radiation treatment planning, a Dice coefficient of 0.921 ± 0.047 (mean ± standard deviation) and a signed distance error of 0.271 ± 0.748 mm was achieved. On the large-sized publicly available VerSe2020 data set with 129 CT scans depicting lumbar and thoracic vertebrae, the overall Dice coefficient was 0.940 ± 0.065 and the signed distance error was 0.109 ± 0.301 mm. A comparison to other methods that have been validated on VerSe data showed that our approach achieved a better overall segmentation performance.

Analysis of prefabricated myofunctional appliances with different overjet and bumper designs: a three-dimensional finite element analysis.

BACKGROUND: Prefabricated myofunctional appliance can guide tooth eruption, improve dentition alignment, correct myofunctional disorders and harmful oral habits. However, its application to skeletal discrepancy may result in unsatisfactory tooth inclination. This study aimed to construct a novel appliance with overjet design to avoid this side effect and investigated its shape and mechanical changes under occlusion using three-dimensional finite element method. METHODS: We established three samples of prefabricated myofunctional appliances. The first one was edge to edge without overjet, and the outer shield of both jaws were flattened. The second one was 3 mm overjet with stepped the outer shield. The last one was 3 mm overjet, and the outer shield of both jaws were flatted, which meant the front wall of lower jaw was strengthened with bumper, termed as lower bumper. A complete dentition model was applied to the study. 150 N occlusal force was applied to each type of appliance and the deformation displacement and the changes in stress was recorded. RESULTS: The deformation was significant in the incisors regions, especially in the vertical and lateral dimensions. The maximum displacements of 3 mm overjet with step shield group were 7.08 mm (vertical), 3.99 mm (lateral), and 2.90 mm (sagittal), while it decreased to 3.92 mm(vertical), 1.94 mm (lateral), and 1.55 mm (sagittal) in overjet with bumper group. Moreover, the upper molar regions exhibited higher vertical and sagittal displacement in 3 mm overjet with step shield group, which were 3.03 mm (vertical) and 1.99 mm (sagittal), and the bumper design could decrease the maximum displacement to 1.72 mm (vertical) and 0.72 mm (sagittal). In addition, the Von Mises stress of appliances was analyzed, and results indicated that 3 mm overjet with step shield generated higher stress than other groups, with the maximum Von Mises stress was 0.9387 MP, which were 0.5858 and 0.5657 MP in edge to edge group and 3 mm overjet with lower bumper group, respectively. CONCLUSION: The prefabricated myofunctional appliances may cause deformation during occlusion. Compared to step shield group, the application of lower bumper exhibited better resistance to occlusal force.

Whole-body magnetic resonance imaging at 0.05 Tesla.

Despite a half-century of advancements, global magnetic resonance imaging (MRI) accessibility remains limited and uneven, hindering its full potential in health care. Initially, MRI development focused on low fields around 0.05 Tesla, but progress halted after the introduction of the 1.5 Tesla whole-body superconducting scanner in 1983. Using a permanent 0.05 Tesla magnet and deep learning for electromagnetic interference elimination, we developed a whole-body scanner that operates using a standard wall power outlet and without radiofrequency and magnetic shielding. We demonstrated its wide-ranging applicability for imaging various anatomical structures. Furthermore, we developed three-dimensional deep learning reconstruction to boost image quality by harnessing extensive high-field MRI data. These advances pave the way for affordable deep learning-powered ultra-low-field MRI scanners, addressing unmet clinical needs in diverse health care settings worldwide.

BeST-Graft viewer, a new system to improve the bone allograft-recipient matching process.

INTRODUCTION: Tissue establishments are responsible for processing, testing, preserving, storing, and distributing allografts from donors to be transplanted into recipients. In some situations, a matching process is required to determine the allograft that best fits the recipient. Allograft morphology is a key consideration for the matching process. The manual procedures applied to obtain these parameters make the process error-prone. MATERIAL AND METHODS: A new system to manage bone allograft-recipient matching for tissue establishments is proposed. The system requires bone allografts to be digitalized and the resulting images to be stored in a DICOM file. The system provides functionalities to: (i) manage DICOM files (registered in the PACs) from both allografts and recipients; (ii) reconstruct 3D models from DICOM images; (iii) explore 3D models using 2D, 3D, and multiplanar reconstructions; (iv) take allograft and recipient measurements; and (v) visualize and interact with recipient and allograft data simultaneously. The system has been installed in the Barcelona Tissue Bank (Banc de Sang i Teixits), which has digitalized the bone allografts to test the system. RESULTS: A use case with a femur is presented to test all the viewer functionalities. In addition, the recipient-allograft workflow is evaluated to show the steps of the procedure where the viewer can be used. CONCLUSIONS: The bone allograft-recipient matching procedure can be optimized using software tools with functionalities to visualize, interact, and take measurements.

GMIM: Self-supervised pre-training for 3D medical image segmentation with adaptive and hierarchical masked image modeling.

Self-supervised pre-training and fully supervised fine-tuning paradigms have received much attention to solve the data annotation problem in deep learning fields. Compared with traditional pre-training on large natural image datasets, medical self-supervised learning methods learn rich representations derived from unlabeled data itself thus avoiding the distribution shift between different image domains. However, nowadays state-of-the-art medical pre-training methods were specifically designed for downstream tasks making them less flexible and difficult to apply to new tasks. In this paper, we propose grid mask image modeling, a flexible and general self-supervised method to pre-train medical vision transformers for 3D medical image segmentation. Our goal is to guide networks to learn the correlations between organs and tissues by reconstructing original images based on partial observations. The relationships are consistent within the human body and invariant to disease type or imaging modality. To achieve this, we design a Siamese framework consisting of an online branch and a target branch. An adaptive and hierarchical masking strategy is employed in the online branch to (1) learn the boundaries or small contextual mutation regions within images; (2) to learn high-level semantic representations from deeper layers of the multiscale encoder. In addition, the target branch provides representations for contrastive learning to further reduce representation redundancy. We evaluate our method through segmentation performance on two public datasets. The experimental results demonstrate our method outperforms other self-supervised methods. Codes are available at https://github.com/mobiletomb/Gmim.