Search

Background: Environmental and genetic factors associated with canine impaction have been extensively researched, whereas the bone characteristics in the impaction area have not been thoroughly studied. Accordingly, the objective of this investigation was to provide a skeletal assessment in terms of bone density, bone microstructure, bone volume, and palatal volume in subjects with unilaterally impacted maxillary canines., Methods: A retrospective design has been employed to address the aim of this study, where the initial pre-treatment cone-beam computed tomography (CBCT) scans of 30 patients with unilateral maxillary canine impaction were assessed. The obtained patients' data were equally divided according to the location of the impaction into 2 groups, one with buccally impacted canines, and another with palatal impactions, with the contra-lateral sides in both groups serving as the controls. Skeletal measurements such as bone density (BD), bone microstructure in terms of fractal dimension (FD), maxillary bone volume (MBV), and palatal volume (PV) were evaluated from the acquired CBCTs in both groups and compared to the controls., Results: With buccal impactions, significantly greater BD and FD have been reported (p < 0.001), whereas non-significant differences were found regarding the PV when compared with controls (p = 0.56). MBV was significantly greater on the non-impaction side in comparison with buccal impaction sides (p < 0.001). For palatal impactions: BD, FD, and MBV were significantly greater on the impaction sides (p < 0.001), and conversely with PV which has been reported to be significantly greater on the non-impaction sides (p < 0.001)., Conclusions: As per the obtained results, buccally impacted canines are associated with greater BD and FD, and less MBV, whereas palatally impacted canines are accompanied with greater BD, FD, and MBV, in addition to less PV, when both conditions are compared with the non-impaction sides., (© 2024. The Author(s).)

We present a method for real-time recording of human interaction with three-dimensional (3D) virtual objects. The approach consists of associating rotation data of the manipulated object with behavioral measures, such as eye tracking, to make better inferences about the underlying cognitive processes. The task consists of displaying two identical models of the same 3D object (a molecule), presented on a computer screen: a rotating, interactive object (iObj) and a static, target object (tObj). Participants must rotate iObj using the mouse until they consider its orientation to be identical to that of tObj. The computer tracks all interaction data in real time. The participant's gaze data are also recorded using an eye tracker. The measurement frequency is 10 Hz on the computer and 60 Hz on the eye tracker. The orientation data of iObj with respect to tObj are recorded in rotation quaternions. The gaze data are synchronized to the orientation of iObj and referenced using this same system. This method enables us to obtain the following visualizations of the human interaction process with iObj and tObj: (1) angular disparity synchronized with other time-dependent data; (2) 3D rotation trajectory inside what we decided to call a "ball of rotations"; (3) 3D fixation heatmap. All steps of the protocol have used free software, such as GNU Octave and Jmol, and all scripts are available as supplementary material. With this approach, we can conduct detailed quantitative studies of the task-solving process involving mental or physical rotations, rather than only the outcome reached. It is possible to measure precisely how important each part of the 3D models is for the participant in solving tasks, and thus relate the models to relevant variables such as the characteristics of the objects, cognitive abilities of the individuals, and the characteristics of human-machine interface.

Intracranial vascular-related diseases are a common occurrence in neurosurgery. They have complex and diverse pathogeneses; further, their diagnosis and treatment remain unclear. Three-dimensional image post-processing technology is an emerging technology that involves converting a brain image scan into a digital model using image post-processing software, thus establishing a 3D view of the region of interest. Three-dimensional visualisation of the brains of patients with cerebrovascular diseases can allow a more intuitive examination of the local anatomy of the lesion as well as the adjacency between the lesion and peripheral nerves, brain tissue, and skull bones. Subsequently, this informs pre-operative planning, allows more accurate diagnosis of cerebrovascular diseases, and improves the safety of surgical treatment. This review summarised the current literature regarding cerebrovascular diseases and the application of 3D image post-processing technology in different cerebrovascular diseases., (© 2024 The Author(s). Published by IMR Press.)

Purpose: The objective of this study was to evaluate the feasibility of using Artificial Intelligence (AI) to measure the long-diameter of tumors for evaluating treatment response., Methods: Our study included 48 patients with lung-specific target lesions and conducted 277 measurements. The radiologists recorded the long-diameter in axial imaging plane of the target lesions for each measurement. Meanwhile, AI software was utilized to measure the long-diameter in both the axial imaging plane and in three dimensions (3D). Statistical analyses including the Bland-Altman plot, Spearman correlation analysis, and paired t-test to ascertain the accuracy and reliability of our findings., Results: The Bland-Altman plot showed that the AI measurements had a bias of -0.28 mm and had limits of agreement ranging from - 13.78 to 13.22 mm (P = 0.497), indicating agreement with the manual measurements. However, there was no agreement between the 3D measurements and the manual measurements, with P < 0.001. The paired t-test revealed no statistically significant difference between the manual measurements and AI measurements (P = 0.497), whereas a statistically significant difference was observed between the manual measurements and 3D measurements (P < 0.001)., Conclusions: The application of AI in measuring the long-diameter of tumors had significantly improved efficiency and reduced the incidence of subjective measurement errors. This advancement facilitated more convenient and accurate tumor response evaluation., (© 2024. The Author(s).)

Background: This study used micro-focus X-ray Computed Tomography (micro-XCT) to examine the anatomical differences and dimensions of the maxillary incisive canal (MIC) in a South African population. The accurate imaging yielded dependable results that support earlier research and enhance anterior maxilla surgery planning. Furthermore, these anatomical features are compared between various racial and gender groupings in the study., Methods: Using a micro-XCT scanner, 108 human cadaver skulls from the Pretoria Bone Collection were scanned and included in the study. Advanced volume rendering software was employed for measuring the MIC length, diameter, shape, and the buccal bone wall measurements in relation to the MIC., Results: Significant anatomical variation in the size and shape of the MIC was identified in the population, with variations seen between racial and gender groups. The incisive foramen (ICO) mean diameter was 6.61 mm, and the MIC length varied from 4.96 to 20.10 mm. There were significant differences in the buccal alveolar bone height between different ethnic groups and gender. Regarding morphological patterns in coronal and sagittal views, single canals were more common in the black population while Y-shaped canals were more common in the white population. The study also introduced a new metric by measuring the mean distances between teeth #11 and #21 and the ICO (1.83 mm and 1.88 mm respectively)., Conclusions: The complex anatomical differences of the MIC in a South African population were clarified. Clinicians should be aware of tooth sockets in near proximity to the MIC and perform accurate preoperative assessment using sophisticated 3-D imaging and preferable guided implant placement in the anterior maxilla., (© 2024. The Author(s).)

The mesoscope has emerged as a powerful imaging tool in biomedical research, yet its high cost and low resolution have limited its broader application. Here, we introduce the Omni-Mesoscope, a high-spatial-temporal and multimodal mesoscopic imaging platform built from cost-efficient off-the-shelf components. This system uniquely merges the capabilities of label-free quantitative phase microscopy to capture live-cell morphodynamics across thousands of cells with highly multiplexed fluorescence imaging for comprehensive molecular characterization. This Omni-Mesoscope offers a mesoscale field of view of ~5 square millimeters with a high spatial resolution down to 700 nanometers, enabling the capture of detailed subcellular features. We demonstrate its capability in delineating molecular characteristics underlying rare morphodynamic cellular phenomena, including cancer cell responses to chemotherapy and the emergence of polyploidy in drug-resistant cells. We also integrate expansion technique to enhance three-dimensional volumetric super-resolution imaging of thicker tissues, opening the avenues for biological exploration at unprecedented scales and resolutions.

Visualizing research data can be an important science communication tool. In recent decades, 3D data visualization has emerged as a key tool for engaging public audiences. Such visualizations are often embedded in scientific documentaries screened on giant domes in planetariums or delivered through video streaming services such as Amazon Prime. 3D data visualization has been shown to be an effective way to communicate complex scientific concepts to the public. With its ability to convey information in a scientifically accurate and visually engaging way, cinematic-style 3D data visualization has the potential to benefit millions of viewers by making scientific information more understandable and interesting. Maximizing the effectiveness of 3D data visualization can benefit millions of viewers. To support a wider shift in this professional field towards more evidence-based practice in 3D data visualization to enhance science communication impact, we have conducted a survey experiment comparing audience responses to two versions of 3D data visualizations from a scientific documentary film on the theme of 'solar superstorms' (n = 577). This study was conducted using a single (with two levels: labeled and unlabeled), between-subjects, factorial design. It reveals key strengths and weaknesses of communicating science using 3D data visualization. It also shows the limited power of strategically deployed informational labels to affect audience perceptions of the documentary film and its content. The major difference identified between experimental and control groups was that the quality ratings of the documentary film clip were significantly higher for the 'labeled' version. Other outcomes showed no statistically significant differences. The limited effects of informational labels point to the idea that other aspects, such as the story structure, voiceover narration and audio-visual content, are more important determinants of outcomes. This study concludes with a discussion of how this new research evidence informs our understanding of 'what works and why' with cinematic-style 3D data visualizations for the public., Competing Interests: I have read the journal’s policy and the authors of this manuscript have the following competing interests. This does not alter our adherence to PLOS ONE policies on sharing data and materials., (Copyright: © 2024 Jensen et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Background: To compare the performance between one-slice two-dimensional (2D) and whole-volume three-dimensional (3D) computed tomography (CT)-based radiomics models in the prediction of lymphovascular invasion (LVI) status in esophageal squamous cell carcinoma (ESCC)., Methods: Two hundred twenty-four patients with ESCC (158 LVI-absent and 66 LVI-present) were enrolled in this retrospective study. The enrolled patients were randomly split into the training and testing sets with a 7:3 ratio. The 2D and 3D radiomics features were derived from the primary tumors' 2D and 3D regions of interest (ROIs) using 1.0 mm thickness contrast-enhanced CT (CECT) images. The 2D and 3D radiomics features were screened using inter-/intra-class correlation coefficient (ICC) analysis, Wilcoxon rank-sum test, Spearman correlation test, and the least absolute shrinkage and selection operator, and the radiomics models were built by multivariate logistic stepwise regression. The performance of 2D and 3D radiomics models was assessed by the area under the receiver operating characteristic (ROC) curve. The actual clinical utility of the 2D and 3D radiomics models was evaluated by decision curve analysis (DCA)., Results: There were 753 radiomics features from 2D ROIs and 1130 radiomics features from 3D ROIs, and finally, 7 features were retained to construct 2D and 3D radiomics models, respectively. ROC analysis revealed that in both the training and testing sets, the 3D radiomics model exhibited higher AUC values than the 2D radiomics model (0.930 versus 0.852 and 0.897 versus 0.851, respectively). The 3D radiomics model showed higher accuracy than the 2D radiomics model in the training and testing sets (0.899 versus 0.728 and 0.788 versus 0.758, respectively). In addition, the 3D radiomics model has higher specificity and positive predictive value, while the 2D radiomics model has higher sensitivity and negative predictive value. The DCA indicated that the 3D radiomics model provided higher actual clinical utility regarding overall net benefit than the 2D radiomics model., Conclusions: Both 2D and 3D radiomics features can be employed as potential biomarkers to predict the LVI in ESCC. The performance of the 3D radiomics model is better than that of the 2D radiomics model for the prediction of the LVI in ESCC., (© 2024. The Author(s).)

A comprehensive understanding of physio-pathological processes necessitates non-invasive intravital three-dimensional (3D) imaging over varying spatial and temporal scales. However, huge data throughput, optical heterogeneity, surface irregularity, and phototoxicity pose great challenges, leading to an inevitable trade-off between volume size, resolution, speed, sample health, and system complexity. Here, we introduce a compact real-time, ultra-large-scale, high-resolution 3D mesoscope (RUSH3D), achieving uniform resolutions of 2.6 × 2.6 × 6 μm 3 across a volume of 8,000 × 6,000 × 400 μm 3 at 20 Hz with low phototoxicity. Through the integration of multiple computational imaging techniques, RUSH3D facilitates a 13-fold improvement in data throughput and an orders-of-magnitude reduction in system size and cost. With these advantages, we observed premovement neural activity and cross-day visual representational drift across the mouse cortex, the formation and progression of multiple germinal centers in mouse inguinal lymph nodes, and heterogeneous immune responses following traumatic brain injury-all at single-cell resolution, opening up a horizon for intravital mesoscale study of large-scale intercellular interactions at the organ level., Competing Interests: Declaration of interests The authors declare the following competing interests: Q.D. and J.W. are founders and equity holders of Zhejiang Hehu Technology LLC. Q.D., J.W., M.W., and Yuanlong Zhang submitted patent applications related to the RUSH3D technology described in this work., (Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.)

Serum amyloid A (SAA) is one of the most important precursor amyloid proteins discovered during the study of amyloidosis, but its underlying aggregation mechanism has not yet been well elucidated. Since SAA aggregation is a key step in the pathogenesis of AA amyloidosis, amyloid inhibitors can be used as a tool to study its pathogenesis. Previously, we reported a novel microliter-scale high-throughput screening (MSHTS) system for screening amyloid β (Aβ) aggregation inhibitors based on quantum dot (QD) fluorescence imaging technology. In this study, we report the aggregation of human SAA (hSAA) in phosphate-buffered saline, in which we successfully visualized hSAA aggregation by QD using fluorescence microscopy and confocal microscopy. Two-dimensional and three-dimensional image analyses showed that most aggregations were observed at 40 μM hSAA, which was the optimal aggregation concentration in vitro. The accuracy of this finding was verified by a Thioflavin T assay. The transmission electron microscopy results showed that QD uniformly bound to hSAA aggregation. hSAA aggregation inhibitory activity was also evaluated by rosmarinic acid (RA). The results showed that RA, which is a compound with high inhibitory activity against Aβ aggregation, also exhibited high inhibitory activity against 40 μM hSAA. These results indicate that the MSHTS system is an effective tool for visualizing hSAA aggregation and for screening highly active inhibitors.

Purpose: To assess the accuracy and precision of prosthetically driven implant placement achieved through static computer-aided implant surgery by analyzing the linear and angular deviations of implants., Materials and Methods: A total of 53 implants were included in the study. The implants were positioned using either tooth-supported templates or tooth-and-tissue-supported templates with fixation pins. Two distinct guided surgery approaches were used: pilot drill guided and fully guided. 3D data from the implant planning phase was superimposed with the 3D data from the final implant positions using the 'Treatment Evaluation' tool within coDiagnostiX implant planning software (Straumann). This enabled the automatic calculation of deviations in implant placement accuracy., Results: The average angular deviation observed was 3.90 degrees. For linear deviations, the mean 3D deviation was 1.04 mm at the most coronal point of the implants and 1.56 mm at the implant apex., Conclusions: This research demonstrates the feasibility of a digital workflow for guided implant surgery, offering a promising treatment option. Nonetheless, it is important to note that deviations do occur, particularly in the apical region of the implant. Care should be taken, particularly in cases of limited bone availability.

The following technique describes the virtual planning of a single implant by combining an intraoral digital scan, an open-source computer-aided design software program, bone sounding, and 2D radiographic imaging. The surgical implant guide is fabricated using additive manufacturing technologies. Further, the surgical implant guide positioned in the patient's mouth is used to radiographically verify the estimated mesiodistal implant angulation before proceeding with the surgical intervention and can be modified if necessary. When a CBCT scan is not available, this technique eases implant planning procedures and minimizes possible surgical complications.

Purpose: This study assessed the accuracy of linear measurements and dental implant selection performed in a smartphone application compared to a computer software., Materials and Methods: Forty-four DICOM files from the posterior mandible in partially edentulous patients were evaluated by three trained and calibrated examiners. Images were analyzed using three visualization methods: cross-sectional view (CScr) and coronal (CSco) plane using the CS 3D Imaging software, and coronal (DRco) plane using the DroidRender smartphone application. For standardization, bone width and height measurements were taken in the edentulous posterior mandible, 10 mm posterior to the mental foramen. Implants were selected according to the 2022/2023Straumann Standard implant catalog. Linear measurements were compared using repeated-measures ANOVA, and implant selection was compared using Friedman test. Statistical analysis was performed using SPSS software, with a significance level of 5%., Results: Linear measurements showed a statistically significant difference for bone width (P &#61; .030), but not for height (P &#61; .685). The choice of implant was not influenced by the visualization method (P &#61; .614)., Conclusions: It is possible to suggest the use of smartphone applications as an additional diagnostic tool for DICOM evaluation and implant planning in the posterior mandible. Smartphone applications allow an assessment not limited to 2D images or to static environments. Therefore, information exchange and diagnostic opinion in emergency situations may be facilitated.

As an alternative to true isotropic 3D imaging, image super-resolution (SR) has been applied to reconstruct an isotropic 3D volume from multiple anisotropic scans. However, traditional SR methods struggle with inadequate performance, prolonged processing times, and the necessity for manual feature extraction. Motivated by the exceptional representational ability and automatic feature extraction of convolutional neural networks (CNNs), in this work, we present an end-to-end isotropic MRI reconstruction strategy based on deep learning. The proposed method is based on 3D convolutional neural networks (3D CNNs), which can effectively capture the 3D structural features of MRI volumes and accurately predict potential structure. In addition, the proposed method takes multiple orthogonal scans as input and thus enables the model to use more complementary information from different dimensions for precise inference. Experimental results show that the proposed algorithm achieves promising performance in terms of both quantitative and qualitative assessments. In addition, it can process a 3D volume with a size of 256 × 256 × 256 in less than 1 min with the support of an NVIDIA GeForce GTX 1080Ti GPU, which suggests that it is not only a quantitatively superior method but also a practical one.

Eukaryotic cells are compartmentalized into membrane-bound organelles that must coordinate their responses to stimuli. One way that organelles communicate is via membrane contact sites (MCSs), sites of close apposition between organelles used for the exchange of ions, lipids and information. In this Cell Science at a Glance article and the accompanying poster, we describe an explosion of new methods that have led to exciting progress in this area and discuss key examples of how these methods have advanced our understanding of MCSs. We discuss how diffraction-limited and super-resolution fluorescence imaging approaches have provided important insight into the biology of interorganelle communication. We also describe how the development of multiple proximity-based methods has enabled the detection of MCSs with high accuracy and precision. Finally, we assess how recent advances in electron microscopy (EM), considered the gold standard for detecting MCSs, have allowed the visualization of MCSs and associated proteins in 3D at ever greater resolution., Competing Interests: Competing interests The authors declare no competing or financial interests., (© 2024. Published by The Company of Biologists Ltd.)

Synchrotron-based tomographic phase-contrast X-ray imaging (SRµCT or SRnCT) is a versatile isotropic three-dimensional imaging technique that can be used to study biological samples spanning from single cells to human-sized specimens. SRµCT and SRnCT take advantage of the highly brilliant and coherent X-rays produced by a synchrotron light source. This enables fast data acquisition and enhanced image contrast for soft biological samples owing to the exploitation of phase contrast. In this Review, we provide an overview of the basics behind the technique, discuss its applications for biologists and provide an outlook on the future of this emerging technique for biology. We introduce the latest advances in the field, such as whole human organs imaged with micron resolution, using X-rays as a tool for virtual histology and resolving neuronal connections in the brain., Competing Interests: Competing interests The authors declare no competing or financial interests., (© 2024. Published by The Company of Biologists Ltd.)

Objective: Subtraction angiographies are calculated using a native and a contrast-enhanced 3D angiography images. This minimizes both bone and metal artifacts and results in a pure image of the vessels. However, carrying out the examination twice means double the radiation dose for the patient. With the help of generative AI, it could be possible to simulate subtraction angiographies from contrast-enhanced 3D angiographies and thus reduce the need for another dose of radiation without a cutback in quality. We implemented this concept by using conditional generative adversarial networks., Methods: We selected all 3D subtraction angiographies from our PACS system, which had performed between 01/01/2018 and 12/31/2022 and randomly divided them into training, validation, and test sets (66%:17%:17%). We adapted the pix2pix framework to work on 3D data and trained a conditional generative adversarial network with 621 data sets. Additionally, we used 158 data sets for validation and 164 for testing. We evaluated two test sets with (n = 72) and without artifacts (n = 92). Five (blinded) neuroradiologists compared these datasets with the original subtraction dataset. They assessed similarity, subjective image quality, and severity of artifacts., Results: Image quality and subjective diagnostic accuracy of the virtual subtraction angiographies revealed no significant differences compared to the original 3D angiographies. While bone and movement artifact level were reduced, artifact level caused by metal implants differed from case to case between both angiographies without one group being significant superior to the other., Conclusion: Conditional generative adversarial networks can be used to simulate subtraction angiographies in clinical practice, however, new artifacts can also appear as a result of this technology., (© 2024. The Author(s).)

Expansion Microscopy (ExM) is an innovative and cost-effective super-resolution microscopy technique that has become popular in cell biology research. It achieves super-resolution by physically expanding specimens. Since its introduction, ExM has undergone continuous methodological developments to enhance its resolution and labeling capabilities. However, ExM imaging often encounters sample drift during image acquisition due to the physical movement of the expanded hydrogel, posing a significant challenge for accurate image reconstruction. Despite many proposed experimental solutions to mitigate sample drift, a universal solution has yet to be established. In response to this challenge, we developed 3D-Aligner, an advanced and user-friendly image analysis tool designed to computationally correct drift in ExM images for precise three-dimensional image reconstruction and downstream quantification. We demonstrate that 3D-Aligner effectively determines and corrects drift in ExM images with different expansion rates and various fluorescently labeled biological targets, showcasing its capabilities and robustness in drift correction. Additionally, we validate the precision of 3D-Aligner by comparing drift values across different labeled targets and highlight the importance of drift correction in quantification of biological structures., (© 2024. The Author(s).)

Background: White matter (WM) fiber tracts in the brainstem communicate with various regions in the cerebrum, cerebellum, and spinal cord. Clinically, small lesions, malformations, or histopathological changes in the brainstem can cause severe neurological disorders. A direct and non-invasive assessment approach could bring valuable information about the intricate anatomical variations of the white matter fiber tracts and nuclei. Although tractography from diffusion tensor imaging has been commonly used to map the WM fiber tracts connectivity, it is difficult to differentiate the complex WM tracts anatomically. Both high field MRI methods and ultrahigh-field MRI methods at 7T and 11.7 T have been used to enhance the contrast of WM fiber tracts. Despite their promising results, it is still challenging to achieve wide clinical adoption at 3T. In this study, we explored a clinically feasible method using a proton density weighted (PDW) 3D gradient echo (GRE) sequence to directly image the WM fiber tracts in the brainstem at 3T in vivo., Methods: We optimized a 3D high resolution, double echo, short TR, PDW GRE sequence on 5 healthy volunteers using a clinical 3T scanner to visualize the complicated anatomy of WM fiber tracts in the brain stem. Tissue properties including T1, proton density and T2* from in vivo quantitative MRI data were used for simulations to determine the optimal flip angle for the sequence. The visualization of multiple WM fiber tracts in the brainstem was assessed qualitatively and quantitatively using relative contrast and contrast-to-noise ratio (CNR). To improve the CNR, the final images were created by averaging over all echoes from two consecutive scans at the optimal flip angle. The results were compared to anatomical atlases and histology sections to identify the major fiber tracts. All the identified major fiber tracts were labeled on axial, sagittal and coronal slices., Results: The WM fiber tracts were found to have distinct hypointense signal throughout the brainstem and most of the major WM fiber tracts, such as the corticospinal tract, medial lemniscus, medial longitudinal fasciculus, and central tegmental tract, in the brainstem up to and including the thalamus were identified in all subjects. Both qualitative and quantitative evaluations showed that the 3° scan offered the best contrast for WM fiber tracts for a TR of 20 ms. The average over the first two echo times and two consecutive 3° scans gave a CNR of 47.8 ± 6.2 for the pyramidal tracts in particular and CNRs values greater than 6.5 ± 2.4 for the rest of the fiber tracts., Conclusions: All the major fiber tracts in the brainstem could be visualized. Given the reasonably short scan time of 10 min at 3T, double echo PDW GRE sequence is a very practical approach for clinical adoption., Competing Interests: Declaration of competing interest All authors declare that they have no conflicts of interest., (Copyright © 2024. Published by Elsevier Inc.)

Cellular heterogeneity is a well-accepted feature of tissues, and both transcriptional and metabolic diversity have been revealed by numerous approaches, including optical imaging. However, the high magnification objective lenses needed for high-resolution imaging provides information from only small layers of tissue, which can result in poor cell statistics. There is therefore an unmet need for an imaging modality that can provide detailed molecular and cellular insight within intact tissue samples in 3D. Using GFP-tagged GLUT4 as proof of concept, we present here a novel optical mesoscopy approach that allows precise measurement of the spatial location of GLUT4 within specific anatomical structures across the myocardium in ultrathick sections (5 mm×5 mm×3 mm) of intact mouse heart. We reveal distinct GLUT4 distribution patterns across cardiac walls and highlight specific changes in GLUT4 expression levels in response to high fat diet-feeding, and we identify sex-dependent differences in expression patterns. This method is applicable to any target that can be labelled for light microscopy, and to other complex tissues when organ structure needs to be considered simultaneously with cellular detail., Competing Interests: Competing interests The authors declare no competing or financial interests., (© 2024. Published by The Company of Biologists Ltd.)

Background: Aortic-valve-stenosis (AS) is a frequent degenerative valvular-disease and carries dismal outcome under-medical-treatment. Transvalvular pressure gradient reflects severity of the valve-disease but is highly dependent on flow-conditions and on other valvular/aortic characteristics. Alternatively, aortic-valve-area (AVA) represents a measure of aortic-valve lesion severity conceptually essential and practically widely-recognized but exhibits multiple-limitations., Methods: We analyzed the 4D multi-detector computed tomography(MDCT) of 20 randomly selected patients with severe AS. For each-patient, we generated the 3D-model of the valve and of its calcifications, and we computed the anatomical AVA accounting for the 3D-morphology of the leaflets in three-different-ways. Finally, we compared our results vs. Doppler-based AVA E measurements and vs. 2D-planimetric AVA-measurements., Results: 3D-reconstruction and identification of the cusps were successful in 90% of the cases. The calcification patterns where highly-variable over patients, ranging from multiple small deposits to wide and c-shaped deposits running from commissure-to-commissure. AVA E was 82 ± 15 mm 2 . When segmenting 18 image planes, AVA Tight , AVA Proj-Ann , AVA Proj-Tip and their average AVA Ave were equal to 80 ± 16, 88 ± 20, 93 ± 21 and 87 ± 19 mm 2 , respectively, while AVA Plan was equal to 143 ± 50 mm 2 . Linear-regression of the three measurements vs. AVA E yielded regression slopes equal to 1.26, 1.13 and 0.93 for AVA Proj-Ann , AVA Proj-Tip and AVA Tight , respectively. The respective Pearson-coefficients were 0.85,0.86 and 0.90. Conversely, when comparing AVA Plan vs. AVA E , linear regression yielded a slope of 1.73 and a Pearson coefficient of 0.53., Conclusions: We described a new-method to obtain a set of flow-independent quantifications that complement pressure gradient measurements and combine the advantages of previously proposed methods, while bypassing the corresponding-limitations., Competing Interests: Declaration of competing interest None., (Copyright © 2024. Published by Elsevier B.V.)

Tissue morphogenesis remains poorly understood. In plants, a central problem is how the 3D cellular architecture of a developing organ contributes to its final shape. We address this question through a comparative analysis of ovule morphogenesis, taking advantage of the diversity in ovule shape across angiosperms. Here, we provide a 3D digital atlas of Cardamine hirsuta ovule development at single cell resolution and compare it with an equivalent atlas of Arabidopsis thaliana. We introduce nerve-based topological analysis as a tool for unbiased detection of differences in cellular architectures and corroborate identified topological differences between two homologous tissues by comparative morphometrics and visual inspection. We find that differences in topology, cell volume variation and tissue growth patterns in the sheet-like integuments and the bulbous chalaza are associated with differences in ovule curvature. In contrast, the radialized conical ovule primordia and nucelli exhibit similar shapes, despite differences in internal cellular topology and tissue growth patterns. Our results support the notion that the structural organization of a tissue is associated with its susceptibility to shape changes during evolutionary shifts in 3D cellular architecture., Competing Interests: Competing interests The authors declare no competing or financial interests., (© 2024. Published by The Company of Biologists Ltd.)

This study aimed to validate the automated temporal analysis of countermovement vertical jump (CMJ) using MMPose, a markerless pose estimation framework, by comparing it with the gold-standard 3D marker-based motion capture system. Twelve participants performed five CMJ trials, which were simultaneously recorded using the marker-based system and two smartphone cameras capturing both sides of the body. Key kinematic points, including center of mass (CoM) and toe trajectories, were analyzed to determine jump phases and temporal variables. The agreement between methods was assessed using Bland-Altman analysis, root mean square error (RMSE), and Pearson's correlation coefficient (r), while consistency was evaluated via intraclass correlation coefficient (ICC 3,1) and two-way repeated-measures ANOVA. Cohen's effect size (d) quantified the practical significance of differences. Results showed strong agreement (r > 0.98) with minimal bias and narrow limits of agreement for most variables. The markerless system slightly overestimated jump height and CoM vertical velocity, but ICC values (ICC > 0.91) confirmed strong reliability. Cohen's d values were near zero, indicating trivial differences, and no variability due to recording side was observed. Overall, MMPose proved to be a reliable alternative for in-field CMJ analysis, supporting its broader application in sports and rehabilitation settings.

Background: The study aimed to observe the internal structure of coconuts from two locations (coastal and non-coastal) using computed tomography (CT)., Methods: Seventy-six mature coconuts were collected from Wenchang and Ding'an cities in Hainan Province. These coconuts were scanned four times using CT, with a two-week interval between each scan. CT data were post-processed to reconstruct two-dimensional slices and three-dimensional models. The density and morphological parameters of coconut structures were measured, and the differences in these characteristics between the two groups and the changes over time were analyzed., Results: Time and location had interactive effects on CT values of embryos, solid endosperms and mesocarps, morphological information such as major axis of coconut, thickness of mesocarp, volume of coconut water and height of bud ( p  < 0.05)., Conclusions: Planting location and observation time can affect the density and morphology of some coconut structures., Competing Interests: Li’an Luo is an employee of Siemens Healthineers, but she was not involved in the analysis of the data and had no control of data or information submitted for publication. There is no conflict of interest or industry support in this study. The other authors declare that they have no competing interests., (©2024 Lin et al.)

Background: To investigate the value and clinical effect of computed tomography (CT) 3-dimensional reconstruction technology in lung bullae resection., Methods: Ninety-eight patients who underwent thoracoscopic surgical resection of lung bullae in our hospital from February 2019 to February 2023 were selected and divided into 2 groups according to the principle of voluntary participation in the clinical trial, of which 43 cases underwent preoperative spiral CT for thin-layer enhancement or planar CT scanning of lung bullae (control group), and 43 cases were imaged with MimicsMedical 21 software for 3-dimensional reconstruction to develop a surgical plan (observation group). To compare the surgery-related indexes, postoperative complications, pain, and analgesic use between the 2 groups, we measured serum creatine phosphokinase and myoglobin levels., Results: The amount of surgical bleeding, drainage volume, hospital stay, and postoperative visual analog scale score of the research group were lower than those of the control group (P < .05), and the duration of analgesic medication was shorter than that of the control group (P < .05), and the levels of serum creatine phosphokinase and myoglobin were lower than those of the control group at 1 and 3 days postoperatively, and the differences were statistically significant (P < .05)., Conclusion: Preoperative CT 3-dimensional reconstruction technique can clearly show the anatomical structures around the lung bullae and has its application value for precise lung bullae., Competing Interests: The authors have no funding and conflicts of interest to disclose., (Copyright © 2024 the Author(s). Published by Wolters Kluwer Health, Inc.)

The integration of artificial intelligence (AI) into lung cancer management offers immense potential to revolutionize diagnostic and treatment strategies. The aim is to develop a resilient AI framework capable of two critical tasks: firstly, achieving accurate and automated segmentation of lung tumors and secondly, facilitating the T classification of lung cancer according to the ninth edition of TNM staging 2024 based on PET/CT imaging. This study presents a robust AI framework for the automated segmentation of lung tumors and T classification of lung cancer using PET/CT imaging. The database includes axial DICOM CT and 18 FDG-PET/CT images. A modified ResNet-50 model was employed for segmentation, achieving high precision and specificity. Reconstructed 3D models of segmented slices enhance tumor boundary visualization, which is essential for treatment planning. The Pulmonary Toolkit facilitated lobe segmentation, providing critical diagnostic insights. Additionally, the segmented images were used as input for the T classification using a CNN ResNet-50 model. Our classification model demonstrated excellent performance, particularly for T1a, T2a, T2b, T3 and T4 tumors, with high precision, F1 scores, and specificity. The T stage is particularly relevant in lung cancer as it determines treatment approaches (surgery, chemotherapy and radiation therapy or supportive care) and prognosis assessment. In fact, for Tis-T2, each increase of one centimeter in tumor size results in a worse prognosis. For locally advanced tumors (T3-T4) and regardless of size, the prognosis is poorer. This AI framework marks a significant advancement in the automation of lung cancer diagnosis and staging, promising improved patient outcomes., (© 2024 IOP Publishing Ltd. All rights, including for text and data mining, AI training, and similar technologies, are reserved.)

Background and Objectives: With the goal of identifying regions with bicortical bone and avoiding root contact, the present study proposes an innovative technique for the simulation of the insertion of mini orthodontic implants using automatic jaw segmentation. The simulation of mini implants takes place in 3D rendering visualization instead of Multi-Planar Reconstruction (MPR) sections. Materials and Methods: The procedure involves utilizing software that automatically segments the jaw, teeth, and implants, ensuring their visibility in 3D rendering images. These segmented files are utilized as study models to determine the optimum location for simulating orthodontic implants, in particular locations characterized by limited distances between the implant and the roots, as well as locations where the bicortical structures are present. Results: By using this method, we were able to simulate the insertion of mini implants in the maxilla by applying two cumulative requirements: the implant tip needs to be positioned in a bicortical area, and it needs to be situated more than 0.6 mm away from the neighboring teeth's roots along all of their axes. Additionally, it is possible to replicate the positioning of the mini implant in order to distalize the molars in the mandible while avoiding the mandibular canal and the path of molar migration. Conclusions: The utilization of automated segmentation and visualization techniques in 3D rendering enhances safety measures during the simulation and insertion of orthodontic mini implants, increasing the insertion precision and providing an advantage in the identification of bicortical structures, increasing their stability.

High-resolution CT images are essential in clinical practice to accurately replicate patient anatomy for 3D virtual surgical planning and designing patient-specific surgical guides. These technologies are commonly used in corrective osteotomy of the distal radius. This study evaluated how the virtual radius models and the surgical guides' surface that is in contact with the bone vary between experienced raters. Further, the discrepancies from the reference radius of surgical guides and radius models created from CT images with slice thicknesses larger than the reference standard of 0.625mm were assessed. Maximum overlap with radius model was measured for guides, and absolute average distance error was measured for radius models. The agreement between the lower-resolution guides surface and the raters' guide surface was evaluated. The average inter-rater guide surface overlap was -0.11mm [95% CI: -0.13-0.09]. The surface of surgical guides designed on CT images with a 1mm slice thickness deviated from the reference radius within the inter-rater range (0.03mm). For slice thicknesses of 1.25mm and 1.5mm, the average guide surface overlap was 0.12mm and 0.15mm, respectively. The average inter-rater radius surface variability was 0.03mm [95% CI: 0.025-0.035]. The discrepancy from the reference of all radius models created from CT images with a slice thickness larger than the reference slice thickness was notably larger than the inter-rater variability but, excluding one case, did not exceed 0.2mm. The results suggest that 1mm CT images are suitable for surgical guide design. While 1.25mm slices are commonly used for virtual planning in hand and forearm surgery, slices larger than 1mm may approach the limit of clinical acceptability. Discrepancies in radius models were below 1mm, likely below clinical relevance., Competing Interests: The authors declare that they have no competing interests., (Copyright: © 2024 Gryska et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Background: Mandibular second molar (M2M) impaction is a clinically significant manifestation of eruption disturbance in dental development. The primary aim of this study was to investigate the impact of the three-dimensional (3D) characterization on clinical and therapeutic decisions for M2M impaction. The secondary aim was to introduce a validated 3D classification system incorporating both surgical and orthodontic parameters., Methods: Bidimensional (2D) and 3D radiological records of 15 impacted M2M were collected and deidentified. Ten experienced clinicians (5 oral surgeons;5 orthodontists) categorized each case, first based on 2D records and then with 3D scans. The degree of orthodontic and surgical difficulty in treating impacted M2M was evaluated using a novel classification system based on anatomical and radiological features. The primary outcome variable was the assessment of differences in diagnosis and decision-making protocol using 2D or 3D records, where clinical relevance ranged from 0 to 4. The secondary outcome variable was the validation analysis of the proposed 3D classification system to determine the concordance among the clinicians. Descriptive statistics and multivariable inferential analysis based on Akaike information criterion (AIC) were performed (α = 0.05)., Results: 3D examination allowed a better visualization of M2M impaction with higher clinical relevance for diagnosis of M2M root relationship to alveolar nerve and lingual plate, height to alveolar crest, depth, and inclination relative to the first molar and position relative to the third molar (range:2.69-3.43). The proposed 3D classification of M2M impaction changed clinical decisions regarding surgical-orthodontic approach, biomechanics, patient education, and treatment time estimate (range:2.59-3.33). In the validation analysis of the classification, no evidence of inter- or intra-group (surgeon/orthodontist) bias in score attribution occurred: the model with the minimum AIC was the null model (AIC = 718.04)., Conclusion: 3D evaluation of impacted M2Ms could enhance diagnostic accuracy, and a classification system was proposed and validated by a group of experienced surgeons and orthodontists with high concordance., (© 2024. The Author(s).)

The study of biological soft tissue structures at the micron scale details the function of healthy and pathological tissues, which is vital in the diagnosis and treatment of diseases. Speckle based X-ray phase contrast tomographic scans at a nanometer scale have the potential to thoroughly analyse such tissues in a quantitative and qualitative manner. Diamond light source, the UKs national synchrotron facility developed and refined a 1-D X-ray speckle-based imaging technique, referred to as Fly scan mode. This novel image acquisition technique was used to perform a rapid structural composition scan of rodent lung histology samples. The rodent samples were taken from healthy and Staphylococcus aureus induced acute respiratory distress syndrome models. The analysis and cross comparison of the fly scan method, absorption-based tomography and conventional histopathology H&E staining microscopy are discussed in this paper. This analysis and cross comparison outline the ways the speckle-based technique can be of benefit. These advantages include improved soft tissue contrast, 3-D volumetric rendering, segmentation of specific gross tissue structures, quantitative analysis of gross tissue volume. A further advantage is the analysis of cellular distribution throughout the volumetric rendering of the tissue sample. The study also details the current limitations of this technique and points to ways in which future work on this imaging modality may progress., (© 2024. The Author(s).)

Background: The impact of extra-articular deformities (EADs) on lower limb alignment and collateral ligament integrity during total knee arthroplasty (TKA) poses significant challenges, increasing surgical complexity. Our study aims to evaluate the influence of EADs on mechanical axis alignment and the risk of collateral ligament injury during TKA using an AI-assisted surgical planning system, with the goal of minimizing ligament damage through precise and scientific planning., Methods: A healthy volunteer underwent CT and MRI scans of the lower limbs. The scan images were imported into Mimics 20.0 software, and the reconstructed models were spatially aligned using 3-maticResearch 11.0 software. Using Unigraphics NX9.0 software, 50 three-dimensional models of femoral lateral joint deformities with varying positions and angles were created. Finally, TKA was simulated using the AI JOINT preoperative planning system., Results: The larger the deformity angle and the closer it is to the knee joint, the more pronounced the deviation of the mechanical axis. During MA-aligned osteotomy, nine types of deformities can damage the collateral ligaments. After adjusting the varus/valgus of the prosthesis within a safe range of 3° and leaving a residual 3° varus/valgus in the lower limb alignment, only the 25° varus and 25° valgus deformities located at 90% of the femoral anatomical axis remain uncorrected., Conclusion: For patients with osteoarthritis and concurrent EAD undergoing TKA, using reconstructed 3D models of the collateral ligaments for preoperative planning helps visually assess collateral ligament damage, providing a practical solution. Minimizing intra-articular osteotomies within a safe range and allowing some residual alignment deviation can reduce the risk of collateral ligament injury., (© 2024. The Author(s).)

Artificial intelligence (AI) has emerged as a transformative technology in the field of healthcare, offering significant advancements in various medical disciplines, including obstetrics. The integration of artificial intelligence into 3D/4D ultrasound analysis of fetal facial profiles presents numerous benefits. By leveraging machine learning and deep learning algorithms, AI can assist in the accurate and efficient interpretation of complex 3D/4D ultrasound data, enabling healthcare providers to make more informed decisions and deliver better prenatal care. One such innovation that has significantly improved the analysis of fetal facial profiles is the integration of AI in 3D/4D ultrasound imaging. In conclusion, the integration of artificial intelligence in the analysis of 3D/4D ultrasound data for fetal facial profiles offers numerous benefits, including improved accuracy, consistency, and efficiency in prenatal diagnosis and care., (© 2024 Walter de Gruyter GmbH, Berlin/Boston.)

Collective cancer invasion exhibits a hierarchical structure characterized by leader-follower organization. Dynamic gene expression analysis of invading cells using nanobiosensors within 3D microenvironments provides a valuable means to explore the regulation of leader cells during collective cancer invasion. Nonetheless, the analysis of time-lapse, multimodal images that capture the intricacies of complex invading structures and gene expression profiles in 3D tumor spheroids poses a significant technological challenge. Here, we present a computer vision-based workflow that streamlines the identification of protrusions and detached clusters from 3D tumor spheroids. This methodology not only discerns invading multicellular structures and quantifies their physical properties, but also captures gene expression patterns associated with these invasive mechanisms using an intracellular nanobiosensor. Consequently, it empowers a systematic exploration of the genotypic and phenotypic heterogeneities inherent in cancer invasion. To illustrate the effectiveness of this approach, we applied it to the analysis of a long noncoding RNA, MALAT1, in tumor spheroids derived from patients with muscle-invasive bladder cancer. Our investigation delved into the heterogeneity of cancer invasion and its relationship to MALAT1 expression. Overall, this workflow represents a valuable tool for gaining insights into the complexities of cancer invasion., (© 2024. The Author(s).)

Parkinson's disease (PD) is one of the most common neurodegenerative disorders that affect the quality of human life of millions of people throughout the world. The probability of getting affected by this disease increases with age, and it is common among the elderly population. Early detection can help in initiating medications at an earlier stage. It can significantly slow down the progression of this disease, assisting the patient to maintain a good quality of life for a more extended period. Magnetic resonance imaging (MRI)-based brain imaging is an area of active research that is used to diagnose PD disease early and to understand the key biomarkers. The prior research investigations using MRI data mainly focus on volume, structural, and morphological changes in the basal ganglia (BG) region for diagnosing PD. Recently, researchers have emphasized the significance of studying other areas of the human brain for a more comprehensive understanding of PD and also to analyze changes happening in brain tissue. Thus, to perform accurate diagnosis and treatment planning for early identification of PD, this work focuses on learning the onset of PD from images taken from whole-brain MRI using a novel 3D-convolutional neural network (3D-CNN) deep learning architecture. The conventional 3D-Resent deep learning model, after various hyper-parameter tuning and architectural changes, has achieved an accuracy of 90%. In this work, a novel 3D-CNN architecture was developed, and after several ablation studies, the model yielded results with an improved accuracy of 93.4%. Combining features from the 3D-CNN and 3D ResNet models using Canonical Correlation Analysis (CCA) resulted in 95% accuracy. For further enhancements of the model performance, feature fusion with optimization was employed, utilizing various optimization techniques. Whale optimization based on a biologically inspired approach was selected on the basis of a convergence diagram. The performance of this approach is compared to other methods and has given an accuracy of 97%. This work represents a critical advancement in improving PD diagnosis techniques and emphasizing the importance of deep nested 3D learning and bio-inspired feature selection., (© 2024. The Author(s).)

Background: Longitudinal T1 relaxation time is a key imaging biomarker. In addition, T1 values are modulated by the administration of T1 contrast agents used in patients with tumors and metastases. However, in clinical practice, dedicated T1 mapping sequences are often not included in brain MRI protocols. The aim of this study is to address the absence of dedicated T1 mapping sequences in imaging protocol by deriving T1 maps from standard T1-weighted sequences., Methods: A phantom, composed of 144 solutions of paramagnetic agents at different concentrations, was imaged with a three-dimensional (3D) T1-weighed turbo spin-echo (TSE) sequence designed for brain imaging. The relationship between the T1 values and the signal intensities was established using this phantom acquisition. T1 mapping derived from 3D T1-weighted TSE acquisitions in four healthy volunteers and one patient with brain metastases were established and compared to reference T1 mapping technique. The concentration of Gd-based contrast agents in brain metastases were assessed from the derived T1 maps., Results: Based on the phantom acquisition, the relationship between T1 values and signal intensity (SI) was found equal to T1 = 0.35 × SI - 1.11 (R 2  = 0.97). TSE-derived T1 values measured in white matter and gray matter in healthy volunteers were equal to 0.997 ± 0.096 s and 1.358 ± 0.056 s (mean ± standard deviation), respectively. Mean Gd 3+ concentration value in brain metastases was 94.7 ± 30.0 μM., Conclusion: The in vivo results support the relevance of the phantom-based approach: brain T1 maps can be derived from T1-weighted acquisitions., Relevance Statement: High-resolution brain T1 maps can be generated, and contrast agent concentration can be quantified and imaged in brain metastases using routine 3D T1-weighted TSE acquisitions., Key Points: Quantitative T1 mapping adds significant value to MRI diagnostics. T1 measurement sequences are rarely included in routine protocols. T1 mapping and concentration of contrast agents can be derived from routine standard scans. The diagnostic value of MRI can be improved without additional scan time., (© 2024. The Author(s).)

Craniofacial structure and dental hard tissue used to be researched on by traditional imaging tools such as light microscope, electron microscope and micro-CT. Due to the limitations of imaging principle, resolution and 3D rendering reconstruction technique, traditional imaging tools are constrained for presenting fine structure and precise measurements. Here a brand-new imaging equipment-3D X-ray microscope is introduced to realize a more efficient scanning by demonstrating the comparison of the craniofacial structures and dental hard tissue of diabetes and normal DBA mouse. To explore a higher resolution, more efficient imaging measurement and 3D reconstruction method on craniofacial structure and dental hard tissue. The study included 12 DBA mice which were divided into two groups (control group and diabetes group). The heads were separated and scanned by 3D X-ray microscope, after which regions of interest were selected, followed by measurement and 3D reconstruction based on microscope attached software Dragonfly pro©. Hemi-mandibles were collected for enamel mineral density assessment supported by QRM-MicroCT-HA phantom. Data was submitted to paired t-tests at a 95% confidence level. The automatic assessed enamel thickness of diabetes mice decreased on average, whereas the rest of manual measurements and automatic assessed density showed no statistical difference. We constructed HA phantom assisted enamel density procedure in Dragonfly software. Craniofacial structure and dental hard tissue were well-presented both in 2D slide and 3D reconstruction viewport by 3D X-ray microscope which can be routinely used as craniofacial structure and dental hard tissue imaging tool., (© 2024. The Author(s).)

Background: Our study aims to examine stress-strain data of the four major knee ligaments-the anterior cruciate ligament (ACL), the posterior cruciate ligament (PCL), the medial collateral ligament (MCL), and the lateral collateral ligament (LCL)-under transient impacts in various knee joint regions and directions within the static standing position of the human body. Subsequently, we will analyze the varying biomechanical properties of knee ligaments under distinct loading conditions., Methods: A 3D simulation model of the human knee joint including bone, meniscus, articular cartilage, ligaments, and other tissues, was reconstructed from MRI images. A vertical load of 300 N was applied to the femur model's top surface to mimic the static standing position, and a 134 N load was applied to the impacted area of the knee joint. Nine scenarios were created to examine the effects of anterior, posterior, and lateral external forces on the upper, middle, and lower regions of the knee joint., Results: The PCL exhibited the highest stress levels among the four ligaments when anterior loads were applied to the upper, middle, and lower parts of the knee, with maximum stresses at the PCL-fibula junction measuring 59.895 MPa, 27.481 MPa, and 28.607 MPa, respectively. Highest stresses on the PCL were observed under posterior loads on the upper, middle, and lower knee areas, with peak stresses of 57.421 MPa, 38.147 MPa, and 26.904 MPa, focusing notably on the PCL-tibia junction. When a lateral load was placed on the upper knee joint, the ACL showed the highest stress 32.102 MPa. Likewise, in a lateral impact on the middle knee joint, the ACL also had the highest stress of 29.544 MPa, with peak force at the ACL-tibia junction each time. In a lateral impact on the lower knee area, the LCL had the highest stress of 22.279 MPa, with the highest force at the LCL-fibula junction. Furthermore, the maximum stress data table indicates that stresses in the ligaments are typically higher when the upper portion of the knee is affected compared to when the middle and lower parts are impacted., Conclusions: This study recommends people avoid impacting the upper knee and use the middle and lower parts of the knee effectively against external forces to minimize ligament damage and safeguard the knee., (© 2024. The Author(s).)

Objective . Joint segmentation of tumors in positron emission tomography-computed tomography (PET-CT) images is crucial for precise treatment planning. However, current segmentation methods often use addition or concatenation to fuse PET and CT images, which potentially overlooks the nuanced interplay between these modalities. Additionally, these methods often neglect multi-view information that is helpful for more accurately locating and segmenting the target structure. This study aims to address these disadvantages and develop a deep learning-based algorithm for joint segmentation of tumors in PET-CT images. Approach . To address these limitations, we propose the Multi-view Information Enhancement and Multi-modal Feature Fusion Network (MIEMFF-Net) for joint tumor segmentation in three-dimensional PET-CT images. Our model incorporates a dynamic multi-modal fusion strategy to effectively exploit the metabolic and anatomical information from PET and CT images and a multi-view information enhancement strategy to effectively recover the lost information during upsamping. A Multi-scale Spatial Perception Block is proposed to effectively extract information from different views and reduce redundancy interference in the multi-view feature extraction process. Main results . The proposed MIEMFF-Net achieved a Dice score of 83.93%, a Precision of 81.49%, a Sensitivity of 87.89% and an IOU of 69.27% on the Soft Tissue Sarcomas dataset and a Dice score of 76.83%, a Precision of 86.21%, a Sensitivity of 80.73% and an IOU of 65.15% on the AutoPET dataset. Significance . Experimental results demonstrate that MIEMFF-Net outperforms existing state-of-the-art models which implies potential applications of the proposed method in clinical practice., (© 2024 Institute of Physics and Engineering in Medicine. All rights, including for text and data mining, AI training, and similar technologies, are reserved.)

Fusing three-dimensional (3D) and multispectral (MS) imaging data holds promise for high-throughput and comprehensive plant phenotyping to decipher genome-to-phenome knowledge. Acquiring high-quality 3D MS point clouds (3DMPCs) of plants remains challenging because of poor 3D data quality and limited radiometric calibration methods for plants with a complex canopy structure. Here, we present a novel 3D spatial-spectral data fusion approach to collect high-quality 3DMPCs of plants by integrating the next-best-view planning for adaptive data acquisition and neural reference field (NeREF) for radiometric calibration. This approach was used to acquire 3DMPCs of perilla, tomato, and rapeseed plants with diverse plant architecture and leaf morphological features evaluated by the accuracy of chlorophyll content and equivalent water thickness (EWT) estimation. The results showed that the completeness of plant point clouds collected by this approach was improved by an average of 23.6% compared with the fixed viewpoints alone. The NeREF-based radiometric calibration with the hemispherical reference outperformed the conventional calibration method by reducing the root mean square error (RMSE) of 58.93% for extracted reflectance spectra. The RMSE for chlorophyll content and EWT predictions decreased by 21.25% and 14.13% using partial least squares regression with the generated 3DMPCs. Collectively, our study provides an effective and efficient way to collect high-quality 3DMPCs of plants under natural light conditions, which improves the accuracy and comprehensiveness of phenotyping plant morphological and physiological traits, and thus will facilitate plant biology and genetic studies as well as crop breeding., (Copyright © 2024 The Author. Published by Elsevier Inc. All rights reserved.)

Patterns of lineal descent play a critical role in the development of metazoan embryos. In eutelic organisms that generate a fixed number of somatic cells, invariance in the topology of their cell lineage provides a powerful opportunity to interrogate developmental events with empirical repeatability across individuals. Studies of embryonic development using the nematode Caenorhabditis elegans have been drivers of discovery. These studies have depended heavily on high-throughput lineage tracing enabled by 4D fluorescence microscopy and robust computer vision pipelines. For a range of applications, computer-aided yet manual lineage tracing using 4D label-free microscopy remains an essential tool. Deep learning approaches to cell detection and tracking in fluorescence microscopy have advanced significantly in recent years, yet solutions for automating cell detection and tracking in 3D label-free imaging of dense tissues and embryos remain inaccessible. Here, we describe embGAN, a deep learning pipeline that addresses the challenge of automated cell detection and tracking in label-free 3D time-lapse imaging. embGAN requires no manual data annotation for training, learns robust detections that exhibits a high degree of scale invariance, and generalizes well to images acquired in multiple labs on multiple instruments. We characterize embGAN's performance using lineage tracing in the C. elegans embryo as a benchmark. embGAN achieves near-state-of-the-art performance in cell detection and tracking, enabling high-throughput studies of cell lineage without the need for fluorescent reporters or transgenics., Competing Interests: Conflicts of interest The authors declare no conflicts of interest., (© The Author(s) 2024. Published by Oxford University Press on behalf of The Genetics Society of America.)

Purpose: To evaluate the scanning strategies affecting the accuracy of virtual interocclusal records (VIR) in partially edentulous arches using an intraoral scanner in vitro., Methods: A reference model of a partially edentulous arch with implant analogs in positions 45,46 and 47 was constructed. Six pairs of 1-mm diameter metal beads were placed on the gingival tissue as markers for measurement. Four scanning strategies were tested: Quadrant-arch Scan (group 1), Quadrant-arch Scan with Auxiliary occlusal devices (AOD) (group 2), Full-arch Scan (group 3), Full-arch Scan with AOD (group 4). The model was digitalized with a lab scanner as a reference and 15 scans were obtained for each group. The accuracy of VIR was assessed by comparing the experiment data to the reference digital model., Results: The mean surface deviations of VIR for Groups 1-4 were 89.4 ± 105.2 μm,95.6 ± 132.8 μm,152.3 ± 159.7 μm and 107.6 ± 138.2 μm respectively. Quadrant-arch scans resulted in lower errors of VIR than full-arch scan (P < 0.001). There was a significant interaction between the AOD and scanning span (P = 0.017). The Quadrant-arch scan with AOD　(group 2) produced the least error in the distally extended edentulous area., Conclusions: Quadrant-arch scans showed better accuracy of VIR than full-arch scans across all tooth positions. The combination of AOD and quadrant-arch scan further enhances VIR accuracy in distally extended edentulous areas., (© 2024. The Author(s).)

The estimation of vessels' centerlines is a critical step in assessing the geometry of the vessel, the topological representation of the vessel tree, and vascular network visualization. In this research, we present a novel method for obtaining geometric parameters from peripheral arteries in 3D medical binary volumes. Our approach focuses on centerline extraction, which yields smooth and robust results. The procedure starts with a segmented 3D binary volume, from which a distance map is generated using the Euclidean distance transform. Subsequently, a skeleton is extracted, and seed points and endpoints are identified. A search methodology is used to derive the best path on the skeletonized 3D binary array while tracking from the goal points to the seed point. We use the distance transform to calculate the distance between voxels and the nearest vessel surface, while also addressing bifurcations when vessels divide into multiple branches. The proposed method was evaluated on 22 real cases and 10 synthetically generated vessels. We compared our method to different state-of-the-art approaches and demonstrated its better performance. The proposed method achieved an average error of 1.382 mm with real patient data and 0.571 mm with synthetic data, both of which are lower than the errors obtained by other state-of-the-art methodologies. This extraction of the centerline facilitates the estimation of multiple geometric parameters of vessels, including radius, curvature, and length.

Objective. Given the different noise distribution information of global and local magnetic resonance (MR) images, this study aims to extend the current work on convolutional neural networks that preserve global structure and local details in MR image denoising tasks. Approach. This study proposed a parallel and serial network for denoising 3D MR images, called 3D-PSNet. We use the residual depthwise separable convolution block to learn the local information of the feature map, reduce the network parameters, and thus improve the training speed and parameter efficiency. In addition, we consider the feature extraction of the global image and utilize residual dilated convolution to process the feature map to expand the receptive field of the network and avoid the loss of global information. Finally, we combine both of them to form a parallel network. What's more, we integrate reinforced residual convolution blocks with dense connections to form serial network branches, which can remove redundant information and refine features to further obtain accurate noise information. Main results. The peak signal-to-noise ratio, structural similarity index measure, and root mean square error metrics of 3D-PSNet are as high as 47.79%, 99.81%, and 0.40%, respectively, achieving competitive denoising effect on three public datasets. The ablation experiments demonstrated the effectiveness of all the designed modules regarding all the evaluated metrics in both datasets. Significance. The proposed 3D-PSNet takes advantage of multi-scale receptive fields, local feature extraction and residual dense connections to more effectively restore the global structure and local fine features in MR images, and is expected to help doctors quickly and accurately diagnose patients' conditions., (© 2024 Institute of Physics and Engineering in Medicine. All rights, including for text and data mining, AI training, and similar technologies, are reserved.)

Background: This study aimed to investigate the facial soft tissue characteristics of patients with different types of malocclusion., Methods: The 3dMD scanning data of patients with malocclusion admitted to our hospital from January 2018 to April 2022 were analyzed retrospectively. Forty-seven patients with Class I malocclusion, 43 patients with Class II malocclusion and 44 patients with Class III malocclusion were selected. All patients underwent 3dMD scans prior to orthodontic treatment. Then the differences in the 3D morphological parameters of the facial soft tissues were compared between different sexes and different types of malocclusion. Spearman's correlation was further used to analyze the correlation between each parameter and the classification of malocclusion., Results: In the Class I group and Class II group, there were no significant differences in the 3D morphometric parameters of malocclusion patients of different sexes (P > 0.05). There were significant differences between Al (R)-AL (L), Ac (R)-Ac (L), Prn-Ac (L), n-Prn-Sn, and Al (R)-Al (L)/Ac (L)-Ah (L) values among the three groups of patients. Spearman correlation analysis showed that Ac (R)-Ac (L) and Al (R)-Al (L)/Ac (R)-Ac (L) were correlated with the type of malocclusion., Conclusion: Differences in facial soft tissues exist in patients with Class I, II, and III malocclusion. 3dMD technique may be helpful in developing an effective treatment plan prior to orthodontic treatment., (© 2024. The Author(s).)

Background and Purpose: The circle of Willis (COW) is a crucial mechanism for cerebral collateral circulation. This proof-of-concept study aims to develop and assess an analysis method to characterize the hemodynamics of the arterial segments in the COW by using arterial spin-labeling (ASL) based non-contrast-enhanced dynamic MR angiography (dMRA)., Materials and Methods: The developed analysis method uses a graph model, bootstrap strategy, and ensemble learning methodologies to determine the time curve shift from ASL dMRA to estimate the flow direction within the COW. The performance of the method was assessed on 52 subjects, by using the flow direction, either antegrade or retrograde, derived from 3D phase-contrast MR imaging as the reference., Results: A total of 340 arterial segments in the COW were evaluated, among which 30 (8.8%) had retrograde flow according to 3D phase-contrast MRI. The ASL dMRA-based flow direction estimation has an accuracy, sensitivity, and specificity of 95.47%, 80%, and 96.34%, respectively., Conclusions: Using ASL dMRA and the developed image analysis method to estimate the flow direction in COW is feasible. This study provides a new method to assess the hemodynamics of the COW, which could be useful for the diagnosis and study of cerebrovascular diseases., (© 2024 by American Journal of Neuroradiology.)

Background and Purpose: Quantitative susceptibility mapping has been proposed to assess intraplaque hemorrhage (IPH) in the carotid artery. The purpose of this study was to compare the diagnostic accuracy of preoperative quantitative susceptibility mapping with that of the conventional T1-weighed 3D-FSE sequence for detecting IPH in cervical ICA stenosis in patients undergoing carotid endarterectomy by using histology as the reference standard., Materials and Methods: Carotid T1-weighted 3D-FSE and QSM images were obtained from 16 patients with cervical ICA stenosis before carotid endarterectomy. Relative signal intensity and susceptibility of the ICA were measured on 3 axial images, including the location of most severe stenosis on T1-weighted 3D-FSE and quantitative susceptibility mapping images, respectively. Three transverse sections of carotid plaques excised by carotid endarterectomy, which corresponded with images on MR imaging, were stained with H&E, antibody against glycophorin A, and Prussian blue, and the relative area of histologic IPH was calculated., Results: The correlation coefficient was significantly greater between susceptibility and relative area-histologic IPH ( ρ = 0.691) than between relative signal intensity and relative area-histologic IPH ( ρ = 0.413; P = .0259). The areas under the receiver operating characteristic curves for detecting histologic sections consisting primarily of IPH (relative area-histologic IPH > 40.7%) tended to be greater for susceptibility (0.964) than for T1WI FSE-relative signal intensity (0.811). Marginal homogeneity was observed between susceptibility and histologic sections consisting primarily of IPH ( P = .0412), but not between T1-weighted FSE-relative signal intensity and histologic sections consisting primarily of IPH ( P = .1824)., Conclusions: Pre-carotid endarterectomy quantitative susceptibility mapping detects histologic IPH in cervical ICA stenosis more accurately than preoperative T1-weighted 3D-FSE imaging., (© 2024 by American Journal of Neuroradiology.)

Background and Purpose: Vein of Galen malformation (VOGM) is the most common congenital cerebrovascular malformation, and many patients have high mortality rates and poor cognitive outcomes. Quantitative diagnostic tools are needed to improve clinical outcomes, and the purpose of this study was to characterize intracranial blood flow in VOGM using quantitative 4D flow MRI., Materials and Methods: A prospective study of children with VOGM was conducted by acquiring 4D flow MRI to quantify total blood inflow to the brain, flow in the pathologic falcine sinus, and flow in the superior sagittal sinus. Linear regression was used to test the relationships between these flows and age, clinical status, and the mediolateral diameter of the outflow tract of the lesion through the falcine or straight sinus diameter, which is a known morphologic prognostic metric., Results: In all 11 subjects (mean age, 22 [SD,17 ] weeks), total blood flow to the brain always exceeded normal levels (mean, 1063 [SD, 403] mL/minute). Significant correlations were observed between falcine sinus flow and the mediolateral diameter of the straight or falcine sinus, the posterior cerebral artery/MCA flow ratio and age at scanning, and superior sagittal sinus flow proximal to malformation inflow and age at scanning., Conclusions: Using 4D flow MRI, we established the hemodynamic underpinnings of the mediolateral diameter of the straight or falcine sinus and investigated metrics representing parenchymal venous drainage that could be used to monitor the normalization of hemodynamics during embolization therapy., (© 2024 by American Journal of Neuroradiology.)

The increasing implementation of high-field MRI scanners and the development of novel imaging techniques have rendered 3D imaging of joints more feasible and efficient than ever. This article describes the current state of 3D MRI of the shoulder and highlights the benefits of the technique over conventional 2D MRI with respect to shoulder derangements., Competing Interests: Declaration of competing interest Avneesh Chhabra: Consultant: ICON Medical and TREACE Medical Concepts Inc., Book Royalties: Jaypee, Wolters, Medical advisor: Image biopsy Lab Inc., Research grant: Image biopsy Lab Inc and Qure-AI., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Background: Cloacal malformation represents the rarest and most complex congenital anorectal malformation in females and is characterized by the convergence of urinary, gynecological, and intestinal systems within a single common channel. Three-dimensional computed tomography reconstruction (3D CT cloacagram) has emerged as a valuable method for anatomical assessment and preoperative planning., Objectives: To evaluate our experience with 3D CT cloacagram and assess its results., Methods: This retrospective case series included all patients with cloacal malformation who underwent preoperative 3D CT cloacagram at a single institution during 2019-2023. Collected data included patient characteristics, timing of the 3D CT cloacagram, results of the 3D CT cloacagram, comparison with endoscopic results, surgical procedures, and postoperative outcome., Results: Six patients with cloacal malformation were included in this study, including two with posterior cloaca. The median common channel length on 3D CT cloacagram was 24.5 mm (range 9-48 mm) and the median urethral length was 15.5 mm (range 13-24 mm). The surgical approach involved a combined abdominoperineal approach in three patients and posterior sagittal anorectal vaginal urethral plasty in one patient. Two patients were awaiting surgical reconstruction at the time of publication., Conclusions: Our implementation of 3D cloacagram has facilitated precise measurements of both the urethra and common channel lengths, two key factors in formulating surgical strategies for cloacal reconstruction. Moreover, this technique has markedly improved our capacity for surgical planning contributing to colorectal, gynecological, and urological perspectives.

Brain reconstruction, specially of the cerebral cortex, is a challenging task and even more so when it comes to highly gyrified brained animals. Here, we present Stitcher, a novel tool capable of generating such surfaces utilizing MRI data and manual segmentation. Stitcher makes a triangulation between consecutive brain slice segmentations by recursively adding edges that minimize the total length and simultaneously avoid self-intersection. We applied this new method to build the cortical surfaces of two dolphins: Guiana dolphin (Sotalia guianensis), Franciscana dolphin (Pontoporia blainvillei); and one pinniped: Steller sea lion (Eumetopias jubatus). Specifically in the case of P. blainvillei, two reconstructions at two different resolutions were made. Additionally, we also performed reconstructions for sub and non-cortical structures of Guiana dolphin. All our cortical mesh results show remarkable resemblance with the real anatomy of the brains, except P. blainvillei with low-resolution data. Sub and non-cortical meshes were also properly reconstructed and the spatial positioning of structures was preserved with respect to S. guianensis cerebral cortex. In a comparative perspective between methods, Stitcher presents compatible results for volumetric measurements when contrasted with other anatomical standard tools. In this way, Stitcher seems to be a viable pipeline for new neuroanatomical analysis, enhancing visualization and descriptions of non-primates species, and broadening the scope of compared neuroanatomy., Competing Interests: Declarations. Competing Interest: The authors declare no competing interests., (© 2024. The Author(s).)