Proper Fusion Research Articles

Outcomes of naviculocuneiform arthrodesis with and without adjunct arthrodesis

Naviculocuneiform (NC) arthrodesis is considered a challenging procedure compared to arthrodesis of other medial column joints and/or hindfoot fusions. The objectives of this study were to 1) report the incidence of nonunion and complications after NC arthrodesis with or without adjunct joint arthrodesis, and 2) report incidences in which a fixation method was used and report how many cuneiform joints were fused. A retrospective review of medical charts and radiographs were performed on patients from 1/2013 through 11/2023 at a single institution in the Midwest region. 137 cases included and 90 (66%) adjunct joint arthrodesis incidents. The overall nonunion rate was 25% (34/137 cases) and overall revision rate was 15% (21/137 cases). The nonunion rate with adjunct joint arthrodesis was 26% (23/90 cases) and without was 23% (11/47 cases). The screws-alone fixation had the lowest nonunion rate of 20% (4/20 cases). The overall complication rate was 47% (65/137 cases), and the most common cause was hardware issues (31%, 43/137 cases). Fixating all three joints regardless of fixation constructs resulted in 18% (5/28 cases) nonunion. Crossed screws with medial plate fixation when fixated medial and middle cuneiform joints had the highest nonunion rates (24%, 10/42 cases) while fixation with screws and staples had the lowest nonunion rates (11%, 1/9 cases). In conclusion, the choice of fixation technique and number of cuneiform joints fused could affect the success of NC arthrodesis. Implementing proper cuneiform joints fusion and recognizing the limitations of fixation techniques potentially reduces the risk of nonunion and complications.

A Task-Guided, Implicitly-Searched and Meta-Initialized Deep Model for Image Fusion.

Image fusion plays a key role in a variety of multi-sensor-based vision systems, especially for enhancing visual quality and/or extracting aggregated features for perception. However, most existing methods just consider image fusion as an individual task, thus ignoring its underlying relationship with these downstream vision problems. Furthermore, designing proper fusion architectures often requires huge engineering labor. It also lacks mechanisms to improve the flexibility and generalization ability of current fusion approaches. To mitigate these issues, we establish a Task-guided, Implicit-searched and Meta-initialized (TIM) deep model to address the image fusion problem in a challenging real-world scenario. Specifically, we first propose a constrained strategy to incorporate information from downstream tasks to guide the unsupervised learning process of image fusion. Within this framework, we then design an implicit search scheme to automatically discover compact architectures for our fusion model with high efficiency. In addition, a pretext meta initialization technique is introduced to leverage divergence fusion data to support fast adaptation for different kinds of image fusion tasks. Qualitative and quantitative experimental results on different categories of image fusion problems and related downstream tasks (e.g., visual enhancement and semantic understanding) substantiate the flexibility and effectiveness of our TIM.

Sensor placement for optimal aerodynamic data fusion

Aircraft design is recently evolving towards a digital twin representation that involves many heterogeneous data sources. The aerodynamic development of aircraft usually incorporates data from computational fluid dynamics simulations, wind tunnel testing, and flight tests. All of these data sources have their advantages and disadvantages, which can optimally be combined using data fusion methods. However, the quality of the data fusion result strongly depends on the experimental design, i.e. the placement of discrete sensors. Therefore, an optimized sensor placement is essential for data fusion applications, as the number of sensors is limited. This work presents a sensor placement strategy for the widely used Gappy proper orthogonal decomposition data fusion methodology. The sensor placement relies on a Bayesian formulation of the data fusion, allowing accurate error estimates. Based on the Bayesian posterior, a utility function characterizes the quality of the fused result by quantifying the expected information gain for the proper orthogonal decomposition coefficients. As the optimization of the sensor locations involves a complex combinatorial problem, we introduce an efficient genetic algorithm for this task. The method is demonstrated on a two-dimensional airfoil and the NASA Common Research Model with synthetic measurement errors. For both test cases, an optimal sensor placement results in smaller reconstruction errors than a conventional layout. The Bayesian approach leads, in most cases, to more accurate reconstructions and is more versatile than other well-established sensor placement methods. The proposed genetic algorithm finds better optima with significantly fewer function evaluations than the widely used greedy algorithms.

Hyper-Selective Posterior Fusion is Recommended When the Modified S-Line is Positive in Lenke 5C Adolescent Idiopathic Scoliosis.

Postoperative coronal decompensation and less fusion level are dilemmas and the proper selective posterior fusion (SPF) strategy should be investigated. We proposed a parameter, modified S-line, and aimed to investigate if the modified S-line could predict postoperative coronal decompensation in patients with Lenke 5C adolescent idiopathic scoliosis (AIS). This is a retrospective radiographic study and Lenke 5C AIS patients undergoing SPF during the period from September 2017 to June 2021 were included. The modified S-line was defined as the line linking the centers of the concave-side pedicles of the upper end vertebra (UEV) and lower end vertebra (LEV) at baseline. A modified S-line tilt to the right is established as modified S-line+ (UEV being to the right of the LEV). The patients were further categorized into two groups: the Cobb to Cobb fusion group and the Cobb-1 to Cobb fusion group. Outcomes including thoracic Cobb angle, TL/L Cobb angle, coronal balance, upper instrumented vertebra (UIV) translation, lower instrumented vertebra (LIV) translation, UIV tilt, LIV tilt, LIV disc angle, thoracic apical vertebral translation, lumbar apical vertebral translation (L-AVT), L-T AVT ratio, L-T Cobb were measured at baseline, immediately after surgery, and the last follow-up. Radiographic parameters and the incidence of both proximal and distal decompensation between the two groups were compared by chi-square test. Among 92 patients, 48 were modified S-line+ and 44 were modified S-line-. Modified S-line+ status was identified as a risk factor for postoperative proximal decompensation (p = 0.005) during follow-up. In Cobb to Cobb group, a higher occurrence of proximal decompensation in individuals with modified S-line+ status (p = 0.001) was confirmed. Also, in the Cobb to Cobb group with baseline modified S-line+ status, patients presenting decompensation showed a significantly larger baseline of the UIV tilt and postoperative disc angle below the lower instrumented vertebra. However, In Cobb-1 group, the incidence of decompensation after surgery showed no association with baseline modified S-line tilt status (p = 0.815 and 0.540, respectively). The modified S-line could serve as an important parameter in surgical decision-making for Lenke 5C AIS patients. Cobb to Cobb SPF is not recommended with a modified S-line+ status, and the Cobb-1 to Cobb fusion may serve as a potential alternative.

Comparing the osteogenesis outcomes of different lumbar interbody fusions (A/O/X/T/PLIF) by evaluating their mechano-driven fusion processes

BackgroundIn lumbar interbody fusion (LIF), achieving proper fusion status requires osteogenesis to occur in the disc space. Current LIF techniques, including anterior, oblique, lateral, transforaminal, and posterior LIF (A/O/X/T/PLIF), may result in varying osteogenesis outcomes due to differences in biomechanical characteristics. MethodsA mechano-regulation algorithm was developed to predict the fusion processes of A/O/X/T/PLIF based on finite element modeling and iterative evaluations of the mechanobiological activities of mesenchymal stem cells (MSCs) and their differentiated cells (osteoblasts, chondrocytes, and fibroblasts). Fusion occurred in the grafting region, and each differentiated cell type generated the corresponding tissue proportional to its concentration. The corresponding osteogenesis volume was calculated by multiplying the osteoblast concentration by the grafting volume. ResultsTLIF and ALIF achieved markedly greater osteogenesis volumes than did PLIF and O/XLIF (5.46, 5.12, 4.26, and 3.15 cm3, respectively). Grafting volume and cage size were the main factors influencing the osteogenesis outcome in patients treated with LIF. A large grafting volume allowed more osteoblasts (bone tissues) to be accommodated in the disc space. A small cage size reduced the cage/endplate ratio and therefore decreased the stiffness of the LIF. This led to a larger osteogenesis region to promote osteoblastic differentiation of MSCs and osteoblast proliferation (bone regeneration), which subsequently increased the bone fraction in the grafting space. ConclusionTLIF and ALIF produced more favorable biomechanical environments for osteogenesis than did PLIF and O/XLIF. A small cage and a large grafting volume improve osteogenesis by facilitating osteogenesis-related cell activities driven by mechanical forces.

An Algorithmic Framework for Optimizing Submerged Arc Additive Manufacturing Process Parameters for User-Specified Bead Width

Submerged Arc Additive Manufacturing (SAAM) is a process known for its high material deposition characteristics, and since it is based on Submerged Arc Welding (SAW), it is expected to obtain thicker material depositions. In this work, an algorithmic framework has been developed which helps product designers or the user by taking their expectations of the bead width according to their requirement, and the algorithm suggests the optimal input process parameters which would help obtain an optimal bead width and optimal use of energy, minimizing the need for post-processing. The framework incorporates penetration depth, a critical factor for proper interlayer fusion. The framework was compared with a Genetic Algorithm (GA) output with similar GA parameters for a single run to evaluate its effectiveness. The proposed framework achieves a 93.7% accuracy in bead width prediction and a 27.5% reduction in energy input per unit length compared to the GA. This user-friendly tool empowers novice SAAM users and manufacturers to optimize deposition and energy efficiency.

IRFR-Net: Interactive Recursive Feature-Reshaping Network for Detecting Salient Objects in RGB-D Images.

Using attention mechanisms in saliency detection networks enables effective feature extraction, and using linear methods can promote proper feature fusion, as verified in numerous existing models. Current networks usually combine depth maps with red-green-blue (RGB) images for salient object detection (SOD). However, fully leveraging depth information complementary to RGB information by accurately highlighting salient objects deserves further study. We combine a gated attention mechanism and a linear fusion method to construct a dual-stream interactive recursive feature-reshaping network (IRFR-Net). The streams for RGB and depth data communicate through a backbone encoder to thoroughly extract complementary information. First, we design a context extraction module (CEM) to obtain low-level depth foreground information. Subsequently, the gated attention fusion module (GAFM) is applied to the RGB depth (RGB-D) information to obtain advantageous structural and spatial fusion features. Then, adjacent depth information is globally integrated to obtain complementary context features. We also introduce a weighted atrous spatial pyramid pooling (WASPP) module to extract the multiscale local information of depth features. Finally, global and local features are fused in a bottom-up scheme to effectively highlight salient objects. Comprehensive experiments on eight representative datasets demonstrate that the proposed IRFR-Net outperforms 11 state-of-the-art (SOTA) RGB-D approaches in various evaluation indicators.

ARTRODESE CERVICAL ANTERIOR COM ESPAçADOR INTERVERTEBRAL E APOIO óSSEO CILíNDRICO

ABSTRACT The anterior cervical discectomy and fusion is considered an established technique in cervical degenerative disease treatment, in which the final goal is the fusion of the segments involved. There are options for spacer grafts, such as bone grafts and synthetic bone substitutes like hydroxyapatite and tricalcium phosphate. This technical note describes the combination of the stand-alone anchored intervertebral spacer and iliac graft, which is used as a pillar between the vertebrae. The iliac crest removal is performed with a 10 mm or 12 mm diameter trephine. The trephine is employed to make a graft in the same format as the inner portion of the intervertebral spacer. The cylindrical bone graft removed must be 1 millimeter higher than the cage that will be implanted so that it is 0.5 mm above and below the upper and lower edges of the cage. The objective is to establish support between the vertebral plateaus and the bone cylinder, as they present similar resistance and biological aspects, which are fundamental characteristics for proper osseointegration and fusion. When the conventional technique is used, the interaction between the cage and the plateaus occurs more intensely, and a plateau fracture may occur, a phenomenon known as subsidence. This technical note describes a feasible way to obtain autograft bone to be used in ACDF stand-alone surgery. This type of graft may be associated with lower rates of pseudoarthrosis. Level of Evidence IV; Case Series.

неЩасливий випадок як поштовх до діагностики хвороби у 16-річного хлопця, пов’язаної з MYH9. Сюжет із практики гематолога

MYH9-related disease (MYH9-RD) is an autosomal dominant hereditary thrombocytopenia caused by mutations in the MYH9 gene with characteristic laboratory features - the presence of giant platelets and basophilic cytoplasmic inclusions in neutrophils (similar to Dele bodies). Patients with MYH9-RD are at high risk for deafness, cataracts, and renal dysfunction, most often occurring in adulthood. Platelet counts in patients with MYH9-RD range from severe thrombocytopenia to near-normal values, although they are usually stable. Propensity for hemorrhagic Complications correlate with platelet count and are usually absent or limited to minor bleeding in patients with mild thrombocytopenia, but may lead to spontaneous and potentially life-threatening bleeding with persistent platelet counts <50×109/l. Purpose - to describe a clinical case of a disease caused by a heterozygous mutation in the MYH9 gene with an emphasis on the importance of genetic tests for the final verification of the disease. Clinical case. Features of diagnosis caused by a heterozygous mutation in the MYH9 gene in a 16-year-old boy are described. Throughout the child's life, the manifestations of the hemorrhagic syndrome were moderate (periodically a small number of bruises on the skin, to which the parents did not pay much attention, bleeding from the gums when brushing the teeth), the child’s blood tests were performed occasionally without determining the number of platelets. The boy suffered a displaced radius fracture as a result of the injury. The orthopedic traumatologist performed an operation of limited reposition of bone fragments followed by implantation of a needle for proper bone fusion without complications. During a general blood test, thrombocytopenia was detected, which prompted the child to be consulted by a hematologist. During the examination at the Western Ukrainian Specialized Pediatric Medical Center, Lviv, it was noted in the hardware count of the hemogram that the number of platelets was 22.0-30.0×109/l, the microscopic count of platelets was 147.0-156.0×109/l, the entire population of platelets was represented by macroforms with mean platelet volume 14.9 fl. We found good aggregation of platelets with ristocytin, and reduced aggregation with epinephrine, arachidonic acid, and adenosine. Verification of the final diagnosis of MYH9-RD caused by a heterozygous mutation in the MYH9 gene occurred by genome sequencing. Therefore, the application of the genome sequencing technique can contribute to the early diagnosis of hereditary macrothrombocytopenia caused by a heterozygous mutation in the MYH9 gene. The research was carried out in accordance with the principles of the Helsinki Declaration. The informed consent of the patient was obtained for conducting the studies. No conflict of interests was declared by the authors.

A comparative study of GNN and MLP based machine learning for the diagnosis of Alzheimer’s Disease involving data synthesis

Alzheimer’s Disease (AD) is a neurodegenerative disease that commonly occurs in older people. It is characterized by both cognitive and functional impairment. However, as AD has an unclear pathological cause, it can be hard to diagnose with confidence. This is even more so in the early stage of Mild Cognitive Impairment (MCI). This paper proposes a U-Net based Generative Adversarial Network (GAN) to synthesize fluorodeoxyglucose - positron emission tomography (FDG-PET) from magnetic resonance imaging - T1 weighted imaging (MRI-T1WI) for further usage in AD diagnosis including its early-stage MCI. The experiments have displayed promising results with Structural Similarity Index Measure (SSIM) reaching 0.9714. Furthermore, three types of classifiers are developed, i.e., one Multi-Layer Perceptron (MLP) based classifier, two Graph Neural Network (GNN) based classifiers where one is for graph classification and the other is for node classification. 10-fold cross-validation has been conducted on all trials of experiments for classifier comparison. The performance of these three types of classifiers has been compared with the different input modalities setting and data fusion strategies. The results have shown that GNN based node classifier surpasses the other two types of classifiers, and has achieved the state-of-the-art (SOTA) performance with the best accuracy at 90.18% for 3-class classification, namely AD, MCI and normal control (NC) with the synthesized fluorodeoxyglucose - positron emission tomography (FDG-PET) features fused at the input level. Moreover, involving synthesized FDG-PET as part of the input with proper data fusion strategies has also proved to enhance all three types of classifiers’ performance. This work provides support for the notion that machine learning-derived image analysis may be a useful approach to improving the diagnosis of AD.

Distributed fusion filtering for cyber-physical systems under Round-Robin protocol: a mixed H 2/H ∞ framework

ABSTRACT In this paper, the distributed mixed fusion filter design problem is investigated for a class of cyber-physical systems subject to non-ideal measurements under Round-Robin protocol. To save the limited communication resources, the Round-Robin protocol is employed to schedule the data transmissions from the sensors to the remote filters. The measurement is imperfect by taking into account the noises, the random saturations, nonlinearity perturbations and packet dropouts. The objective of this study is to propose a desired fusion filtering method that ensures the prescribed performance constraints on both the local and fusion filtering error dynamics. With the aid of Lyapunov function and stochastic analysis technique, a sufficient condition is established to guarantee the mixed / performance index for the local filtering error systems, and then the filter parameter matrices are derived by resorting to the solutions to some matrix inequalities. Subsequently, on the basis of the obtained local state estimates, the proper fusion parameters are acquired by solving a convex optimisation problem. Finally, a numerical example is provided to demonstrate the effectiveness of the designed fusion filter.

Progressively Hybrid Transformer for Multi-Modal Vehicle Re-Identification.

Multi-modal (i.e., visible, near-infrared, and thermal-infrared) vehicle re-identification has good potential to search vehicles of interest in low illumination. However, due to the fact that different modalities have varying imaging characteristics, a proper multi-modal complementary information fusion is crucial to multi-modal vehicle re-identification. For that, this paper proposes a progressively hybrid transformer (PHT). The PHT method consists of two aspects: random hybrid augmentation (RHA) and a feature hybrid mechanism (FHM). Regarding RHA, an image random cropper and a local region hybrider are designed. The image random cropper simultaneously crops multi-modal images of random positions, random numbers, random sizes, and random aspect ratios to generate local regions. The local region hybrider fuses the cropped regions to let regions of each modal bring local structural characteristics of all modalities, mitigating modal differences at the beginning of feature learning. Regarding the FHM, a modal-specific controller and a modal information embedding are designed to effectively fuse multi-modal information at the feature level. Experimental results show the proposed method wins the state-of-the-art method by a larger 2.7% mAP on RGBNT100 and a larger 6.6% mAP on RGBN300, demonstrating that the proposed method can learn multi-modal complementary information effectively.

Adaptive coloured noise multirate Kalman filter and its application in coseismic deformations

SUMMARYThe accuracy and sampling rate of a coseismic displacement and velocity waveform can be improved by fusing Global Navigation Satellite System (GNSS) and strong motion (SM) sensor data with a multirate Kalman filter. However, many studies have shown that the noise in GNSS coseismic waveforms includes coloured noise, and it is challenging to obtain proper GNSS and SM fusion results if the GNSS coloured noise is not accurately represented. In this paper, we propose a coloured noise multirate Kalman filter, which uses a stochastic model for modelling the GNSS coloured noise to achieve an accurate fusion of data from GNSS and SM for different sampling rates. In addition, we also propose an estimation method for the multirate Kalman filter stochastic model under coloured noise to achieve the optimal adaptive fusion of GNSS and SM data. After the reliability of the proposed method was confirmed using Monte Carlo simulations and earthquake engineering data tests, the proposed method was applied to data collected from the 2019 Mw 7.1 Ridgecrest earthquake and 2016 Mw 7.8 Kaikoura earthquake. The test results show that the proposed method can effectively fuse GNSS and SM data and accurately obtain broadband coseismic displacement and velocity waveforms.

Protein S-palmitoylation regulates different stages of meiosis in Schizosaccharomyces pombe.

Posttranslational protein S-palmitoylation regulates the localization and function of its target proteins involved in diverse cellular processes including meiosis. In this study, we demonstrate that S-palmitoylation mediated by Erf2-Erf4 and Akr1 palmitoylacyltransferases is required at multiple meiotic stages in the fission yeast Schizosaccharomyces pombe We find that S-palmitoylation by Erf2-Erf4 is required for Ras1 localization at the cell periphery to enrich at the cell conjugation site for mating pheromone response. In the absence of Erf2 or Erf4, mutant cells are sterile. A role of Akr1 S-palmitoylating the nuclear fusion protein Tht1 to function in karyogamy is identified. We demonstrate that S-palmitoylation stabilizes and localizes Tht1 to ER, interacting with Sey1 ER fusion GTPase for proper meiotic nuclear fusion. In akr1, tht1, or sey1 mutant, meiotic cells, haploid nuclei are unfused with subsequent chromosome segregation defects. Erf2-Erf4 has an additional substrate of the spore coat protein Isp3. In the absence of Erf2, Isp3 is mislocalized from the spore coat. Together, these results highlight the versatility of the cellular processes in which protein S-palmitoylation participates.

An Image Construction Based on the VTLF Fusion Technique for Oil–Water Two-Phase Flow of Noncontact Electrical Impedance Tomography

Electrical tomography (ET) has attracted extensive attention in the petroleum multiphase flow field due to its advantages of nonintrusion, nonradiation, and simple equipment structure. Some contactless impedance imaging methods, such as capacitively coupled electrical resistance tomography (CCERT) and phase-based dielectric spectroscopy tomography, or displacement current phase tomography (DCPT), have been studied for the parameter measurement of two-phase flow. The mentioned research mainly focuses on the separate imaging by real part, imaginary part, or phase information of the voltage/current. However, the distribution change of media in the region of interest (RoI), especially the presence of high permittivity and conductivity materials, involves the distribution change of conductivity, permittivity, and loss factor. Developing a proper image fusion technique based on the three components can provide more comprehensive image information for tomographic imaging. This article proposed an improved logic filter image fusion algorithm based on a variable threshold (VTLF), and a noncontact electrical impedance tomography (NEIT) system for imaging water–oil two-phase flow is carried out. Image reconstruction is implemented by the VTLF image fusion algorithm under different media distributions, conductivities, and excitation frequencies, and the image fusion algorithms of a weighted average (WA) and logic filter (LF) are also used for comparison. The simulation results show that the reconstructed images by the proposed fusion method of VTLF had the lowest artifacts and the highest correlation coefficient (above 0.7) compared with other methods. Also, in the experiment, the VTLF also got the best performance, so it is effective to improve the reconstruction accuracy.

Automatic targetless LiDAR–camera calibration: a survey

The recent trend of fusing complementary data from LiDARs and cameras for more accurate perception has made the extrinsic calibration between the two sensors critically important. Indeed, to align the sensors spatially for proper data fusion, the calibration process usually involves estimating the extrinsic parameters between them. Traditional LiDAR–camera calibration methods often depend on explicit targets or human intervention, which can be prohibitively expensive and cumbersome. Recognizing these weaknesses, recent methods usually adopt the autonomic targetless calibration approach, which can be conducted at a much lower cost. This paper presents a thorough review of these automatic targetless LiDAR–camera calibration methods. Specifically, based on how the potential cues in the environment are retrieved and utilized in the calibration process, we divide the methods into four categories: information theory based, feature based, ego-motion based, and learning based methods. For each category, we provide an in-depth overview with insights we have gathered, hoping to serve as a potential guidance for researchers in the related fields.

Application of the core shell model for strengthening polymer filament interfaces

While surface segregation has been intensively studied in thin films, relatively little has been investigated in filament geometries. In contrast to thin films, the filament surface forms a continuum, with interactions both at the free air and internal filament interface, which makes it difficult to achieve an equilibrium configuration. This asymmetry has become particularly apparent with the increasing use of additive manufacturing where entire structures are constructed via layered deposition of filamentous layers from a moving thermal nozzle. In addition, this process is highly non-equilibrated with poor thermal retention and is responsible for insufficient filament–filament interfacial fusion and internal pore formation along the printing direction. These features all contribute to poor mechanical and structural properties, which are exacerbated in semi-crystalline polymers, such as Polylactic Acid (PLA), where the melting point, Tm, is much higher than the glass transition, Tg. Even though system is liquid the molecules become ordered within the crystal structure and this ordering interferes with interdiffusion, which in turn prevents proper interfacial fusion. Capitalizing on the differential in surface tension, we show that addition of less than 1%, or trace amounts, of longer chain polymers, an oriented core shell structure, will be formed with a self-limiting thickness of three time the radius of gyration, Rg, of the tracer chains. The lower Tg of the tracers and their orientation makes them poised for interdiffusion when subsequent layers are deposited producing structures with significant improvement of the mechanical properties and internal structural integrity.

A CADAVERIC STUDY OF SEEMANTA MARMA

Background: The marma sharira is a prime territory of Rachana sharira. Sushruta had elaborated marma sharira at a certain depth. Marma (vital area) is described in the Hindu scripture Atharva Veda. During the Vedic era, the Marma Sharira had particular importance in the case of war field. The seemanta marma is shira marma, kalantara pranahara. The nature of this marma is sandhi marma. Aims: There are very few studies regarding the cadaveric study of seemanta marma. This study aims to identify the possible anatomical structure and analyze those structures. Perhaps it could be helpful for future scholars of Ayurveda. Material and method: The review was performed based on traditional Ayurvedic classics and contemporary medical sciences, journals, publications, articles, e-journals etc. The region of seemanta marma and surrounding area was dissected, and complete anatomical study was done. Discussion: The term seemanta indicates that the bony joint is present in the skull region. The joints present in the skull region are mainly sutural joints and fibrous, which provide malleable head quality. There are five major sutures in adult like coronal suture, sagittal suture, lambdoid suture and two squamous sutures, the frontal sutures present in infant and children. Conclusion: It has a significant role during delivery and brain development, which allows normal vaginal birth of the head. It also offers normal cranial growth by proper fusion if the premature fusion of sutures occurs (craniosynostosis), which results in cranial malformation.

Hemophagocytic Lymphohistiocytosis.

Hemophagocytic Lymphohistiocytosis.

Simulating upright cervical lordosis in the supine position.

Cervical alignment or lordosis evolution is still attained by direct radiography in standing position because an ideal cervical curvature is essential to maintain a horizontal gaze with minimal energy consumption. However, upright cervical lordosis changes in supine position. Anterior fusion surgery and more sophisticated radiological examinations, such as Computed Tomography (CT) and Magnetic Resonance Imaging (MRI), are performed in lying position. Therefore, if upright cervical alignment can be simulated in the supine position, true (upright) cervical lordosis can be demonstrated on CT and MRI and also a more proper anterior cervical fusion can be performed in operation with better surgical outcomes. Forty-nine (49) adult patients underwent radiological examinations, including upright cervical radiography and three session of supine MRI in different positions. MRI was performed in (1) conventional neutral supine position, (2) supine position with a 5-cm-high pillow, and (3) supine position with a 10-cm-high pillow under the shoulders. MRI results were analyzed. Wilcoxon, Kolmogorov-Smirnov, and Spearman correlation tests were used to analyze MRI the validity in compared with those of cervical radiography. Cervical lordosis (C2-C7 Cobb angle) of the radiography group was similar to that of supine MRI group using a 5-cm-high pillow, and they have a strong correlation. The T-1 slope from radiography group was similar to and correlated with that of supine MRI groups with both pillows. Cranial tilt measurements of radiography group were different but correlated with the MRI group using a 5-cm-high pillow. Simulating upright cervical lordosis in the supine position is possible by adding a 5-cm- high pillow under the shoulders of the patients. This simulation reduces the need for direct radiography. Anterior cervical fusion surgery performed in this position can provide better surgical results.