A Preliminary Diagnostic Model for Forward Head Posture among Adolescents Using Forward Neck Tilt Angle and Radiographic Sagittal Alignment Parameters.

Despite numerous attempts to correct forward head posture (FHP), definitive evidence-based screening and diagnostic methods remain elusive. This study proposes a preliminary diagnostic methodology for FHP, utilizing a noninvasive body angle measurement system as a screening test for FHP and incorporating radiological parameters for sagittal alignment. We enrolled 145 adolescents for FHP screening. The forward neck tilt angle (FNTA), defined as the angle between the vertical line and the line connecting the participant's acromion and tragus, was measured using the POM-Checker (a noninvasive depth sensor-based body angle measurement system). A whole-spine standing lateral radiograph was obtained, and eight sagittal alignment parameters were measured. Statistical analyses of the association between the FNTA and eight sagittal alignment parameters were conducted. We used 70% of the participant data to establish a preliminary diagnostic model for FHP based on FNTA and each sagittal alignment parameter. The accuracy of the model was evaluated using the remaining 30% of the participant data. All radiological parameters of sagittal alignment showed weak statistical significance with respect to FNTA (best case: r = 0.16, p = 0.0500; cranial tilt). The proposed preliminary diagnostic model for FHP demonstrated 95.35% agreement. Notably, the model using FNTA without radiological parameters accurately identified (100%) participants who required radiographic scanning for FHP diagnosis. Owing to the weak statistical significance of the association between radiological parameters and external body angle, both factors must be considered for accurate FHP diagnosis. When a clear and severe angle variation is observed in an external body angle check, medical professionals should perform radiographic scanning for an accurate FHP diagnosis. In conclusion, FNTA assessment of FNTA through the proposed preliminary diagnostic model is a significant screening factor for selecting participants who must undergo radiographic scanning so that a diagnosis of FHP can be obtained.

Automatic segmentation of inconstant fractured fragments for tibia/fibula from CT images using deep learning.

Orthopaedic surgeons need to correctly identify bone fragments using 2D/3D CT images before trauma surgery. Advances in deep learning technology provide good insights into trauma surgery over manual diagnosis. This study demonstrates the application of the DeepLab v3+ -based deep learning model for the automatic segmentation of fragments of the fractured tibia and fibula from CT images and the results of the evaluation of the performance of the automatic segmentation. The deep learning model, which was trained using over 11 million images, showed good performance with a global accuracy of 98.92%, a weighted intersection over the union of 0.9841, and a mean boundary F1 score of 0.8921. Moreover, deep learning performed 5-8 times faster than the experts' recognition performed manually, which is comparatively inefficient, with almost the same significance. This study will play an important role in preoperative surgical planning for trauma surgery with convenience and speed.

Structural analysis of customized 3D printed plate for pelvic bone by comparison with conventional plate based on bending process.

Pelvic bone fracture is highly complex, and its anatomical reduction is difficult. Therefore, patient-specific customized plates have been developed using three-dimensional (3D) printing technology and are being increasingly used. In this study, the reduction status in five representative pelvic fracture models was compared between two groups: the 3D printing plate (3DP) group using a patient-specific 3D printed plate after virtual reduction and the conventional plate (CP) group using a conventional plate by manual bending. The 3DP and CP groups included 10 and 5 cases, respectively. The fractured models were reduced virtually and their non-locking metal plates were customized using 3D printing. The process of contouring the conventional plates to fit the contact surface of the bone with the bending tool was conducted by an experienced pelvic bone trauma surgeon. The reduction and fixation achieved using the two different plate groups was compared, and the significance of differences in the results was analyzed using paired t-tests, after verifying the normality of data distribution. The vertex distances between the surface of the bone and the contact surface of the plate were significantly lower in the 3DP group than in the CP group (0.407 ± 0.342 and 2.195 ± 1.643, respectively, P = 0.008). Length and angular variations, which are measurements of the reduction state, were also lower in the 3DP group than in the CP group (length variation: 3.211 ± 2.497 and 5.493 ± 3.609, respectively, P = 0.051; angular variation: 2.958 ± 1.977 and 4.352 ± 1.947, respectively, P = 0.037). The customized 3D printed plate in the virtual reduction model provided a highly accurate reduction of pelvic bone fractures, suggesting that the customized 3D printed plate may help ensure easy and accurate reduction.

Deep Learning Model Based on You Only Look Once Algorithm for Detection and Visualization of Fracture Areas in Three-Dimensional Skeletal Images.

Utilizing "You only look once" (YOLO) v4 AI offers valuable support in fracture detection and diagnostic decision-making. The purpose of this study was to help doctors to detect and diagnose fractures more accurately and intuitively, with fewer errors. The data accepted into the backbone are diversified through CSPDarkNet-53. Feature maps are extracted using Spatial Pyramid Pooling and a Path Aggregation Network in the neck part. The head part aggregates and generates the final output. All bounding boxes by the YOLO v4 are mapped onto the 3D reconstructed bone images after being resized to match the same region as shown in the 2D CT images. The YOLO v4-based AI model was evaluated through precision-recall (PR) curves and the intersection over union (IoU). Our proposed system facilitated an intuitive display of the fractured area through a distinctive red mask overlaid on the 3D reconstructed bone images. The high average precision values (>0.60) were reported as 0.71 and 0.81 from the PR curves of the tibia and elbow, respectively. The IoU values were calculated as 0.6327 (tibia) and 0.6638 (elbow). When utilized by orthopedic surgeons in real clinical scenarios, this AI-powered 3D diagnosis support system could enable a quick and accurate trauma diagnosis.

Quantitative Assessment of the Restoration of Original Anatomy after 3D Virtual Reduction of Long Bone Fractures.

Background: The purpose of this study was to demonstrate the usefulness of 3D image-based virtual reduction by validating the evaluation criteria according to guidelines suggested by the AO Surgery Reference. Methods: For this experiment, 19 intact radial ORTHObones (ORTHObones radius, 3B Scientific, Germany, Hamburg) without any fractures were prepared. All ORTHObones with six cortical marking holes (three points on the distal part and three points on the proximal part) were scanned using a CT scanner twice (before/after intentional fracture of the ORTHObone). After the virtual reduction of all 19 ORTHObones, accuracy evaluations using the four criteria (length variation, apposition variation, alignment variation, Rotation Variation) suggested in the AO Surgery Reference were performed. Results: The mean (M) length variation was 0.42 mm, with 0.01 mm standard deviation (SD). The M apposition variation was 0.48 mm, with 0.40 mm SD. The M AP angulation variation (for alignment variation) was 3.24°, with 2.95° SD. The M lateral angulation variation (for alignment variation) was 0.09°, with 0.13° SD. The M angle of axial rotation was 1.27° with SD: 1.19°. Conclusions: The method of accuracy evaluation used in this study can be helpful in establishing a reliable plan.

Does a Customized 3D Printing Plate Based on Virtual Reduction Facilitate the Restoration of Original Anatomy in Fractures?

The purpose of this study was to evaluate the restoration of original anatomy after fixation of sawbone fractures using case-specific 3D printing plates based on virtual reduction (VR). Three-dimensional models of 28 tibia sawbones with cortical marking holes were obtained. The sawbones were fractured at various locations of the shaft and 3D models were obtained. The fractured models were reduced virtually and customized non-locking metal plates that fit the reduced model were produced via 3D printing. The fractured sawbones were actually fixed to the customized plate with nonlocking screws and 3D models were generated. With the proximal fragments of the 3D models overlapped, the changes in length, 3D angulation, and rotation of the distal fragment were evaluated. Compared to the intact model (IN), the virtual reduction model (VR) and the actual fixation model (AF) showed no significant differences in length. Compared to the IN, the VR and the AF had mean 3D angulations of 0.39° and 0.64°, respectively. Compared to the IN model, the VR and the AF showed mean rotations of 0.89° and 1.51°, respectively. A customized plate based on VR facilitates the restoration of near-original anatomy in fractures of tibial sawbone shaft.

Simplified sigmoidal curve fitting for a 6 MV FFF photon beam of the Halcyon to determine the field size for beam commissioning and quality assurance.

BACKGROUND: An O-ring gantry-type linear accelerator (LINAC) with a 6-MV flattening filter-free (FFF) photon beam, Halcyon, includes a reference beam that contains representative information such as the percent depth dose, profile and output factor for commissioning and quality assurance. However, because it does not provide information about the field size, we proposed a method to determine all field sizes according to all depths for radiation therapy using simplified sigmoidal curve fitting (SCF). METHODS: After mathematical definition of the SCF using four coefficients, the defined curves were fitted to both the reference data (RD) and the measured data (MD). For good agreement between the fitting curve and the profiles in each data set, the field sizes were determined by identifying the maximum point along the third derivative of the fitting curve. The curve fitting included the field sizes for beam profiles of 2 × 2, 4 × 4, 6 × 6, 8 × 8, 10 × 10, 20 × 20 and 28 × 28 cm2 as a function of depth (at 1.3, 5, 10 and 20 cm). The field size results from the RD were compared with the results from the MD using the same condition. RESULTS: All fitting curves show goodness of fit, R2, values that are greater than 0.99. The differences in field size between the RD and the MD were within the range of 0 to 0.2 cm. The smallest difference in the field sizes at a depth of 10 cm, which is a surface-to-axis distance, was reported. CONCLUSION: Application of the SCF method has been proven to accurately capture the field size of the preconfigured RD and the measured FFF photon beam data for the Halcyon system. The current work can be useful for beam commissioning as a countercheck methodology to determine the field size from RD in the treatment planning system of a newly installed Halcyon system and for routine quality assurance to ascertain the correctness of field sizes for clinical use of the Halcyon system.

Quantitative analysis of prompt gamma ray imaging during proton boron fusion therapy according to boron concentration.

The purpose of this study is to evaluate the prompt gamma ray imaging technique according to the clinical boron concentration range during proton boron fusion therapy (PBFT). To acquire a prompt gamma ray image from 32 projections, we simulated four head single photon emission computed tomography and a proton beam nozzle using a Monte Carlo simulation. We used modified ordered subset expectation maximization reconstruction algorithm with a graphic processing unit for fast image acquisition. Boron concentration was set as 20 to 100 µg at intervals of 20 µg. For quantitative analysis of the prompt gamma ray image, we acquired an image profile drawn through two boron uptake regions (BURs) and calculated the contrast value, signal-to-noise ratio (SNR), and difference between the physical target volume and volume of the prompt gamma ray image. The relative counts of prompt gamma rays were noticeably increased with increasing boron concentration. Although the intensities on the image profiles showed a similar tendency according to the boron concentration, the SNR and contrast value were improved with increasing boron concentration. This study suggests that a tumor monitoring technique using prompt gamma ray detection can be clinically applicable even if the boron concentration is relatively low.

Prompt gamma ray imaging for verification of proton boron fusion therapy: A Monte Carlo study.

PURPOSE: The purpose of this study was to verify acquisition feasibility of a single photon emission computed tomography image using prompt gamma rays for proton boron fusion therapy (PBFT) and to confirm an enhanced therapeutic effect of PBFT by comparison with conventional proton therapy without use of boron. METHODS: Monte Carlo simulation was performed to acquire reconstructed image during PBFT. We acquired percentage depth dose (PDD) of the proton beams in a water phantom, energy spectrum of the prompt gamma rays, and tomographic images, including the boron uptake region (BUR; target). The prompt gamma ray image was reconstructed using maximum likelihood expectation maximisation (MLEM) with 64 projection raw data. To verify the reconstructed image, both an image profile and contrast analysis according to the iteration number were conducted. In addition, the physical distance between two BURs in the region of interest of each BUR was measured. RESULTS: The PDD of the proton beam from the water phantom including the BURs shows more efficient than that of conventional proton therapy on tumour region. A 719keV prompt gamma ray peak was clearly observed in the prompt gamma ray energy spectrum. The prompt gamma ray image was reconstructed successfully using 64 projections. Different image profiles including two BURs were acquired from the reconstructed image according to the iteration number. CONCLUSION: We confirmed successful acquisition of a prompt gamma ray image during PBFT. In addition, the quantitative image analysis results showed relatively good performance for further study.

Bioelectrocatalytic detection of glycated hemoglobin (HbA1c) based on the competitive binding of target and signaling glycoproteins to a boronate-modified surface.

We developed an electrochemical glycated hemoglobin (HbA(1c)) biosensor for diagnosing diabetes in whole human blood based on the competitive binding reaction of glycated proteins. Until now, no studies have reported a simple and accurate electrochemical biosensor for the quantification of HbA(1c) in whole blood. This is because it is very difficult to correctly distinguish HbA(1c) from large amounts of hemoglobin and other components in whole blood. To detect glycated hemoglobin, we used electrodes modified with boronic acid, which forms a covalent bond between its diol group and the cis-diol group of the carbohydrate moiety of glycated proteins. For accurate HbA(1c) biosensing, we first removed blood components (except for hemoglobin) such as glycated proteins and blood glucose as they interfere with the boronate-based HbA(1c) competition analysis by reacting with the boronate-modified surface via a cis-diol interaction. After hemoglobin separation, target HbA(1c) and GOx at a predetermined concentration were reacted through a competition onto the boronate-modified electrode, allowing HbA(1c) to be detected linearly within a range of 4.5-15% of the separated hemoglobin sample (HbA(1c)/total hemoglobin). This range covers the required clinical reference range of diabetes mellitus. Hence, the proposed method can be used for measuring %HbA(1c) in whole human blood, and can also be applied to measuring the concentration of various glycated proteins that contain peripheral sugar groups.

Atomic force microscope anodization lithography using pulsed bias voltage synchronized with resonance frequency of cantilever.

An applied bias voltage between the atomic force microscope tip and the substrate is one of the important factors related to the growth of oxide patterns. A pulse modulator was used to apply a pulsed bias voltage that synchronizes with the resonance frequency of the cantilever between the tip and the substrate in tapping mode. The height of the protruded oxide structure was increased for short duration times of the pulsed bias due to the reduction of built-up space charge in oxide. The aspect ratio of patterns using pulsed bias voltage was about two times higher than that using continuous bias voltage. This study revealed that the pulsed bias has an advantage for obtaining a higher aspect ratio pattern than the continuous bias by reducing the effect of space charge in oxide.