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PURPOSE: To determine if patient-specific IMRT quality assurance can be measured on any matched treatment delivery system (TDS) for patient treatment delivery on another. METHODS: Three VMAT plans of varying complexity were created for each available energy for head and neck, SBRT lung, and right chestwall anatomical sites. Each plan was delivered on three matched Varian TrueBeam TDSs to the same Scandidos Delta4 Phantom+ diode array with only energy-specific device calibrations. Dose distributions were corrected for TDS output and then compared to TPS calculations using gamma analysis. Round-robin comparisons between measurements from each TDS were also performed using point-by-point dose difference, median dose difference, and the percent of point dose differences within 2% of the mean metrics. RESULTS: All plans had more than 95% of points passing a gamma analysis using 3%/3 mm criteria with global normalization and a 20% threshold when comparing measurements to calculations. The tightest gamma analysis criteria where a plan still passed > 95% were similar across delivery systems-within 0.5%/0.5 mm for all but three plan/energy combinations. Median dose deviations in measurement-to-measurement comparisons were within 0.7% and 1.0% for global and local normalization, respectively. More than 90% of the point differences were within 2%. CONCLUSION: A set of plans spanning available energies and complexity levels were delivered by three matched TDSs. Comparisons to calculations and between measurements showed dose distributions delivered by each TDS using the same DICOM RT-plan file meet tolerances much smaller than typical clinical IMRT QA criteria. This demonstrates each TDS is modeled to a similar accuracy by a common class (shared) beam model. Additionally, it demonstrates that dose distributions from one TDS show small differences in median dose to the others. This is an important validation component of the common beam model approach, allowing for operational improvements in the clinic.

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PURPOSE: Genitoplasty is becoming more and more common, and it is important to improve the accuracy of the procedure and simplify the procedure. This experiment explores the feasibility of using augmented reality (AR) technology combined with PSI titanium plates for navigational assistance in genioplasty performed on models, aiming to study the precision of such surgical interventions. METHODS: Twelve genioplasty procedures were designed and implemented on 3D-printed resin mandibular models by the same surgeon using three different approaches: AR+3DT group (AR+PSI) , 3DT group (patient-specific titanium plate) , and a traditional free-hand group(FH group). Postoperative models were assessed using CBCT to evaluate surgical accuracy. RESULTS: In terms of osteotomy accuracy, the AR group demonstrated a surgical error of 0.9440±0.5441 mm, significantly lower than the control group, which had an error of 1.685±0.8907 mm (P < 0.0001). In experiments positioning the distal segment of the chin, the overall centroid shift in the AR group was 0.3661±0.1360 mm, significantly less than the 2.304±0.9629 mm in the 3DT group and 1.562±0.9799 mm in the FH group (P < 0.0001). Regarding angular error, the AR+3DT group showed 2.825±1.373°, significantly <8.283±3.640° in the 3DT group and 7.234±5.241° in the FH group. CONCLUSION: AR navigation technology combined with PSI titanium plates demonstrates higher surgical accuracy compared to traditional methods and shows feasibility for use. Further validation through clinical trials is necessary.

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BACKGROUND: Pencil Beam Scanning proton therapy has many advantages from a therapeutic point of view, but raises technical constraints in terms of treatment verification. The treatment relies on a large number of planned pencil beams (PB) (up to thousands), whose delivery is divided in several low-intensity pulses delivered a high frequency (1 kHz in this study). PURPOSE: The purpose of this study was to develop a three-dimensional quality assurance system allowing to verify all the PBs' characteristics (position, energy, intensity in terms of delivered monitor unit-MU) of patient treatment plans on a pulse-by-pulse or a PB-by-PB basis. METHODS: A system named SCICOPRO has been developed. It is based on a 10 × 10 × 10 cm3 scintillator cube and a fast camera, synchronized with beam delivery, recording two views (direct and using a mirror) of the scintillation distribution generated by the pulses. A specific calibration and analysis process allowed to extract the characteristics of all the pulses delivered during the treatment, and consequently of all the PBs. The system uncertainties, defined here as average value + standard deviation, were characterized with a customized irradiation plan at different PB intensities (0.02, 0.1, and 1 MU) and with two patient's treatment plans of three beams each. The system's ability to detect potential treatment delivery problems, such as positioning errors of the treatment table in this work (1° rotations and a 2 mm translation), was assessed by calculating the confidence intervals (CI) for the different characteristics and evaluating the proportion of PBs within these intervals. RESULTS: The performances of SCICOPRO were evaluated on a pulse-by-pulse basis. They showed a very good signal-to-noise ratio for all the pulse intensities (between 2 × 10-3 MU and 150 × 10-3 MU) allowing uncertainties smaller than 580 µm for the position, 180 keV for the energy and 3% for the intensity on patients treatment plans. The position and energy uncertainties were found to be little dependent from the pulse intensities whereas the intensity uncertainty depends on the pulses number and intensity distribution. Finally, treatment plans evaluations showed that 98% of the PBs were within the CIs with a nominal positioning against 83% or less with the table positioning errors, thus proving the ability of SCICOPRO to detect this kind of errors. CONCLUSION: The high acquisition rate and the very high sensitivity of the system developed in this work allowed to record pulses of intensities as low as 2 × 10-3 MU. SCICOPRO was thus able to measure all the characteristics of the spots of a treatment (position, energy, intensity) in a single measurement, making it possible to verify their compliance with the treatment plan. SCICOPRO thus proved to be a fast and accurate tool that would be useful for patient-specific quality assurance (PSQA) on a pulse-by-pulse or PB-by-PB verification basis.

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PURPOSE: Deformable image registration (DIR) has been increasingly used in radiation therapy (RT). The accuracy of DIR algorithms and how it impacts on the RT plan dosimetrically were examined in our study for abdominal sites using biomechanically modeled deformations. METHODS: Five pancreatic cancer patients were enrolled in this study. Following the guidelines of AAPM TG-132, a patient-specific quality assurance (QA) workflow was developed to evaluate DIR for the abdomen using the TG-132 recommended virtual simulation software ImSimQA (Shrewsbury, UK). First, the planning CT was deformed to simulate respiratory motion using the embedded biomechanical model in ImSimQA. Additionally, 5 mm translational motion was added to the stomach, duodenum, and small bowel. The original planning CT and the deformed CT were then imported into Eclipse and MIM to perform DIR. The output displacement vector fields (DVFs) were compared with the ground truth from ImSimQA. Furthermore, the original treatment plan was recalculated on the ground-truth deformed CT and the deformed CT (with Eclipse and MIM DVF). The dose errors were calculated on a voxel-to-voxel basis. RESULTS: Data analysis comparing DVF from Eclipse versus MIM show the average mean DVF magnitude errors of 2.8 ± 1.0  versus 1.1 ± 0.7 mm for stomach and duodenum, 5.2 ± 4.0  versus 2.5 ± 1.0 mm for small bowel, and 4.8 ± 4.1  versus 2.7 ± 1.1 mm for the gross tumor volume (GTV), respectively, across all patients. The mean dose error on stomach+duodenum and small bowel were 2.3 ± 0.6% for Eclipse, and 1.0 ± 0.3% for MIM. As the DIR magnitude error increases, the dose error range increase, for both Eclipse and MIM. CONCLUSION: In our study, an initial assessment was conducted to evaluate the accuracy of DIR and its dosimetric impact on radiotherapy. A patient-specific DIR QA workflow was developed for pancreatic cancer patients. This workflow exhibits promising potential for future implementation as a clinical workflow.

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This study aimed to identify and quantify the variations in PSI designs intended for an identical patient. Records from 10 patients with an orbital fracture involving two walls, for which a primary orbital reconstruction was indicated, were retrospectively included. Clinical engineers from two centers independently generated proposal designs for all patients. Following web meeting(s) with the surgeon from the same institute, the PSI designs were finalized by the engineer. A cross-over of the engineer with the surgeon of the other center created two new design teams. In total, 20 proposal and 40 final PSI designs were produced. A three-dimensional comparison between different PSI designs for the same patient was performed by computing a difference score. Initially, the design proposals of the two engineers showed a median difference score of 37%, which was significantly reduced to a median difference score of 26% for the final designs with different engineers. The median difference score of 22% between surgeons demonstrated that both parties introduced notable user variations to the final designs. Evidence supporting the advantages of an experienced design team was found, with significantly fewer modifications, fewer meetings, and less time required to complete the design (up to 40% time reduction). The findings of the study underline the dependency of PSI design on the surgeon and engineer, and support the need for a more evidence-based protocol for PSI design.

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Computational methodologies for predicting the fractional flow reserve (FFR) in coronary arteries with stenosis have gained significant attention due to their potential impact on healthcare outcomes. Coronary artery disease is a leading cause of mortality worldwide, prompting the need for accurate diagnostic and treatment approaches. The use of medical image-based anatomical vascular geometries in computational fluid dynamics (CFD) simulations to evaluate the hemodynamics has emerged as a promising tool in the medical field. This comprehensive review aims to explore the state-of-the-art computational methodologies focusing on the possible considerations. Key aspects include the rheology of blood, boundary conditions, fluid-structure interaction (FSI) between blood and the arterial wall, and multiscale modelling (MM) of stenosis. Through an in-depth analysis of the literature, the goal is to obtain an overview of the major achievements regarding non-invasive methods to compute FFR and to identify existing gaps and challenges that inform further advances in the field. This research has the major objective of improving the current diagnostic capabilities and enhancing patient care in the context of cardiovascular diseases.

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The Ozaki procedure is a surgical technique which avoids to implant foreign aortic valve prostheses in human heart, using the patient's own pericardium. Although this approach has well-identified benefits, it is still a topic of debate in the cardiac surgical community, which prevents its larger use to treat valve pathologies. This is linked to the actual lack of knowledge regarding the dynamics of tissue deformations and surrounding blood flow for this autograft pericardial valve. So far, there is no numerical study examining the coupling between the blood flow characteristics and the Ozaki leaflets dynamics. To fill this gap, we propose here a comprehensive comparison of various performance criteria between a healthy native valve, its pericardium-based counterpart, and a bioprosthetic solution, this is done using a three-dimensional fluid-structure interaction solver. Our findings reveal similar physiological dynamics between the valves but with the emergence of fluttering for the Ozaki leaflets and higher velocity and wall shear stress for the bioprosthetic heart valve.

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PURPOSE: The objective of this study is to validate a novel workflow for implementing patient-specific finite element (FE) simulations to virtually replicate the Transcatheter Aortic Valve Implantation (TAVI) procedure. METHODS: Seven patients undergoing TAVI were enrolled. Patient-specific anatomical models were reconstructed from pre-operative computed tomography (CT) scans and subsequentially discretized, considering the native aortic leaflets and calcifications. Moreover, high-fidelity models of CoreValve Evolut R and Acurate Neo2 valves were built. To determine the most suitable material properties for the two stents, an accurate calibration process was undertaken. This involved conducting crimping simulations and fine-tuning Nitinol parameters to fit experimental force-diameter curves. Subsequently, FE simulations of TAVI procedures were conducted. To validate the reliability of the implemented implantation simulations, qualitative and quantitative comparisons with post-operative clinical data, such as angiographies and CT scans, were performed. RESULTS: For both devices, the simulation curves closely matched the experimental data, indicating successful validation of the valves mechanical behaviour. An accurate qualitative superimposition with both angiographies and CTs was evident, proving the reliability of the simulated implantation. Furthermore, a mean percentage difference of 1,79 ± 0,93 % and 3,67 ± 2,73 % between the simulated and segmented final configurations of the stents was calculated in terms of orifice area and eccentricity, respectively. CONCLUSION: This study shows the successful validation of TAVI simulations in patient-specific anatomies, offering a valuable tool to optimize patients care through personalized pre-operative planning. A systematic approach for the validation is presented, laying the groundwork for enhanced predictive modeling in clinical practice.

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INTRODUCTION: This study conducted a Bayesian network meta-analysis (NMA) to compare the imaging and functional outcomes of patient-specific instrument-assisted unicompartmental knee arthroplasty (P-UKA), robot-assisted unicompartmental knee arthroplasty (R-UKA), and conventional unicompartmental knee arthroplasty (C-UKA). MATERIALS AND METHODS: A comprehensive search was performed on five electronic databases and major orthopedic journals as of September 24, 2023. We included randomized controlled studies featuring at least two interventions of P-UKA, R-UKA, or C-UKA. Primary outcomes encompassed the deviation angle of hip-knee-ankle angle, as well as the coronal and sagittal plane alignment of femoral and tibial components. Secondary outcomes included patient-reported outcome measures (PROM), surgery time, revision rate, and complication rate. Bayesian framework was employed for risk ratio (RR) or mean deviation (MD) analysis, and treatment hierarchy was established based on rank probabilities. RESULTS: This NMA included 871 knees from 12 selected studies. In sagittal plane, R-UKA exhibited a significantly reduced deviation angle of femoral component compared to P-UKA (MD: 4.16, 95% CI: 0.21, 8.07), and of tibial component in comparison to C-UKA (MD: -2.45, 95% CI: -4.20, -0.68). Notably, the surgery time was significantly longer in R-UKA than in C-UKA (MD: 15.98, 95% CI: 3.11, 28.88). However, no significant differences were observed in other outcomes. CONCLUSION: Compared with P-UKA or C-UKA, R-UKA significantly improves the femoral and tibial component alignment in the sagittal plane, although this does not translate into discernible differences in functional outcomes. Comprehensive considerations of economic and learning costs are imperative for the judicious selection of the appropriate procedure.

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Background The purpose of this study is to optimize conservative treatment of distal radius and scaphoid fracture, in terms of comfort, fracture stabilization, and prevention of cast complications. Description of Technique Advances in additive manufacturing have allowed the development of patient-specific anatomical braces (PSABs) which have the potential to fulfill this purpose. Our specific aims were to develop a model of PSAB, adapted to fracture care, to evaluate if this brace would be well tolerated by healthy volunteers and to determine its mechanical properties as compared with conventional methods of wrist immobilization. Materials and Methods Several three-dimensional-printed splint prototypes were designed by mechanical engineers based on surgeons' and hand therapists' clinical expertise. These experimental braces underwent testing in a preclinical study involving 10 healthy volunteers, assessing comfort, satisfaction, and activities. The final prototype was mechanically compared with a conventional cast and a prefabricated splint, testing different closing systems. A mathematical algorithm was created to automatically adapt the final PSAB model to the patient's anatomy. Results The final prototype achieved an overall satisfaction score of 79%, weighing less than 90 g, made from polyamide, and fixed using hook and loop straps. The PSAB stiffness varied between 0.64 and 0.99 Nm/degree, surpassing the performance of both conventional plaster casts and prefabricated splints. Conclusion The final wrist PSAB model, adapted for fracture treatment, is lightweight, comfortable, and provides anatomical contention. It is currently being tested for the treatment of stable distal radius and scaphoid fractures in comparison to conventional plaster cast.

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BACKGROUND: Current research lacks comprehensive investigation into the biomechanical changes in the spinal cord and nerve roots during scoliosis correction. This study employs finite element analysis to extensively explore these biomechanical variations across different Cobb angles, providing valuable insights for clinical treatment. METHODS: A personalized finite element model, incorporating vertebrae, ligaments, spinal cord, and nerve roots, was constructed using engineering software. Forces and displacements were applied to achieve Cobb angle improvements, designating T1/2-T4/5 as the upper segment, T5/6-T8/9 as the middle segment, and T9/10-L1/2 as the lower segment. Simulations under traction, pushing, and traction + torsion conditions were conducted, and biomechanical changes in each spinal cord segment and nerve roots were analyzed. RESULTS: Throughout the scoliosis correction process, the middle spinal cord segment consistently exhibited a risk of injury under various conditions and displacements. The lower spinal cord segment showed no significant injury changes under traction + torsion conditions. In the early correction phase, the upper spinal cord segment demonstrated a risk of injury under all conditions, and the lower spinal cord segment presented a risk of injury under pushing conditions. Traction conditions posed a risk of nerve injury on both sides in the middle and lower segments. Under pushing conditions, there was a risk of nerve injury on both sides in all segments. Traction + torsion conditions implicated a risk of injury to the right nerves in the upper segment, both sides in the middle segment, and the left side in the lower segment. In the later correction stage, there was a risk of injury to the upper spinal cord segment under traction + torsion conditions, the left nerves in the middle segment under traction conditions, and the right nerves in the upper segment under pushing conditions. CONCLUSION: When the correction rate reaches 61-68%, particular attention should be given to the upper-mid spinal cord. Pushing conditions also warrant attention to the lower spinal cord and the nerve roots on both sides of the main thoracic curve. Traction conditions require attention to nerve roots bilaterally in the middle and lower segments, while traction combined with torsion conditions necessitate focus on the right-side nerve roots in the upper segment, both sides in the middle segment, and the left-side nerve roots in the lower segment.

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BACKGROUND: In acetabular fracture surgery, understanding the biomechanical behaviour of fractures and implants is beneficial for clinical decision-making about implant selection and postoperative (early) weightbearing protocols. This study outlines a novel approach for creating finite element models (FEA) from actual clinical cases. Our objectives were to (1) create a detailed semi-automatic three-dimensional FEA of a patient with a transverse posterior wall acetabular fracture and (2) biomechanically compare patient-specific implants with manually bent off-the-shelf implants. METHODS: A computational study was performed in which we developed three finite element models. The models were derived from clinical imaging data of a 20-year-old male with a transverse posterior wall acetabular fracture treated with a patient-specific implant. This implant was designed to fit the patient's anatomy and fracture configuration, allowing for optimal placement and predetermined screw trajectories. The three FEA models included an intact hemipelvis for baseline comparison, one with a fracture fixated with a patient-specific implant, and another with a conventional implant. Two loading conditions were investigated: standing up and peak walking forces. Von Mises stress and displacement patterns in bone, implants and screws were analysed to assess the biomechanical behaviour of fracture fixation with either a patient-specific versus a conventional implant. RESULTS: The finite element models demonstrated that for a transverse posterior wall type fracture, a patient-specific implant resulted in lower peak stresses in the bone (30 MPa and 56 MPa) in standing-up and peak walking scenario, respectively, compared to the conventional implant model (46 MPa and 90 MPa). The results suggested that patient-specific implant could safely withstand standing-up and walking after surgery, with maximum von Mises stresses in the implant of 156 MPa and 371 MPa, respectively. The results from the conventional implant indicate a likelihood of implant failure, with von Mises stresses in the implant (499 MPa and 1000 MPa) exceeding the yield stress of stainless steel. CONCLUSION: This study presents a workflow for conducting finite element analysis of real clinical cases in acetabular fracture surgery. This concept of personalized biomechanical fracture and implant assessment can eventually be applied in clinical settings to guide implant selection, compare conventional implants with innovative patient-specific ones, optimizing implant designs (including shape, size, materials, screw positions), and determine whether immediate full weight-bearing can be safely permitted.

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Background: Patient-specific computer simulation of transcatheter aortic valve implantation (TAVI) predicts the interaction between an implanted device and the surrounding anatomy. In this study, we validated the predictive value of computer simulation for the frame deformation following a Venus-A TAVI implant in patients with pure aortic regurgitation (AR). Furthermore, we used the validated computational model to evaluate the anchoring mechanism within the same cohort. Methods: This was a retrospective study. FEops HEARTguide technology was used to simulate the virtual implantation of a Venus-A valve model in a patient-specific geometry. The predicted frame deformation was quantitatively compared to the postoperative device deformation at multiple levels. The outward forces acting on the frame were extracted for each patient and the total outward force acting around the aortic annular (AA) and sinotubular junction (STJ) planes were recorded. Results: Thirty patients were enrolled in the study with 10 in the migration group and 20 in the non-migration group. The dimensions of the simulated and observed frames had good correlations at Dmax (R2=0.88), Dmin (R2=0.91), perimeter (R2=0.92), and area (R2=0.92). The predicted outward force acting on the frame at the AA level was comparable between the migration and no-migration groups. The predicted outward force acting on the frame at the STJ level was always significantly higher in the migration group than the no migration group at different bandwidths: 3 mm (P=0.002), 5 mm (P=0.005), 10 mm (P=0.002). Conclusions: Patient-specific computer simulation of TAVI accurately predicted frame deformation in Chinese patients with pure AR. The forces at the STJ facilitated stabilization of the device within the aortic root, which might be used as a discriminator to identify patients at risk of device migration prior to intervention.

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Additive manufacturing (AM) allows the creation of customized designs for various medical devices, such as implants, casts, and splints. Amongst other AM technologies, fused filament fabrication (FFF) facilitates the production of intricate geometries that are often unattainable through conventional methods like subtractive manufacturing. This study aimed to develop a methodology for substituting a pathological talus bone with a personalized one created using additive manufacturing. The process involved generating a numerical parametric solid model of the specific anatomical region using computed tomography (CT) scans of the corresponding healthy organ from the patient. The healthy talus served as a mirrored template to replace the defective one. Structural simulation of the model through finite element analysis (FEA) helped compare and select different materials to identify the most suitable one for the replacement bone. The implant was then produced using FFF technology. The developed procedure yielded commendable results. The models maintained high geometric accuracy, while significantly reducing the computational time. PEEK emerged as the optimal material for bone replacement among the considered options and several specimens of talus were successfully printed.

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BACKGROUND AND PURPOSE: Fast and automated generation of treatment plans is desirable for magnetic resonance imaging (MRI)-guided adaptive radiotherapy (MRIgART). This study proposed a novel patient-specific auto-planning method and validated its feasibility in improving the existing online planning workflow. MATERIALS AND METHODS: Data from 40 patients with prostate cancer were collected retrospectively. A patient-specific auto-planning method was proposed to generate adaptive treatment plans. First, a population dose-prediction model (M0) was trained using data from previous patients. Second, a patient-specific model (Mps) was created for each new patient by fine-tuning M0 with the patient's data. Finally, an auto plan was optimized using the parameters derived from the predicted dose distribution by Mps. The auto plans were compared with manual plans in terms of plan quality, efficiency, dosimetric verification, and clinical evaluation. RESULTS: The auto plans improved target coverage, reduced irradiation to the rectum, and provided comparable protection to other organs-at-risk. Target coverage for the planning target volume (+0.61 %, P = 0.023) and clinical target volume 4000 (+1.60 %, P < 0.001) increased. V2900cGy (-1.06 %, P = 0.004) and V1810cGy (-2.49 %, P < 0.001) to the rectal wall and V1810cGy (-2.82 %, P = 0.012) to the rectum were significantly reduced. The auto plans required less planning time (-3.92 min, P = 0.001), monitor units (-46.48, P = 0.003), and delivery time (-0.26 min, P = 0.004), and their gamma pass rates (3 %/2 mm) were higher (+0.47 %, P = 0.014). CONCLUSION: The proposed patient-specific auto-planning method demonstrated a robust level of automation and was able to generate high-quality treatment plans in less time for MRIgART in prostate cancer.

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Background: Repetitive transcranial magnetic stimulation (rTMS) therapy could be improved by more accurate and earlier prediction of response. Latent class mixture (LCMM) and non-linear mixed effects (NLME) modeling have been applied to model the trajectories of antidepressant response (or non-response) to TMS, but it is not known whether such models are useful in predicting clinically meaningful change in symptom severity, i.e. categorical (non)response as opposed to continuous scores. Methods: We compared LCMM and NLME approaches to model the antidepressant response to TMS in a naturalistic sample of 238 patients receiving rTMS for treatment resistant depression, across multiple coils and protocols. We then compared the predictive power of those models. Results: LCMM trajectories were influenced largely by baseline symptom severity, but baseline symptoms provided little predictive power for later antidepressant response. Rather, the optimal LCMM model was a nonlinear two-class model that accounted for baseline symptoms. This model accurately predicted patient response at 4 weeks of treatment (AUC = 0.70, 95% CI = [0.52 - 0.87]), but not before. NLME offered slightly improved predictive performance at 4 weeks of treatment (AUC = 0.76, 95% CI = [0.58 - 0.94], but likewise, not before. Conclusions: In showing the predictive validity of these approaches to model response trajectories to rTMS, we provided preliminary evidence that trajectory modeling could be used to guide future treatment decisions.

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Purpose: Dental reconstruction for patients diagnosed with severe mandibular bone atrophy using common dental implants is a challenging process. In such cases, surgeons may encounter challenges such as insufficient available bone, soft tissue, damage to the inferior alveolar nerve, and even the risk of bone fracture. In this study, a new design concept of mandibular patient-specific implants for severely atrophic ridges followed by finite element evaluation was presented to investigate the mechanical functionality of the concept. Method: The implant is comprised of two modular parts including an inferior border cover and a horseshoe-shaped structure. This horseshoe segment fits into the cover and is then screwed to it using two screws on each side. A 1 mm deflection was applied to a reference point located between the two anterior posts to extract the resulting Von Mises stress distribution in each part and the reaction force on the reference point which corresponds to the chewing force that the patient must apply to deform the horseshoe. This 1 mm gap is a design consideration and critical distance that horseshoe contacts the gingiva and disturbs the alveolar nerve. Results: The results revealed that load was transmitted from the horseshoe to the cover, and there were no stress contours on the body of the mandible. However, stress concentration was observed in screw locations in the mandible, the amount of which was decreased by increasing the number of used screws. In horseshoe, stress concentration values were around 350 MPa, and the measured reaction force on the reference point was just under 200 N. Conclusion: The finite element analysis results showed that this concept would be functional as the minimum load would be transmitted to the mandibular ridge, and since the patients diagnosed with atrophic ridge are not able to apply load to an amount near 200 N, the horseshoe would not contact the gingiva. Also, it is concluded that increasing the number of bone screw fixations would decrease the risk of long-term screw loosening.

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Phalangeal fractures are common, particularly in younger patients, leading to a large economic burden due to higher incident rates among patients of working age. In traumatic cases where the fracture may be unstable, plate fixation has grown in popularity due to its greater construct rigidity. However, these metal plates have increased reoperation rates due to inflammation of the surrounding soft tissue. To overcome these challenges, a novel osteosynthesis platform, AdhFix, has been developed. This method uses a light-curable polymer that can be shaped in situ around traditional metal screws to create a plate-like structure that has been shown to not induce soft tissue adhesions. However, to effectively evaluate any novel osteosynthesis device, the biomechanical environment must first be understood. In this study, the internal loads in a phalangeal plate osteosynthesis were measured under simulated rehabilitation exercises. In a human hand cadaver study, a plastic plate with known biomechanical properties was used to fix a 3 mm osteotomy and each finger was fully flexed to mimic traditional rehabilitation exercises. The displacements of the bone fragments were tracked with a stereographic camera system and coupled with specimen specific finite element (FE) models to calculate the internal loads in the osteosynthesis. Following this, AdhFix patches were created and monotonically tested under similar conditions to determine survival of the novel technique. The internal bending moment in the osteosynthesis was 6.78 ± 1.62 Nmm and none of the AdhFix patches failed under the monotonic rehabilitation exercises. This study demonstrates a method to calculate the internal loads on an osteosynthesis device during non-load bearing exercises and that the novel AdhFix solution did not fail under traditional rehabilitation protocols in this controlled setting. Further studies are required prior to clinical application.

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BACKGROUND: Both Alzheimer's disease (AD) and deliriogenic medications increase the risk of delirium in older adults. This study examined the association between delirium and the subsequent monthly use of anticholinergic, sedative, and opioid medications in the 1 year after delirium in older adults with AD. METHODS: This comparative interrupted time series analysis involved adults (aged 65 years and older) with a diagnosis of AD initiating on cholinesterase inhibitors (ChEIs) based on 2013-2017 Medicare data. Separate patient-level segmented regression models were used for each outcome to evaluate changes in the cumulative anticholinergic burden (CAB), sedative load, and opioid load after the delirium/index event using a 12-month baseline and follow-up period among patients who had a delirium event and those without delirium (control group). Propensity score-based stabilized weights were utilized to balance baseline factors in the delirium and control groups. RESULTS: The study included 80,019 older adults with AD with incident ChEI use; 17.11% had delirium. There was an immediate decline in monthly CAB after the delirium event (mean estimate -0.86, p-value: 0.01) compared to the control group. A similar decline was observed when examining the sedative load (-0.06, p-value: 0.002) after the delirium event. However, there was no decline in opioid load (-0.50, p-value: 0.18). In the long term, CAB (0.13; p-value: <0.0001), sedative load (0.01; p-value: <0.001), and opioid load (0.07; p-value: 0.006) increased over the 1-year post-delirium period in the delirium group compared to those without delirium. CONCLUSION: This study found the burden of deliriogenic medications over the 1-year follow-up showed increasing trends in older adults with AD, even though there was some level shift in CAB and sedative load after the delirium event.