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The design and optimization of laser-Compton x-ray systems based on compact distributed charge accelerator structures can enable micron-scale imaging of disease and the concomitant production of beams of Very High Energy Electrons (VHEEs) capable of producing FLASH-relevant dose rates. The physics of laser-Compton x-ray scattering ensures that the scattered x-rays follow exactly the trajectory of the incident electrons, thus providing a route to image-guided, VHEE FLASH radiotherapy. The keys to a compact architecture capable of producing both laser-Compton x-rays and VHEEs are the use of X-band RF accelerator structures which have been demonstrated to operate with over 100 MeV/m acceleration gradients. The operation of these structures in a distributed charge mode in which each radiofrequency (RF) cycle of the drive RF pulse is filled with a low-charge, high-brightness electron bunch is enabled by the illumination of a high-brightness photogun with a train of UV laser pulses synchronized to the frequency of the underlying accelerator system. The UV pulse trains are created by a patented pulse synthesis approach which utilizes the RF clock of the accelerator to phase and amplitude modulate a narrow band continuous wave (CW) seed laser. In this way it is possible to produce up to 10 μA of average beam current from the accelerator. Such high current from a compact accelerator enables production of sufficient x-rays via laser-Compton scattering for clinical imaging and does so from a machine of "clinical" footprint. At the same time, the production of 1000 or greater individual micro-bunches per RF pulse enables > 10 nC of charge to be produced in a macrobunch of < 100 ns. The design, construction, and test of the 100-MeV class prototype system in Irvine, CA is also presented., Competing Interests: CONFLICT OF INTEREST STATEMENT CPJB, JMA, AJA, JCRB, SMB, MMC, RADLL, DAD, HHE, RF, AG, KJG, ASG, FVH, YH, GI, MJ, CAJ, KWK, AL, RJL, MWM, EM, CLN, HJN, KRP, ZRP, MEQ, FR, TR, JS, MES, MWLS, JYY, CBZ, LEZ, and EJZ were employed by Lumitron Technologies, Inc. CPJB holds patents related to the underlying research presented in this work.

Background: Recently, magnetic and inertial measurement units (MIMU) based systems have been applied in the spine mobility assessment; this evaluation is essential in the clinical practice for diagnosis and treatment evaluation. The available systems are limited in the number of sensors, and neither develops a methodology for the correct placement of the sensors, seeking the relevant mobility information of the spine., Methods: This work presents a methodology for analyzing a system consisting of sixteen MIMUs to reduce the amount of information and obtain an optimal configuration that allows distinguishing between different body postures in a movement. Four machine learning algorithms were trained and assessed using data from the range of motion in three movements (Mov.1-Anterior hip flexion; Mov.2-Lateral trunk flexion; Mov.3-Axial trunk rotation) obtained from 12 patients with Ankylosing Spondylitis., Results: The methodology identified the optimal minimal configuration for different movements. The configuration showed good accuracy in discriminating between different body postures. Specifically, it had an accuracy of 0.963 ± 0.021 for detecting when the subject is upright or bending in Mov.1, 0.944 ± 0.038 for identifying when the subject is flexed to the left or right in Mov.2, and 0.852 ± 0.097 for recognizing when the subject is rotated to the right or left in Mov.3., Conclusions: Our results indicate that the methodology developed results in a feasible configuration for practical clinical studies and paves the way for designing specific IMU-based assessment instruments., Trial Registration: Study approved by the Local Ethics Committee of the General Hospital of Mexico "Dr. Eduardo Liceaga" (protocol code DI/03/17/471)., (© 2024. The Author(s).)

Recreating cerebral tissue using a tissue-mimicking phantom is valuable because it provides a tool for studying physiological and biological processes related to tissues without the necessity of performing the study directly in the tissue or even in a patient. The reproduction of the optical properties allows investigation in areas such as imaging, optics, and ultrasound, among others. This paper presents a methodology for manufacturing agarose-based phantoms that mimic the optical characteristics of brain tissue using scattering and absorbing agents and proposes combinations of these agents to recreate the healthy brain tissue optical coefficients within the wavelength range of 350 to 500 nm. The results of the characterization of the manufactured phantoms propose ideal combinations of the used materials for their use in controlled environment experiments in the UV range, following a cost-effective methodology.

Body composition assessment using instruments such as dual X-ray densitometry (DXA) can be complex and their use is often limited to research. This cross-sectional study aimed to develop and validate a densitometric method for fat mass (FM) estimation using 3D cameras. Using two such cameras, stereographic images, and a mesh reconstruction algorithm, 3D models were obtained. The FM estimations were compared using DXA as a reference. In total, 28 adults, with a mean BMI of 24.5 (±3.7) kg/m 2 and mean FM (by DXA) of 19.6 (±5.8) kg, were enrolled. The intraclass correlation coefficient (ICC) for body volume (BV) was 0.98-0.99 (95% CI, 0.97-0.99) for intra-observer and 0.98 (95% CI, 0.96-0.99) for inter-observer reliability. The coefficient of variation for kinetic BV was 0.20 and the mean difference (bias) for BV (liter) between Bod Pod and Kinect was 0.16 (95% CI, -1.2 to 1.6), while the limits of agreement (LoA) were 7.1 to -7.5 L. The mean bias for FM (kg) between DXA and Kinect was -0.29 (95% CI, -2.7 to 2.1), and the LoA was 12.1 to -12.7 kg. The adjusted R 2 obtained using an FM regression model was 0.86. The measurements of this 3D camera-based system aligned with the reference measurements, showing the system's feasibility as a simpler, more economical screening tool than current systems.

Background: With the identification of COVID-19 disease in China, a pandemic began that affected health-care systems. The Neonatal Intensive Care Unit (NICU) of the Hospital de Ginecobstetricia del Centro Médico Nacional de Occidente experienced an increase in patient flow as part of the COVID-19 strategy of the Instituto Mexicano del Seguro Social (IMSS). This study aimed to analyze the impact of the COVID-19 pandemic on neonatal care and mortality indicators in our unit., Methods: We conducted a retrospective study to compare the number of hospital births, pre-term newborns (PTNB), NICU admissions, and deaths. Changes in frequencies between 2019 and 2021 were analyzed using Poisson distribution. Changes in PTNB births, proportion of admissions, and deaths/NICU discharges were analyzed by z-test for two proportions., Results: Between 2019 and 2021, the number of births increased by more than 2-fold. NICU admissions increased from 770 in 2019 to 1045 in 2021 (p < 0.01). The ratio of deaths/discharge from the service was 16.9% in 2019 and 13.1% in 2021 (p = 0.02)., Conclusions: Mortality indicators in the NICU decreased from 2019 to 2021, even with the increase in the number of patients admitted during the COVID-19 pandemic., (Copyright: © 2023 Permanyer.)

Background: Lumbar puncture is an essential medical procedure whose objective is to obtain cerebrospinal fluid. Lumbar puncture is considered a complex procedure, mainly for novice residents who suffer from stress and low confidence, which may result in harm to the patient., Methods: The LPVirSim, has been developed in four stages: i) requirements analysis through user-centred design; ii) prototyping of the virtual environment and the haptic component; iii) preliminary tests with Ph.D. students and physicians using two haptic devices (Omega.7 and Sigma.7); iv) a user study where physicians evaluated the usability and user experience., Results: The LPVirSim integrates non-technical skills and the possibility of representing different patients for training. Usability increased from 61.76 to 68.75 in the preliminary tests to 71.43 in the user study., Conclusions: All the results showed good usability and demonstrated that the simulator arouses interest and realistically represents a Lumbar puncture, through the force and visual feedback., (© 2023 John Wiley & Sons Ltd.)

Synthetic phantoms that recreate the characteristics of biological tissues are valuable tools for systematically studying and comprehending physiologies, pathologies, and biological processes related to tissues. The reproduction of mechanical and optical properties allows for the development and evaluation of novel systems and applications in areas such as imaging, optics, ultrasound, or dosimetry, among others. This paper proposes a methodology for manufacturing agarose-based phantoms that mimics the optical properties of healthy brain tissue within the wavelength infrared range of 800 to 820 nm. The fabrication of such phantoms enables the possibility of testing and experimentation in controlled and safe environments toward the design of new near-infrared multispectral imaging systems in neurosurgery. The results of an experimental optical characterization study indicate the validity and reliability of the proposed method for fabricating brain tissue phantoms in a cost-effective and straightforward fashion.

Background: Ventricular puncture is a common procedure in neurosurgery and the first that resident must learn. Ongoing education is critical to improving patient outcomes. However, training at the expense of potential risk to patients warrants new and safer training methods for residents., Methods: An augmented reality (AR) simulator for the practice of ventricular punctures was designed. It consists of a navigation system with a virtual 3D projection of the anatomy over a 3D-printed patient model. Forty-eight participants from neurosurgery staff performed two free-hand ventricular punctures before and after a training session., Results: Participants achieved enhanced accuracy in reaching the target at the Monro foramen after practicing with the system. Additional metrics revealed significantly better trajectories after the training., Conclusion: The study confirms the feasibility of AR as a training tool. This motivates future work towards standardising new educative methodologies in neurosurgery., (© 2023 The Authors. The International Journal of Medical Robotics and Computer Assisted Surgery published by John Wiley & Sons Ltd.)

The implementation of robotic systems for minimally invasive surgery and medical procedures is an active topic of research in recent years. One of the most common procedures is the palpation of soft tissues to identify their mechanical characteristics. In particular, it is very useful to identify the tissue's stiffness or equivalently its elasticity coefficient. However, this identification relies on the existence of a force sensor or a tactile sensor mounted at the tip of the robot, as well as on measuring the robot velocity. For some applications it would be desirable to identify the biomechanical characteristics of soft tissues without the need for a force/tactile nor velocity sensors. An estimation of such quantities can be obtained by a model-based state observer for which the inputs are only the robot joint positions and its commanded joint torques. The estimated velocities and forces can then be employed for closed-loop force control, force reflection, and mechanical parameters estimation. In this work, a closed-loop force control is proposed based on the estimated contact forces to avoid any tissue damage. Then, the information from the estimated forces and velocities is used in a least squares estimator of the mechanical parameters. Moreover, the estimated biomechanical parameters are employed in a Bayesian classifier to provide further help for the physician to make a diagnosis. We have found that a combination of the parameters of both linear and nonlinear viscoelastic models provide better classification results: 0% misclassifications against 50% when using a linear model, and 3.12% when using only a nonlinear model, for the case in which the samples have very similar mechanical properties.

Spinal mobility assessment is essential for the diagnostic of patients with ankylosing spondylitis. BASMI is a routine clinical evaluation of the spine; its measurements are made with goniometers and tape measures, implying systematic errors, subjectivity, and low sensitivity. Therefore, it is crucial to develop better mobility assessment methods. The design, implementation, and evaluation of a novel system for assessing the entire spine's motion are presented. It consists of 16 magnetic and inertial measurement units (MIMUs) communicated wirelessly with a computer. The system evaluates the patient's movements by implementing a sensor fusion of the triaxial gyroscope, accelerometer, and magnetometer signals using a Kalman filter. Fifteen healthy participants were assessed with the system through six movements involving the entire spine to calculate continuous kinematics and maximum range of motion (RoM). The intrarater reliability was computed over the observed RoM, showing excellent reliability levels (intraclass correlation >0.9) in five of the six movements. The results demonstrate the feasibility of the system for further clinical studies with patients. The system has the potential to improve the BASMI method. To the best of our knowledge, our system involves the highest number of sensors, thus providing more objective information than current similar systems.