Noninvasive Estimation Research Articles

Machine learning approach for noninvasive intracranial pressure estimation using pulsatile cranial expansion waveforms

Noninvasive methods for intracranial pressure (ICP) monitoring have emerged, but none has successfully replaced invasive techniques. This observational study developed and tested a machine learning (ML) model to estimate ICP using waveforms from a cranial extensometer device (brain4care [B4C] System). The model explored multiple waveform parameters to optimize mean ICP estimation. Data from 112 neurocritical patients with acute brain injuries were used, with 92 patients randomly assigned to training and testing, and 20 reserved for independent validation. The ML model achieved a mean absolute error of 3.00 mmHg, with a 95% confidence interval within ±7.5 mmHg. Approximately 72% of estimates from the validation sample were within 0-4 mmHg of invasive ICP values. This proof-of-concept study demonstrates that noninvasive ICP estimation via the B4C System and ML is feasible. Prospective studies are needed to validate the model’s clinical utility across diverse settings.

P0243 Evaluation of liver fibrosis and steatohepatitis associated with metabolic dysfunction (MASH) in patients with inflammatory bowel disease (IBD) and steatotic liver disease associated with metabolic dysfunction (MASLD)

Abstract Background Inflammatory bowel disease (IBD) is associated with a systemic inflammatory state and dysbiosis, which may increase the risk of metabolic dysfunction-associated steatotic liver disease (MASLD). This occurs through intestinal bacterial translocation and the increased entry of lipopolysaccharides, free fatty acids, and other toxins into the liver via the portal circulation. One significant complication of MASLD is metabolic dysfunction-associated steatohepatitis (MASH), which can progress to cirrhosis. This study aimed to evaluate the prevalence of MASLD in IBD patients and assess the frequency of complications, such as MASH and liver fibrosis. Methods The presence of MASLD was based on the presence of NAFLD associated with the metabolic criterion in outpatients with IBD. The presence of NAFLD was confirmed using liver ultrasound. Noninvasive estimate of liver fibrosis (FIB-4) Index and NAFLD Fibrosis Score (NFS) were used as indirect scores of liver fibrosis. Patients with scores greater than NFS > 0.675 and/or FIB-4 > 2.67; and patients with indeterminate or discordant scores were indicated for liver biopsy to quantify liver fibrosis and evaluate MASH. Liver elastography was not performed due to unavailability in our center. Results A total of 179 patients underwent liver ultrasound, with 72 (40.2%) diagnosed with MASLD, including 33 with Crohn’s disease (CD) and 39 with ulcerative colitis (UC). Regarding disease activity, 36.11% were clinically active and 50% were endoscopically active. Biological therapy was used by 54.2% of patients. The degree of steatosis was mild (41.67%), moderate (44.4%) and intense (13.89%). According to the FIB-4 Index, patients were classified as low risk of fibrosis (72.22%), intermediate risk (26.32%) and high risk (1.39%). According to the NFS, the risks for fibrosis were low (53.52%), undetermined (38.08%) and high (8.45%). Sixteen (22.22%) patients underwent liver biopsy, and the presence of fibrosis was observed in 11 (68.75%) patients. The histological stage of fibrosis was F1 (n=6, 54.5%), F2 (n=3, 27,3%), F3 (n=1, 9.1%) and F4 (n=1, 9.1%) according to Kleiner's classification. 4 patients (25%) met criteria for MASH. Conclusion A high prevalence of MASLD was observed in patients with IBD. Among patients with MASLD, we must be aware of the risk of liver fibrosis and MASH. Routine monitoring of liver function and fibrosis, including liver biopsy or elastography when appropriate, is crucial for early detection and management of complications. Due to the lack of routine elastography in our center in Brazil, liver biopsy remains essential for accurate assessment in those patients.

Precision of in vivo pressure gradient estimations using synthetic aperture ultrasound.

Non-invasive estimation of pressure differences using 2D synthetic aperture ultrasound imaging offers a precise, low-cost, and risk-free diagnostic tool. Unlike invasive techniques, this preserves natural blood flow and avoids the limitations of devices that occupy lumen space. This paper evaluates a previously published estimator, modified to incorporate Singular Value Decomposition (SVD) echo-cancellation, using data from ten healthy volunteers and one patient. It is hypothesized that the estimator will enable precise pressure differences from the common carotid artery with a coefficient of variation of approximately 10% over a 10-second data acquisition period. Here, precision is essential to demonstrate the method's consistency and its ability to differentiate between healthy and diseased arteries at the earliest possible stage. Data are acquired using a GE-9L-D, 5.2 MHz linear transducer connected to a Vantage 256 research scanner. The estimator was applied to the left common carotid artery of ten healthy volunteers, with precision being evaluated over the recorded heart cycles by using the coefficient of variation. Eight out of ten individuals showed precision below 10%, whereas two individuals showed precision above 20%. The best precision was attained by subject_03 with a coefficient of variation of 4.64% (16.1 Pa) and the worst precision was attained by subject 09 with a coefficient of variation of 23.3% (30.2 Pa). The average range of pressure differences across volunteers (from maximum positive to maximum negative pressure difference) was 297 Pa when measured across a 14 mm streamline. The corresponding average coefficient of variation was found to be 9.95% (24.6 Pa). A comparison of peak systolic velocities between the experimental scanner and the reference scanner demonstrates a strong positive linear correlation (R2 = 0.76). The corresponding slope of the linear best fit is 0.95, indicating that the relationship between the two scanners is close to a one-to-one match, with the experimental scanner's measurements being slightly less than those of the reference scanner. Finally, data attained from a single patient example shows pressure differences ranging from -61.81 Pa to 1240.82 Pa with blood velocities as high as 1.73 m/s, which is significantly higher than seen in any of the healthy volunteers, supporting the likelihood of differentiating between stenosis grades in future studies. While this study is limited to 10 healthy volunteers and one patient, a different study design is needed to quantify the severity of stenosis and correlate it with pressure differences.

Metrologically Interpretable Soft-Sensing Technique for Non-Invasive Liquid Flow Estimation from Vibration Data

This paper proposes a metrologically interpretable soft sensing method for estimating the liquid flow rates in hydraulic systems from non-invasive vibration frequency power band data. Despite considerable interest in non-invasive flow estimation, state-of-the-art methods provide little to no metrological capabilities. In this work, a dedicated test rig was developed to automatically acquire vibration and flow rate data from a centrifugal pump, in a flow rate range between 0.05 × 10−5m3/s and 9.11 × 10−5m3/s. The vibration data were processed into power bands, which were subsequently used to optimize and train a multilayer perceptron neural network for flow soft sensing. The trained model was compared with models with different vibration processing methods from literature. The power band processing model resulted in a root mean squared error 75.4% smaller than the second-best model in cross-validation, and 51.5% smaller with test data. The uncertainty of the proposed regression model was estimated using a combination of ensemble learning and Monte Carlo simulations, and combined with the reference flow sensor uncertainty to obtain the total combined uncertainty of the soft sensor, found to be between 3.9 × 10−6m3/s and 6.1 × 10−6m3/s throughout the measured flow range. The reference flow sensor accuracy was found to be the largest individual contribution for the final uncertainty, closely followed by the regression model uncertainty.

Analysis of Body Fluid Distribution, Phase Angle and Its Association With Maximal Oxygen Consumption in Facioscapulohumeral Dystrophy: An Observational Study.

Body composition parameters associated with aerobic fitness, mirrored by maximal oxygen consumption (V̇O2max), have recently gained interest as indicators of physical efficiency in facioscapulohumeral dystrophy (FSHD). Bioimpedance analysis (BIA) allows a noninvasive and repeatable estimate of body composition but is based on the use of predictive equations which, if used in cohorts with different characteristics from those for which the equation was originally formulated, could give biased results. Instead, the phase angle (PhA), a BIA raw bioelectrical parameter reflecting body fluids distribution, could provide reliable data for such analysis. 33 clinically and genetically characterized FSHD patients (mean age 35.7; 10 females) and 27 sex and age-matched healthy controls (HC) were included in the analysis. BIA was used to evaluate body fluids distribution (intracellular water [ICW], extracellular water [ECW], and total body water [TBW]), and PhA, while cardiopulmonary exercise test was used to estimate V̇O2max. The groups were comparable for ECW and TBW. Instead, patients showed lower values of ICW (p = 0.020), ICW/ECW ratio (p < 0.001), and PhA (p < 0.001). Moreover, patients reported lower V̇O2max (p = 0.001 for absolute values; p = 0.002 for values expressed in relation to body weight) which, unlike HC, was not associated to PhA. Based on our results, PhA of FSHD patients is lower than HC. Since PhA mirrors the ICW/ECW ratio, the lower share of ICW seems to be the basis of such difference. Given the lack of association with V̇O2max, PhA cannot be considered a reliable indicator of aerobic fitness in FSHD.

Non-Invasive Estimation of Absorbed Ionizing Radiation Dose in Mice Using Near-Infrared Spectroscopy (NIRS) and Aquaphotomics

Non-Invasive Estimation of Absorbed Ionizing Radiation Dose in Mice Using Near-Infrared Spectroscopy (NIRS) and Aquaphotomics

In silico validation of non-invasive arterial compliance estimation and potential determinants of its variability.

Arterial compliance (AC) is an important cardiovascular parameter characterizing mechanical properties of arteries. AC is significantly influenced by arterial wall structure and vasomotion, and it markedly influences cardiac load. A new method, based on a two-element Windkessel model, has been recently proposed for estimating AC as the ratio of the time constant T of the diastolic blood pressure decay and peripheral vascular resistance derived from clinically available stroke volume measurements and selected peripheral blood pressure parameters which are less prone to peripheral distortions. The aim of this study was to validate AC estimation using a virtual population generated by in silico model of the systemic arterial tree. In the second part of study, we analysed causal coupling between AC oscillations and variability of its potential determinants - systolic blood pressure and heart rate in healthy young human subjects. The pool of virtual subjects (n=3818) represented an extensive AC distribution. AC was estimated from the peripheral blood pressure curve and by the standard method from the aortic blood pressure curve. The proposed method slightly overestimated AC set in the model but both ACs were strongly correlated (r=0.94, p<0.001). In real data, we observed that AC dynamics was coupled with basic cardiovascular parameters variability independently of the autonomic nervous system state. In silico analysis suggests that AC can be reliably estimated by noninvasive method. The analysis of short-term AC variability together with its determinants could improve our understanding of factors involved in AC dynamics potentially improving assessment of AC changes associated with atherosclerosis process. Key words Arterial compliance, Cardiovascular model, Arterial blood pressure, Causal analysis, Volume-clamp photoplethysmography.

Noninvasive estimation of PaCO2 from volumetric capnography in animals with injured lungs: an Artificial Intelligence approach.

To investigate the feasibility of non-invasively estimating the arterial partial pressure of carbon dioxide (PaCO2) using a computational Adaptive Neuro-Fuzzy Inference System (ANFIS) model fed by noninvasive volumetric capnography (VCap) parameters. In 14 lung-lavaged pigs, we continuously measured PaCO2 with an optical intravascular catheter and VCap on a breath-by-breath basis. Animals were mechanically ventilated with fixed settings and subjected to 0 to 22 cmH2O of positive end-expiratory pressure steps. The resultant 8599 pairs of data points - one PaCO2 value matched with twelve Vcap and ventilatory parameters derived in one breath - fed the ANFIS model. The data was separated into 7370 data points for training the model (85%) and 1229 for testing (15%). The ANFIS analysis was repeated 10 independent times, randomly mixing the total data points. Bland-Altman plot (accuracy and precision), root mean square error (quality of prediction) and four-quadrant and polar plots concordance indexes (trending ability) between reference and estimated PaCO2 were analyzed. The Bland-Altman plot performed in 10 independent tested ANFIS models showed a mean bias between reference and estimated PaCO2 of 0.03 ± 0.03 mmHg, with limits of agreement of 2.25 ± 0.42 mmHg, and a root mean square error of 1.15 ± 0.06 mmHg. A good trending ability was confirmed by four quadrant and polar plots concordance indexes of 95.5% and 94.3%, respectively. In an animal lung injury model, the Adaptive Neuro-Fuzzy Inference System model fed by noninvasive volumetric capnography parameters can estimate PaCO2 with high accuracy, acceptable precision, and good trending ability.

Noninvasive estimation of central blood pressure through fluid-structure interaction modeling.

Central blood pressure (cBP) is considered a superior indicator of cardiovascular fitness than brachial blood pressure (bBP). Even though bBP is easy to measure noninvasively, it is usually higher than cBP due to pulse wave amplification, characterized by the gradual increase in peak systolic pressure during pulse wave propagation. In this study, we aim to develop an individualized transfer function that can accurately estimate cBP from bBP. We first construct a three-dimensional, patient-specific model of the upper limb arterial system using fluid-structure interaction simulations, incorporating variable material properties and complex boundary conditions. Then, we develop an analytical brachial-aortic transfer function based on novel solutions for compliant vessels. The accuracy of this transfer function is successfully validated against numerical simulation results, which effectively reproduce pulse wave propagation and amplification, with key hemodynamic parameters falling within the range of clinical measurements. Further analysis of the transfer function reveals that cBP is a linear combination of bBP and aortic flow rate in the frequency domain, with the coefficients determined by vessel geometry, material properties, and boundary conditions. Additionally, bBP primarily contributes to the steady component of cBP, while the aortic flow rate is responsible for the pulsatile component. Furthermore, local sensitivity analysis indicates that the lumen radius is the most influential parameter in accurately estimating cBP. Although not directly applicable clinically, the proposed transfer function enhances understanding of the underlying physics-highlighting the importance of aortic flow and lumen radius-and can guide the development of more practical transfer functions.

Commentary: Diagnostic Accuracy of Optic Nerve Sheath Diameter Measurement by Ultrasonography for Noninvasive Estimation of Intracranial Hypertension in Traumatic Brain Injury: Systematic Review and Meta-Analysis.

Commentary: Diagnostic Accuracy of Optic Nerve Sheath Diameter Measurement by Ultrasonography for Noninvasive Estimation of Intracranial Hypertension in Traumatic Brain Injury: Systematic Review and Meta-Analysis.

Novel algorithm for non-invasive estimation of left atrial pressure in patients with atrial fibrillation.

Determining elevated left atrial (LA) pressure is crucial in patients with atrial fibrillation (AF), yet non-invasive estimation using echocardiography remains unclear. This study aimed to identify useful echocardiographic indices for identifying elevated LA pressure in patients with AF. Patients with paroxysmal or persistent AF referred for catheter ablation at two tertiary hospitals were prospectively enrolled. Mean LA pressure was measured immediately after transseptal puncture. Elevated mean LA pressure was defined as ≥15 mmHg. Transthoracic echocardiography was performed to acquire the guideline-recommended parameters. A total of 176 patients were included, and 63 (36%) patients had a mean LA pressure ≥15 mmHg. Patients with elevated LA pressure had more frequent hypertension, larger LA, higher septal E/e', and worse LA strain than the remaining patients. The correlations between mean LA pressure and each echocardiographic parameter were weak. Septal E/e' ratio showed the best correlation with mean LA pressure (r = 0.351, P < 0.001), and septal E/e' ratio ≥11 was the best parameter (area under the curve = 0.7, sensitivity = 65%, specificity = 73%, accuracy = 70%) to identify elevated mean LA pressure. A hierarchical algorithm consisting of septal E/e' ratio, LA reservoir strain, and LA volume index improved identification of patients with elevated mean LA pressure (sensitivity = 61%, specificity = 91%, accuracy = 80%). In patients with AF, the septal E/e' ratio was the best single parameter for identifying elevated mean LA pressure. A hierarchical algorithm combining the septal E/e' ratio, LA reservoir strain, and LA volume index helps identify elevated LA pressure in patients with AF.

Joint quaternion valued features and quaternion valued long short term memory based recurrent neural network for non-invasive blood glucose estimation

For the four channel photoplethysmograms (PPGs), this paper proposes a quaternion valued based method for performing the non-invasive blood glucose estimation. First, these four channel PPGs form a quaternion valued signal. Then, the quaternion valued means and the quaternion valued medians of this quaternion valued PPGs are employed as features. Next, the quaternion valued long short term memory (QLSTM) based recurrent neural network (RNN) is employed for estimating the non-invasive blood glucose values. Unlike the traditional methods based on extracting the features in each channel of the PPGs independently and fusing all the features together in the conventional neural networks, the quaternion valued operations performed on the quaternion valued PPGs only fuse the same features among these four channels together while do not fuse different features among these four channels together. Hence, the physical interpretations of the features preserve. To demonstrate the effectiveness and the robustness of our proposed method, two datasets are evaluated. The computer numerical simulation results show that our proposed method can yield 81.43% and 83.09% of the test data falling in the zone A of the Clark error grid for the test data in the first dataset and in the second dataset, respectively. Also, it can yield the mean absolute relative difference (MARD) at 14.41% and 14.31% for the test data in the first dataset and the second dataset, respectively. This demonstrates the superior performance of our proposed method over the existing methods for the test data in the both datasets.

119 Rapid and noninvasive estimation of human arsenic exposure based on 4-photo-set of the hand and foot photos through artificial intelligence

119 Rapid and noninvasive estimation of human arsenic exposure based on 4-photo-set of the hand and foot photos through artificial intelligence

Blood volume deficit in postural orthostatic tachycardia syndrome assessed by semiautomated carbon monoxide rebreathing

Abstract Purpose The semiautomated carbon monoxide (CO) rebreathing method has been introduced as a noninvasive and radiation-free blood volume estimation method. We tested whether the semiautomated CO rebreathing method can detect the blood volume deficit in postural orthostatic tachycardia syndrome (POTS). In addition, we explored the relationship between blood volume estimated from CO rebreathing and body impedance. Patients and methods We recruited 53 subjects (21 female patients with POTS, 19 healthy female participants, and 13 healthy male participants) to record blood volumes and hemodynamic data. Blood volumes were measured by CO rebreathing and segmental body impedance. Linear regression models to predict normal values of red blood cell volume (RBCV), plasma volume (PV), and total blood volume (BV) were developed. Percentage deviations from the predicted normal volumes were calculated. Results Patients with POTS had lower RBCV (25.18 ± 3.95 versus 28.57 ± 3.68 mL/kg, p = 0.008, patients with POTS versus healthy female participants), BV (64.53 ± 10.02 versus 76.78 ± 10.00 mL/kg, p &lt; 0.001), and BV deviation (−13.92 ± 10.38% versus −0.02 ± 10.18%, p &lt; 0.001). Patients with POTS had higher supine heart rate (HR) (84 ± 14 versus 69 ± 11 bpm, p &lt; 0.001) and upright HR (123 ± 23 versus 89 ± 22 bpm, p &lt; 0.001). We found a correlation between BV deviation and upright HR in patients with POTS (r = −0.608, p = 0.003), but not in healthy participants. Volumes from the CO rebreathing and body impedance were well correlated (r = 0.629, p &lt; 0.001). Conclusions The CO rebreathing method can detect BV deficit, as well as the RBCV deficit in patients with POTS. The negative correlation between BV deviation and upright HR indicates that hypovolemia is one of the pathophysiological causes of POTS. Correlations between body impedance and CO rebreathing volume suggest its usefulness for measurements of volume changes.

Development and Evaluation of Regolith Mass Estimation Sensor Based on Photoresist Effect

This paper presents the design, implementation, and laboratory validation of an optoelectronic-based mass estimation sensor for regolith sampling devices. The sensor integrates multiple photoresistors into the walls of a shovel of a sampling device, where the sensors detect varying levels of light occlusion caused by the deposited regolith. By analyzing the output signals from these photoresistors, the sensor estimates the mass of the sampled regolith. The device is designed to handle a typical sample mass range of 100–300 g. Laboratory tests demonstrated that the sensor can estimate the regolith mass with a relative error of approximately 23%, which is suitable for early-stage applications where rapid, non-invasive mass estimation is essential. The shown level of accuracy underscores the potential for further refining the calibration process, enhancing sensor sensitivity, and integrating multi-sensor approaches to improve performance. This conceptual study highlights the feasibility of using optoelectronic sensors for regolith mass estimation, paving the way for future innovations in ISRU missions and other granular material sampling applications. Future work will focus on the optimization of photoresistor placements, refining the calibration process, and enhancing sensor sensitivity to improve the accuracy of mass estimation.

Abstract 4137465: Estimating Arterial Stiffness Using a Smart Ring and the Impact of HIIT Exercise: A Pilot Study

Introduction: Arterial stiffness is an important marker of cardiovascular health, but measuring it requires specialized equipment and trained personnel. This study aimed to evaluate a novel method for estimating arterial stiffness using photoplethysmography (PPG) signals recorded by a commercially available device (Oura Ring) and to study the impact of a high-intensity interval training (HIIT) intervention on arterial stiffness. Research Questions: 1. Can a smart ring provide accurate estimates of arterial stiffness comparable to the reference device (Sphygmocor)? 2. Does a three-month supervised HIIT cycling protocol reduce arterial stiffness? Aims: 1. Evaluate a PPG-based arterial stiffness estimation method using a smart ring. 2. Assess the efficacy of HIIT in reducing arterial stiffness and improving VO2max. Methods: The study comprised two parts: 1. A cross-sectional study (N=300, age 18-78) for collecting arterial stiffness data using the Sphygmocor and the Smart Ring to evaluate the PPG-based algorithm. 2. A randomized exercise intervention pilot study (N=80, a subset of the cross-sectional study), assigned to either a three-month HIIT protocol or a control group. Arterial stiffness was measured pre- and post-intervention using both devices. Pearson’s correlation coefficients assessed the agreement between the novel method and reference device, and effects of the intervention were analyzed using ANCOVA. Results: The novel PPG-based method demonstrated good correlation with the Sphygmocor device (R = 0.77 and 0.80 in pre- and post-timepoints, respectively). However, despite improving the participants’ aerobic fitness (average increase in VO2max of 1.41 ml/min/kg; 95% CI: [0.15, 2.67], P = 0.029) the HIIT intervention did not significantly improve arterial stiffness, as measured by both methods. Conclusions: The developed smart ring method provides a reliable, non-invasive, and continuous estimation of arterial stiffness. This innovative approach could significantly impact how arterial stiffness is monitored in an everyday setting. The null results of the HIIT intervention suggest that HIIT may not be effective in reducing arterial stiffness, highlighting the need for further research into different exercise modalities for cardiovascular health improvement. This study underscores the potential of wearable technology in cardiovascular health monitoring and the importance of evaluating diverse exercise protocols for arterial health.

Potential of Near-Infrared Optical Techniques for Non-invasive Blood Glucose Measurement: A Pilot Study

BackgroundDiabetes mellitus manifested by escalated blood glucose, demands periodic or continuous glucose monitoring in the pursuit of improved control, optimal management, and appropriate medication. The existing state-of-the-art for blood glucose estimation are invasive methodologies necessitating the acquisition of blood sample through either a finger-stick or venipuncture. MethodsWe propose a dual Near-infrared wavelength integrated in a 3D printed enclosure as the optical prototype for non-invasive glucose estimation. We acquired data from both diabetic and healthy subjects with the developed system and subsequently validated the system. ResultsThe system demonstrated commendable clinical accuracy, as evidenced by the alignment of data pairs representing actual blood glucose levels and blood glucose levels predicted by our optical system within the A+B zones of the Parkes error grid and zones of no-risk and lower risk as defined by the surveillance error grid. We achieved compliant pairs percentage of 95.6%, which satisfies the accuracy requirements of the blood glucose monitoring surveillance study. The mean absolute percentage error attained with the proposed device (5.99%) was significant in predicting the blood glucose. ConclusionWe successfully deployed the NIR wavelengths functionality as the promising approach for glucose monitoring, offering new possibilities for improved medical interventions.

Utilizing retinal arteriole/venule ratio to estimate intracranial pressure

PurposeIntracranial pressure (ICP) control is important to avoid secondary brain injury in patients with intracranial pathologies. Current methods for measuring ICP are invasive and carry risks of infection and hemorrhage. Previously we found correlation between ICP and the arteriole-venous ratio (A/V ratio) of retinal vessels in an outpatient setting. This study investigated the usability of fundoscopy for non-invasive ICP estimation with the addition of intraocular pressure (IOP) in patients in a neuro-intensive care unit (NICU).MethodsThis single-center prospective cohort study was conducted at the NICU of Odense University Hospital from September 2020 to May 2021. Adult patients with a Glasgow Coma Score of 8 or less, who underwent invasive pressure neuromonitoring were included. Fundoscopy videos were captured daily and analyzed using deep learning algorithms. The A/V ratio was calculated and correlated with ICP. The data was analyzed using mixed-effect linear regression models.ResultsForty patients were enrolled. Fifteen were included in the final analysis. ICP ranged from -1 to 31 mmHg (mean: 10.9, SD: 5.7), and IOP ranged from 4 to 13 mmHg (mean: 7.4, SD: 2.1). The A/V ratio showed a significant negative correlation with ICP > 15 mmHg (regression slope: -0.0659, 95%-CI: [-0.0665;-0.0653], p < 0.001). No significant change in A/V ratio was observed for ICP ≤ 15 mmHg. A similar significant correlation was found for ICP > IOP (regression slope: -0.0055, 95%-CI: [-0.0062;-0.0048], p < 0.001). Taking the IOP into account did not improve the model. The sensitivity analysis showed a sensitivity of 80.08% and a specificity of 22.51%, with an AUC of 0.6389.ConclusionIn line with our previous work, non-invasive fundoscopy is a potential tool for detecting elevated ICP. However, challenges such as image quality and diagnostic specificity remains. Further research with larger, multi-center studies are needed to validate the utility. Standardization may enhance the technique's clinical applicability.

Diagnostic Accuracy of Optic Nerve Sheath Diameter Measurement by Ultrasonography for Noninvasive Estimation of Intracranial Hypertension in Traumatic Brain Injury: A Systematic Review and Meta-Analysis.

Intracranial hypertension (IH) is associated with an unfavorable outcome in traumatic brain injury (TBI), and management strategies guided by intracranial pressure monitoring improve prognosis. Owing to the limitations of using invasive devices, measurement of optic nerve sheath diameter (ONSD) by ultrasonography is an alternative noninvasive method. However, its accuracy has not been validated in patients with TBI, so we aim to determine the diagnostic accuracy of measuring ONSD by ultrasonography in patients with TBI to estimate IH, compared with invasive monitoring. Systematic review of electronic databases and manual literature review from inception to June 2023. The analysis included diagnostic accuracy studies of ultrasonographic measurement of ONSD compared with invasive monitoring published in any language and with patients of any age. A qualitative synthesis was performed describing the clinical and methodological characteristics, strengths, limitations, and quality of evidence. In addition, a bivariate random effects model meta-analysis and a hierarchical summary receiver operating characteristics model were performed for the pediatric and adult population separately. Five hundred and forty eight patients of 688 in 16 eligible studies were adults and 120 were children. Pooled sensitivity and specificity of ONSD measurement by ultrasonography were 84% (95% CI, 76%-89%) and 83% (95% CI, 73%-90%), respectively. During the sensitivity analysis, these parameters exhibited consistent values. Pooled area under the curve was 0.91 for adults and 0.76 for children. Optimal threshold for estimating IH was 5.76 mm for adults and 5.78 mm for children. Measurement of ONSD by ultrasonography is a reliable, low-cost, and safe alternative for the estimation of IH with TBI in adults. More robust studies are needed to overcome the high risk of bias and heterogeneity for this analysis.

Noninvasive, epigenetic age estimation in an elasmobranch, the cownose ray (Rhinoptera bonasus)

Age data are essential for estimating life history parameters and are thus critical for population assessment, management, and conservation. Traditional vertebrae-based age estimation in elasmobranchs can be costly, time intensive, of low accuracy, and is by necessity lethal. Herein, epigenetic clocks were developed for an elasmobranch, the cownose ray (Rhinoptera bonasus), using aquarium-born individuals (n = 42) with known dates of birth (age range: 7−7,878 days or 0−21 years) and two tissue types (fin clips and whole blood) that can be sampled in a relatively non-invasive manner. Enzymatically-converted restriction site-associated DNA sequencing (ECrad-seq) was used to identify CpG sites that exhibited age-correlated DNA methylation. The epigenetic clocks developed were highly accurate (mean absolute error, MAE, < 0.75 years) and precise (R2 > 0.98). Age-associated CpG sites were identified across tissues, and a multi-tissue clock was also highly accurate (MAE < 1 year) and precise (R2 = 0.97). Using the developed fin clip clock, three wild-caught individuals of unknown age but managed in aquariums for > 22 years were predicted to be 22.10−23.49 years old. Overall, the results have important implications for future epigenetic clock development and noninvasive age estimation in elasmobranchs.