Conventional Parameters Research Articles

Adaptive unscented Kalman filter methods for identifying time‐variant parameters via state covariance re‐updating

AbstractThe conventional parameter identification process generally assumes that parameters remain constant. However, under extreme loading conditions, structures may exhibit nonlinear behavior, and parameters could demonstrate time‐variant characteristics. The unscented Kalman filter (UKF), as an efficient online recursive estimator, is widely used for identifying parameters of nonlinear systems. Nevertheless, it exhibits limitations when attempting to identify time‐variant parameters. To address this issue, this paper proposes a covariance matching technique that produces an array of adaptive UKF algorithms. Firstly, the sensitivity parameter η is defined to identify the instant when the parameter change occurs, and its threshold is calculated based on the sensitivity parameter time history curve. Secondly, an adaptive forgetting factor is introduced to simultaneously update the innovation, cross, and state covariance matrices when the kth‐step sensitive parameter surpasses the threshold. Finally, a secondary correction forgetting factor (SCFF) is employed to further re‐update the state covariance values at the identified damage locations. This creative step enhances the adaptive capability and optimizes the identification accuracy of the proposed algorithms. Both the numerical simulations and shaking table test demonstrate that the proposed adaptive algorithms can efficiently identify the time‐variant stiffness‐type parameters, and accurately capture their time‐variant characteristics.

Impact of Antioxidants on Conventional and Advanced Sperm Function Parameters: An Updated Review.

Antioxidants include diverse exogenous and endogenouscompounds that can neutralize free radical activity, which ultimately protects sperm from oxidative stress (OS). Nevertheless, a controlled balance between oxidation and reduction is of paramount importance for cellular function. Excessive use of antioxidants should be avoided. A combination of antioxidants has been utilized to obtain a synergetic effect in the treatment of male infertility. Antioxidants have been shown to have a positive effect on semen parameters with a decrease in DNA damage. Future large randomized controlled trials are needed to determine the real impact of antioxidants on semen parameters, reproductive outcomes, and DNA integrity.

Left Atrial Strain in Multisystem Inflammatory Syndrome in Children and Associations with Systemic Inflammation and Cardiac Injury.

Multisystem inflammatory syndrome in children (MIS-C) commonly involves cardiac injury with both systolic and diastolic dysfunction. Left atrial strain (LAS) detects subclinical diastolic dysfunction in adults but is infrequently used in children. We evaluated LAS in MIS-C and the associations with systemic inflammation and cardiac injury. In this retrospective cohort study, LAS parameters [reservoir (LAS-r), conduit (LAS-cd), and contractile (LAS-ct)] obtained from admission echocardiograms of MIS-C patients were compared to healthy controls and between MIS-C patients with and without cardiac injury (BNP > 500pg/ml or troponin-I > 0.04ng/ml). Correlation and logistic regression analyses were performed to assess LAS associations with admission inflammatory and cardiac biomarkers. Reliability testing was performed. We identified 118 patients with MIS-C and 20 healthy controls. Median LAS parameters were reduced in MIS-C patients compared to controls (LAS-r: 31.8 vs. 43.1%, p < 0.001; LAS-cd: -28.8 vs. -34.5%, p = 0.006; LAS-ct: -5.2 vs. -9.3%, p < 0.001) and reduced in MIS-C patients with cardiac injury (n = 59) compared to no injury (n = 59) (LAS-r: 29.6 vs. 35.8%, p = 0.001; LAS-cd: -26.5 vs. -30.4%, p = 0.036; LAS-ct: -4.6 vs. -9.3%, p = 0.008). A discrete LAS-ct peak was absent in 65 (55%) MIS-C patients but present in all controls (p < 0.001). Procalcitonin correlated strongly with averaged E/e' (r = 0.55, p = 0.001). Moderate correlations were found for ESR and LAS-ct (r = -0.41, p = 0.007) as well as BNP and LAS-r (r = -0.39, p < 0.001) and LAS-ct (r = 0.31, p = 0.023). Troponin-I had only weak correlations. Intra-rater reliability was good for all LAS parameters, and inter-rater reliability was good to excellent for LAS-r, and fair for LAS-cd and LAS-ct. LAS analysis, particularly the absence of a LAS-ct peak, was reproducible and may be superior to conventional echocardiographic parameters for detecting diastolic dysfunction in MIS-C. No strain parameters on admission were independently associated with cardiac injury.

Study on Improved Computed Tomography Scanning Parameters for Patients with Nasal Bone Fracture Based on ITK Three-dimensional Labelling.

To investigate the influence of improved exposure parameters on the image quality of multi-slice spiral computed tomography in nasal bone fracture imaging. Fifty patients with optimised parameters combined with coronal scanning were allocated to the modified group and 50 patients with routine scanning parameters to the routine group. The image quality and nasal bone display of the two groups were assessed and statistically analysed, and the quality of scanned images before and after parameter optimisation was compared. The optimised image quality was better than that of conventional scanning parameters. The parameters used were 120 kv, 180 mA, a layer thickness of 0.625 mm, a layer spacing of 0.312 mm, a pitch of 0.516:1, a frame speed of 1 s, a scanning field of 12 cm and a reconstructed layer thickness for scanning of 0.625 mm; the scanned image was clear, and the parameter optimisation was achieved. This ensures that the annotation data in ITK labelling is more accurate. The optimised parameters and scanned coronal plane show the nasal bone and its surrounding structures more comprehensively, which is of high diagnostic value for nasal bone fractures. The three-dimensional annotation data based on ITK is more standardised, laying a foundation for the subsequent research of artificial intelligence modelling.

Predicting residual pressure gradients after balloon angioplasty in patients with femoropopliteal artery lesions.

In endovascular therapy (EVT) for femoropopliteal artery (FPA) lesions, studies examining the relationship between lesion morphology and hemodynamic status are limited. The purpose of this study was to investigate FPA lesion characteristics, including imaging findings and their cutoff values that can predict hemodynamic significance after balloon angioplasty. This single-center retrospective study enrolled 50 de novo FPA lesions from 43 patients treated under intravascular ultrasound (IVUS) usage between June 2022 and March 2023. As a physiological parameter, the pressure gradient was measured, and the cutoff value of the residual pressure gradient (RPG) was defined as a systolic pressure > 10mmHg through the lesions after balloon angioplasty. The pressure gradients were measured using a 0.014-inch wire-guided, rapid exchange-type microcatheter, Navvus II (Acist, Eden Prairie, Minnesota, USA). Predictive risk factors for RPG were analyzed using the random forest (RF) method. The relationship between the variables, RPG, and the cutoff points of each predictor was assessed using the partial dependence plot (PDP) method. RPG was observed in 20% of the lesions after balloon angioplasty. The RF model revealed that the percent diameter stenosis (%DS) and minimum lumen area (MLA) on IVUS assessment were strong predictive factors for RPG after balloon angioplasty. The PDP model revealed that a higher %DS (cutoff 30%) and smaller MLA (cutoff 10 mm2) could predict RPG after balloon angioplasty. Conventional lesion parameters such as %DS and MLA can predict hemodynamic significance during EVT for FPA lesions.

Research on the influence factors of hydraulic oscillator on drag reduction efficiency in horizontal well drilling

The application of hydraulic oscillator can solve the problems of large friction and serious pressure support in the drilling process of extended reach well and long horizontal well, but the conventional hydraulic oscillator parameter setting is not reasonable, high pressure consumption, easy to make the ground machine pump overload operation and failure. Therefore, based on the LuGre dynamic friction model theory, a calculation model for the friction between drill string and rock wall under the condition of longitudinal oscillation is established, and the influence law of hydraulic oscillator oscillation parameters on drag reduction efficiency is studied. The results show that the change of oscillation intensity, oscillation frequency and oscillation amplitude can improve the drag reduction efficiency, and the increase trend of drag reduction efficiency is first increased and then decreased. The selection of each parameter has the optimal value. According to the analysis of orthogonal test results, it is found that the reduction degree of friction between drill string and borehole wall rock by each parameter is in the order of oscillation intensity, oscillation frequency and oscillation amplitude from the largest to the smallest.

Textural and Conventional Pretherapeutic [18F]FDG PET/CT Parameters for Survival Outcome Prediction in Stage III and IV Oropharyngeal Cancer Patients

Evidence is emerging about the value of textural features as powerful outcome predictors in cancer lesions. The aim of this study is to evaluate the potential of [18F]FDG PET/CT conventional and textural parameters as survival predictors in patients with stage III and IV oropharyngeal cancer. The database includes 39 patients. Segmentation of the primary lesions was performed. A total of 48 features were extracted, comprising conventional parameters and textural features. A 2-year follow-up period to analyze the Overall Survival (OS) and Relapse-Free Survival (RFS) rates was defined. Kaplan–Meier and Cox proportional hazards regression analyses were computed. Higher TLG (p = 0.001) and Surface (p = 0.001) are significantly related to better OS in Cox regression analysis after multiple-testing correction. Higher GLZLM_ZLNU (p = 0.001) is significantly related to greater relapse rates in RFS Kaplan–Meier analysis after multiple-testing correction. Quantitative [18F]FDG PET/CT image features, especially the TLG, have been confirmed as predictors of OS and RFS. Textural features, such as GLZLM_ZLNU, demonstrated a potential predictive value for the OS and RFS of the patients. RFS analysis suggest stabilization of patients adhering to the treatment, showing no relapse events after 20 months of follow-up. [18F]FDG PET/CT is a useful tool for predicting prognosis after chemoradiation therapy of oropharyngeal cancer patients.

Hydrogeochemical investigation of irrigation water in the vicinity of metallic ore deposits in Kiraz‐İzmir, Turkey: Understanding the crucial nexus between “geology and food safety”

AbstractThe increasing drought due to climate change poses a threat to issues such as safe and accessible drinking water, food safety, and protection from diseases. The provision of water supply is vital for agricultural and livestock activities, which are commonly practiced around natural ore deposits. Examining traditional “irrigation water quality” methods alone is insufficient; investigating potentially toxic metal content in the region's waters is vital, especially around metallic ore deposits. This study focused on the Kiraz district in Turkey, known for its agricultural activities, to assess the impact of geogenic water pollution on irrigation water quality and its implications for food safety and human health. Geology determines nutrient availability, water resources, and land suitability for agriculture. Conventional irrigation water quality parameters indicate groundwater suitability for irrigation in the study area, considering Na%, sodium adsorption ratio, residual sodium carbonate, permeability index, Kelly ratio, magnesium hazard, and potential salinity. However, when examining the potential toxic metal content in the region, it was determined that the values of Al ranged from 96 to 8676 ppb, Ni values ranged from 27 to 360 ppb, and Sb concentrations varied between 9 and 53 432 ppb. Utilizing geogenically contaminated water for irrigation and its indiscriminate use in livestock, dairy, and food industries can lead to foodborne illnesses (cancer, endocrine disruptors, tuberculosis, antimony spots, thyroid tumors, goiter, neurologic and cardiovascular diseases) that endanger human health. The use of low‐quality water throughout the agricultural sector and food production chain increases food safety risks.

Impact of interstitial lung disease on left ventricular myocardial function.

Interstitial lung disease (ILD) comprises a wide variety of pulmonary parenchymal disorders within which progressive fibrosing ILD (PF-ILD) constitutes a phenotypic subset. By use of speckle tracking-based strain analysis we aimed to evaluate the degree of left ventricular (LV) dysfunction in progressive vs. non-progressive fibrosing ILD (non-PF-ILD). A total of 99 ILD patients (mean age 63.7 ± 13.5 years, 37.4% female), composed of 50 PF-ILD and 49 non-PF-ILD patients, and 33 controls were prospectively enrolled and underwent conventional and speckle tracking echocardiography. Additional laboratory and pulmonary function testing, as well as six-minute walk test were performed. As compared to the non-PF-ILD cohort, PF-ILD patients exhibited a significantly impaired forced vital capacity (2.4 ± 1.0l vs. 3.1 ± 0.9l, p = 0.002), diffusion capacity for carbon monoxide (DLCO, 25.6 ± 16.3% predicted vs. 43.6 ± 16.67% predicted, p <0.001) and exercise capacity response as measured by the six-minute walk test distance (268.1 ± 178.2m vs. 432.6 ± 94.2m, p <0.001). Contrary to conventional echocardiographic LV parameters, both regional and global longitudinal LV strain measurements were significantly altered in ILD patients as compared to controls. No differences in LV strain were found between both patient groups. Significant correlations were observed between global longitudinal strain, on the one hand, and systemic inflammation markers, total lung capacity (TLC) and DLCO, on the other hand (high-sensitivity C-reactive protein: Pearson´s r = -0.30, p< 0.001; interleukin-6: Pearson´s r = -0.26, p = 0.007; TLC % predicted: Pearson´s r = 0.22, p = 0.02; DLCO % predicted: Pearson´s r = 0.21, p = 0.02). ILD is accompanied by LV dysfunction. LV functionality inversely correlates with the severity of the restrictive ventilatory defect and inflammation marker levels. These observations support the assumption of persistent low-grade systemic inflammation that may link systemic cardiovascular function to ILD status.

The importance of speckle tracking echocardiography in the evaluation of cardiac functions in patients with rheumatoid arthritis

Objectives: In this study, we aimed to analyze the layer-specific strain values obtained by speckle tracking echocardiography (STE) method in the determination of subclinical cardiac dysfunction in rheumatoid arthritis (RA) patients. Patients and methods: Between February 2019 and October 2019, a total of 63 female RA patients (mean age: 51.82±6.07 years; range, 40 and 65 years) who had a confirmed diagnosis were included. Thirty-one age-matched female healthy individuals (mean age: 50.71±5.37 years; range, 40 and 65 years) were selected as the control group. The patients were divided into three groups according to the duration of disease as &lt;5 years, 5-10 years and &gt;10 years. The Disease Activity Score in 28 joint - C-reactive protein (CRP) was used to determine disease activation. The standard assessment included complete serum CRP, anti-cyclic citrullinated peptide, rheumatoid factor, N-terminal pro B-type natriuretic peptide (NT-proBNP), and homocysteine. Global longitudinal strain (GLS) analysis was performed with STE. Results: The NT-proBNP values were found to be higher in RA patients compared to the control group (p=0.044). In terms of conventional echocardiographic parameters, a significant difference between E/A and E/E’ ratios was observed (p&lt;0.001 and p=0.015). Endocardium, transmural, and epicardium GLS values obtained by STE were found to be lower in RA patients (p&lt;0.05). The left ventricular (LV) GLS values worsened, as the duration of disease increased (p&lt;0.05). There was a significant correlation between RA disease activity and LV GLS values, showing that increasing levels of disease activity was associated with worse LV GLS (r=0.583, p&lt;0.01 and r=0.681, p&lt;0.01 and r=0.689, p&lt;0.01 for endocardium, transmural and epicardium, respectively). Conclusion: Our study results suggest that the layer-specific GLS values obtained by STE decrease in RA patients.

Body mass index's effect on CRSwNP extends to pathological endotype and recurrence.

Elevated body mass index (BMI) has been recognized as an important contributor to corticosteroid insensitivity in chronic rhinosinusitis with nasal polyps (CRSwNP). We aimed to delineate the effects of elevated BMI on immunological endotype and recurrence in CRSwNP individuals. A total of 325 patients with CRSwNP undergoing FESS were recruited and stratified by BMI. H&E staining was employed for histological evaluation. Characteristics of inflammatory patterns were identified by immunohistochemical staining. The predictive factors for recurrence were determined and evaluated by multivariable logistic regression analysis and the receiver operating characteristic (ROC) curves across all subjects and by weight group. In all patients with CRSwNP, 26.15% subjects were classified as overweight/obese group across BMI categories and exhibited a higher symptom burden. The upregulated eosinophil/neutrophil-dominant cellular endotype and amplified type 2/ type 3 coexisting inflammation was present in overweight/obese compared to underweight/normal weight controls. Additionally, a higher recurrent proportion was shown in overweight/obese patients than that in underweight/normal weight cohorts. Multivariable logistic regression analysis identified BMI as an independent predictor for recurrence. The predictive capacity of each conventional parameter (tissue eosinophil and CLCs count, and blood eosinophil percentage) alone or in combination was poor in overweight/obese subjects. Overweight/obese CRSwNP stands for a unique phenotype and endotype. Conventional parameters predicting recurrence are compromised in overweight/obese CRSwNP, and there is an urgent need for novel biomarkers that predict recurrence for these patients.

ECG-only explainable deep learning algorithm predicts the risk for malignant ventricular arrhythmia in phospholamban cardiomyopathy

BackgroundPhospholamban (PLN) p.(Arg14del) variant carriers are at risk for development of malignant ventricular arrhythmia (MVA). Accurate risk stratification allows timely implantation of intracardiac defibrillators and is currently performed with a multimodality prediction model. ObjectiveThis study aimed to investigate whether an explainable deep learning–based approach allows risk prediction with only electrocardiogram (ECG) data. MethodsA total of 679 PLN p.(Arg14del) carriers without MVA at baseline were identified. A deep learning–based variational auto-encoder, trained on 1.1 million ECGs, was used to convert the 12-lead baseline ECG into its FactorECG, a compressed version of the ECG that summarizes it into 32 explainable factors. Prediction models were developed by Cox regression. ResultsThe deep learning–based ECG-only approach was able to predict MVA with a C statistic of 0.79 (95% CI, 0.76–0.83), comparable to the current prediction model (C statistic, 0.83 [95% CI, 0.79–0.88]; P = .054) and outperforming a model based on conventional ECG parameters (low-voltage ECG and negative T waves; C statistic, 0.65 [95% CI, 0.58–0.73]; P < .001). Clinical simulations showed that a 2-step approach, with ECG-only screening followed by a full workup, resulted in 60% less additional diagnostics while outperforming the multimodal prediction model in all patients. A visualization tool was created to provide interactive visualizations (https://pln.ecgx.ai). ConclusionOur deep learning–based algorithm based on ECG data only accurately predicts the occurrence of MVA in PLN p.(Arg14del) carriers, enabling more efficient stratification of patients who need additional diagnostic testing and follow-up.

Comparison of whole slide image–based deep learning algorithms and genomic classifiers for assessing the risk of prostate cancer metastasis in surgically treated patients.

344 Background: Genomic classifiers improve post-radical prostatectomy (RP) risk stratification compared to conventional clinical-pathologic parameters, but are tissue-destructive and expensive. In contrast, artificial intelligence algorithms utilizing diagnostic hematoxylin and eosin (H&amp;E)-stained slides for risk stratification conserve tissue and could be made widely available at point-of-care. We compared the predictive output of a deep learning-based algorithm applied to H&amp;E-stained whole slide images (WSI) of prostate tumors to commercial genomic classifiers such as Decipher and Prolaris in three diverse RP cohorts with follow-up for metastasis. Methods: We used subsets of three previously published Johns Hopkins RP cohorts with available genomic classifier data. The Natural History Cohort (n=249, Decipher test, PMID: 26058959) and Case-Cohort (n=210, Prolaris CCP test, PMID: 36006048) both utilized a case-cohort design on the outcome of metastasis and consisted of predominantly self-identified White patients, while the Race Cohort (n=93, Decipher test, PMID: 31969336) included only self-identified Black patients with clinical follow-up. For each cohort, a single representative H&amp;E-stained slide from the dominant tumor nodule at RP was scanned. The DL algorithm utilized tumor detection in H&amp;E-stained WSI followed by a classification model to predict metastasis, with or without clinical parameters (age, race, pre-operative PSA, pathologic T- and N-stage, and margin status). The algorithm was trained (n=197) and validated (n=52) on patients from Natural History Cohort and tested on the Race Cohort and Case-Cohort. Harrell’s C-indices based on unadjusted Cox models for time to metastasis were evaluated. Results: The C-index for the WSI-based deep learning algorithm on the Natural History Cohort validation subset was 0.766 (95% confidence interval [CI]: 0.730-0.802) compared to 0.732 (95% CI:0.698-0.766) for the Decipher score. The C-index for WSI-based deep learning algorithm in the Race Cohort was 0.804 (95% CI: 0.790-0.818) compared to 0.724 (95% CI: 0.721-0.726) for the Decipher score. The C-index for the WSI-based deep learning algorithm in the Case-Cohort was 0.840 (95% CI: 0.829-0.851) compared to 0.801 (95% CI: 0.800-0.802) for the Prolaris CCP score. The C-index values for the deep learning algorithm utilizing WSI plus clinical-pathologic parameters were 0.836 (95% CI: 0.796-0.876), 0.882 (95% CI: 0.869-0.894), and 0.890 (95% CI: 0.878-0.901) for the Natural History Cohort, Race-Cohort, and Case-Cohort, respectively. Conclusions: DL algorithms utilizing WSI with or without clinical-pathologic parameters outperform currently employed genomic classifiers for the prediction of metastasis. Validation in additional multi-institutional and racially diverse cohorts is underway.

Prognostic Value of Immune Cells Subsets Within the Tumor Microenvironment in Patients With Rectal Adenocarcinoma.

One-third of newly diagnosed colorectal cancer cases are rectal cancers. Multimodal treatment regimens including surgery, radiotherapy, and chemotherapy improve local control and survival outcome and decrease tumor relapse for patients with rectal adenocarcinoma (READ). However, stratification of patients to predict their responses is urgently needed to improve therapeutic responses. Immunostainings of CD3+, CD8+, and CD45RO+ immune cell subsets within the tumor microenvironment were evaluated using immunohistochemistry in two hundred seventy-nine READ patients. In this study, we found that examination of the adaptive immune response by quantifying CD3+, CD8+, and CD45RO+ immune cell subsets, provides improved and independent prognostic value for patients with READ. Regardless of conventional clinical and pathologic parameters, the densities of T cell subsets were strongly related to a better prognosis in patients with READ. High density of intratumoral immune cells is associated with absence of nodal metastasis, lymphovascular invasion, and perineural invasion. Moreover, high tumor-infiltrating lymphocyte (TIL) subsets were associated with favorable survival outcome in patients with READ, especially high-risk patients with advanced READ. Immune cell subsets including CD3, CD8, and CD45RO within the tumor microenvironment were independent prognostic factors for patients with READ.

Research on motor speed control based on the improved genetic algorithm to optimize fuzzy PID

This study aims to optimize the speed control effect of fuzzy PID controller in brushless DC motor control, and improve the traditional genetic optimization algorithm to improve fuzzy PID algorithm, mainly for genetic algorithm coding, crossover, and mutation process. In the three processes of the genetic algorithm, real number field coding is used, Taguchi orthogonal table is introduced into the cross-process, and Gaussian variation is applied to the mutation process. In the part of model construction and verification, this study uses Simulink software to build a brushless DC motor model and sets the same conventional parameters for simulation. The simulation results show that the algorithm overshoot and stability time of the fuzzy PID controller optimized by the improved genetic algorithm are obviously improved.

Predicting radiation pneumonitis in lung cancer: a EUD-based machine learning approach for volumetric modulated arc therapy patients.

This study aims to develop an optimal machine learning model that uses lung equivalent uniform dose (lung EUD to predict radiation pneumonitis (RP) occurrence in lung cancer patients treated with volumetric modulated arc therapy (VMAT). We analyzed a cohort of 77 patients diagnosed with locally advanced squamous cell lung cancer (LASCLC) receiving concurrent chemoradiotherapy with VMAT. Patients were categorized based on the onset of grade II or higher radiation pneumonitis (RP 2+). Dose volume histogram data, extracted from the treatment planning system, were used to compute the lung EUD values for both groups using a specialized numerical analysis code. We identified the parameter α, representing the most significant relative difference in lung EUD between the two groups. The predictive potential of variables for RP2+, including physical dose metrics, lung EUD, normal tissue complication probability (NTCP) from the Lyman-Kutcher-Burman (LKB) model, and lung EUD-calibrated NTCP for affected and whole lung, underwent both univariate and multivariate analyses. Relevant variables were then employed as inputs for machine learning models: multiple logistic regression (MLR), support vector machine (SVM), decision tree (DT), and K-nearest neighbor (KNN). Each model's performance was gauged using the area under the curve (AUC), determining the best-performing model. The optimal α-value for lung EUD was 0.3, maximizing the relative lung EUD difference between the RP 2+ and non-RP 2+ groups. A strong correlation coefficient of 0.929 (P< 0.01) was observed between lung EUD (α = 0.3) and physical dose metrics. When examining predictive capabilities, lung EUD-based NTCP for the affected lung (AUC: 0.862) and whole lung (AUC: 0.815) surpassed LKB-based NTCP for the respective lungs. The decision tree (DT) model using lung EUD-based predictors emerged as the superior model, achieving an AUC of 0.98 in both training and validation datasets. The likelihood of developing RP 2+ has shown a significant correlation with the advancements in RT technology. From traditional 3-D conformal RT, lung cancer treatment methodologies have transitioned to sophisticated techniques like static IMRT. Accurately deriving such a dose-effect relationship through NTCP modeling of RP incidence is statistically challenging due to the increased number of degrees-of-freedom. To the best of our knowledge, many studies have not clarified the rationale behind setting the α-value to 0.99 or 1, despite the closely aligned calculated lung EUD and lung mean dose MLD. Perfect independence among variables is rarely achievable in real-world scenarios. Four prominent machine learning algorithms were used to devise our prediction models. The inclusion of lung EUD-based factors substantially enhanced their predictive performance for RP 2+. Our results advocate for the decision tree model with lung EUD-based predictors as the optimal prediction tool for VMAT-treated lung cancer patients. Which could replace conventional dosimetric parameters, potentially simplifying complex neural network structures in prediction models.

Evaluation of Ultrasonography with Conventional Clinical Parameters for Predicting Difficult Laryngoscopy

Background: Unanticipated difficult intubation poses a challenge in routine practice for anaesthesiologists. A preoperative airway evaluation helps in the identification of a difficult airway. Airway assessment with ultrasound is a modality recently being used to predict difficult airway. In this study we evaluate ultrasonography parameters with conventional clinical parameters for predicting difficult airway in adults undergoing elective surgeries.&#x0D; Methods: This cross sectional randomised clinical trial analyses ASA class 1 and 2 adults requiring endotracheal intubation for surgeries under general anaesthesia were enrolled following which Modified Mallampatti score and thyromental distance as well as ultrasound distance to epiglottis (DSE) and distance to hyoid bone (DSHB) were measured and based on Cormack Lehane grading they were categorised into easy and difficult airway groups.&#x0D; Results: DSE had the highest sensitivity of 90.48% whereas Modified Mallampatti grading had least sensitivity of 66.67%.&#x0D; Conclusion: The results of this study showed that ultrasonographic measurements at the thyrohyoid and hyoid level have higher sensitivity and specificity than the clinical parameters for airway assessment.

Longitudinal Changes of Cornea Volume Measured by Means of Anterior Segment-Optical Coherence Tomography in Patients with Stable and Progressive Keratoconus.

Keratoconus is a corneal disease which results in progressive thinning and protrusion of the cornea leading to irregular astigmatism. The purpose of this study was to evaluate longitudinal changes in corneal volume (CV) occurring over time in keratoconus eyes. Consecutive patients affected by keratoconus were evaluated by means of anterior segment-optical coherence tomography (AS-OCT) at two different time points: baseline (T0) and after 1 year (T1). Anterior and posterior refractive value; corneal thickness at the thinnest point (TP) and corneal volume (CV) calculated within discs of 3, 5 and 8 mm of diameter; anterior chamber depth (ACD); and anterior chamber volume (ACV) were obtained. Enrolled patients were divided into 3 groups (groups 1, 2, 3) according to the increasing disease severity and into 2 groups (groups A, B) according to the progression or stability of the disease. Overall, 116 eyes of 116 patients (76 males and 40 females, mean age 34.76 ± 13.99 years) were included. For the entire group of keratoconus patients, in comparison with T0, mean TP decreased at T1 from 458.7 ± 52.2 µm to 454.6 ± 51.6 µm (p = 0.0004); in parallel, mean value of CV calculated at 5 mm and 8 mm decreased significantly (from 10.78 ± 0.8 at T0 to 10.75 ± 0.79 at T1 (p = 0.02), and from 32.03 ± 2.01 mm3 at T0 to 31.95 ± 1.98 at T1 (p = 0.02), respectively). Conversely, there were no statistically significant differences in CV at 3 mm from T0 to T1 (p = 0.08), as well as for ACD and ACV. Regarding the course of the disease, patients belonging to group A showed statistically significant differences from T0 to T1 for TP, and for CV at 3 mm, 5 mm and 8 mm (p < 0.0001, p < 0.0001, p < 0.001 and p = 0.0058 respectively). There were no statistically significant differences for ACD (p = 0.6916) and ACV calculated at 3, 5 and 8 mm (p = 0.7709, p = 0.3765, p = 0.2475, respectively) in group A. At the same time, no statistically significant differences for ACD (p = 0.2897) and ACV calculated at 3, 5 and 8 mm (p = 0.9849, p = 0.6420, p = 0.8338, respectively) were found in group B. There were statistically significant positive correlations between changes of TP and CV at 3 mm (r = 0.6324, p < 0.0001), 5 mm (r = 0.7622, p < 0.0001) and 8 mm (r = 0.5987 p < 0.0001). In conclusion, given the strong correlation with TP, CV might be considered an additional AS-OCT parameter to be used in association with conventional parameters when detecting longitudinal changes in keratoconic eyes.

P243 Multi-modality intestinal ultrasound is accurate and reproducible to distinguish inflammatory from chronic fibrotic strictures in Crohn’s disease – results from the STRICTURE study

Abstract Background In 30%-50% of patients with Crohn’s disease (CD) stenotic complications occur1. There is currently no imaging modality to identify stricture composition, which would allow early targeted (anti-inflammatory vs surgical) treatment. Intestinal ultrasound (IUS) and advanced modalities (contrast-enhanced ultrasound (CEUS) and shear-wave elastography (SWE)) have the potential for transmural disease evaluation. The STRICTURE study investigated whether (advanced) IUS techniques could distinguish between inflammatory- (IP) and non-inflammatory phenotypes (non-IP) of stricturing CD. Methods In this prospective, cross-sectional study consecutive patients with small bowel CD undergoing surgery were included. Patients were eligible if they had a non-passable stricture during endoscopy in the small bowel and/or a stricture at cross-sectional imaging (IUS or MRE)2. Prior to surgery, IUS, CEUS and SWE were performed. Two blinded sonographers scored the cine-loops for IUS and CEUS. After surgery, histological slides were retrieved and location matched with IUS. Two blinded pathologists scored for inflammation, adipocytes and fibrosis. Subsequently the predominant phenotype was determined as: [1] inflammatory (IP; Nancy score 4 with no marked fibrosis/adipocytes), [2] fibrotic (FP; structural changes due to marked fibrosis/adipocytes3) or [3] mixed phenotype (MP; inflammatory and fibrotic aspects but no predominant phenotype). FP and MP were both classified as non-IP. Results A total of 36 patients (age: 42±18 years) with a mean BWT of 6.7±1.7 mm were included. Median time between IUS and surgery was 14 [3-50] days. A total of 7 patients had an IP, 18 a FP and 11 a MP. For the conventional IUS parameters, loss of wall layer stratification (WLS) was more frequently found in IP strictures(OR: 7.87 [1.24-50.00], p=0.029). For CEUS, most parameters were significantly higher in IP versus non-IP (Table 1) and at multi-variable logistic regression Wash-in area under the curve remained the only accurate parameter to distinguish IP from non-IP (OR:1.55 [1.03-2.34], p=0.035) [Figure 1]. SWE inversely correlated with CEUS (Table 1, Figure 1) but did not differentiate between IP and non-IP (33.30 kPa vs 43.49 kPa, p=0.48). The agreement for BWT and loss of WLS was good (ICC: 0.77, p&amp;lt;0.001) and moderate (κ: 0.56, p&amp;lt;0.001), respectively. For CEUS, the most accurate parameters had good to excellent agreement [Table 1]. Conclusion Loss of WLS and CEUS are accurate to distinguish an IP from a non-IP stricture in CD and CEUS inversely correlates with SWE. In addition to accuracy, reproducibility was high and multi-modality IUS could be of additional value in this specific population to select patients most suitable for anti-inflammatory treatment. Table 1 Figure 1

Echocardiographic Myocardial Work: A Novel Method to Assess Left Ventricular Function in Patients with Coronary Artery Disease and Diabetes Mellitus.

Myocardial ischemia caused by coronary artery disease (CAD) and the presence of metabolic abnormalities and microvascular impairments detected in patients with diabetes mellitus (DM) are a common cause of left ventricular (LV) dysfunction. Transthoracic echocardiography is the most-used, non-invasive imaging method for the assessment of myocardial contractility. The accurate evaluation of LV function is crucial for identifying patients who are at high risk or may have worse outcomes. Myocardial work (MW) is emerging as an alternative tool for the evaluation of LV systolic function, providing additional information on cardiac performance when compared to conventional parameters such as left ventricular ejection fraction (LVEF) and global longitudinal strain (GLS) because it incorporates deformation and load into its analysis. The potential of MW in various conditions is promising and it has gained increased attention. However, larger studies are necessary to further investigate its role and application before giving an answer to the question of whether it can have widespread implementation into clinical practice. The aim of this review is to summarize the actual knowledge of MW for the analysis of LV dysfunction caused by myocardial ischemia and hyperglycemia.