Optimal Time Research Articles

When after radical prostatectomy radiotherapy should be performed? Comparison of adjuvant and salvage radiotherapy (literature review)

The question of optimal times and indications for radiotherapy (adjuvant or salvage) after surgical treatment of prostate cancer remains unanswered. Therefore, studies of this problem are essential and important for clinical practice. The article evaluates the effectiveness of adjuvant radiotherapy compared to salvage radiotherapy in the context of recurrence-free survival and associated adverse events. In 3 randomized clinical trials and meta-analysis, adjuvant radiotherapy did not show improved recurrence-free survival compared to salvage radiotherapy. The choice between adjuvant and salvage radiotherapy should be based on individual patient history and the risk of recurrence. Delayed radiotherapy can help some patients to avoid excessive treatment and associated adverse events.

Evaluating the Ability of the Sentinel-1 Cross-Polarization Ratio to Detect Spring Maize Phenology Using Adaptive Dynamic Threshold

Accurate, timely, and fine-resolution crop phenology is essential for determining the optimal timing of agronomic management practices supporting precision agriculture and food security. Synthetic Aperture Radar (SAR) methods, unaffected by cloud occlusion, have been widely applied in monitoring maize phenology. Nonetheless, their reliance on manual threshold settings, which depend on the user’s expertise, limits their applicability. Furthermore, the neglect of SAR’s potential for monitoring other phenological periods (e.g., seven-leaves date (V7), jointing date (JD), tassel date (TD), and milky date (MID)) hinders their robustness, particularly for regional-scale applications. To address these issues, this study used an adaptive dynamic threshold to evaluate the ability of the Sentinel-1 cross-polarization ratio (CR) in detecting the three-leaves date (V3), V7, JD, TD, MID, and maturity date (MD) of maize. We analyzed the effect of incidence angle, precipitation, and wind speed on Sentinel-1 features to identify the optimal feature for time series fitting. Then, we employed linear regression to determine the optimal threshold and developed an adaptive dynamic threshold for phenology detection. This approach effectively mitigated the speckle noise of Sentinel-1 and minimized artificial interference caused by customary conventional thresholds. Finally, we mapped phenology across 8.3 million ha in Heilongjiang Province. The results indicated that the approach has a higher ability to detect JD (RMSE = 11.10 d), MID (RMSE = 10.31 d), and MD (RMSE = 9.41 d) than that of V3 (RMSE = 32.07 d), V7 (RMSE = 56.37 d), and TD (RMSE = 43.33 d) in Sentinel-1. Compared with Sentinel-2, the average RMSE of JD, MID, and MD decreased by 4.14%, 35.28%, and 26.48%. Moreover, when compared to different thresholds, the adaptive dynamic threshold can quickly determine the optimal threshold for detecting each phenological stage. CR is least affected by incident angle, precipitation, and wind speed, effectively suppressing noise to reflect phenological development better. This approach supports the rapid and feasible mapping of maize phenology across broad spatial regions with a few samples.

Crossover can guarantee exponential speed-ups in evolutionary multi-objective optimisation

Evolutionary algorithms are popular algorithms for multi-objective optimisation (also called Pareto optimisation) as they use a population to store trade-offs between different objectives. Despite their popularity, the theoretical foundation of multi-objective evolutionary optimisation (EMO) is still in its early development. Fundamental questions such as the benefits of the crossover operator are still not fully understood. We provide a theoretical analysis of the well-known EMO algorithms GSEMO and NSGA-II to showcase the possible advantages of crossover: we propose classes of “royal road” functions on which these algorithms cover the whole Pareto front in expected polynomial time if crossover is being used. But when disabling crossover, they require exponential time in expectation to cover the Pareto front. The latter even holds for a large class of black-box algorithms using any elitist selection and any unbiased mutation operator. Moreover, even the expected time to create a single Pareto-optimal search point is exponential. We provide two different function classes, one tailored for one-point crossover and another one tailored for uniform crossover, and we show that some immune-inspired hypermutations cannot avoid exponential optimisation times. Our work shows the first example of an exponential performance gap through the use of crossover for the widely used NSGA-II algorithm and contributes to a deeper understanding of its limitations and capabilities.

Inkjet-printed MOS-based MEMS sensor array combined with one-dimensional convolutional neural network algorithm for identifying indoor harmful gases

To achieve a highly accurate and efficient analysis of mixed gases, it is crucial to develop an electronic nose system with high sensitivity of gas sensors and low data processing complexity. In this study, the metal oxide semiconductor (MOS) based micro-electromechanical system (MEMS) gas sensor array was prepared by inkjet printing sensing materials onto a micro-hotplate. The pattern recognition unit employed a one-dimensional convolutional neural network (1D-CNN) to identify 7 types of gases. While the optimal traditional machine learning algorithm achieved an 80% recognition accuracy, the 1D-CNN can achieve 99.8%. Furthermore, the impact of varying time series input lengths on the model accuracy was investigated, pinpointing an optimal sampling time of 15 s. This work showed that integrating the MEMS sensor array with the 1D-CNN algorithm might offer a promising approach for intricate gas classification and identification.

Traumatic rotator cuff injury: does delayed surgery worsen functional outcomes?

The optimal timing of surgery after traumatic rotator cuff tears (RCT) is unclear, with its impact on functional outcomes under debate. This study aimed to review functional outcomes after RCT repair in patients who underwent early vs delayed surgery at our unit. This was single-centre retrospective evaluation. Patients with an acute traumatic RCT that underwent repair between 2017 and 2019 and had local follow-up were included and placed into two groups: early surgery (within 6months from injury) and delayed surgery (more than 6months from injury). Patient demographics, RCT data and pre- and post-operative (after 12months) Oxford Shoulder Score (OSS) were extracted from medical records. Data was analysed to compare OSS scores between groups, as well as the effect of cuff tear sizes on OSS scores. Forty-nine patients were included in the analysis (15 early, 34 delayed). There were no significant differences in age, sex or cuff tear sizes between groups. No difference was identified in the mean post-operative OSS between early vs delayed groups (40.9 ± 6.34 vs 40.5 ± 7.65, p = 0.86). The mean improvement in OSS after surgery was also similar between groups (22.5 ± 7.81 vs 20.97 ± 7.19, p = 0.498). Having a large or massive RCT did not worsen OSS compared to small or medium RCT (p = 0.44), even when stratified by early or delayed surgery. Delayed surgery for traumatic RCT greater than 6months from injury did not negatively impact long-term functional outcomes at our unit. Patients should be reassured as applicable before surgery in the event of prolonged or unavoidable delays.

Low-Voltage Distribution Network Loss-Reduction Method Based on Load-Timing Characteristics and Adjustment Capabilities

The primary contributors to elevated line losses in low-voltage distribution networks are three-phase load imbalances and variations in load peak–valley differentials. The conventional manual phase sequence adjustment fails to capitalize on the temporal characteristics of the load, and the proliferation of smart homes has opened up new scheduling possibilities for managing the load. Consequently, this paper introduces a loss-reduction method for low-voltage distribution networks that leverages load-timing characteristics and adjustment capabilities. This method combines dynamic and static methods to reduce energy consumption from different time scales. To commence, this paper introduced a hierarchical fuzzy C-means algorithm (H-FCM), taking into account the distance and similarity of load curves. Subsequently, a phase sequence adjustment method, grounded in load-timing characteristics, was developed. The typical user load curve, derived from the classification of user loads, serves as the foundation for constructing a long-term commutation model, therefore mitigating the impact of load fluctuations on artificial commutation. Following this, this paper addressed the interruptible and transferable characteristics of various smart homes. This paper proposed a multi-objective transferable load (TL) optimal timing task adjustment model and a peak-shaving control strategy specifically designed for maximum sustainable power reduction of temperature-controlled loads (TCL). These strategies aim to achieve real-time load adjustment, correct static commutation errors, and reduce peak-to-valley differences. Finally, a simulation verification model was established in MATLAB (R2022a). The results show that the proposed method mainly solves the problems of three-phase imbalance and large load peak–valley difference in low-voltage distribution networks and reduces the line loss of low-voltage distribution networks through manual commutation and load adjustment.

Distribution and elimination kinetics of midazolam and metabolites after post-resuscitation care: a prospective observational study

Administration of sedatives for post-resuscitation care can complicate the determination of the optimal timing to avoid inappropriate, pessimistic prognostications. This prospective study aimed to investigate the distribution and elimination kinetics of midazolam (MDZ) and its metabolites, and their association with awakening time. The concentrations of MDZ and its seven metabolites were measured immediately and at 4, 8, 12, and 24 h after the discontinuation of MDZ infusion, using liquid chromatography-tandem mass spectrometry. The area under the time-plasma concentration curve from 0 to 24 h after MDZ discontinuation (AUClast) was calculated based on the trapezoidal rule. Of the 15 enrolled patients, seven awakened after the discontinuation of MDZ infusion. MDZ and three of its metabolites were major compounds and their elimination kinetics followed a first-order elimination profile. In the multivariable analysis, only MDZ was associated with awakening time (AUClast: R2 = 0.59, p = 0.03; AUCinf: R2 = 0.96, p < 0.001). Specifically, a 0.001% increase in MDZ AUC was associated with a 1% increase in awakening time. In the individual regression analysis between MDZ concentration and awakening time, the mean MDZ concentration at awakening time was 16.8 ng/mL. The AUC of MDZ is the only significant factor associated with the awakening time.

Perspectives on the optimal timing of advance care planning among Japanese patients undergoing dialysis and clinicians: a cross-sectional study.

The majority of dialysis patients and clinicians favor early advance care planning in our sample. Yet, there is a disconnect: only 11% of patients discussed future care with their clinicians. Our findings indicate Japanese dialysis patients and clinicians support proactive advance care planning at or before dialysis initiation. Little is known about the optimal timing of discussions about advance care planning among dialysis patients and clinicians engaged in dialysis care. We aimed to explore the preferred timing for advance care planning and assess actual participation in advance care planning among dialysis patients and their clinicians. A scenario-based survey on Japanese patients aged ≥65years on dialysis and clinicians involved in their dialysis care was performed. Participants were asked if they would feel prepared to engage in advance care planning with their clinicians, offering a choice among four hypothetical stages within the illness trajectory, extending from the initiation of dialysis to a later phase characterized by the patient's extreme frailty. Overall, 181 patients and 128 clinicians participated in the study. Among these, 131 (72%) patients, and 84 (66%) clinicians indicated that they would prefer to initiate advance care planning around the time of dialysis initiation. Only 20 patients (11%) indicated that they had participated in advance care planning with at least one clinician, including 11 (6%) who indicated that they had discussed their preferences around life-sustaining treatments and 8 (4%) who had discussed their preferences around dialysis continuation. While fewer than 11% of patients undergoing dialysis and their clinicians enrolled in our study had participated in advance care planning, most indicated that they would be comfortable initiating the discussion around the time of dialysis initiation. These findings suggest untapped opportunities to engage patients in advance care planning early in the course of their dialysis.

Optimal duration of breastfeeding

Introduction. The question of the optimal timing of cessation of lactation from the perspective of maternal-child relationships remains controversial.Aim. Тo determine the optimal timing for stopping breastfeeding based on data on the formation of the child’s personal characteristics and the relationship with the mother.Materials and methods. The results of a prospective study of mother-child relationships during the period of cessation of breastfeeding are presented. The age of the child was assessed at the termination of breastfeeding, the difficulties experienced by the mother and the child at its termination (affective attachment, characteristics of the child’s behavior). Observation was carried out in the classroom in the group of short-term stay in preschool conditions 1–2 times a week for at least 1.5 hours. 108 mother-child pairs were under observation. Depending on the duration of breastfeeding, couples were divided into two groups. The first group – 64 children who are breastfed for no more than 18 months, the second group – 44 children who are breastfed for more than 18 months. Statistical processing of the obtained data was carried out using the Excel program using Student’s t-test and Pearson’s χ2 method. Differences were considered statistically significant at p &lt; 0.05.Results and discussion. Since the conditions of the children’s polyclinic do not allow for monitoring the child and his mother, the study was carried out in a group of short-term stay in a preschool educational institution, which is quite typical for the modern urban maternal population. The work was carried out jointly with teachers and psychologists who developed criteria for assessing mother-child relations and the child’s behavioral characteristics. In the group of children who were breastfed after 18 months, affective attachment to the mother, use of the breast to soothe them in the absence of breast milk, anxiety when falling asleep, were 2 times more common than in children who were breastfed for less than 18 months. The data obtained indicate the need to inform nursing mothers about the mental characteristics of a child’s development in certain age periods, a decrease in lactation after a year, and its frequent termination by 18 months.Conclusions. Based on the data obtained, it can be considered appropriate the optimal duration of breastfeeding up to one and a half years.

Asymptotic Duration for Optimal Multiple Stopping Problems

We study the asymptotic duration of optimal stopping problems involving a sequence of independent random variables that are drawn from a known continuous distribution. These variables are observed as a sequence, where no recall of previous observations is permitted, and the objective is to form an optimal strategy to maximise the expected reward. In our previous work, we presented a methodology, borrowing techniques from applied mathematics, for obtaining asymptotic expressions for the expectation duration of the optimal stopping time where one stop is permitted. In this study, we generalise further to the case where more than one stop is permitted, with an updated objective function of maximising the expected sum of the variables chosen. We formulate a complete generalisation for an exponential family as well as the uniform distribution by utilising an inductive approach in the formulation of the stopping rule. Explicit examples are shown for common probability functions as well as simulations to verify the asymptotic calculations.

Can sodium and potassium measured in timed voids be used as reference instruments for validating self-report instruments? Results from a urine calibration study

BackgroundSodium and potassium measured in 24-h urine collections are often used as reference measurements to validate self-reported dietary intake instruments. ObjectivesTo evaluate whether collection and analysis of a limited number of urine voids at specified times during the day (“timed voids”) can provide alternative reference measurements, and to identify their optimal number and timing. MethodsWe used data from a urine calibration study among 441 adults aged 18–39 y. Participants collected each urine void in a separate container for 24 h and recorded the collection time. For the same day, they reported dietary intake using a 24-h recall. Urinary sodium and potassium were analyzed in a 24-h composite sample and in 4 timed voids (morning, afternoon, evening, and overnight). Linear regression models were used to develop equations predicting log-transformed 24-h urinary sodium or potassium levels using each of the 4 single timed voids, 6 pairs, and 4 triples. The equations also included age, sex, race, BMI (kg/m2), and log creatinine. Optimal combinations minimizing the mean squared prediction error were selected, and the observed and predicted 24-h levels were then used as reference measures to estimate the group bias and attenuation factors of the 24-h dietary recall. These estimates were compared. ResultsOptimal combinations found were as follows: single voids—evening; paired voids—afternoon + overnight (sodium) and morning + evening (potassium); and triple voids—morning + evening + overnight (sodium) and morning + afternoon + evening (potassium). Predicted 24-h urinary levels estimated 24-h recall group biases and attenuation factors without apparent bias, but with less precision than observed 24-h urinary levels. To recover lost precision, it was estimated that sample sizes need to be increased by ∼2.6–2.7 times for a single void, 1.7–2.1 times for paired voids, and 1.5–1.6 times for triple voids. ConclusionsOur results provide the basis for further development of new reference biomarkers based on timed voids. Clinical Trial Registryclinicaltrials.gov as NCT01631240.

Establishment and application of a rapid molecular diagnostic platform for the isothermal visual amplification of group B Streptococcus based on recombinase polymerase.

With growing concerns about Group B streptococcal (GBS) infections and their adverse effects on perinatal pregnancies, including infection, premature delivery, neonatal septicemia, and meningitis, it is urgent to promote GBS screening at all pregnancy stages. The purpose of this study is to establish a device-independent, fast, sensitive, and visual GBS detection method. Taking advantage of the characteristics of the recombinase polymerase isothermal amplification (RPA), the activity of the nfo nuclease cleavage base analog (tetrahydrofuran, THF) site, and the advantages of visual reading of the lateral flow chromatography strip (LFS), a GBS detection method was developed. This method focused on the conservative region of the Christie-Atkins-Munch-Petersen factor encoded by the cfb gene, a virulence gene specific to GBS. Two forward primers, two biotin-labeled reverse primers, and one fluorescein isothiocyanate (FITC)-labeled and C3spacer-blocked probe were designed. The study involved optimizing the primer pair and probe combination, determining the optimal reaction temperature and time, evaluating specificity, analyzing detection limits, and testing the method on 87 vaginal swabs from perinatal pregnant women. The results showed that the visual detection method of GBS-RPA-LFS, using the cfb-F1/R2/P1 primer probe, could detect GBS within 15 min at the temperature ranging from 39°C to 42°C. Furthermore, the method specifically amplified only GBS, without cross-reacting with pathogens like Lactobacillus iners, Lactobacillus crispatus, Candida albicans, Listeria monocytogenes, Yersinia enterocolitica, Klebsiella Pneumoniae, Enterobacter cloacae, Citrobacter freundii, Vibrio alginolyticus, Vibrio parahaemolyticus, Salmonella typhimurium, Staphylococcus aureus, Pseudomonas aeruginosa, or Trichomonas vaginalis. It could detect a minimum of 100 copies per reaction. In clinical 98 samples of vaginal swabs from pregnant women, the agreement rate between the GBS-RPA-LFS method and TaqMan real-time fluorescence quantification method was 95.92%. In conclusion, this study successfully established a combined RPA and LFS GBS in situ detection platform, with short reaction time, high sensitivity, high specificity, portability, and device independence, providing a feasible strategy for clinical GBS screening.

Timing and green decisions for competitive manufacturers under demand uncertainty and risk aversion

AbstractLeveraging real options theory, we have constructed a utility‐based model to examine the influence of uncertainty, risk aversion, and competition on the optimal entry timing for green manufacturers and traditional manufacturers, as well as the degree of greenness for follower products. Our analysis reveals that increased uncertainty and risk aversion enhance the value of investment opportunities for manufacturers, thereby raising their investment thresholds. Even though competition reduces the value of market entry for the leader compared to monopoly, its investment thresholds are unaffected by competition. More interestingly, consumer green preferences exhibit a non‐monotonic impact on green enterprise's entry timing.

Global well-posedness and decay estimates for the one-dimensional models of blood flow with a general parabolic velocity profile

In this paper, we study the one-dimensional models of blood flow arising from the hemodynamics of aorta, which are derived from the averaging of the Navier–Stokes equations. We establish the global well-posedness and long-time behavior of the viscid 1D models of blood flow in the Sobolev space framework, where a general parabolic velocity profile is considered. Precisely speaking, we prove the global existence of smooth solution when the initial data is sufficiently small. Moreover, by combining the time-weighted energy estimates with the Green function method, we obtain the optimal time decay rate in Lp (2≤p≤∞) norm. In addition, one can see the area-averaged axial velocity decays faster than the cross-sectional area of vessel from the Green function of the linearized system. This observation is essential to study the decay rates of our nonlinear system.

Predicting postoperative systolic dysfunction in mitral regurgitation: CT vs. echocardiography.

Volume overload from mitral regurgitation can result in left ventricular systolic dysfunction. To prevent this, it is essential to operate before irreversible dysfunction occurs, but the optimal timing of intervention remains unclear. Current echocardiographic guidelines are based on 2D linear measurement thresholds only. We compared volumetric CT-based and 2D echocardiographic indices of LV size and function as predictors of post-operative systolic dysfunction following mitral repair. We retrospectively identified patients with primary mitral valve regurgitation who underwent repair between 2005 and 2021. Several indices of LV size and function measured on preoperative cardiac CT were compared with 2D echocardiography in predicting post-operative LV systolic dysfunction (LVEFecho <50%). Area under the curve (AUC) was the primary metric of predictive performance. A total of 243 patients were included (mean age 57 ± 12 years; 65 females). The most effective CT-based predictors of post-operative LV systolic dysfunction were ejection fraction [LVEFCT; AUC 0.84 (95% CI: 0.77-0.92)] and LV end systolic volume indexed to body surface area [LVESViCT; AUC 0.88 (0.82-0.95)]. The best echocardiographic predictors were LVEFecho [AUC 0.70 (0.58-0.82)] and LVESDecho [AUC 0.79 (0.70-0.89)]. LVEFCT was a significantly better predictor of post-operative LV systolic dysfunction than LVEFecho (p = 0.02) and LVESViCT was a significantly better predictor than LVESDecho (p = 0.03). Ejection fraction measured by CT demonstrated significantly greater reproducibility than echocardiography. CT-based volumetric measurements may be superior to established 2D echocardiographic parameters for predicting LV systolic dysfunction following mitral valve repair. Validation with prospective study is warranted.

Association of continuous kidney replacement therapy timing and mortality in critically ill children.

Acute kidney injury (AKI) is a common complication of critical illness and associated with high morbidity and mortality. Optimal timing of continuous kidney replacement therapy (CKRT) in children is unknown. We aimed to measure the association between timing of initiation and mortality. This is a single-center retrospective cohort study of pediatric patients receiving CKRT from 2013 to 2019. The primary exposure, time to CKRT initiation, was measured from onset of stage 3 AKI during hospitalization (defined using Kidney Disease: Improving Global Outcomes creatinine and urine output criteria) and analyzed as both a continuous and categorical variable. The primary outcome was ICU mortality. Ninety-nine patients met criteria for analysis. Overall mortality was 39% (39/99). Median time from stage 3 AKI onset to CKRT initiation was 1.5days in survivors and 5.5days in nonsurvivors (p < 0.001). In multivariable analysis, increased time to CKRT initiation was independently associated with mortality [OR 1.02 per hour (95% CI 1.01-1.04), p < 0.001]. Longer time to CKRT initiation was associated with higher odds of mortality in ascending time intervals. Patients started on CKRT > 2days compared to < 2days after stage 3 AKI onset had higher mortality (65% vs. 5%, p < 0.001), longer median ICU length of stay (25 vs. 12 d, p < 0.001), longer median CKRT duration (11 vs. 5 d, p < 0.001), and fewer AKI-free days (0 vs. 14 d, p < 0.001). Longer time to initiation of CKRT after development of severe AKI is independently associated with mortality. Consideration of early CKRT in this high-risk population may be a strategy to reduce mortality and improve recovery of kidney function. However, there remains significant heterogeneity in the definition of early versus late initiation and the optimal timing of CKRT remains unknown.

Approaching an optimum time resolution for synchroscan streak-camera measurements with visible synchrotron light

The optical beam diagnostics at the BESSY II light source in Berlin have been improved significantly over the last few years. In particular, the streak-camera system has been extended in precision and sensitivity to allow two-dimensional imaging in time and space for equilibrated and non-equilibrated bunch patterns. In this paper, we prove experimentally and theoretically that we have reached a sub-ps RMS total time resolution using filtered synchrotron light. Detailed simulations, including the different physical time-dispersion mechanisms, show the influence of various band-pass and edge wavelength filters on the resolution. The limits for unfiltered near-visible synchrotron radiation (white-light) and the band-pass filter to achieve optimal time resolution are derived as well, providing a basis for more advanced beam-dynamics studies in the near future.

Urban Traffic Flow Prediction Based on Bayesian Deep Learning Considering Optimal Aggregation Time Interval

Predicting short-term urban traffic flow is a fundamental and cost-effective strategy in traffic signal control systems. However, due to the interrupted, periodic, and stochastic characteristics of urban traffic flow influenced by signal control, there are still unresolved issues related to the selection of the optimal aggregation time interval and the quantifiable uncertainties in prediction. To tackle these challenges, this research introduces a method for predicting urban interrupted traffic flow, which is based on Bayesian deep learning and considers the optimal aggregation time interval. Specifically, this method utilizes the cross-validation mean square error (CVMSE) method to obtain the optimal aggregation time interval and to establish the relationship between the optimal aggregation time interval and the signal cycle. A Bayesian LSTM-CNN prediction model, which extends the LSTM-CNN model under the Bayesian framework to a probabilistic model to better capture the stochasticity and variation in the data, is proposed. Experimental results derived from real-world data demonstrate gathering traffic flow data based on the optimal aggregation time interval significantly enhances the prediction accuracy of the urban interrupted traffic flow model. The optimal aggregation time interval for urban interrupted traffic flow data corresponds to a multiple of the traffic signal control cycle. Comparative experiments indicate that the Bayesian LSTM-CNN prediction model outperforms the state-of-the-art prediction models.

Delayed Enhancement of Intracranial Atherosclerotic Plaque Can Better Differentiate Culprit Lesions: A Multiphase Contrast-Enhanced Vessel Wall MRI Study.

Intracranial plaque enhancement (IPE) identified by contrast-enhanced vessel wall MR imaging (VW-MR imaging) is an emerging marker of plaque instability related to stroke risk, but there was no standardized timing for postcontrast acquisition. We aim to explore the optimal postcontrast timing by using multiphase contrast-enhanced VW-MR imaging and to test its performance in differentiating culprit and nonculprit lesions. Patients with acute ischemic stroke due to intracranial plaque were prospectively recruited to undergo VW-MR imaging with 1 precontrast phase and 4 consecutive postcontrast phases (9 minutes and 13 seconds for each phase). The signal intensity (SI) values of the CSF and intracranial plaque were measured on 1 precontrast and 4 postcontrast phases to determine the intracranial plaque enhancement index (PEI). The dynamic changes of the PEI were compared between culprit and nonculprit plaques on the postcontrast acquisitions. Thirty patients with acute stroke (aged 59 ± 10 years, 18 [60%] men) with 113 intracranial plaques were included. The average PEI of all intracranial plaques significantly increased (up to 14%) over the 4 phases. There was significantly increased PEI over the 4 phases for culprit plaques (an average increase of 23%), but this was not observed for nonculprit plaques. For differentiating culprit and nonculprit plaques, we observed that the performance of IPE in the second postcontrast phase (cutoff = 0.83, AUC = 0.829 [0.746-0.893]) exhibited superior accuracy when compared with PEI in the first postcontrast phase (cutoff = 0.48; AUC = 0.768 [0.680-0.843]) (P = .022). A 9-minute delay of postcontrast acquisition can maximize plaque enhancement and better differentiate between culprit and nonculprit plaques. In addition, culprit and nonculprit plaques have different enhancement temporal patterns, which should be evaluated in future studies.

Central venous catheter tip positioning using ultrasound in pediatric patients-A prospective observational study.

In children, central venous catheter (CVC) placement is usually performed under ultrasound guidance for optimal visualization of vessels and reduction of puncture-related complications. Nevertheless, in many cases, additional radiographic examinations are performed to check the position of the catheter tip. The primary objective of this observational feasibility study was to determine the number of ultrasound-guided central venous catheter tips that can be identified in a subsequent position check using ultrasonography. Furthermore, we investigated the optimal ultrasound window, time expenditure, and success rate concerning puncture attempts and side effects. In addition, we compared the calculated and real insertion depths and analyzed the position of the catheter tip on postoperative radiographs with the tracheal bifurcation as a traditional landmark. Ninety children with congenital heart defects who required a central venous line for cardiac surgery were included in this single-center study. After the insertion of the catheter, the optimal position of its tip was controlled using one of four predefined ultrasound windows. A chest radiograph was obtained postoperatively in accordance with hospital standards to check the catheter tip position determined by ultrasonography. The children had a median (IQR) age of 11.5 (4.0, 58.8) months and a mean (SD) BMI of 15.3 (2.91) kg/m2 Ultrasound visualization of the catheter tip was successful in 86/90 (95.6%) children (95% confidence interval [CI]: 91.3%, 99.8%). Postoperative radiographic examination showed that the catheter tip was in the desired position in 94.4% (95% CI: 89.7%, 99.2%) of the cases. None of the children needed the catheter tip position being corrected based on chest radiography. Additional radiation exposure after the placement of central venous catheters can be avoided with the correct interpretation of standardized ultrasound windows, especially in vulnerable children with cardiac disease.