Dexmedetomidine improves pulmonary outcomes in thoracic surgery under one-lung ventilation: A meta-analysis.

INTRODUCTION: Dexmedetomidine improves intrapulmonary shunt in thoracic surgery and minimizes inflammatory response during one-lung ventilation (OLV). However, it is unclear whether such benefits translate into less postoperative pulmonary complications (PPCs). Our objective was to determine the impact of dexmedetomidine on the incidence of PPCs after thoracic surgery. METHODS: Major databases were used to identify randomized trials that compared dexmedetomidine versus placebo during thoracic surgery in terms of PPCs. Our primary outcome was atelectasis within 7 days after surgery. Other specific PPCs included hypoxemia, pneumonia, and acute respiratory distress syndrome (ARDS). Secondary outcome included intraoperative respiratory mechanics (respiratory compliance [Cdyn]) and postoperative lung function (forced expiratory volume [FEV1]). Random effects models were used to estimate odds ratios (OR). RESULTS: Twelve randomized trials, including 365 patients in the dexmedetomidine group and 359 in the placebo group, were analyzed in this meta-analysis. Patients in the dexmedetomidine group were less likely to develop postoperative atelectasis (2.3% vs 6.8%, OR 0.42, 95%CI 0.18-0.95, P = 0.04; low certainty) and hypoxemia (3.4% vs 11.7%, OR 0.26, 95%CI 0.10-0.68, P = 0.01; moderate certainty) compared to the placebo group. The incidence of postoperative pneumonia (3.2% vs 5.8%, OR 0.57, 95%CI 0.25-1.26, P = 0.17; moderate certainty) or ARDS (0.9% vs 3.5%, OR 0.39, 95%CI 0.07-2.08, P = 0.27; moderate certainty) was comparable between groups. Both intraoperative Cdyn and postoperative FEV1 were higher among patients that received dexmedetomidine with a mean difference of 4.42 mL/cmH2O (95%CI 3.13-5.72) and 0.27 L (95%CI 0.12-0.41), respectively. CONCLUSION: Dexmedetomidine administration during thoracic surgery may potentially reduce the risk of postoperative atelectasis and hypoxemia. However, current evidence is insufficient to demonstrate an effect on pneumonia or ARDS.

Medicines and Healthcare products Regulatory Agency's "Consultation on proposals for legislative changes for clinical trials": a response from the Trials Methodology Research Partnership Adaptive Designs Working Group, with a focus on data sharing.

In the UK, the Medicines and Healthcare products Regulatory Agency consulted on proposals "to improve and strengthen the UK clinical trials legislation to help us make the UK the best place to research and develop safe and innovative medicines". The purpose of the consultation was to help finalise the proposals and contribute to the drafting of secondary legislation. We discussed these proposals as members of the Trials Methodology Research Partnership Adaptive Designs Working Group, which is jointly funded by the Medical Research Council and the National Institute for Health and Care Research. Two topics arose frequently in the discussion: the emphasis on legislation, and the absence of questions on data sharing. It is our opinion that the proposals rely heavily on legislation to change practice. However, clinical trials are heterogeneous, and as a result some trials will struggle to comply with all of the proposed legislation. Furthermore, adaptive design clinical trials are even more heterogeneous than their non-adaptive counterparts, and face more challenges. Consequently, it is possible that increased legislation could have a greater negative impact on adaptive designs than non-adaptive designs. Overall, we are sceptical that the introduction of legislation will achieve the desired outcomes, with some exceptions. Meanwhile the topic of data sharing - making anonymised individual-level clinical trial data available to other investigators for further use - is entirely absent from the proposals and the consultation in general. However, as an aspect of the wider concept of open science and reproducible research, data sharing is an increasingly important aspect of clinical trials. The benefits of data sharing include faster innovation, improved surveillance of drug safety and effectiveness and decreasing participant exposure to unnecessary risk. There are already a number of UK-focused documents that discuss and encourage data sharing, for example, the Concordat on Open Research Data and the Medical Research Council's Data Sharing Policy. We strongly suggest that data sharing should be the norm rather than the exception, and hope that the forthcoming proposals on clinical trials invite discussion on this important topic.

Continuous Positive Airway Pressure plus Mandibular Advancement Therapy (PAPMAT): study protocol for an adaptive randomised crossover trial comparing the benefits and costs of combining two established treatments for obstructive sleep apnoea.

BACKGROUND: Obstructive sleep apnoea (OSA) involves repeated breathing pauses during sleep due to upper airway obstruction. It causes excessive daytime sleepiness and has other health impacts. Continuous positive airway pressure (CPAP) therapy is effective first line treatment for moderate to severe OSA. Unfortunately, many patients have difficulty tolerating CPAP and pressure intolerance is probably an important contributing factor. Mandibular advancement devices (MAD) are an alternative to CPAP. They are worn in the mouth during sleep to reduce airway obstruction. There is some evidence that, when used in combination with CPAP, MADs improve airway anatomy enough to reduce the CPAP pressure required to treat OSA and that this combination therapy could improve CPAP adherence. METHODS: Consecutive patients starting on CPAP for moderate to severe OSA will be recruited at a regional NHS sleep service. Patients with high CPAP pressure requirements after initial titration, who satisfy all entry criteria and consent to participate, will undertake a 2-arm randomised crossover trial. The arms will be (i) standalone CPAP and (ii) CPAP + MAD therapy. Each arm will last 12 weeks, including 2 weeks acclimatisation. CPAP machines will be auto-titrating and with facility for data download, so the impact of MAD on CPAP pressure requirements and CPAP adherence can be easily measured. The primary outcome will be CPAP adherence. Secondary outcomes will include measures of OSA severity, patient-reported outcome measures including subjective daytime sleepiness, quality of life, and treatment preference at the trial exit and health service use. Cost-effectiveness analyses will be undertaken. DISCUSSION: If the intervention is shown to be effective and cost-effective in improving adherence in this standard CPAP-eligible OSA patient population it would be relatively straightforward to introduce into existing OSA treatment pathways, within the wider NHS and more widely. Both MAD and CPAP are already used by sleep services so their combination would require only minor adjustments to existing clinical pathways. It would be straightforward to disseminate the results of the study through regional, national, and international respiratory meetings. The health economics analysis would provide cost-effectiveness data to inform service planning and clinical guidelines through policy briefing papers, including those by NICE and SIGN. TRIAL REGISTRATION: PAPMAT was registered with ISRCTN prior to recruitment beginning (ISRCTN Registry 2021): https://www.isrctn.com/ISRCTN33966032 . Registered on 17th November 2021.

A Double-Blind, Randomized, Placebo-controlled Trial of Long-Term Doxycycline Therapy on Exacerbation Rate in Patients with Stable Chronic Obstructive Pulmonary Disease.

Rationale: Chronic obstructive pulmonary disease (COPD) exacerbations are a major cause of morbidity and mortality, and preventing them is a key treatment target. Long-term macrolide treatment is effective at reducing exacerbations, but there is a paucity of evidence for other antibiotic classes. Objectives: To assess whether 12-month use of doxycycline reduces the exacerbation rate in people with COPD. Methods: People with moderate to very severe COPD and an exacerbation history were recruited from three UK centers and randomized to 12 months of doxycycline 100 mg once daily or placebo. The primary study outcome was the exacerbation rate per person-year. Results: A total of 222 people were randomized. Baseline mean FEV1 was 1.35 L (SD, 0.35 L), 52.5% predicted (SD, 15.9% predicted). The median number of treated exacerbations in the year before the study was 2 (SD, 1-4). A total of 71% of patients reported two or more exacerbations, and 81% were already prescribed inhaled corticosteroids at baseline. The COPD exacerbation rate did not differ between the groups (doxycycline/placebo rate ratio [RR], 0.86; 95% confidence interval [CI], 0.67-1.10; P = 0.23). No difference was seen if only treated exacerbations or hospitalizations were considered. In preplanned subgroup analysis, doxycycline appeared to better reduce the exacerbation rate among people with severe COPD (RR, 0.36; 95% CI, 0.15-0.85; P = 0.019) and in those with an eosinophil count <300 cells/µl (RR, 0.50; 95% CI, 0.29-0.84; P = 0.01). Health status measured by St. George's Respiratory Questionnaire was 5.2 points worse in the doxycycline group at 12 months (P < 0.007). Conclusions: Doxycycline did not significantly reduce the exacerbation rate, over 12 months, in participants with COPD who exacerbated regularly, but it may have benefitted those with more severe COPD or blood eosinophil counts <300 cells/µl. Clinical trial registered with www.clinicaltrials.gov (NCT02305940).

Efficacy and effectiveness of inactivated vaccines against symptomatic COVID-19, severe COVID-19, and COVID-19 clinical outcomes in the general population: a systematic review and meta-analysis.

Background: Inactivated, whole-virion vaccines have been used extensively in the SARS-CoV-2 pandemic. Its efficacy and effectiveness across regions have not been systematically evaluated. Efficacy refers to how well a vaccine performs in a controlled environment. Effectiveness refers to how well it performs in real world settings. Methods: This systematic review and meta-analysis reviewed published, peer-reviewed evidence on all WHO-approved inactivated vaccines and evaluated their efficacy and effectiveness against SARS-CoV-2 infection, symptomatic infection, severe clinical outcomes, and severe COVID-19. We searched Pubmed (including MEDLINE), EMBASE (via OVID), Web of Science Core Collection, Web of Science Chinese Science Citation Database, and Clinicaltrials.gov. Findings: The final pool included 28 studies representing over 32 million individuals reporting efficacy or effectiveness estimates of complete vaccination using any approved inactivated vaccine between January 1, 2019 and June 27, 2022. Evidence was found for efficacy and effectiveness against symptomatic infection (OR 0.21, 95% CI 0.16-0.27, I2 = 28% and OR 0.32, 95% CI 0.16-0.64, I2 = 98%, respectively) and infection (OR 0.53, 95% CI 0.49-0.57, I2 = 90% and OR 0.31, 95% CI 0.24-0.41, I2 = 0%, respectively) for early SARS-CoV-2 variants of concern (VoCs) (Alpha, Delta), and for waning of vaccine effectiveness with more recent VoCs (Gamma, Omicron). Effectiveness remained robust against COVID-related ICU admission (OR 0.21, 95% CI 0.04-1.08, I2 = 99%) and death (OR 0.08, 95% CI 0.00-2.02, I2 = 96%), although effectiveness estimates against hospitalization (OR 0.44, 95% CI 0.37-0.53, I2 = 0%) were inconsistent. Interpretation: This study showed evidence of efficacy and effectiveness of inactivated vaccines for all outcomes, although inconsistent reporting of key study parameters, high heterogeneity of observational studies, and the small number of studies of particular designs for most outcomes undermined the reliability of the findings. Findings highlight the need for additional research to address these limitations so that more definitive conclusions can be drawn to inform SARS-CoV-2 vaccine development and vaccination policies. Funding: Health and Medical Research Fund on COVID-19, Health Bureau of the Government of the Hong Kong SAR.

Artificial intelligence and end user tools to develop a nurse duty roster scheduling system.

Objectives: A nurse duty roster is usually prepared monthly in a hospital ward. It is common for nurses to make duty shift requests prior to scheduling. A ward manager normally spends more than a working day to manually prepare and subsequently to optimally adjust the schedule upon staff requests and hospital policies. This study aimed to develop an automatic nurse roster scheduling system with the use of open-source operational research tools by taking into account the hospital standards and the constraints from nurses. Methods: Artificial intelligence and end user tools operational research tools were used to develop the code for the nurse duty roster scheduling system. To compare with previous research on various heuristics in employee scheduling, the current system was developed on open architecture and adopted with real shift duty requirements in a hospital ward. Results: The schedule can be generated within 1 min under both hard and soft constraint optimization. All hard constraints are fulfilled and most nurse soft constraints could be met. Compared with those schedules prepared manually, the computer-generated schedules were more optimally adjusted as real time interaction among nurses and management personnel. The generated schedules were flexible to cope with daily and hourly duty changes by redeploying ward staff in order to maintain safe staffing levels. Conclusions: An economical but yet highly efficient and user friendly solution to nurse roster scheduling system has been developed and adopted using open-source operational research methodology. The open-source platform is found to perform satisfactorily in scheduling application. The system can be implemented to different wards in hospitals and be regularly updated with new hospital polices and nurse manpower by hospital information personnel with training in artificial intelligence.

A stochastically curtailed single-arm phase II trial design for binary outcomes.

Phase II clinical trials are a critical aspect of the drug development process. With drug development costs ever increasing, novel designs that can improve the efficiency of phase II trials are extremely valuable.Phase II clinical trials for cancer treatments often measure a binary outcome. The final trial decision is generally to continue or cease development. When this decision is based solely on the result of a hypothesis test, the result may be known with certainty before the planned end of the trial. Unfortunately, there is often no opportunity for early stopping when this occurs.Some existing designs do permit early stopping in this case, accordingly reducing the required sample size and potentially speeding up drug development. However, more improvements can be achieved by stopping early when the final trial decision is very likely, rather than certain, known as stochastic curtailment. While some authors have proposed approaches of this form, these approaches have various limitations.In this work we address these limitations by proposing new design approaches for single-arm phase II binary outcome trials that use stochastic curtailment. We use exact distributions, avoid simulation, consider a wider range of possible designs and permit early stopping for promising treatments. As a result, we are able to obtain trial designs that have considerably reduced sample sizes on average.

Positioning imatinib for pulmonary arterial hypertension: A phase I/II design comprising dose finding and single-arm efficacy.

Pulmonary arterial hypertension is an unmet clinical need. Imatinib, a tyrosine kinase inhibitor, 200 to 400 mg daily reduces pulmonary artery pressure and increases functional capacity in this patient group, but is generally poorly tolerated at the higher dose. We have designed an open-label, single-arm clinical study to investigate whether there is a tolerated dose of imatinib that can be better targeted to patients who will benefit. The study consists of two parts. Part 1 seeks to identify the best tolerated dose of Imatinib in the range from 100 and up to 400 mg using a Bayesian Continuous Reassessment Method. Part 2 will measure efficacy after 24 weeks treatment with the best tolerated dose using a Simon's two-stage design. The primary efficacy endpoint is a binary variable. For patients with a baseline pulmonary vascular resistance (PVR) >1000 dynes · s · cm-5, success is defined by an absolute reduction in PVR of ≥300 dynes · s · cm-5 at 24 weeks. For patients with a baseline PVR ≤1000 dynes · s · cm-5, success is a 30% reduction in PVR at 24 weeks. PVR will also be evaluated as a continuous variable by genotype as an exploratory analysis. Evaluating the response to that dose by genotype may inform a prospective biomarker-driven study.

Patient-Derived Nasopharyngeal Cancer Organoids for Disease Modeling and Radiation Dose Optimization.

Effective radiation treatment (RT) for recurrent nasopharyngeal cancers (NPC), featuring an intrinsic hypoxic sub-volume, remains a clinical challenge. Lack of disease-specific in-vitro models of NPC, together with difficulties in establishing patient derived xenograft (PDX) models, have further hindered development of personalized therapeutic options. Herein, we established two NPC organoid lines from recurrent NPC PDX models and further characterized and compared these models with original patient tumors using RNA sequencing analysis. Organoids were cultured in hypoxic conditions to examine the effects of hypoxia and radioresistance. These models were then utilized to determine the radiobiological parameters, such as α/ß ratio and oxygen enhancement ratio (OER), characteristic to radiosensitive normoxic and radioresistant hypoxic NPC, using simple dose-survival data analytic tools. The results were further validated in-vitro and in-vivo, to determine the optimal boost dose and fractionation regimen required to achieve effective NPC tumor regression. Despite the differences in tumor microenvironment due to the lack of human stroma, RNA sequencing analysis revealed good correlation of NPC PDX and organoid models with patient tumors. Additionally, the established models also mimicked inter-tumoral heterogeneity. Hypoxic NPC organoids were highly radioresistant and had high α/ß ratio compared to its normoxic counterparts. In-vitro and in-vivo fractionation studies showed that hypoxic NPC was less sensitive to RT fractionation scheme and required a large bolus dose or 1.4 times of the fractionated dose that was effective against normoxic cells in order to compensate for oxygen deficiency. This study is the first direct experimental evidence to predict optimal RT boost dose required to cause sufficient damage to recurrent hypoxic NPC tumor cells, which can be further used to develop dose-painting algorithms in clinical practice.

A stochastically curtailed two-arm randomised phase II trial design for binary outcomes.

Randomised controlled trials are considered the gold standard in trial design. However, phase II oncology trials with a binary outcome are often single-arm. Although a number of reasons exist for choosing a single-arm trial, the primary reason is that single-arm designs require fewer participants than their randomised equivalents. Therefore, the development of novel methodology that makes randomised designs more efficient is of value to the trials community. This article introduces a randomised two-arm binary outcome trial design that includes stochastic curtailment (SC), allowing for the possibility of stopping a trial before the final conclusions are known with certainty. In addition to SC, the proposed design involves the use of a randomised block design, which allows investigators to control the number of interim analyses. This approach is compared with existing designs that also use early stopping, through the use of a loss function comprised of a weighted sum of design characteristics. Comparisons are also made using an example from a real trial. The comparisons show that for many possible loss functions, the proposed design is superior to existing designs. Further, the proposed design may be more practical, by allowing a flexible number of interim analyses. One existing design produces superior design realisations when the anticipated response rate is low. However, when using this design, the probability of rejecting the null hypothesis is sensitive to misspecification of the null response rate. Therefore, when considering randomised designs in phase II, we recommend the proposed approach be preferred over other sequential designs.

Simplified sigmoidal curve fitting for a 6 MV FFF photon beam of the Halcyon to determine the field size for beam commissioning and quality assurance.

BACKGROUND: An O-ring gantry-type linear accelerator (LINAC) with a 6-MV flattening filter-free (FFF) photon beam, Halcyon, includes a reference beam that contains representative information such as the percent depth dose, profile and output factor for commissioning and quality assurance. However, because it does not provide information about the field size, we proposed a method to determine all field sizes according to all depths for radiation therapy using simplified sigmoidal curve fitting (SCF). METHODS: After mathematical definition of the SCF using four coefficients, the defined curves were fitted to both the reference data (RD) and the measured data (MD). For good agreement between the fitting curve and the profiles in each data set, the field sizes were determined by identifying the maximum point along the third derivative of the fitting curve. The curve fitting included the field sizes for beam profiles of 2 × 2, 4 × 4, 6 × 6, 8 × 8, 10 × 10, 20 × 20 and 28 × 28 cm2 as a function of depth (at 1.3, 5, 10 and 20 cm). The field size results from the RD were compared with the results from the MD using the same condition. RESULTS: All fitting curves show goodness of fit, R2, values that are greater than 0.99. The differences in field size between the RD and the MD were within the range of 0 to 0.2 cm. The smallest difference in the field sizes at a depth of 10 cm, which is a surface-to-axis distance, was reported. CONCLUSION: Application of the SCF method has been proven to accurately capture the field size of the preconfigured RD and the measured FFF photon beam data for the Halcyon system. The current work can be useful for beam commissioning as a countercheck methodology to determine the field size from RD in the treatment planning system of a newly installed Halcyon system and for routine quality assurance to ascertain the correctness of field sizes for clinical use of the Halcyon system.

Targeted Retreatment of Incompletely Recovered Chronic Obstructive Pulmonary Disease Exacerbations with Ciprofloxacin. A Double-Blind, Randomized, Placebo-controlled, Multicenter, Phase III Clinical Trial.

Rationale: Chronic obstructive pulmonary disease (COPD) exacerbations are prone to nonrecovery, but there are no data about the effectiveness of retreatment for these prolonged events. We examined whether further therapy with ciprofloxacin for incompletely resolved COPD exacerbations prolonged the time until the next event.Objectives: To assess whether incompletely recovered COPD exacerbations benefit from additional treatment with ciprofloxacin, at Day 14.Methods: In a multicenter, randomized double-blind placebo-controlled trial, we studied retreatment with oral ciprofloxacin 500 mg or matched placebo twice daily for 7 days in patients with Global Initiative for Chronic Obstructive Lung Disease stage II-IV COPD and persistent symptoms and/or serum C-reactive protein ≥8 mg/L initiated 14 (±3) days after an index COPD exacerbation. The primary outcome was the time to the next exacerbation within a 90-day period.Measurements and Main Results: Among 826 patients screened at four centers, 144 eligible participants with incomplete recovery were randomized to receive ciprofloxacin (n = 72) or placebo (n = 72). Within 90 days of randomization, 57% of the patients in the ciprofloxacin group and 53% in the placebo group experienced one or more exacerbations. The median time to the next exacerbation was 32.5 days (interquartile range 13-50) in the placebo arm and 34 days (interquartile range 17-62) in the ciprofloxacin arm, which was not significantly different (adjusted hazard ratio, 1.07; 95% confidence interval, 0.68-1.68; P = 0.76). No significant differences were seen in quality-of-life scores or lung function between the treatment groups.Conclusions: In patients with persistent symptoms and/or raised C-reactive protein 14 days after a COPD exacerbation, an additional course of ciprofloxacin resulted in no additional benefit compared with placebo. This suggests that nonrecovered exacerbations are not driven by ongoing bacterial infection and may potentially be targeted with antiinflammatory therapy.Clinical trial registered with www.clinicaltrials.gov (NCT02300220).

Two new approaches for the visualisation of models for network meta-analysis.

BACKGROUND: Meta-analysis is a useful tool for combining evidence from multiple studies to estimate a pooled treatment effect. An extension of meta-analysis, network meta-analysis, is becoming more commonly used as a way to simultaneously compare multiple treatments in a single analysis. Despite the variety of approaches available for presenting fitted models, ascertaining an intuitive understanding of these models is often difficult. This is especially challenging in large networks with many different treatments. Here we propose two visualisation methods, so that network meta-analysis models can be more easily interpreted. METHODS: Our methods can be used irrespective of the statistical model or the estimation method used and are grounded in network analysis. We define three types of distance measures between the treatments that contribute to the network. These three distance measures are based on 1) the estimated treatment effects, 2) their standard errors and 3) the corresponding p-values. Then, by using a suitable threshold, we categorise some treatment pairs as being "close" (short distances). Treatments that are close are regarded as "connected" in the network analysis theory. Finally, we group the treatments into communities using standard methods for network analysis. We are then able to identify which parts of the network are estimated to have similar (or different) treatment efficacy and which parts of the network are better identified. We also propose a second method using parametric bootstrapping, where a heat map is used in the visualisation. We use the software R and provide the code used. RESULTS: We illustrate our new methods using a challenging dataset containing 22 treatments, and a previously fitted model for this data. Two communities of treatments that appear to have similar efficacy are identified. Furthermore using our methods we can identify parts of the network that are better (and less well) identified. CONCLUSIONS: Our new visualisation approaches may be used by network meta-analysts to gain an intuitive understanding of the implications of their fitted models. Our visualisation methods may be used informally, to identify the most salient features of the fitted models that can then be reported, or more formally by presenting the new visualisation devices within published reports.

Development and validation of an imaging and clinical scoring system to predict early mortality in spontaneous ruptured hepatocellular carcinoma treated with transarterial embolization.

PURPOSE: To develop and validate a scoring system using a combination of imaging and clinical parameters to predict 30-day mortality in ruptured HCC (rHCC) patients after transarterial embolization (TAE). METHODS: 98 consecutive patients with rHCC who underwent abdominal CT and subsequent TAE between January 2007 and December 2016 were retrospectively reviewed. The CT scans were reviewed by two radiologists blinded to the patient outcome. Clinical parameters including serum bilirubin, albumin, INR, creatinine, and hemoglobin were recorded. Independent risk factors for 30-day mortality after TAE were identified using multivariate binary logistic regression, for development of a scoring system. The scoring system was then validated in 20 patients between January 2017 and May 2018. RESULTS: In the development cohort, bilobar tumor distribution (OR = 29.6), clinical parameters of bilirubin > 2.5 mg/dL (OR = 5.9), and albumin < 30 g/L (OR = 4.1) were independent predictors for 30-day mortality. A 6-point score was derived and yielded area-under-the-receiver-operating-characteristic-curve (AUC) of 0.904. A score ≥ 4 resulted in sensitivity of 80.5% and specificity of 91.2% for 30-day mortality. In the validation cohort, AUC for 30-day mortality was 0.939. A score ≥ 4 resulted in sensitivity of 81.2% and specificity of 88.9%. In both development and validation cohorts, the proposed scoring system was better than biochemical components of Child-Pugh score and serum bilirubin to predict 30-day mortality. CONCLUSION: Imaging and clinical parameters can be combined into a scoring system to accurately predict 30-day mortality after TAE in rHCC patients. The score may help identify and counsel high-risk patients.

Cumulative Effective Dose and Cancer Risk of Pediatric Population in Repetitive Whole-Body Scan Using Dual-Energy X-Ray Absorptiometry.

This study aims to quantitatively evaluate the cumulative effective dose and associated cancer risk of pediatric patients of US and Hong Kong population undergoing repetitive whole-body scans with dual-energy X-ray absorptiometry (DXA) during their diagnosis and follow-up periods. Organ-absorbed doses of pediatric patients undergoing DXA whole-body scan have been computer simulated using patient imaging parameters input to the Monte Carlo software PCXMC. Gender- and age-specific effective doses have been calculated with the simulated organ-absorbed doses using the ICRP-103 approach. The associated radiation-induced cancer risk, expressed as lifetime attributable cancer risk (LAR), has been estimated according to the method introduced in the Biological Effects of Ionizing Radiation VII report. Mathematical fitting for effective dose and for LAR, as a function of age at exposure, has been analytically obtained to quantitatively estimate the cumulated effective dose and LAR for pediatric patients of US and Hong Kong population with repetitive DXA whole-body scan during their follow-up period. The effective dose of a single DXA whole-body scan for patients exposed at the age between 5 and 18 years was calculated as 8.47-17.68 µSv. The corresponding LAR for US and Hong Kong population was between the range of 4.57 × 10-7 and 7.14 × 10-7. The cumulative effective dose of DXA whole-body scan for patients exposed annually at age between 5 and 18 years was calculated as 180 µSv for girls and 168 µSv for boys. The corresponding cumulative LAR for US and Hong Kong population was calculated as 3.77 × 10-6 to 5.48 × 10-6. Girls would be at a statistically significant higher cumulated cancer risk than boys under the same whole-body DXA protocol (p = 0.03). The probability of cumulative LAR for pediatric populations undergoing annual DXA whole-body scan is regarded as minimal. We demonstrate the use of computer simulation and analytic formulation to quantitatively obtain the cumulated effective dose and cancer risk at any age of exposure, which are useful information for medical personnel to track patient radiation dose and to alleviate patients' parents concern about radiation safety in repetitive whole-body scan using DXA.

Tumor Segmentation in Contrast-Enhanced Magnetic Resonance Imaging for Nasopharyngeal Carcinoma: Deep Learning with Convolutional Neural Network.

OBJECTIVES: To evaluate the application of a deep learning architecture, based on the convolutional neural network (CNN) technique, to perform automatic tumor segmentation of magnetic resonance imaging (MRI) for nasopharyngeal carcinoma (NPC). MATERIALS AND METHODS: In this prospective study, 87 MRI containing tumor regions were acquired from newly diagnosed NPC patients. These 87 MRI were augmented to >60,000 images. The proposed CNN network is composed of two phases: feature representation and scores map reconstruction. We designed a stepwise scheme to train our CNN network. To evaluate the performance of our method, we used case-by-case leave-one-out cross-validation (LOOCV). The ground truth of tumor contouring was acquired by the consensus of two experienced radiologists. RESULTS: The mean values of dice similarity coefficient, percent match, and their corresponding ratio with our method were 0.89±0.05, 0.90±0.04, and 0.84±0.06, respectively, all of which were better than reported values in the similar studies. CONCLUSIONS: We successfully established a segmentation method for NPC based on deep learning in contrast-enhanced magnetic resonance imaging. Further clinical trials with dedicated algorithms are warranted.

Failure Analysis for Ultrasound Machines in a Radiology Department after Implementation of Predictive Maintenance Method.

OBJECTIVE: The objective of the study was to perform quantitative failure and fault analysis to the diagnostic ultrasound (US) scanners in a radiology department after the implementation of the predictive maintenance (PdM) method; to study the reduction trend of machine failure; to understand machine operating parameters affecting the failure; to further optimize the method to maximize the machine clinically service time. MATERIALS AND METHODS: The PdM method has been implemented to the 5 US machines since 2013. Log books were used to record machine failures and their root causes together with the time spent on repair, all of which were retrieved, categorized, and analyzed for the period between 2013 and 2016. RESULTS: There were a total of 108 cases of failure occurred in these 5 US machines during the 4-year study period. The average number of failure per month for all these machines was 2.4. Failure analysis showed that there were 33 cases (30.5%) due to software, 44 cases (40.7%) due to hardware, and 31 cases (28.7%) due to US probe. There was a statistically significant negative correlation between the time spent on regular quality assurance (QA) by hospital physicists with the time spent on faulty parts replacement over the study period (P = 0.007). However, there was no statistically significant correlation between regular QA time and total yearly breakdown case (P = 0.12), although there has been a decreasing trend observed in the yearly total breakdown. CONCLUSION: There has been a significant improvement on the machine failure of US machines attributed to the concerted effort of sonographers and physicists in our department to practice the PdM method, in that system component repair time has been reduced, and a decreasing trend in the number of system breakdown has been observed.

Opportunistic screening for osteoporosis in abdominal computed tomography for Chinese population.

This study assessed the possibility of diagnosing and excluding osteoporosis with routine abdominal CT scans in a Chinese population who underwent both DXA and CT for unrelated reasons. Statistical correlation was made between the HU measured of the spine on CT and various parameters on DXA. Diagnostic cutoff points in terms of HU were established for the diagnosis (≤ 136 HU) and exclusion (≥ 175 HU) of osteoporosis on sagittal reformatted images. There was excellent positive and negative predictive value for the DXA-defined diagnostic subgroups and were also comparable with previous studies in Caucasian populations. The authors exhort radiologists to report these incidental findings to facilitate early detection and treatment of osteoporosis in unsuspecting patients to prevent fractures and related complications. PURPOSE: The suspicion for osteoporosis can be raised in diagnostic computed tomography of the abdomen performed for other indications. We derived cutoff thresholds for the attenuation value of the lumbar spinal vertebrae (L1-5) in Hounsfield units (HU) in a Chinese patient population to facilitate implementation of opportunistic screening in radiologists. METHODS: We included 109 Chinese patients who concomitantly underwent abdominal CT and dual X-ray absorptiometry (DXA) within 6 months between July 2014 and July 2017 at a university hospital in Hong Kong. Images were retrospectively reviewed on sagittal reformats, and region-of-interest (ROI) markers were placed on the anterior portion of each of the L1-L5 vertebra to measure the HU. The mean values of CT HU were then compared with the bone mineral density (BMD) and T-score obtained by DXA. Receiver operator characteristic (ROC) curves were generated to determine diagnostic cutoff thresholds and their sensitivity and specificity values. RESULTS: The mean CT HU differed significantly (p < 0.01) for the three DXA-defined BMD categories of osteoporosis (97 HU), of osteopenia (135 HU), and of normal individuals (230 HU). There was good correlation between the mean CT HU and BMD and T-score (Pearson coefficient of 0.62 and 0.61, respectively, p < 0.001). The optimal cutoff point for exclusion of osteoporosis or osteopenia was HU ≥ 175 with negative predictive value as 98.9% and with area under curve (AUC) of ROC curve as 0.97. The optimal cutoff point for diagnosis of osteoporosis was HU ≤ 136 with positive predictive value as 81.2% and with AUC of ROC curve as 0.86. CONCLUSION: This is the first study on osteoporosis diagnosis with routine CT abdominal scans in Chinese population. The cutoff values were comparable with previous studies in Caucasian populations suggesting generalizability. Radiologists should consider routinely reporting these opportunistic findings to facilitate early detection and treatment of osteoporosis to prevent fractures and related complications.