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ABSTRACTThis study contributes an efficient method for assessing the structural integrity of concrete bridges by collecting images of surface cracks and defects with drones. The use of drones to gather crack samples reduces human error and is appropriate in adverse working conditions and short-duration examinations. This work introduces a new POI (Points of Interest) flying algorithm for typical flight paths, based on the drone flying criteria of safe viewing distance and the POI concept. In this research, the flight controller of the drone was combined with a Raspberry Pi4 to build and alter a typical flight path suitable for the mission, with the addition of interactive features that control flight mode switching, separation, and automatic return to the original orbit to meet expertly specified POIs. In other words, as drones approach a region requiring image capture, they automatically move to a safe distance to photograph cracks and then return to their predetermined orbit. An experiment at the Cau May bridge demonstrates that the path-planning algorithms created on an embedded computer can successfully coordinate with the flight controller switching three times to hover and zoom in on fractures during the inspection.

Introduction Diabetic ketoacidosis (DKA) is a potentially life-threatening diabetic complication. Despite the high prevalence of DKA and the substantial associated healthcare burden, limited research on strategies to improve outcomes currently exists.Thiamine (vitamin B1) is a cofactor of pyruvate dehydrogenase, which plays a key role in aerobic glucose metabolism. Thiamine deficiency is common in patients with DKA, resulting in a shift to anaerobic metabolism and hyperlactatemia, which can prolong and complicate recovery. Therefore, we hypothesise that thiamine administration will improve aerobic metabolism and lead to faster resolution of acidemia in patients with DKA.Methods and analysis In this single centre, double-blind, randomised, placebo-controlled, parallel group interventional trial, 100 patients admitted to the hospital with DKA will be randomised to receive either intravenous thiamine (200 mg in 50 mL 0.9% saline) or placebo (0.9% saline identical in appearance and volume) two times per day for 2 days. The primary outcome will be the change in bicarbonate level over 24 hours as compared between the two treatment groups. Additional secondary outcomes include the change over time in anion gap, lactate levels, oxygen consumption by circulating mononuclear cells, intensive care unit and hospital length-of-stay and hospital resource usage when comparing the two study arms.Ethics and dissemination This trial was approved by the Committee on Clinical Investigations, the institutional review board of Beth Israel Deaconess Medical Center (protocol number 2018P000475). Findings will be disseminated through peer-reviewed publications and professional conference presentations.Trial registration number NCT03717896; clinicaltrials.gov.

ABSTRACT: Background: Left ventricular ejection fraction (LVEF) is the most commonly clinically used imaging parameter for assessing cancer therapy-related cardiac dysfunction (CTRCD). However, LVEF declines may occur late, after substantial injury. This study sought to investigate cardiovascular magnetic resonance (CMR) imaging markers of subclinical cardiac injury in a miniature swine model. Methods: Female Yucatan miniature swine (n = 14) received doxorubicin (2 mg/kg) every 3 weeks for 4 cycles. CMR, including cine, tissue characterization via T1 and T2 mapping, and late gadolinium enhancement (LGE) were performed on the same day as doxorubicin administration and 3 weeks after the final chemotherapy cycle. In addition, magnetic resonance spectroscopy (MRS) was performed during the 3 weeks after the final chemotherapy in 7 pigs. A single CMR and MRS exam were also performed in 3 Yucatan miniature swine that were age- and weight-matched to the final imaging exam of the doxorubicin-treated swine to serve as controls. CTRCD was defined as histological early morphologic changes, including cytoplasmic vacuolization and myofibrillar loss of myocytes, based on post-mortem analysis of humanely euthanized pigs after the final CMR exam. Results: Of 13 swine completing 5 serial CMR scans, 10 (77%) had histological evidence of CTRCD. Three animals had neither histological evidence nor changes in LVEF from baseline. No absolute LVEF

ABSTRACTCrack detection is one of the crucial aspects of bridge evaluation and maintenance. Several existing image-based methods require capturing the bridge surface and extracting crack features to detect the crack. However, in some positions such as the space under the bridge and piers, it is difficult to capture crack images. This paper aims to apply a method to detect cracks on the bridge surface by using a drone that can capture images in challenging positions. The video recorded from the drone will be automatically identified the cracks by employing the deep learning method. Deep learning is designed for training and testing the dataset with 51.000 images, each image sized 244 × 244. The deep learning method shows the feasibility of detecting the cracks in the transport facility. This is supported by the high accuracy of the experimental results of 95.19%. In addition, the tool can assign an ID containing information to each crack from video so that these cracks can then be mounted on a 3D map of the bridge for research on crack development over time in the task of assessing the health of bridges.

Abstract Purpose To develop and evaluate MyoMapNet, a rapid myocardial T1 mapping approach that uses fully connected neural networks (FCNN) to estimate T1 values from four T1-weighted images collected after a single inversion pulse in four heartbeats (Look-Locker, LL4). Method We implemented an FCNN for MyoMapNet to estimate T1 values from a reduced number of T1-weighted images and corresponding inversion-recovery times. We studied MyoMapNet performance when trained using native, post-contrast T1, or a combination of both. We also explored the effects of number of T1-weighted images (four and five) for native T1. After rigorous training using in-vivo modified Look-Locker inversion recovery (MOLLI) T1 mapping data of 607 patients, MyoMapNet performance was evaluated using MOLLI T1 data from 61 patients by discarding the additional T1-weighted images. Subsequently, we implemented a prototype MyoMapNet and LL4 on a 3 T scanner. LL4 was used to collect T1 mapping data in 27 subjects with inline T1 map reconstruction by MyoMapNet. The resulting T1 values were compared to MOLLI. Results MyoMapNet trained using a combination of native and post-contrast T1-weighted images had excellent native and post-contrast T1 accuracy compared to MOLLI. The FCNN model using four T1-weighted images yields similar performance compared to five T1-weighted images, suggesting that four T1 weighted images may be sufficient. The inline implementation of LL4 and MyoMapNet enables successful acquisition and reconstruction of T1 maps on the scanner. Native and post-contrast myocardium T1 by MOLLI and MyoMapNet was 1170 ± 55 ms vs. 1183 ± 57 ms (P = 0.03), and 645 ± 26 ms vs. 630 ± 30 ms (P = 0.60), and native and post-contrast blood T1 was 1820 ± 29 ms vs. 1854 ± 34 ms (P = 0.14), and 508 ± 9 ms vs. 514 ± 15 ms (P = 0.02), respectively. Conclusion A FCNN, trained using MOLLI data, can estimate T1 values from only four T1-weighted images. MyoMapNet enables myocardial T1 mapping in four heartbeats with similar accuracy as MOLLI with inline map reconstruction.

Delirium is a common postoperative complication among older patients with many adverse outcomes. Due to a lack of validated biomarkers, prediction and monitoring of delirium by biological testing is not currently feasible. Circulating proteins in cerebrospinal fluid (CSF) may reflect biological processes causing delirium. Our goal was to discover and investigate candidate protein biomarkers in preoperative CSF that were associated with the development of postoperative delirium in older surgical patients. We employed a nested case–control study design coupled with high multiplex affinity proteomics analysis to measure 1305 proteins in preoperative CSF. Twenty-four matched delirium cases and non-delirium controls were selected from the Healthier Postoperative Recovery (HiPOR) cohort, and the associations between preoperative protein levels and postoperative delirium were assessed using t-test statistics with further analysis by systems biology to elucidate delirium pathophysiology. Proteomics analysis identified 32 proteins in preoperative CSF that significantly associate with delirium (t-test p < 0.05). Due to the limited sample size, these proteins did not remain significant by multiple hypothesis testing using the Benjamini–Hochberg correction and q-value method. Three algorithms were applied to separate delirium cases from non-delirium controls. Hierarchical clustering classified 40/48 case–control samples correctly, and principal components analysis separated 43/48. The receiver operating characteristic curve yielded an area under the curve [95% confidence interval] of 0.91 [0.80–0.97]. Systems biology analysis identified several key pathways associated with risk of delirium: inflammation, immune cell migration, apoptosis, angiogenesis, synaptic depression and neuronal cell death. Proteomics analysis of preoperative CSF identified 32 proteins that might discriminate individuals who subsequently develop postoperative delirium from matched control samples. These proteins are potential candidate biomarkers for delirium and may play a role in its pathophysiology.

Abstract Background Chronic pain has emerged as a disease in itself, affecting a growing number of people. Effective patient-provider communication is central to good pain management because pain can only be understood from the patient’s perspective. We aimed to develop a user-centered tool to improve patient-provider communication about chronic pain and assess its feasibility in real-world settings in preparation for further evaluation and distribution. Methods To identify and prioritize patient treatment goals for chronic pain, strategies to improve patient-provider communication about chronic pain, and facilitate implementation of the tool, we conducted nominal group technique meetings and card sorting with patients with chronic pain and experienced providers (n = 12). These findings informed the design of the PainAPP tool. Usability and beta-testing with patients (n = 38) and their providers refined the tool and assessed its feasibility, acceptability, and preliminary impact. Results Formative work revealed that patients felt neither respected nor trusted by their providers and focused on transforming providers’ negative attitudes towards them, whereas providers focused on gathering patient information. PainAPP incorporated areas prioritized by patients and providers: assessing patient treatment goals and preferences, functional abilities and pain, and providing patients tailored education and an overall summary that patients can share with providers. Beta-testing involved 38 patients and their providers. Half of PainAPP users shared their summaries with their providers. Patients rated PainAPP highly in all areas. All users would recommend it to others with chronic pain; nearly all trusted the information and said it helped them think about my treatment goals (94%), understand my chronic pain (82%), make the most of my next doctor’s visit (82%), and not want to use opioids (73%). Beta-testing revealed challenges delivering the tool and summary report to patients and providers in a timely manner and obtaining provider feedback. Conclusions PainAPP appears feasible for use, but further adaptation and testing is needed to assess its impact on patients and providers. Trial registration This study was approved by the University of New England Independent Review Board for the Protection of Human Subjects in Research (012616–019) and was registered with ClinicalTrials.gov (protocol ID: NCT03425266) prior to enrollment. The trial was prospectively registered and was approved on February 7, 2018.

BackgroundGuidelines recommend including the patient's values and preferences when choosing treatment for severe aortic stenosis (sAS). However, little is known about what matters most to patients as they develop treatment preferences. Our objective was to identify, prioritize, and organize patient-reported goals and features of treatment for sAS.MethodsThis multi-center mixed-methods study conducted structured focus groups using the nominal group technique to identify patients' most important treatment goals and features. Patients separately rated and grouped those items using card sorting techniques. Multidimensional scaling and hierarchical cluster analyses generated a cognitive map and clusters.Results51 adults with sAS and 3 caregivers with experience choosing treatment (age 36-92 years) were included. Participants were referred from multiple health centers across the U.S. and online. Eight nominal group meetings generated 32 unique treatment goals and 46 treatment features, which were grouped into 10 clusters of goals and 11 clusters of features. The most important clusters were: 1) trust in the healthcare team, 2) having good information about options, and 3) long-term outlook. Other clusters addressed the need for and urgency of treatment, being independent and active, overall health, quality of life, family and friends, recovery, homecare, and the process of decision-making.ConclusionsThese patient-reported items addressed the impact of the treatment decision on the lives of patients and their families from the time of decision-making through recovery, homecare, and beyond. Many attributes had not been previously reported for sAS. The goals and features that patients' value, and the relative importance that they attach to them, differ from those reported in clinical trials and vary substantially from one individual to another. These findings are being used to design a shared decision-making tool to help patients and their clinicians choose a treatment that aligns with the patients' priorities.Trial registrationClinicalTrials.gov, Trial ID: NCT04755426, Trial URL https://clinicaltrials.gov/ct2/show/NCT04755426.

ObjectiveAs there is significant heterogeneity in the weight loss response to pharmacotherapy, one of the most important clinical questions in obesity medicine is how to predict an individual’s response to pharmacotherapy. The present study examines patterns of weight loss among overweight and obese women who demonstrated early robust response to twice daily exenatide treatment compared to those treated with hypocaloric diet and matched placebo injections.MethodsWe randomized 182 women (BMI 25-48 kg/m2) to treatment with exenatide alone or matched placebo injections plus hypocaloric diet. In both treatment groups, women who demonstrated ≥ 5% weight loss at 12 weeks were characterized as high responders and those who lost ≥10% of body weight were classified as super responders. Our primary outcome was long-term change in body weight among early high responders to either treatment. An exploratory metabolomic analysis was also performed.ResultsWe observed individual variability in weight loss with both exenatide and hypocaloric diet plus placebo injections. There was a trend toward a higher percentage of subjects who achieved ≥ 5% weight loss with exenatide compared to diet (56% of those treated with exenatide, 76% of those treated with diet, p = 0.05) but no significant difference in those who achieved ≥ 10% weight loss (23% of individuals treated with exenatide and 36% of those treated with diet, p = 0.55). In both treatment groups, higher weight loss at 3 months of treatment predicted super responder status (diet p=0.0098, exenatide p=0.0080). Both treatment groups also demonstrated similar peak weight loss during the study period. We observed lower cysteine concentrations in the exenatide responder group (0.81 vs 0.48 p < 0.0001) and a trend toward higher levels of serotonin, aminoisobutyric acid, anandamide, and sarcosine in the exenatide super responder group.ConclusionIn a population of early high responders, longer term weight loss with exenatide treatment is similar to that achieved with a hypocaloric diet.Clinical Trial Registrationwww.clinicaltrialsgov, identifier NCT01590433.

BackgroundAlthough analgesics are initiated on hospital discharge in millions of adults each year, studies quantifying the risks of opioids and nonsteroidal anti-inflammatory drugs (NSAIDs) among older adults during this transition are limited. We sought to determine the incidence and risk of post-discharge adverse events among older adults with an opioid claim in the week after hospital discharge, compared to those with NSAID claims only.Methods and findingsWe performed a retrospective cohort study using a national sample of Medicare beneficiaries age 65 and older, hospitalized in United States hospitals in 2016. We excluded beneficiaries admitted from or discharged to a facility. We derived a propensity score that included over 100 factors potentially related to the choice of analgesic, including demographics, diagnoses, surgeries, and medication coadministrations. Using 3:1 propensity matching, beneficiaries with an opioid claim in the week after hospital discharge (with or without NSAID claims) were matched to beneficiaries with an NSAID claim only. Primary outcomes included death, healthcare utilization (emergency department [ED] visits and rehospitalization), and a composite of known adverse effects of opioids or NSAIDs (fall/fracture, delirium, nausea/vomiting, complications of slowed colonic motility, acute renal failure, and gastritis/duodenitis) within 30 days of discharge. After propensity matching, there were 13,385 beneficiaries in the opioid cohort and 4,677 in the NSAID cohort (mean age: 74 years, 57% female). Beneficiaries receiving opioids had a higher incidence of death (1.8% versus 1.1%; relative risk [RR] 1.7 [1.3 to 2.3], p < 0.001, number needed to harm [NNH] 125), healthcare utilization (19.0% versus 17.4%; RR 1.1 [1.02 to 1.2], p = 0.02, NNH 59), and any potential adverse effect (25.2% versus 21.3%; RR 1.2 [1.1 to 1.3], p < 0.001, NNH 26), compared to those with an NSAID claim only. Specifically, they had higher relative risk of fall/fracture (4.5% versus 3.4%; RR 1.3 [1.1 to 1.6], p = 0.002), nausea/vomiting (9.2% versus 7.3%; RR 1.3 [1.1 to 1.4], p < 0.001), and slowed colonic motility (8.0% versus 6.2%; RR 1.3 [1.1 to 1.4], p < 0.001). Risks of delirium, acute renal failure, and gastritis/duodenitis did not differ between groups. The main limitation of our study is the observational nature of the data and possibility of residual confounding.ConclusionsOlder adults filling an opioid prescription in the week after hospital discharge were at higher risk for mortality and other post-discharge adverse outcomes compared to those filling an NSAID prescription only.

Abstract Introduction The Role of Inflammation after Surgery for Elders study correlates novel inflammatory markers measured in blood, cerebrospinal fluid (CSF) assays, and [11C]‐PBR28 positron‐emission tomography imaging. Methods This study involved a prospective cohort design with patients who underwent elective hip and knee arthroplasty under spinal anesthesia. Sixty‐five adults participated with their family members. Inflammatory biomarker assays were measured preoperatively on day 1 and postoperatively at one month. Results On average, participants were 75 years old, and 72% were female. 54% underwent total knee arthroplasty, and 46% underwent total hip arthroplasty. The mean Modified Mini‐Mental State (3MS) Examination score was 89.3; four patients (6%) scored ≤77 points. Plasma assays were completed in 63 (97%) participants, cerebrospinal fluid assays in 61 (94%), and PET imaging in 44 (68%). Discussion This complex study presents an innovative effort to correlate peripheral and central inflammatory biomarkers before and after major surgery in older adults. Strengths include collecting concurrent blood, cerebrospinal fluid, and positron‐emission tomography with detailed clinical characterization of delirium, cognition, and functional status.

Background: The Sequential Organ Failure Assessment (SOFA) score is a commonly used severity-of-illness score in cardiac arrest research. Due to its nature, the SOFA score often has missing data. How much data is missing and how that missing data is handled is unknown. Objectives: We conducted a scoping review on cardiac arrest studies using SOFA, focusing on missing data. Data sources: PubMed, Embase, and Web of Science. Study selection: All English-language peer-reviewed studies of cardiac arrest with SOFA as an outcome or exposure were included. Data extraction: For each study, quantity of missing SOFA data, analytic strategy to handle missing SOFA variables, whether/to what degree mortality influenced the amount of missing SOFA scores), SOFA score modifications, and number of SOFA measurements was extracted. Data synthesis: We included 66 studies published between 2006–2019. Five studies were randomized controlled trials, 26 were prospective cohort studies, and 25 were retrospective cohort studies. SOFA was used as an outcome in 36 (55%) and a primary outcome in 10 (15%). Nine studies (14%) mentioned the quantity of missing SOFA data, which ranged from 0 to 76% (median: 10% [IQR: 6%, 42%]). Twenty-seven (41%) studies reported a method to handle missing SOFA. The most common method used excluded subjects with missing data (81%). In the 50 studies using serial SOFA scores, 11 (22%) documented mortality prior to SOFA measurement; which ranged from 3% to 76% (median: 12% [IQR: 6%–35%]). Conclusions: Missing data is common in cardiac arrest research using SOFA scores. Variability exists in reporting and handling missing SOFA variables.

BACKGROUND:The pattern of myocardial fibrosis differs significantly between different cardiomyopathies. Fibrosis in hypertrophic cardiomyopathy (HCM) is characteristically as patchy and regional but in dilated cardiomyopathy (DCM) as diffuse and global. We sought to investigate if texture analyses on myocardial native T1 mapping can differentiate between fibrosis patterns in patients with HCM and DCM. METHODS:We prospectively acquired native myocardial T1 mapping images for 321 subjects (55±15 years, 70% male): 65 control, 116 HCM, and 140 DCM patients. To quantify different fibrosis patterns, four sets of texture descriptors were used to extract 152 texture features from native T1 maps. Seven features were sequentially selected to identify HCM- and DCM-specific patterns in 70% of data (training dataset). Pattern reproducibility and generalizability were tested on the rest of data (testing dataset) using support vector machines (SVM) and regression models. RESULTS:Pattern-derived texture features were capable to identify subjects in HCM, DCM, and controls cohorts with 202/237(85.2%) accuracy of all subjects in the training dataset using 10-fold cross-validation on SVM (AUC = 0.93, 0.93, and 0.93 for controls, HCM and DCM, respectively), while pattern-independent global native T1 mapping was poorly capable to identify those subjects with 121/237(51.1%) accuracy (AUC = 0.78, 0.51, and 0.74) (P

Abstract Background We sought to determine the effects of alternative resuscitation strategies on microcirculatory perfusion and examine any association between microcirculatory perfusion and mortality in sepsis. Methods This was a prospective, formally designed substudy of participants in the Protocolized Care in Early Septic Shock (ProCESS) trial. We recruited from six sites with the equipment and training to perform these study procedures. All subjects were adults with septic shock, and each was assigned to alternative resuscitation strategies. The two main analyses assessed (1) the impact of resuscitation strategies on microcirculatory perfusion parameters and (2) the association of microcirculatory perfusion with 60-day in-hospital mortality. We measured sublingual microcirculatory perfusion using sidestream dark field in vivo video microscopy at the completion of the 6-h ProCESS resuscitation protocol and then again at 24 and 72 h. Results We enrolled 207 subjects (demographics were similar to the overall ProCESS cohort) and observed 40 (19.3%) deaths. There were no differences in average perfusion characteristics between treatment arms. Analyzing the relationship between microcirculatory perfusion and mortality, we found an association between vascular density parameters and mortality. Total vascular density (beta = 0.006, p

Abstract Background Low scar-to-blood contrast in late gadolinium enhanced (LGE) MRI limits the visualization of scars adjacent to the blood pool. Nulling the blood signal improves scar detection but results in lack of contrast between myocardium and blood, which makes clinical evaluation of LGE images more difficult. Methods GB-LGE contrast is achieved through partial suppression of the blood signal using T2 magnetization preparation between the inversion pulse and acquisition. The timing parameters of GB-LGE sequence are determined by optimizing a cost-function representing the desired tissue contrast. The proposed 3D GB-LGE sequence was evaluated using phantoms, human subjects (n = 45) and a swine model of myocardial infarction (n = 5). Two independent readers subjectively evaluated the image quality and ability to identify and localize scarring in GB-LGE compared to black-blood LGE (BB-LGE) (i.e., with complete blood nulling) and conventional (bright-blood) LGE. Results GB-LGE contrast was successfully generated in phantoms and all in-vivo scans. The scar-to-blood contrast was improved in GB-LGE compared to conventional LGE in humans (1.1 ± 0.5 vs. 0.6 ± 0.4, P

Abstract Background More than 1 in 7 patients with human immunodeficiency virus (HIV) infection in the United States are unaware of their serostatus despite recommendations of US agencies that all adults through age 65 be screened for HIV at least once. To facilitate universal screening, an electronic medical record (EMR) reminder was created for our primary care practice. Screening rates before and after implementation were assessed to determine the impact of the reminder on screening rates. Methods A retrospective cohort analysis was performed for patients age 18–65 with visits between January 1, 2012-October 30, 2014. EMR databases were examined for HIV testing and selected patient characteristics. We evaluated the probability of HIV screening in unscreened patients before and after the reminder and used a multivariable generalized linear model to test the association between likelihood of HIV testing and specific patient characteristics. Results Prior to the reminder, the probability of receiving an HIV test for previously unscreened patients was 15.3%. This increased to 30.7% after the reminder (RR 2.02, CI 1.95–2.09, p

Background . Most people with multiple sclerosis (MS) want to be involved in medical decision making about disease-modifying therapies (DMTs), but new approaches are needed to overcome barriers to participation. Objectives . We sought to develop a shared decision-making (SDM) tool for MS DMTs, evaluate patient and provider responses to the tool, and address challenges encountered during development to guide a future trial. Methods . We created a patient-centered design process informed by image theory to develop the MS-SUPPORT SDM tool. Development included semistructured interviews and alpha and beta testing with MS patients and providers. Beta testing assessed dissemination and clinical integration strategies, decision-making processes, communication, and adherence. Patients evaluated the tool before and after a clinic visit. Results . MS-SUPPORT combines self-assessment with tailored feedback to help patients identify their treatment goals and preferences, correct misperceptions, frame decisions, and promote adherence. MS-SUPPORT generates a personal summary of their responses that patients can share with their provider to facilitate communication. Alpha testing (14 patients) identified areas needing improvement, resulting in reorganization and shortening of the tool. MS-SUPPORT was highly rated in beta testing (15 patients, 4 providers) on patient-provider communication, patient preparation, adherence, and other endpoints. Dissemination through both patient and provider networks appeared feasible. All patient testers wanted to share the summary report with their provider, but only 60% did. Limitations . Small sample size, no comparison group. Conclusions . The development process resulted in a patient-centered SDM tool for MS that may facilitate patient involvement in decision making, help providers understand their patients’ preferences, and improve adherence, though further testing is needed. Beta testing in real-world conditions was critical to prepare the tool for future testing and inform the design of future studies.

Objectives: We sought to determine the rate of response to hepatitis B (HBV) vaccination among HIV-infected adults in Vietnam. Methods: We retrospectively abstracted data from a cohort of HIV-infected adults who had received HBV vaccine at an HIV clinic in Hanoi. We examined demographic, clinical and laboratory factors for associations with development of a protective antibody (Ab) response following vaccination (defined as ‘responders’ with anti-HBs >10 IU/L). Results: Out of 302 HIV-infected patients who completed the vaccine series and follow-up serology testing, 189 (62.6%) had a positive protective Ab response. Female patients had a higher response rate compared to male patients (71.4% vs 56.8%, P=0.01). Among responders, mean CD4 T cell count was 309 cells/μL as compared to 204 cells/μL in non-responders (P

PURPOSEWe aimed to examine current practice patterns of international thoracic radiologists regarding radiation dose management in adult thoracic computed tomography (CT) examinations. MATERIALS AND METHODSAn electronic questionnaire was sent to 800 members of five thoracic radiology societies in North America, Europe, Asia, and Latin America addressing radiation dose training and education, standard kVp and mAs settings for thoracic CT, dose reduction practices, clinical scenarios, and demographics. RESULTSOf the 800 radiologists, 146 responded to our survey. Nearly half (66/146, 45% [95% confidence interval, 37%–53%]) had no formal training in dose reduction, with “self-study of the literature” being the most common form of training (54/146, 37% [29%–45%]). One hundred and seventeen (80% [74%–87%]) had automatic exposure control, and 76 (65% [56%–74%]) used it in all patients. Notably, most respondents (89% [84%–94%]) used a 120 to 125 kVp standard setting, whereas none used 140 kVp. The most common average dose-length-product (DLP) value was 150 to 249 mGy.cm (75/146, 51% [43%–59%]), and 59% (51%–67%) delivered less than 250 mGy.cm in a 70 kg patient. There was a tendency towards higher DLP values with multidetector-row CT. Age, gender, and pregnancy were associated more with dose reduction than weight and clinical indication. CONCLUSIONEfforts for reducing patient radiation dose are highly prevalent among thoracic radiologists. Areas for improvement include reduction of default tube current settings, reduction of anatomical scan coverage, greater use of automatic exposure control, and eventually, reduction of current reference dose values. Our study emphasizes the need for international guidelines to foster greater conformity in dose reduction by thoracic radiologists.

Smoothing methods that use basis functions with penalization can be formulated as fits in a mixed model framework. One of the major benefits is that software for mixed model analysis can be used for smoothing. We illustrate this for several smoothing models such as additive and varying coefficient models for both S-PLUS and SAS software. Code for each of the illustrations is available on the Internet.