Patient preference for commonly-used, head and neck cancer-specific quality of life questionnaires in the follow-up setting (Determin): A multi-centre randomised controlled trial and mixed methods study.

BACKGROUND: Quality of life (QoL) assessment forms an integral part of modern cancer care and research. The aim of this study is to determine patients' preferences and willingness to complete commonly used head-and-neck cancer (HNC) QoL questionnaires (QLQs) in routine follow-up clinics. METHODS: This is a randomised control trial of 583 subjects from 17 centres during follow-up after treatment for oral, oropharyngeal or laryngeal cancer. Subjects completed three structured validated questionnaires: EORTC QLQ-HN35; FACT-HN and UW-QOL, and an unstructured patient-generated list. The order of questionnaire presentation was randomised, and subjects were stratified by disease site and stage. Patients self-rated the questionnaires they found most helpful to communicate their health concerns to their clinicians. RESULTS: Of the 558 respondents, 82% (457) found QLQs useful to communicate their health concerns to their clinician (OR = 15.76; 95% CI 10.83-22.94). Patients preferred the structured disease-specific instruments (OR 8.79; 95% CI 5.99-12.91), while the open list was the most disliked (OR = 4.25; 95% CI 3.04-5.94). There was no difference in preference by treatment modality. More women preferred the FACT-HN (OR = 3.01, 95% CI 1.05-8.62), and patients under 70 preferred EORTC QLQ-HN35 (OR = 3.14, 95% CI 1.3-7.59). However, only 55% of patients expressed preference to complete questionnaires routinely at the clinic. CONCLUSIONS: Most patients found QLQs helpful during their follow-up and 55% supported routine questionnaires in follow-up clinics. Males and people over 70 years old were the least willing to complete the routine questionnaires and preferred shorter questionnaires (e.g., UW-QOL). Women preferred FACT-HN, and younger patients preferred EORTC QLQ-HN35. Reasons for the reluctance to complete questionnaires require elucidation.

Demystifying the Black Box: The Importance of Interpretability of Predictive Models in Neurocritical Care.

Neurocritical care patients are a complex patient population, and to aid clinical decision-making, many models and scoring systems have previously been developed. More recently, techniques from the field of machine learning have been applied to neurocritical care patient data to develop models with high levels of predictive accuracy. However, although these recent models appear clinically promising, their interpretability has often not been considered and they tend to be black box models, making it extremely difficult to understand how the model came to its conclusion. Interpretable machine learning methods have the potential to provide the means to overcome some of these issues but are largely unexplored within the neurocritical care domain. This article examines existing models used in neurocritical care from the perspective of interpretability. Further, the use of interpretable machine learning will be explored, in particular the potential benefits and drawbacks that the techniques may have when applied to neurocritical care data. Finding a solution to the lack of model explanation, transparency, and accountability is important because these issues have the potential to contribute to model trust and clinical acceptance, and, increasingly, regulation is stipulating a right to explanation for decisions made by models and algorithms. To ensure that the prospective gains from sophisticated predictive models to neurocritical care provision can be realized, it is imperative that interpretability of these models is fully considered.

Influence of Patient Demographics on Optimal Cerebral Perfusion Pressure Following Traumatic Brain Injury.

The relationship between optimal cerebral perfusion pressure (CPPopt) and patient characteristics has yet to be defined but could have significant implications for future guidelines recommending cerebral perfusion pressure (CPP) targets.Data from 36 traumatic brain injured patients admitted to neurological intensive care were analysed retrospectively. Linear mixed effects (LME) analysis was performed using an unadjusted-adjusted approach.Clinical characteristics with p < 0.10 were included in the adjusted model. A second adjusted model which included all variables of interest was created. Model fit was assessed using the root-mean-square error (RMSE).The adjusted model included time from initiation of intracranial pressure (ICP) monitoring (estimate = 0.00292, p < 0.001), age (estimate = -0.211, p = 0.0750) and the presence of diffuse axonal injury (DAI) (estimate = -35.5, p < 0.001). The RMSE of this model was 8.11 mmHg. The RMSE of the model containing all variables was 8.09 mmHg.Time, age and the presence of DAI may be important predictors of CPPopt. The models were too inaccurate at predicting CPPopt for employment in clinical practice but warrant further investigation. CPPopt is a dynamic measurement influenced by many factors, supporting the utility of investigating the feasibility of CPPopt-guided therapy.

Evaluation of Software for Automated Measurement of Adherence to ICP-Monitoring Threshold Guideline.

Challenges inherent in clinical guideline development include a long time lag between the key results and incorporation into best practice and the qualitative nature of adherence measurement, meaning it will have no directly measurable impact. To address these issues, a framework has been developed to automatically measure adherence by clinicians in neurological intensive care units to the Brain Trauma Foundation's intracranial pressure (ICP)-monitoring guidelines for severe traumatic brain injury (TBI).The framework processes physiological and treatment data taken from the bedside, standardises the data as a set of process models, then compares these models against similar process models constructed from published guidelines. A similarity metric (i.e. adherence measure) between the two models is calculated, composed of duration and scale of non-adherence.In a pilot clinical validation test, the framework was applied to physiological/treatment data from three TBI patients exhibiting ICP secondary insults at a local neuro-centre where clinical experts coded key clinical interventions/decisions about patient management.The framework identified non-adherence with respect to drug administration in one patient, with a spike in non-adherence due to an inappropriately high dosage; a second patient showed a high severity of guideline non-adherence; and a third patient showed non-adherence due to a low number of associated events and treatment annotations.

Time Series Analysis and Prediction of Intracranial Pressure Using Time-Varying Dynamic Linear Models.

Intracranial pressure (ICP) monitoring is a key clinical tool in the assessment and treatment of patients in a neuro-intensive care unit (neuro-ICU). As such, a deeper understanding of how an individual patient's ICP can be influenced by therapeutic interventions could improve clinical decision-making. A pilot application of a time-varying dynamic linear model was conducted using the BrainIT dataset, a multi-centre European dataset containing temporaneous treatment and vital-sign recordings. The study included 106 patients with a minimum of 27 h of ICP monitoring. The model was trained on the first 24 h of each patient's ICU stay, and then the next 2 h of ICP was forecast. The algorithm enabled switching between three interventional states: analgesia, osmotic therapy and paralysis, with the inclusion of arterial blood pressure, age and gender as exogenous regressors. The overall median absolute error was 2.98 (2.41-5.24) mmHg calculated using all 106 2-h forecasts. This is a novel technique which shows some promise for forecasting ICP with an adequate accuracy of approximately 3 mmHg. Further optimisation is required for the algorithm to become a usable clinical tool.

Use of Direct Intracranial Pressure and Brain Tissue Oxygen Monitoring in Perioperative Management of Patients with Moyamoya Disease.

Intracranial pressure monitoring and brain tissue oxygen monitoring are commonly used in head injury for goal-directed therapies, but there may be more indications for its use. Moyamoya disease involves progressive stenosis of the arterial circulation and formation of collateral vessels that are at risk of hemorrhage. The risk of ischemic events during revascularization surgery and postoperatively is high. Impaired cerebral autoregulation may be one of the factors that are implicated. We present our experience with monitoring of cerebral oxygenation and autoregulation in the pathological hemisphere during the perioperative period in four patients with moyamoya disease.

Telemetric Intracranial Pressure: A Snapshot Does not Give the Full Story.

Telemetric intracranial pressure (ICP) monitors are useful tools in the management of complex hydrocephalus and idiopathic intracranial hypertension (IIH). Clinicians may use them as a "snapshot" screening tool to assess shunt function or ICP. We compared "snapshot" telemetric ICP recordings with extended, in-patient periods of monitoring to determine whether this practice is safe and useful for clinical decision making.

Investigating the potential clinical benefit of Selumetinib in resensitising advanced iodine refractory differentiated thyroid cancer to radioiodine therapy (SEL-I-METRY): protocol for a multicentre UK single arm phase II trial.

BACKGROUND: Thyroid cancer is the most common endocrine malignancy. Some advanced disease is, or becomes, resistant to radioactive iodine therapy (refractory disease); this holds poor prognosis of 10% 10-year overall survival. Whilst Sorafenib and Lenvatinib are now licenced for the treatment of progressive iodine refractory thyroid cancer, these treatments require continuing treatment and can be associated with significant toxicity. Evidence from a pilot study has demonstrated feasibility of Selumetinib to allow the reintroduction of I-131 therapy; this larger, multicentre study is required to demonstrate the broader clinical impact of this approach before progression to a confirmatory trial. METHODS: SEL-I-METRY is a UK, single-arm, multi-centre, two-stage phase II trial. Participants with locally advanced or metastatic differentiated thyroid cancer with at least one measureable lesion and iodine refractory disease will be recruited from eight NHS Hospitals and treated with four-weeks of oral Selumetinib and assessed for sufficient I-123 uptake (defined as any uptake in a lesion with no previous uptake or 30% or greater increase in uptake). Those with sufficient uptake will be treated with I-131 and followed for clinical outcomes. Radiation absorbed doses will be predicted from I-123 SPECT/CT and verified from scans following the therapy. Sixty patients will be recruited to assess the primary objective of whether the treatment schedule leads to increased progression-free survival compared to historical control data. DISCUSSION: The SEL-I-METRY trial will investigate the effect of Selumetinib followed by I-131 therapy on progression-free survival in radioiodine refractory patients with differentiated thyroid cancer showing increased radioiodine uptake following initial treatment with Selumetinib. In addition, information on toxicity and dosimetry will be collected. This study presents an unprecedented opportunity to investigate the role of lesional dosimetry in molecular radiotherapy, leading to greater personalisation of therapy. To date this has been a neglected area of research. The findings of this trial will be useful to healthcare professionals and patients alike to determine whether further study of this agent is warranted. It is hoped that the development of the infrastructure to deliver a multicentre trial involving molecular radiotherapy dosimetry will lead to further trials in this field. TRIAL REGISTRATION: SEL-I-METRY is registered under ISRCTN17468602 , 02/12/2015.

Transcranial Bioimpedance Measurement as a Non-invasive Estimate of Intracranial Pressure.

OBJECTIVES: We have previously demonstrated a relationship between transcranial bioimpedance (TCB) measurements and intracranial pressure (ICP) in an animal model of raised ICP. The primary objective of this study was to explore the relationship between non-invasive bioelectrical impedance measurements of the brain and skull and ICP in traumatic brain injury (TBI) patients. MATERIALS AND METHODS: Included patients were adults admitted to the Neurological Intensive Care Unit with TBI and undergoing invasive ICP monitoring as part of their routine clinical care. Multi-frequency TCB measurements were performed hourly through bi-temporal electrodes. The bioimpedance parameters of Z c (impedance at the characteristic frequency) and R 0 (resistance to a direct current) were then modelled against ICP using unadjusted and adjusted linear models. RESULTS: One hundred and sixty-eight TCB measurements were available from ten study participants. Using an unadjusted linear modelling approach, there was no significant relationship between measured ICP and Zc or R0. The most significant relationship between ICP and TCB parameters was found by adjusting for multiple patient specific variables and using Zc and R0 normalised per patient (p < 0.0001, r 2 = 0.32). CONCLUSIONS: These pilot results confirm some degree of relationship between TCB parameters and invasively measured ICP. The magnitude of this relationship is small and, on the basis of the current study, TCB is unlikely to provide a clinically useful estimate of ICP in patients admitted with TBI.

Medical Waveform Format Encoding Rules Representation of Neurointensive Care Waveform Data.

OBJECTIVE: Technology in neurointensive care units can collect and store vast amounts of complex patient data. The CHART-ADAPT project is aimed at developing technology that will allow for the collection, analysis and use of these big data at the patient's bedside in neurointensive care units. A requirement of this project is to automatically extract and transfer high-frequency waveform data (e.g. ICP) from monitoring equipment to high performance computing infrastructure for analysis. Currently, no agreed data standard exists in neurointensive care for the description of this type of data. In this pilot study, we investigated the use of Medical Waveform Format Encoding Rules (MFER- www.mfer.org-ISO 11073-92001) as a possible data standard for neurointensive care waveform data. MATERIALS AND METHODS: Several waveform formats were explored (e.g. XML, DICOM waveform) and evaluated for suitability given existing computing infrastructure constraints, e.g. NHS network capacity and the processing capabilities of existing integration software. Key requirements of the format included a compact data size and the use of a recognised standard. The MFER waveform format (ISO/TS 11073-92001) met both requirements. To evaluate the practicality of the MFER waveform format, seven waveform signals (ICP, ECG, ART, CVP, EtCO2, Pleth, Resp) collected over a period of 8 h from a patient at the Institute of Neurological Sciences in Glasgow were converted into MFER waveform format. RESULTS: The MFER waveform format has two main components: sampling information and frame information. Sampling information describes the frequency of the data sampling and the resolution of the data. Frame information describes the data itself; it consists of three elements: data block (the actual data), channel (each type of waveform data occupies a channel) and sequence (the repetition of the data). All seven waveform signals were automatically and successfully converted into the MFER waveform format. One MFER file was created for each minute of data (total of 479 files, 181 KB each). CONCLUSIONS: The MFER waveform format has potential as a lightweight standard for representing high-frequency neurointensive care waveform data. Further work will include a comparison with other waveform data formats and a live trial of using the MFER waveform format to stream patient data over a longer period.

Investigation of the Relationship Between the Burden of Raised ICP and the Length of Stay in a Neuro-Intensive Care Unit.

OBJECTIVES: Raised intracranial pressure (ICP) is well known to be indicative of a poor outcome in traumatic brain injury (TBI). This phenomenon was quantified using a pressure time index (PTI) model of raised ICP burden in a paediatric population. Using the PTI methodology, this pilot study is aimed at investigating the relationship between raised ICP and length of stay (LOS) in adults admitted to a neurological intensive care unit (neuro-ICU). MATERIALS AND METHODS: In 10 patients admitted to the neuro-ICU following TBI, ICP was measured and data from the first 24 h were analysed. The PTI is a bounded area under the curve, where the bound is the threshold limit of interest for the signal. The upper bound of 20 mmHg for ICP is commonly used in clinical practice. To fully investigate the relationship between ICP and LOS, further bounds from 1 to 40 mmHg were used during the PTI calculations. A backwards step Poisson regression model with a log link function was used to find the important thresholds for the prediction of full LOS, measured in hours, in the neuro-ICU. RESULTS: The fit was assessed using a Chi-squared deviance goodness of fit method, which showed a non-significant p value of 0.97, indicating a correctly specified model. The backwards step strategy, minimising the model's Akaike information criteria (AIC) at each change, found that levels 13-16, 18 and 20-21 combined were the most predictive. From this model it can be shown that for every 1 mmHg/h increase in burden, as measured by the PTI, the LOS has a base exponential increase of approximately 2 h, with the largest increases in the LOS given at the 20-mmHg threshold level. CONCLUSIONS: This model demonstrates that increased duration of raised ICP in the early monitoring period is associated with a prolonged LOS in the neuro-ICU. Further validation of the PTI model in a larger cohort is currently underway as part of the CHART-ADAPT project. Second, further adjustment with known predictors of outcome, such as severity of injury, would help to improve the fit and validate the current combination of predictors.

Cerebral Perfusion Pressure Variability Between Patients and Between Centres.

INTRODUCTION: The aim of this analysis was to investigate to what extent median cerebral perfusion pressure (CPP) differs between severe traumatic brain injury (TBI) patients and between centres, and whether the 2007 change in CPP threshold in the Brain Trauma Foundation guidelines is reflected in patient data collected at several centres over different time periods. METHODS: Data were collected from the Brain-IT database, a multi-centre project between 2003 and 2005, and from a recent project in four centres between 2009 and 2013. For patients nursed with their head up at 30° and with the blood pressure transducer at atrium level, CPP was corrected by 10 mmHg. Median CPP, interquartile ranges and total CPP ranges over the monitoring time were calculated per patient and per centre. RESULTS: Per-centre medians pre-2007 were situated between 50 and 70 mmHg in 6 out of 16 centres, while 10 centres had medians above 70 mmHg and 4 above 80 mmHg. Post-2007, three out of four centres had medians between 60 and 70 mmHg and one above 80 mmHg. One out of two centres with data pre- and post-2007 shifted from a median CPP of 76 mmHg to 60 mmHg, while the other remained at 68-67 mmHg. CONCLUSIONS: CPP data are characterised by a high inter-individual variability, but the data also suggest differences in CPP policies between centres. The 2007 guideline change may have affected policies towards lower CPP in some centres. Deviations from the guidelines occur in the direction of CPP > 70 mmHg.

Visualizing Cerebrovascular Autoregulation Insults and Their Association with Outcome in Adult and Paediatric Traumatic Brain Injury.

OBJECTIVE: The aim of this study is to assess visually the impact of duration and intensity of cerebrovascular autoregulation insults on 6-month neurological outcome in severe traumatic brain injury. MATERIAL AND METHODS: Retrospective analysis of prospectively collected minute-by-minute intracranial pressure (ICP) and mean arterial blood pressure data of 259 adult and 99 paediatric traumatic brain injury (TBI) patients from multiple European centres. The relationship of the 6-month Glasgow Outcome Scale with cerebrovascular autoregulation insults (defined as the low-frequency autoregulation index above a certain threshold during a certain time) was visualized in a colour-coded plot. The analysis was performed separately for autoregulation insults occurring with cerebral perfusion pressure (CPP) below 50 mmHg, with ICP above 25 mmHg and for the subset of adult patients that did not undergo decompressive craniectomy. RESULTS: The colour-coded plots showed a time-intensity-dependent association with outcome for cerebrovascular autoregulation insults in adult and paediatric TBI patients. Insults with a low-frequency autoregulation index above 0.2 were associated with worse outcomes and below -0.6 with better outcomes, with and approximately exponentially decreasing transition curve between the two intensity thresholds. All insults were associated with worse outcomes when CPP was below 50 mmHg or ICP was above 25 mmHg. CONCLUSIONS: The colour-coded plots indicate that cerebrovascular autoregulation is disturbed in a dynamic manner, such that duration and intensity play a role in the determination of a zone associated with better neurological outcome.

Automatic Calculation of Hydrostatic Pressure Gradient in Patients with Head Injury: A Pilot Study.

The non-surgical management of patients with traumatic brain injury is the treatment and prevention of secondary insults, such as low cerebral perfusion pressure (CPP). Most clinical pressure monitoring systems measure pressure relative to atmospheric pressure. If a patient is managed with their head tilted up, relative to their arterial pressure transducer, then a hydrostatic pressure gradient (HPG) can act against arterial pressure and cause significant errors in calculated CPP.To correct for HPG, the arterial pressure transducer should be placed level with the intracranial pressure transducer. However, this is not always achieved. In this chapter, we describe a pilot study investigating the application of speckled computing (or "specks") for the automatic monitoring of the patient's head tilt and subsequent automatic calculation of HPG. In future applications this will allow us to automatically correct CPP to take into account any HPG.

Ablation with low-dose radioiodine and thyrotropin alfa in thyroid cancer.

BACKGROUND: It is not known whether low-dose radioiodine (1.1 GBq [30 mCi]) is as effective as high-dose radioiodine (3.7 GBq [100 mCi]) for treating patients with differentiated thyroid cancer or whether the effects of radioiodine (especially at a low dose) are influenced by using either recombinant human thyrotropin (thyrotropin alfa) or thyroid hormone withdrawal. METHODS: At 29 centers in the United Kingdom, we conducted a randomized noninferiority trial comparing low-dose and high-dose radioiodine, each in combination with either thyrotropin alfa or thyroid hormone withdrawal before ablation. Patients (age range, 16 to 80 years) had tumor stage T1 to T3, with possible spread to nearby lymph nodes but without metastasis. End points were the rate of success of ablation at 6 to 9 months, adverse events, quality of life, and length of hospital stay. RESULTS: A total of 438 patients underwent randomization; data could be analyzed for 421. Ablation success rates were 85.0% in the group receiving low-dose radioiodine versus 88.9% in the group receiving the high dose and 87.1% in the thyrotropin alfa group versus 86.7% in the group undergoing thyroid hormone withdrawal. All 95% confidence intervals for the differences were within ±10 percentage points, indicating noninferiority. Similar results were found for low-dose radioiodine plus thyrotropin alfa (84.3%) versus high-dose radioiodine plus thyroid hormone withdrawal (87.6%) or high-dose radioiodine plus thyrotropin alfa (90.2%). More patients in the high-dose group than in the low-dose group were hospitalized for at least 3 days (36.3% vs. 13.0%, P<0.001). The proportions of patients with adverse events were 21% in the low-dose group versus 33% in the high-dose group (P=0.007) and 23% in the thyrotropin alfa group versus 30% in the group undergoing thyroid hormone withdrawal (P=0.11). CONCLUSIONS: Low-dose radioiodine plus thyrotropin alfa was as effective as high-dose radioiodine, with a lower rate of adverse events. (Funded by Cancer Research UK; ClinicalTrials.gov number, NCT00415233.).

Exploration of the relationship between partial pressure of brain tissue oxygen and intracranial pressure.

Introduction: Partial pressure of brain tissue oxygen (PbtO2) has been shown to be a safe an effective monitoring modality to compliment intracranial pressure (ICP) monitoring. It is related to metabolic activity, disease severity and mortality. Research question: Understanding the complex relationship between PbtO2 and ICP for patients with traumatic brain injury will enable better clinical decision making beyond simple threshold treatment strategies. Material and methods: Patients with PbtO2 monitoring were identified from the BrainIT database, a multi-centre dataset, containing minute by minute PbtO2 and ICP readings. Missing data was imputed and a multi-level log-normal regression model with a compound symmetry correlation structure was built. This accounted for any increased correlation due to the repeated measurements. The model was adjusted for mean arterial pressure and the partial pressure of carbon dioxide. Non-linearity was assessed using analysis of deviance and trends using expected marginal means. Results: 11 subjects with over 82,000 readings were included. They had a median age of 38 (IQR: 37-47), 73% were male, a median length of stay of 11.8 (IQR: 6.6-19.7) days and a median extended Glasgow outcome scale of 7.00 (IQR: 5-8).There is a statistically significant (p < 0.001) non-linear effect of ICP on PbtO2. With an overall increase in PbtO2 of 5.2% (95% CI 4%-6.4%, p < 0.001) for a 10 mmHg increase in ICP below 22 mmHg and a decrease of 5.5% (95% CI 2.7%-8.3%, p=<0.001) in PbtO2 for a 10 mmHg increase in ICP above 22 mmHg. As well as a decrease of 40.9% (95% CI 2.3%-64.3%, p = 0.040) in PbtO2 per day in the intensive care unit. Discussion and conclusion: This model demonstrates that there is a significant non-linear relationship between ICP and PbtO2, however, this is a small heterogeneous cohort and further validation will be required.

The impact of electronic versus paper-based data capture on data collection logistics and on missing scores in thyroid cancer patients.

PURPOSE: The purpose of this study was to investigate the impact of the type of data capture on the time and help needed for collecting patient-reported outcomes as well as on the proportion of missing scores. METHODS: In a multinational prospective study, thyroid cancer patients from 17 countries completed a validated questionnaire measuring quality of life. Electronic data capture was compared to the paper-based approach using multivariate logistic regression. RESULTS: A total of 437 patients were included, of whom 13% used electronic data capture. The relation between data capture and time needed was modified by the emotional functioning of the patients. Those with clinical impairments in that respect needed more time to complete the questionnaire when they used electronic data capture compared to paper and pencil (ORadj 24.0; p = 0.006). This was not the case when patients had sub-threshold emotional problems (ORadj 1.9; p = 0.48). The odds of having the researcher reading the questions out (instead of the patient doing this themselves) (ORadj 0.1; p = 0.01) and of needing any help (ORadj 0.1; p = 0.01) were lower when electronic data capture was used. The proportion of missing scores was equivalent in both groups (ORadj 0.4, p = 0.42). CONCLUSIONS: The advantages of electronic data capture, such as real-time assessment and fewer data entry errors, may come at the price of more time required for data collection when the patients have mental health problems. As this is not uncommon in thyroid cancer, researchers need to choose the type of data capture wisely for their particular research question.

Thyroid cancer susceptibility polymorphisms: confirmation of loci on chromosomes 9q22 and 14q13, validation of a recessive 8q24 locus and failure to replicate a locus on 5q24.

Five single nucleotide polymorphisms (SNPs) associated with thyroid cancer (TC) risk have been reported: rs2910164 (5q24); rs6983267 (8q24); rs965513 and rs1867277 (9q22); and rs944289 (14q13). Most of these associations have not been replicated in independent populations and the combined effects of the SNPs on risk have not been examined. This study genotyped the five TC SNPs in 781 patients recruited through the TCUKIN study. Genotype data from 6122 controls were obtained from the CORGI and Wellcome Trust Case-Control Consortium studies. Significant associations were detected between TC and rs965513A (p=6.35×10(-34)), rs1867277A (p=5.90×10(-24)), rs944289T (p=6.95×10(-7)), and rs6983267G (p=0.016). rs6983267 was most strongly associated under a recessive model (P(GG vs GT + TT)=0.004), in contrast to the association of this SNP with other cancer types. However, no evidence was found of an association between rs2910164 and disease under any risk model (p>0.7). The rs1867277 association remained significant (p=0.008) after accounting for genotypes at the nearby rs965513 (p=2.3×10(-13)) and these SNPs did not tag a single high risk haplotype. The four validated TC SNPs accounted for a relatively large proportion (∼11%) of the sibling relative risk of TC, principally owing to the large effect size of rs965513 (OR 1.74).

Application of synthetic data in the training of artificial intelligence for automated quality assurance in magnetic resonance imaging.

BACKGROUND: Magnetic resonance imaging scanner faults can be missed during routine quality assurance (QA) if they are subtle, intermittent, or the test being performed is insensitive to the type of fault. Coil element malfunction is a common fault within MRI scanners, which may go undetected for quite some time. Consequently, this may lead to poor image quality and the potential for misdiagnoses. PURPOSE: Daily QA typically consists of an automated signal to noise ratio test and in some instances this test is insensitive to coil element malfunction. Instead of relying on daily QA testing, it was proposed to utilize patient images in conjunction with a trained neural network to detect coil element malfunction, even when it presents as a very subtle defect. The advantage to using patient images over phantom testing is real-time monitoring can be achieved. This allows clinical staff to focus more on patient throughput without being burdened by daily testing. METHODS: A neural network was trained using simulated coil failure in 3958 abdominal or pelvic images from 497 patients. The accuracy of the trained network was then tested on an unseen dataset of 109 images from which 44 patients which had coil element malfunction present. Five MRI radiographers were shown 249 images with and without real coil malfunction to assess their accuracy compared to the neural network in identifying the scanner fault. RESULTS: The neural network achieved an accuracy of 91.74% in identifying coil element malfunction in the unseen data. Radiographers tasked with identifying coil element malfunction had an average accuracy of 59.99%. In the same test case, the neural network outperformed all radiographers with an accuracy of 91.56%. CONCLUSION: This work demonstrates that neural networks trained with artificial data can successfully identify MRI scanner coil element malfunction in clinical images. The method provided better accuracy than MRI radiographers (technologists) at identifying coil element malfunction and highlights the potential utility of AI methods as an alternative to support traditional QA. Further, our methodology of training neural networks with simulated data could potentially identify other faults, allowing centers to produce robust fault detection systems with minimal data.

Serum antibodies to periodontal pathogens prior to rheumatoid arthritis diagnosis: A case-control study.

OBJECTIVES: 1) To quantify the association between anti-Porphyromonas gingivalis serum antibody concentrations and the risk of developing rheumatoid arthritis (RA), and 2) to quantify the associations among RA cases between anti-P. gingivalis serum antibody concentrations and RA-specific autoantibodies. Additional anti-bacterial antibodies evaluated included anti-Fusobacterium nucleatum and anti-Prevotella intermedia. METHODS: Serum samples were acquired pre- and post- RA diagnosis from the U.S. Department of Defense Serum Repository (n = 214 cases, 210 matched controls). Using separate mixed-models, the timing of elevations of anti-P. gingivalis, anti-P. intermedia, and anti-F. nucleatum antibody concentrations relative to RA diagnosis were compared in RA cases versus controls. Associations were determined between serum anti-CCP2, ACPA fine specificities (vimentin, histone, and alpha-enolase), and IgA, IgG, and IgM RF in pre-RA diagnosis samples and anti-bacterial antibodies using mixed-effects linear regression models. RESULTS: No compelling evidence of case-control divergence in serum anti-P. gingivalis, anti-F. nucleatum, and anti-P. intermedia was observed. Among RA cases, including all pre-diagnosis serum samples, anti-P. intermedia was significantly positively associated with anti-CCP2, ACPA fine specificities targeting vimentin, histone, alpha-enolase, and IgA RF (p<0.001), IgG RF (p = 0.049), and IgM RF (p = 0.004), while anti-P. gingivalis and anti-F. nucleatum were not. CONCLUSIONS: No longitudinal elevations of anti-bacterial serum antibody concentrations were observed in RA patients prior to RA diagnosis compared to controls. However, anti-P. intermedia displayed significant associations with RA autoantibody concentrations prior to RA diagnosis, suggesting a potential role of this organism in progression towards clinically-detectable RA.