Leveraging CMR for 3D echocardiography: an annotated multimodality dataset for AI

Funding Acknowledgements: Type of funding sources: Public grant(s) – National budget only. Main funding source(s): Health Research Council of New Zealand (HRC)

National Heart Foundation of New Zealand (NHF)

Segmentation of the left ventricular myocardium and cavity in 3D echocardiography (3DE) is a critical task for the quantification of systolic function in heart disease. Continuing advances in 3DE have considerably improved image quality, prompting increased clinical uptake in recent years, particularly for volumetric measurements. Nevertheless, analysis of 3DE remains a difficult problem due to inherently complex noise characteristics, anisotropic image resolution, and regions of acoustic dropout.

One of the primary challenges associated with the development of automated methods for 3DE analysis is the requirement of a sufficiently large training dataset. Historically, ground truth annotations have been difficult to obtain due to the high degree of inter- and intra-observer variability associated with manual 3DE segmentation, thus, limiting the scope of AI-based solutions. To address the lack of expert consensus, we instead used labels derived from cardiac magnetic resonance (CMR) images of the same subjects. By spatiotemporally registering CMR labels to corresponding 3DE image data on a per subject basis (Figure 1), we collated 520 annotated 3DE images from a mixed cohort of 130 human subjects (2 independent single-beat acquisitions per subject at end-diastole and end-systole) consisting of healthy controls and patients with acquired cardiac disease. Comprising images acquired across a range of patient demographics, this curated dataset exhibits variation in image quality, 3DE acquisition parameters, as well as left ventricular shape and pose within the 3D image volume.

To demonstrate the utility of such a dataset, nn-UNet, a self-configuring deep learning method for semantic segmentation was employed. An 80/20 split of the dataset was used for training and testing, respectively, and data augmentations were applied in the form of scaling, rotation, and reflection. The trained network was capable of reproducing measurements derived from CMR for end-diastolic volume, end-systolic volume, ejection fraction, and mass, while outperforming an expert human observer in terms of accuracy as well as scan-rescan reproducibility (Table I).

As part of ongoing efforts to improve the accuracy and efficiency of 3DE analysis, we have leveraged the high resolution and signal-to-noise-ratio of CMR (relative to 3DE), to create a novel, publicly available benchmark dataset for developing and evaluating 3DE labelling methods. This approach not only significantly reduces the effects of observer-specific bias and variability in training data arising from conventional manual 3DE analysis methods, but also improves the agreement between cardiac indices derived from 3DE and CMR.

Figure 1. Data annotation workflow Table I. Results

Left ventricular dimensions and mass measurement from 3D echocardiography: are we there yet?

Funding Acknowledgements

Type of funding sources: Public grant(s) – National budget only. Main funding source(s): Health Research Council (HRC) of New Zealand and National Heart Foundation (NHF) of New Zealand

Introduction—Echocardiographic measures of left ventricular (LV) structure and size, including LV wall thickness and LV end-diastolic dimension (LVID), provide important information in the assessment of patients with heart disease. For example, LV mass is a predictor of outcome for patients with hypertension and LVID is a predictor of cardiac resynchronisation response in patients with heart failure. Advances in 3D echocardiography (3DE) have enabled full-volume acquisitions, which overcome geometric assumptions present in conventional 2D echocardiography (2DE), providing a more accurate representation of cardiac geometry. Although numerous validation studies have been performed for 3DE-derived LV volumes, comparisons of LV dimension by 3DE against established methods are limited.

Purpose—We sought to compare routine LV dimension measurements between 3DE and 2DE, with validation using cardiac magnetic resonance (CMR) imaging.

Methods—Transthoracic echocardiography (2D and 3D) and cine CMR imaging were performed in 62 prospectively recruited participants (47 healthy controls, 9 patients with LVH, 6 patients with aortic regurgitation), <1 h apart. 2DE LV dimension measurements (interventricular septum [IVS], posterior wall thickness [PWT], and LVID) were taken at end-diastole from the parasternal long axis, and mass was calculated using the linear method based on ASE/EACVI guidelines. For 3DE, 3D geometric models of the LV were constructed by interactively fitting surfaces to the endocardium and epicardium using previously validated software, from which corresponding LV dimension measurements and mass were extracted. Measurements were obtained from CMR by a similar 3D geometric modelling process.

Results—Differences (mean ± SD) in LV dimension measurements between the three modalities and intraclass correlation coefficients (ICC) are presented in Table I. When compared with CMR, 3DE exhibited higher agreement in terms of LVID and mass than 2DE, but lower agreement in wall thickness measurements. Statistically significant differences were found between 2DE and 3DE for PWT, LVID, and mass, as well as 2DE and CMR for LVID and mass (where P < 0.01 for a paired sample t­-test, marked with an asterisk). Meanwhile, there were no statistically significant differences between 3DE and CMR for IVS, PWT, LVID, or mass.

Conclusions—Our results demonstrate that 3DE is superior to 2DE in terms of LVID and mass quantification, exhibiting good agreement with CMR. 3DE exhibited moderate and poor agreement for IVS and PWT, respectively, with both 2DE and CMR, likely due to the lower spatial resolution of 3DE. Further advances in 3DE image quality and analysis tools are therefore needed to improve accuracy of wall thickness measurements. Since 2DE imaging plane and probe positioning can result in oblique measurement and underestimation of LVID, the assessment of LVID and mass by 3DE is likely to lead to more accurate diagnostic and prognostic outcomes. Abstract Table 1

Longitudinal strain measurement by 3D modelling from cine CMR: feasibility and comparison to 2D speckle tracking echocardiography

Background

Global longitudinal strain (GLS) has emerged as a sensitive index of left ventricular (LV) systolic function with greater prognostic value than LV ejection fraction (LVEF) in a variety of cardiac disorders. While GLS is routinely derived from 2D speckle tracking echocardiography (STE) and feature tracking in cardiac magnetic resonance (CMR) imaging, calculation of strain via 3D geometric modelling enables analyses of deformation that are independent of 2D image plane constraints.

Purpose

We sought to compare longitudinal strain measurements extracted from geometric 3D analysis of CMR against values obtained from conventional 2D-STE.

Methods

Consecutive 2D-echocardiography (2D-echo) and steady-state free precession multiplanar cine CMR scans were performed in 80 prospectively recruited participants (48 healthy controls with LVEF range 53–74%, 30 patients with non-ischaemic cardiac disease with LVEF range 25–77%, and 2 heart transplant recipients with LVEF 53% and 58%), <1 hour apart. Average endocardial peak GLS from 2D-STE was calculated offline using vendor-independent clinical software from apical triplane (2, 3 and 4-chamber) images for each of the standardised LV walls (anterior, anteroseptal, inferoseptal, inferior, inferolateral, anterolateral). Dynamic 3D geometric models of the LV were reconstructed from 3 long- and 6 short-axis CMR slices over one cardiac cycle. Corresponding longitudinal strain measurements were then evaluated by extracting analogous endocardial arc lengths (apex to base of each LV wall) from the 3D LV model. Finally, an average peak GLS was calculated as the mean of the peak longitudinal strains in each LV wall.

Results

GLS measured by 2D-STE ranged between −6.5% and −27.9% for the study population. A two-way mixed-effects intraclass correlation coefficient (ICC) for absolute agreement of 0.820 (95% CI: [0.720, 0.885]) demonstrated good correlation between average GLS obtained from 2D-STE and CMR. A Bland-Altman analysis revealed a minimal bias (<1%) and 95% limits of agreement (LOA) between −6.3% and 5.5% (Fig. 1), with no apparent proportional bias. Comparatively lower correlation and wider LOA between longitudinal strains from 2D-STE and CMR were observed for each LV wall (Table I).

Conclusions

Fully automated calculation of LV GLS can be obtained from geometric 3D CMR analysis. Average peak GLS from cine CMR exhibits good agreement with 2D-STE, despite showing only moderate agreement at each LV wall. The increased discrepancy in regional longitudinal strain may be attributed to subjective plane positioning in 2D-echo, which can be expected to improve with advances in 3D-STE. The calculation of GLS by 3D geometric modelling may enhance the diagnostic value of routine cine CMR examinations for LV systolic function assessment.

Funding Acknowledgement

Type of funding sources: Public grant(s) – National budget only. Main funding source(s): Health Research Council (HRC) of New Zealand and National Heart Foundation (NHF) of New Zealand Figure 1. Bland-Altman analysisTable I. Regional correlations

Flow vorticity relationships with right ventricular geometry in adult tetralogy of Fallot

Background

Repaired tetralogy of Fallot adults (rToF) undergo right ventricular (RV) remodeling, in part due to volume overload of residual pulmonary regurgitation volume (PRV). Time-resolved phase-contrast cardiac magnetic resonance imaging (4D Flow MRI) enables the qualitative and quantitative measurement of altered blood flow patterns, including vorticity. Cardiac atlases allow for complex three-dimensional heart shapes to be expressed as morphometric scores. Those scores show the extent of geometrical shift and can help explore uncharted relationships between vorticity and architecture.

Purpose

We aimed to quantify vorticity, incorporating deep learning to enhance 4D Flow data, and correlate this with global cardiac parameters and morphometric scores.

Methods

12 Adult rToF patients and 10 age-matched controls underwent 4D flow MRI and cine imaging. RV interventricular vorticity was calculated for outflow and inflow tracts. EDV, ESV and SV were computed from cines which were also used to build three-dimensional shape models.

The biventricular models were projected onto an atlas generated from 95 rToF patients, and twenty-one principal component analysis shape modes were correlated with cardiac metrics and vorticity to identify global shape variations. Association between biventricular shape and vorticity was further analysed using multivariate multiple regression models.

Results

Strong correlation was found between PRV and the right ventricular outflow tract (RVOT) vorticity. PRV and RVOT vorticity both correlated with the same 3 shape modes (r=−0.55, −0.50 and 0.6 (p<0.05) respectively for PR and r=0.63, −0.82 and 0.60 (p<0.05) respectively for vorticity) i.e., the RV dilates with an increase in basal bulging, apical bulging and tricuspid annulus tilting with more severe regurgitation, as well as a smaller LV, and a paradoxical movement of the septum (Figure 1). However, RV vorticity correlated with 2 modes that did not correlate with PRV, (r=−0.62, −0.69, p<0.05). With higher vorticity the RV was longer, increased tilting of the tricuspid annulus and an increased basal bulge around the tricuspid area. The multivariate analysis model demonstrated that higher vorticity was associated with displacement of the pulmonary valve and change in the RVOT length and direction. A septal displacement towards the left ventricle was observed and increased apical flatness of the RV (Figure 1). Qualitatively, vorticity in rToF group was more heterogeneous than controls (Figure 2).

Conclusions

Vorticity is a novel marker based on the influence of blood motion providing new insight into early diagnosis and prognosis of cardiac disease. This is the first study to examine the relationships between vorticity and regional RV shape changes in rToF. Mode associations with vorticity were different to associations with PRV. More longitudinal studies are required for standardization of change in vorticity with the disease process.

Funding Acknowledgement

Type of funding sources: Foundation. Main funding source(s): The New Zealand heart foundation Mode variations and morphometric modelVorticity visualization and analysis

Derivation of in vivo pressure-volume loops for post-heart transplant patients using real-time 3D echocardiography and left ventricular catheterisation

Background

Image-based methods that combine catheterisation with non-concurrent cardiac magnetic resonance (CMR) imaging data and echocardiography (echo) is gaining more interest than the conductance catheter method to derive pressure-volume loops (PVLs) due to improved accuracy and accessibility of LV volume quantification [1–3]. However, accurate temporal registration between LV pressure and volume is not well developed.

Purpose

We propose a framework for temporally registering invasive LV and aortic pressures (LVP and AOP) acquired during left heart catheterisation with real time 3D echocardiography (RT3DE) to generate in vivo PVLs in a group of heart transplant (HTx) recipients.

Methods

25 orthotopic HTx recipients (mean age: 54±8 years and 7 female) indicated for routine coronary assessment were recruited for invasive hemodynamic measurement and RT3DE imaging. A fluid-filled pigtail catheter was used to measure LVP and AOP with simultaneous electrocardiogram (ECG) over several (9–15) heartbeats. Within an hour of catheterisation, single-beat transthoracic RT3DE of the LV was performed from the apical window in a left lateral decubitus position. Imaging parameters were optimized for each patient to maximize the temporal resolution (between 15–41 imaging frames per cycle). We developed a piecewise linear temporal scaling method based on cardiac events (end-diastole (ED), end of isovolumic contraction (eIVC), end-systole (ES), end of isovolumic relaxation (eIVR), and diastasis (DS)) of RT3DE and haemodynamic measurement to resample the LVP at the RT3DE imaging frames between the cardiac events to construct PVLs (Fig. 1a). Geometric LV models were manually fitted at ED and ES, followed by automatic tracking across intermediary frames to estimate LV volume over the entire cardiac cycle (Fig. 1b). The temporally aligned pressure values were further averaged to find the beat-averaged LV PVL (Fig. 1c).

Results

Based on the number of cardiac cycles selected for haemodynamic analysis, multiple in vivo PVLs were constructed for each patient. A beat-averaged PVL was also computed for each patient (Fig.1d). With the exception of one case, the beat-averaged PVLs exhibited classically representative shape with distinct isovolumic contraction and isovolumic relaxation phases. The individual diastolic PVRs for all patients are shown in Fig.1e, with beat-to-beat variation observed in most patients. For some cases, the variation manifested as an offset in LVP, whereas changes in the diastolic PVR slope were observed in other cases.

Conclusion

Temporal alignment scheme based on cardiac events allowed accurate derivation of patient-specific in vivo PVLs from catheterization and RT3DE measurements. Application to heart transplant recipients revealed beat-to-beat variation of haemodynamic state. Further analysis of the diastolic PVRs will allow quantification of chamber stiffness for HTx recipients.

Funding Acknowledgement

Type of funding sources: Public grant(s) – National budget only. Main funding source(s): Health Research Council of New Zealand Patient-specific PVLs

Clinical features and presentation of cervicofacial infection: a Maxillofacial Trainee Research Collaborative (MTReC) study

Cervicofacial infection (CFI) is a common presentation to the Oral and Maxillofacial (OMFS) department and accounts for significant emergency activity. The current study aims to understand the aetiology, management, and clinical features of patients hospitalised with CFI. Our study included all patients admitted for management of CFI from May to October 2017 at 25 OMFS units across 17 UK regions. Data were collected prospectively and included age, comorbidities, prior treatment received, markers of sepsis, and presenting clinical features. One thousand and two (1002) admissions were recorded; 546 (54.5%) were male. Median (range) age was 34 (1-94) years. The most common presenting complaints were trismus (46%) and dysphagia (27%). Airway compromise was present in 1.7% of cases. Odontogenic infection accounted for 822/1002 (82%) admissions. Of those with an infection of odontogenic origin, 453/822 (55.1%) had received previous treatment. Two-thirds of those who had received treatment were managed by antibiotics alone (300/453, 66.2%). Patients met criteria for sepsis in 437/1002 (43.6%) of CFI, and in 374/822 (45.5%) of odontogenic infections. This is the largest study worldwide of patients requiring inpatient management for CFI. Infection due to odontogenic origin is the most frequent reason for admission and nearly half do not seek treatment before presentation. Patients with CFI often present late in their disease and frequently meet criteria for sepsis, requiring timely and aggressive treatment to ensure optimum outcomes. Trismus is an emerging dominant feature with all the implications related to the anaesthetic management of these patients. Knowledge of these factors has implications for the referrer, triage, the emergency department, the anaesthetic team, and members of the OMFS team.

Automated analysis of 3D-echocardiography using spatially registered patient-specific CMR meshes

Funding Acknowledgements

Type of funding sources: Public grant(s) – National budget only. Main funding source(s): National Heart Foundation (NHF) of New Zealand Health Research Council (HRC) of New Zealand

Artificial intelligence shows considerable promise for automated analysis and interpretation of medical images, particularly in the domain of cardiovascular imaging. While application to cardiac magnetic resonance (CMR) has demonstrated excellent results, automated analysis of 3D echocardiography (3D-echo) remains challenging, due to the lower signal-to-noise ratio (SNR), signal dropout, and greater interobserver variability in manual annotations. As 3D-echo is becoming increasingly widespread, robust analysis methods will substantially benefit patient evaluation. 

We sought to leverage the high SNR of CMR to provide training data for a convolutional neural network (CNN) capable of analysing 3D-echo. We imaged 73 participants (53 healthy volunteers, 20 patients with non-ischaemic cardiac disease) under both CMR and 3D-echo (<1 hour between scans). 3D models of the left ventricle (LV) were independently constructed from CMR and 3D-echo, and used to spatially align the image volumes using least squares fitting to a cardiac template. The resultant transformation was used to map the CMR mesh to the 3D-echo image. Alignment of mesh and image was verified through volume slicing and visual inspection (Fig. 1) for 120 paired datasets (including 47 rescans) each at end-diastole and end-systole.

100 datasets (80 for training, 20 for validation) were used to train a shallow CNN for mesh extraction from 3D-echo, optimised with a composite loss function consisting of normalised Euclidian distance (for 290 mesh points) and volume. Data augmentation was applied in the form of rotations and tilts (<15 degrees) about the long axis. The network was tested on the remaining 20 datasets (different participants) of varying image quality (Tab. I). For comparison, corresponding LV measurements from conventional manual analysis of 3D-echo and associated interobserver variability (for two observers) were also estimated.

Initial results indicate that the use of embedded CMR meshes as training data for 3D-echo analysis is a promising alternative to manual analysis, with improved accuracy and precision compared with conventional methods. Further optimisations and a larger dataset are expected to improve network performance.

(n = 20) LV EDV (ml) LV ESV (ml) LV EF (%) LV mass (g) Ground truth CMR 150.5 ± 29.5 57.9 ± 12.7 61.5 ± 3.4 128.1 ± 29.8 Algorithm error -13.3 ± 15.7 -1.4 ± 7.6 -2.8 ± 5.5 0.1 ± 20.9 Manual error -30.1 ± 21.0 -15.1 ± 12.4 3.0 ± 5.0 Not available Interobserver error 19.1 ± 14.3 14.4 ± 7.6 -6.4 ± 4.8 Not available Tab. 1. LV mass and volume differences (means ± standard deviations) for 20 test cases. Algorithm: CNN – CMR (as ground truth). Abstract Figure. Fig 1. CMR mesh registered to 3D-echo.

P185 Patient perceptions of physical activity following a diagnosis of giant cell arteritis: a multinational qualitative study

Background

Giant cell arteritis (GCA) is the most common vasculitis in the UK, with an incidence of 220 cases per million in adults over 50 years of age. The physical symptoms as well as the side effects of glucocorticoids may impact patients’ ability to exercise. Maintaining physical activity (PA) has been shown to be beneficial to disease activity in other inflammatory conditions and is also a specific priority for GCA patients. The aim of this project was to explore patient perceptions of physical activity in GCA.

Methods

Multinational qualitative study, using interviews with 36 patients from the UK (25) and Australia (11), all of whom had a definitive diagnosis from imaging or biopsy. Interviews were recorded, transcribed, and analysed using inductive thematic analysis. This is secondary analysis of data collected to explore health-related quality of life in people with GCA.

Results

107 individual themes were reported by patients, which divided broadly into two overarching themes: barriers to (59) and facilitators of (48) physical activity. Four sub-themes were identified within each overarching theme. For barriers, these were: negative physical symptoms (including effects of disease flares, visual loss, fatigue, weakness, pain and stiffness), lack of physical capability (including poor stamina, confidence and mobility), negative perceptions around PA, and negative reinforcement (i.e. new physical symptoms following PA). Facilitators of physical activity were also grouped into four sub-themes: external facilitators (including motivation from healthcare professionals), access to appropriate facilities, personal strategies (including pacing and goal-setting) and personal facilitators (including internal motivation to improve symptoms, and positive reinforcement from noticing physical and psychological benefits of PA).

Conclusion

There are a variety of barriers to physical activity in GCA patients, including patients being fearful of exercise. In other inflammatory conditions, patients report improved symptoms following physical activity as well as wider benefits to general wellbeing and cardiovascular health. Education, motivational interviewing, and personalised strategies may be beneficial components of an intervention to support physical activity in patients with GCA.

Disclosures

K. Austin None. E. Dures Grants/research support; Has previously received an independent learning grant from Pfizer, however the work has been completed and the grant has been closed. C. Almeida None. F. Cramp None. K. Gilbert None. C. Guly None. C. Hill None. S. Mackie None. A. O'Brien None. R. Watts None. J. Robson None.

P4360Personalised shape models of the left ventricle from 3D echocardiography: an initial comparison to cardiac magnetic resonance imaging

Background

The heart constantly adapts to maintain cardiac output. In the longer term, this process (remodeling) can manifest as changes in ventricular volume, sphericity, and/or wall thickness, amongst several other morphological indices. Previous studies have shown the significance of remodeling in evaluations of survival, and as a determinant of the clinical course of heart failure. Yet surprisingly, diagnostic measures, typically of left ventricular (LV) mass and ejection fraction, neglect much of the shape information that is available through imaging. A recent UK Biobank study revealed that morphometric atlases show more compelling associations with cardiovascular risk factors, than do LV mass and volumes. While it has been possible to construct shape models from cardiac magnetic resonance imaging (MRI), such a framework is still under development for echocardiography (echo).

Purpose

Despite MRI being long regarded as the gold standard, it is greatly limited by high costs, long scan times and incompatibility with ferromagnetic cardiac devices. In contrast, echo has presented as a convenient alternative, whilst also offering good temporal resolution. The advancements of 3D echo now provide adequate spatial resolution and thus elicit the possibility of conducting more complex analyses on this modality. With the ability to extract LV geometry directly from 3D echo acquisitions, we sought to create dynamic, 3D patient-specific models–and subsequently compare these results to those derived from MRI.

Methods

As part of an ongoing study, 8 volunteers with no known cardiovascular problems (nor family history thereof), were recruited for non-invasive imaging. Cine MRI and 3D echo of the LV were acquired within a 2 hour session. A Siemens Avanto Fit 1.5 T MRI scanner and Siemens ACUSON SC2000 Ultrasound System with a 4Z1c Transducer were used. 3D models of the LV were generated independently from echo (EchobuildR 2.7 prototype software, Siemens Ultrasound) and MRI acquisitions (Cardiac Image Modeller v8.1), and registered to fiducial landmarks (apex, base plane, right ventricular inserts) and myocardial contours.

Results

Euclidian distances between 1682 corresponding points sampled from the surface of echo/MRI models were calculated, and used as a discrepancy measure (Figure). Across the 8 cases, we found an average root mean square deviation (RMSD) of 5.71 mm at end-systole and 6.03 mm at end-diastole. The maximum RMSD for a single model was 9.47 mm (case 8, ES).

Conclusion

We demonstrate that it is possible to create shape models from 3D echo examinations for comparison with MRI. As more cases are collected, we will devise methods to objectively quantify the mismatch that may arise between models derived from the two modalities. The establishment of such a framework would not only provide previously unavailable measures of shape and function, but in turn leverage the significantly wider clinical reach of echocardiography.

2018 EULAR recommendations for a core data set to support observational research and clinical care in giant cell arteritis

Giant cell arteritis (GCA) represents the most common form of primary systemic vasculitis and is frequently associated with comorbidities related to the disease itself or induced by the treatment. Systematically collected data on disease course, treatment and outcomes of GCA remain scarce. The aim of this EULAR Task Force was to identify a core set of items which can easily be collected by experienced clinicians, in order to facilitate collaborative research into the course and outcomes of GCA. A multidisciplinary EULAR task force group of 20 experts including rheumatologists, internists, epidemiologists and patient representatives was assembled. During a 1-day meeting, breakout groups discussed items from a previously compiled collection of parameters describing GCA status and disease course. Feedback from breakout groups was further discussed. Final consensus was achieved by means of several rounds of email discussions after the meeting. A three-round Delphi survey was conducted to determine a core set of parameters including the level of agreement. 117 parameters were regarded as relevant. Potential items were subdivided into the following categories: General, demographics, GCA-related signs and symptoms, other medical conditions and treatment. Possible instruments and assessment intervals were proposed for documentation of each item. To facilitate implementation of the recommendations in clinical care and clinical research, a minimum core set of 50 parameters was agreed. This proposed core set intends to ensure that relevant items from different GCA registries and databases can be compared for the dual purposes of facilitating clinical research and improving clinical care.

Examining management and research priorities in patients with polymyalgia rheumatica: a primary care questionnaire survey

Introduction/objectives

Polymyalgia rheumatica (PMR) is a common inflammatory disorder that is usually managed with oral glucocorticoids, which although effective can cause significant adverse events. Support group survey data suggests length of glucocorticoid treatment and managing side effects are key priority areas of management for patients. Recognising that not all patients will access patient support organisations, our objective was to identify priorities for PMR management and research among primary care PMR patients.

Method

All adults aged ≥ 50 years registered with 150 English general practices who had a first read code for PMR in their medical records in the preceding 3 years were mailed a self-completion questionnaire (n = 704). Survey items included questions regarding patient priorities for PMR management (from a pre-defined list of 10 items) and suggestions for future research (8 items, plus a free-text option), which were developed in collaboration with PMRGCAuk.

Results

Five hundred fifty patients responded (78%). The mean (SD) age was 74.1 (8.5) years and 361 (66%) were female. Priority research areas were focused on how to better manage pain, stiffness and fatigue (431, 78%), improving the diagnosis of PMR (393, 71%) and steroid management (342, 62%).

Conclusions

This survey of PMR patients suggests that symptom management, early diagnosis and managing medication are key areas for patients for future research. Researchers and funding organisations should be aware of these priorities if we are to generate research findings that are relevant to the widest range of stakeholders.

Support available for and perceived priorities of people with polymyalgia rheumatica and giant cell arteritis: results of the PMRGCAuk members' survey 2017

Polymyalgia rheumatica and giant cell arteritis are relatively common, but under research inflammatory rheumatological conditions. This survey aimed to ascertain the matters in which patients feel they need support with these conditions and appraise how the Charity PMRGCAuk currently supports these needs and could do so in the future. PMRGCAuk members (n = 910) were invited to complete an on-line survey. The survey requested the respondent's history of PMR and or GCA, their perceived priorities for support for people with PMR and or GCA and views on the services already provided by the Charity. A total of 209 people completed the survey. Less than 24% had heard of either PMR or GCA before their diagnosis. Priorities in supporting people with PMR and or GCA included: being on and tapering off glucocorticoids (76.6%), specifically, length of treatment and the risks versus benefits and managing side effects. Respondents generally reported satisfaction with the services currently provided by PMRGCAuk. The support provided by PMRGCAuk is very helpful to members and fills an important gap in provision for people with PMR and or GCA. The areas in which the greatest proportions of participants requested support do not have an evidence base to underpin them. It is incumbent on the research community to address patients' concerns and provide an evidence base where it is required by those affected.

An Iterative Diffeomorphic Algorithm for Registration of Subdivision Surfaces: Application to Congenital Heart Disease

In this paper, we present a new diffeomorphic registration algorithm for the registration of 3D models to 3D points. A biventricular template is iteratively fitted to the data by a series of implicitly constrained diffeomorphic linear least squares fits with decreasing regularization weights before performing an explicitly constrained diffeomorphic fit. The algorithm has been tested on a set of manual contours from 20 patients with a variety of congenital heart disease. Registration accuracy was assessed by calculating the mean point-to-point distance and the Dice overlap metric. Results showed that the method was able to accurately fit the biventricular model to 3D points and that the deformable model was able to fit all the pathologies while being diffeomorphic. The algorithm took approximately 5 minutes to fit each case, with an average of 52,580 points per case.

Recruitment of patients into head and neck clinical trials: acceptability of studies to patients from perspective of the research team

We reviewed longitudinal recruitment data to assess recruitment into head and neck cancer trials, and to identify factors that could influence this and affect their acceptability to patients. We retrieved data from the prospective computerised database (2009-2016) to measure acceptability to patients using the recruitment:screening ratio, and compared observational with interventional studies, single specialty (or site) with multispecialty (or site) studies, and "step-up" randomisation with "non-inferiority" randomisation designs. A total of 1283 patients were screened and 583 recruited. The recruitment:screening ratio for all National Institute for Health Research (NIHR) portfolio studies combined was 0.47 (486/1133). Studies that involved treatment by several specialties or at several sites had a significantly adverse impact on acceptability (p=0.01). Recruitment into non-inferiority randomised controlled studies was lower than that into step-up randomised studies (p=0.06). The complexity of a study's design did not compromise recruitment. Treatment across several specialties or several sites and perceived non-inferiority designs, reduced the acceptability of some trials.

2015 recommendations for the management of polymyalgia rheumatica: a European League Against Rheumatism/American College of Rheumatology collaborative initiative

Therapy for polymyalgia rheumatica (PMR) varies widely in clinical practice as international recommendations for PMR treatment are not currently available. In this paper, we report the 2015 European League Against Rheumatism (EULAR)/American College of Rheumatology (ACR) recommendations for the management of PMR. We used the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) methodology as a framework for the project. Accordingly, the direction and strength of the recommendations are based on the quality of evidence, the balance between desirable and undesirable effects, patients' and clinicians' values and preferences, and resource use. Eight overarching principles and nine specific recommendations were developed covering several aspects of PMR, including basic and follow-up investigations of patients under treatment, risk factor assessment, medical access for patients and specialist referral, treatment strategies such as initial glucocorticoid (GC) doses and subsequent tapering regimens, use of intramuscular GCs and disease modifying anti-rheumatic drugs (DMARDs), as well as the roles of non-steroidal anti-rheumatic drugs and non-pharmacological interventions. These recommendations will inform primary, secondary and tertiary care physicians about an international consensus on the management of PMR. These recommendations should serve to inform clinicians about best practices in the care of patients with PMR.

An interactive tool for rapid biventricular analysis of congenital heart disease

Cardiac malformations are the most common birth defect. Better interventions in early life have improved mortality for children with congenital heart disease, but heart failure is a significant problem in adulthood. These patients require regular imaging and analysis of biventricular (left and right ventricular) function. In this study, we describe a rapid method to analyse left and right ventricular shape and function from cardiac MRI examinations. A 4D (3D+time) finite element model template is interactively customized to the anatomy and motion of the biventricular unit. The method was validated in 17 patients and 10 ex-vivo hearts. Interactive model updates were achieved through preconditioned conjugate gradient optimization on a multithread system, and by precomputing points predicted from a coarse mesh optimization.

Vagotomy prevents the effect of probiotics on caspase activity in a model of postmyocardial infarction depression

BACKGROUND

Myocardial infarction (MI) is associated with apoptosis in the amygdala and, ultimately, with clinical signs of depression. Different treatments have proven to be beneficial in preventing depression, including combination of the probiotics Lactobacillus helveticus and Bifidobacterium longum for prophylaxis. We have speculated previously that the benefit of these probiotics is due to their anti-inflammatory properties, and evidence suggests that an intact vagus nerve is important for this effect to occur. This study was designed to ascertain vagus nerve involvement in the beneficial influence of probiotics on caspase activities in our post-MI animal model of depression.

METHODS

Probiotics and/or vehicle were administered daily to male adult rats, 14 days before MI and until euthanasia. Vagotomy was performed in subgroups of rats 40 min before MI. They were sacrificed after 3 days of reperfusion, and MI size was assessed along with caspase-3 and -8 activities in the amygdala.

KEY RESULTS

Probiotics had no effect on infarct size but vagotomy increased it. Caspase-3 and caspase-8 activities in the amygdala were higher in MI than in sham-operated rats, and this outcome was reversed by probiotics. The beneficial influence of probiotics was abolished by vagotomy.

CONCLUSIONS & INFERENCES

Our data indicate that the effect of probiotics on caspase activities in the amygdala after MI depends on an intact vagus nerve.

Effects of losartan on whole body, skeletal muscle and vascular insulin responses in obesity/insulin resistance without hypertension

AIMS

Renin-angiotensin system antagonists have been found to improve glucose metabolism in obese hypertensive and type 2 diabetic subjects. The mechanism of these effects is not well understood. We hypothesized that the angiotensin receptor antagonist losartan would improve insulin-mediated vasodilation, and thereby improve insulin-stimulated glucose uptake in skeletal muscle of insulin-resistant subjects.

METHODS

We studied subjects with obesity and insulin resistance but without hypertension, hypercholesterolaemia or dysglycaemia [age 39.0 ± 9.6 yr (mean ± SD), body mass index (BMI) 33.2 ± 5.9 kg/m(2) , BP 115.8 ± 12.2/70.9 ± 7.2 mmHg, LDL 2.1 ± 0.5 mmol/l]. Subjects were randomized to 12 weeks' double-blind treatment with losartan 100 mg once daily (n = 9) or matching placebo (n = 8). Before and after treatment, under hyperinsulinaemic euglycaemic clamp conditions we measured whole-body insulin-stimulated glucose disposal, insulin-mediated vasodilation, and insulin-stimulated leg glucose uptake by the limb balance technique.

RESULTS

Whole-body insulin-stimulated glucose disposal was not significantly increased by losartan. Insulin-mediated vasodilation was augmented following both treatments [increase in leg vascular conductance: pretreatment 0.7 ± 0.3 l/min/mmHg (losartan, mean ± SEM) and 0.9 ± 0.3 (placebo), posttreatment 1.0 ± 0.4 (losartan) and 1.3 ± 0.6 (placebo)] but not different between treatment groups (p = 0.53). Insulin's action to augment nitric oxide (NO) production and to augment endothelium-dependent vasodilation was also not improved. Leg glucose uptake was not significantly changed by treatments, and not different between groups (p = 0.11).

CONCLUSIONS

These findings argue against the hypothesis that losartan might improve skeletal muscle glucose metabolism by improving insulin-mediated vasodilation in normotensive insulin-resistant obese subjects. The metabolic benefits of angiotensin receptor blockers may require the presence of hypertension in addition to obesity-associated insulin resistance.

Influence of the site of measurement on the ability of plethysmographic variability index to predict fluid responsiveness

BACKGROUND

Plethysmographic variability index (PVI) is an accurate predictor of fluid responsiveness in mechanically ventilated patients. However, the site of measurement of the plethysmographic waveform impacts its morphology and its respiratory variation. The goal of this study was to investigate the ability of PVI to predict fluid responsiveness at three sites of measurement (the forehead, ear, and finger) in mechanically ventilated patients under general anaesthesia.

METHODS

We studied 28 subjects after induction of general anaesthesia. Subjects were monitored with a pulmonary artery catheter and three pulse oximeter sensors (the finger, ear, and forehead). Pulse pressure variation, central venous pressure, cardiac index (CI), and PVI measured at the forehead, ear, and finger (PVI(forehead), PVI(ear), and PVI(finger)) were recorded before and after fluid loading (FL). Subjects were responders to volume expansion if CI increased >15% after FL.

RESULTS

Areas under the receiver-operating curves to predict fluid responsiveness were 0.906, 0.880, and 0.836 for PVI(forehead), PVI(ear), and PVI(finger), respectively (P<0.05). PVI(forehead), PVI(ear), and PVI(finger) had a threshold value to predict fluid responsiveness of 15%, 16%, and 12% with sensitivities of 89%, 74%, and 74% and specificities of 78%, 74%, and 67%, respectively.

CONCLUSIONS

PVI can predict fluid responsiveness in anaesthetized and ventilated subjects at all three sites of measurement. However, the threshold values for predicting fluid responsiveness differ with the site of measurement. These results support the use of this plethysmographic dynamic index in the cephalic region when the finger is inaccessible or during states of low peripheral perfusion.

Staging of laryngeal cancer using 64-channel multidetector row CT: comparison of standard neck CT with dedicated breath-maneuver laryngeal CT

BACKGROUND AND PURPOSE

With a 64-channel multidetector row CT, imaging acquisition during speech, swallowing, or phonation has become feasible. However, the actual benefit of these additional focused images should be critically evaluated with respect to radiation dose. The purpose of this study was to determine if dedicated laryngeal CT using breath-holding and straw-blowing improved the accuracy of TNM-staging for patients with biopsy-proved laryngeal carcinomas in comparison with a standard neck CT.

MATERIALS AND METHODS

A total of 27 patients underwent a standard neck CT and a laryngeal CT with additional images acquired while patients held their breath or blew through a straw. Two radiologists interpreted the neck CT and later the laryngeal CT and assigned a TNM-stage for each case. These interpretations were compared with a TNM-stage determined by surgery and/or clinical examination for the individual patients. The accuracy of standard neck CT was compared with the accuracy of laryngeal CT.

RESULTS

The overall accuracy was not significantly different between standard neck CT and the additional laryngeal CT and was, in fact, lower in cases with additional larynx images. The accuracy of staging was slightly improved with the additional laryngeal CT for glottic cancers; however, it was decreased for supraglottic cancers. The accuracy of a dichotomous diagnosis of early-versus-advanced-stage cancer was 0.86 for the standard neck CT and 0.80 for the laryngeal CT. The readers' confidence levels did not improve with the use of the additional images.

CONCLUSIONS

In the era of isovoxel multidetector CT technology and judicious monitoring of radiation dose, a standard neck CT with coronal and sagittal reformats should suffice for the staging of laryngeal cancer.

Pathologic findings and liver elements in hibernating bats with white-nose syndrome

Two groups of vespertilionid bats were collected from affected hibernacula. In group 1 (n, 14; pathology and microbiology), the average body weights of all species were at the lower limit of published ranges. Twelve bats (86%) had mycotic growth in the epidermis, hair follicles, and sebaceous glands. Geomyces destructans, with its characteristic curved conidia, was observed microscopically, cultured, and confirmed by polymerase chain reaction. Dermatitis and mural folliculitis was nil to mild. When focally coinfected with Gram-negative bacteria, there was necrosis and pustules. Fat stores were little to abundant in 12 bats (86%) and nil in 2. Thirteen bats (93%) had pulmonary congestion and 7 (50%) had bone marrow granulocytosis. In group 2 (n, 24; liver elements), 3 bats (13%) had potentially toxic lead levels and 1 (4%), potentially toxic arsenic level. There was no evidence of major organ failure or consistent element toxicity.

Identifying Symptom Clusters in Breast Cancer: Implications on Patient Quality of Life

Background: Patients undergoing treatment for advanced cancer often experience multiple symptoms. These symptoms occur with varying frequency, intensity, and impact. Pain, fatigue, insomnia, anorexia and dyspnea are consistently among the 10 most prevalent symptoms associated with cancer and its treatment. We conducted a multivariate analysis to investigate the impact of cancer symptoms on patient quality of life (QoL) in breast cancer.Material and Methods: A consecutive series of 226 breast cancer patients treated at the Cancer Treatment Centers of America at Southwestern Regional Medical Center between Jan 2001 and Nov 2006. Cancer symptoms were assessed using the symptom subscales of European Organization for Research Treatment of Cancer - Quality of Life Questionnaire (QLQ-C30). Symptom scores range from 0-100 with lower scores indicating better while higher scores indicating worse symptoms. QoL was assessed using Ferrans and Powers Quality of Life Index (QLI). QLI measures overall QoL and QoL in 4 major subscales: health/physical, social/economic, psychological/spiritual, and family. QLI scores range from 0-30 with higher scores indicating better QoL. The relationship between QLQ-C30 symptoms and QLI was evaluated using multivariate linear regression.Results: Of 226 patients, 98 were newly diagnosed while 128 had failed prior treatment before coming to our hospital. The mean age was 52.5 years (range = 27-82 years). We found that every 10 unit increase in fatigue (p=.004) and pain (p=.001) was significantly associated with 0.65 and 0.66 unit decline in QLI health/physical subscale after controlling for age, treatment history, stage at diagnosis and other cancer symptoms. Similarly, every 10 unit increase in insomnia (p=.02) was significantly associated with 0.35 unit decline in QLI family subscale. Finally, every 10 unit increase in pain (p=.01) and insomnia (p=.03) was significantly associated with 0.34 and 0.21 unit decline in overall QoL.Discussion: We found fatigue, pain and insomnia to be independent predictors of QoL after controlling for each other, age, treatment history and stage at diagnosis. Recognition and timely treatment of symptom clusters could result in improved QoL in patients with breast cancer.

Citation Information: Cancer Res 2009;69(24 Suppl):Abstract nr 5043.