A multicentre comparison of quantitative 90Y PET/CT for dosimetric purposes after radioembolization with resin microspheres

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Theranostic SPECT reconstruction for improved resolution: application to radionuclide therapy dosimetry

BACKGROUND: SPECT-derived dose estimates in tissues of diameter less than 3× system resolution are subject to significant losses due to the limited spatial resolution of the gamma camera. Incorporating resolution modelling (RM) into the SPECT reconstruction has been proposed as a possible solution; however, the images produced are prone to noise amplification and Gibbs artefacts. We propose a novel approach to SPECT reconstruction in a theranostic setting, which we term SPECTRE (single photon emission computed theranostic reconstruction); using a diagnostic PET image, with its superior resolution, to guide the SPECT reconstruction of the therapeutic equivalent. This report demonstrates a proof in principle of this approach. METHODS: We have employed the hybrid kernelised expectation maximisation (HKEM) algorithm implemented in STIR, with the aim of producing SPECT images with PET-equivalent resolution. We demonstrate its application in both a dual 68Ga/177Lu IEC phantom study and a clinical example using 64Cu/67Cu. RESULTS: SPECTRE is shown to produce images comparable in accuracy and recovery to PET with minimal introduction of artefacts and amplification of noise. CONCLUSION: The SPECTRE approach to image reconstruction shows improved quantitative accuracy with a reduction in noise amplification. SPECTRE shows great promise as a method of improving SPECT radioactivity concentrations, directly leading to more accurate dosimetry estimates in small structures and target lesions. Further investigation and optimisation of the algorithm parameters is needed before this reconstruction method can be utilised in a clinical setting

The impact of the COVID-19 pandemic on referrals to musculoskeletal services from primary care and subsequent incidence of inflammatory rheumatic musculoskeletal disease: an observational study

Objectives To describe the impact of the COVID-19 pandemic upon referral patterns and incident diagnosis of inflammatory rheumatic and musculoskeletal diseases (iRMDs). Methods UK primary care data was used to describe referral patterns for patients with musculoskeletal conditions. Trends in referrals to musculoskeletal services and incident diagnoses of iRMDs (specifically rheumatoid arthritis (RA) and juvenile inflammatory arthritis (JIA)) were described using Joinpoint Regression and comparisons made between key pandemic time periods. Results The incidence of RA and JIA reduced by -13.3% and -17.4% per month respectively between January 2020 and April 2020, and then increased by 1.9% and 3.7% per month respectively between April 2020 and October 2021. The incidence of all diagnosed iRMDs was stable until October 2021. Referrals decreased between February 2020 and May 2020 by -16.8% per month from 4.8% to 2.4% in patients presenting with a musculoskeletal condition. After May 2020, referrals increased significantly (16.8% per month) to 4.5% in July 2020. Time from first musculoskeletal consultation to RA diagnosis, and referral to RA diagnosis increased in the early-pandemic period (rate ratio (RR) 1.11, 95%CI 1.07-1.15; RR 1.23, 95%CI 1.17-1.30) and remained consistently higher in the late-pandemic (RR 1.13, 95%CI 1.11-1.16; RR 1.27, 95%CI 1.23-1.32) periods respectively, compared to the pre-COVID-19 period. Conclusion Patients with underlying RA and JIA that developed during the pandemic may be yet to present, or be in the referral and/or diagnostic process. Clinicians should remain alert to this possibility and commissioners aware of these findings, enabling the appropriate planning and commissioning of services

P183 Establishing the epidemiology of rheumatoid arthritis, psoriatic arthritis, and axial spondyloarthritis in England using primary care electronic health record data

Abstract Background/Aims The substantial personal and socioeconomic costs associated with rheumatoid arthritis (RA), psoriatic arthritis (PsA), and axial spondyloarthritis (SpA) make understanding their epidemiology crucial. The Clinical Practice Research Datalink (Aurum) is an electronic healthcare record (EHR) database, containing primary care records from ∼20% of English practices (&amp;gt;13 million patients currently registered). To determine RA/PsA/axial SpA epidemiology using EHR data, validated methods need to be applied to ascertain patients with these diagnoses. To address this, we updated and applied approaches validated in other primary care EHR databases in Aurum and described the annual incidence/point-prevalence of RA/PsA/axial SpA alongside patient characteristics (providing indirect evidence of coding accuracy). Methods Diagnosis and synthetic disease-modifying anti-rheumatic drug (DMARD) prescription code lists were constructed, and pre-defined approaches for ascertaining patients with RA/axial SpA/PsA applied. The annual incidence and point-prevalence of RA/PsA/axial SpA were calculated from 2004-2020. Samples were stratified by age/gender, and mean age and gender/ethnic-group relative frequencies described. The study was approved by the CPRD Independent Scientific Advisory Committee (reference 20_000244). Results From 2004-2019 the point-prevalence of RA/PsA increased annually, peaking in 2019 (RA 7.79/1,000; PsA 2.87/1,000) then falling slightly. From 2004-2020 the point-prevalence of axial SpA increased annually (except in 2018/2019), peaking in 2020 (1.13/1,000). Annual RA incidence was higher between 2013-2019 (when included in the Quality Outcomes Framework, ranging 0.491 to 0.521/1,000 person-years) than 2004-2012 (ranging 0.345 to 0.400/1,000 person-years). The annual incidence of PsA and axial SpA increased from 2006 (0.108 to a peak of 0.172/1,000 person-years) and 2010 (0.025 to a peak of 0.045/1,000 person-years), respectively. These years were when new disease classification criteria were introduced. Marked falls in the annual incidence of RA, PsA and axial SpA between 2019 and 2020 were seen, reducing by 40.1%, 67.4% and 38.1%, respectively, reflecting the impact of the COVID-19 pandemic on arthritis diagnoses. Stratifying incidence/prevalence by age/gender broadly showed expected patterns (although the incidence of axial SpA/PsA in women increased over time), and the mean age and gender proportions followed those previously reported. Conclusion The approaches we used to determine patients with RA, PsA, and axial SpA in Aurum led to incidence/prevalence estimates broadly consistent with published studies, and patient characteristics as would be expected. These data support the potential of the Aurum-updated ascertainment approaches for use in further studies of RA, PsA and axial SpA. Disclosure I. Scott: None. R. Whittle: None. J. Bailey: None. H. Twohig: None. S. Hider: None. C. Mallen: None. S. Muller: None. K. Jordan: None. </jats:sec

Persistent inequalities in consultation incidence and prevalence of low back pain and osteoarthritis in England between 2004-2019

Objective To determine whether socioeconomic inequalities in primary care consultation rates for two major, disabling musculoskeletal conditions in England narrowed or widened between 2004-2019. Methods We analysed data from Clinical Practice Research Datalink Aurum, a national general practice electronic health records database, linked to national deprivation ranking of each patients’ registered residential postcode. For each year we estimated the age-sex standardised consultation incidence and prevalence for low back pain and osteoarthritis for the most deprived 10% of neighbourhoods through to the least deprived 10%. We then calculated the Slope Index of Inequality and Relative Index of Inequality overall, and by sex, age-group, and geographical region. Results Inequalities in LBP incidence and prevalence over socioeconomic status widened between 2004-2013 and stabilised between 2014-2019. Inequalities in OA incidence remained stable over socioeconomic status within study period, whereas inequalities in OA prevalence markedly widened over socioeconomic status between 2004-2019. Widest gap in LBP incidence and prevalence over socioeconomic status was observed in population resident in Northern English regions and London, and in those of working age, peaking at 45-54 years. Conclusions We found persistent, and generally increasing, socioeconomic inequalities in the rate of adults presenting to primary care in England with low back pain and osteoarthritis between 2004-2019. Lay summary What does this mean for patients? Our study describes the extent of social inequalities in how many adults present to primary care with a painful musculoskeletal condition. We focussed on two of the most common, disabling conditions: back pain and osteoarthritis. We analysed information from primary care electronic medical records across England. People living in the most deprived (“poorest”) neighbourhoods were more likely to seek the help of primary care than people of the same age and sex who lived in the least deprived (“richest”) neighbourhoods. Compared to general practices serving the richest neighbourhoods, a general practice serving the poorest neighbourhoods in England could see 15-40% more patients presenting with a new episode of back pain or osteoarthritis each year. These differences in rates between rich and poor were particularly noticeable among women, among working-age adults, and in the north of England and in London. Inequalities did not appear to have reduced between 2004 and 2019. Our study did not investigate underlying causes. However, it does highlight issues around workload and resourcing of general practices and the need for earlier and sustained preventive actions focussed towards poorer communities across England

Rheumatoid arthritis, psoriatic arthritis, and axial spondyloarthritis epidemiology in England from 2004 to 2020: An observational study using primary care electronic health record data.

Background: Contemporary data on rheumatoid arthritis (RA), psoriatic arthritis (PsA) and axial spondyloarthritits (SpA) epidemiology in England are lacking. This knowledge is crucial to planning healthcare services. We updated algorithms defining patients with diagnoses of RA, PsA, and axial SpA in primary care and applied them to describe their incidence and prevalence in the Clinical Practice Research Datalink Aurum, an electronic health record (EHR) database covering ∼20% of England. Methods: Algorithms for ascertaining patients with RA, axial SpA, and PsA diagnoses validated in primary care EHR databases using Read codes were updated (to account for the English NHS change to SNOMED CT diagnosis coding) and applied. Updated diagnosis and synthetic disease-modifying anti-rheumatic drug code lists were devised by rheumatologists and general practitioners. Annual incidence/point-prevalence of RA, PsA, and axial SpA diagnoses were calculated from 2004 to 2020 and stratified by age/sex. Findings: Point-prevalence of RA/PsA diagnoses increased annually, peaking in 2019 (RA 0·779% [95% confidence interval (CI) 0·773, 0·784]; PsA 0·287% [95% CI 0·284, 0·291]) then falling slightly. Point-prevalence of axial SpA diagnoses increased annually (except in 2018/2019), peaking in 2020 (0·113% [95% CI 0·111, 0·115]). RA diagnosis annual incidence was higher between 2013-2019 (after inclusion in the Quality and Outcomes Framework, range 49·1 [95% CI 47·7, 50·5] to 52·1 [95% CI 50·6, 53·6]/100,000 person-years) than 2004-2012 (range 34·5 [95% CI 33·2, 35·7] to 40·0 [95% CI 38·6, 41·4]/100,000 person-years). Increases in the annual incidence of PsA/axial SpA diagnosis occurred following new classification criteria publication. Annual incidence of RA, PsA and axial SpA diagnoses fell by 40·1%, 67·4%, and 38·1%, respectively between 2019 and 2020, likely reflecting the COVID-19 pandemic's impact on their diagnosis. Interpretation: Recorded RA, PsA, and axial SpA diagnoses are increasingly prevalent in England, underlining the importance of organising healthcare services to provide timely, treat-to-target care to optimise the health of >1% of adults in England. Funding: National Institute for Health and Care Research (NIHR300826)

Bayesian Multimodel Inference for Geostatistical Regression Models

The problem of simultaneous covariate selection and parameter inference for spatial regression models is considered. Previous research has shown that failure to take spatial correlation into account can influence the outcome of standard model selection methods. A Markov chain Monte Carlo (MCMC) method is investigated for the calculation of parameter estimates and posterior model probabilities for spatial regression models. The method can accommodate normal and non-normal response data and a large number of covariates. Thus the method is very flexible and can be used to fit spatial linear models, spatial linear mixed models, and spatial generalized linear mixed models (GLMMs). The Bayesian MCMC method also allows a priori unequal weighting of covariates, which is not possible with many model selection methods such as Akaike's information criterion (AIC). The proposed method is demonstrated on two data sets. The first is the whiptail lizard data set which has been previously analyzed by other researchers investigating model selection methods. Our results confirmed the previous analysis suggesting that sandy soil and ant abundance were strongly associated with lizard abundance. The second data set concerned pollution tolerant fish abundance in relation to several environmental factors. Results indicate that abundance is positively related to Strahler stream order and a habitat quality index. Abundance is negatively related to percent watershed disturbance

A pipeline to quantify serum and cerebrospinal fluid microRNAs for diagnosis and detection of relapse in paediatric malignant germ-cell tumours

Background:The current biomarkers alpha-fetoprotein and human chorionic gonadotropin have limited sensitivity and specificity for diagnosing malignant germ-cell tumours (GCTs). MicroRNAs (miRNAs) from the miR-371-373 and miR-302/367 clusters are overexpressed in all malignant GCTs, and some of these miRNAs show elevated serum levels at diagnosis. Here, we developed a robust technical pipeline to quantify these miRNAs in the serum and cerebrospinal fluid (CSF). The pipeline was used in samples from a cohort of exclusively paediatric patients with gonadal and extragonadal malignant GCTs, compared with appropriate tumour and non-tumour control groups.Methods:We developed a method for miRNA quantification that enabled sample adequacy assessment and reliable data normalisation. We performed qRT-PCR profiling for miR-371-373 and miR-302/367 cluster miRNAs in a total of 45 serum and CSF samples, obtained from 25 paediatric patients.Results:The exogenous non-human spike-in cel-miR-39-3p and the endogenous housekeeper miR-30b-5p were optimal for obtaining robust serum and CSF qRT-PCR quantification. A four-serum miRNA panel (miR-371a-3p, miR-372-3p, miR-373-3p and miR-367-3p): (i) showed high sensitivity/specificity for diagnosing paediatric extracranial malignant GCT; (ii) allowed early detection of relapse of a testicular mixed malignant GCT; and (iii) distinguished intracranial malignant GCT from intracranial non-GCT tumours at diagnosis, using CSF and serum samples.Conclusions:The pipeline we have developed is robust, scalable and transferable. It potentially promises to improve clinical management of paediatric (and adult) malignant GCTs