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INTRODUCTION: This work reports on a systematic approach to select MRI sequences, quantify inter-observer image registration variation and determine patient positioning for the clinical implementation of MR-guided adaptive radiotherapy (MRgRT) in patients with oropharyngeal (H&N) and lung cancer. METHODS: A total of 30 participants (N=10 H&N and N=10 lung cancer patients and N=10 healthy participants) were scanned on the Elekta Unity Magnetic Resonance Linear Accelerator (MRL). Participant experience questionnaires were used to determine the most appropriate positioning device for lung treatments and tolerability of H&N immobilization devices within the confined MR Linac environment. Visual guided assessments (VGAs) completed by three observers (one oncologist and two radiographers) were used to determine the most suitable tissue weighting (using vendor-provided 3D T1w and T2w sequences) for online image registration. Offline MRI to CT and MRI to MRI rigid registrations were undertaken by nine radiographers using bony and soft tissue matching. Single-factor ANOVA and paired t-tests were utilized to determine the interobserver variation. RESULTS: Based on oncologist and patient feedback, lung cancer patients would be treated in a vac-bag with their arms by their sides, while H&N cancer patients would be immobilized using a 5-point fixation device and 5-point personalized thermoplastic shell. There was no clear preference for T1w or T2w images in the H&N cohort. However, observers preferred T2w sequences for tumour and organ at risk (OAR) visualization in the lung images. When a bony match was conducted, single-factor ANOVA tests showed no statistically significant differences between all H&N image registration types (p=0.09). For the soft-tissue registrations, T1w-CT and T1w-T1w registrations showed a statistically significant (p=0.01) reduction in inter-observer variability over T2w-CT registrations. Paired t-tests showed no statistically significant differences for bony or soft tissue matches using T1w or T2w sequences to the planning CT in the lung cohorts (p=0.63 and p=0.52, respectively). CONCLUSION: We describe the systematic approach to the selection of strategies for imaging, immobilization, and online image registration we used for H&N and lung cancer treatments on the MRL. This has facilitated the selection of the most appropriate adaptive MRgRT strategies for treating these sites at our institution.
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PURPOSE: The current subclassifications of dry eye disease (DED) are aqueous deficient (ADDE) and evaporative (EDE) forms, but there lacks consistency in the clinical characteristics used to define each of these. This study used clinical data to inform cut-off values for the subclassification of ADDE and EDE, to allow more consistent study of the epidemiology of both DED subtypes. METHODS: The study enrolled 261 residents from the UK, extracted from a cohort with demographics representing the population (mean 42.4 ± 18.7 years, 56 % females). The TFOS DEWS II diagnostic criteria were used to identify those with DED. Meibomian gland loss/drop-out (from meibography), lipid layer thickness (LLT - from interferometry graded on the Guillon-Keeler scale), and tear meniscus height (TMH - Keratograph 5M) along with tear evaporation (Delfin Vapometer) were used to characterise the subclassification. The Dry Eye Risk Factor Survey was used to assess risk factors associated with each DED subtype. RESULTS: Compared to individuals who were not diagnosed with DED, EDE was characterized by signs of meibomian gland loss of > 28 %, LLT grade < 3 and tear evaporation > 46 g/m2/h. In contrast, ADDE was best characterized by a reduced TMH < 0.2 mm. Based on these criteria, the prevalence of ADDE was 6.2 %, EDE was 64.2 %, and 11.1 % exhibited features of both ADDE and EDE, with 18.5 % unclassified despite having a DED diagnosis. Contact lens wear and computer use were risk factors for ADDE (p < 0.05), whereas age was a positive risk factor for EDE (p < 0.01). Meibomian gland loss (occurring in 27.9 %) was the most commonly observed sign in EDE. CONCLUSIONS: Data driven-classification of DED confirms that the evaporative form is most prevalent and identified that in a generalisable UK population, ADDE alone occurs only in approximately 1 in 16 cases of DED.
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Background: Physical activity and sport (PAS) have been related to many health outcomes and social benefits. The main aim of this research is to build a Social Return on Investment (SROI) model of PAS based on experts' opinion to clarify the domains of impact and how to measure and value them. Methods and analysis: A Delphi method will be employed with a systematic review on the SROI framework applied to PAS and initial interviews with experts informing the design of the Delphi survey statements. Three iterative rounds of communication with the expert panel will be carried out. Participants will indicate their level of agreement with each statement on a five-point Likert scale. During the second and third iterative rounds, experts will reappraise the statements and will be provided with a summary of the group responses from the panel. A statement will have reached consensus if ≥70% of the panel agree/strongly agree or disagree/strongly disagree after round 3. Finally, group meetings (3-4 experts) will be conducted to ask about the measurement and valuation methods for each domain. Discussion: The final goal of this project will result in the design of a toolkit for organizations, professionals, and policymakers on how to measure the social benefits of PAS.