Dynamics of Daily Glioblastoma Evolution During Chemoradiation Therapy on the 0.35T Magnetic Resonance Imaging-Linear Accelerator.

PURPOSE: Glioblastoma changes during chemoradiation therapy are inferred from magnetic resonance imaging (MRI) before and after treatment but are rarely investigated due to logistics of frequent MRI. Using a combination MRI-linear accelerator (MRI-linac), we evaluated changes during daily chemoradiation therapy. METHODS AND MATERIALS: Patients with glioblastoma were prospectively imaged daily during chemoradiation therapy on 0.35T MRI-linac and at 3 timepoints with and without contrast on standalone high-field MRI. Tumor or edema (lesion) and resection cavity dynamics throughout treatment were analyzed and compared with standalone T1 postcontrast (T1+C) and T2 volumes. RESULTS: Of 36 patients included in this analysis, 8 had cavity only, 12 had lesion only, and 16 had both cavity and lesion. Of these, 64% had lesion growth and 46% had cavity shrinkage during treatment on MRI-linac scans. The average MRI-linac migration distance was 1.3 cm (range, 0-4.1 cm) for lesion and 0.6 cm (range, 0.1-2.1 cm) for cavity. Standalone versus MRI-linac volumes correlated strongly with R2 values: 0.991 (T2 vs MRI-linac cavity), 0.972 (T1+C vs MRI-linac cavity), and 0.973 (T2 vs MRI-linac lesion). There was a moderate correlation between T1+C and MRI-linac lesion (R2 = 0.609), despite noncontrast MRI-linac inability to separate contrast enhancement from surrounding nonenhancing tumor and edema. From pretreatment to posttreatment in patients with all available scans (n = 35), T1+C and MRI-linac lesions changed together-shrank (n = 6), grew (n = 12), or unchanged (n = 8)-in 26 (74%) patients. Another 9 patients (26%) had growth on MRI-linac, although the T1+C component shrank. In no patient did T1+C lesion grow while MRI-linac lesion shrank. CONCLUSIONS: Anatomic changes are seen in patients with glioblastoma imaged daily on MRI-linac throughout the chemoradiation therapy course. As surgical resection cavities shrink, margins may be reduced to save normal brain. Patients with unresected or growing lesions may require margin expansions to cover changes. Limited volume glioblastoma boost trials could consider triggered gadolinium contrast administration for evaluation of adaptive radiation therapy when lesion growth is seen on noncontrast MRI-linac.

Adjusting primary-care funding by deprivation: a cross-sectional study of lower-super-output-areas in England.

BACKGROUND: Previous research has called for General Practice (GP) funding to be adjusted by deprivation data. However, there is no evidence that this would better meet clinical need. AIM: We assessed 1. how accurately the capitation formula (Carr Hill), and total GP funding predicts clinical need and 2. whether adjusting by the Index of Multiple Deprivation score (IMD), improves accuracy. DESIGN & SETTING: Cross-sectional analysis of 32 844 Lower-Super-Output-Areas in England in 2021-2022. Sensitivity analysis used data from 2015-2019. METHOD: Weighted average Carr-Hill Index (CHI), total GP funding and five measures of clinical need were calculated for each LSOA. For both CHI and total funding, four sets of generalised linear models were calculated for each outcome measure: unadjusted; Age-adjusted; IMD-adjusted; and age and IMD adjusted. Adjusted R2 assessed model accuracy. RESULTS: In unadjusted models, CHI was a better predictor than total-funding of Combined Morbidity Index (CMI) (R2=49.81%,29.31% respectively), combined diagnosed and undiagnosed morbidity (R2=43.52%,21.9%), emergency admissions (R2=32.75%,16.95%). Total-funding was a better predictor than capitation of GP appointments per patient (R2=28.5%, 22.5% respectively) and age and sex standardised mortality rates (R2=0.42%,0.37%).. Adjusting for age and IMD improved all ten models (R2=62.2%,53.2%,48.6%,38.5%,40.5%, 32.8%, 29.1%,34.6%, 25.2%,25.2% respectively). All age and IMD adjusted models significantly outperformed age-adjusted models (p<0.001). Sensitivity analysis confirmed findings. CONCLUSION: Adjusting capitation or total-funding by IMD would increase funding efficiency, especially for long term outcomes, such as mortality. However, adjusting for IMD without age could have unwanted consequences.

Do primary care quality improvement frameworks consider equity?

BACKGROUND: Quality improvement (QI) is used by healthcare organisations internationally to improve care. Unless QI explicitly addresses equity, projects that aim to improve care may exacerbate health and care inequalities for disadvantaged groups. There are several QI frameworks used in primary care, but we do not know the extent to which they consider equity. This work aimed to investigate whether primary care QI frameworks consider equity. METHODS: We conducted a search of MEDLINE, EMBASE and key websites to compile a list of the QI frameworks used in primary care. This list was refined by an expert panel. Guidance documents for each of the QI frameworks were identified from national websites or QI organisations. We undertook a document analysis of the guidance using NVivo. RESULTS: We analysed 15 guidance documents. We identified the following themes: (1) there was a limited discussion of equity or targeted QI for disadvantaged groups in the documents, (2) there were indirect considerations of inequalities via patient involvement or targeting QI to patient demographics and (3) there was a greater focus on efficiency than equity in the documents. CONCLUSION: There is limited consideration of equity in QI frameworks used in primary care. Where equity is discussed, it is implicit and open to interpretation. This research demonstrates a need for frameworks to be revised with an explicit equity focus to ensure the distribution of benefits from QI is equitable.

How can healthcare organisations improve the social determinants of health for their local communities? Findings from realist-informed case studies among secondary healthcare organisations in England.

OBJECTIVES: Increasingly, healthcare and public health strategists invite us to look at healthcare organisations as not just care providers but as anchor institutions (ie, large community-rooted organisations with significant impact in the local economy, social fabric and overall community well-being). In response, this study explores the mechanisms through which healthcare organisations can impact social determinants of health and communities in their local areas. DESIGN: We conducted case studies with interviews and synthesised the findings using a realist approach to produce a set of explanations (programme theory) of how healthcare organisations can have a positive impact on the overall well-being of local communities by operating as anchor institutions. SETTING: Secondary healthcare organisations in England, including mental health and community services. PARTICIPANTS: Staff from case study sites which were directly employed or actively engaged in the organisation's anchor institution strategy. Data collection took place from early June to the end of August 2023. RESULTS: We found four building blocks for effective anchor activity including employment, spending, estates and sustainability. Healthcare organisations-as anchor institutions-can improve the social determinants of health for their local communities through enabling accessible paths for local community recruitment and career progression; empowering local businesses to join supply chains boosting income and wealth; transforming organisational spaces into community assets; and supporting local innovation and technology to achieve their sustainability goals. These blocks need to be integrated across organisations on the basis of a population health approach promoted by supportive leadership, and in collaboration with a diverse range of local partners. CONCLUSIONS: Healthcare organisations have the potential for a positive impact on the overall well-being of local communities. Policymakers should support healthcare organisations to leverage employment, spending, estates and sustainability to help address the unequal distribution of the social determinants of health.

Practice list size, workforce composition and performance in English general practice: a latent profile analysis.

BACKGROUND: Following government calls for General Practices in England to work at scale, some practices have grown in size from traditionally small, General Practitioner (GP)-led organisations to large multidisciplinary enterprises. We assessed the effect of practice list size and workforce composition on practice performance in clinical outcomes and patient experience. METHODS: We linked five practice-level datasets in England to obtain a single dataset of practice workforce, list size, proportion of registered patients ≥ 65 years of age, female-male sex ratio, deprivation, rurality, GP contract type, patient experience of care, and Quality and Outcomes Framework (QOF) and non-QOF clinical processes and outcomes. Latent Profile Analysis (LPA) was used to cluster general practices into groups based on practice list size and workforce composition. Bayesian Information Criterion, Akaike Information Criterion and deliberation within the research team were used to determine the most informative number of groups. One-way ANOVA was used to assess how groups differed on indicator variables and other variables of interest. Linear regression was used to assess the association between practice group and practice performance. RESULTS: A total of 6024 practices were available for class assignment. We determined that a 3-class grouping provided the most meaningful interpretation; 4494 (74.6%) were classified as 'Small GP-reliant practices', 1400 (23.2%) were labelled 'Medium-size GP-led practices with a multidisciplinary team (MDT) input' and 131 (2.2%) practices were named 'Large multidisciplinary practices'. Small GP-reliant practices outperformed larger multidisciplinary practices on all patient-reported indicators except on confidence and trust where medium-size GP-led practices with MDT input appeared to do better. There was no difference in performance between small GP-reliant practices and larger multidisciplinary practices on QOF incentivised indicators except on asthma reviews where medium-size GP-led practices with MDT input performed worse than smaller GP-reliant practices and immunisation coverage where the same group performed better than smaller GP-reliant practices. For non-incentivised indicators, larger multidisciplinary practices had higher cancer detection rates than small GP-reliant practices. CONCLUSION: Small GP-reliant practices were found to provide better patient reported access, continuity of care, experience and satisfaction with care. Larger multidisciplinary practices appeared to have better cancer detection rates but had no effect on other clinical processes and outcomes. As England moves towards larger multidisciplinary practices efforts should be made to preserve good patient experience.

Increasing the efficiency of cone-beam CT based delta-radiomics using automated contours to predict radiotherapy-related toxicities in prostate cancer.

Extracting longitudinal image quantitative data, known as delta-radiomics, has the potential to capture changes in a patient's anatomy throughout the course of radiation treatment for prostate cancer. Some of the major challenges of delta-radiomics studies are contouring the structures for individual fractions and accruing patients' data in an efficient manner. The manual contouring process is often time consuming and would limit the efficiency of accruing larger sample sizes for future studies. The problem is amplified because the contours are often made by highly trained radiation oncologists with limited time to dedicate to research studies of this nature. This work compares the use of automated prostate contours generated using a deformable image-based algorithm to make predictive models of genitourinary and changes in total international prostate symptom score in comparison to manually contours for a cohort of fifty patients. Area under the curve of manual and automated models were compared using the Delong test. This study demonstrated that the delta-radiomics models were similar for both automated and manual delta-radiomics models.

Correction: Won et al. Ex Vivo Perfusion Using a Mathematical Modeled, Controlled Gas Exchange Self-Contained Bioreactor Can Maintain a Mouse Kidney for Seven Days. Cells 2022, 11, 1822.

In the original publication [...].

Reducing health inequalities through general practice: a realist review and action framework.

Background: Socio-economic inequalities in health have been in the public agenda for decades. General practice has an influential role to play in mitigating the impact of inequalities especially regarding chronic conditions. At the moment, general practice is dealing with serious challenges in relation to workforce shortages, increasing workload and the impact of the COVID-19 pandemic. It is important to identify effective ways so that general practice can play its role in reducing health inequalities. Objectives: We explored what types of interventions and aspects of routine care in general practice decrease or increase inequalities in health and care-related outcomes. We focused on cardiovascular disease, cancer, diabetes and/or chronic obstructive pulmonary disease. We explored for whom these interventions and aspects of care work best, why, and in what circumstances. Our main objective was to synthesise this evidence into specific guidance for healthcare professionals and decision-makers about how best to achieve equitable general practice. Design: Realist review. Main outcome measures: Clinical or care-related outcomes by socio-economic group, or other PROGRESS-Plus criteria. Review methods: Realist review based on Pawson's five steps: (1) locating existing theories, (2) searching for evidence, (3) selecting articles, (4) extracting and organising data and (5) synthesising the evidence. Results: Three hundred and twenty-five studies met the inclusion criteria and 159 of them were selected for the evidence synthesis. Evidence about the impact of general practice interventions on health inequalities is limited. To reduce health inequalities, general practice needs to be: • connected so that interventions are linked and coordinated across the sector; • intersectional to account for the fact that people's experience is affected by many of their characteristics; • flexible to meet patients' different needs and preferences; • inclusive so that it does not exclude people because of who they are; • community-centred so that people who receive care engage with its design and delivery. These qualities should inform action across four domains: structures like funding and workforce distribution, organisational culture, everyday regulated procedures involved in care delivery, interpersonal and community relationships. Limitations: The reviewed evidence offers limited detail about the ways and the extent to which specific interventions increase or decrease inequalities in general practice. Therefore, we focused on the underpinning principles that were common across interventions to produce higher-level, transferrable conclusions about ways to achieve equitable care. Conclusions: Inequalities in general practice result from complex processes across four different domains that include structures, ideas, regulated everyday procedures, and relationships among individuals and communities. To achieve equity, general practice needs to be connected, intersectional, flexible, inclusive and community-centred. Future work: Future work should focus on how these five essential qualities can be better used to shape the organisational development of future general practice. Study registration: This trial is registered as PROSPERO CRD42020217871. Funding: This award was funded by the National Institute for Health and Care Research (NIHR) Health and Social Care Delivery Research programme (NIHR award ref: NIHR130694) and is published in full in Health and Social Care Delivery Research; Vol. 12, No. 7. See the NIHR Funding and Awards website for further award information.

Health inequalities are unfair differences in health across different groups of the population. In the United Kingdom, the health inequality gap in life expectancy between the richest and poorest is increasing and is caused mostly by differences in long-term conditions like cancer and cardiovascular disease and respiratory conditions, such as chronic obstructive pulmonary disease. Partly National Health Service inequalities arise in delays in seeing a doctor and care provided through doctors' surgery, such as delays in getting tests. This study explored how general practice services can increase or decrease inequalities in cancer, cardiovascular disease, diabetes and chronic obstructive pulmonary disease, under what circumstances and for whom. It also produced guidance for general practice, both local general practices and the wider general practice system, to reduce inequalities. We reviewed existing studies using a realist methodology. This methodology helps us understand the different contexts in which interventions work or not. We found that inequalities in general practice result from complex processes across different areas. These include funding and workforce, perceptions about health and disease among patients and healthcare staff, everyday procedures involved in care delivery, and relationships among individuals and communities. To reduce inequalities in general practice, action should be taken in all these areas and services need to be connected (i.e. linked and coordinated across the sector), intersectional (i.e. accounting for the fact that people's experience is affected by many of their characteristics like their gender and socio-economic position), flexible (i.e. meeting patients' different needs and preferences), inclusive (i.e. not excluding people because of who they are) and community-centred (i.e. working with the people who will receive care when designing and providing it). There is no one single intervention that will make general practice more equitable, rather it requires long-term organisational change based on these principles.

Implementation and evaluation of a dynamic contrast-enhanced MR perfusion protocol for glioblastoma using a 0.35 T MRI-Linac system.

PURPOSE: MRI-linear accelerator (MRI-Linac) systems allow for daily tracking of MRI changes during radiotherapy (RT). Since one common MRI-Linac operates at 0.35 T, there are efforts towards developing protocols at that field strength. In this study we demonstrate the implementation of a post-contrast 3DT1-weighted (3D-T1w) and dynamic contrast-enhancement (DCE) protocol to assess glioblastoma response to RT using a 0.35 T MRI-Linac. METHODS AND MATERIALS: The protocol implemented was used to acquire 3D-T1w and DCE data from a flow phantom and two patients with glioblastoma (a responder and a non-responder) who underwent RT on a 0.35 T MRI-Linac. The detection of post-contrast-enhanced volumes was evaluated by comparing the 3DT1w images from the 0.35 T MRI-Linac to images obtained using a 3 T scanner. The DCE data were tested temporally and spatially using data from a flow phantom and patients. Ktrans maps were derived from DCE at three time points (a week before treatment-Pre RT, four weeks through treatment-Mid RT, and three weeks after treatment-Post RT) and were validated with patients' treatment outcomes. RESULTS: The 3D-T1w contrast-enhancement volumes were visually and volumetrically similar between 0.35 T MRI-Linac and 3 T. DCE images showed temporal stability, and associated Ktrans maps were consistent with patient response to treatment. On average, Ktrans values showed a 54 % decrease and 8.6 % increase for a responder and non-responder respectively when Pre RT and Mid RT images were compared. CONCLUSION: Our findings support the feasibility of obtaining post-contrast 3D-T1w and DCE data from patients with glioblastoma using a 0.35 T MRI-Linac system.

How and why do financial incentives contribute to helping people stop smoking? A realist review.

BACKGROUND: Tobacco smoking remains a key cause of preventable illness and death globally. In response, many countries provide extensive services to help people to stop smoking by offering a variety of effective behavioural and pharmacological therapies. However, many people who wish to stop smoking do not have access to or use stop smoking supports, and new modes of support, including the use of financial incentives, are needed to address this issue. A realist review of published international literature was undertaken to understand how, why, for whom, and in which circumstances financial incentives contribute to success in stopping smoking for general population groups and among pregnant women. METHODS: Systematic searches were undertaken from inception to February 2022 of five academic databases: MEDLINE (ovid), Embase.com, CIHAHL, Scopus and PsycINFO. Study selection was inclusive of all study designs. Twenty-two studies were included. Using Pawson and Tilley's iterative realist review approach, data collected were screened, selected, coded, analysed, and synthesised into a set of explanatory theoretical findings. RESULTS: Data were synthesised into six Context-Mechanism-Outcome Configurations and one overarching programme theory after iterative rounds of analysis, team discussion, and expert panel feedback. Our programme theory shows that financial incentives are particularly useful to help people stop smoking if they have a financial need, are pregnant or recently post-partum, have a high threshold for behaviour change, and/or respond well to external rewards. The incentives work through a number of mechanisms including the role their direct monetary value can play in a person's life and through a process of reinforcement where they can help build confidence and self-esteem. CONCLUSION: This is the first realist review to synthesise how, why, and for whom financial incentives work among those attempting to stop smoking, adding to the existing evidence demonstrating their efficacy. The findings will support the implementation of current knowledge into effective programmes which can enhance the impact of stop smoking care. PROSPERO REGISTRATION NUMBER: CRD42022298941.

Does workforce explain the relationship between funding and patient experience? A mediation analysis of primary care data in England.

OBJECTIVES: To determine whether general practitioner (GP) workforce contributes to the link between practice funding and patient experience. Specifically, to determine whether increased practice funding is associated with better patient experience, and to what degree an increase in workforce accounts for this relationship. SETTING: Primary care practice level analysis of workforce, funding and patient experience of all NHS practices in England. PRIMARY AND SECONDARY OUTCOME MEASURES: The link between NHS-provided funding to general practice (payments per patient) and patient experience, as per the General Practice Patient Survey, was evaluated. Subsequently, mediation analysis, adjusted for covariates, was used to scrutinise the extent to which GP workforce accounts for this relationship (measured as the number of GPs per 10 000 patients). PARTICIPANTS: We included all general practices in England for which there was relevant data for each primary variable. Atypical practices were excluded, such as those with a patient list size of 0 or where the workforce variable was recorded as being more than 3 SD from the mean. After exclusion, 6139 practices were included in the final analysis. RESULTS: We found that workforce (GPs per 10 000 population) significantly (p<0.001) acts as a mediator in the effect of practice funding on overall patient experience even after adjusting for rurality, sex and age, and deprivation. On average, the mediated effect constitutes 30% of the total effect of practice funding on patient experience. CONCLUSIONS: The increase in the number of doctors in primary care in England appears to be a mechanism through which augmented practice funding could positively impact patient experience. Policy initiatives targeting improved patient experience should prioritise considerations related to workforce and practice funding.

Bellwethers of change: population modelling of North Pacific humpback whales from 2002 through 2021 reveals shift from recovery to climate response.

For the 40 years after the end of commercial whaling in 1976, humpback whale populations in the North Pacific Ocean exhibited a prolonged period of recovery. Using mark-recapture methods on the largest individual photo-identification dataset ever assembled for a cetacean, we estimated annual ocean-basin-wide abundance for the species from 2002 through 2021. Trends in annual estimates describe strong post-whaling era population recovery from 16 875 (± 5955) in 2002 to a peak abundance estimate of 33 488 (± 4455) in 2012. An apparent 20% decline from 2012 to 2021, 33 488 (± 4455) to 26 662 (± 4192), suggests the population abruptly reached carrying capacity due to loss of prey resources. This was particularly evident for humpback whales wintering in Hawai'i, where, by 2021, estimated abundance had declined by 34% from a peak in 2013, down to abundance levels previously seen in 2006, and contrasted to an absence of decline in Mainland Mexico breeding humpbacks. The strongest marine heatwave recorded globally to date during the 2014-2016 period appeared to have altered the course of species recovery, with enduring effects. Extending this time series will allow humpback whales to serve as an indicator species for the ecosystem in the face of a changing climate.

A systematic review of 'equity-focused' game-based learning in the teaching of health staff.

Background: An unequal distribution of the social determinants of health drives health inequalities. Existing training fails to communicate the impossible circumstances that disadvantaged groups face. Game-based learning is increasingly used as an innovative method with the potential to enhance health staff's ability to address health inequalities, but its effectiveness is unknown. Therefore, the aim of this systematic review was to evaluate the effectiveness of 'equity-focused' game-based learning in training health staff. Study design: Systematic Review. Methods: Three databases (Ovid Medline, Embase, Web of Science) and a citation search were systematically searched for articles from January 2010 to July 2023, reporting on effectiveness of 'equity-focused' game-based learning. Titles and abstracts were screened using eligibility criteria to identify relevant studies. Data was extracted and the ROBINS-I tool was used to assess quality. Results: The search identified 7615 articles, of which thirteen were included involving 2412 healthcare workers. A variety of game-based learning tools were found to have an overall positive effect on motivation, knowledge, attitudes, and engagement of health staff. However, the significance of the results varied depending on specific game context. All included studies were judged to have serious to critical risk of bias. Conclusions: Game-based learning has the potential to improve the effectiveness of 'equity-focused' training for health staff. Educators and researchers should further collaborate to expand the tools available and evaluate their effectiveness on long-term clinical practice.

Uncovering prostate cancer aggressiveness signal in T2-weighted MRI through a three-reference tissues normalization technique.

Quantitative T2-weighted MRI (T2W) interpretation is impeded by the variability of acquisition-related features, such as field strength, coil type, signal amplification, and pulse sequence parameters. The main purpose of this work is to develop an automated method for prostate T2W intensity normalization. The procedure includes the following: (i) a deep learning-based network utilizing MASK R-CNN for automatic segmentation of three reference tissues: gluteus maximus muscle, femur, and bladder; (ii) fitting a spline function between average intensities in these structures and reference values; and (iii) using the function to transform all T2W intensities. The T2W distributions in the prostate cancer regions of interest (ROIs) and normal appearing prostate tissue (NAT) were compared before and after normalization using Student's t-test. The ROIs' T2W associations with the Gleason Score (GS), Decipher genomic score, and a three-tier prostate cancer risk were evaluated with Spearman's correlation coefficient (rS ). T2W differences in indolent and aggressive prostate cancer lesions were also assessed. The MASK R-CNN was trained with manual contours from 32 patients. The normalization procedure was applied to an independent MRI dataset from 83 patients. T2W differences between ROIs and NAT significantly increased after normalization. T2W intensities in 231 biopsy ROIs were significantly negatively correlated with GS (rS = -0.21, p = 0.001), Decipher (rS = -0.193, p = 0.003), and three-tier risk (rS = -0.235, p < 0.001). The average T2W intensities in the aggressive ROIs were significantly lower than in the indolent ROIs after normalization. In conclusion, the automated triple-reference tissue normalization method significantly improved the discrimination between prostate cancer and normal prostate tissue. In addition, the normalized T2W intensities of cancer exhibited a significant association with tumor aggressiveness. By improving the quantitative utilization of the T2W in the assessment of prostate cancer on MRI, the new normalization method represents an important advance over clinical protocols that do not include sequences for the measurement of T2 relaxation times.

What impact do self-referral and direct access pathways for patients have on health inequalities?

BACKGROUND: There is increasing interest in self-referral and direct access as alternatives pathways to care to improve patient access to specialist services. The impact of these pathways on health inequalities is unknown. OBJECTIVES: The purpose of this systematic review is to explore the impact of self-referral and direct access pathways on inequalities in health care use. DESIGN: Three databases (Ovid Medline, Embase, Web of Science) and grey literature were systematically searched for articles from January 2000 to February 2023, reporting on self-referral and direct access pathways to care. Title and abstracts were screened against eligibility criteria to identify studies that evaluated the impact on health inequalities. Data were extracted from eligible studies after full text review and a quality assessment was performed using the ROBINS-I tool. RESULTS: The search strategy identified 2948 articles. Nineteen records were included, covering seven countries and six healthcare services. The impact of self-referral and direct access on inequalities was mixed, suggesting that the relationship is dependent on patient and system factors. Typically self-referral pathways and direct access pathways tend to widen health inequalities. White, younger, educated women from less deprived backgrounds are more likely to self-refer, exacerbating existing health inequalities. CONCLUSIONS: Self-referral pathways risk widening health inequalities. Further research is required to understand the context-dependent mechanisms by which this can occur, explore ways to mitigate this and even narrow health inequalities, as well as understand the impact on the wider healthcare system.

Single-handed versus multiple-handed General practices: A cross-sectional study of quality outcomes in England.

OBJECTIVES: As general practice increasingly moves towards large group practices, there is debate about the relative benefits, safety and sustainability of different care delivery models. This study investigates the performance of single-handed practices compared to practices with multiple doctors in England, UK. METHODS: Practices in England with more than 1000 patients were included. Workforce data and a quality control process classified practices as single-handed or multiple-handed. Outcomes were (i) GP patient survey scores measuring access, continuity, confidence in health professional and overall satisfaction; (ii) reported diabetes and hypertension outcomes; and (iii) emergency department presentation rates and cancer detection (percentage of cancers diagnosed by a 2-week wait). Generalised linear models, controlling for patient and practice characteristics, compared outcomes in single and multiple-handed practices and assessed the effect of GP age in single-handed practices. RESULTS: Single-handed practices were more commonly found in areas of high deprivation (41% compared to 20% of multiple-handed practices). Single-handed practices had higher patient-reported access, continuity and overall satisfaction but slightly lower diabetes management and cancer detection rates. Emergency department presentations were higher when controlling for patient characteristics in single-handed practices but not when also controlling for practice rurality and size. Increased deprivation was associated with lower performance in seven out of eight outcomes. CONCLUSIONS: We found single-handed practices to be associated with high patient satisfaction while performing slightly less well on selected clinical outcomes. Further research is required to better understand the association between practice size, including increasing multidisciplinary working, on patient experience and outcomes.

Improvement of 2D cine image quality using 3D priors and cycle generative adversarial network for low field MRI-guided radiation therapy.

BACKGROUND: Cine magnetic resonance (MR) images have been used for real-time MR guided radiation therapy (MRgRT). However, the onboard MR systems with low-field strength face the problem of limited image quality. PURPOSE: To improve the quality of cine MR images in MRgRT using prior image information provided by the patient planning and positioning MR images. METHODS: This study employed MR images from 18 pancreatic cancer patients who received MR-guided stereotactic body radiation therapy. Planning 3D MR images were acquired during the patient simulation, and positioning 3D MR images and 2D sagittal cine MR images were acquired before and during the beam delivery, respectively. A deep learning-based framework consisting of two cycle generative adversarial networks (CycleGAN), Denoising CycleGAN and Enhancement CycleGAN, was developed to establish the mapping between the 3D and 2D MR images. The Denoising CycleGAN was trained to first denoise the cine images using the time domain cine image series, and the Enhancement CycleGAN was trained to enhance the spatial resolution and contrast by taking advantage of the prior image information from the planning and positioning images. The denoising performance was assessed by signal-to-noise ratio (SNR), structural similarity index measure, peak SNR, blind/reference-less image spatial quality evaluator (BRISQUE), natural image quality evaluator, and perception-based image quality evaluator scores. The quality enhancement performance was assessed by the BRISQUE and physician visual scores. In addition, the target contouring was evaluated on the original and processed images. RESULTS: Significant differences were found for all evaluation metrics after Denoising CycleGAN processing. The BRISQUE and visual scores were also significantly improved after sequential Denoising and Enhancement CycleGAN processing. In target contouring evaluation, Dice similarity coefficient, centroid distance, Hausdorff distance, and average surface distance values were significantly improved on the enhanced images. The whole processing time was within 20 ms for a typical input image size of 512 × 512. CONCLUSION: Taking advantage of the prior high-quality positioning and planning MR images, the deep learning-based framework enhanced the cine MR image quality significantly, leading to improved accuracy in automatic target contouring. With the merits of both high computational efficiency and considerable image quality enhancement, the proposed method may hold important clinical implication for real-time MRgRT.