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Adaptive radiotherapy (ART) is commonly used to mitigate effects of anatomical change during head and neck (H&N) radiotherapy. The process of identifying patients for ART can be subjective and resource-intensive. This feasibility project aims to design and validate a pipeline to automate the process and use it to assess the current clinical pathway for H&N treatments.
Methods:
The pipeline analysed patients’ on-set cone-beam CT (CBCT) scans to identify inter-fractional anatomical changes. CBCTs were converted into synthetic CTs, contours were automatically generated, and the original plan was recomputed. Each synthetic CT was evaluated against a set of dosimetric goals, with failed goals causing an ART recommendation.
To validate pipeline performance, a ‘gold standard’ was synthesised by recomputing patients’ original plans on a rescan-CT acquired during treatment and identifying failed clinical goals. The pipeline sensitivity and specificity compared to this ‘gold standard’ were calculated for 12 ART patients. The pipeline was then run on a cohort of 12 ART and 14 non-ART patients, and its sensitivity and specificity were instead calculated against the clinical decision made.
Results:
The pipeline showed good agreement with the synthesised ‘gold standard’ with an optimum sensitivity of 0·83 and specificity of 0·67. When run over a cohort containing both ART and non-ART patients and assessed against the subjective clinical decision made, the pipeline showed no predictive power (sensitivity: 0·58, specificity: 0·47).
Conclusions:
Good agreement with the ‘gold standard’ gives confidence in pipeline performance and disagreement with clinical decisions implies implementation could help standardise the current clinical pathway.
Only a few years ago, the future of tax policy seemed clear to all. The rhetoric, and to some extent the reality, of tax policy were dominated by the image of “levelling the playing field”, and the much-touted phenomenon of “globalisation” was taken to mean that the field was likely to be levelled somewhere close to a common denominator. Governments were no longer growing, the “welfare state” was increasingly seen as obsolete, and only the occasional out-of-touch crank seemed at all concerned about the redistributive consequences of reducing taxes on wealth and high incomes.
This project developed and validated an automated pipeline for prostate treatments to accurately determine which patients could benefit from adaptive radiotherapy (ART) using synthetic CTs (sCTs) generated from on-treatment cone-beam CT (CBCT) images.
Materials and methods:
The automated pipeline converted CBCTs to sCTs utilising deep-learning, for accurate dose recalculation. Deformable image registration mapped contours from the planning CT to the sCT, with the treatment plan recalculated. A pass/fail assessment used relevant clinical goals. A fail threshold indicated ART was required. All acquired CBCTs (230 sCTs) for 31 patients (6 who had ART) were assessed for pipeline accuracy and clinical viability, comparing clinical outcomes to pipeline outcomes.
Results:
The pipeline distinguished patients requiring ART; 74·4% of sCTs for ART patients were red (failure) results, compared to 6·4% of non-ART sCTs. The receiver operator characteristic area under curve was 0·98, demonstrating high performance. The automated pipeline was statistically significantly (p < 0·05) quicker than the current clinical assessment methods (182·5s and 556·4s, respectively), and deformed contour accuracy was acceptable, with 96·6% of deformed clinical target volumes (CTVs) clinically acceptable.
Conclusion:
The automated pipeline identified patients who required ART with high accuracy while reducing time and resource requirements. This could reduce departmental workload and increase efficiency and personalisation of patient treatments. Further work aims to apply the pipeline to other treatment sites and investigate its potential for taking into account dose accumulation.
To investigate the symptoms of SARS-CoV-2 infection, their dynamics and their discriminatory power for the disease using longitudinally, prospectively collected information reported at the time of their occurrence. We have analysed data from a large phase 3 clinical UK COVID-19 vaccine trial. The alpha variant was the predominant strain. Participants were assessed for SARS-CoV-2 infection via nasal/throat PCR at recruitment, vaccination appointments, and when symptomatic. Statistical techniques were implemented to infer estimates representative of the UK population, accounting for multiple symptomatic episodes associated with one individual. An optimal diagnostic model for SARS-CoV-2 infection was derived. The 4-month prevalence of SARS-CoV-2 was 2.1%; increasing to 19.4% (16.0%–22.7%) in participants reporting loss of appetite and 31.9% (27.1%–36.8%) in those with anosmia/ageusia. The model identified anosmia and/or ageusia, fever, congestion, and cough to be significantly associated with SARS-CoV-2 infection. Symptoms’ dynamics were vastly different in the two groups; after a slow start peaking later and lasting longer in PCR+ participants, whilst exhibiting a consistent decline in PCR- participants, with, on average, fewer than 3 days of symptoms reported. Anosmia/ageusia peaked late in confirmed SARS-CoV-2 infection (day 12), indicating a low discrimination power for early disease diagnosis.
Trauma is prevalent amongst early psychosis patients and associated with adverse outcomes. Past trials of trauma-focused therapy have focused on chronic patients with psychosis/schizophrenia and comorbid Post-Traumatic Stress Disorder (PTSD). We aimed to determine the feasibility of a large-scale randomized controlled trial (RCT) of an Eye Movement Desensitization and Reprocessing for psychosis (EMDRp) intervention for early psychosis service users.
Methods
A single-blind RCT comparing 16 sessions of EMDRp + TAU v. TAU only was conducted. Participants completed baseline, 6-month and 12-month post-randomization assessments. EMDRp and trial assessments were delivered both in-person and remotely due to COVID-19 restrictions. Feasibility outcomes were recruitment and retention, therapy attendance/engagement, adherence to EMDRp treatment protocol, and the ‘promise of efficacy’ of EMDRp on relevant clinical outcomes.
Results
Sixty participants (100% of the recruitment target) received TAU or EMDR + TAU. 83% completed at least one follow-up assessment, with 74% at 6-month and 70% at 12-month. 74% of EMDRp + TAU participants received at least eight therapy sessions and 97% rated therapy sessions demonstrated good treatment fidelity. At 6-month, there were signals of promise of efficacy of EMDRp + TAU v. TAU for total psychotic symptoms (PANSS), subjective recovery from psychosis, PTSD symptoms, depression, anxiety, and general health status. Signals of efficacy at 12-month were less pronounced but remained robust for PTSD symptoms and general health status.
Conclusions
The trial feasibility criteria were fully met, and EMDRp was associated with promising signals of efficacy on a range of valuable clinical outcomes. A larger-scale, multi-center trial of EMDRp is feasible and warranted.
In 1961 twenty latin american countries signed a document which committed them “to reform tax laws, demanding more from those who have most, to punish tax evasion severely, and to redistribute the national income in order to benefit those who are most in need while, at the same time, promoting savings and investment and reinvestment of capital.” Both before and since this declaration a great deal of research on taxation has been carried out in Latin America, and even more has been said about the “need” for tax “reform.”
Not since the heyday of foreign tax missions in the 1960s has tax reform been discussed as intensively in Latin America. During the 1980s, major tax reforms took place in Mexico, Bolivia, Argentina, and Colombia, and somewhat similar reforms occurred in the previous decade in Chile and Uruguay. Moreover, tax reform seems to be climbing higher on the policy agenda in countries as diverse as Guatemala, Venezuela, Paraguay, and Peru.
Consider the following puzzle: given a number, remove k digits such that the resulting number is as large as possible. Various techniques are employed to derive a linear-time solution to the puzzle: we justify the structure of a greedy algorithm by predicate logic, give a constructive proof of the greedy condition using a dependently typed proof assistant and calculate the greedy step as well as the final, linear-time optimisation by equational reasoning.
The patient experience of radiotherapy magnetic resonance (MR) simulation is unknown. This study aims to evaluate the patient experience of MR simulation in comparison to computed tomography (CT) simulation, identifying the quality of patient experience and pathway changes which could improve patient experience outcomes.
Materials and Methods:
MR simulation was acquired for 46 anal and rectal cancer patients. Patient experience questionnaires were provided directly after MR simulation. Questionnaire responses were assessed after 33 patients (cohort one). Changes to the scanning pathway were identified and implemented. The impact of changes was assessed by cohort two (13 patients).
Results:
Response rates were 85% (cohort one) and 54% (cohort two). 75% of cohort one respondents found the magnetic resonance imaging (MRI) experience to be better or similar to their CT experience. Implemented changes included routine use of blankets, earplugs and headphones, music and feet-first positioning and further MRI protocol optimisation. All cohort two respondents found the MRI experience to be better or similar to the CT experience.
Findings:
MR simulation can be a comfortable and positive experience that is comparable to that of standard radiotherapy CT simulation. Special attention is required due to the fundamental differences between CT and MRI scanning.