Bone metastases from chondroblastoma: a rare pattern of metastatic disease in an adult.

Chondroblastoma is a rare benign tumor, typically presenting in the first two decades. Systemic metastases in chondroblastoma are extremely rare and it is the rarity of these metastases which lead the World Health Organisation to re-classify this lesion from "intermediate" to "benign" in its updated classification of bone tumors in 2020. We present an unusual case of a 55 year-old male patient who presented with multiple FDG-avid bone lesions on a background of conventional chondroblastoma of the rib excised at another institution 11-years previously. Two of these lesions were also histologically-proven as conventional chondroblastoma at biopsy. This case highlights that, although rare, metastases can be seen in patients with chondroblastoma. To our knowledge, this is the only case with an unusual pattern of metastases limited to bone.

Could ChatGPT Pass the UK Radiology Fellowship Examinations?

RATIONALE AND OBJECTIVES: Chat Generative Pre-trained Transformer (ChatGPT) is an artificial intelligence (AI) tool which utilises machine learning to generate original text resembling human language. AI models have recently demonstrated remarkable ability at analysing and solving problems, including passing professional examinations. We investigate the performance of ChatGPT on some of the UK radiology fellowship equivalent examination questions. METHODS: ChatGPT was asked to answer questions from question banks resembling the Fellowship of the Royal College of Radiologists (FRCR) examination. The entire physics part 1 question bank (203 5-part true/false questions) was answered by the GPT-4 model and answers recorded. 240 single best answer questions (SBAs) (representing the true length of the FRCR 2A examination) were answered by both GPT-3.5 and GPT-4 models. RESULTS: ChatGPT 4 answered 74.8% of part 1 true/false statements correctly. The spring 2023 passing mark of the part 1 examination was 75.5% and ChatGPT thus narrowly failed. In the 2A examination, ChatGPT 3.5 answered 50.8% SBAs correctly, while GPT-4 answered 74.2% correctly. The winter 2022 2A pass mark was 63.3% and thus GPT-4 clearly passed. CONCLUSION: AI models such as ChatGPT are able to answer the majority of questions in an FRCR style examination. It is reasonable to assume that further developments in AI will be more likely to succeed in comprehending and solving questions related to medicine, specifically clinical radiology. ADVANCES IN KNOWLEDGE: Our findings outline the unprecedented capabilities of AI, adding to the current relatively small body of literature on the subject, which in turn can play a role medical training, evaluation and practice. This can undoubtedly have implications for radiology.

Rapid development of COVID-19 rapid diagnostics for low resource settings: accelerating delivery through transparency, responsiveness, and open collaboration

Here we describe an open and transparent consortium for the rapid development of COVID-19 rapid diagnostics tests. We report diagnostic accuracy data on the Mologic manufactured IgG COVID-19 ELISA on known positive serum samples and on a panel of known negative respiratory and viral serum samples pre-December 2019. In January, Mologic, embarked on a product development pathway for COVID-19 diagnostics focusing on ELISA and rapid diagnostic tests (RDTs), with anticipated funding from Wellcome Trust and DFID. 834 clinical samples from known COVID-19 patients and hospital negative controls were tested on Mologics IgG ELISA. The reported sensitivity on 270 clinical samples from 124 prospectively enrolled patients was 94% (95% CI: 89.60% - 96.81%) on day 10 or more post laboratory diagnosis, and 96% (95% CI: 84.85% - 99.46%) between 14-21 days post symptom onset. A specificity panel comprising 564 samples collected pre-December 2019 were tested to include most common respiratory pathogens, other types of coronavirus, and flaviviruses. Specificity in this panel was 97% (95% CI: 95.65% - 98.50%). This is the first in a series of Mologic products for COVID-19, which will be deployed for COVID-19 diagnosis, contact tracing and sero-epidemiological studies to estimate disease burden and transmission with a focus on ensuring access, affordability, and availability to low-resource settings.

A phased approach to unlocking during the COVID-19 pandemic; Lessons from trend analysis

With the COVID-19 pandemic leading to radical political control of social behaviour, including restricted movement outsides homes. Can more detailed analysis of the published confirmed local case data from the pandemic in England using infection ratio and comparing local level data provide a deeper understanding of the wider community infection and inform the future unlocking process. The historic daily published 78,842 confirmed cases in England up to 13/4/2020 in each of 149 Upper Tier Local Authority (UTLA) were converted to Average Daily Infection Rate (RADIR), an R-value - the number of further people infected by one infected person after their 5-day incubation and during their 5-day infectious phase, and the associated Rate of Change of Infection Rate ({Delta}IR) also calculated. Results compared to look for significant variances between regions. Stepwise regression was carried out to see what local factors could be linked to the difference in local infection rates. The peak of COVID-19 infection has passed. The current RADIR is now below 1. The rate of decline is such that within 14 days it may be below 0.5. There are significant variations in the current RADIR and {Delta}IR between the UTLAs, suggesting that the disease locally may be at different stages. Regression analysis across UTLAs found that the only factor that could be related to the fall in RADIR was an increase in the number of confirmed infection/1,000 population. Extrapolation of these results showed that based on assuming a link to increased immunity, unreported community infection may be over 200 times higher than the reported confirmed cases providing evidence that by the end of the second week in April 26% of the population may already have had the disease and so now have increased immunity. Linking these increased estimated infected numbers to recorded deaths indicates a possible mortality rate of 0.14%. Analysis of the current reported local case data using the infectious ratio does provide greater insight into the current levels of community infection and can be used to make better-informed decisions about the future management of restricted social behaviour and movement

COVID-19: Modelling Local Transmission and Morbidity effects to provide an estimate of overall Relative Healthcare Resource Impact by General Practice Granularity

IntroductionSevere Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) is the name given to the 2019 novel coronavirus. COVID-19 is the name given to the disease associated with the virus. SARS-CoV-2 is a new strain of coronavirus that has not been previously identified in humans. MethodsTwo key factors were analysed which when multiplied together would give an estimate of relative demand on healthcare utilisation. These factors were case incidence and case morbidity. GP Practice data was used as this provided the most geographically granular source of published public population data. To analyse case incidence, the latest values for indicators that could be associated with infection transmission rates were collected from the Office of National Statistics (ONS) and Quality Outcome Framework (QOF) sources. These included population density, % age >16 at fulltime work/education, % age over 60, % BME ethnicity, social deprivation as IMD 2019, Location as latitude/longitude, and patient engagement as % self-confident in their own long term condition management. Average case morbidity was calculated by applying the international mortality Odds Ratio to the local population relevant age and disease prevalences and then summing and dividing by the equivalent national figure. To provide a comparative measure of overall healthcare resource impact, individual GP practice impact scores were compared against the median practice. ResultsThe case incidence regression is a dynamic situation with the significance of specific factors moderating over time as the balance between external infection, community transmission and impact of mitigation measures feeds through to the number of cases. It showed that currently Urban, % Working and age >60 were the strongest determinants of case incidence. The local population comorbidity remains unchanged. The range of relative HC impact was wide with 80% of practices falling between 20%-250% of the national median. Once practice population numbers were included it showed that the top 33% of GP practices supporting 45% of the patient population would require 68% of COVID-19 healthcare resources. The model provides useful information about the relative impact of Covid-19 on healthcare workload at GP practice granularity in all parts of England. ConclusionCovid-19 is impacting on the utilisation of health and social care resources across the country. This model provides a method for predicting relative local levels of disease burden based on defined criteria and thereby providing a method for targeting limited (and perhaps soon to be scarce) care resources to optimise national, regional and local responses to the COVID-19 outbreak..

A comparison of commercially available demineralized bone matrix for spinal fusion.

In an effort to augment the available grafting material as well as to increase spinal fusion rates, the utilization of a demineralized bone matrix (DBM) as a graft extender or replacement is common. There are several commercially available DBM substances available for use in spinal surgery, each with different amounts of DBM containing osteoinductive proteins. Each product may have different osteoinductivity potential due to different methods of preparation, storage, and donor specifications. The purpose of this study is to prospectively compare the osteoinductive potential of three different commercially available DBM substances in an athymic rodent spinal fusion model and to discuss the reasons of the variability in osteoinductivity. A posterolateral fusion was performed in 72 mature athymic nude female rats. Three groups of 18 rats were implanted with 1 of 3 DBMs (Osteofil, Grafton, and Dynagraft). A fourth group was implanted with rodent autogenous iliac crest bone graft. The rats were sacrificed at 2, 4, 6, and 8 weeks. A dose of 0.3 cm(3) per side (0.6 cm(3)per animal) was used for each substance. Radiographs were taken at 2 weeks intervals until sacrifice. Fusion was determined by radiographs, manual palpation, and histological analysis. The Osteofil substance had the highest overall fusion rate (14/18), and the highest early 4 weeks fusion rate of (4/5). Grafton produced slightly lower fusion rates of (11/17) overall, and lower early 4 weeks fusion rate of (2/5). There was no statistically significant difference between the rate of fusion after implantation of Osteofil and Grafton. None of the sites implanted with Dynagraft fused at any time point (0/17), and there was a significantly lower fusion rate between the Dynagraft and the other two substances at the six-week-time point and for final fusion rate (P = 0.0001, Fischer's exact test). None of the autogenous iliac crest animals fused at any time point. Non-decalcified histology confirmed the presence of a pseudarthrosis or the presence of a solid fusion, and the results were highly correlated with the manual testing. Although all products claim to have significant osteoinductive capabilities, this study demonstrates that there are significant differences between some of the tested products.