Prostate MR image quality of apparent diffusion coefficient maps versus fractional intracellular volume maps from VERDICT MRI using the PI-QUAL score and a dedicated Likert scale for artefacts

PURPOSE: This study aimed to assess the image quality of apparent diffusion coefficient (ADC) maps derived from conventional diffusion-weighted MRI and fractional intracellular volume maps (FIC) from VERDICT MRI (Vascular, Extracellular, Restricted Diffusion for Cytometry in Tumours) in patients from the INNOVATE trial. The inter-reader agreement was also assessed. METHODS: Two readers analysed both ADC and FIC maps from 57 patients enrolled in the INNOVATE prospective trial. Image quality was assessed using the Prostate Imaging Quality (PI-QUAL) score and a subjective image quality Likert score (Likert-IQ). The image quality of FIC and ADC were compared using a Wilcoxon Signed Ranks test. The inter-reader agreement was assessed with Cohen's kappa. RESULTS: There was no statistically significant difference between the PI-QUAL score for FIC datasets compared to ADC datasets for either reader (p = 0.240 and p = 0.614). Using the Likert-IQ score, FIC image quality was higher compared to ADC (p = 0.021) as assessed by reader-1 but not for reader-2 (p = 0.663). The inter-reader agreement was 'fair' for PI-QUAL scoring of datasets with FIC maps at 0.27 (95% confidence interval; 0.08-0.46) and ADC datasets at 0.39 (95% confidence interval 0.22-0.57). For Likert scoring, the inter-reader agreement was also 'fair' for FIC maps at 0.38 (95% confidence interval; 0.10-0.65) and substantial for ADC maps at 0.62 (95% confidence interval; 0.39-0.86). CONCLUSION: Image quality was comparable for FIC and ADC. The inter-reader agreement was similar when using PIQUAL for both FIC and ADC datasets but higher for ADC maps compared to FIC maps using the image quality Likert score

Development and Assessment of an Artificial Intelligence-Based Tool for Ptosis Measurement in Adult Myasthenia Gravis Patients Using Selfie Video Clips Recorded on Smartphones

Introduction: Myasthenia gravis (MG) is a rare autoimmune disease characterized by muscle weakness and fatigue. Ptosis (eyelid drooping) occurs due to fatigue of the muscles for eyelid elevation and is one symptom widely used by patients and healthcare providers to track progression of the disease. Margin reflex distance 1 (MRD1) is an accepted clinical measure of ptosis and is typically assessed using a hand-held ruler. In this work, we develop an AI model that enables automated measurement of MRD1 in self-recorded video clips collected using patient smartphones. Methods: A 3-month prospective observational study collected a dataset of video clips from patients with MG. Study participants were asked to perform an eyelid fatigability exercise to elicit ptosis while filming “selfie” videos on their smartphones. These images were collected in nonclinical settings, with no in-person training. The dataset was annotated by non-clinicians for (1) eye landmarks to establish ground truth MRD1 and (2) the quality of the video frames. The ground truth MRD1 (in millimeters, mm) was calculated from eye landmark annotations in the video frames using a standard conversion factor, the horizontal visible iris diameter of the human eye. To develop the model, we trained a neural network for eye landmark detection consisting of a ResNet50 backbone plus two dense layers of 78 dimensions on publicly available datasets. Only the ResNet50 backbone was used, discarding the last two layers. The embeddings from the ResNet50 were used as features for a support vector regressor (SVR) using a linear kernel, for regression to MRD1, in mm. The SVR was trained on data collected remotely from MG patients in the prospective study, split into training and development folds. The model’s performance for MRD1 estimation was evaluated on a separate test fold from the study dataset. Results: On the full test fold (N = 664 images), the correlation between the ground truth and predicted MRD1 values was strong (r = 0.732). The mean absolute error was 0.822 mm; the mean of differences was −0.256 mm; and 95% limits of agreement (LOA) were −0.214–1.768 mm. Model performance showed no improvement when test data were gated to exclude “poor” quality images. Conclusions: On data generated under highly challenging real-world conditions from a variety of different smartphone devices, the model predicts MRD1 with a strong correlation (r = 0.732) between ground truth and predicted MRD1

Whole genome sequencing in the investigation of recurrent invasive Group A streptococcus outbreaks in a maternity unit

Background: The clinical manifestations of Group A streptococcus (GAS) – (Streptococcus pyogenes) are diverse, ranging from asymptomatic colonisation to devastating invasive disease. Maternity related clusters of invasive Group A streptococcus (iGAS) infection are complex to investigate and control, especially if recurrent. Aim: We report on the investigation into three episodes of emm 75 GAS/iGAS infection in maternity patients at one hospital site over a 4 year period, two with monophyletic ancestry. Methods: The episodes are described, together with whole genome sequence isolate analyses. Single nucleotide polymorphism differences were compared with contemporaneous emm 75 genomes. Findings: Seven mothers had GAS/iGAS in over a 4 year period, emm 75, S.pyogenes and one had iGAS (in year 4) emm 3, S.pyogenes (subsequently discounted as linked). Three (clinical/screening samples) of the seven babies of emm 75 positive mothers and 3 screened healthcare workers were positive for GAS emm 75. Whole genome sequence similarity suggests a shared ancestral lineage and suggested a common source transmission but directionality of transmission cannot be inferred. However the findings indicate that persistence of a particular clone in a given setting may be long-term. Conclusions: Occupational health procedures were enhanced, staff were screened and antibiotic therapy provided to GAS positive staff and patients. The definitive source of infection could not be identified, although staff/patient transmission is the most likely route. The pattern of clonal GAS transmission over 4 years suggests long-term persistence of GAS may have occurred

Digital clubbing in tuberculosis – relationship to HIV infection, extent of disease and hypoalbuminemia

BACKGROUND: Digital clubbing is a sign of chest disease known since the time of Hippocrates. Its association with tuberculosis (TB) has not been well studied, particularly in Africa where TB is common. The prevalence of clubbing in patients with pulmonary TB and its association with Human Immunodeficiency Virus (HIV), severity of disease, and nutritional status was assessed. METHODS: A cross-sectional study was carried out among patients with smear-positive TB recruited consecutively from the medical and TB wards and outpatient clinics at a public hospital in Uganda. The presence of clubbing was assessed by clinical signs and measurement of the ratio of the distal and inter-phalangeal diameters (DPD/IPD) of both index fingers. Clubbing was defined as a ratio > 1.0. Chest radiograph, serum albumin and HIV testing were done. RESULTS: Two hundred patients (82% HIV-infected) participated; 34% had clubbing by clinical criteria whilst 30% had clubbing based on DPD/IPD ratio. Smear grade, extensive or cavitary disease, early versus late HIV disease, and hypoalbuminemia were not associated with clubbing. Clubbing was more common among patients with a lower Karnofsky performance scale score or with prior TB. CONCLUSION: Clubbing occurs in up to one-third of Ugandan patients with pulmonary TB. Clubbing was not associated with stage of HIV infection, extensive disease or hypoalbuminemia

Touching liberty: abolition, feminism, and the politics of the body

In this striking study of the pre-Civil War literary imagination, Karen Sánchez-Eppler charts how bodily difference came to be recognized as a central problem for both political and literary expression. Her readings of sentimental anti-slavery fiction, slave narratives, and the lyric poetry of Walt Whitman and Emily Dickinson demonstrate how these texts participated in producing a new model of personhood, one in which the racially distinct and physically constrained slave body converged with the sexually distinct and domestically circumscribed female body.Moving from the public domain of abolitionist politics to the privacy of lyric poetry, Sánchez-Eppler argues that attention to the physical body blurs the boundaries between public and private. Drawing analogies between black and female bodies, feminist-abolitionists use the public sphere of anti-slavery politics to write about sexual desires and anxieties they cannot voice directly.Sánchez-Eppler warns against exaggerating the positive links between literature and politics, however. She finds that the relationships between feminism and abolitionism reveal patterns of exploitation, appropriation, and displacement of the black body that acknowledge the difficulties in embracing "difference," in the nineteenth century as in the twentieth. Her insightful examination of issues that continue to be relevant today will make a distinctive mark on American literary and cultural studies

Research data supporting Protective human IgE responses are promoted by comparable life-cycle dependent Tegument Allergen-Like protein expression in Schistosoma haematobium and Schistosoma mansoni infection

Individual level S. mansoni infection data obtained from individuals residing in a fishing village in the Lake Victoria region, Uganda, Musoli. Data include human host age; baseline S. mansoni egg counts, 9-week post-treatment Kato Katz S. mansoni egg counts (eggs/gram feces); 2-year post-treatment Kato Katz S. mansoni egg counts (epg), and post-treatment IgE-TAL titers (ng/ul). Detailed descriptions of the study cohorts, data collection and analysis can be found in: Fitzsimmons et al. 2012 DOI:10.1128/IAI.00641-12 Individual level S. haematobium infection data from three villages in the Segou Region, Mali. Data include human host age, sex and residence in high or moderate transmission intensity villages; pre-treatment baseline CAA measurement; 9-week post-treatment urine filtration S. haematobium egg counts (eggs/10 ml urine); 2-year post-treatment infection status (presence/absence of S. haematobium eggs by urine filtration); post-treatment seroprevalence of measurable IgE responses to specified members of the Tegument Allergen Like protein family (compared to non-endemic control response, data also available); pre-treatment IgE and IgG4 seroprevalence to specific ShTAL proteins; pre- and post-treatment IgE-TAL titers (ng/ul). Detailed descriptions of the study cohorts, data collection and analysis can be found in: Wilson et al. 2014 DOI: 10.1093/infdis/jiu374This study was funded by Medical Research Council, UK (grant MR/M019780/1). RCO was funded by the Medical Research Council, UK Doctoral Training Partnership (grant MR/K50127X/1). The original field studies were supported by the Commission of the European Community’s Science and Technology for Development Programme (contract 517733 [MUSTSchistUKEMA])

The Unseen Hand:AI-Based Prescribing Decision Support Tools and the Evaluation of Drug Safety and Effectiveness

The use of artificial intelligence (AI)-based tools to guide prescribing decisions is full of promise and may enhance patient outcomes. These tools can perform actions such as choosing the ‘safest’ medication, choosing between competing medications, promoting de-prescribing or even predicting non-adherence. These tools can exist in a variety of formats; for example, they may be directly integrated into electronic medical records or they may exist in a stand-alone website accessible by a web browser. One potential impact of these tools is that they could manipulate our understanding of the benefit-risk of medicines in the real world. Currently, the benefit risk of approved medications is assessed according to carefully planned agreements covering spontaneous reporting systems and planned surveillance studies. But AI-based tools may limit or even block prescription to high-risk patients or prevent off-label use. The uptake and temporal availability of these tools may be uneven across healthcare systems and geographies, creating artefacts in data that are difficult to account for. It is also hard to estimate the ‘true impact’ that a tool had on a prescribing decision. International borders may also be highly porous to these tools, especially in cases where tools are available over the web. These tools already exist, and their use is likely to increase in the coming years. How they can be accounted for in benefit-risk decisions is yet to be seen.</p