Clinical Diagnostic Services: Recent submissions
Now showing items 1-20 of 31
-
Changes in body composition and average daily energy expenditure of men and women during arduous extended polar travel.Weight and skin-fold measurements were made at five-day intervals during a 47-day expedition by six men and three women from the edge of the sea ice to the South Pole. From these, together with detailed manual records of the nutrition for individual participants, the average daily energy expenditure was determined before and after a resupply at approximately mid-point of the expedition. For all participants body weight fell during the expedition with the overall loss being much smaller for the three female participants (-4.0, -4.0, -4.4kg) than for the male participants, (mean±sd) -8.6±2.0kg. Fat weight fell approximately linearly during the expedition with a total loss of (-4.1, -6.5 and -2.5kg) for the three female participants and -6.8±1.7kg for the male participants. Individual fat-free weight changed by a smaller amount overall: (0.13, 2.5 and -1.8kg) for the three female participants; -1.8±2.0kg for the male participants who, with one exception, lost fat-free tissue All participants showed a substantial variation in fat-free tissue weight during the expedition. Analysis of the daily energy expenditure showed adequate nutrition but the intake fell for the second part of the expedition although the reasons for this are unclear, but adaptation to the cold, altitude and workload are possible explanations. The validity of this time-averaged measurement for individual participants was determined from analysing moments about the mean of timeseries actigraphy data from wrist worn devices. The mean and autocorrelation function of the actigraphy data across subjects were analysed to determine whether measures could be compared between participants. The first, second and third moment about the mean of the day-to-day activity was found to be time-invariant for individual subjects (χ2, p>0.05) and the normalized mean and autocorrelation measured over a day for each participant
-
Birds of a feather : an uncommon cause of pneumonia and meningoencephalitisA 61-year-old man was admitted with a 1-week history of influenza-like symptoms during a period of increased influenza virus activity. He soon developed type 2 respiratory failure and became increasingly drowsy. He later suffered a convulsive episode in the intensive care unit (ICU) which self-terminated. Initial clinical findings suggested community-acquired pneumonia and meningoencephalitis. However, a detailed history revealed that he was a pet bird-keeper, which raised a suspicion of ornithosis. Chlamydia psittaci DNA was detected in sputum by PCR. He was started on appropriate antibiotics and made a full recovery. We present this uncommon cause of pneumonia as an example of the importance of accurate history-taking to ensure a correct diagnosis for optimal management.
-
A Prospective Analysis of Screen-Detected Cancers Recalled and Not Recalled by Artificial Intelligence.Objective: The use of artificial intelligence has potential in assisting many aspects of imaging interpretation. We undertook a prospective service evaluation from March to October 2022 of Mammography Intelligent Assessment (MIA) operating "silently" within our Breast Screening Service, with a view to establishing its performance in the local population and setting. This evaluation addressed the performance of standalone MIA vs conventional double human reading of mammograms. Methods: MIA analyzed 8779 screening events over an 8-month period. The MIA outcome did not influence the decisions made on the clinical pathway. Cases were reviewed approximately 6 weeks after the screen reading decision when human reading and/or MIA indicated a recall. Results: There were 146 women with positive concordance between human reading and MIA (human reader and MIA recalled) in whom 58 breast cancers were detected. There were 270 women with negative discordance (MIA no recall, human reader recall) for whom 19 breast cancers and 1 breast lymphoma were detected, with 1 cancer being an incidental finding at assessment. Six hundred and four women had positive discordance (MIA recall, human reader no recall) in whom 2 breast cancers were detected at review. The breast cancers demonstrated a wide spectrum of mammographic features, sites, sizes, and pathologies, with no statistically significant difference in features between the negative discordant and positive concordant cases. Conclusion: Of 79 breast cancers identified by human readers, 18 were not identified by MIA, and these had no specific features or site to suggest a systematic error for MIA analysis of 2D screening mammograms. Keywords: National Health Service Breast Screening Programme; artificial intelligence; breast cancer screening; digital mammography; double reading
-
Solitary pulmonary hyalinising granuloma : a rare cause of pulmonary noduleA pulmonary nodule is a common incidental finding on chest imaging, which includes a wide variety of differential diagnosis. Pulmonary hyalinising granuloma is a rare disease aetiology of pulmonary nodule(s). We report a 74-year-old female who was referred to the respiratory clinic with incidental finding of a solitary pulmonary nodule on chest X-ray. CT confirmed the presence of a 1.2 cm solitary pulmonary nodule in the left upper lobe with no lymphadenopathy. The patient underwent wedge resection, and histopathological examination of the lesion confirmed pulmonary hyalinising granuloma. In most previously reported cases, patients had multiple lesions on chest radiography. Solitary pulmonary lesion is an uncommon presentation of this clinical entity and only a few cases have been reported in the literature.
-
Role of Coriolis flow measurement technology in validation of model of syringe driver performanceThe development of a flow/pressure measurement system in association with Bronkhorst High-Tech B.V. incorporating a Coriolis flow transducer, provided an opportunity to observe the flow/pressure dynamics of syringe drivers. A model of flow/pressure performance of syringe drivers was established where key variable factors included the compliance of the connected system and the associated line resistance. It was identified that the flow/pressure dynamics observed with the flow measurement system incorporating the Coriolis transducer matched that of the model. In this consideration the dominant compliance contribution related to that of the syringe. The model operates by considering the notional volume change in the residual fluid volume in the syringe with inflow from stepper motor action and outflow in the interval between sequential pulses. While many of the observations in the literature of syringe driver function are qualitative, the model allows a more precise prediction of associated device performance.
-
Estimation of infant radiation exposure from ingestion of breastmilk after SeHCAT capsule administrationim: Assessment of the imaging properties of 3D-printable materials using dual energy computed tomography (DECT) to match clinical values for imaging phantoms. Methods: 3D-printed samples were imaged using DECT. Regions of interest were analyzed to assess spectral computed tomography (CT) numbers at various energies and measure the electron density (ρe) and effective atomic number (Zeff). Results: Electron density was proportional to the CT number for the materials assessed with Zeff between 6.43 and 7.01. The measured CT number increased with monochromatic energy for all but one sample. Conclusion: A single DECT scan provides valuable information regarding the properties of 3D-printable material due to the ease of measurement of ρe and Zeff. The majority of 3D-printed materials analyzed behaved like adipose tissue across a range of energies in CT imaging.
-
Artificial Intelligence-Based Mitosis Scoring in Breast Cancer: Clinical Application.In recent years, artificial intelligence (AI) has demonstrated exceptional performance in mitosis identification and quantification. However, the implementation of AI in clinical practice needs to be evaluated against the existing methods. This study is aimed at assessing the optimal method of using AI-based mitotic figure scoring in breast cancer (BC). We utilized whole slide images from a large cohort of BC with extended follow-up comprising a discovery (n = 1715) and a validation (n = 859) set (Nottingham cohort). The Cancer Genome Atlas of breast invasive carcinoma (TCGA-BRCA) cohort (n = 757) was used as an external test set. Employing automated mitosis detection, the mitotic count was assessed using 3 different methods, the mitotic count per tumor area (MCT; calculated by dividing the number of mitotic figures by the total tumor area), the mitotic index (MI; defined as the average number of mitotic figures per 1000 malignant cells), and the mitotic activity index (MAI; defined as the number of mitotic figures in 3 mm2 area within the mitotic hotspot). These automated metrics were evaluated and compared based on their correlation with the well-established visual scoring method of the Nottingham grading system and Ki67 score, clinicopathologic parameters, and patient outcomes. AI-based mitotic scores derived from the 3 methods (MCT, MI, and MAI) were significantly correlated with the clinicopathologic characteristics and patient survival (P < .001). However, the mitotic counts and the derived cutoffs varied significantly between the 3 methods. Only MAI and MCT were positively correlated with the gold standard visual scoring method used in Nottingham grading system (r = 0.8 and r = 0.7, respectively) and Ki67 scores (r = 0.69 and r = 0.55, respectively), and MAI was the only independent predictor of survival (P < .05) in multivariate Cox regression analysis. For clinical applications, the optimum method of scoring mitosis using AI needs to be considered. MAI can provide reliable and reproducible results and can accurately quantify mitotic figures in BC.
-
Why do errors arise in artificial intelligence diagnostic tools in histopathology and how can we minimize them?Artificial intelligence (AI)-based diagnostic tools can offer numerous benefits to the field of histopathology, including improved diagnostic accuracy, efficiency and productivity. As a result, such tools are likely to have an increasing role in routine practice. However, all AI tools are prone to errors, and these AI-associated errors have been identified as a major risk in the introduction of AI into healthcare. The errors made by AI tools are different, in terms of both cause and nature, to the errors made by human pathologists. As highlighted by the National Institute for Health and Care Excellence, it is imperative that practising pathologists understand the potential limitations of AI tools, including the errors made. Pathologists are in a unique position to be gatekeepers of AI tool use, maximizing patient benefit while minimizing harm. Furthermore, their pathological knowledge is essential to understanding when, and why, errors have occurred and so to developing safer future algorithms. This paper summarises the literature on errors made by AI diagnostic tools in histopathology. These include erroneous errors, data concerns (data bias, hidden stratification, data imbalances, distributional shift, and lack of generalisability), reinforcement of outdated practices, unsafe failure mode, automation bias, and insensitivity to impact. Methods to reduce errors in both tool design and clinical use are discussed, and the practical roles for pathologists in error minimisation are highlighted. This aims to inform and empower pathologists to move safely through this seismic change in practice and help ensure that novel AI tools are adopted safely.
-
CD, or not CD, that is the question: a digital interobserver agreement study in coeliac disease.Objective: Coeliac disease (CD) diagnosis generally depends on histological examination of duodenal biopsies. We present the first study analysing the concordance in examination of duodenal biopsies using digitised whole-slide images (WSIs). We further investigate whether the inclusion of immunoglobulin A tissue transglutaminase (IgA tTG) and haemoglobin (Hb) data improves the interobserver agreement of diagnosis. Design: We undertook a large study of the concordance in histological examination of duodenal biopsies using digitised WSIs in an entirely virtual reporting setting. Our study was organised in two phases: in phase 1, 13 pathologists independently classified 100 duodenal biopsies (40 normal; 40 CD; 20 indeterminate enteropathy) in the absence of any clinical or laboratory data. In phase 2, the same pathologists examined the (re-anonymised) WSIs with the inclusion of IgA tTG and Hb data. Results: We found the mean probability of two observers agreeing in the absence of additional data to be 0.73 (±0.08) with a corresponding Cohen's kappa of 0.59 (±0.11). We further showed that the inclusion of additional data increased the concordance to 0.80 (±0.06) with a Cohen's kappa coefficient of 0.67 (±0.09). Conclusion: We showed that the addition of serological data significantly improves the quality of CD diagnosis. However, the limited interobserver agreement in CD diagnosis using digitised WSIs, even after the inclusion of IgA tTG and Hb data, indicates the importance of interpreting duodenal biopsy in the appropriate clinical context. It further highlights the unmet need for an objective means of reproducible duodenal biopsy diagnosis, such as the automated analysis of WSIs using artificial intelligence.
-
The Role of Far-UVC in DentistryNo Abstract
-
Healthcare professionals' perspectives of the management of people with palliative care needs in the emergency department of a UK hospitalThe Emergency Department (ED) is not always the optimal place for people with palliative care needs but is the most common route for treatment when urgent care is sought. The aim of this study,’’REasons for PalLIative Care Admissions (REPLICA)’ was to explore the perspectives of ED healthcare professionals of hospital admission or discharge via ED for palliative care patients.
-
Digital pathology reporting for histopathology samples definitive evidence from a multi-site studyHISTOP-07-23-0452.R2 - Digital pathology for reporting histopathology samples, including cancer screening samples – definitive evidence from a multi-site study
-
Modelling of psychosocial and lifestyle predictors of peripartum depressive symptoms associated with distinct risk trajectories : a prospective cohort studyPerinatal depression involves interplay between individual chronic and acute disease burdens, biological and psychosocial environmental and behavioural factors. Here we explored the predictive potential of specific psycho-socio-demographic characteristics for antenatal and postpartum depression symptoms and contribution to severity scores on the Edinburgh Postnatal Depression Scale (EPDS) screening tool. We determined depression risk trajectories in 480 women that prospectively completed the EPDS during pregnancy (TP1) and postpartum (TP2). Multinomial logistic and penalised linear regression investigated covariates associated with increased antenatal and postpartum EPDS scores contributing to the average or the difference of paired scores across time points. History of anxiety was identified as the strongest contribution to antenatal EPDS scores followed by the social status, whereas a history of depression, postpartum depression (PPD) and family history of PPD exhibited the strongest association with postpartum EPDS. These covariates were the strongest differentiating factors that increased the spread between antenatal and postpartum EPDS scores. Available covariates appeared better suited to predict EPDS scores antenatally than postpartum. As women move from the antenatal to the postpartum period, socio-demographic and lifestyle risk factors appear to play a smaller role in risk, and a personal and family history of depression and PPD become increasingly important.