Recent Submissions

  • A Prospective Analysis of Screen-Detected Cancers Recalled and Not Recalled by Artificial Intelligence.

    Smith, Samantha J; Bradley, Sally Anne; Walker-Stabeler, Katie; Siafakas, Michael; Smith, Samantha; Medical and Dental; Samantha J Smith, MHSc, Sally Anne Bradley, MB.ChB, Katie Walker-Stabeler, MSc, Michael Siafakas, MS, MD (Journal of Breast Imaging, 2024-05-27)
    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.
  • Role of Coriolis flow measurement technology in validation of model of syringe driver performance

    Clarkson, Douglas; Medical and Dental; D.M. Clarkson, M. Tshangini (Science Direct, 2024)
    The 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.
  • Socioeconomic and ethnic disparities associated with access to cochlear implantation for severe-to-profound hearing loss: A multicentre observational study of UK adults.

    Swords, Chloe; Ghedia, Reshma; Blanchford, Hannah; Arwyn-Jones, James; Heward, Elliot; Milinis, Kristijonas; Hardman, John; Smith, Matthew E; Bance, Manohar; Muzaffar, Jameel; et al. (PLOS Medicine, 2024-04-04)
    No Abstract
  • Estimation of infant radiation exposure from ingestion of breastmilk after SeHCAT capsule administration

    Rowley, Lisa; Medical and Dental; Comber, E.A., Adesanya, O., Gladstone, J., Coleclough, S., Rowley, L., (Lippincott, Williams & Wilkins, 2023-01-31)
    im: 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.
  • Development and validation of artificial intelligence-based prescreening of large-bowel biopsies taken in the UK and Portugal: a retrospective cohort study

    Ali, Mahmoud; Evans, Harriet; Whitney, Peter; Minhas, Fayyaz; Snead, David R J; Snead, David; Medical and Dental; Bilal M, Tsang YW, Ali M, Graham S, Hero E, Wahab N, Dodd K, Sahota H, Wu S, Lu W, Jahanifar M, Robinson A, Azam A, Benes K, Nimir M, Hewitt K, Bhalerao A, Eldaly H, Raza SEA, Gopalakrishnan K, Minhas F, Snead D, Rajpoot N. (Lancet Digit Health, 2022-09-27)
    No Abstract
  • Screening of normal endoscopic large bowel biopsies with interpretable graph learning: a retrospective study.

    Graham, Simon; Minhas, Fayyaz; Bilal, Mohsin; Ali, Mahmoud; Tsang, Yee Wah; Eastwood, Mark; Wahab, Noorul; Jahanifar, Mostafa; Hero, Emily; Dodd, Katherine; et al. (Gut, 2023-05-12)
    No Abstract
  • Development and validation of artificial intelligence-based prescreening of large-bowel biopsies taken in the UK and Portugal: a retrospective cohort study

    Atallah, Nehal M; Wahab, Noorul; Toss, Michael S; Makhlouf, Shorouk; Ibrahim, Asmaa Y; Lashen, Ayat G; Ghannam, Suzan; Mongan, Nigel P; Jahanifar, Mostafa; Graham, Simon; et al. (Lancet Digit Health, 2023-06-27)
    No Abstract
  • Standardized Clinical Annotation of Digital Histopathology Slides at the Point of Diagnosis.

    Evans, Harriet; Hero, Emily; Minhas, Fayyaz; Wahab, Noorul; Dodd, Katherine; Sahota, Harvir; Ganguly, Ratnadeep; Robinson, Andrew; Neerudu, Manjuvani; Blessing, Elaine; et al. (Mod Pathol, 2023-08-04)
    No Abstract
  • Development and validation of artificial intelligence-based prescreening of large-bowel biopsies taken in the UK and Portugal: a retrospective cohort study

    Snead, David; Medical and Dental; Bilal M, Tsang YW, Ali M, Graham S, Hero E, Wahab N, Dodd K, Sahota H, Wu S, Lu W, Jahanifar M, Robinson A, Azam A, Benes K, Nimir M, Hewitt K, Bhalerao A, Eldaly H, Raza SEA, Gopalakrishnan K, Minhas F, Snead D, Rajpoot N. (Lancet Digit Health, 2023-10-27)
    No Abstract
  • AI-enabled routine H&E image based prognostic marker for early-stage luminal breast cancer.

    Wahab, Noorul; Toss, Michael; Miligy, Islam M; Jahanifar, Mostafa; Atallah, Nehal M; Lu, Wenqi; Graham, Simon; Bilal, Mohsin; Bhalerao, Abhir; Lashen, Ayat G; et al. (NPJ Precis Oncol, 2023-11-15)
    No Abstract
  • Artificial Intelligence-Based Mitosis Scoring in Breast Cancer: Clinical Application.

    Ibrahim, Asmaa; Jahanifar, Mostafa; Wahab, Noorul; Toss, Michael S; Makhlouf, Shorouk; Atallah, Nehal; Lashen, Ayat G; Katayama, Ayaka; Graham, Simon; Bilal, Mohsin; et al. (Mod Pathol, 2023-12-27)
    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?

    Evans, Harriet; Snead, David; Snead, David; Medical and Dental; Evans H, Snead D. (Med Image Anal, 2023-11-03)
    No Abstarct
  • CoNIC Challenge: Pushing the frontiers of nuclear detection, segmentation, classification and counting.

    Graham, Simon; Vu, Quoc Dang; Jahanifar, Mostafa; Weigert, Martin; Schmidt, Uwe; Zhang, Wenhua; Zhang, Jun; Yang, Sen; Xiang, Jinxi; Wang, Xiyue; et al. (Med Image Anal, 2023-12-13)
    No Abstract
  • CD, or not CD, that is the question: a digital interobserver agreement study in coeliac disease.

    Denholm, James; Schreiber, Benjamin A; Jaeckle, Florian; Wicks, Mike N; Benbow, Emyr W; Bracey, Tim S; Chan, James Y H; Farkas, Lorant; Fryer, Eve; Gopalakrishnan, Kishore; et al. (BMJ Publishing Group Ltd, 2024-02-01)
    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 Dentistry

    Clarkson, Douglas; Medical and Dental; Clarkson DM (Dent Update, 2024-02)
    No Abstract
  • Healthcare professionals' perspectives of the management of people with palliative care needs in the emergency department of a UK hospital.

    Arif, Azra; Sausman, Jane; Young, Annie; Burt, Rebecca; Jane Sausman, Azra Arif, Annie Young, John MacArtney, Cara Bailey, Jaimini Rajani & Rebecca Burt (BMC, 2023-09-06)
    The 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 study

    Snead, David; Snead, David; Medical and Dental; David Snead (Wiley, 2023-11-13)
    HISTOP-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 study

    English, Sarah; Steele, Amber; Williams, Alison; Blacklay, Jayne; Sorinola, Olanrewaju; Wernisch, Lorenz; Grammatopoulos, Dimitris K.; Williams, Alison; Blacklay, Jayne; Sorinola, Olanrewaju; et al. (Nature Research, 2018-08)
    Perinatal 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.
  • Designing economic evaluations alongside clinical trials in maternal health care: A guide for clinical trial design

    Snead, David; Medical and Dental; Harriet Evans 1 2, David Snead 1 2 Affiliations 1Histopathology Department, University Hospitals Coventry and Warwickshire NHS Trust, Coventry, UK. 2Warwick Medical School, University of Warwick, Coventry, UK. (University Hospitals Coventry and Warwickshire NHS Trust, 2023-11-03)
    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.
  • Facial twitching: calcium or concussion conundrum? Hypocalcaemia in a young American football player masking an internal carotid artery dissection

    Muthalagappan, Seethalakshmi; Robbins, Timothy; Mehta, Hiten; Murthy, Narasimha; Muthalagappan, Seethalakshmi; Robbins, Timothy; Murthy, Narasimha; Mehta, Hiten; Diabetes and Endocrinology; Medical and Dental; et al. (BMJ Publishing Group, 2020-04)
    A 30-year-old male American football player presented to the acute medical unit with left-hand and hemifacial spasms. History and examination revealed hemifacial spasms in keeping with seizure-like activity possibly due to symptomatic hypocalcaemia. Subsequent investigations revealed an adjusted calcium of 1.87 mmol/L and, hence, he was managed with intravenous calcium replacement. He presented two further times in a 1-month period, with subjective limb weakness, despite normal adjusted calcium. During his third admission, he developed slurred speech and a marked facial droop, with absence of power in the right upper limb. Imaging revealed acute and old infarctions in the left middle cerebral artery territory and appearances consistent with left internal carotid artery dissection. This presentation of arterial stroke is atypical but with potentially grave consequences if missed. There is limited literature on the presentation of hemifacial spasm, and its association with ischaemic or haemorrhagic stroke represents a key learning point. Keywords: calcium and bone; stroke.

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