Since the emergence of Coronavirus Disease 2019 (COVID-19), researchers in machine learning and radiology have rushed to develop algorithms that could assist with diagnosis, triage and management of the disease (1). As a result, thousands of diagnostic and prognostic models using chest radiographs and computed tomography (CT) have been developed. However, with no standardised approach to development or evaluation, it is difficult, even for experts, to determine which models may be of most clinical benefit. In this work, we share our main concerns and present some possible solutions. ; NIHR Cambridge Biomedical Research Centre; the EPSRC; the BHF; CRUK National Cancer Imaging Translational Accelerator (NCITA) [C22479/A28667]; Intel Corporation; the DRAGON consortium, which received funding from the Innovative Medicines Initiative 2 Joint Undertaking (JU) under grant agreement No 101005122, and the Cambridge Mathematics of Information in Healthcare (CMIH) Hub EP/T017961/1. The Philip Leverhulme Prize, the Royal Society Wolfson Fellowship, the EPSRC grants EP/S026045/1 and EP/T003553/1, EP/N014588/1, the Wellcome Innovator Award RG98755, European Union Horizon 2020 research and innovation programme under the Marie Skodowska- Curie grant agreement No. 777826 NoMADS, the Cantab Capital Institute for the Mathematics of Information and the Alan Turing Institute.
The prevalence of the coronavirus SARS-CoV-2 disease has resulted in the unprecedented collection of health data to support research. Historically, coordinating the collation of such datasets on a national scale has been challenging to execute for several reasons, including issues with data privacy, the lack of data reporting standards, interoperable technologies, and distribution methods. The coronavirus SARS-CoV-2 disease pandemic has highlighted the importance of collaboration between government bodies, healthcare institutions, academic researchers and commercial companies in overcoming these issues during times of urgency. The National COVID-19 Chest Imaging Database, led by NHSX, British Society of Thoracic Imaging, Royal Surrey NHS Foundation Trust and Faculty, is an example of such a national initiative. Here, we summarise the experiences and challenges of setting up the National COVID-19 Chest Imaging Database, and the implications for future ambitions of national data curation in medical imaging to advance the safe adoption of artificial intelligence in healthcare.
BACKGROUND: Activated phosphoinositide 3-kinase δ syndrome (APDS) is a recently described combined immunodeficiency resulting from gain-of-function mutations in PIK3CD, the gene encoding the catalytic subunit of phosphoinositide 3-kinase δ (PI3Kδ). OBJECTIVE: We sought to review the clinical, immunologic, histopathologic, and radiologic features of APDS in a large genetically defined international cohort. METHODS: We applied a clinical questionnaire and performed review of medical notes, radiology, histopathology, and laboratory investigations of 53 patients with APDS. RESULTS: Recurrent sinopulmonary infections (98%) and nonneoplastic lymphoproliferation (75%) were common, often from childhood. Other significant complications included herpesvirus infections (49%), autoinflammatory disease (34%), and lymphoma (13%). Unexpectedly, neurodevelopmental delay occurred in 19% of the cohort, suggesting a role for PI3Kδ in the central nervous system; consistent with this, PI3Kδ is broadly expressed in the developing murine central nervous system. Thoracic imaging revealed high rates of mosaic attenuation (90%) and bronchiectasis (60%). Increased IgM levels (78%), IgG deficiency (43%), and CD4 lymphopenia (84%) were significant immunologic features. No immunologic marker reliably predicted clinical severity, which ranged from asymptomatic to death in early childhood. The majority of patients received immunoglobulin replacement and antibiotic prophylaxis, and 5 patients underwent hematopoietic stem cell transplantation. Five patients died from complications of APDS. CONCLUSION: APDS is a combined immunodeficiency with multiple clinical manifestations, many with incomplete penetrance and others with variable expressivity. The severity of complications in some patients supports consideration of hematopoietic stem cell transplantation for severe childhood disease. Clinical trials of selective PI3Kδ inhibitors offer new prospects for APDS treatment. ; T.C. is supported by National Children's Research Centre, Our Lady's Children's Hospital Crumlin, Dublin, Ireland. A.C. has a Wellcome Trust Postdoctoral Training Fellowship for Clinicians (103413/Z/13/Z). K.O. is supported by funding from BBSRC, MRC, Wellcome Trust and GSK. R.D. and D.S.K are funded by National Institute for Health Research (NIHR) Cambridge Biomedical Research Centre, Cambridge, UK. C.S. and S.E. are supported by the German Federal Ministry of Education and Research (BMBF 01 EO 0803 grant to the Center of Chronic immunodeficiency and BMBF 01GM1111B grant to the PID-NET initiative). S.N.F is supported in part by the Southampton UK National Institute for Health Research (NIHR) Wellcome Trust Clinical Research Facility and NIHR Respiratory Biomedical Research Unit. M.A.A.I. is funded by NHS Innovation London and King's College Hospital Charitable Trust. A.F., S.L., A.D., F.R-L and S.K. are supported by the European Union's 7th RTD Framework Programme (ERC advanced grant PID-IMMUNE contract 249816) and a government grant managed by the French Agence Nationale de la Recherche as part of the "Investments for the Future" program (ANR-10-IAHU-01). S.L. is supported by the Agence Nationale de la Recherche (ANR) (ANR-14-CE14-0028-01), the Foundation ARC pour la Recherche sur le Cancer (France), the Rare Diseases Foundation (France) and François Aupetit Association (France). S.L. is a senior scientist and S.K is a researcher at the Centre National de la Recherche Scientifique-CNRS (France). A.D. and S.K. are supported by the "Institut National de la Santé et de la Recherche Médicale". S.K. also supported by the Fondation pour la Recherche Médicale (grant number: ING20130526624), la Ligue Contre le Cancer (Comité de Paris) and the Centre de Référence Déficits Immunitaires Héréditaires (CEREDIH). S.O.B is supported by the Higher Education Funding Council for England. B.V. is supported by the UK Biotechnology and Biological Sciences Research Council [BB/I007806/1], Cancer Research UK [C23338/A15965) and the National Institute for Health Research (NIHR) University College London Hospitals Biomedical Research Centre. B.V. is consultant to Karus Therapeutics (Oxford, UK). S.N. is a Wellcome Trust Senior Research Fellow in Basic Biomedical Science (095198/Z/10/Z). S.N. is also supported by the European Research Council Starting grant 260477, the EU FP7 collaborative grant 261441 (PEVNET project) and the National Institute for Health Research (NIHR) Cambridge Biomedical Research Centre, UK. A.M.C. is funded by the Medical Research Council, British Lung Foundation, University of Sheffield and Cambridge NIHR-BRC. Research in A.M.C. laboratory has received non-commercial grant support from GSK, Novartis, and MedImmune. ; This is the author accepted manuscript. The final version is available from Elsevier via http://dx.doi.org/10.1016/j.jaci.2016.06.021
