{
  "abstract": "Introduction Diagnosing pulmonary tuberculosis (PTB) in children is challenging owing to paucibacillary disease, non-specific symptoms and signs and challenges in microbiological confirmation. Chest X-ray (CXR) interpretation is fundamental for diagnosis and classifying disease as severe or non-severe. In adults with PTB, there is substantial evidence showing the usefulness of artificial intelligence (AI) in CXR interpretation, but very limited data exist in children.Methods and analysis A prospective two-stage study of children with presumed PTB in three sites (one in South Africa and two in Pakistan) will be conducted. In stage I, eligible children will be enrolled and comprehensively investigated for PTB. A CXR radiological reference standard (RRS) will be established by an expert panel of blinded radiologists. CXRs will be classified into those with findings consistent with PTB or not based on RRS. Cases will be classified as confirmed, unconfirmed or unlikely PTB according to National Institutes of Health definitions. Data from 300 confirmed and unconfirmed PTB cases and 250 unlikely PTB cases will be collected. An AI-CXR algorithm (qXR) will be used to process CXRs. The primary endpoint will be sensitivity and specificity of AI to detect confirmed and unconfirmed PTB cases (composite reference standard); a secondary endpoint will be evaluated for confirmed PTB cases (microbiological reference standard). In stage II, a multi-reader multi-case study using a cross-over design will be conducted with 16 readers and 350 CXRs to assess the usefulness of AI-assisted CXR interpretation for readers (clinicians and radiologists). The primary endpoint will be the difference in the area under the receiver operating characteristic curve of readers with and without AI assistance in correctly classifying CXRs as per RRS.Ethics and dissemination The study has been approved by a local institutional ethics committee at each site. Results will be published in academic journals and presented at conferences. Data will be made available as an open-source database.Study registration number PACTR202502517486411",
  "authors": [
    {
      "affiliations": [
        "Centre for International Health, Department of Global Public Health and Primary Care, University of Bergen, Bergen, Norway"
      ],
      "name": "Brekhna Aurangzeb"
    },
    {
      "affiliations": [
        "Clinical Research, Qure.ai Technologies Private Limited, Bangalore, India"
      ],
      "name": "Dennis Robert"
    },
    {
      "affiliations": [
        "Department of Paediatrics and Child Health, University of Cape Town, Cape Town, South Africa",
        "South African Medical Research Council (SA-MRC) Unit on Child and Adolescent Health, University of Cape Town, Cape Town, South Africa"
      ],
      "name": "Cynthia Baard"
    },
    {
      "affiliations": [
        "Department of Radiology, University of Child Health Sciences, Children’s Hospital Lahore, Lahore, Pakistan"
      ],
      "name": "Abid Ali Qureshi"
    },
    {
      "affiliations": [
        "Department of Paediatric Medicine, Gulab Devi Teaching Hospital, Lahore, Pakistan"
      ],
      "name": "Aneela Shaheen"
    },
    {
      "affiliations": [
        "Department of Microbiology, Gulab Devi Teaching Hospital, Lahore, Pakistan"
      ],
      "name": "Atiqa Ambreen"
    },
    {
      "affiliations": [
        "Department of Paediatrics and Child Health, University of Cape Town, Cape Town, South Africa",
        "South African Medical Research Council (SA-MRC) Unit on Child and Adolescent Health, University of Cape Town, Cape Town, South Africa"
      ],
      "name": "David McFarlane"
    },
    {
      "affiliations": [
        "Department of Microbiology, University of Child Health Sciences, Children’s Hospital Lahore, Lahore, Pakistan"
      ],
      "name": "Humera Javed"
    },
    {
      "affiliations": [
        "Department of Pulmonology, Children’s Hospital Lahore, Lahore, Pakistan"
      ],
      "name": "Iqbal Bano"
    },
    {
      "affiliations": [
        "Product, Qure.ai Technologies Private Limited, New York City, New York, USA"
      ],
      "name": "Justy Antony Chiramal"
    },
    {
      "affiliations": [
        "Department of Paediatrics and Child Health, University of Cape Town, Cape Town, South Africa",
        "South African Medical Research Council (SA-MRC) Unit on Child and Adolescent Health, University of Cape Town, Cape Town, South Africa"
      ],
      "name": "Lesley Workman"
    },
    {
      "affiliations": [
        "Department of Paediatrics and Child Health, University of Cape Town, Cape Town, South Africa",
        "South African Medical Research Council (SA-MRC) Unit on Child and Adolescent Health, University of Cape Town, Cape Town, South Africa"
      ],
      "name": "Tanyia Pillay"
    },
    {
      "affiliations": [
        "Department of Paediatrics and Child Health, University of Cape Town, Cape Town, South Africa",
        "South African Medical Research Council (SA-MRC) Unit on Child and Adolescent Health, University of Cape Town, Cape Town, South Africa"
      ],
      "name": "Zoe Franckling-Smith"
    },
    {
      "affiliations": [
        "Centre for International Health, Department of Global Public Health and Primary Care, University of Bergen, Bergen, Norway",
        "Department of Thoracic Medicine, Haukeland University Hospital, Bergen, Norway"
      ],
      "name": "Tehmina Mustafa"
    },
    {
      "affiliations": [
        "Department of Radiology, The Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, USA",
        "Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA"
      ],
      "name": "Savvas Andronikou"
    },
    {
      "affiliations": [
        "Department of Paediatrics and Child Health, University of Cape Town, Cape Town, South Africa",
        "South African Medical Research Council (SA-MRC) Unit on Child and Adolescent Health, University of Cape Town, Cape Town, South Africa"
      ],
      "name": "Heather J Zar"
    }
  ],
  "title": "Evaluating the accuracy of artificial intelligence-powered chest X-ray diagnosis for paediatric pulmonary tuberculosis (EVAL-PAEDTBAID): Study protocol for a multi-centre diagnostic accuracy study",
  "uid": "f0b94be6-743b-56a6-8fbb-7d5dd1735960"
}