Computer-aided diagnosis for World Health Organization-defined chest radiograph primary-endpoint pneumonia in children.

Background: The chest radiograph is the most common imaging modality to assess childhood pneumonia. It has been used in epidemiological and vaccine efficacy/effectiveness studies on childhood pneumonia.Objective: To develop computer-aided diagnosis (CAD4Kids) for chest radiography in children and to...

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Published in:Pediatric Radiology Vol. 50; no. 4; pp. 482 - 492
Main Authors: Mahomed, Nasreen, van Ginneken, Bram, Philipsen, Rick H. H. M., Melendez, Jaime, Moore, David P., Moodley, Halvani, Sewchuran, Tanusha, Mathew, Denny, Madhi, Shabir A.
Format: research Journal Article
Published: Springer Nature Apr2020
Online Access:View this record in EBSCOhost
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      pub: Springer Nature
      place: New York, New York
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        atl: Computer-aided diagnosis for World Health Organization-defined chest radiograph primary-endpoint pneumonia in children.
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          Mahomed, Nasreen
          van Ginneken, Bram
          Philipsen, Rick H. H. M.
          Melendez, Jaime
          Moore, David P.
          Moodley, Halvani
          Sewchuran, Tanusha
          Mathew, Denny
          Madhi, Shabir A.
        affil: Department of Radiology, Faculty of Health Sciences, University of Witwatersrand, 2000, Johannesburg, South Africa
      sug:
        subj:
          Pneumonia
          World Health Organization
          Diagnosis, Computer Assisted Methods
          Radiography, Thoracic Methods
          Infant
          Child, Preschool
          Child
          Male
          Infant, Newborn
          Adolescence
          Female
          Funding Source
          Infant: 1-23 months
          Child, Preschool: 2-5 years
          Child: 6-12 years
          Infant, Newborn: birth-1 month
          Adolescent: 13-18 years
          Male
          Female
      ab: Background: The chest radiograph is the most common imaging modality to assess childhood pneumonia. It has been used in epidemiological and vaccine efficacy/effectiveness studies on childhood pneumonia.Objective: To develop computer-aided diagnosis (CAD4Kids) for chest radiography in children and to evaluate its accuracy in identifying World Health Organization (WHO)-defined chest radiograph primary-endpoint pneumonia compared to a consensus interpretation.Materials and Methods: Chest radiographs were independently evaluated by three radiologists based on WHO criteria. Automatic lung field segmentation was followed by manual inspection and correction, training, feature extraction and classification. Radiographs were filtered with Gaussian derivatives on multiple scales, extracting texture features to classify each pixel in the lung region. To obtain an image score, the 95th percentile score of the pixels was used. Training and testing were done in 10-fold cross validation.Results: The radiologist majority consensus reading of 858 interpretable chest radiographs included 333 (39%) categorised as primary-endpoint pneumonia, 208 (24%) as other infiltrate only and 317 (37%) as no primary-endpoint pneumonia or other infiltrate. Compared to the reference radiologist consensus reading, CAD4Kids had an area under the receiver operator characteristic (ROC) curve of 0.850 (95% confidence interval [CI] 0.823-0.876), with a sensitivity of 76% and specificity of 80% for identifying primary-endpoint pneumonia on chest radiograph. Furthermore, the ROC curve was 0.810 (95% CI 0.772-0.846) for CAD4Kids identifying primary-endpoint pneumonia compared to other infiltrate only.Conclusion: Further development of the CAD4Kids software and validation in multicentre studies are important for future research on computer-aided diagnosis and artificial intelligence in paediatric radiology.
      pubtype: Academic Journal
      doctype:
        research
        Journal Article
      ougenre: Article
    language: English
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