Evidence map›Paper›PMID 37192175›Full record

ArticlePLOS global public health2023

Optimising computer aided detection to identify intra-thoracic tuberculosis on chest x-ray in South African children.

Megan Palmer, James A Seddon, Marieke M van der Zalm, Anneke C Hesseling, Pierre Goussard, H Simon Schaaf, Julie Morrison, Bram van Ginneken, Jaime Melendez, Elisabetta Walters and 1 more

Abstract read
In one paragraph

Article in PLOS global public health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

20 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Review
  7. Article
  8. Article
  9. Article
  10. Article
  11. Review
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Review
  18. Article
  19. Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Megan PalmerFaculty of Medicine and Health Sciences, Department of Paediatrics and Child Health, Demond Tutu TB Centre, Stellenbosch University, Cape Town, South Africa.ORCID https://orcid.org/0000-0002-2534-2483
James A SeddonFaculty of Medicine and Health Sciences, Department of Paediatrics and Child Health, Demond Tutu TB Centre, Stellenbosch University, Cape Town, South Africa.
Marieke M van der ZalmFaculty of Medicine and Health Sciences, Department of Paediatrics and Child Health, Demond Tutu TB Centre, Stellenbosch University, Cape Town, South Africa.ORCID https://orcid.org/0000-0002-8787-9139
Anneke C HesselingFaculty of Medicine and Health Sciences, Department of Paediatrics and Child Health, Demond Tutu TB Centre, Stellenbosch University, Cape Town, South Africa.
Pierre GoussardFaculty of Medicine and Health Sciences, Department of Paediatrics and Child Health, Stellenbosch University, Stellenbosch, South Africa.
H Simon SchaafFaculty of Medicine and Health Sciences, Department of Paediatrics and Child Health, Demond Tutu TB Centre, Stellenbosch University, Cape Town, South Africa.
Julie MorrisonFaculty of Medicine and Health Sciences, Department of Paediatrics and Child Health, Stellenbosch University, Stellenbosch, South Africa.
Bram van GinnekenRadboud University Medical Center, Nijmegen, The Netherlands.ORCID https://orcid.org/0000-0003-2028-8972
Jaime MelendezRadboud University Medical Center, Nijmegen, The Netherlands.
Elisabetta WaltersFaculty of Medicine and Health Sciences, Department of Paediatrics and Child Health, Demond Tutu TB Centre, Stellenbosch University, Cape Town, South Africa.ORCID https://orcid.org/0000-0003-0546-2995
Keelin MurphyRadboud University Medical Center, Nijmegen, The Netherlands.ORCID https://orcid.org/0000-0001-6831-4020

Funding

The long-term consequences of pulmonary tuberculosis and respiratory viruses on lung health in young South African childrenK43TW011028 · FIC · STELLENBOSCH UNIVERSITY · PI VAN DER ZALM, MARIEKE MARGREET · 2020 to 2024
$647k
FIC NIH HHS K43 TW011028Medical Research Council MR/R007942/1
6 · The paper itself

Abstract

Diagnostic tools for paediatric tuberculosis remain limited, with heavy reliance on clinical algorithms which include chest x-ray. Computer aided detection (CAD) for tuberculosis on chest x-ray has shown promise in adults. We aimed to measure and optimise the performance of an adult CAD system, CAD4TB, to identify tuberculosis on chest x-rays from children with presumptive tuberculosis. Chest x-rays from 620 children <13 years enrolled in a prospective observational diagnostic study in South Africa, were evaluated. All chest x-rays were read by a panel of expert readers who attributed each with a radiological reference of either 'tuberculosis' or 'not tuberculosis'. Of the 525 chest x-rays included in this analysis, 80 (40 with a reference of 'tuberculosis' and 40 with 'not tuberculosis') were allocated to an independent test set. The remainder made up the training set. The performance of CAD4TB to identify 'tuberculosis' versus 'not tuberculosis' on chest x-ray against the radiological reference read was calculated. The CAD4TB software was then fine-tuned using the paediatric training set. We compared the performance of the fine-tuned model to the original model. Our findings were that the area under the receiver operating characteristic curve (AUC) of the original CAD4TB model, prior to fine-tuning, was 0.58. After fine-tuning there was an improvement in the AUC to 0.72 (p = 0.0016). In this first-ever description of the use of CAD to identify tuberculosis on chest x-ray in children, we demonstrate a significant improvement in the performance of CAD4TB after fine-tuning with a set of well-characterised paediatric chest x-rays. CAD has the potential to be a useful additional diagnostic tool for paediatric tuberculosis. We recommend replicating the methods we describe using a larger chest x-ray dataset from a more diverse population and evaluating the potential role of CAD to replace a human-read chest x-ray within treatment-decision algorithms for paediatric tuberculosis.

Identifiers

PMID37192175
PMCPMC10187911

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.