Radiology screening scale for usual interstitial pneumonia as an additional tool for establishing the diagnosis of pulmonary fibrosis in patients with post-COVID-19 ILD.
<bold>Background:</bold> The COVID-19 pandemic has adversely affected the diagnosis of interstitial lung disease (ILD) and led to a diagnostic dilemma in the diagnosis of pulmonary fibrosis (PF). Despite the fact that PF has distinct radiological patterns (RP), we continue to face over diagnosis of PF in post-COVID-19 ILD. <bold>Aims:</bold> A radiology screening scale (RSS) for usual interstitial pneumonia (UIP) was developed to confirm the radiological diagnosis of PF in patients with post-COVID-19 ILD. <bold>Methods:</bold> RSS for UIP of localization (A) and RP (B). A: Bilateral basal lesion plus 20 points (P), bilateral sub pleural lesions plus 20 P, lesions of the upper parts (apex) prevail min 10 P, only unilateral lesions/lesions of the upper parts min 10 P. B: Bilateral reticulation plus 20 P, similar bilateral honeycombing (HC) plus 10 P, bilateral HC plus 20 P, bilateral pattern similar to bronchiectasis (BE) plus 10 P, bilateral pattern of BE plus 20 P, presence of bilateral consolidation min 10 P, the predominance of ground glass opacity min 10 P, presence of emphysema/emphysematous cysts/cylindrical BE min 10 P. Computed tomography images were analyzed using the K-PACS program. <bold>Results:</bold> RSS for UIP was used for the reference analysis of the findings of patients with post-COVID-19 ILD (n=105) who were previously diagnosed with PF. The discrepancy between the previously established diagnosis of PF and the diagnosis of PF based on the RSS for UIP amounted to 88.57% (n=93). The diagnosis of PF was confirmed in 11.43% (n=12) based on RP from 60 to 80 P on this scale. <bold>Conclusions:</bold> The proposed RSS for UIP can be used by doctors as an additional diagnostic tool, as well as as an action algorithm for an artificial intelligence program to interpret radiological patterns of progressive PF and idiopathic PF.
Authors
- Oleksandr Dziublyk (ORCID: https://orcid.org/0000-0001-5751-684X)
- Eduard Khodosh (ORCID: https://orcid.org/0000-0003-0572-4932)
- Yaroslav Dziublyk (ORCID: https://orcid.org/0000-0002-6497-5267)
- Oleh Yakovenko (ORCID: https://orcid.org/0000-0002-8655-2273)
- Tetiana Yakovenko (ORCID: https://orcid.org/0000-0002-7426-5605)
- Alla Hrytsiuk
Institutions
- Lutsk National Technical University (UA)
- Lesya Ukrainka Volyn National University (UA)
- Institute of Pharmacology and Toxicology of the National Academy of Medical Sciences of Ukraine (UA)
- State Institution «Academician O.F.Vozianov Institute of Urology of the National Academy of Medical Sciences of Ukraine» (UA)
- National Academy of Medical Sciences of Ukraine (UA)
- Kharkiv National Medical University (UA)
Publication Details
- Published
- 2024-09-14
- DOI
- https://doi.org/10.1183/13993003.congress-2024.pa3410
- Primary Topic
- COVID-19 diagnosis using AI
- Type
- article
- Field-Weighted Citation Impact
- 0.00