Chest CT Computerized Aided Quantification of PNEUMONIA Lesions in COVID-19 Infection: A Comparison among Three Commercial Software.
COVID-19
computed tomography
computer-aided quantification
Journal
International journal of environmental research and public health
ISSN: 1660-4601
Titre abrégé: Int J Environ Res Public Health
Pays: Switzerland
ID NLM: 101238455
Informations de publication
Date de publication:
22 09 2020
22 09 2020
Historique:
received:
01
08
2020
revised:
08
09
2020
accepted:
10
09
2020
entrez:
25
9
2020
pubmed:
26
9
2020
medline:
30
9
2020
Statut:
epublish
Résumé
To compare different commercial software in the quantification of Pneumonia Lesions in COVID-19 infection and to stratify the patients based on the disease severity using on chest computed tomography (CT) images. We retrospectively examined 162 patients with confirmed COVID-19 infection by reverse transcriptase-polymerase chain reaction (RT-PCR) test. All cases were evaluated separately by radiologists (visually) and by using three computer software programs: (1) Thoracic VCAR software, GE Healthcare, United States; (2) Myrian, Intrasense, France; (3) InferRead, InferVision Europe, Wiesbaden, Germany. The degree of lesions was visually scored by the radiologist using a score on 5 levels (none, mild, moderate, severe, and critic). The parameters obtained using the computer tools included healthy residual lung parenchyma, ground-glass opacity area, and consolidation volume. Intraclass coefficient (ICC), Spearman correlation analysis, and non-parametric tests were performed. Thoracic VCAR software was not able to perform volumes segmentation in 26/162 (16.0%) cases, Myrian software in 12/162 (7.4%) patients while InferRead software in 61/162 (37.7%) patients. A great variability (ICC ranged for 0.17 to 0.51) was detected among the quantitative measurements of the residual healthy lung parenchyma volume, GGO, and consolidations volumes calculated by different computer tools. The overall radiological severity score was moderately correlated with the residual healthy lung parenchyma volume obtained by ThoracicVCAR or Myrian software, with the GGO area obtained by the ThoracicVCAR tool and with consolidation volume obtained by Myrian software. Quantified volumes by InferRead software had a low correlation with the overall radiological severity score. Computer-aided pneumonia quantification could be an easy and feasible way to stratify COVID-19 cases according to severity; however, a great variability among quantitative measurements provided by computer tools should be considered.
Identifiants
pubmed: 32971756
pii: ijerph17186914
doi: 10.3390/ijerph17186914
pmc: PMC7558768
pii:
doi:
Types de publication
Comparative Study
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Références
Radiol Med. 2018 Apr;123(4):245-253
pubmed: 29230680
AJR Am J Roentgenol. 2020 Jun;214(6):1280-1286
pubmed: 32130038
Eur Respir J. 2014 Jan;43(1):204-12
pubmed: 23563264
Healthcare (Basel). 2020 Feb 27;8(1):
pubmed: 32120822
Radiol Med. 2020 Jun;125(6):517-521
pubmed: 32006241
Radiology. 2020 Apr;295(1):18
pubmed: 32003646
Radiol Med. 2019 Apr;124(4):241-242
pubmed: 30707375
Radiology. 2020 Jun;295(3):715-721
pubmed: 32053470
Radiology. 2020 Apr;295(1):202-207
pubmed: 32017661
Radiology. 2020 Jul;296(1):172-180
pubmed: 32255413
Radiol Med. 2020 May;125(5):505-508
pubmed: 32350794
Radiology. 2020 Aug;296(2):E65-E71
pubmed: 32191588
Radiology. 2020 Aug;296(2):E106-E112
pubmed: 32175814
Thorax. 2011 Sep;66(9):782-7
pubmed: 21474499
Radiology. 2020 Aug;296(2):E15-E25
pubmed: 32083985
Diagnostics (Basel). 2020 Apr 17;10(4):
pubmed: 32316503
Lancet. 2020 Feb 15;395(10223):497-506
pubmed: 31986264
Radiology. 2020 Aug;296(2):E86-E96
pubmed: 32301647
J Am Coll Radiol. 2020 Jun;17(6):699-700
pubmed: 32348740
Cytometry A. 2020 Mar;97(3):215-216
pubmed: 32142596
Radiol Med. 2020 May;125(5):500-504
pubmed: 32367319