ArticleInternational journal of environmental research and public health2020
Chest CT Computerized Aided Quantification of PNEUMONIA Lesions in COVID-19 Infection: A Comparison among Three Commercial Software.
Article in International journal of environmental research and public health, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers.
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Who cites it
37 citing papers in PubMed.
- Assessing the multi-software robustness of radiomic biomarkers: a three-tool evaluation.Frontiers in oncology · 2026Article
- Consolidation-to-ground-glass opacity ratio on chest CT as a prognostic marker for critical outcomes in COVID-19: a retrospective cohort study.BMC pulmonary medicine · 2025Article
- Artificial intelligence algorithms based approach in evaluating COVID-19 patients and management.Journal of critical care medicine (Universitatea de Medicina si Farmacie din Targu-Mures) · 2025Article
- A Nomogram for Predicting Survival in Patients with SARS-CoV-2 Omicron Variant Pneumonia Based on Admission Data.Infection and drug resistance · 2025Article
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- Artificial intelligence and radiation effects on brain tissue in glioblastoma patient: preliminary data using a quantitative tool.La Radiologia medica · 2023Article
- Qualitative and semi-quantitative ultrasound assessment in delta and Omicron Covid-19 patients: data from high volume reference center.Infectious agents and cancer · 2023Article
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- Structured reporting of computed tomography in the polytrauma patient assessment: a Delphi consensus proposal.La Radiologia medica · 2023Article
- Risk Assessment and Cholangiocarcinoma: Diagnostic Management and Artificial Intelligence.Biology · 2023Review
- Immunotherapy Assessment: A New Paradigm for Radiologists.Diagnostics (Basel, Switzerland) · 2023Review
- Imaging Features of Main Hepatic Resections: The Radiologist Challenging.Journal of personalized medicine · 2023Review
- Risk Assessment and Pancreatic Cancer: Diagnostic Management and Artificial Intelligence.Cancers · 2023Review
- Feasibility of a New Lung Ultrasound Protocol to Determine the Extent of Lung Injury in COVID-19 Pneumonia.Chest · 2023Article
- Quantitative analysis of chest computed tomography of COVID-19 pneumonia using a software widely used in Japan.PloS one · 2023Article
- Behçet's Disease: A Radiological Review of Vascular and Parenchymal Pulmonary Involvement.Diagnostics (Basel, Switzerland) · 2022Review
- AI for COVID-19 Detection from Radiographs: Incisive Analysis of State of the Art Techniques, Key Challenges and Future Directions.Ingenierie et recherche biomedicale : IRBM = Biomedical engineering and research · 2022Review
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20 authors.
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Abstract
purposeTo 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. MATERIALS AND
methodsWe 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.
resultsThoracic 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.
conclusionsComputer-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.
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