Computer-Aided Diagnosis of Pulmonary Nodules in Rheumatoid Arthritis
(1) Background: Rheumatoid arthritis (RA) is considered a systemic inflammatory pathology characterized by symmetric polyarthritis associated with extra-articular manifestations, such as lung disease. The purpose of the present study is to use CAD in the detection of rheumatoid pulmonary nodules. In...
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MDPI AG
2022-11-01
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| Series: | Life |
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| Online Access: | https://www.mdpi.com/2075-1729/12/11/1935 |
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| author | Anca Emanuela Mușetescu Florin Liviu Gherghina Lucian-Mihai Florescu Liliana Streba Paulina Lucia Ciurea Alesandra Florescu Ioana Andreea Gheonea |
| author_facet | Anca Emanuela Mușetescu Florin Liviu Gherghina Lucian-Mihai Florescu Liliana Streba Paulina Lucia Ciurea Alesandra Florescu Ioana Andreea Gheonea |
| author_sort | Anca Emanuela Mușetescu |
| collection | DOAJ |
| description | (1) Background: Rheumatoid arthritis (RA) is considered a systemic inflammatory pathology characterized by symmetric polyarthritis associated with extra-articular manifestations, such as lung disease. The purpose of the present study is to use CAD in the detection of rheumatoid pulmonary nodules. In addition, we aim to identify the characteristics and associations between clinical, laboratory and imaging data in patients with rheumatoid arthritis and lung nodules. (2) Methods: The study included a number of 42 patients diagnosed with rheumatoid arthritis according to the 2010 American College of Rheumatology (ACR)/European League Against Rheumatism (EULAR) criteria, examined from January 2017 to November 2022 in the Departments of Rheumatology and Radiology and Medical Imaging of the University of Medicine and Pharmacy of Craiova. Medical records were reviewed. A retrospective blinded review of CT for biopsy-proven pulmonary nodules in RA using Veolity LungCAD software was performed (MeVis Medical Solutions AG, Bremen, Germany). Imaging was also reviewed by a senior radiologist. (3) Results: The interobserver agreement proved to be moderate (κ = 0.478) for the overall examined cases. CAD interpretation resulted in false positive results in the case of 12 lung nodules, whereas false negative results were reported in the case of 8 lung nodules. The mean time it took for the detection of lung nodules using CAD was 4.2 min per patient, whereas the detection of lung nodules by the radiologist was 8.1 min per patient. This resulted in a faster interpretation of lung CT scans, almost reducing the detection time by half (<i>p</i> < 0.001). (4) Conclusions: The CAD software is useful in identifying lung nodules, in shortening the interpretation time of the CT examination and also in aiding the radiologist in better assessing all the pulmonary lung nodules. However, the CAD software cannot replace the human eye yet due to the relative high rate of false positive and false negative results. |
| first_indexed | 2024-03-09T18:12:53Z |
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| issn | 2075-1729 |
| language | English |
| last_indexed | 2024-03-09T18:12:53Z |
| publishDate | 2022-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Life |
| spelling | doaj.art-81df55de502b476ca118bdc9b4fd496c2023-11-24T08:58:19ZengMDPI AGLife2075-17292022-11-011211193510.3390/life12111935Computer-Aided Diagnosis of Pulmonary Nodules in Rheumatoid ArthritisAnca Emanuela Mușetescu0Florin Liviu Gherghina1Lucian-Mihai Florescu2Liliana Streba3Paulina Lucia Ciurea4Alesandra Florescu5Ioana Andreea Gheonea6Department of Rheumatology, University of Medicine and Pharmacy of Craiova, 200349 Craiova, RomaniaDepartment of Medical Rehabilitation, University of Medicine and Pharmacy of Craiova, 200349 Craiova, RomaniaDepartment of Radiology and Medical Imaging, University of Medicine and Pharmacy of Craiova, 200349 Craiova, RomaniaDepartment of Oncology, University of Medicine and Pharmacy of Craiova, 200349 Craiova, RomaniaDepartment of Rheumatology, University of Medicine and Pharmacy of Craiova, 200349 Craiova, RomaniaDepartment of Rheumatology, University of Medicine and Pharmacy of Craiova, 200349 Craiova, RomaniaDepartment of Radiology and Medical Imaging, University of Medicine and Pharmacy of Craiova, 200349 Craiova, Romania(1) Background: Rheumatoid arthritis (RA) is considered a systemic inflammatory pathology characterized by symmetric polyarthritis associated with extra-articular manifestations, such as lung disease. The purpose of the present study is to use CAD in the detection of rheumatoid pulmonary nodules. In addition, we aim to identify the characteristics and associations between clinical, laboratory and imaging data in patients with rheumatoid arthritis and lung nodules. (2) Methods: The study included a number of 42 patients diagnosed with rheumatoid arthritis according to the 2010 American College of Rheumatology (ACR)/European League Against Rheumatism (EULAR) criteria, examined from January 2017 to November 2022 in the Departments of Rheumatology and Radiology and Medical Imaging of the University of Medicine and Pharmacy of Craiova. Medical records were reviewed. A retrospective blinded review of CT for biopsy-proven pulmonary nodules in RA using Veolity LungCAD software was performed (MeVis Medical Solutions AG, Bremen, Germany). Imaging was also reviewed by a senior radiologist. (3) Results: The interobserver agreement proved to be moderate (κ = 0.478) for the overall examined cases. CAD interpretation resulted in false positive results in the case of 12 lung nodules, whereas false negative results were reported in the case of 8 lung nodules. The mean time it took for the detection of lung nodules using CAD was 4.2 min per patient, whereas the detection of lung nodules by the radiologist was 8.1 min per patient. This resulted in a faster interpretation of lung CT scans, almost reducing the detection time by half (<i>p</i> < 0.001). (4) Conclusions: The CAD software is useful in identifying lung nodules, in shortening the interpretation time of the CT examination and also in aiding the radiologist in better assessing all the pulmonary lung nodules. However, the CAD software cannot replace the human eye yet due to the relative high rate of false positive and false negative results.https://www.mdpi.com/2075-1729/12/11/1935rheumatoid nodulescomputed tomographycomputer-aided diagnosis |
| spellingShingle | Anca Emanuela Mușetescu Florin Liviu Gherghina Lucian-Mihai Florescu Liliana Streba Paulina Lucia Ciurea Alesandra Florescu Ioana Andreea Gheonea Computer-Aided Diagnosis of Pulmonary Nodules in Rheumatoid Arthritis Life rheumatoid nodules computed tomography computer-aided diagnosis |
| title | Computer-Aided Diagnosis of Pulmonary Nodules in Rheumatoid Arthritis |
| title_full | Computer-Aided Diagnosis of Pulmonary Nodules in Rheumatoid Arthritis |
| title_fullStr | Computer-Aided Diagnosis of Pulmonary Nodules in Rheumatoid Arthritis |
| title_full_unstemmed | Computer-Aided Diagnosis of Pulmonary Nodules in Rheumatoid Arthritis |
| title_short | Computer-Aided Diagnosis of Pulmonary Nodules in Rheumatoid Arthritis |
| title_sort | computer aided diagnosis of pulmonary nodules in rheumatoid arthritis |
| topic | rheumatoid nodules computed tomography computer-aided diagnosis |
| url | https://www.mdpi.com/2075-1729/12/11/1935 |
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