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Catalano M, Bortolotto C, Nicora G, Achilli MF, Consonni A, Ruongo L, Callea G, Lo Tito A, Biasibetti C, Donatelli A, Cutti S, Comotto F, Stella GM, Corsico A, Perlini S, Bellazzi R, Bruno R, Filippi A, Preda L. Performance of an AI algorithm during the different phases of the COVID pandemics: what can we learn from the AI and vice versa. Eur J Radiol Open 2023; 11:100497. [PMID: 37360770 PMCID: PMC10278371 DOI: 10.1016/j.ejro.2023.100497] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2023] [Revised: 06/02/2023] [Accepted: 06/04/2023] [Indexed: 06/28/2023] Open
Abstract
Background Artificial intelligence (AI) has proved to be of great value in diagnosing and managing Sars-Cov-2 infection. ALFABETO (ALL-FAster-BEtter-TOgether) is a tool created to support healthcare professionals in the triage, mainly in optimizing hospital admissions. Methods The AI was trained during the pandemic's "first wave" (February-April 2020). Our aim was to assess the performance during the "third wave" of the pandemics (February-April 2021) and evaluate its evolution. The neural network proposed behavior (hospitalization vs home care) was compared with what was actually done. If there were discrepancies between ALFABETO's predictions and clinicians' decisions, the disease's progression was monitored. Clinical course was defined as "favorable/mild" if patients could be managed at home or in spoke centers and "unfavorable/severe" if patients need to be managed in a hub center. Results ALFABETO showed accuracy of 76%, AUROC of 83%; specificity was 78% and recall 74%. ALFABETO also showed high precision (88%). 81 hospitalized patients were incorrectly predicted to be in "home care" class. Among those "home-cared" by the AI and "hospitalized" by the clinicians, 3 out of 4 misclassified patients (76.5%) showed a favorable/mild clinical course. ALFABETO's performance matched the reports in literature. Conclusions The discrepancies mostly occurred when the AI predicted patients could stay at home but clinicians hospitalized them; these cases could be handled in spoke centers rather than hubs, and the discrepancies may aid clinicians in patient selection. The interaction between AI and human experience has the potential to improve both AI performance and our comprehension of pandemic management.
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Affiliation(s)
- Michele Catalano
- Department of Clinical, Surgical, Diagnostic and Pediatric Sciences, University of Pavia, Pavia, Italy and Radiology Department, Fondazione IRCCS Policlinico San Matteo, Pavia, Italy
| | - Chandra Bortolotto
- Department of Clinical, Surgical, Diagnostic and Pediatric Sciences, University of Pavia, Pavia, Italy and Radiology Department, Fondazione IRCCS Policlinico San Matteo, Pavia, Italy
| | - Giovanna Nicora
- Department of Electrical, Computer and Biomedical Engineering, University of Pavia, Pavia, Italy
| | - Marina Francesca Achilli
- Department of Clinical, Surgical, Diagnostic and Pediatric Sciences, University of Pavia, Pavia, Italy and Radiology Department, Fondazione IRCCS Policlinico San Matteo, Pavia, Italy
| | - Alessio Consonni
- Department of Clinical, Surgical, Diagnostic and Pediatric Sciences, University of Pavia, Pavia, Italy and Radiology Department, Fondazione IRCCS Policlinico San Matteo, Pavia, Italy
| | - Lidia Ruongo
- Department of Clinical, Surgical, Diagnostic and Pediatric Sciences, University of Pavia, Pavia, Italy and Radiology Department, Fondazione IRCCS Policlinico San Matteo, Pavia, Italy
| | - Giovanni Callea
- Department of Clinical, Surgical, Diagnostic and Pediatric Sciences, University of Pavia, Pavia, Italy and Radiology Department, Fondazione IRCCS Policlinico San Matteo, Pavia, Italy
| | - Antonio Lo Tito
- Department of Clinical, Surgical, Diagnostic and Pediatric Sciences, University of Pavia, Pavia, Italy and Radiology Department, Fondazione IRCCS Policlinico San Matteo, Pavia, Italy
| | - Carla Biasibetti
- Department of Clinical, Surgical, Diagnostic and Pediatric Sciences, University of Pavia, Pavia, Italy and Radiology Department, Fondazione IRCCS Policlinico San Matteo, Pavia, Italy
| | - Antonella Donatelli
- Department of Clinical, Surgical, Diagnostic and Pediatric Sciences, University of Pavia, Pavia, Italy and Radiology Department, Fondazione IRCCS Policlinico San Matteo, Pavia, Italy
| | - Sara Cutti
- Medical Direction, Fondazione IRCCS Policlinico San Matteo, Pavia, Italy
| | | | - Giulia Maria Stella
- Department of Internal Medicine and Therapeutics, University of Pavia, Pavia, Italy and Dept. of Respiratory Diseases Unit, Fondazione IRCCS Policlinico San Matteo, Pavia, Italy
| | - Angelo Corsico
- Department of Internal Medicine and Therapeutics, University of Pavia, Pavia, Italy and Dept. of Respiratory Diseases Unit, Fondazione IRCCS Policlinico San Matteo, Pavia, Italy
| | - Stefano Perlini
- Department of Internal Medicine and Therapeutics, University of Pavia, Pavia, Italy and Dept. of Emergency Department, Fondazione IRCCS Policlinico San Matteo, Pavia, Italy
| | - Riccardo Bellazzi
- Department of Electrical, Computer and Biomedical Engineering, University of Pavia, Pavia, Italy
| | - Raffaele Bruno
- Department of Clinical, Surgical, Diagnostic and Pediatric Sciences, University of Pavia, Pavia, Italy and Infectious Diseases Unit, Fondazione IRCCS Policlinico San Matteo, Pavia, Italy
| | - Andrea Filippi
- Radiation Oncology Unit, University of Pavia, Pavia, Italy and Infectious Diseases Unit, Fondazione IRCCS Policlinico San Matteo, Pavia, Italy
| | - Lorenzo Preda
- Department of Clinical, Surgical, Diagnostic and Pediatric Sciences, University of Pavia, Pavia, Italy and Radiology Department, Fondazione IRCCS Policlinico San Matteo, Pavia, Italy
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Bortolotto C, Messana G, Lo Tito A, Stella GM, Pinto A, Podrecca C, Bellazzi R, Gerbasi A, Agustoni F, Han F, Nickel MD, Zacà D, Filippi AR, Bottinelli OM, Preda L. The Role of Native T1 and T2 Mapping Times in Identifying PD-L1 Expression and the Histological Subtype of NSCLCs. Cancers (Basel) 2023; 15:3252. [PMID: 37370861 DOI: 10.3390/cancers15123252] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2023] [Revised: 06/08/2023] [Accepted: 06/16/2023] [Indexed: 06/29/2023] Open
Abstract
We investigated the association of T1/T2 mapping values with programmed death-ligand 1 protein (PD-L1) expression in lung cancer and their potential in distinguishing between different histological subtypes of non-small cell lung cancers (NSCLCs). Thirty-five patients diagnosed with stage III NSCLC from April 2021 to December 2022 were included. Conventional MRI sequences were acquired with a 1.5 T system. Mean T1 and T2 mapping values were computed for six manually traced ROIs on different areas of the tumor. Data were analyzed through RStudio. Correlation between T1/T2 mapping values and PD-L1 expression was studied with a Wilcoxon-Mann-Whitney test. A Kruskal-Wallis test with a post-hoc Dunn test was used to study the correlation between T1/T2 mapping values and the histological subtypes: squamocellular carcinoma (SCC), adenocarcinoma (ADK), and poorly differentiated NSCLC (PD). There was no statistically significant correlation between T1/T2 mapping values and PD-L1 expression in NSCLC. We found statistically significant differences in T1 mapping values between ADK and SCC for the periphery ROI (p-value 0.004), the core ROI (p-value 0.01), and the whole tumor ROI (p-value 0.02). No differences were found concerning the PD NSCLCs.
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Affiliation(s)
- Chandra Bortolotto
- Diagnostic Imaging and Radiotherapy Unit, Department of Clinical, Surgical, Diagnostic, and Pediatric Sciences, University of Pavia, 27100 Pavia, Italy
- Radiology Institute, Fondazione IRCCS Policlinico San Matteo, 27100 Pavia, Italy
| | - Gaia Messana
- Diagnostic Imaging and Radiotherapy Unit, Department of Clinical, Surgical, Diagnostic, and Pediatric Sciences, University of Pavia, 27100 Pavia, Italy
| | - Antonio Lo Tito
- Diagnostic Imaging and Radiotherapy Unit, Department of Clinical, Surgical, Diagnostic, and Pediatric Sciences, University of Pavia, 27100 Pavia, Italy
| | - Giulia Maria Stella
- Unit of Respiratory Diseases, Department of Medical Sciences and Infective Diseases, Fondazione IRCCS Policlinico San Matteo, 27100 Pavia, Italy
- Department of Internal Medicine and Medical Therapeutics, University of Pavia, 27100 Pavia, Italy
| | - Alessandra Pinto
- Diagnostic Imaging and Radiotherapy Unit, Department of Clinical, Surgical, Diagnostic, and Pediatric Sciences, University of Pavia, 27100 Pavia, Italy
| | - Chiara Podrecca
- Department of Electrical, Computer and Biomedical Engineering, University of Pavia, 27100 Pavia, Italy
| | - Riccardo Bellazzi
- Department of Electrical, Computer and Biomedical Engineering, University of Pavia, 27100 Pavia, Italy
| | - Alessia Gerbasi
- Department of Electrical, Computer and Biomedical Engineering, University of Pavia, 27100 Pavia, Italy
| | - Francesco Agustoni
- Department of Medical Oncology, Fondazione IRCCS Policlinico San Matteo, 27100 Pavia, Italy
| | - Fei Han
- MR Application Predevelopment, Siemens Healthcare GmbH, Allee am Roethelheimpark 2, 91052 Erlangen, Germany
| | - Marcel Dominik Nickel
- MR Application Predevelopment, Siemens Healthcare GmbH, Allee am Roethelheimpark 2, 91052 Erlangen, Germany
| | | | - Andrea Riccardo Filippi
- Diagnostic Imaging and Radiotherapy Unit, Department of Clinical, Surgical, Diagnostic, and Pediatric Sciences, University of Pavia, 27100 Pavia, Italy
- Department of Radiation Oncology, Fondazione IRCCS Policlinico San Matteo, 27100 Pavia, Italy
| | - Olivia Maria Bottinelli
- Diagnostic Imaging and Radiotherapy Unit, Department of Clinical, Surgical, Diagnostic, and Pediatric Sciences, University of Pavia, 27100 Pavia, Italy
| | - Lorenzo Preda
- Diagnostic Imaging and Radiotherapy Unit, Department of Clinical, Surgical, Diagnostic, and Pediatric Sciences, University of Pavia, 27100 Pavia, Italy
- Radiology Institute, Fondazione IRCCS Policlinico San Matteo, 27100 Pavia, Italy
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