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Stanzione A, Cuocolo R, Bombace C, Pesce I, Mainolfi CG, De Giorgi M, Delli Paoli G, La Selva P, Petrone J, Camera L, Klain M, Del Vecchio S, Cuocolo A, Maurea S. Prediction of 2-[ 18F]FDG PET-CT SUVmax for Adrenal Mass Characterization: A CT Radiomics Feasibility Study. Cancers (Basel) 2023; 15:3439. [PMID: 37444549 DOI: 10.3390/cancers15133439] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2023] [Revised: 06/20/2023] [Accepted: 06/28/2023] [Indexed: 07/15/2023] Open
Abstract
BACKGROUND Indeterminate adrenal masses (AM) pose a diagnostic challenge, and 2-[18F]FDG PET-CT serves as a problem-solving tool. Aim of this study was to investigate whether CT radiomics features could be used to predict the 2-[18F]FDG SUVmax of AM. METHODS Patients with AM on 2-[18F]FDG PET-CT scan were grouped based on iodine contrast injection as CT contrast-enhanced (CE) or CT unenhanced (NCE). Two-dimensional segmentations of AM were manually obtained by multiple operators on CT images. Image resampling and discretization (bin number = 16) were performed. 919 features were calculated using PyRadiomics. After scaling, unstable, redundant, and low variance features were discarded. Using linear regression and the Uniform Manifold Approximation and Projection technique, a CT radiomics synthetic value (RadSV) was obtained. The correlation between CT RadSV and 2-[18F]FDG SUVmax was assessed with Pearson test. RESULTS A total of 725 patients underwent PET-CT from April 2020 to April 2021. In 150 (21%) patients, a total of 179 AM (29 bilateral) were detected. Group CE consisted of 84 patients with 108 AM (size = 18.1 ± 4.9 mm) and Group NCE of 66 patients with 71 AM (size = 18.5 ± 3.8 mm). In both groups, 39 features were selected. No statisticallyf significant correlation between CT RadSV and 2-[18F]FDG SUVmax was found (Group CE, r = 0.18 and p = 0.058; Group NCE, r = 0.13 and p = 0.27). CONCLUSIONS It might not be feasible to predict 2-[18F]FDG SUVmax of AM using CT RadSV. Its role as a problem-solving tool for indeterminate AM remains fundamental.
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Affiliation(s)
- Arnaldo Stanzione
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", 80131 Naples, Italy
| | - Renato Cuocolo
- Department of Medicine, Surgery and Dentistry, University of Salerno, 84084 Baronissi, Italy
| | - Claudia Bombace
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", 80131 Naples, Italy
| | - Ilaria Pesce
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", 80131 Naples, Italy
| | - Ciro Gabriele Mainolfi
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", 80131 Naples, Italy
| | - Marco De Giorgi
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", 80131 Naples, Italy
| | - Gregorio Delli Paoli
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", 80131 Naples, Italy
| | - Pasquale La Selva
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", 80131 Naples, Italy
| | - Jessica Petrone
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", 80131 Naples, Italy
| | - Luigi Camera
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", 80131 Naples, Italy
| | - Michele Klain
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", 80131 Naples, Italy
| | - Silvana Del Vecchio
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", 80131 Naples, Italy
| | - Alberto Cuocolo
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", 80131 Naples, Italy
| | - Simone Maurea
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", 80131 Naples, Italy
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Canivet P, Desir C, Thys M, Henket M, Frix AN, Ernst B, Walsh S, Occhipinti M, Vos W, Maes N, Canivet JL, Louis R, Meunier P, Guiot J. The Role of Imaging in the Detection of Non-COVID-19 Pathologies during the Massive Screening of the First Pandemic Wave. Diagnostics (Basel) 2022; 12:diagnostics12071567. [PMID: 35885473 PMCID: PMC9324631 DOI: 10.3390/diagnostics12071567] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2022] [Revised: 06/25/2022] [Accepted: 06/26/2022] [Indexed: 11/24/2022] Open
Abstract
During the COVID-19 pandemic induced by the SARS-CoV-2, numerous chest scans were carried out in order to establish the diagnosis, quantify the extension of lesions but also identify the occurrence of potential pulmonary embolisms. In this perspective, the performed chest scans provided a varied database for a retrospective analysis of non-COVID-19 chest pathologies discovered de novo. The fortuitous discovery of de novo non-COVID-19 lesions was generally not detected by the automated systems for COVID-19 pneumonia developed in parallel during the pandemic and was thus identified on chest CT by the radiologist. The objective is to use the study of the occurrence of non-COVID-19-related chest abnormalities (known and unknown) in a large cohort of patients having suffered from confirmed COVID-19 infection and statistically correlate the clinical data and the occurrence of these abnormalities in order to assess the potential of increased early detection of lesions/alterations. This study was performed on a group of 362 COVID-19-positive patients who were prescribed a CT scan in order to diagnose and predict COVID-19-associated lung disease. Statistical analysis using mean, standard deviation (SD) or median and interquartile range (IQR), logistic regression models and linear regression models were used for data analysis. Results were considered significant at the 5% critical level (p < 0.05). These de novo non-COVID-19 thoracic lesions detected on chest CT showed a significant prevalence in cardiovascular pathologies, with calcifying atheromatous anomalies approaching nearly 35.4% in patients over 65 years of age. The detection of non-COVID-19 pathologies was mostly already known, except for suspicious nodule, thyroid goiter and the ascending thoracic aortic aneurysm. The presence of vertebral compression or signs of pulmonary fibrosis has shown a significant impact on inpatient length of stay. The characteristics of the patients in this sample, both from a demographic and a tomodensitometric point of view on non-COVID-19 pathologies, influenced the length of hospital stay as well as the risk of intra-hospital death. This retrospective study showed that the potential importance of the detection of these non-COVID-19 lesions by the radiologist was essential in the management and the intra-hospital course of the patients.
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Affiliation(s)
- Perrine Canivet
- Department of Radiology, University Hospital of Liège, 4000 Liège, Belgium; (C.D.); (P.M.)
- Correspondence:
| | - Colin Desir
- Department of Radiology, University Hospital of Liège, 4000 Liège, Belgium; (C.D.); (P.M.)
| | - Marie Thys
- Department of Medico-Economic Information, University Hospital of Liège, 4000 Liège, Belgium;
| | - Monique Henket
- Department of Pneumology, University Hospital of Liège, 4000 Liège, Belgium; (M.H.); (A.-N.F.); (B.E.); (R.L.); (J.G.)
| | - Anne-Noëlle Frix
- Department of Pneumology, University Hospital of Liège, 4000 Liège, Belgium; (M.H.); (A.-N.F.); (B.E.); (R.L.); (J.G.)
| | - Benoit Ernst
- Department of Pneumology, University Hospital of Liège, 4000 Liège, Belgium; (M.H.); (A.-N.F.); (B.E.); (R.L.); (J.G.)
| | - Sean Walsh
- Radiomics (Oncoradiomics SA), 4000 Liège, Belgium; (S.W.); (M.O.); (W.V.)
| | | | - Wim Vos
- Radiomics (Oncoradiomics SA), 4000 Liège, Belgium; (S.W.); (M.O.); (W.V.)
| | - Nathalie Maes
- Biostatistics and Medico-Economic Information Department, University Hospital of Liège, 4000 Liège, Belgium;
| | - Jean Luc Canivet
- Department of Intensive Unit Care, University Hospital of Liège, 4000 Liège, Belgium;
| | - Renaud Louis
- Department of Pneumology, University Hospital of Liège, 4000 Liège, Belgium; (M.H.); (A.-N.F.); (B.E.); (R.L.); (J.G.)
| | - Paul Meunier
- Department of Radiology, University Hospital of Liège, 4000 Liège, Belgium; (C.D.); (P.M.)
| | - Julien Guiot
- Department of Pneumology, University Hospital of Liège, 4000 Liège, Belgium; (M.H.); (A.-N.F.); (B.E.); (R.L.); (J.G.)
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