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Rocca A, Komici K, Brunese MC, Pacella G, Avella P, Di Benedetto C, Caiazzo C, Zappia M, Brunese L, Vallone G. Quantitative ultrasound (QUS) in the evaluation of liver steatosis: data reliability in different respiratory phases and body positions. LA RADIOLOGIA MEDICA 2024; 129:549-557. [PMID: 38512608 PMCID: PMC11021279 DOI: 10.1007/s11547-024-01786-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/21/2023] [Accepted: 01/10/2024] [Indexed: 03/23/2024]
Abstract
Liver steatosis is the most common chronic liver disease and affects 10-24% of the general population. As the grade of disease can range from fat infiltration to steatohepatitis and cirrhosis, an early diagnosis is needed to set the most appropriate therapy. Innovative noninvasive radiological techniques have been developed through MRI and US. MRI-PDFF is the reference standard, but it is not so widely diffused due to its cost. For this reason, ultrasound tools have been validated to study liver parenchyma. The qualitative assessment of the brightness of liver parenchyma has now been supported by quantitative values of attenuation and scattering to make the analysis objective and reproducible. We aim to demonstrate the reliability of quantitative ultrasound in assessing liver fat and to confirm the inter-operator reliability in different respiratory phases. We enrolled 45 patients examined during normal breathing at rest, peak inspiration, peak expiration, and semi-sitting position. The highest inter-operator agreement in both attenuation and scattering parameters was achieved at peak inspiration and peak expiration, followed by semi-sitting position. In conclusion, this technology also allows to monitor uncompliant patients, as it grants high reliability and reproducibility in different body position and respiratory phases.
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Affiliation(s)
- Aldo Rocca
- Department of Medicine and Health Sciences "Vincenzo Tiberio", University of Molise, 86100, Campobasso, Italy
| | - Klara Komici
- Department of Medicine and Health Sciences "Vincenzo Tiberio", University of Molise, 86100, Campobasso, Italy
| | - Maria Chiara Brunese
- Department of Medicine and Health Sciences "Vincenzo Tiberio", University of Molise, 86100, Campobasso, Italy.
| | - Giulia Pacella
- Department of Medicine and Health Sciences "Vincenzo Tiberio", University of Molise, 86100, Campobasso, Italy
| | - Pasquale Avella
- Department of General Surgery, Center for Hepatobiliary and Pancreatic Surgery, Pineta Grande Hospital, Castel Volturno, CE, Italy
| | - Chiara Di Benedetto
- Department of Medicine and Health Sciences "Vincenzo Tiberio", University of Molise, 86100, Campobasso, Italy
| | - Corrado Caiazzo
- Department of Medicine and Health Sciences "Vincenzo Tiberio", University of Molise, 86100, Campobasso, Italy
| | - Marcello Zappia
- Department of Medicine and Health Sciences "Vincenzo Tiberio", University of Molise, 86100, Campobasso, Italy
| | - Luca Brunese
- Department of Medicine and Health Sciences "Vincenzo Tiberio", University of Molise, 86100, Campobasso, Italy
| | - Gianfranco Vallone
- Department of Medicine and Health Sciences "Vincenzo Tiberio", University of Molise, 86100, Campobasso, Italy
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Ma P, Gao H, Shen N, Zhang L, Zhang Y, Zheng K, Xu B, Qin J, He J, Xu T, Li Y, Wu J, Yuan Y, Xue B. Association of urinary chlorpyrifos, paraquat, and cyproconazole levels with the severity of fatty liver based on MRI. BMC Public Health 2024; 24:807. [PMID: 38486191 PMCID: PMC10941454 DOI: 10.1186/s12889-024-18129-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2023] [Accepted: 02/16/2024] [Indexed: 03/17/2024] Open
Abstract
BACKGROUND The objective of this study was to detect the urinary levels of chlorpyrifos, paraquat, and cyproconazole in residents living in Fuyang City and to analyze the correlation between these urinary pesticides levels and the severity of fatty liver disease (FLD). METHODS All participants' fat fraction (FF) values were recorded by MRI (Magnetic resonance imaging). First-morning urine samples were collected from 53 participants from Fuyang Peoples'Hospital. The levels of three urinary pesticides were measured using β-glucuronidase hydrolysis followed by a. The results were analyzed by using Pearson correlation analysis and binary logistic regression analysis to reveal the correlation between three urinary pesticides and the severity of fatty liver. RESULTS 53 individuals were divided into 3 groups based on the results from MRI, with 20 cases in the normal control group, 16 cases in the mild fatty liver group, and 17 cases in the moderate and severe fatty liver group. Urinary chlorpyrifos level was increased along with the increase of the severity of fatty liver. Urinary paraquat level was significantly higher both in the low-grade fatty liver group and moderate & serve grade fatty liver group compared with the control group. No significant differences in urinary cyproconazole levels were observed among the three groups. Furthermore, urinary chlorpyrifos and paraquat levels were positively correlated with FF value. And chlorpyrifos was the risk factor that may be involved in the development of FLD and Receiver Operating Characteristic curve (ROC curve) analysis showed that chlorpyrifos and paraquat may serve as potential predictors of FLD. CONCLUSION The present findings indicate urinary chlorpyrifos and paraquat were positively correlated with the severity of fatty liver. Moreover, urinary chlorpyrifos and paraquat have the potential to be considered as the predictors for development of FLD. Thus, this study may provide a new perspective from the environmental factors for the diagnosis, prevention, and treatment of FLD.
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Affiliation(s)
- Peiqi Ma
- Medical imaging center, Fuyang People's Hospital, 236000, Fuyang, China
| | - Hongliang Gao
- Core Laboratory, Department of Clinical Laboratory Sir Run Run Hospital, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, 211166, Nanjing, China
- School of Clinical Medicine, Wannan Medical College, 241000, Wuhu, China
| | - Ning Shen
- China Exposomics Institute (CEI) Precision Medicine Co. Ltd, 200120, Shanghai, China
| | - Lei Zhang
- Medical imaging center, Fuyang People's Hospital, 236000, Fuyang, China
| | - Yang Zhang
- Medical imaging center, Fuyang People's Hospital, 236000, Fuyang, China
| | - Kai Zheng
- Jiangsu Engineering Research Center of Stomatological Translational Medicine, Nanjing Medical University, 210029, Nanjing, China
| | - Boqun Xu
- Department of Obstetrics and Gynecology, the Second Affiliated Hospital of Nanjing Medical University, 210011, Nanjing, China
| | - Jian Qin
- Department of Orthopaedics, Sir Run Run Hospital, Nanjing Medical University, 211100, Nanjing, China
| | - Jian He
- Department of Nuclear Medicine, Affiliated Hospital of Medical School, Nanjing Drum Tower Hospital, Nanjing University, 210029, Nanjing, China
| | - Tao Xu
- Core Laboratory, Department of Clinical Laboratory Sir Run Run Hospital, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, 211166, Nanjing, China
| | - Yan Li
- Core Laboratory, Department of Clinical Laboratory Sir Run Run Hospital, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, 211166, Nanjing, China.
| | - Jing Wu
- Core Laboratory, Department of Clinical Laboratory Sir Run Run Hospital, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, 211166, Nanjing, China.
| | - Yushan Yuan
- Medical imaging center, Fuyang People's Hospital, 236000, Fuyang, China.
| | - Bin Xue
- Department of General Surgery, The Affiliated Changzhou Second People's Hospital of Nanjing Medical University, Nanjing Medical University, 213003, Changzhou, China.
- Core Laboratory, Department of Clinical Laboratory Sir Run Run Hospital, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, 211166, Nanjing, China.
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Maino C, Vernuccio F, Cannella R, Franco PN, Giannini V, Dezio M, Pisani AR, Blandino AA, Faletti R, De Bernardi E, Ippolito D, Gatti M, Inchingolo R. Radiomics and liver: Where we are and where we are headed? Eur J Radiol 2024; 171:111297. [PMID: 38237517 DOI: 10.1016/j.ejrad.2024.111297] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2023] [Revised: 01/03/2024] [Accepted: 01/07/2024] [Indexed: 02/10/2024]
Abstract
Hepatic diffuse conditions and focal liver lesions represent two of the most common scenarios to face in everyday radiological clinical practice. Thanks to the advances in technology, radiology has gained a central role in the management of patients with liver disease, especially due to its high sensitivity and specificity. Since the introduction of computed tomography (CT) and magnetic resonance imaging (MRI), radiology has been considered the non-invasive reference modality to assess and characterize liver pathologies. In recent years, clinical practice has moved forward to a quantitative approach to better evaluate and manage each patient with a more fitted approach. In this setting, radiomics has gained an important role in helping radiologists and clinicians characterize hepatic pathological entities, in managing patients, and in determining prognosis. Radiomics can extract a large amount of data from radiological images, which can be associated with different liver scenarios. Thanks to its wide applications in ultrasonography (US), CT, and MRI, different studies were focused on specific aspects related to liver diseases. Even if broadly applied, radiomics has some advantages and different pitfalls. This review aims to summarize the most important and robust studies published in the field of liver radiomics, underlying their main limitations and issues, and what they can add to the current and future clinical practice and literature.
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Affiliation(s)
- Cesare Maino
- Department of Radiology, Fondazione IRCCS San Gerardo dei Tintori, Monza 20900, Italy.
| | - Federica Vernuccio
- Institute of Radiology, University Hospital of Padova, Padova 35128, Italy
| | - Roberto Cannella
- Department of Biomedicine, Neuroscience and Advanced Diagnostics (BiND), University of Palermo, Palermo 90127, Italy
| | - Paolo Niccolò Franco
- Department of Radiology, Fondazione IRCCS San Gerardo dei Tintori, Monza 20900, Italy
| | - Valentina Giannini
- Department of Surgical Sciences, University of Turin, Turin 10126, Italy
| | - Michele Dezio
- Department of Radiology, Miulli Hospital, Acquaviva delle Fonti 70021, Bari, Italy
| | - Antonio Rosario Pisani
- Nuclear Medicine Unit, Interdisciplinary Department of Medicine, University of Bari, Bari 70121, Italy
| | - Antonino Andrea Blandino
- Department of Biomedicine, Neuroscience and Advanced Diagnostics (BiND), University of Palermo, Palermo 90127, Italy
| | - Riccardo Faletti
- Department of Surgical Sciences, University of Turin, Turin 10126, Italy
| | - Elisabetta De Bernardi
- Bicocca Bioinformatics Biostatistics and Bioimaging Centre - B4, University of Milano Bicocca, Milano 20100, Italy; School of Medicine, University of Milano Bicocca, Milano 20100, Italy
| | - Davide Ippolito
- Department of Radiology, Fondazione IRCCS San Gerardo dei Tintori, Monza 20900, Italy; School of Medicine, University of Milano Bicocca, Milano 20100, Italy
| | - Marco Gatti
- Department of Surgical Sciences, University of Turin, Turin 10126, Italy
| | - Riccardo Inchingolo
- Unit of Interventional Radiology, F. Miulli Hospital, Acquaviva delle Fonti 70021, Italy
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Brunese MC, Fantozzi MR, Fusco R, De Muzio F, Gabelloni M, Danti G, Borgheresi A, Palumbo P, Bruno F, Gandolfo N, Giovagnoni A, Miele V, Barile A, Granata V. Update on the Applications of Radiomics in Diagnosis, Staging, and Recurrence of Intrahepatic Cholangiocarcinoma. Diagnostics (Basel) 2023; 13:diagnostics13081488. [PMID: 37189589 DOI: 10.3390/diagnostics13081488] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2023] [Revised: 04/14/2023] [Accepted: 04/18/2023] [Indexed: 05/17/2023] Open
Abstract
BACKGROUND This paper offers an assessment of radiomics tools in the evaluation of intrahepatic cholangiocarcinoma. METHODS The PubMed database was searched for papers published in the English language no earlier than October 2022. RESULTS We found 236 studies, and 37 satisfied our research criteria. Several studies addressed multidisciplinary topics, especially diagnosis, prognosis, response to therapy, and prediction of staging (TNM) or pathomorphological patterns. In this review, we have covered diagnostic tools developed through machine learning, deep learning, and neural network for the recurrence and prediction of biological characteristics. The majority of the studies were retrospective. CONCLUSIONS It is possible to conclude that many performing models have been developed to make differential diagnosis easier for radiologists to predict recurrence and genomic patterns. However, all the studies were retrospective, lacking further external validation in prospective and multicentric cohorts. Furthermore, the radiomics models and the expression of results should be standardized and automatized to be applicable in clinical practice.
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Affiliation(s)
- Maria Chiara Brunese
- Department of Medicine and Health Sciences "V. Tiberio", University of Molise, 86100 Campobasso, Italy
| | | | - Roberta Fusco
- Medical Oncology Division, Igea SpA, 80013 Naples, Italy
| | - Federica De Muzio
- Department of Medicine and Health Sciences "V. Tiberio", University of Molise, 86100 Campobasso, Italy
| | - Michela Gabelloni
- Nuclear Medicine Unit, Department of Translational Research, University of Pisa, 56126 Pisa, Italy
| | - Ginevra Danti
- Italian Society of Medical and Interventional Radiology (SIRM), SIRM Foundation, Via della Signora 2, 20122 Milan, Italy
- Department of Emergency Radiology, Careggi University Hospital, Largo Brambilla 3, 50134 Florence, Italy
| | - Alessandra Borgheresi
- Department of Radiology, University Hospital "Azienda Ospedaliera Universitaria delle Marche", 60121 Ancona, Italy
- Department of Clinical, Special and Dental Sciences, Università Politecnica delle Marche, 60121 Ancona, Italy
| | - Pierpaolo Palumbo
- Department of Diagnostic Imaging, Area of Cardiovascular and Interventional Imaging, Abruzzo Health Unit 1, 67100 L'Aquila, Italy
| | - Federico Bruno
- Department of Diagnostic Imaging, Area of Cardiovascular and Interventional Imaging, Abruzzo Health Unit 1, 67100 L'Aquila, Italy
| | - Nicoletta Gandolfo
- Diagnostic Imaging Department, Villa Scassi Hospital-ASL 3, 16149 Genoa, Italy
| | - Andrea Giovagnoni
- Department of Radiology, University Hospital "Azienda Ospedaliera Universitaria delle Marche", 60121 Ancona, Italy
- Department of Clinical, Special and Dental Sciences, Università Politecnica delle Marche, 60121 Ancona, Italy
| | - Vittorio Miele
- Italian Society of Medical and Interventional Radiology (SIRM), SIRM Foundation, Via della Signora 2, 20122 Milan, Italy
- Department of Emergency Radiology, Careggi University Hospital, Largo Brambilla 3, 50134 Florence, Italy
| | - Antonio Barile
- Department of Biotechnological and Applied Clinical Sciences, University of L'Aquila, 67100 L'Aquila, Italy
| | - Vincenza Granata
- Division of Radiology, Istituto Nazionale Tumori IRCCS Fondazione Pascale-IRCCS di Napoli, 80131 Naples, Italy
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