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Granata V, Fusco R, De Muzio F, Brunese MC, Setola SV, Ottaiano A, Cardone C, Avallone A, Patrone R, Pradella S, Miele V, Tatangelo F, Cutolo C, Maggialetti N, Caruso D, Izzo F, Petrillo A. Radiomics and machine learning analysis by computed tomography and magnetic resonance imaging in colorectal liver metastases prognostic assessment. LA RADIOLOGIA MEDICA 2023; 128:1310-1332. [PMID: 37697033 DOI: 10.1007/s11547-023-01710-w] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/18/2023] [Accepted: 08/22/2023] [Indexed: 09/13/2023]
Abstract
OBJECTIVE The aim of this study was the evaluation radiomics analysis efficacy performed using computed tomography (CT) and magnetic resonance imaging in the prediction of colorectal liver metastases patterns linked to patient prognosis: tumor growth front; grade; tumor budding; mucinous type. Moreover, the prediction of liver recurrence was also evaluated. METHODS The retrospective study included an internal and validation dataset; the first was composed by 119 liver metastases from 49 patients while the second consisted to 28 patients with single lesion. Radiomic features were extracted using PyRadiomics. Univariate and multivariate approaches including machine learning algorithms were employed. RESULTS The best predictor to identify tumor growth was the Wavelet_HLH_glcm_MaximumProbability with an accuracy of 84% and to detect recurrence the best predictor was wavelet_HLH_ngtdm_Complexity with an accuracy of 90%, both extracted by T1-weigthed arterial phase sequence. The best predictor to detect tumor budding was the wavelet_LLH_glcm_Imc1 with an accuracy of 88% and to identify mucinous type was wavelet_LLH_glcm_JointEntropy with an accuracy of 92%, both calculated on T2-weigthed sequence. An increase statistically significant of accuracy (90%) was obtained using a linear weighted combination of 15 predictors extracted by T2-weigthed images to detect tumor front growth. An increase statistically significant of accuracy at 93% was obtained using a linear weighted combination of 11 predictors by the T1-weigthed arterial phase sequence to classify tumor budding. An increase statistically significant of accuracy at 97% was obtained using a linear weighted combination of 16 predictors extracted on CT to detect recurrence. An increase statistically significant of accuracy was obtained in the tumor budding identification considering a K-nearest neighbors and the 11 significant features extracted T1-weigthed arterial phase sequence. CONCLUSIONS The results confirmed the Radiomics capacity to recognize clinical and histopathological prognostic features that should influence the choice of treatments in colorectal liver metastases patients to obtain a more personalized therapy.
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Affiliation(s)
- Vincenza Granata
- Division of Radiology, Istituto Nazionale Tumori IRCCS Fondazione Pascale - IRCCS di Napoli, Naples, Italy.
| | | | - Federica De Muzio
- Department of Medicine and Health Sciences V. Tiberio, University of Molise, 86100, Campobasso, Italy
| | - Maria Chiara Brunese
- Department of Medicine and Health Sciences V. Tiberio, University of Molise, 86100, Campobasso, Italy
| | - Sergio Venanzio Setola
- Division of Radiology, Istituto Nazionale Tumori IRCCS Fondazione Pascale - IRCCS di Napoli, Naples, Italy
| | - Alessandro Ottaiano
- Clinical Experimental Abdominal Oncology Unit, Istituto Nazionale Tumori, IRCCS Fondazione G. Pascale, 80131, Naples, Italy
| | - Claudia Cardone
- Clinical Experimental Abdominal Oncology Unit, Istituto Nazionale Tumori, IRCCS Fondazione G. Pascale, 80131, Naples, Italy
| | - Antonio Avallone
- Clinical Experimental Abdominal Oncology Unit, Istituto Nazionale Tumori, IRCCS Fondazione G. Pascale, 80131, Naples, Italy
| | - Renato Patrone
- Division of Hepatobiliary Surgical Oncology, Istituto Nazionale Tumori IRCCS Fondazione Pascale-IRCCS di Napoli, 80131, Naples, Italy
| | - Silvia Pradella
- Department of Radiology, Careggi University Hospital, Largo Brambilla 3, 50134, Florence, Italy
- SIRM Foundation, Italian Society of Medical and Interventional Radiology (SIRM), 20122, Milan, Italy
| | - Vittorio Miele
- Department of Radiology, Careggi University Hospital, Largo Brambilla 3, 50134, Florence, Italy
- SIRM Foundation, Italian Society of Medical and Interventional Radiology (SIRM), 20122, Milan, Italy
| | - Fabiana Tatangelo
- Division of Pathological Anatomy and Cytopathology, Istituto Nazionale Tumori IRCCS Fondazione Pascale-IRCCS di Napoli, 80131, Naples, Italy
| | - Carmen Cutolo
- Department of Medicine, Surgery and Dentistry, University of Salerno, 84084, Salerno, Italy
| | - Nicola Maggialetti
- Department of Medical Science, Neuroscience and Sensory Organs (DSMBNOS), University of Bari "Aldo Moro", 70124, Bari, Italy
| | - Damiano Caruso
- Department of Medical Surgical Sciences and Translational Medicine, Radiology Unit-Sant'Andrea University Hospital, Sapienza-University of Rome, 00189, Rome, Italy
| | - Francesco Izzo
- Division of Hepatobiliary Surgical Oncology, Istituto Nazionale Tumori IRCCS Fondazione Pascale-IRCCS di Napoli, 80131, Naples, Italy
| | - Antonella Petrillo
- Division of Radiology, Istituto Nazionale Tumori IRCCS Fondazione Pascale - IRCCS di Napoli, Naples, Italy
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De Muzio F, Pellegrino F, Fusco R, Tafuto S, Scaglione M, Ottaiano A, Petrillo A, Izzo F, Granata V. Prognostic Assessment of Gastropancreatic Neuroendocrine Neoplasm: Prospects and Limits of Radiomics. Diagnostics (Basel) 2023; 13:2877. [PMID: 37761243 PMCID: PMC10529975 DOI: 10.3390/diagnostics13182877] [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: 07/13/2023] [Revised: 08/28/2023] [Accepted: 08/30/2023] [Indexed: 09/29/2023] Open
Abstract
Neuroendocrine neoplasms (NENs) are a group of lesions originating from cells of the diffuse neuroendocrine system. NENs may involve different sites, including the gastrointestinal tract (GEP-NENs). The incidence and prevalence of GEP-NENs has been constantly rising thanks to the increased diagnostic power of imaging and immuno-histochemistry. Despite the plethora of biochemical markers and imaging techniques, the prognosis and therapeutic choice in GEP-NENs still represents a challenge, mainly due to the great heterogeneity in terms of tumor lesions and clinical behavior. The concept that biomedical images contain information about tissue heterogeneity and pathological processes invisible to the human eye is now well established. From this substrate comes the idea of radiomics. Computational analysis has achieved promising results in several oncological settings, and the use of radiomics in different types of GEP-NENs is growing in the field of research, yet with conflicting results. The aim of this narrative review is to provide a comprehensive update on the role of radiomics on GEP-NEN management, focusing on the main clinical aspects analyzed by most existing reports: predicting tumor grade, distinguishing NET from other tumors, and prognosis assessment.
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Affiliation(s)
- Federica De Muzio
- Department of Medicine and Health Sciences “V. Tiberio”, University of Molise, 86100 Campobasso, Italy;
| | | | - Roberta Fusco
- Medical Oncology Division, Igea SpA, 80013 Napoli, Italy;
| | - Salvatore Tafuto
- Unit of Sarcomi e Tumori Rari, Istituto Nazionale Tumori, IRCCS, Fondazione G. Pascale, 80131 Naples, Italy;
| | - Mariano Scaglione
- Department of Medical, Surgical and Experimental Sciences, University of Sassari, 07100 Sassari, Italy
| | - Alessandro Ottaiano
- Unit for Innovative Therapies of Abdominal Metastastes, Istituto Nazionale Tumori, IRCCS, Fondazione G. Pascale, 80131 Naples, Italy;
| | - Antonella Petrillo
- Division of Radiology, Istituto Nazionale Tumori, IRCCS, Fondazione G. Pascale, 80131 Naples, Italy;
| | - Francesco Izzo
- Division of Hepatobiliary Surgery, Istituto Nazionale Tumori, IRCCS, Fondazione G. Pascale, 80131 Naples, Italy
| | - Vincenza Granata
- Division of Radiology, Istituto Nazionale Tumori, IRCCS, Fondazione G. Pascale, 80131 Naples, Italy;
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3
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Borgheresi A, Agostini A, Pierpaoli L, Bruno A, Valeri T, Danti G, Bicci E, Gabelloni M, De Muzio F, Brunese MC, Bruno F, Palumbo P, Fusco R, Granata V, Gandolfo N, Miele V, Barile A, Giovagnoni A. Tips and Tricks in Thoracic Radiology for Beginners: A Findings-Based Approach. Tomography 2023; 9:1153-1186. [PMID: 37368547 DOI: 10.3390/tomography9030095] [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: 05/05/2023] [Revised: 06/03/2023] [Accepted: 06/12/2023] [Indexed: 06/29/2023] Open
Abstract
This review has the purpose of illustrating schematically and comprehensively the key concepts for the beginner who approaches chest radiology for the first time. The approach to thoracic imaging may be challenging for the beginner due to the wide spectrum of diseases, their overlap, and the complexity of radiological findings. The first step consists of the proper assessment of the basic imaging findings. This review is divided into three main districts (mediastinum, pleura, focal and diffuse diseases of the lung parenchyma): the main findings will be discussed in a clinical scenario. Radiological tips and tricks, and relative clinical background, will be provided to orient the beginner toward the differential diagnoses of the main thoracic diseases.
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Affiliation(s)
- Alessandra Borgheresi
- Department of Clinical, Special and Dental Sciences, University Politecnica delle Marche, Via Tronto 10/a, 60126 Ancona, Italy
- Department of Radiology, University Hospital "Azienda Ospedaliero Universitaria delle Marche", Via Conca 71, 60126 Ancona, Italy
| | - Andrea Agostini
- Department of Clinical, Special and Dental Sciences, University Politecnica delle Marche, Via Tronto 10/a, 60126 Ancona, Italy
- Department of Radiology, University Hospital "Azienda Ospedaliero Universitaria delle Marche", Via Conca 71, 60126 Ancona, Italy
- Italian Society of Medical and Interventional Radiology (SIRM), SIRM Foundation, 20122 Milan, Italy
| | - Luca Pierpaoli
- School of Radiology, University Politecnica delle Marche, Via Tronto 10/a, 60126 Ancona, Italy
| | - Alessandra Bruno
- School of Radiology, University Politecnica delle Marche, Via Tronto 10/a, 60126 Ancona, Italy
| | - Tommaso Valeri
- School of Radiology, University Politecnica delle Marche, Via Tronto 10/a, 60126 Ancona, Italy
| | - Ginevra Danti
- Department of Radiology, Azienda Ospedaliero-Universitaria Careggi, 50134 Florence, Italy
| | - Eleonora Bicci
- Department of Radiology, Azienda Ospedaliero-Universitaria Careggi, 50134 Florence, Italy
| | - Michela Gabelloni
- Nuclear Medicine Unit, Department of Translational Research, University of Pisa, 56126 Pisa, Italy
| | - Federica De Muzio
- Department of Medicine and Health Sciences V. Tiberio, University of Molise, 86100 Campobasso, Italy
| | - Maria Chiara Brunese
- Department of Medicine and Health Sciences V. Tiberio, University of Molise, 86100 Campobasso, Italy
| | - Federico Bruno
- Italian Society of Medical and Interventional Radiology (SIRM), SIRM Foundation, 20122 Milan, Italy
- Department of Diagnostic Imaging, Area of Cardiovascular and Interventional Imaging, Abruzzo Health, Unit 1, 67100 L'Aquila, Italy
| | - Pierpaolo Palumbo
- Italian Society of Medical and Interventional Radiology (SIRM), SIRM Foundation, 20122 Milan, Italy
- Department of Diagnostic Imaging, Area of Cardiovascular and Interventional Imaging, Abruzzo Health, Unit 1, 67100 L'Aquila, Italy
| | - Roberta Fusco
- Medical Oncology Division, Igea SpA, 80013 Naples, Italy
| | - Vincenza Granata
- Division of Radiology, Istituto Nazionale Tumori IRCCS Fondazione Pascale-IRCCS di Napoli, 80131 Naples, Italy
| | - Nicoletta Gandolfo
- Diagnostic Imaging Department, Villa Scassi Hospital-ASL 3, 16149 Genoa, Italy
| | - Vittorio Miele
- Italian Society of Medical and Interventional Radiology (SIRM), SIRM Foundation, 20122 Milan, Italy
- Department of Radiology, Azienda Ospedaliero-Universitaria Careggi, 50134 Florence, Italy
| | - Antonio Barile
- Department of Biotechnological and Applied Clinical Sciences, University of L'Aquila, 67100 L'Aquila, Italy
| | - Andrea Giovagnoni
- Department of Clinical, Special and Dental Sciences, University Politecnica delle Marche, Via Tronto 10/a, 60126 Ancona, Italy
- Department of Radiology, University Hospital "Azienda Ospedaliero Universitaria delle Marche", Via Conca 71, 60126 Ancona, Italy
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Granata V, Fusco R, Setola SV, Galdiero R, Maggialetti N, Patrone R, Ottaiano A, Nasti G, Silvestro L, Cassata A, Grassi F, Avallone A, Izzo F, Petrillo A. Colorectal liver metastases patients prognostic assessment: prospects and limits of radiomics and radiogenomics. Infect Agent Cancer 2023; 18:18. [PMID: 36927442 PMCID: PMC10018963 DOI: 10.1186/s13027-023-00495-x] [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: 01/31/2023] [Accepted: 03/07/2023] [Indexed: 03/18/2023] Open
Abstract
In this narrative review, we reported un up-to-date on the role of radiomics to assess prognostic features, which can impact on the liver metastases patient treatment choice. In the liver metastases patients, the possibility to assess mutational status (RAS or MSI), the tumor growth pattern and the histological subtype (NOS or mucinous) allows a better treatment selection to avoid unnecessary therapies. However, today, the detection of these features require an invasive approach. Recently, radiomics analysis application has improved rapidly, with a consequent growing interest in the oncological field. Radiomics analysis allows the textural characteristics assessment, which are correlated to biological data. This approach is captivating since it should allow to extract biological data from the radiological images, without invasive approach, so that to reduce costs and time, avoiding any risk for the patients. Several studies showed the ability of Radiomics to identify mutational status, tumor growth pattern and histological type in colorectal liver metastases. Although, radiomics analysis in a non-invasive and repeatable way, however features as the poor standardization and generalization of clinical studies results limit the translation of this analysis into clinical practice. Clear limits are data-quality control, reproducibility, repeatability, generalizability of results, and issues related to model overfitting.
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Affiliation(s)
- Vincenza Granata
- Division of Radiology, "Istituto Nazionale Tumori IRCCS Fondazione Pascale - IRCCS di Napoli", Naples, Italy.
| | - Roberta Fusco
- Medical Oncology Division, Igea SpA, Napoli, Italy.,Italian Society of Medical and Interventional Radiology (SIRM), SIRM Foundation, Via della Signora 2, Milan, 20122, Italy
| | - Sergio Venanzio Setola
- Division of Radiology, "Istituto Nazionale Tumori IRCCS Fondazione Pascale - IRCCS di Napoli", Naples, Italy
| | - Roberta Galdiero
- Division of Radiology, "Istituto Nazionale Tumori IRCCS Fondazione Pascale - IRCCS di Napoli", Naples, Italy
| | - Nicola Maggialetti
- Department of Medical Science, Neuroscience and Sensory Organs (DSMBNOS), University of Bari "Aldo Moro", Bari, 70124, Italy
| | - Renato Patrone
- Division of Epatobiliary Surgical Oncology, Istituto Nazionale Tumori IRCCS Fondazione Pascale-IRCCS di Napoli, Naples, 80131, Italy
| | - Alessandro Ottaiano
- Clinical Sperimental Abdominal Oncology Unit, Istituto Nazionale Tumori, IRCCS Fondazione G. Pascale, Napoli, 80131, Italy
| | - Guglielmo Nasti
- Clinical Sperimental Abdominal Oncology Unit, Istituto Nazionale Tumori, IRCCS Fondazione G. Pascale, Napoli, 80131, Italy
| | - Lucrezia Silvestro
- Clinical Sperimental Abdominal Oncology Unit, Istituto Nazionale Tumori, IRCCS Fondazione G. Pascale, Napoli, 80131, Italy
| | - Antonio Cassata
- Clinical Sperimental Abdominal Oncology Unit, Istituto Nazionale Tumori, IRCCS Fondazione G. Pascale, Napoli, 80131, Italy
| | - Francesca Grassi
- Division of Radiology, "Università degli Studi della Campania Luigi Vanvitelli", Naples, 80138, Italy
| | - Antonio Avallone
- Clinical Sperimental Abdominal Oncology Unit, Istituto Nazionale Tumori, IRCCS Fondazione G. Pascale, Napoli, 80131, Italy
| | - Francesco Izzo
- Division of Epatobiliary Surgical Oncology, Istituto Nazionale Tumori IRCCS Fondazione Pascale-IRCCS di Napoli, Naples, 80131, Italy
| | - Antonella Petrillo
- Division of Radiology, "Istituto Nazionale Tumori IRCCS Fondazione Pascale - IRCCS di Napoli", Naples, Italy
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Picone C, Fusco R, Tonerini M, Fanni SC, Neri E, Brunese MC, Grassi R, Danti G, Petrillo A, Scaglione M, Gandolfo N, Giovagnoni A, Barile A, Miele V, Granata C, Granata V. Dose Reduction Strategies for Pregnant Women in Emergency Settings. J Clin Med 2023; 12:jcm12051847. [PMID: 36902633 PMCID: PMC10003653 DOI: 10.3390/jcm12051847] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2023] [Revised: 02/11/2023] [Accepted: 02/23/2023] [Indexed: 03/03/2023] Open
Abstract
In modern clinical practice, there is an increasing dependence on imaging techniques in several settings, and especially during emergencies. Consequently, there has been an increase in the frequency of imaging examinations and thus also an increased risk of radiation exposure. In this context, a critical phase is a woman's pregnancy management that requires a proper diagnostic assessment to reduce radiation risk to the fetus and mother. The risk is greatest during the first phases of pregnancy at the time of organogenesis. Therefore, the principles of radiation protection should guide the multidisciplinary team. Although diagnostic tools that do not employ ionizing radiation, such as ultrasound (US) and magnetic resonance imaging (MRI) should be preferred, in several settings as polytrauma, computed tomography (CT) nonetheless remains the examination to perform, beyond the fetus risk. In addition, protocol optimization, using dose-limiting protocols and avoiding multiple acquisitions, is a critical point that makes it possible to reduce risks. The purpose of this review is to provide a critical evaluation of emergency conditions, e.g., abdominal pain and trauma, considering the different diagnostic tools that should be used as study protocols in order to control the dose to the pregnant woman and fetus.
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Affiliation(s)
- Carmine Picone
- Division of Radiology, “Instituto Nazionale Tumori IRCCS Fondazione Pascale—IRCCS di Napoli”, 80131 Naples, Italy
| | - Roberta Fusco
- Medical Oncology Division, Igea SpA, 80013 Naples, Italy
- Correspondence:
| | - Michele Tonerini
- Department of Emergency Radiology, University Hospital of Pisa, 56124 Pisa, Italy
| | - Salvatore Claudio Fanni
- Department of Translational Research, Academic Radiology, University of Pisa, 56124 Pisa, Italy
| | - Emanuele Neri
- Department of Translational Research, Academic Radiology, University of Pisa, 56124 Pisa, Italy
| | - Maria Chiara Brunese
- Diagnostic Imaging Section, Department of Medical and Surgical Sciences & Neurosciences, University of Molise, 86100 Campobasso, Italy
| | - Roberta Grassi
- Division of Radiology, “Università degli Studi della Campania Luigi Vanvitelli”, 81100 Naples, Italy
| | - Ginevra Danti
- Division of Radiology, Azienda Ospedaliera Universitaria Careggi, 50134 Florence, Italy
- Italian Society of Medical and Interventional Radiology (SIRM), SIRM Foundation, Via della Signora 2, 20122 Milan, Italy
| | - Antonella Petrillo
- Division of Radiology, “Instituto Nazionale Tumori IRCCS Fondazione Pascale—IRCCS di Napoli”, 80131 Naples, Italy
| | - Mariano Scaglione
- Department of Clinical and Experimental Medicine, University of Sassari, 07100 Sassari, Italy
| | - Nicoletta Gandolfo
- Diagnostic Imaging Department, Villa Scassi Hospital-ASL 3, Corso Scassi 1, 16121 Genoa, Italy
| | - Andrea Giovagnoni
- Department of Clinical, Special and Dental Sciences, University Politecnica Delle Marche, Via Conca 71, 60126 Ancona, Italy
- Department of Radiology, University Hospital “Azienda Ospedaliera Universitaria delle Marche”, Via Conca 71, 60126 Ancona, Italy
| | - Antonio Barile
- Department of Radiology, Careggi University Hospital, Largo Brambilla 3, 50134 Florence, Italy
| | - Vittorio Miele
- Division of Radiology, Azienda Ospedaliera Universitaria Careggi, 50134 Florence, Italy
- Italian Society of Medical and Interventional Radiology (SIRM), SIRM Foundation, Via della Signora 2, 20122 Milan, Italy
| | - Claudio Granata
- Department of Radiology, G. Gaslini Institute, IRCCS, 16147 Genova, Italy
| | - Vincenza Granata
- Division of Radiology, “Instituto Nazionale Tumori IRCCS Fondazione Pascale—IRCCS di Napoli”, 80131 Naples, Italy
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Post-Surgical Imaging Assessment in Rectal Cancer: Normal Findings and Complications. J Clin Med 2023; 12:jcm12041489. [PMID: 36836024 PMCID: PMC9966470 DOI: 10.3390/jcm12041489] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2022] [Revised: 12/30/2022] [Accepted: 02/09/2023] [Indexed: 02/16/2023] Open
Abstract
Rectal cancer (RC) is one of the deadliest malignancies worldwide. Surgery is the most common treatment for RC, performed in 63.2% of patients. The type of surgical approach chosen aims to achieve maximum residual function with the lowest risk of recurrence. The selection is made by a multidisciplinary team that assesses the characteristics of the patient and the tumor. Total mesorectal excision (TME), including both low anterior resection (LAR) and abdominoperineal resection (APR), is still the standard of care for RC. Radical surgery is burdened by a 31% rate of major complications (Clavien-Dindo grade 3-4), such as anastomotic leaks and a risk of a permanent stoma. In recent years, less-invasive techniques, such as local excision, have been tested. These additional procedures could mitigate the morbidity of rectal resection, while providing acceptable oncologic results. The "watch and wait" approach is not a globally accepted model of care but encouraging results on selected groups of patients make it a promising strategy. In this plethora of treatments, the radiologist is called upon to distinguish a physiological from a pathological postoperative finding. The aim of this narrative review is to identify the main post-surgical complications and the most effective imaging techniques.
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Granata V, Fusco R, De Muzio F, Cutolo C, Grassi F, Brunese MC, Simonetti I, Catalano O, Gabelloni M, Pradella S, Danti G, Flammia F, Borgheresi A, Agostini A, Bruno F, Palumbo P, Ottaiano A, Izzo F, Giovagnoni A, Barile A, Gandolfo N, Miele V. Risk Assessment and Cholangiocarcinoma: Diagnostic Management and Artificial Intelligence. BIOLOGY 2023; 12:biology12020213. [PMID: 36829492 PMCID: PMC9952965 DOI: 10.3390/biology12020213] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/19/2022] [Revised: 01/21/2023] [Accepted: 01/25/2023] [Indexed: 01/31/2023]
Abstract
Intrahepatic cholangiocarcinoma (iCCA) is the second most common primary liver tumor, with a median survival of only 13 months. Surgical resection remains the only curative therapy; however, at first detection, only one-third of patients are at an early enough stage for this approach to be effective, thus rendering early diagnosis as an efficient approach to improving survival. Therefore, the identification of higher-risk patients, whose risk is correlated with genetic and pre-cancerous conditions, and the employment of non-invasive-screening modalities would be appropriate. For several at-risk patients, such as those suffering from primary sclerosing cholangitis or fibropolycystic liver disease, the use of periodic (6-12 months) imaging of the liver by ultrasound (US), magnetic Resonance Imaging (MRI)/cholangiopancreatography (MRCP), or computed tomography (CT) in association with serum CA19-9 measurement has been proposed. For liver cirrhosis patients, it has been proposed that at-risk iCCA patients are monitored in a similar fashion to at-risk HCC patients. The possibility of using Artificial Intelligence models to evaluate higher-risk patients could favor the diagnosis of these entities, although more data are needed to support the practical utility of these applications in the field of screening. For these reasons, it would be appropriate to develop screening programs in the research protocols setting. In fact, the success of these programs reauires patient compliance and multidisciplinary cooperation.
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Affiliation(s)
- Vincenza Granata
- Division of Radiology, Istituto Nazionale Tumori IRCCS Fondazione Pascale—IRCCS di Napoli, 80131 Naples, Italy
| | - Roberta Fusco
- Medical Oncology Division, Igea SpA, 80013 Naples, Italy
- Correspondence:
| | - Federica De Muzio
- Diagnostic Imaging Section, Department of Medical and Surgical Sciences & Neurosciences, University of Molise, 86100 Campobasso, Italy
| | - Carmen Cutolo
- Department of Medicine, Surgery and Dentistry, University of Salerno, 84081 Salerno, Italy
| | - Francesca Grassi
- Division of Radiology, Università degli Studi della Campania Luigi Vanvitelli, 80138 Naples, Italy
| | - Maria Chiara Brunese
- Diagnostic Imaging Section, Department of Medical and Surgical Sciences & Neurosciences, University of Molise, 86100 Campobasso, Italy
| | - Igino Simonetti
- Division of Radiology, Istituto Nazionale Tumori IRCCS Fondazione Pascale—IRCCS di Napoli, 80131 Naples, Italy
| | - Orlando Catalano
- Radiology Unit, Istituto Diagnostico Varelli, Via Cornelia dei Gracchi 65, 80126 Naples, Italy
| | - Michela Gabelloni
- Nuclear Medicine Unit, Department of Translational Research, University of Pisa, 56216 Pisa, Italy
| | - Silvia Pradella
- Department of Radiology, Careggi University Hospital, Largo Brambilla 3, 50134 Florence, Italy
| | - Ginevra Danti
- Department of Radiology, Careggi University Hospital, Largo Brambilla 3, 50134 Florence, Italy
| | - Federica Flammia
- Department of Radiology, Careggi University Hospital, Largo Brambilla 3, 50134 Florence, Italy
| | - Alessandra Borgheresi
- Department of Clinical, Special and Dental Sciences, University Politecnica delle Marche, Via Conca 71, 60126 Ancona, Italy
- Department of Radiology, University Hospital “Azienda Ospedaliera Universitaria delle Marche”, Via Conca 71, 60126 Ancona, Italy
| | - Andrea Agostini
- Department of Clinical, Special and Dental Sciences, University Politecnica delle Marche, Via Conca 71, 60126 Ancona, Italy
- Department of Radiology, University Hospital “Azienda Ospedaliera Universitaria delle Marche”, Via Conca 71, 60126 Ancona, Italy
| | - Federico Bruno
- Department of Applied Clinical Sciences and Biotechnology, University of L’Aquila, Via Vetoio 1, 67100 L’Aquila, Italy
| | - Pierpaolo Palumbo
- Department of Applied Clinical Sciences and Biotechnology, University of L’Aquila, Via Vetoio 1, 67100 L’Aquila, Italy
| | - Alessandro Ottaiano
- SSD Innovative Therapies for Abdominal Metastases, Istituto Nazionale Tumori IRCCS-Fondazione G. Pascale, 80130 Naples, Italy
| | - Francesco Izzo
- Division of Epatobiliary Surgical Oncology, Istituto Nazionale Tumori IRCCS Fondazione Pascale—IRCCS di Napoli, 80131 Naples, Italy
| | - Andrea Giovagnoni
- Department of Clinical, Special and Dental Sciences, University Politecnica delle Marche, Via Conca 71, 60126 Ancona, Italy
- Department of Radiology, University Hospital “Azienda Ospedaliera Universitaria delle Marche”, Via Conca 71, 60126 Ancona, Italy
| | - Antonio Barile
- Department of Applied Clinical Sciences and Biotechnology, University of L’Aquila, Via Vetoio 1, 67100 L’Aquila, Italy
| | - Nicoletta Gandolfo
- Diagnostic Imaging Department, Villa Scassi Hospital-ASL 3, Corso Scassi 1, 16149 Genoa, Italy
- Italian Society of Medical and Interventional Radiology (SIRM), SIRM Foundation, Via della Signora 2, 20122 Milan, Italy
| | - Vittorio Miele
- Department of Radiology, Careggi University Hospital, Largo Brambilla 3, 50134 Florence, Italy
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Granata V, Fusco R, Setola SV, Simonetti I, Picone C, Simeone E, Festino L, Vanella V, Vitale MG, Montanino A, Morabito A, Izzo F, Ascierto PA, Petrillo A. Immunotherapy Assessment: A New Paradigm for Radiologists. Diagnostics (Basel) 2023; 13:diagnostics13020302. [PMID: 36673112 PMCID: PMC9857844 DOI: 10.3390/diagnostics13020302] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2022] [Revised: 12/31/2022] [Accepted: 01/08/2023] [Indexed: 01/14/2023] Open
Abstract
Immunotherapy denotes an exemplar change in an oncological setting. Despite the effective application of these treatments across a broad range of tumors, only a minority of patients have beneficial effects. The efficacy of immunotherapy is affected by several factors, including human immunity, which is strongly correlated to genetic features, such as intra-tumor heterogeneity. Classic imaging assessment, based on computed tomography (CT) or magnetic resonance imaging (MRI), which is useful for conventional treatments, has a limited role in immunotherapy. The reason is due to different patterns of response and/or progression during this kind of treatment which differs from those seen during other treatments, such as the possibility to assess the wide spectrum of immunotherapy-correlated toxic effects (ir-AEs) as soon as possible. In addition, considering the unusual response patterns, the limits of conventional response criteria and the necessity of using related immune-response criteria are clear. Radiomics analysis is a recent field of great interest in a radiological setting and recently it has grown the idea that we could identify patients who will be fit for this treatment or who will develop ir-AEs.
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Affiliation(s)
- Vincenza Granata
- Division of Radiology, Istituto Nazionale Tumori IRCCS Fondazione Pascale—IRCCS di Napoli, 80131 Naples, Italy
- Correspondence:
| | - Roberta Fusco
- Medical Oncology Division, Igea SpA, 80013 Naples, Italy
- Italian Society of Medical and Interventional Radiology (SIRM), SIRM Foundation, 20122 Milan, Italy
| | - Sergio Venanzio Setola
- Division of Radiology, Istituto Nazionale Tumori IRCCS Fondazione Pascale—IRCCS di Napoli, 80131 Naples, Italy
| | - Igino Simonetti
- Division of Radiology, Istituto Nazionale Tumori IRCCS Fondazione Pascale—IRCCS di Napoli, 80131 Naples, Italy
| | - Carmine Picone
- Division of Radiology, Istituto Nazionale Tumori IRCCS Fondazione Pascale—IRCCS di Napoli, 80131 Naples, Italy
| | - Ester Simeone
- Melanoma, Cancer Immunotherapy and Development Therapeutics Unit, Istituto Nazionale Tumori IRCCS Fondazione G. Pascale, 80131 Naples, Italy
| | - Lucia Festino
- Melanoma, Cancer Immunotherapy and Development Therapeutics Unit, Istituto Nazionale Tumori IRCCS Fondazione G. Pascale, 80131 Naples, Italy
| | - Vito Vanella
- Melanoma, Cancer Immunotherapy and Development Therapeutics Unit, Istituto Nazionale Tumori IRCCS Fondazione G. Pascale, 80131 Naples, Italy
| | - Maria Grazia Vitale
- Melanoma, Cancer Immunotherapy and Development Therapeutics Unit, Istituto Nazionale Tumori IRCCS Fondazione G. Pascale, 80131 Naples, Italy
| | - Agnese Montanino
- Thoracic Medical Oncology, Istituto Nazionale Tumori IRCCS Fondazione Pascale—IRCCS di Napoli, 80131 Naples, Italy
| | - Alessandro Morabito
- Thoracic Medical Oncology, Istituto Nazionale Tumori IRCCS Fondazione Pascale—IRCCS di Napoli, 80131 Naples, Italy
| | - Francesco Izzo
- Division of Epatobiliary Surgical Oncology, Istituto Nazionale Tumori IRCCS Fondazione Pascale—IRCCS di Napoli, 80131 Naples, Italy
| | - Paolo Antonio Ascierto
- Italian Society of Medical and Interventional Radiology (SIRM), SIRM Foundation, 20122 Milan, Italy
| | - Antonella Petrillo
- Division of Radiology, Istituto Nazionale Tumori IRCCS Fondazione Pascale—IRCCS di Napoli, 80131 Naples, Italy
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Cutolo C, Fusco R, Simonetti I, De Muzio F, Grassi F, Trovato P, Palumbo P, Bruno F, Maggialetti N, Borgheresi A, Bruno A, Chiti G, Bicci E, Brunese MC, Giovagnoni A, Miele V, Barile A, Izzo F, Granata V. Imaging Features of Main Hepatic Resections: The Radiologist Challenging. J Pers Med 2023; 13:jpm13010134. [PMID: 36675795 PMCID: PMC9862253 DOI: 10.3390/jpm13010134] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2022] [Revised: 12/31/2022] [Accepted: 01/06/2023] [Indexed: 01/12/2023] Open
Abstract
Liver resection is still the most effective treatment of primary liver malignancies, including hepatocellular carcinoma (HCC) and cholangiocarcinoma (CCA), and of metastatic disease, such as colorectal liver metastases. The type of liver resection (anatomic versus non anatomic resection) depends on different features, mainly on the type of malignancy (primary liver neoplasm versus metastatic lesion), size of tumor, its relation with blood and biliary vessels, and the volume of future liver remnant (FLT). Imaging plays a critical role in postoperative assessment, offering the possibility to recognize normal postoperative findings and potential complications. Ultrasonography (US) is the first-line diagnostic tool to use in post-surgical phase. However, computed tomography (CT), due to its comprehensive assessment, allows for a more accurate evaluation and more normal findings than the possible postoperative complications. Magnetic resonance imaging (MRI) with cholangiopancreatography (MRCP) and/or hepatospecific contrast agents remains the best tool for bile duct injuries diagnosis and for ischemic cholangitis evaluation. Consequently, radiologists should be familiar with the surgical approaches for a better comprehension of normal postoperative findings and of postoperative complications.
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Affiliation(s)
- Carmen Cutolo
- Department of Medicine, Surgery and Dentistry, University of Salerno, 84084 Salerno, Italy
| | - Roberta Fusco
- Medical Oncology Division, Igea SpA, 80013 Napoli, Italy
- Correspondence:
| | - Igino Simonetti
- Division of Radiology, Istituto Nazionale Tumori IRCCS Fondazione Pascale—IRCCS di Napoli, 80131 Naples, Italy
| | - Federica De Muzio
- Department of Medicine and Health Sciences “V. Tiberio”, University of Molise, 86100 Campobasso, Italy
| | - Francesca Grassi
- Division of Radiology, Università degli Studi della Campania Luigi Vanvitelli, 80127 Naples, Italy
| | - Piero Trovato
- Division of Radiology, Istituto Nazionale Tumori IRCCS Fondazione Pascale—IRCCS di Napoli, 80131 Naples, Italy
| | - Pierpaolo Palumbo
- Department of Diagnostic Imaging, Area of Cardiovascular and Interventional Imaging, Abruzzo Health Unit 1, 67100 L’Aquila, Italy
- Italian Society of Medical and Interventional Radiology (SIRM), SIRM Foundation, Via della Signora 2, 20122 Milan, Italy
| | - Federico Bruno
- Department of Diagnostic Imaging, Area of Cardiovascular and Interventional Imaging, Abruzzo Health Unit 1, 67100 L’Aquila, Italy
- Italian Society of Medical and Interventional Radiology (SIRM), SIRM Foundation, Via della Signora 2, 20122 Milan, Italy
| | - Nicola Maggialetti
- Department of Medical Science, Neuroscience and Sensory Organs (DSMBNOS), University of Bari “Aldo Moro”, 70124 Bari, Italy
| | - Alessandra Borgheresi
- Department of Radiology, University Hospital “Azienda Ospedaliera Universitaria delle Marche”, Via Conca 71, 60126 Ancona, Italy
- Department of Clinical, Special and Dental Sciences, University Politecnica delle Marche, Via Conca 71, 60126 Ancona, Italy
| | - Alessandra Bruno
- Department of Radiology, University Hospital “Azienda Ospedaliera Universitaria delle Marche”, Via Conca 71, 60126 Ancona, Italy
- Department of Clinical, Special and Dental Sciences, University Politecnica delle Marche, Via Conca 71, 60126 Ancona, Italy
| | - Giuditta Chiti
- Italian Society of Medical and Interventional Radiology (SIRM), SIRM Foundation, Via della Signora 2, 20122 Milan, Italy
- Department of Emergency Radiology, University Hospital Careggi, Largo Brambilla 3, 50134 Florence, Italy
| | - Eleonora Bicci
- Italian Society of Medical and Interventional Radiology (SIRM), SIRM Foundation, Via della Signora 2, 20122 Milan, Italy
- Department of Emergency Radiology, University Hospital Careggi, Largo Brambilla 3, 50134 Florence, Italy
| | - Maria Chiara Brunese
- Department of Medicine and Health Sciences “V. Tiberio”, University of Molise, 86100 Campobasso, Italy
| | - Andrea Giovagnoni
- Department of Radiology, University Hospital “Azienda Ospedaliera Universitaria delle Marche”, Via Conca 71, 60126 Ancona, Italy
- Department of Clinical, Special and Dental Sciences, University Politecnica delle Marche, Via Conca 71, 60126 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, University Hospital Careggi, Largo Brambilla 3, 50134 Florence, Italy
| | - Antonio Barile
- Department of Applied Clinical Sciences and Biotechnology, University of L’Aquila, 67100 L’Aquila, Italy
| | - Francesco Izzo
- Division of Epatobiliary Surgical Oncology, Istituto Nazionale Tumori IRCCS Fondazione Pascale—IRCCS di Napoli, 80131 Naples, Italy
| | - Vincenza Granata
- Division of Radiology, Istituto Nazionale Tumori IRCCS Fondazione Pascale—IRCCS di Napoli, 80131 Naples, Italy
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Sansone M, Fusco R, Grassi F, Gatta G, Belfiore MP, Angelone F, Ricciardi C, Ponsiglione AM, Amato F, Galdiero R, Grassi R, Granata V, Grassi R. Machine Learning Approaches with Textural Features to Calculate Breast Density on Mammography. Curr Oncol 2023; 30:839-853. [PMID: 36661713 PMCID: PMC9858566 DOI: 10.3390/curroncol30010064] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2022] [Revised: 12/31/2022] [Accepted: 01/06/2023] [Indexed: 01/11/2023] Open
Abstract
BACKGROUND breast cancer (BC) is the world's most prevalent cancer in the female population, with 2.3 million new cases diagnosed worldwide in 2020. The great efforts made to set screening campaigns, early detection programs, and increasingly targeted treatments led to significant improvement in patients' survival. The Full-Field Digital Mammograph (FFDM) is considered the gold standard method for the early diagnosis of BC. From several previous studies, it has emerged that breast density (BD) is a risk factor in the development of BC, affecting the periodicity of screening plans present today at an international level. OBJECTIVE in this study, the focus is the development of mammographic image processing techniques that allow the extraction of indicators derived from textural patterns of the mammary parenchyma indicative of BD risk factors. METHODS a total of 168 patients were enrolled in the internal training and test set while a total of 51 patients were enrolled to compose the external validation cohort. Different Machine Learning (ML) techniques have been employed to classify breasts based on the values of the tissue density. Textural features were extracted only from breast parenchyma with which to train classifiers, thanks to the aid of ML algorithms. RESULTS the accuracy of different tested classifiers varied between 74.15% and 93.55%. The best results were reached by a Support Vector Machine (accuracy of 93.55% and a percentage of true positives and negatives equal to TPP = 94.44% and TNP = 92.31%). The best accuracy was not influenced by the choice of the features selection approach. Considering the external validation cohort, the SVM, as the best classifier with the 7 features selected by a wrapper method, showed an accuracy of 0.95, a sensitivity of 0.96, and a specificity of 0.90. CONCLUSIONS our preliminary results showed that the Radiomics analysis and ML approach allow us to objectively identify BD.
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Affiliation(s)
- Mario Sansone
- Department of Electrical Engineering Information Technology, University of Naples Federico II, 80125 Naples, Italy
| | - Roberta Fusco
- Medical Oncology Division, Igea SpA, 80013 Napoli, Italy
| | - Francesca Grassi
- Department of Precision Medicine, Division of Radiology, University of Campania Luigi Vanvitelli, 80127 Naples, Italy
- Italian Society of Medical and Interventional Radiology (SIRM), SIRM Foundation, 20122 Milan, Italy
| | - Gianluca Gatta
- Department of Precision Medicine, Division of Radiology, University of Campania Luigi Vanvitelli, 80127 Naples, Italy
| | - Maria Paola Belfiore
- Department of Precision Medicine, Division of Radiology, University of Campania Luigi Vanvitelli, 80127 Naples, Italy
| | - Francesca Angelone
- Department of Electrical Engineering Information Technology, University of Naples Federico II, 80125 Naples, Italy
| | - Carlo Ricciardi
- Department of Electrical Engineering Information Technology, University of Naples Federico II, 80125 Naples, Italy
| | - Alfonso Maria Ponsiglione
- Department of Electrical Engineering Information Technology, University of Naples Federico II, 80125 Naples, Italy
| | - Francesco Amato
- Department of Electrical Engineering Information Technology, University of Naples Federico II, 80125 Naples, Italy
| | - Roberta Galdiero
- Division of Radiology, Istituto Nazionale Tumori IRCCS Fondazione Pascale—IRCCS di Napoli, 80131 Naples, Italy
| | - Roberta Grassi
- Department of Precision Medicine, Division of Radiology, University of Campania Luigi Vanvitelli, 80127 Naples, Italy
| | - Vincenza Granata
- Division of Radiology, Istituto Nazionale Tumori IRCCS Fondazione Pascale—IRCCS di Napoli, 80131 Naples, Italy
| | - Roberto Grassi
- Department of Precision Medicine, Division of Radiology, University of Campania Luigi Vanvitelli, 80127 Naples, Italy
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Granata V, Fusco R, D’Alessio V, Simonetti I, Grassi F, Silvestro L, Palaia R, Belli A, Patrone R, Piccirillo M, Izzo F. Percutanous Electrochemotherapy (ECT) in Primary and Secondary Liver Malignancies: A Systematic Review. Diagnostics (Basel) 2023; 13:diagnostics13020209. [PMID: 36673019 PMCID: PMC9858594 DOI: 10.3390/diagnostics13020209] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2022] [Revised: 12/29/2022] [Accepted: 12/31/2022] [Indexed: 01/09/2023] Open
Abstract
The aim of the study was to analyse papers describing the use of Electrochemotherapy (ECT) in local treatment of primary and secondary liver tumours located at different sites and with different histologies. Other Local Ablative Therapies (LAT) are also discussed. Analyses of these papers demonstrate that ECT use is safe and effective in lesions of large size, independently of the histology of the treated lesions. ECT performed better than other thermal ablation techniques in lesions > 6 cm in size and can be safely used to treat lesions distant, close, or adjacent to vital structures. ECT spares vessel and bile ducts, is repeatable, and can be performed between chemotherapeutic cycles. ECT can fill the gap in local ablative therapies due to being lesions too large or localized in highly challenging anatomical sites.
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Affiliation(s)
- Vincenza Granata
- Division of Radiology, Istituto Nazionale Tumori IRCCS Fondazione Pascale—IRCCS di Napoli, 80131 Naples, Italy
| | - Roberta Fusco
- Oncology Medical and Research & Development Division, Casalnuovo di Napoli, 80013 Naples, Italy
| | - Valeria D’Alessio
- Oncology Medical and Research & Development Division, Casalnuovo di Napoli, 80013 Naples, Italy
- Correspondence:
| | - Igino Simonetti
- Division of Radiology, Istituto Nazionale Tumori IRCCS Fondazione Pascale—IRCCS di Napoli, 80131 Naples, Italy
| | - Francesca Grassi
- Division of Radiology, Università degli Studi della Campania Luigi Vanvitelli, 80127 Naples, Italy
| | - Lucrezia Silvestro
- Division of Clinical Experimental Oncology Abdomen, Istituto Nazionale Tumori IRCCS Fondazione Pascale—IRCCS di Napoli, 80131 Naples, Italy
| | - Raffaele Palaia
- Division of Epatobiliary Surgical Oncology, Istituto Nazionale Tumori IRCCS Fondazione Pascale—IRCCS di Napoli, 80131 Naples, Italy
| | - Andrea Belli
- Division of Epatobiliary Surgical Oncology, Istituto Nazionale Tumori IRCCS Fondazione Pascale—IRCCS di Napoli, 80131 Naples, Italy
| | - Renato Patrone
- Division of Epatobiliary Surgical Oncology, Istituto Nazionale Tumori IRCCS Fondazione Pascale—IRCCS di Napoli, 80131 Naples, Italy
| | - Mauro Piccirillo
- Division of Epatobiliary Surgical Oncology, Istituto Nazionale Tumori IRCCS Fondazione Pascale—IRCCS di Napoli, 80131 Naples, Italy
| | - Francesco Izzo
- Division of Epatobiliary Surgical Oncology, Istituto Nazionale Tumori IRCCS Fondazione Pascale—IRCCS di Napoli, 80131 Naples, Italy
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12
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Risk Assessment and Pancreatic Cancer: Diagnostic Management and Artificial Intelligence. Cancers (Basel) 2023; 15:cancers15020351. [PMID: 36672301 PMCID: PMC9857317 DOI: 10.3390/cancers15020351] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2022] [Revised: 12/30/2022] [Accepted: 01/03/2023] [Indexed: 01/06/2023] Open
Abstract
Pancreatic cancer (PC) is one of the deadliest cancers, and it is responsible for a number of deaths almost equal to its incidence. The high mortality rate is correlated with several explanations; the main one is the late disease stage at which the majority of patients are diagnosed. Since surgical resection has been recognised as the only curative treatment, a PC diagnosis at the initial stage is believed the main tool to improve survival. Therefore, patient stratification according to familial and genetic risk and the creation of screening protocol by using minimally invasive diagnostic tools would be appropriate. Pancreatic cystic neoplasms (PCNs) are subsets of lesions which deserve special management to avoid overtreatment. The current PC screening programs are based on the annual employment of magnetic resonance imaging with cholangiopancreatography sequences (MR/MRCP) and/or endoscopic ultrasonography (EUS). For patients unfit for MRI, computed tomography (CT) could be proposed, although CT results in lower detection rates, compared to MRI, for small lesions. The actual major limit is the incapacity to detect and characterize the pancreatic intraepithelial neoplasia (PanIN) by EUS and MR/MRCP. The possibility of utilizing artificial intelligence models to evaluate higher-risk patients could favour the diagnosis of these entities, although more data are needed to support the real utility of these applications in the field of screening. For these motives, it would be appropriate to realize screening programs in research settings.
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Momin S, Lei Y, McCall NS, Zhang J, Roper J, Harms J, Tian S, Lloyd MS, Liu T, Bradley JD, Higgins K, Yang X. Mutual enhancing learning-based automatic segmentation of CT cardiac substructure. Phys Med Biol 2022; 67. [PMID: 35447610 PMCID: PMC9148580 DOI: 10.1088/1361-6560/ac692d] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2021] [Accepted: 04/21/2022] [Indexed: 11/12/2022]
Abstract
Abstract
Objective. Current segmentation practice for thoracic cancer RT considers the whole heart as a single organ despite increased risks of cardiac toxicities from irradiation of specific cardiac substructures. Segmenting up to 15 different cardiac substructures can be a very time-intensive process, especially due to their different volume sizes and anatomical variations amongst different patients. In this work, a new deep learning (DL)-based mutual enhancing strategy is introduced for accurate and automatic segmentation, especially of smaller substructures such as coronary arteries. Approach. Our proposed method consists of three subnetworks: retina U-net, classification module, and segmentation module. Retina U-net is used as a backbone network architecture that aims to learn deep features from the whole heart. Whole heart feature maps from retina U-net are then transferred to four different sets of classification modules to generate classification localization maps of coronary arteries, great vessels, chambers of the heart, and valves of the heart. Each classification module is in sync with its corresponding subsequent segmentation module in a bootstrapping manner, allowing them to share their encoding paths to generate a mutual enhancing strategy. We evaluated our method on three different datasets: institutional CT datasets (55 subjects) 2) publicly available Multi-Modality Whole Heart Segmentation (MM-WHS) challenge datasets (120 subjects), and Automated Cardiac Diagnosis Challenge (ACDC) datasets (100 subjects). For institutional datasets, we performed five-fold cross-validation on training data (45 subjects) and performed inference on separate hold-out data (10 subjects). For each subject, 15 cardiac substructures were manually contoured by a resident physician and evaluated by an attending radiation oncologist. For the MM-WHS dataset, we trained the network on 100 datasets and performed an inference on a separate hold-out dataset with 20 subjects, each with 7 cardiac substructures. For ACDC datasets, we performed five-fold cross-validation on 100 datasets, each with 3 cardiac substructures. We compared the proposed method against four different network architectures: 3D U-net, mask R-CNN, mask scoring R-CNN, and proposed network without classification module. Segmentation accuracies were statistically compared through dice similarity coefficient, Jaccard, 95% Hausdorff distance, mean surface distance, root mean square distance, center of mass distance, and volume difference. Main results. The proposed method generated cardiac substructure segmentations with significantly higher accuracy (P < 0.05) for small substructures, especially for coronary arteries such as left anterior descending artery (CA-LADA) and right coronary artery (CA-RCA) in comparison to four competing methods. For large substructures (i.e. chambers of the heart), our method yielded comparable results to mask scoring R-CNN method, resulting in significantly (P < 0.05) improved segmentation accuracy in comparison to 3D U-net and mask R-CNN. Significance. A new DL-based mutual enhancing strategy was introduced for automatic segmentation of cardiac substructures. Overall results of this work demonstrate the ability of the proposed method to improve segmentation accuracies of smaller substructures such as coronary arteries without largely compromising the segmentation accuracies of larger substructures. Fast and accurate segmentations of up to 15 substructures can possibly be used as a tool to rapidly generate substructure segmentations followed by physicians’ reviews to improve clinical workflow.
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Chau OW, Fakir H, Lock M, Dinniwell R, Perera F, Erickson A, Gaede S. Dosimetric Planning Comparison for Left-Sided Breast Cancer Radiotherapy: The Clinical Feasibility of Four-Dimensional-Computed Tomography-Based Treatment Planning Optimization. Cureus 2022; 14:e24777. [PMID: 35673303 PMCID: PMC9165918 DOI: 10.7759/cureus.24777] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/06/2022] [Indexed: 11/30/2022] Open
Abstract
Background: Adjuvant whole-breast radiotherapy (RT) is a significant part of the standard of care treatment after breast cancer (BC) conserving surgery. Modern techniques including intensity-modulated radiation therapy (IMRT) and volumetric-modulated arc therapy (VMAT) have constituted to better target coverage and critical organs sparing. However, BC survivors are at risk of developing radiation-induced cardiac toxicity. Hence, deep-inspiration breath-hold (DIBH) techniques have been implemented at many centers to further reduce cardiac exposure but require compliance. 4D-CT robust optimization can account for heart intrafractional motion per breathing phase. The optimization has been explored in cardiac sparing of breast IMRT compared to DIBH in a small sample size but has not been evaluated in substructures sparing, nor in VMAT. To provide patients who are not compliant to breath-hold with an optimal treatment approach, various heart sparing techniques need to be evaluated for statistical significance and clinical feasibility. Aim: This retrospective study aimed to provide an extensive dosimetric heart sparing comparison of free-breathing, 4D-CT-based treatment planning, including robust optimization with DIBH-based treatment planning. Combinations of forward and inverse IMRT and VMAT are also considered. Methods: Fifteen early stage left-sided BC standard treatment plans were selected. Breast, lung, left anterior descending artery (LAD), left ventricle (LV), and the whole heart were contoured on each 4D-CT phase and DIBH CT dataset. Each treatment plan was optimized using forward/inverse IMRT and VMAT on the following CT datasets: DIBH, average 4D-CT, and the complete 4D-CT dataset needed for robust optimization. Dose-volume histograms were used to compare V5GyHeart, mean heart dose, mean and max LAD dose, mean LV dose, and V50%Lung. Results: All RT techniques assessed including 4D robust optimization were clinically feasible. Statistically significant differences in mean heart, LAD and LV dose, max LAD dose, and V5GyHeart (p < 0.01) but no difference in V50%Lung (p = 0.29) were found between different techniques. IMRT DIBH achieved the optimal cardiac and substructure sparing among treatment plans. 4D robust IMRT had significantly greater mean heart and LV dose than DIBH IMRT (p ≤ 0.01), except LAD dose. Among free-breathing methods, no difference in all cardiac and substructure dose parameters was observed (p > 0.2) in comparing forward and inverse IMRT with average 4D-CT, inverse average 4D-CT, and 4D robust with IMRT, and between average 4D-CT VMAT and 4D robust VMAT. Only V5GyHeart and mean LV dose were significantly greater in 4D robust VMAT (p < 0.01) compared to DIBH VMAT. Mean heart and LV doses were significantly reduced (p < 0.01) in DIBH IMRT compared to DIBH VMAT. Moreover, mean heart and LV dose, V5GyHeart were significantly reduced in inverse IMRT average 4D-CT compared to average 4D-CT VMAT (p < 0.02) and in 4D robust IMRT compared to 4D robust VMAT (p < 0.04). Conclusion: This study demonstrated the clinical feasibility of 4D robust optimization in limiting the cardiac and substructures dose during free-breathing RT with both IMRT/VMAT for patients who are not compliant with breath-hold RT. However, this study also presents that 4D robust optimization can reduce LAD dose but not fully outperform DIBH or conventional 4D-CT-based planning with IMRT/VMAT in heart sparing in treating early staged left-sided BC patients.
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15
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Albano D, Benenati M, Bruno A, Bruno F, Calandri M, Caruso D, Cozzi D, De Robertis R, Gentili F, Grazzini I, Micci G, Palmisano A, Pessina C, Scalise P, Vernuccio F, Barile A, Miele V, Grassi R, Messina C. Imaging side effects and complications of chemotherapy and radiation therapy: a pictorial review from head to toe. Insights Imaging 2021; 12:76. [PMID: 34114094 PMCID: PMC8192650 DOI: 10.1186/s13244-021-01017-2] [Citation(s) in RCA: 37] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2021] [Accepted: 05/18/2021] [Indexed: 02/08/2023] Open
Abstract
Newer biologic drugs and immunomodulatory agents, as well as more tolerated and effective radiation therapy schemes, have reduced treatment toxicity in oncology patients. However, although imaging assessment of tumor response is adapting to atypical responses like tumor flare, expected changes and complications of chemo/radiotherapy are still routinely encountered in post-treatment imaging examinations. Radiologists must be aware of old and newer therapeutic options and related side effects or complications to avoid a misinterpretation of imaging findings. Further, advancements in oncology research have increased life expectancy of patients as well as the frequency of long-term therapy-related side effects that once could not be observed. This pictorial will help radiologists tasked to detect therapy-related complications and to differentiate expected changes of normal tissues from tumor relapse.
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Affiliation(s)
- Domenico Albano
- IRCCS Istituto Ortopedico Galeazzi, Via Riccardo Galeazzi 4, 20161, Milan, Italy. .,Sezione di Scienze Radiologiche, Dipartimento di Biomedicina, Neuroscienze e Diagnostica Avanzata, Università Degli Studi di Palermo, Via del Vespro 127, 90127, Palermo, Italy. .,Italian Society of Medical and Interventional Radiology (SIRM), SIRM Foundation, Via della Signora 2, 20122, Milan, Italy.
| | - Massimo Benenati
- Italian Society of Medical and Interventional Radiology (SIRM), SIRM Foundation, Via della Signora 2, 20122, Milan, Italy.,Dipartimento di Diagnostica per Immagini, Radioterapia, Oncologia ed Ematologia, Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy
| | - Antonio Bruno
- Diagnostic and Interventional Radiology Unit, Maggiore Hospital "C. A. Pizzardi", 40133, Bologna, Italy
| | - Federico Bruno
- Italian Society of Medical and Interventional Radiology (SIRM), SIRM Foundation, Via della Signora 2, 20122, Milan, Italy.,Department of Biotechnology and Applied Clinical Sciences, University of L'Aquila, 67100, L'Aquila, Italy
| | - Marco Calandri
- Radiology Unit, A.O.U. San Luigi Gonzaga di Orbassano, Department of Oncology, University of Torino, 10043, Turin, Italy
| | - Damiano Caruso
- Department of Surgical and Medical Sciences and Translational Medicine, Sapienza University of Rome - Sant'Andrea University Hospital, Via di Grottarossa, 1035-1039, 00189, Rome, Italy
| | - Diletta Cozzi
- Italian Society of Medical and Interventional Radiology (SIRM), SIRM Foundation, Via della Signora 2, 20122, Milan, Italy.,Department of Emergency Radiology, University Hospital Careggi, Largo Brambilla 3, 50123, Florence, Italy
| | - Riccardo De Robertis
- U.O.C. Radiologia BT, Ospedale Civile Maggiore - Azienda Ospedaliera Universitaria Integrata Verona, Piazzale A. Stefani 1, 37126, Verona, Italy
| | - Francesco Gentili
- Unit of Diagnostic Imaging, Department of Radiological Sciences, University of Siena, Azienda Ospedaliero-Universitaria Senese, Siena, Italy
| | - Irene Grazzini
- Department of Radiology, Section of Neuroradiology, San Donato Hospital, Arezzo, Italy
| | - Giuseppe Micci
- Sezione di Scienze Radiologiche, Dipartimento di Biomedicina, Neuroscienze e Diagnostica Avanzata, Università Degli Studi di Palermo, Via del Vespro 127, 90127, Palermo, Italy.,Italian Society of Medical and Interventional Radiology (SIRM), SIRM Foundation, Via della Signora 2, 20122, Milan, Italy
| | - Anna Palmisano
- Experimental Imaging Centre, Radiology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy.,School of Medicine, Vita-Salute San Raffaele University, via Olgettina 58, 20132, Milan, Italy
| | - Carlotta Pessina
- Department of Radiology, University of Brescia, Piazzale Spedali Civili 1, 25123, Brescia, Italy
| | - Paola Scalise
- Department of Diagnostic Imaging, Pisa University Hospital, Via Paradisa 2, 56124, Pisa, Italy
| | - Federica Vernuccio
- Sezione di Scienze Radiologiche, Dipartimento di Biomedicina, Neuroscienze e Diagnostica Avanzata, Università Degli Studi di Palermo, Via del Vespro 127, 90127, Palermo, Italy
| | - Antonio Barile
- Department of Biotechnology and Applied Clinical Sciences, University of L'Aquila, 67100, L'Aquila, Italy
| | - Vittorio Miele
- Department of Emergency Radiology, University Hospital Careggi, Largo Brambilla 3, 50123, Florence, Italy
| | - Roberto Grassi
- Italian Society of Medical and Interventional Radiology (SIRM), SIRM Foundation, Via della Signora 2, 20122, Milan, Italy.,Department of Precision Medicine, University of Campania "L. Vanvitelli", 80138, Naples, Italy
| | - Carmelo Messina
- IRCCS Istituto Ortopedico Galeazzi, Via Riccardo Galeazzi 4, 20161, Milan, Italy
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