Review
Medicine, General & Internal
Dan Zheng, Xiujing He, Jing Jing
Summary: The heavy burden and mortality of breast cancer highlight the importance of early diagnosis and treatment. Imaging detection is a key tool in clinical practice for breast cancer screening, diagnosis, and treatment evaluation. The use of AI-assisted imaging diagnosis can improve efficiency and accuracy in recognizing, segmenting, and diagnosing tumor lesions.
JOURNAL OF CLINICAL MEDICINE
(2023)
Article
Oncology
Mitchell Chen, Susan J. Copley, Patrizia Viola, Haonan Lu, Eric O. Aboagye
Summary: Lung cancer, the leading cause of cancer-related deaths worldwide, can be captured non-invasively on medical imaging as radiomic features, which can be used in an artificial intelligence paradigm to predict clinical outcomes and improve patient care. Compared to tissue sampling-driven approaches, radiomics-based methods are superior for being non-invasive, reproducible, cheaper, and less susceptible to intra-tumoral heterogeneity.
SEMINARS IN CANCER BIOLOGY
(2023)
Article
Oncology
Enrico Capobianco
Summary: The use of Artificial Intelligence and Machine Learning in cancer research has the potential to enhance information processing capabilities and improve the accuracy of clinical decision-making. However, challenges such as generating interpretable model results and designing automated clinical decision processes still need to be addressed in this field.
BRITISH JOURNAL OF CANCER
(2022)
Review
Oncology
Ahmad Chaddad, Michael J. Kucharczyk, Abbas Cheddad, Sharon E. Clarke, Lama Hassan, Shuxue Ding, Saima Rathore, Mingli Zhang, Yousef Katib, Boris Bahoric, Gad Abikhzer, Stephan Probst, Tamim Niazi
Summary: The use of artificial intelligence in medical imaging analysis, specifically radiomic models, is gaining increasing attention. This study explores the application of magnetic resonance imaging-based radiomics models in evaluating prostate cancer and discusses future directions. It highlights the potential of deep radiomics analysis and the need for multi-institutional collaboration for clinical translation.
Review
Gastroenterology & Hepatology
Arnaldo Stanzione, Francesco Verde, Valeria Romeo, Francesca Boccadifuoco, Pier Paolo Mainenti, Simone Maurea
Summary: Rectal cancer is a common tumor with significant morbidity and mortality rates. Medical imaging, particularly using artificial intelligence, plays a crucial role in diagnosis and treatment, offering promising results but facing challenges in clinical translation.
WORLD JOURNAL OF GASTROENTEROLOGY
(2021)
Article
Radiology, Nuclear Medicine & Medical Imaging
Giuseppe Corrias, Giulio Micheletti, Luigi Barberini, Jasjit S. Suri, Luca Saba
Summary: Texture analysis and radiomics are tools used to explore the amount of data in images. Texture analysis extracts features to uncover disease characteristics, while radiomics extracts quantitative data from medical images to correlate with clinical outcomes. In recent years, these methods have been widely used in various fields, providing clinical radiologists with tools for data processing and identifying important papers.
EUROPEAN JOURNAL OF RADIOLOGY
(2022)
Article
Oncology
Anna-Katharina Meissner, Robin Gutsche, Norbert Galldiks, Martin Kocher, Stephanie T. Juenger, Marie-Lisa Eich, Manuel Montesinos-Rongen, Anna Brunn, Martina Deckert, Christina Wendl, Wolfgang Dietmaier, Roland Goldbrunner, Maximilian Ruge, Cornelia Mauch, Nils-Ole Schmidt, Martin Proescholdt, Stefan Grau, Philipp Lohmann
Summary: MRI radiomics can predict the intracranial BRAF V600E mutation status in patients with melanoma brain metastases noninvasively, and the method shows high diagnostic performance.
Article
Biology
Maria Aymerich, Alejandra Garcia-Baizan, Paolo Niccolo Franco, Milagros Otero-Garcia
Summary: This study investigates the use of radiomic features and machine learning models to differentiate between chromophobe renal cell carcinomas (chRCCs) and renal oncocytomas (ROs). Three-dimensional segmentations of the lesions were performed and radiomic features were extracted. Logistic regression (LR) was found to be the best model, achieving an 83% precision.
Review
Oncology
Ming Zhu, Sijia Li, Yu Kuang, Virginia B. B. Hill, Amy B. B. Heimberger, Lijie Zhai, Shengjie Zhai
Summary: Radiological imaging techniques, including MRI and PET, are widely used in neuro-oncology, but accurate interpretation of the data is challenging due to indistinguishable features shared by different pathological changes. Machine learning technology has been applied in medical image processing and bioinformatics, but still faces hurdles in neuro-oncological radiomic analysis.
FRONTIERS IN ONCOLOGY
(2022)
Article
Medical Informatics
Lili Feng, Zhenyu Liu, Chaofeng Li, Zhenhui Li, Xiaoying Lou, Lizhi Shao, Yunlong Wang, Yan Huang, Haiyang Chen, Xiaolin Pang, Shuai Liu, Fang He, Jian Zheng, Xiaochun Meng, Peiyi Xie, Guanyu Yang, Yi Ding, Mingbiao Wei, Jingping Yun, Mien-Chie Hung, Weihua Zhou, Dantel R. Wahl, Ping Lan, Jie Tian, Xiangbo Wan
Summary: Accurate prediction of pathological complete response to neoadjuvant chemoradiotherapy for locally advanced rectal cancer was achieved using an artificial intelligence radiopathomics integrated model based on pretreatment MRI and H&E-stained biopsy slides. The model, RAPIDS, showed high accuracy and outperformed single-modality prediction models, providing a novel tool for individualized management of locally advanced rectal cancer.
LANCET DIGITAL HEALTH
(2022)
Review
Medicine, General & Internal
Elizabeth von Ende, Sean Ryan, Matthew A. Crain, Mina S. Makary
Summary: Artificial intelligence (AI) uses computer algorithms to process and interpret data, while continuously redefining itself. Machine learning, a subset of AI, evaluates and extracts data from labeled examples. AI can extract complex, high-level data from unlabeled datasets and emulate or exceed human brain capabilities. In the field of radiology, AI innovations have revolutionized diagnostic radiology and hold significant potential for further growth, especially when incorporated into other technologies like augmented reality and radiogenomics.
Article
Biology
Francesco Lorenzo Serafini, Paola Lanuti, Andrea Delli Pizzi, Luca Procaccini, Michela Villani, Alessio Lino Taraschi, Luca Pascucci, Erica Mincuzzi, Jacopo Izzi, Piero Chiacchiaretta, Davide Buca, Giulia Catitti, Giuseppina Bologna, Pasquale Simeone, Damiana Pieragostino, Massimo Caulo
Summary: Modern diagnostic technologies continue to advance, providing more possibilities for early detection and optimal treatment of diseases. Collaboration and integration among different fields such as radiology, flow cytometry, omics sciences, and artificial intelligence may lead to more effective disease diagnosis and treatment methods.
Article
Biochemistry & Molecular Biology
Jacobo Porto-Alvarez, Eva Cernadas, Rebeca Aldaz Martinez, Manuel Fernandez-Delgado, Emilio Huelga Zapico, Victor Gonzalez-Castro, Sandra Baleato-Gonzalez, Roberto Garcia-Figueiras, J. Ramon Antunez-Lopez, Miguel Souto-Bayarri
Summary: This article aims to prove that CT-based radiomics can predict KRAS mutation in CRC patients. The study used 56 CRC patients from the Hospital of Santiago de Compostela in Spain and obtained radiomics features through abdominal contrast enhancement CT. The results showed that AdaBoost ensemble on clinical patient data had the most reliable prediction ability, with a kappa and accuracy of 53.7% and 76.8% for KRAS mutation.
Review
Radiology, Nuclear Medicine & Medical Imaging
Salvatore Gitto, Renato Cuocolo, Domenico Albano, Francesco Morelli, Lorenzo Carlo Pescatori, Carmelo Messina, Massimo Imbriaco, Luca Maria Sconfienza
Summary: This study systematically reviewed radiomic feature reproducibility and predictive model validation strategies in studies dealing with CT and MRI radiomics of bone and soft-tissue sarcomas. The findings showed variations in approaches among studies, with some including feature reproducibility analysis, utilizing machine learning validation techniques for model development, and conducting clinical validation.
INSIGHTS INTO IMAGING
(2021)
Review
Radiology, Nuclear Medicine & Medical Imaging
Guangyao Wu, Arthur Jochems, Turkey Refaee, Abdalla Ibrahim, Chenggong Yan, Sebastian Sanduleanu, Henry C. Woodruff, Philippe Lambin
Summary: Radiomics plays a crucial role in the detection, diagnosis, and prediction of lung cancer, covering pathology, gene mutation, treatment strategy, follow-up, treatment response evaluation, and prognosis. However, challenges such as limited large datasets, methodology standardization, the black-box nature of deep learning, and reproducibility need to be addressed for the clinical implementation of radiomics. Future directions include developing a safer and more efficient model training mode, merging multi-modality images, and combining multi-discipline or multi-omics to form Medomics.
EUROPEAN JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING
(2021)
Letter
Radiology, Nuclear Medicine & Medical Imaging
Valerio Nardone, Alfonso Reginelli, Giuseppina De Marco, Teresa Di Pietro, Roberta Grassi, Carminia Maria Della Corte, Morena Fasano, Patrizia Ciammella, Giovanni Vicidomini, Floriana Morgillo, Fortunato Ciardiello, Salvatore Cappabianca
EUROPEAN JOURNAL OF RADIOLOGY
(2022)
Article
Radiology, Nuclear Medicine & Medical Imaging
Vincenza Granata, Lorenzo Faggioni, Roberta Grassi, Roberta Fusco, Alfonso Reginelli, Daniela Rega, Nicola Maggialetti, Duccio Buccicardi, Barbara Frittoli, Marco Rengo, Chandra Bortolotto, Roberto Prost, Giorgia Viola Lacasella, Marco Montella, Eleonora Ciaghi, Francesco Bellifemine, Federica De Muzio, Giulia Grazzini, Massimo De Filippo, Salvatore Cappabianca, Andrea Laghi, Roberto Grassi, Luca Brunese, Emanuele Neri, Vittorio Miele, Francesca Coppola
Summary: The study aimed to build structured CT-based reports in colon cancer to enhance communication among radiologists, multidisciplinary teams, and patients. By using a panel of expert radiologists and a modified Delphi process, the final structured report included 63 items and received high ratings.
Article
Radiology, Nuclear Medicine & Medical Imaging
Roberta Fusco, Vincenza Granata, Giulia Grazzini, Silvia Pradella, Alessandra Borgheresi, Alessandra Bruno, Pierpaolo Palumbo, Federico Bruno, Roberta Grassi, Andrea Giovagnoni, Roberto Grassi, Vittorio Miele, Antonio Barile
Summary: Radiomics is a technique that extracts quantitative data from medical images, showing great potential. However, there are some current issues such as poor standardization and generalization of results, data quality control, repeatability, and reproducibility.
JAPANESE JOURNAL OF RADIOLOGY
(2022)
Review
Medicine, General & Internal
Marysol Biondi, Eleonora Bicci, Ginevra Danti, Federica Flammia, Giuditta Chiti, Pierpaolo Palumbo, Federico Bruno, Alessandra Borgheresi, Roberta Grassi, Francesca Grassi, Roberta Fusco, Vincenza Granata, Andrea Giovagnoni, Antonio Barile, Vittorio Miele
Summary: This paper investigates the role of imaging in the diagnosis and follow-up of patients with Crohn's disease (CD), with a particular focus on recent innovations in magnetic resonance enterography (MRE) as a pivotal diagnostic tool. The study analyzes the MRE study protocol and imaging features during the various phases of disease activity and its complications.
Article
Health Care Sciences & Services
Roberta Fusco, Igino Simonetti, Stefania Ianniello, Alberta Villanacci, Francesca Grassi, Federica Dell'Aversana, Roberta Grassi, Diletta Cozzi, Eleonora Bicci, Pierpaolo Palumbo, Alessandra Borgheresi, Andrea Giovagnoni, Vittorio Miele, Antonio Barile, Vincenza Granata
Summary: This article highlights the importance for radiologists to know the COVID-19 infection and vaccination history of their patients in order to avoid misleading results and unnecessary alarmism. It also discusses the potential occurrence of therapy-related pneumonitis in cancer patients undergoing immunotherapy.
JOURNAL OF PERSONALIZED MEDICINE
(2022)
Article
Oncology
Valerio Nardone, Alfonso Reginelli, Roberta Grassi, Giovanna Vacca, Giuliana Giacobbe, Antonio Angrisani, Alfredo Clemente, Ginevra Danti, Pierpaolo Correale, Salvatore Francesco Carbone, Luigi Pirtoli, Lorenzo Bianchi, Angelo Vanzulli, Cesare Guida, Roberto Grassi, Salvatore Cappabianca
Summary: This study aimed to investigate the use of MRI delta texture analysis (D-TA) in predicting pathological response in patients with locally advanced rectal cancer. The results showed that D-TA could predict the frequency of complete pathological responses and could potentially be used to identify patients who would benefit from radical surgery.
Review
Medicine, General & Internal
Federica De Muzio, Francesca Grassi, Federica Dell'Aversana, Roberta Fusco, Ginevra Danti, Federica Flammia, Giuditta Chiti, Tommaso Valeri, Andrea Agostini, Pierpaolo Palumbo, Federico Bruno, Carmen Cutolo, Roberta Grassi, Igino Simonetti, Andrea Giovagnoni, Vittorio Miele, Antonio Barile, Vincenza Granata
Summary: Liver cancer is a common and deadly disease, with hepatocellular carcinoma being the most prevalent form. Imaging plays a crucial role in the management of this type of cancer, and LI-RADS is the most widely used classification system for its diagnosis and treatment response. However, there is still room for improvement in differentiating liver lesions and assessing treatment.
Review
Health Care Sciences & Services
Igino Simonetti, Federico Bruno, Roberta Fusco, Carmen Cutolo, Sergio Venanzio Setola, Renato Patrone, Carlo Masciocchi, Pierpaolo Palumbo, Francesco Arrigoni, Carmine Picone, Andrea Belli, Roberta Grassi, Francesca Grassi, Antonio Barile, Francesco Izzo, Antonella Petrillo, Vincenza Granata
Summary: Desmoid tumors are rare soft tissue tumors that can mimic other pathological conditions. Imaging techniques such as ultrasound, CT, and MRI play a crucial role in diagnosis and treatment evaluation.
JOURNAL OF PERSONALIZED MEDICINE
(2022)
Review
Oncology
Giulio Francolini, Ilaria Morelli, Maria Grazia Carnevale, Roberta Grassi, Valerio Nardone, Mauro Loi, Marianna Valzano, Viola Salvestrini, Lorenzo Livi, Isacco Desideri
Summary: This paper explores the impact of novel imaging technologies and modern radiotherapy techniques on cancer management, focusing on prostate adenocarcinoma. It highlights the importance of diagnostic imaging in treatment planning, the role of radiomics in predicting outcomes, the benefits of novel imaging in radiotherapy planning, and the influence of advanced technologies in systemic treatment and non-oncological condition management, all aimed at tailoring the best therapeutic strategies.
Review
Medicine, General & Internal
Pierpaolo Palumbo, Ester Cannizzaro, Maria Michela Palumbo, Annamaria Di Cesare, Federico Bruno, Chiara Acanfora, Antonella Arceri, Laura Evangelista, Francesco Arrigoni, Francesca Grassi, Roberta Grassi, Silvia Pradella, Vittorio Miele, Andrea Giovagnoni, Alessandra Splendiani, Antonio Barile, Carlo Masciocchi, Ernesto Di Cesare
Summary: This narrative review aims to describe the main mechanisms leading to heart failure in different cardiomyopathies, as well as the current diagnostic and prognostic advantages deriving from advanced imaging in the cardiac field.
Review
Health Care Sciences & Services
Valerio Nardone, Emma D'Ippolito, Roberta Grassi, Angelo Sangiovanni, Federico Gagliardi, Giuseppina De Marco, Vittorio Salvatore Menditti, Luca D'Ambrosio, Fabrizio Cioce, Luca Boldrini, Viola Salvestrini, Carlo Greco, Isacco Desideri, Francesca De Felice, Ida D'Onofrio, Roberto Grassi, Alfonso Reginelli, Salvatore Cappabianca
Summary: Despite being mainly used in oncological patients, radiotherapy can also be an effective treatment for non-malignant disorders. Recent interest has shed light on this approach, and further investigation and clinical application are needed.
JOURNAL OF PERSONALIZED MEDICINE
(2022)
Review
Health Care Sciences & Services
Vincenza Granata, Federica De Muzio, Carmen Cutolo, Federica Dell'Aversana, Francesca Grassi, Roberta Grassi, Igino Simonetti, Federico Bruno, Pierpaolo Palumbo, Giuditta Chiti, Ginevra Danti, Roberta Fusco
Summary: This article provides an overview of structured reporting in radiological settings. Structured reporting allows for a standardized approach, improving communication and clarification. It also enables the connection of radiological data with clinical features, facilitating personalized medicine. Additionally, structured reporting allows for data mining to obtain new biomarkers and aid in the development of new application domains, particularly in radiomics.
JOURNAL OF PERSONALIZED MEDICINE
(2022)
Review
Health Care Sciences & Services
Anna Russo, Alfonso Reginelli, Giorgia Viola Lacasella, Enrico Grassi, Michele Ahmed Antonio Karaboue, Tiziana Quarto, Gian Maria Busetto, Alberto Aliprandi, Roberta Grassi, Daniela Berritto
Summary: Musculoskeletal ultrasound is a research method that focuses on superficial targets, particularly in the hands, wrists, and feet. Its high spatial resolution and superb image quality have the potential to bring innovation to diagnostic imaging.
JOURNAL OF PERSONALIZED MEDICINE
(2022)
Article
Radiology, Nuclear Medicine & Medical Imaging
Vincenza Granata, Roberta Fusco, Federica De Muzio, Carmen Cutolo, Sergio Venanzio Setola, Roberta Grassi, Francesca Grassi, Alessandro Ottaiano, Guglielmo Nasti, Fabiana Tatangelo, Vincenzo Pilone, Vittorio Miele, Maria Chiara Brunese, Francesco Izzo, Antonella Petrillo
Summary: The study evaluated the efficacy of radiomics features obtained by T2-weighted sequences in predicting clinical outcomes following liver resection in colorectal liver metastases patients. The results confirmed the capacity of radiomics to identify prognostic features that could affect treatment choice, leading to a more personalized approach in patients with liver metastases.
Article
Pharmacology & Pharmacy
V Granata, R. Fusco, S. Venanzio Setola, M. L. Barretta, D. M. A. Iasevoli, R. Palaia, A. Belli, R. Patrone, F. Tatangelo, G. Grazzini, R. Grassi, F. Grassi, A. Anselmo, F. Izzo, A. Petrillo
Summary: This study reports the experience of a National Cancer Center in studying the radiological features of rare liver lesions and assessing their diagnostic performances. The results show that radiological features can accurately identify benign and malignant lesions, and the presence of ancillary features aids in making correct diagnoses.
EUROPEAN REVIEW FOR MEDICAL AND PHARMACOLOGICAL SCIENCES
(2022)
