Journal ArticleDOI
CT Radiomics Signature of Tumor and Peritumoral Lung Parenchyma to Predict Nonsmall Cell Lung Cancer Postsurgical Recurrence Risk.
Tugba Akinci D'Antonoli,Alessandra Farchione,Jacopo Lenkowicz,Marco Chiappetta,Giuseppe Cicchetti,A. Martino,Alessandra Ottavianelli,Riccardo Manfredi,Stefano Margaritora,Lorenzo Bonomo,Vincenzo Valentini,Anna Rita Larici +11 more
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TLDR
Combination of the tumoral and peritumoral RS with TNM staging system outperformedTNM staging alone in individualized recurrence risk estimation of patients with surgically treated NSCLC.About:
This article is published in Academic Radiology.The article was published on 2020-04-01. It has received 59 citations till now. The article focuses on the topics: TNM staging system.read more
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Predicting cancer outcomes with radiomics and artificial intelligence in radiology.
Kaustav Bera,Kaustav Bera,Nathaniel Braman,Amit Gupta,Amit Gupta,Vamsidhar Velcheti,Anant Madabhushi +6 more
TL;DR: In this article, the authors discuss the next generation of challenges in clinical decision-making that AI tools can solve using radiology images, such as prognostication of outcome across multiple cancers, prediction of response to various treatment modalities, discrimination of benign treatment confounders from true progression, identification of unusual response patterns and prediction of the mutational and molecular profile of tumours.
Journal ArticleDOI
Radiomics as a personalized medicine tool in lung cancer: Separating the hope from the hype.
TL;DR: Radiomics studies in NSCLC suffer from a number of limitations, and identification of limitations can help future studies to expedite biomarker translation.
Journal ArticleDOI
MRI-based clinical-radiomics model predicts tumor response before treatment in locally advanced rectal cancer.
Andrea Delli Pizzi,Antonio Maria Chiarelli,Piero Chiacchiaretta,Martina d’Annibale,Pierpaolo Croce,Consuelo Rosa,Domenico Mastrodicasa,Stefano Trebeschi,Doenja Marina Johanna Lambregts,Daniele Caposiena,Francesco Lorenzo Serafini,Raffaella Basilico,Giulio Cocco,Pierluigi Di Sebastiano,Sebastiano Cinalli,Antonio Ferretti,Richard G. Wise,Domenico Genovesi,Regina G. H. Beets-Tan,Regina G. H. Beets-Tan,Regina G. H. Beets-Tan,Massimo Caulo +21 more
TL;DR: In this paper, a machine learning model combining pre-treatment MRI-based clinical and radiomic features for the early prediction of treatment response in LARC patients was presented, and the model correctly predicted the treatment response.
Journal ArticleDOI
CT-based radiomics for prediction of histologic subtype and metastatic disease in primary malignant lung neoplasms.
José Raniery Ferreira-Junior,Marcel Koenigkam-Santos,Ariane Priscilla Magalhães Tenório,Matheus Calil Faleiros,Federico Enrique Garcia Cipriano,Alexandre Todorovic Fabro,Janne J. Näppi,Hiroyuki Yoshida,Paulo Mazzoncini de Azevedo-Marques +8 more
TL;DR: Several radiomic features significantly associated with distant metastasis, nodal metastases, and histology were discovered in this work, presenting great potential as imaging biomarkers for pathological diagnosis and target therapy decision.
Journal ArticleDOI
CT-Imaging Based Analysis of Invasive Lung Adenocarcinoma Presenting as Ground Glass Nodules Using Peri- and Intra-nodular Radiomic Features.
TL;DR: The gross radiomic signature of intra- and peri-nodular regions improved the prediction ability and aided predicting the invasiveness of lung adenocarcinoma appearing as GGN.
References
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Journal ArticleDOI
Global cancer statistics, 2012
Lindsey A. Torre,Freddie Bray,Rebecca L. Siegel,Jacques Ferlay,Joannie Lortet-Tieulent,Ahmedin Jemal +5 more
TL;DR: A substantial portion of cancer cases and deaths could be prevented by broadly applying effective prevention measures, such as tobacco control, vaccination, and the use of early detection tests.
Journal ArticleDOI
Radiomics: Images Are More than Pictures, They Are Data.
TL;DR: This report describes the process of radiomics, its challenges, and its potential power to facilitate better clinical decision making, particularly in the care of patients with cancer.
BookDOI
Regression Modeling Strategies
TL;DR: Regression models are frequently used to develop diagnostic, prognostic, and health resource utilization models in clinical, health services, outcomes, pharmacoeconomic, and epidemiologic research, and in a multitude of non-health-related areas.
Journal ArticleDOI
Randomized trial of lobectomy versus limited resection for T1 N0 non-small cell lung cancer
TL;DR: Compared with lobectomy, limited pulmonary resection does not confer improved perioperative morbidity, mortality, or late postoperative pulmonary function and lobectomy still must be considered the surgical procedure of choice for patients with peripheral T1 N0 non-small cell lung cancer.
Journal ArticleDOI
Early and locally advanced non-small-cell lung cancer (NSCLC): ESMO Clinical Practice Guidelines for diagnosis, treatment and follow-up
Johan Vansteenkiste,Dirk De Ruysscher,Wilfried Eberhardt,Eric Lim,Suresh Senan,Enriqueta Felip,Solange Peters +6 more
TL;DR: The Clatterbridge Cancer Centre and Liverpool Heart and Chest Hospital, Liverpool; University of Aberdeen, Aberdeen, UK; Center for Medical Imaging, University of Groningen, Groningen; Department of Radiation Oncology, VU University Medical Center, Amsterdam, The Netherlands; and Department of Thoracic Surgery, University Hospitals of Leicester NHS Trust, Leicester, UK.
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