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Radiomics in Abdominopelvic Solid-Organ Oncologic Imaging: Current Status.
Liu, Xiaoyang; Elbanan, Mohamed G; Luna, Antonio; Haider, Masoom A; Smith, Andrew D; Sabottke, Carl F; Spieler, Bradley M; Turkbey, Baris; Fuentes, David; Moawad, Ahmed; Kamel, Serageldin; Horvat, Natally; Elsayes, Khaled M.
Afiliação
  • Liu X; Joint Department of Medical Imaging, Division of Abdominal Imaging, University Health Network, University of Toronto, ON, Canada.
  • Elbanan MG; Department of Radiology, Yale New Haven Health, Bridgeport Hospital, Bridgeport, CT.
  • Luna A; Department of Imaging, HT Médica, Jaén, Spain.
  • Haider MA; Lunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, ON, Canada.
  • Smith AD; Joint Department of Medical Imaging, University Health Network, Sinai Health System and University of Toronto, Toronto, ON, Canada.
  • Sabottke CF; Department of Radiology, University of Alabama at Birmingham, Birmingham, AL.
  • Spieler BM; Department of Medical Imaging, University of Arizona College of Medicine, Tucson, AZ.
  • Turkbey B; Department of Radiology, University Medical Center, Louisiana State University Health Sciences Center, New Orleans, LA.
  • Fuentes D; Molecular Imaging Program, National Cancer Institute, NIH, Bethesda, MD.
  • Moawad A; Department of Imaging Physics, University of Texas MD Anderson Cancer Center, Houston, TX.
  • Kamel S; Department of Diagnostic and Interventional Radiology, Mercy Catholic Medical Center, Darby, PA.
  • Horvat N; Department of Lymphoma, University of Texas MD Anderson Cancer Center, Houston, TX.
  • Elsayes KM; Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY.
AJR Am J Roentgenol ; 219(6): 985-995, 2022 12.
Article em En | MEDLINE | ID: mdl-35766531
Radiomics is the process of extraction of high-throughput quantitative imaging features from medical images. These features represent noninvasive quantitative biomarkers that go beyond the traditional imaging features visible to the human eye. This article first reviews the steps of the radiomics pipeline, including image acquisition, ROI selection and image segmentation, image preprocessing, feature extraction, feature selection, and model development and application. Current evidence for the application of radiomics in abdominopelvic solid-organ cancers is then reviewed. Applications including diagnosis, subtype determination, treatment response assessment, and outcome prediction are explored within the context of hepatobiliary and pancreatic cancer, renal cell carcinoma, prostate cancer, gynecologic cancer, and adrenal masses. This literature review focuses on the strongest available evidence, including systematic reviews, meta-analyses, and large multicenter studies. Limitations of the available literature are highlighted, including marked heterogeneity in radiomics methodology, frequent use of small sample sizes with high risk of overfitting, and lack of prospective design, external validation, and standardized radiomics workflow. Thus, although studies have laid a foundation that supports continued investigation into radiomics models, stronger evidence is needed before clinical adoption.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Oncologia / Neoplasias Tipo de estudo: Clinical_trials / Prognostic_studies Limite: Female / Humans / Male Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Oncologia / Neoplasias Tipo de estudo: Clinical_trials / Prognostic_studies Limite: Female / Humans / Male Idioma: En Ano de publicação: 2022 Tipo de documento: Article