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Advances in Imaging and Automated Quantification of Malignant Pulmonary Diseases: A State-of-the-Art Review.
Hochhegger, Bruno; Zanon, Matheus; Altmayer, Stephan; Pacini, Gabriel S; Balbinot, Fernanda; Francisco, Martina Z; Dalla Costa, Ruhana; Watte, Guilherme; Santos, Marcel Koenigkam; Barros, Marcelo C; Penha, Diana; Irion, Klaus; Marchiori, Edson.
Afiliação
  • Hochhegger B; LABIMED - Medical Imaging Research Lab, Department of Radiology, Pavilhão, Pereira Filho Hospital, Irmandade Santa Casa de Misericórdia de Porto Alegre, Av. Independência, 75, Porto Alegre, 90020-160, Brazil. brunoho@ufcspa.edu.br.
  • Zanon M; Department of Imaging, Pontifical Catholic University of Rio Grande do Sul, Av. Ipiranga, 6681 - Partenon, Porto Alegre, RS, 90619-900, Brazil. brunoho@ufcspa.edu.br.
  • Altmayer S; Medical Imaging Research Laboratory, Federal University of Health Sciences of Porto Alegre, R. Sarmento Leite, 245, Porto Alegre, Rio Grande Do Sul, 90050-170, Brazil.
  • Pacini GS; Medical Imaging Research Laboratory, Federal University of Health Sciences of Porto Alegre, R. Sarmento Leite, 245, Porto Alegre, Rio Grande Do Sul, 90050-170, Brazil.
  • Balbinot F; Medical Imaging Research Laboratory, Federal University of Health Sciences of Porto Alegre, R. Sarmento Leite, 245, Porto Alegre, Rio Grande Do Sul, 90050-170, Brazil.
  • Francisco MZ; Medical Imaging Research Laboratory, Federal University of Health Sciences of Porto Alegre, R. Sarmento Leite, 245, Porto Alegre, Rio Grande Do Sul, 90050-170, Brazil.
  • Dalla Costa R; Department of Radiology, Irmandade da Santa Casa de Misericordia de Porto Alegre, Av. Independência, 75, Porto Alegre, 90035-072, Brazil.
  • Watte G; Department of Radiology, Irmandade da Santa Casa de Misericordia de Porto Alegre, Av. Independência, 75, Porto Alegre, 90035-072, Brazil.
  • Santos MK; Department of Imaging, Pontifical Catholic University of Rio Grande do Sul, Av. Ipiranga, 6681 - Partenon, Porto Alegre, RS, 90619-900, Brazil.
  • Barros MC; Medical Imaging Research Laboratory, Federal University of Health Sciences of Porto Alegre, R. Sarmento Leite, 245, Porto Alegre, Rio Grande Do Sul, 90050-170, Brazil.
  • Penha D; Ribeirao Preto Medical School, Av. Bandeirantes, 3900, Monte Alegre, Ribeirão Preto, São Paulo, 14049-900, Brazil.
  • Irion K; Department of Radiology, Irmandade da Santa Casa de Misericordia de Porto Alegre, Av. Independência, 75, Porto Alegre, 90035-072, Brazil.
  • Marchiori E; Radiology, Liverpool Heart and Chest Hospital, Thomas Dr, Liverpool, L14 3PE, UK.
Lung ; 196(6): 633-642, 2018 12.
Article em En | MEDLINE | ID: mdl-30302536
Quantitative imaging in lung cancer is a rapidly evolving modality in radiology that is changing clinical practice from a qualitative analysis of imaging features to a more dynamic, spatial, and phenotypical characterization of suspected lesions. Some quantitative parameters, such as the use of 18F-FDG PET/CT-derived standard uptake values (SUV), have already been incorporated into current practice as it provides important information for diagnosis, staging, and treatment response of patients with lung cancer. A growing body of evidence is emerging to support the use of quantitative parameters from other modalities. CT-derived volumetric assessment, CT and MRI lung perfusion scans, and diffusion-weighted MRI are some of the examples. Software-assisted technologies are the future of quantitative analyses in order to decrease intra- and inter-observer variability. In the era of "big data", widespread incorporation of radiomics (extracting quantitative information from medical images by converting them into minable high-dimensional data) will allow medical imaging to surpass its current status quo and provide more accurate histological correlations and prognostic value in lung cancer. This is a comprehensive review of some of the quantitative image methods and computer-aided systems to the diagnosis and follow-up of patients with lung cancer.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Interpretação de Imagem Assistida por Computador / Nódulo Pulmonar Solitário / Imagem de Perfusão / Tomografia por Emissão de Pósitrons combinada à Tomografia Computadorizada / Neoplasias Pulmonares Tipo de estudo: Qualitative_research Limite: Humans Idioma: En Revista: Lung Ano de publicação: 2018 Tipo de documento: Article País de afiliação: Brasil

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Interpretação de Imagem Assistida por Computador / Nódulo Pulmonar Solitário / Imagem de Perfusão / Tomografia por Emissão de Pósitrons combinada à Tomografia Computadorizada / Neoplasias Pulmonares Tipo de estudo: Qualitative_research Limite: Humans Idioma: En Revista: Lung Ano de publicação: 2018 Tipo de documento: Article País de afiliação: Brasil