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Haralick's texture features for the prediction of response to therapy in colorectal cancer: a preliminary study.
Caruso, Damiano; Zerunian, Marta; Ciolina, Maria; de Santis, Domenico; Rengo, Marco; Soomro, Mumtaz H; Giunta, Gaetano; Conforto, Silvia; Schmid, Maurizio; Neri, Emanuele; Laghi, Andrea.
  • Caruso D; Department of Radiological Sciences, Oncology and Pathology, "Sapienza" - University of Rome, I.C.O.T. Hospital, Via Franco Faggiana 1668, 04100, Latina, Italy.
  • Zerunian M; Department of Radiological Sciences, Oncology and Pathology, "Sapienza" - University of Rome, I.C.O.T. Hospital, Via Franco Faggiana 1668, 04100, Latina, Italy.
  • Ciolina M; Department of Radiological Sciences, Oncology and Pathology, "Sapienza" - University of Rome, I.C.O.T. Hospital, Via Franco Faggiana 1668, 04100, Latina, Italy.
  • de Santis D; Department of Radiological Sciences, Oncology and Pathology, "Sapienza" - University of Rome, I.C.O.T. Hospital, Via Franco Faggiana 1668, 04100, Latina, Italy.
  • Rengo M; Department of Radiological Sciences, Oncology and Pathology, "Sapienza" - University of Rome, I.C.O.T. Hospital, Via Franco Faggiana 1668, 04100, Latina, Italy.
  • Soomro MH; Department of Engineering, University of Roma Tre, Via Vito Volterra 62, 00146, Rome, Italy.
  • Giunta G; Department of Engineering, University of Roma Tre, Via Vito Volterra 62, 00146, Rome, Italy.
  • Conforto S; Department of Engineering, University of Roma Tre, Via Vito Volterra 62, 00146, Rome, Italy.
  • Schmid M; Department of Engineering, University of Roma Tre, Via Vito Volterra 62, 00146, Rome, Italy.
  • Neri E; Department of Radiological Sciences, AOUP, Via Savi 10, 56126, Pisa, Italy.
  • Laghi A; Department of Radiological Sciences, Oncology and Pathology, "Sapienza" - University of Rome, I.C.O.T. Hospital, Via Franco Faggiana 1668, 04100, Latina, Italy. andrea.laghi@uniroma1.it.
Radiol Med ; 123(3): 161-167, 2018 Mar.
Article en En | MEDLINE | ID: mdl-29119525
ABSTRACT

PURPOSE:

Haralick features Texture analysis is a recent oncologic imaging biomarker used to assess quantitatively the heterogeneity within a tumor. The aim of this study is to evaluate which Haralick's features are the most feasible in predicting tumor response to neoadjuvant chemoradiotherapy (CRT) in colorectal cancer. MATERIALS AND

METHODS:

After MRI and histological assessment, eight patients were enrolled and divided into two groups based on response to neoadjuvant CRT in complete responders (CR) and non-responders (NR). Oblique Axial T2-weighted MRI sequences before CRT were analyzed by two radiologists in consensus drawing a ROI around the tumor. 14 over 192 Haralick's features were extrapolated from normalized gray-level co-occurrence matrix in four different directions. A dedicated statistical analysis was performed to evaluate distribution of the extracted Haralick's features computing mean and standard deviation.

RESULTS:

Pretreatment MRI examination showed significant value (p < 0.05) of 5 over 14 computed Haralick texture. In particular, the significant features are the following concerning energy, contrast, correlation, entropy and inverse difference moment.

CONCLUSIONS:

Five Haralick's features showed significant relevance in the prediction of response to therapy in colorectal cancer and might be used as additional imaging biomarker in the oncologic management of colorectal patients.
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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Procesamiento de Imagen Asistido por Computador / Imagen por Resonancia Magnética / Neoplasias Colorrectales / Adenocarcinoma Tipo de estudio: Diagnostic_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Aged / Female / Humans / Male / Middle aged Idioma: En Año: 2018 Tipo del documento: Article

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Procesamiento de Imagen Asistido por Computador / Imagen por Resonancia Magnética / Neoplasias Colorrectales / Adenocarcinoma Tipo de estudio: Diagnostic_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Aged / Female / Humans / Male / Middle aged Idioma: En Año: 2018 Tipo del documento: Article