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.

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. - In: LA RADIOLOGIA MEDICA. - ISSN 0033-8362. - STAMPA. - 123:3(2018), pp. 161-167. [10.1007/s11547-017-0833-8]

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;Giunta, Gaetano;CONFORTO, SILVIA;Laghi, Andrea
2018

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.
2018
Colorectal cancer; Haralick's texture analysis; response to therapy; T2 weighted MRI
01 Pubblicazione su rivista::01a Articolo in rivista
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. - In: LA RADIOLOGIA MEDICA. - ISSN 0033-8362. - STAMPA. - 123:3(2018), pp. 161-167. [10.1007/s11547-017-0833-8]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1071952
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