Maria Antonietta Mazzei1, Letizia Di Giacomo1, Giulio Bagnacci1, Valerio Nardone2, Francesco Gentili3, Gabriele Lucii1, Paolo Tini4, Daniele Marrelli5, Paolo Morgagni6, Gianni Mura7, Gian Luca Baiocchi8, Frida Pittiani9, Luca Volterrani1, Franco Roviello5. 1. Department of Medical, Surgical and Neuro Sciences, University of Siena and Department of Radiological Sciences, Unit of Diagnostic Imaging, Azienda Ospedaliera Universitaria Senese, Siena, Italy. 2. Unit of Radiation Therapy, Ospedale del Mare, Naples, Italy. 3. Section of Radiology, Unit of Surgical Sciences, University of Parma, Parma, Italy. 4. Unit of Radiation Oncology, Azienda Ospedaliera Universitaria Senese, Siena, Italy. 5. Department of Medical, Surgical and Neuro Sciences, Unit of Surgical Oncology, University of Siena, Azienda Ospedaliera Universitaria Senese, Siena, Italy. 6. Department of General Surgery, Morgagni-Pierantoni Hospital, Forlì, Italy. 7. Department of Surgery, San Donato Hospital, Arezzo, Italy. 8. Department of Clinical and Experimental Studies, Surgical Clinic, University of Brescia, Brescia, Italy. 9. Department of Radiology, ASST Spedali Civili Brescia, Brescia, Italy.
Abstract
BACKGROUND: To predict response to neoadjuvant chemotherapy (NAC) of gastric cancer (GC), prior to surgery, would be pivotal to customize patient treatment. The aim of this study is to investigate the reliability of computed tomography (CT) texture analysis (TA) in predicting the histo-pathological response to NAC in patients with resectable locally advanced gastric cancer (AGC). METHODS: Seventy (40 male, mean age 63.3 years) patients with resectable locally AGC, treated with NAC and radical surgery, were included in this retrospective study from 5 centers of the Italian Research Group for Gastric Cancer (GIRCG). Population was divided into two groups: 29 patients from one center (internal cohort for model development and internal validation) and 41 from other four centers (external cohort for independent external validation). Gross tumor volume (GTV) was segmented on each pre- and post-NAC multidetector CT (MDCT) image by using a dedicated software (RayStation), and 14 TA parameters were then extrapolated. Correlation between TA parameters and complete pathological response (tumor regression grade, TRG1), was initially investigated for the internal cohort. The univariate significant variables were tested on the external cohort and multivariate logistic analysis was performed. RESULTS: In multivariate logistic regression the only significant TA variable was delta gray-level co-occurrence matrix (GLCM) contrast (P=0.001, Nagelkerke R2: 0.546 for the internal cohort and P=0.014, Nagelkerke R2: 0.435 for the external cohort). Receiver operating characteristic (ROC) curves, generated from the logistic regression of all the patients, showed an area under the curve (AUC) of 0.763. CONCLUSIONS: Post-NAC GLCM contrast and dissimilarity and delta GLCM contrast TA parameters seem to be reliable for identifying patients with locally AGC responder to NAC. 2021 Quantitative Imaging in Medicine and Surgery. All rights reserved.
BACKGROUND: To predict response to neoadjuvant chemotherapy (NAC) of gastric cancer (GC), prior to surgery, would be pivotal to customize patient treatment. The aim of this study is to investigate the reliability of computed tomography (CT) texture analysis (TA) in predicting the histo-pathological response to NAC in patients with resectable locally advanced gastric cancer (AGC). METHODS: Seventy (40 male, mean age 63.3 years) patients with resectable locally AGC, treated with NAC and radical surgery, were included in this retrospective study from 5 centers of the Italian Research Group for Gastric Cancer (GIRCG). Population was divided into two groups: 29 patients from one center (internal cohort for model development and internal validation) and 41 from other four centers (external cohort for independent external validation). Gross tumor volume (GTV) was segmented on each pre- and post-NAC multidetector CT (MDCT) image by using a dedicated software (RayStation), and 14 TA parameters were then extrapolated. Correlation between TA parameters and complete pathological response (tumor regression grade, TRG1), was initially investigated for the internal cohort. The univariate significant variables were tested on the external cohort and multivariate logistic analysis was performed. RESULTS: In multivariate logistic regression the only significant TA variable was delta gray-level co-occurrence matrix (GLCM) contrast (P=0.001, Nagelkerke R2: 0.546 for the internal cohort and P=0.014, Nagelkerke R2: 0.435 for the external cohort). Receiver operating characteristic (ROC) curves, generated from the logistic regression of all the patients, showed an area under the curve (AUC) of 0.763. CONCLUSIONS: Post-NAC GLCM contrast and dissimilarity and delta GLCM contrast TA parameters seem to be reliable for identifying patients with locally AGC responder to NAC. 2021 Quantitative Imaging in Medicine and Surgery. All rights reserved.
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