Aytul Hande Yardimci1, Ipek Sel2, Ceyda Turan Bektas2, Enver Yarikkaya3, Nevra Dursun3, Hasan Bektas4, Cigdem Usul Afsar5, Rıza Umar Gursu6, Veysi Hakan Yardimci7, Elif Ertas8, Ozgur Kilickesmez2. 1. Department of Radiology, Istanbul Training and Research Hospital, Kasap İlyas Mah., Org. Abdurrahman Nafiz Gürman Cd., Fatih, 34098, Istanbul, Turkey. yahandeoo@yahoo.com. 2. Department of Radiology, Istanbul Training and Research Hospital, Kasap İlyas Mah., Org. Abdurrahman Nafiz Gürman Cd., Fatih, 34098, Istanbul, Turkey. 3. Department of Pathology, Istanbul Training and Research Hospital, Istanbul, Turkey. 4. Department of General Surgery, Istanbul Training and Research Hospital, Istanbul, Turkey. 5. Department of Medical Oncology, Acıbadem Mehmet Ali Aydınlar University Medical Faculty, Istanbul, Turkey. 6. Department of Medical Oncology, Istanbul Training and Research Hospital, Istanbul, Turkey. 7. Institute of Health Sciences, Istanbul Gelisim University, Istanbul, Turkey. 8. Department of Biostatistics, Mersin University, Mersin, Turkey.
Abstract
PURPOSE: The aim of the study is to explore the role of computed tomography texture analysis (CT-TA) for predicting clinical T and N stages and tumor grade before neoadjuvant chemotherapy treatment in gastric cancer (GC) patients during the preoperative period. MATERIALS AND METHODS: CT images of 114 patients with GC were included in this retrospective study. Following pre-processing steps, textural features were extracted using MaZda software in the portal venous phase. We evaluated and analyzed texture features of six principal categories for differentiating between T stages (T1,2 vs T3,4), N stages (N+ vs N-) and grades (low-intermediate vs. high). Classification was performed based on texture parameters with high model coefficients in linear discriminant analysis (LDA). RESULTS: Dimension-reduction steps yielded five textural features for T stage, three for N stage and two for tumor grade. The discriminatory capacities of T stage, N stage and tumor grade were 90.4%, 81.6% and 64.5%, respectively, when LDA algorithm was employed. CONCLUSION: CT-TA yields potentially useful imaging biomarkers for predicting the T and N stages of patients with GC and can be used for preoperative evaluation before neoadjuvant treatment planning.
PURPOSE: The aim of the study is to explore the role of computed tomography texture analysis (CT-TA) for predicting clinical T and N stages and tumor grade before neoadjuvant chemotherapy treatment in gastric cancer (GC) patients during the preoperative period. MATERIALS AND METHODS: CT images of 114 patients with GC were included in this retrospective study. Following pre-processing steps, textural features were extracted using MaZda software in the portal venous phase. We evaluated and analyzed texture features of six principal categories for differentiating between T stages (T1,2 vs T3,4), N stages (N+ vs N-) and grades (low-intermediate vs. high). Classification was performed based on texture parameters with high model coefficients in linear discriminant analysis (LDA). RESULTS: Dimension-reduction steps yielded five textural features for T stage, three for N stage and two for tumor grade. The discriminatory capacities of T stage, N stage and tumor grade were 90.4%, 81.6% and 64.5%, respectively, when LDA algorithm was employed. CONCLUSION:CT-TA yields potentially useful imaging biomarkers for predicting the T and N stages of patients with GC and can be used for preoperative evaluation before neoadjuvant treatment planning.