Computed tomography texture analysis in patients with gastric cancer: a quantitative imaging biomarker for preoperative evaluation before neoadjuvant chemotherapy treatment

Yardimci A. H., Sel I., Bektas C. T., Yarikkaya E., Dursun N., Bektas H., ...Daha Fazla

Japanese Journal of Radiology, cilt.38, sa.6, ss.553-560, 2020 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 38 Sayı: 6
  • Basım Tarihi: 2020
  • Doi Numarası: 10.1007/s11604-020-00936-2
  • Dergi Adı: Japanese Journal of Radiology
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Agricultural & Environmental Science Database, Biotechnology Research Abstracts, CINAHL, EMBASE, MEDLINE
  • Sayfa Sayıları: ss.553-560
  • Anahtar Kelimeler: Gastric cancer, Lymph node metastasis, Multidetector computed tomography, Texture analysis, Tumor grade, Tumor stage
  • İstanbul Gelişim Üniversitesi Adresli: Evet

Özet

© 2020, Japan Radiological Society.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.