Computed tomography texture analysis in patients with gastric cancer: a quantitative imaging biomarker for preoperative evaluation before neoadjuvant chemotherapy treatment
Japanese Journal of Radiology, cilt.38, sa.6, ss.553-560, 2020 (SCI-Expanded, Scopus)
- 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.