Gastrointestinal Cancer

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SU_10_2095 - Texture Analysis of FDG-PET/CT for Patients with Esophageal SCC Treated By Chemoradiotherapy

Sunday, October 21
1:15 PM - 2:45 PM
Location: Innovation Hub, Exhibit Hall 3

Texture Analysis of FDG-PET/CT for Patients with Esophageal SCC Treated By Chemoradiotherapy
N. Takahashi1, K. Takanami2, R. Umezawa1, K. Takeda1, H. Matsushita1, T. Yamamoto1, Y. Ishikawa1, Y. Katagiri1, S. Tasaka1, Y. Suzuki1, N. Kadoya1, K. Ito1, and K. Jingu1; 1Department of Radiation Oncology, Tohoku University Graduate School of Medicine, Sendai, Japan, 2Department of Diagnostic Radiology, Tohoku University Graduate School of Medicine, Sendai 982-0014, Japan

Purpose/Objective(s): The aim of this study was to determine whether texture analysis of FDG-PET/CT is a predictor of outcomes of definitive chemoradiotherapy (dCRT) for patients with stage II - III thoracic esophageal cancer.

Materials/Methods: We included patients who were treated between 2005 & 2013 and underwent FDG-PET/CT within 45 days before dCRT at our institution. Patients who had massive pneumonia caused by perforation of the tumor at FDG-PET/CT & patients in whom the metabolic tumor volume (MTV) of the primary tumor were less than 10 ml were excluded. 46 patients were enrolled in this study. We measured the primary tumor’s MTV by using a commercially available deformable registration algorithm and calculated the texture parameters in the MTV using a computer algorithm. Texture parameters that had strong correlation with TLG whole body & with each other texture parameters were excluded. Survival estimates were calculated using the Kaplan-Meier method from the first date of dCRT. Predictors were analyzed using Cox’s hazards model.

Results: The median follow-up period was 27.7 months & the 3-year overall survival (OS) rate, local control (LC) rate and progression-free survival (PFS) rate were 49.7%, 32.7% & 30.4%, respectively. In multivariate analysis, correlation (co-occurrence matrix) was an independent predictor for OS (p= 0.0067). The number of cycles of concurrent chemotherapy (1 cycle vs 2 cycles, p = 0.0061), inverse difference moment (normalized co-occurrence matrix, p= 0.0014) & Correlation (co-occurrence matrix, p= 0.035) were independent predictors for LC. The number of cycles of concurrent chemotherapy (1 cycle vs 2 cycles, p= 0.0074), correlation (co-occurrence matrix, p= 0.001) & code similarity (texture feature coding co-occurrence matrix, p= 0.034) were independent predictors for PFS.

Conclusion: Correlation was an independent predictor for OS, LC & PFS. Inverse difference moment was an independent predictor for LC, & code similarity was an independent predictor for PFS. It is possible that texture analysis will become an important method to predict outcomes of dCRT for patients with esophageal SCC.
Multivariate analysis
OS LC PFS
Variables HR (95% CI) p value HR (95% CI) p value HR (95% CI) p value
Gender (male vs female) 3.00 (0.47-59.1) 0.274
Chemo 1 cycle vs 2 cycles 6.63 (1.78-23.6) 0.0061 6.27 (1.69-22.2) 0.0074
TLGWB* 2.45 (0.62-9.68) 0.199
Intensity variability* (Voxel-alignment) 1.44 (0.33-6.31) 0.632
High-intensity run emphasis* (Voxel-alignment) 0.76 (0.32-1.79) 0.519 0.92 (0.39-2.19) 0.852
Contrast* (Neighborhood intensity-difference) 2.67 (0.54-15.4) 0.235
Short-zone emphasis* (Intensity-size-zone) 0.79 (0.24-2.40) 0.683
Inverse difference moment* (Normalized co-occurrence) 2.33 (0.92-6.55) 0.074 3.78 (1.64-9.46) 0.0015 2.08 (0.82-5.39) 0.122
Correlation* (Co-occurrence) 4.25 (1.47-13.6) 0.0067 2.29 (1.06-5.10) 0.035 3.84 (1.72-8.90) 0.001
Code Similarity* (Texture Feature Coding co-occurrence) 0.33 (0.12-0.92) 0.034
note: * ≥ median vs < median

Author Disclosure: N. Takahashi: None. K. Takanami: None. R. Umezawa: None. K. Takeda: None. H. Matsushita: None. K. Ito: None. K. Jingu: None.

Noriyoshi Takahashi, MD, PhD

Biography:
Noriyoshi Takahashi, M.D., Ph.D. has been Assistant Professor in the Department of Radiation Oncology Tohoku University Hospital since 2016.
He received his M.D. in 2011 from Tohoku University School of Medicine, Japan, and he received his Ph.D. in 2016 from Tohoku University Graduate School of Medicine, Japan.
His research interests lie in the area of radiotherapy of esophageal cancer and head and neck cancer and in the area of prognostic research using functional imaging. He received a scientific award of the 27th annual meeting of JASTRO in 2014.

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