Subclinical lesions detected in large pathological slices of the primary CTV margin in esophageal squamous cell carcinoma and their relationship with FDG PET/CT: An initial report

---

Dali Han, Yinping Yuan, Jie Chai, Guifang Zhang, Lili Wang, Aijun Ren, Pingping Song, Dianbin Mu, Yonghua Yu, Zheng Fu and Jinming Yu

Shandong University, China

: J Clin Exp Oncol

Abstract

---

Objective: The objective is to detect subclinical lesions which determine primary Clinical Target Volume (CTV) of esophageal squamous cell carcinomas in large pathological slices and determine their relationship with 18F-fluorodeoxyglucose (FDG) PET/CT parameters. Material & Methods: Each patient was imaged using FDG PET/CT before surgery, and the maximum standardized uptake value (SUVmax) and metabolic tumor volumes (MTV) were determined in a circular region of interest around the lesions of interest. The patients underwent a radical surgery where the specimen was collected as a large tissue slice for pathological examination by specific techniques. Results: It was observed that, those subclinical lesions incidence were direct invasion (DI, 56.37%), intra-mural metastasis (IMM, 30.9%), multicentric occurrence lesions (MOLs, 40.0%), vascular invasion (VI, 21.8%), and perineural invasion (PNI, 18.2%). The mean distances of the subclinical lesions from the gross tumor were 0.79±1.28 cm in the cranial direction and 0.87±1.00 cm in the caudal direction. The most distant subclinical lesion was 8.0 cm, which was an MOL located cranially from the tumor. Both the SUVmax and MTV values determined by FDG PET/CT had a liner correlation with the subclinical lesions {R=0.487, 95% CI=0.119- 0.689 (P=0.003) and R=0.342, 95% CI= -0.099-0.661 (P=0.044)}, respectively. Conclusion: Based on the findings from these patients, to cover 94.5% of the subclinical lesions in the CTVp of esophageal SCC, a 3-cm margin along the cranial-caudal axis should be added to the gross tumor volume (GTVp). Although, FDG PET/CT could not detect the subclinical lesions directly, it may predict the existence of subclinical lesions based on both SUVmax and MTV measurements.

Biography

---

Email: dalihan2008@163.com