SU-F-R-48: Early Prediction of Pathological Response of Locally Advanced Rectal Cancer Using Perfusion CT:A Prospective Clinical Study

Authors


Abstract

Purpose:

To prospectively evaluate the tumor vascularity assessed by perfusion CT for prediction of chemo-radiation treatment (CRT) response in locally advanced rectal cancer (LARC).

Methods:

Eighteen consecutive patients (61.9±8.8 years, from March–June 2015) diagnosed with LARC who underwent 6–8 weeks CRT followed by surgery were included. The pre-treatment perfusion CT was acquired after a 5s delay of contrast agent injection for 45s with 1s interval. A total of 7-cm craniocaudal range covered the tumor region with 3-mm slice thickness. The effective radiation dose is around 15mSv, which is about 1.5 the conventional abdomen/pelvis CT dose. The parametric map of blood flow (BF), blood volume (BV), mean transit time (MTT), permeability (PMB), and maximum intensity map (MIP) were obtained from commercial software (Syngo-CT 2011A, Siemens). An experienced radiation oncologist outlined the tumor based on the pre-operative MR and pathologic residual region, but was blinded with regards to pathological tumor stage. The perfusion parameters were compared to histopathological response quantified by tumor regression grade as good-responder (GR, TRG 0-1) vs. non-good responder (non-GR). Furthermore, the predictive value for pathological complete response (pCR) was also investigated.

Results:

Both BV (p=0.02) and MTT (P=0.02) was significantly higher and permeambility was lower (p=0.004) in the good responders. The BF was higher in GR group but not statistically significant. Regarding the discrimination of pCR vs non-pCR, the BF was higher in the pCR group (p=0.08) but none of those parameters showed statistically significant differences.

Conclusion:

BV and MTT can discriminate patients with a favorable response from those that fail to respond well, potentially selecting high-risk patients with resistant tumors that may benefit from an aggressive preoperative treatment approach. However, future studies with more patient data are needed to verify the prognostic value of perfusion CT especially for pCR prediction.

This work is supported by the National High-tech R&D program for Young Scientists by the Ministry of Science and Technology of China (Grant No. 2015AA020917), Natural Science Foundation of China (NSFC Grant No. 81201091).

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