Value of PET/MR-IVIM in predicting early prognosis of patients with concurrent chemoradiotherapy for cervical cancer
10.3760/cma.j.cn321828-20200811-00309
- VernacularTitle:PET/MR-IVIM在预测宫颈癌同步放化疗患者早期预后中的价值
- Author:
Yangtong LI
1
;
Ke WU
;
Hongzan SUN
Author Information
1. 中国医科大学附属盛京医院放射科，沈阳 110004
- Keywords:
Uterine cervical neoplasms;
Radiotherapy;
Drug therapy;
Positron-emission tomography;
Magnetic resonance imaging;
Deoxyglucose
- From:
Chinese Journal of Nuclear Medicine and Molecular Imaging
2021;41(7):399-404
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To evaluate the value of PET/MR multiple parameters before treatment and MR-intravoxel incoherent motion (IVIM) parameters 4 weeks after concurrent chemoradiotherapy (CCRT) in predicting the prognosis of cervical cancer patients 6 months after treatment.Methods:From September 2017 to March 2019, 58 cervical cancer patients (age: 35-78 years) performed CCRT in Shengjing Hospital of China Medical University were retrospectively enrolled. PET/MR was performed before treatment, and MR-IVIM was performed at the end of the fourth week of treatment and 6 months after treatment. Patients were divided into complete response (CR) group and non-CR group according to the response evaluation criteria in solid tumors (RECIST). PET imaging parameters (maximum standardized uptake value (SUV max), metabolic tumor volume (MTV), total lesion glycolysis (TLG)), MR-IVIM parameters (slow diffusion coefficient (D), fast diffusion coefficient (D *), perfusion fraction (F), gross tumor volume (GTV), diffusion volume (DV)) before (referred to as 1) and after (at the end of the fourth week; referred to as 2) treatment and their percentage changes (ΔD, ΔD *, ΔF, ΔGTV, ΔDV) were measured. The parameters of PET and MR-IVIM were analyzed by the receiver operating characteristic (ROC) curve analysis. Multiple logistic regression was used to establish the combination prediction model of parameters before treatment and all parameters before and after treatment (Combination1 and Combination2 respectively), and the two models were compared by Delong test. Results:Of 58 patients, 37(63.79%) were CR, and 21 (36.21%) were non-CR. MTV (area under curve (AUC)=0.764, P<0.01), TLG (AUC=0.719, P<0.01), GTV 1 (AUC=0.761, P<0.01) and DV 1 (AUC=0.785, P<0.01) before treatment had positive effects on the treatment response, and the valuable parameters after treatment were D 2 (AUC=0.683, P<0.01), GTV 2 (AUC=0.861, P<0.01), DV 2 (AUC=0.891, P<0.01), ΔD (AUC=0.723, P<0.01), ΔGTV (AUC=0.768, P<0.01) and ΔDV (AUC=0.865, P<0.01). The best prediction model before treatment was DV 1 (Combination1; AUC=0.785, P=0.004). The best prediction model for all parameters before and after treatment was the combination pre-treatment of MTV, DV 2 and ΔD (Combination2; AUC=0.965, P<0.001). Combination2 was superior to Combination1 ( z=2.982, P=0.003). Conclusion:In evaluating the early prognosis of cervical cancer patients treated with CCRT, DV 1 has good predictive potential before treatment, while the combination of pre-treatment MTV with post-treatment DV 2 and ΔD has superior joint predictive potential and can provide help for patients′ personalized treatment.
