医学
正电子发射断层摄影术
磁共振成像
比例危险模型
核医学
阶段(地层学)
单变量分析
标准摄取值
危险系数
有效扩散系数
氟脱氧葡萄糖
放射科
肿瘤科
多元分析
内科学
置信区间
古生物学
生物
作者
Caiyun Huang,Lingyu Zhang,Zhaoting Meng,Tianbin Song,Suresh K. Mukherji,Xiaohong Chen,Jie Lu,Junfang Xian
出处
期刊:Journal of Computer Assisted Tomography
[Ovid Technologies (Wolters Kluwer)]
日期:2022-09-01
卷期号:46 (6): 968-977
被引量:2
标识
DOI:10.1097/rct.0000000000001365
摘要
The aim of the study is to investigate the value of pretreatment integrated positron emission tomography/magnetic resonance imaging (PET/MRI) in predicting the prognosis of patients with hypopharyngeal squamous cell carcinoma (HSCC).Twenty-one untreated patients with HSCC who underwent PET/MRI before treatment were enrolled. We analyzed the value of PET/MRI parameters in predicting the progression-free survival (PFS) and overall survival (OS) of HSCC patients. Kaplan-Meier method and log rank test were used to perform univariate survival analysis, whereas Cox proportional hazard regression models were used to perform multivariate analysis.Of the 21 patients with a median follow-up time of 20.3 months (range, 4.2-37.6 months), 2 (9.5%) had local recurrence, 2 (9.5%) had distant metastases, and 8 (38.1%) died because of cancer. Univariate analysis showed that T stage, clinical stage, total lesion glycolysis (TLG), and metabolic tumor volume (MTV) were significant prognostic factors for PFS (P < 0.05). T stage, clinical stage, TLG, MTV, the mean apparent diffusion coefficient (ADCmean), and the minimal apparent diffusion coefficient (ADCmin) were significant prognostic factors for OS (P < 0.05). The Cox proportional hazard regression model revealed that MTV was an independent prognostic factor for PFS, and TLG was an independent prognostic factor for OS (P < 0.05).Metabolic tumor volume was an independent predictor of PFS in patients with HSCC, while TLG was an independent predictor of OS. T stage, clinical stage, ADCmean, and ADCmin are potential prognostic indicators for HSCC. Positron emission tomography/magnetic resonance imaging can provide effective information for predicting the prognosis for HSCC patients.
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