Hotton Judicael, Raimond Emilie, Reyal Fabien, Michel Sophie, Ceccato Vivien, Moubtakir Abdenasser, Papathanassiou Dimitri, Morland David
Department of Surgical Oncology, Institut Godinot, 51100 Reims, France.
CReSTIC, UR 3804, Université de Reims Champagne-Ardenne, 51687 Reims, France.
Diagnostics (Basel). 2024 Nov 20;14(22):2607. doi: 10.3390/diagnostics14222607.
: The aim is to propose a model for predicting occult paraaortic lymph node (PALN) involvement in locally advanced cervical cancer (LACC) patients by including parameters such as reconstruction detection technology (use of time-of-flight) and parameters related to the primary tumor. This model will then be compared with the scores used in routine clinical practice; : This retrospective observational cohort study included patients diagnosed with LACC who underwent F-FDG PET/CT prior to PALN surgical staging between February 2012 and May 2020. The following parameters were collected on PET/CT: tumor SUVmax, tumor MTV, number of common and distal pelvic node involvements. A multivariate regression analysis estimating the probability of PALN involvement was performed, with optimal thresholds determined via ROC curves; : In total, 71 patients met the inclusion criteria. Occult PALN involvement was detected in 12.7% of patients. A derived multivariate PET model selected four variables: number of common and distal iliac lymph nodes (OR 5.9 and 2.7, respectively), tumor-to-liver SUV ratio (OR 0.9) and the use of time-of-flight technology (OR 21.4 if no time-of-flight available). At the optimal threshold, a sensitivity of 77.8% and specificity of 88.7% was found. The model's performances varied significantly between patients whose PET/CT used time-of-flight and those whose PET/CT did not. No significant differences were found between our model and the one used in clinical practice ( = 0.55); : This study shows that PET/CT technology influences the ability to detect occult PALN involvement in LACC. This parameter should be considered in the regular revision of PET-based scores.
目的是通过纳入诸如重建检测技术(飞行时间的使用)和与原发肿瘤相关的参数等,提出一种预测局部晚期宫颈癌(LACC)患者隐匿性腹主动脉旁淋巴结(PALN)受累的模型。然后将该模型与常规临床实践中使用的评分进行比较。
这项回顾性观察队列研究纳入了2012年2月至2020年5月期间在PALN手术分期前接受F-FDG PET/CT检查的LACC确诊患者。在PET/CT上收集了以下参数:肿瘤SUVmax、肿瘤MTV、常见和远处盆腔淋巴结受累数量。进行了多因素回归分析以估计PALN受累的概率,并通过ROC曲线确定最佳阈值。
总共71例患者符合纳入标准。12.7%的患者检测到隐匿性PALN受累。一个推导的多因素PET模型选择了四个变量:常见和远处髂淋巴结数量(分别为OR 5.9和2.7)、肿瘤与肝脏SUV比值(OR 0.9)以及飞行时间技术的使用(如果没有飞行时间则为OR 21.4)。在最佳阈值下,灵敏度为77.8%,特异性为88.7%。该模型在使用飞行时间的PET/CT患者和未使用飞行时间的PET/CT患者之间的表现有显著差异。我们的模型与临床实践中使用的模型之间未发现显著差异( = 0.55)。
这项研究表明,PET/CT技术会影响检测LACC患者隐匿性PALN受累的能力。在定期修订基于PET的评分时应考虑该参数。