Abstract：
BACKGROUND: To assess the feasibility and diagnostic performance of the fractional order calculus (FROC), continuous-time random-walk (CTRW), diffusion kurtosis imaging (DKI), intravoxel incoherent motion (IVIM), mono-exponential (MEM) and stretched exponential models (SEM) for predicting response to neoadjuvant chemotherapy (NACT) in patients with esophageal squamous cell carcinoma (ESCC).
METHODS: This study prospectively included consecutive ESCC patients with baseline and follow up MR imaging and pathologically confirmed cT1-4aN + M0 or T3-4aN0M0 and underwent radical resection after neoadjuvant chemotherapy (NACT) between July 2019 and January 2023. Patients were divided into pCR (TRG 0) and non-pCR (TRG1 + 2 + 3) groups according to tumor regression grading (TRG). The Pre-, Post- and Delta-treatment models were built. 18 predictive models were generated according to different feature categories, based on six models by five-fold cross-validation. Areas under the curve (AUCs) of the models were compared by using DeLong method.
RESULTS: Overall, 90 patients (71 men, 19 women; mean age, 64 years ± 6 [SD]) received NACT and underwent baseline and Post-NACT esophageal MRI, with 29 patients in the pCR group and 61 patients in the non-pCR group. Among 18 predictive models, The Pre-, Post-, and Delta-CTRW model showed good predictive efficacy (AUC = 0.722, 0.833 and 0.790). Additionally, the Post-FROC model (AUC = 0.907) also exhibited good diagnostic performance.
CONCLUSIONS: Our study indicates that the CTRW model, along with the Post-FROC model, holds significant promise for the future of NACT efficacy prediction in ESCC patients.
METHODS: This study prospectively included consecutive ESCC patients with baseline and follow up MR imaging and pathologically confirmed cT1-4aN + M0 or T3-4aN0M0 and underwent radical resection after neoadjuvant chemotherapy (NACT) between July 2019 and January 2023. Patients were divided into pCR (TRG 0) and non-pCR (TRG1 + 2 + 3) groups according to tumor regression grading (TRG). The Pre-, Post- and Delta-treatment models were built. 18 predictive models were generated according to different feature categories, based on six models by five-fold cross-validation. Areas under the curve (AUCs) of the models were compared by using DeLong method.
RESULTS: Overall, 90 patients (71 men, 19 women; mean age, 64 years ± 6 [SD]) received NACT and underwent baseline and Post-NACT esophageal MRI, with 29 patients in the pCR group and 61 patients in the non-pCR group. Among 18 predictive models, The Pre-, Post-, and Delta-CTRW model showed good predictive efficacy (AUC = 0.722, 0.833 and 0.790). Additionally, the Post-FROC model (AUC = 0.907) also exhibited good diagnostic performance.
CONCLUSIONS: Our study indicates that the CTRW model, along with the Post-FROC model, holds significant promise for the future of NACT efficacy prediction in ESCC patients.
摘要：
背景：为了评估分数阶微积分（FROC）的可行性和诊断性能，连续时间随机游走(CTRW)，扩散峰度成像（DKI），体素内不相干运动(IVIM)，单指数（MEM）和拉伸指数模型（SEM）用于预测食管鳞状细胞癌（ESCC）患者对新辅助化疗（NACT）的反应。
方法：本研究前瞻性纳入2019年7月至2023年1月期间连续接受ESCC患者的基线和随访MR成像和病理证实的cT1-4aN+M0或T3-4aN0M0，并在新辅助化疗（NACT）后接受根治性切除术。根据肿瘤消退分级（TRG）将患者分为pCR（TRG0）和非pCR（TRG123）组。前-，建立后处理和Delta治疗模型。根据不同的特征类别生成了18个预测模型，基于六个模型，通过五折交叉验证。通过使用DeLong方法比较模型的曲线下面积(AUC)。
结果：总体而言，90名患者（71名男性，19名妇女；平均年龄，64岁±6[SD]）接受NACT，并接受基线和NACT后食管MRI，pCR组29例，非pCR组61例。在18个预测模型中，前-，Post-,和Delta-CTRW模型显示出良好的预测功效(AUC=0.722、0.833和0.790)。此外,后FROC模型(AUC=0.907)也表现出良好的诊断性能。
结论：我们的研究表明，CTRW模型，以及后FROC模型，对ESCC患者NACT疗效预测的未来具有重要意义。
方法：本研究前瞻性纳入2019年7月至2023年1月期间连续接受ESCC患者的基线和随访MR成像和病理证实的cT1-4aN+M0或T3-4aN0M0，并在新辅助化疗（NACT）后接受根治性切除术。根据肿瘤消退分级（TRG）将患者分为pCR（TRG0）和非pCR（TRG123）组。前-，建立后处理和Delta治疗模型。根据不同的特征类别生成了18个预测模型，基于六个模型，通过五折交叉验证。通过使用DeLong方法比较模型的曲线下面积(AUC)。
结果：总体而言，90名患者（71名男性，19名妇女；平均年龄，64岁±6[SD]）接受NACT，并接受基线和NACT后食管MRI，pCR组29例，非pCR组61例。在18个预测模型中，前-，Post-,和Delta-CTRW模型显示出良好的预测功效(AUC=0.722、0.833和0.790)。此外,后FROC模型(AUC=0.907)也表现出良好的诊断性能。
结论：我们的研究表明，CTRW模型，以及后FROC模型，对ESCC患者NACT疗效预测的未来具有重要意义。
