基于MRI定量、病理及血细胞参数的ⅡB～Ⅲ期宫颈癌同步放化疗疗效预测模型构建及外部验证

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• 临床研究 •

王雅静李伟兰程慧欣崔立强虞红郭艳娟谢宗源

WANG Y J, LI W L, CHENG H X, et al. The development and external validation of a model based on MRI quantification, pathology, and blood cell parameters to predict the efficacy of concurrent chemoradiotherapy for stage ⅡB-Ⅲ cervical cancer[J]. Chin J Magn Reson Imaging, 2023, 14(8): 86-93.引用本文：王雅静, 李伟兰, 程慧欣, 等. 基于MRI定量、病理及血细胞参数的ⅡB～Ⅲ期宫颈癌同步放化疗疗效预测模型构建及外部验证[J]. 磁共振成像, 2023, 14(8): 86-93. DOI:10.12015/issn.1674-8034.2023.08.014.

摘要

[摘要] 目的探索构建基于MRI定量、病理及血细胞参数的ⅡB～Ⅲ期宫颈癌同步放化疗疗效预测模型，并评估该模型的价值。材料与方法 回顾性分析华北理工大学附属医院2020年3月至2022年6月的151例宫颈癌患者临床资料，将同期来自河北省退役军人总医院的93例宫颈癌患者资料用于模型外部验证。用最小绝对收缩和选择算子（least absolute shrinkage and selection operator, LASSO）算法回归筛选同步放化疗疗效相关风险因素。构建同步放化疗疗效的风险因素模型，用一致性指数（consistency index, C-index）、校准曲线、平均绝对误差（mean absolute error, MAE）和决策曲线分析（decision curve analysis, DCA）评价模型价值。结果 LASSO回归分析结果显示，容积转运常数（K^trans）升高、表观扩散系数（apparent dispersion coefficient, ADC）升高和灌注相关体积分数（f）升高是同步放化疗后客观缓解（objective remission, OR）的独立保护因素，国际妇产科联盟（International Federation of Gynecology and Obstetrics, FIGO）分期高、淋巴结转移、血管外细胞外间隙容积分数（Ve）升高、慢速ADC（D）升高和单核细胞/淋巴细胞值（monocyte to lymphocyte ratio, MLR）升高是同步放化疗后OR的独立危险因素。模型F（由FIGO分期、淋巴结转移、K^trans、Ve、ADC、D、f和MLR构成）的C-index和MAE分别为0.984和0.033，均高于模型S（由K^trans、Ve、ADC、D和f构成，0.940和0.020）和模型T（由FIGO分期、淋巴结转移和MLR构成，0.897和0.020）。校准曲线显示，模型S的校准曲线与理想曲线重合度较模型F和模型T略高。DCA显示，在全风险阈值范围内，模型F的净收益高于模型S和模型T。模型的验证结果显示，模型F的C-index为0.996，高于模型S（0.942）和模型T（0.917）；MAE为0.017，低于模型S（0.043）和模型T（0.043）。校准曲线显示，模型F和模型S的校准曲线与理想曲线重合度较模型T高。DCA显示，在全风险阈值范围内，模型F的净收益高于模型S和模型T。结论 FIGO分期、淋巴结转移、K^trans、Ve、ADC、D、f和MLR与ⅡB～Ⅲ期宫颈癌同步放化疗疗效有关。基于上述指标构建的模型有助于预测同步放化疗疗效，其效能高于单纯MRI定量参数模型、病理和血细胞参数模型。

[Abstract] Objective To develop and test a model for predicting the efficacy of concurrent chemoradiotherapy for stage ⅡB-Ⅲ cervical cancer based on quantitative MRI, pathology, and blood cell parameters.Materials and Methods From March 2020 to June 2022, clinical data from 151 cervical cancer patients at the North China University of Science and Technology Affiliated Hospital were analyzed retrospectively, and data from 93 cervical cancer patients at the Hebei General Hospital for Veterans were used for model external validation. To screen for risk factors associated with the efficacy of concurrent chemoradiotherapy, least absolute shrinkage and selection operator (LASSO) regression was used. The value of a risk factor model for the efficacy of concurrent chemoradiotherapy was evaluated using the consistency index (C-index), calibration curve, mean absolute error (MAE), and decision curve analysis (DCA).Results LASSO regression analysis revealed that elevated volume transport constant (K^trans), apparent dispersion coefficient (ADC), and perfusion-related volume fraction (f) were independent factors for objective remission (OR) following concurrent chemoradiotherapy. High International Federation of Gynecology and Obstetrics (FIGO) staging, lymph node metastasis, elevated extravascular extracellular volume ratio (Ve), elevated slow ADC (D), and elevated monocyte to lymphocyte ratio (MLR) were all independent risk factors for OR after concurrent chemoradiotherapy. The C-index and MAE of model F (which included FIGO staging, lymph node metastasis, K^trans, Ve, ADC, D, f, and MLR) were 0.984 and 0.033, respectively, which were higher than those of model S (which included K^trans, Ve, ADC, D, and f; 0.940, 0.020) and model T (which included FIGO staging, lymph node metastasis, and MLR; 0.897, 0.020). The calibration curves showed that the calibration curve for model S overlapped with the ideal curve slightly better than the calibration curves for models F and T. Over the entire risk threshold range, the DCA showed that model F had a higher net benefit than model S and model T. Model F had a higher C-index (0.996) than model S (0.942) and model T (0.917) and a lower MAE (0.017) than model S (0.043) and model T (0.043), according to the model validation results. The calibration curves showed that the calibration curves for model F and model S overlapped with the ideal curve more closely than model T. Over the entire risk threshold range, the DCA showed that model F had a higher net benefit than model S and model T.Conclusions FIGO staging, lymph node metastasis, K^trans, Ve, ADC, D, f, and MLR are associated with the efficacy of concurrent chemoradiotherapy for stage ⅡB-Ⅲ cervical cancer. The model based on the above indicators can aid in predicting the efficacy of concurrent chemoradiotherapy, and its efficacy is higher than that of the MRI-only quantitative parameter model and the pathology and blood cell parameter model.

[关键词] 宫颈癌；同步放化疗；磁共振成像；模型；病理；血细胞；疗效预测；外部验证

[Keywords] cervical cancer；concurrent chemoradiotherapy；magnetic resonance imaging；model；pathology；blood cells；efficacy prediction；external validation

作者信息

王雅静 ¹ 李伟兰 ¹ 程慧欣 ² 崔立强 ² 虞红 ³ 郭艳娟 ⁴ 谢宗源 ^1*

¹ 华北理工大学附属医院核磁室，唐山　063000

² 河北省退役军人总医院CT/MRI室，邢台　054000

³ 唐山市曹妃甸区医院核磁室，唐山　063200

⁴ 华北理工大学附属医院妇科，唐山　063000

通信作者：谢宗源，E-mail：xied126@126.com

作者贡献声明：谢宗源设计本研究方案，对稿件内容进行审校；王雅静设计本研究方案，起草和撰写稿件，获取、分析及解释本研究的数据，对稿件内容进行质量控制；李伟兰、程慧欣、崔立强、虞红和郭艳娟获取、分析或解释本研究的数据，对稿件内容进行质量控制；李伟兰和王雅静获得了河北省卫生健康委医学科学研究项目资助；全体作者都同意发表最后的修改稿，同意对本研究的所有方面负责，确保本研究的准确性和诚信。

出版信息

基金项目： 河北省卫生健康委医学科学研究项目 20201245，20231255

收稿日期：2023-03-02

接受日期：2023-07-21

中图分类号：R445.2 R737.33

文献标识码：A

DOI: 10.12015/issn.1674-8034.2023.08.014

引用本文：王雅静, 李伟兰, 程慧欣, 等. 基于MRI定量、病理及血细胞参数的ⅡB～Ⅲ期宫颈癌同步放化疗疗效预测模型构建及外部验证[J]. 磁共振成像, 2023, 14(8): 86-93. DOI:10.12015/issn.1674-8034.2023.08.014.

正文

0 前言

宫颈癌是一种高发于50～55岁女性的恶性肿瘤^[¹^]。据调查^[²^]显示，全球每年约53万宫颈癌新发病例，约27万死亡病例。中国宫颈癌发病率为10.87%，死亡率为3.15%，严重威胁着女性的生命安全^[³^]。《宫颈癌临床实践指南》^[⁴^]中建议局部晚期宫颈癌患者应首选同步放化疗，但因肿瘤异质性及个体差异，并非全部患者均能从同步放化疗中获益，约30%～50%患者治疗失败^[⁵^,⁶^,⁷^]。此外，若初始同步放化疗治疗失败，后续治疗受限严重^[⁸^,⁹^]。因此，早期准确预测宫颈癌同步放化疗疗效，对于其治疗方案的制订及后续调整有着重要意义。

宫颈癌血流灌注、血管通透性及细胞代谢等功能信息与放化疗疗效相关，常规MRI不能反映上述信息，因此，其在评价放化疗疗效方面存在一定不足。目前，有研究^[¹⁰^,¹¹^,¹²^,¹³^]用体素内不相干运动扩散加权成像（intravoxel incoherent motion-diffusion weighted imaging, IVIM-DWI）或动态对比增强（dynamic contrast enhancement, DCE）MRI参数评价宫颈癌同步放化疗疗效，因参数测量存在人为因素差异、感兴趣区（region of interest, ROI）选择重复性差及b值选取尚无统一标准等，结果不尽相同。此外，较少研究同时用IVIM-DWI和DCE-MRI参数评价宫颈癌同步放化疗疗效，因此，尚不能确定各参数与同步放化疗疗效的强弱关系。中性粒细胞、淋巴细胞及单核细胞等在肿瘤诱发的免疫反应中发挥着重要作用，由上述细胞计数计算的相关指数与肿瘤预后密切相关^[¹⁴^,¹⁵^,¹⁶^,¹⁷^,¹⁸^]。近年来，多数研究^[¹⁹^,²⁰^,²¹^]证实部分病理及血细胞参数与宫颈癌治疗预后有关。目前，联合IVIM-DWI和DCE-MRI定量、病理及血细胞参数，综合分析宫颈癌同步放化疗疗效，构建预测模型并外部验证模型效能的研究较少。本研究探索回顾性分析ⅡB～Ⅲ期宫颈癌同步放化疗前IVIM-DWI和DCE-MRI定量、病理及血细胞参数资料，筛选与同步放化疗疗效相关的风险因素，构建疗效预测模型并外部验证模型效能，为宫颈癌的精准治疗提供参考。

1 材料与方法

1.1 一般资料

本研究为回顾性研究，遵守《赫尔辛基宣言》，经华北理工大学附属医院和河北省退役军人总医院医学伦理委员会批准，免除受试者知情同意，批准文号分别为20200228011和200224001。分析华北理工大学附属医院和河北省退役军人总医院2020年3月至2022年6月的244例宫颈癌患者临床资料。将来自华北理工大学附属医院的151例宫颈癌患者的资料用于模型构建（训练组），将来自河北省退役军人总医院的93例宫颈癌患者资料用于模型验证（验证组）。纳入标准：（1）病理检查确诊为宫颈癌；（2）国际妇产科联盟（International Federation of Gynecology and Obstetrics, FIGO）ⅡB～Ⅲ期；（3）首次接受同步放化疗，且于同步放化疗前1周内接受MRI和血常规检查；（4）临床资料完整。排除标准：（1）同步放化疗前接受其他抗肿瘤治疗；（2）自身免疫性疾病或血液系统疾病；（3）其他恶性肿瘤；（4）感染性疾病；（5）未完成同步放化疗方案。

1.2 MRI检查

采用飞利浦Ingenia 3.0 T全数字MRI（Philips Electronics Inc., Netherlands）扫描仪和体部表面线圈，于同步放化疗前1周内行盆腔常规MRI、IVIM-DWI和DCE-MRI扫描。常规MRI扫描包括矢状位、冠状位、轴位T2WI和轴位T1WI序列；IVIM-DWI扫描取扩散敏感系数b值分别为0、50、100、150、200、300、400、600、800和1000 s/mm²时的轴位DWI；DCE-MRI扫描取T1 THRIVE序列，扫描范围包括子宫、附件及阴道。由2名高年资副主任医师独立分析MRI检查相关图像（图1）。MRI扫描参数详见表1。

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图1 女，65岁，鳞状细胞癌，FIGO ⅢA期。1A：T2WI图示宫颈弥漫性高信号，累及宫旁；1B：DCE-MRI（K^trans、Kep和Ve）伪彩图；1C：ADC图；1D：IVIM-DWI参数图。FIGO：国际妇产科联盟；DCE：动态对比增强；K^trans：容积转运常数；Kep：回流速率常数；Ve：血管外细胞外间隙容积分数；ADC：表观扩散系数；IVIM：体素内不相干运动；DWI：扩散加权成像；f：灌注相关体积分数；D：慢速ADC；D^*：快速ADC。
Fig. 1 Female, 65 years old, squamous cell carcinoma, FIGO stage ⅢA. 1A: T2WI image shows diffuse high signal in the cervix with parametrial involvement; 1B: DCE-MRI (K^trans, Kep, and Ve) pseudo-color image; 1C: ADC image; 1D: IVIM-DWI parametric image. FIGO: International Federation of Gynecology and Obstetrics; DCE: dynamic contrast enhancement; K^trans: volume transport constant; Kep: reflux rate constant; Ve: extravascular extracellular space fraction; ADC: apparent diffusion coefficient; IVIM: intravoxel incoherent motion; DWI: diffusion weighted imaging; f: perfusion-related volume fraction; D: slow ADC; D^*: fast ADC.

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表1 MRI扫描参数
Tab. 1 MRI scan parameters

1.3 图像分析

IVIM-DWI图像分析：工作站中取b值为800 s/mm²的IVIM-DWI序列，取肿瘤的最大横截面和上下层面（相邻1～2个层面内），避开囊性病变、出血、坏死和宫颈管区域，沿肿瘤边缘勾画3个ROI，ROI大小至少为肿瘤面积的2/3。收集IVIM-DWI定量参数，包括表观扩散系数（apparent dispersion coefficient, ADC）、慢速ADC（D）、快速ADC（D^*）和灌注相关体积分数（f）。DCE-MRI图像分析：将多翻转角和多期动态增强扫描序列图像导入血流动力学后处理软件，在髂动脉血管内勾画圆形动脉输入函数（arterial input function, AIF）的ROI，获取时间浓度曲线。在肿瘤的最大层面明显强化区，避开血管、囊性病变、出血和坏死等区域勾画ROI，同一病灶勾画3次。以AIF时间浓度曲线为标准，用Extended Tofls linear双室模型进行微血管渗透性定量分析。收集DCE-MRI定量参数，包括回流速率常数（Kep）、容积转运常数（K^trans）和血管外细胞外间隙容积分数（Ve）。IVIM-DWI和DCE-MRI参数均取3次测量平均值，最终将2名医师测量的结果平均值纳入研究分析。

1.4 血液学检测

放化疗前1周内抽取患者空腹时肘部静脉血5 mL，用血细胞分析仪检测中性粒细胞计数（×10⁹/L）、淋巴细胞计数（×10⁹/L）、单核细胞计数（×10⁹/L）、血小板计数（×10⁹/L）和血红蛋白（g/L）含量。计算中性粒细胞/淋巴细胞值（neutrophil to lymphocyte ratio, NLR）、血小板/淋巴细胞值（platelet to lymphocyte ratio, PLR）、单核细胞/淋巴细胞值（monocyte to lymphocyte ratio, MLR）、血小板/单核细胞值（platelet to monocyte ratio, PMR）、系统免疫炎症指数（systemic immune inflammation index, SII）和全身炎症反应指数（systemic inflammatory response index, SIRI）。SII=中性粒细胞×血小板/淋巴细胞，SIRI=中性粒细胞×单核细胞/淋巴细胞。

1.5 同步放化疗方案及疗效评价

所有患者均给予同步放化疗，放疗采用盆腔外照射放疗（三维适形放疗，2 Gy/次，5次/周，持续5周）联合腔内后装放疗（¹⁹²Ir腔内放疗，A点剂量6～7 Gy/次，1次/周，4～6次）；同步化疗（顺铂，40 mg/m²/周）。

参照文献^[²²^]，根据患者治疗后肿瘤病灶大小及状态持续时间将其分为完全缓解、部分缓解、疾病稳定和疾病进展。本研究将完全缓解和部分缓解定义为客观缓解（objective remission, OR）。

1.6 统计学分析

用SPSS 23.0软件和R 4.1.1软件行统计学分析。正态分布的计量资料用平均值±标准差（x¯±s）表示，用独立样本t检验比较两组间差异；非正态分布的计量资料用中位数和四分位数间距[M（P25，P75）]表示，用Mann-Whitney U检验比较两组间差异。计数资料用例（%）表示，用χ²检验比较组间差异。用组内相关系数（intra-class correlation coefficient, ICC）分析2名阅片医师测量的MRI定量参数值的一致性，ICC≥0.75提示一致性良好。用最小绝对收缩和选择算子（least absolute shrinkage and selection operator, LASSO）算法回归（“glmnet”包）筛选同步放化疗疗效相关风险因素。用logistic回归输入法（“rms”包中“lrm”函数）构建同步放化疗疗效的风险因素模型，用“nomogram”函数展示模型。用一致性指数（consistency index, C-index）评价模型的区分度，用校准曲线和平均绝对误差（mean absolute error, MAE）评价模型的精准度，用决策曲线分析（decision curve analysis, DCA；“rmda”包）评价模型的临床应用价值。P＜0.05为差异有统计学意义。

2 结果

2.1 训练组和验证组临床特征比较

训练组和验证组的年龄、体质量指数（body mass index, BMI）、FIGO分期、病理类型、肿瘤直径、淋巴结转移占比、ADC、D、f、Kep、K^trans、Ve、中性粒细胞计数、淋巴细胞计数、单核细胞计数、血小板计数、血红蛋白、NLR、PLR、MLR、PMR、SII和SIRI差异均无统计学意义（P＞0.05）。训练组的D^*高于验证组（P＜0.05），见表2。2名阅片医师测量的MRI定量参数（ADC、D、D^*、f、Kep、K^trans和Ve）的ICC分别为0.959、0.844、0.885、0.950、0.996、0.970和0.952，均＞0.75，提示一致性良好。

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表2 训练组和验证组基线资料比较
Tab. 2 Comparison of baseline information between the training and testing groups

2.2 OR组和非OR组临床特征比较

151例患者同步放化疗后39例完全缓解，58例部分缓解，35例疾病稳定，19例疾病进展。根据同步放化疗后是否达到OR将患者分为OR组（n=97）和非OR组（n=54）。OR组和非OR组的年龄、BMI、病理类型、肿瘤直径、D^*、Kep、中性粒细胞计数、淋巴细胞计数、单核细胞计数、血小板计数、NLR、PLR、MLR、PMR和SII差异均无统计学意义（P＞0.05）。OR组的FIGO ⅡB期占比、ADC、f、K^trans和血红蛋白均高于非OR组，淋巴结转移占比、D、Ve和SIRI均低于非OR组（P＜0.05），详见表3。

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表3 OR组和非OR组临床特征比较
Tab. 3 Comparison of clinical characteristics between the OR and non-OR groups

2.3 同步放化疗疗效相关风险因素

将同步放化疗疗效作为因变量（OR=0，非OR=1），将年龄、BMI、FIGO分期（ⅡB期=0，ⅢA期=1，ⅢB期=2，ⅢC1期=3，ⅢC2期=4）、病理类型（鳞状细胞癌=0，腺癌=1）、肿瘤直径、淋巴结转移（无=0，有=1）、IVIM-DWI参数、DCE-MRI参数和血液学参数作为自变量，当λ为0.053时（λ取值见图2A），LASSO回归分析结果显示，FIGO分期高、淋巴结转移、Ve升高、D升高和MLR升高是同步放化疗后OR的独立危险因素，K^trans升高、ADC升高和f升高是同步放化疗后OR的独立保护因素，详见图2B和表4。

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图2 LASSO回归分析结果。2A为λ取值范围，虚线对应分别在lambda.min和lambda.1se筛选变量的个数；2B为各因素系数，虚线对应分别在lambda.min和lambda.1se筛选变量的个数。LASSO：最小绝对收缩和选择算子。
Fig. 2 Results of LASSO regression analysis. 2A: The range of λ values, the dashed line corresponds to the number of screening variables in lambda.min and lambda1se, respectively; 2B: The coefficient of each factor, the dashed line corresponds to the number of screening variables in lambda.min and lambda.1se, respectively. LASSO: least absolute shrinkage and selection operator.

点击查看表格

表4 各因素LASSO回归分析系数
Tab. 4 Coefficients of LASSO regression analysis for each factor

2.4 模型构建及评价

预测同步放化疗疗效的模型F公式为lnP/（1-P）=4.705+1.027×FIGO分期+2.845×淋巴结转移-7.749×K^trans+9.097×Ve-25.229×ADC+9.890×D-7.790×f+1.756×MLR（图3A）；模型S公式为lnP/（1-P）=1.592-4.497×K^trans+6.062×Ve-16.167×ADC+13.569×D-11.342×f（图3B）；模型T公式为lnP/（1-P）=-3.153+0.699×FIGO分期+2.810×淋巴结转移+1.517×MLR（图3C）。模型F的C-index为0.984（95% CI：0.970～0.998），高于模型S（0.940，95% CI：0.906～0.974；Z=2.916，P=0.004）和模型T（0.897，95% CI：0.839～0.956；Z=3.194，P=0.001）。校准曲线显示，模型S的校准曲线与理想曲线重合度较模型F和模型T略高（图3D、3E、3F）。模型F的MAE为0.033，高于模型S（0.020）和模型T（0.020）。DCA显示，在全风险阈值范围内，模型F的净收益高于模型S和模型T（图3G）。

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图3 模型及评价结果。3A、3B、3C分别为模型F、模型S、模型T；3D、3E、3F分别为模型F、模型S、模型T的校准曲线；3G为决策曲线分析（DCA）结果。FIGO为国际妇产科联盟；K^trans为容积转运常数；Ve为血管外细胞外间隙容积分数；ADC为表观扩散系数；D为慢速ADC；f为灌注相关体积分数；MLR为单核细胞/淋巴细胞值；OR为客观缓解。
Fig. 3 Model and evaluation results. 3A, 3B, and 3C are model F, model S, and model T, respectively; 3D, 3E, and 3F are the calibration curves of model F, model S, and model T, respectively; 3G is the result of decision curve analysis (DCA). FIGO: International Federation of Gynecology and Obstetrics; K^trans: volume transport constant; Ve: extravascular extracellular space fraction; D: slow ADC; f: perfusion-related volume fraction; MLR: monocyte to lymphocyte ratio; OR: objective remission.

2.5 模型外部验证结果

93例患者用于模型外部验证，其中57例同步放化疗后达到OR，36例同步放化疗后未达到OR。模型F的C-index为0.996（95% CI：0.990～1.000），高于模型S（0.942，95% CI：0.898～0.986；Z=2.568，P=0.010）和模型T（0.917，95% CI：0.849～0.985；Z=2.284，P=0.022）。校准曲线显示，模型F和模型S的校准曲线与理想曲线重合度较模型T高（图4A～4C）。模型F的MAE为0.017，低于模型S（0.043）和模型T（0.043）。DCA显示，在全风险阈值范围内，模型F的净收益高于模型S和模型T（图4D）。

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图4 模型外部验证结果。4A、4B、4C分别为模型F、模型S、模型T的校准曲线；4D为决策曲线分析（DCA）结果。
Fig. 4 Model external validation results. 4A, 4B, and 4C are the calibration curves of model F, model S, and model T, respectively; 4D is the result of decision curve analysis (DCA).

3 讨论

本研究回顾性分析了ⅡB～Ⅲ期宫颈癌同步放化疗前IVIM-DWI和DCE-MRI定量参数、病理及血细胞参数资料，筛选与同步放化疗疗效相关的风险因素，构建疗效预测模型并外部验证模型效能。结果显示，K^trans、ADC和f是同步放化疗后OR的独立保护因素，FIGO分期、淋巴结转移、Ve、D和MLR是同步放化疗后OR的独立危险因素。由上述风险因素构建的同步放化疗疗效预测模型F的效能（训练组：C-index=0.984，MAE=0.033；验证组：C-index=0.996，MAE=0.017）高于单纯影像学参数模型S（训练组：C-index=0.940，MAE=0.020；验证组：C-index=0.942，MAE=0.043）和单纯临床模型T（训练组：C-index=0.897，MAE=0.020；验证组：C-index=0.917，MAE=0.043），给出具体的指标C-index、AUC等。

3.1 IVIM-DWI和DCE-MRI在宫颈癌同步放化疗疗效预测中的应用

预测宫颈癌同步放化疗疗效对于精准治疗及后续治疗方案的调整，提高治疗有效率等有着重要作用。目前，已有相关研究^[²³^,²⁴^,²⁵^]用IVIM-DWI或DCE-MRI参数预测宫颈癌同步放化疗疗效。本研究结果显示，K^trans升高、ADC升高和f升高是同步放化疗后OR的独立保护因素，Ve升高和D升高是同步放化疗后OR的独立危险因素。相关研究^[²⁶^,²⁷^]表明ADC值越高，宫颈癌同步放化疗疗效越好，其可用于预测同步放化疗疗效。梁彬玲等^[²⁸^]证实宫颈癌同步放化疗敏感组的D值低于不敏感组，其可用于局部晚期宫颈癌同步放化疗早期疗效预测；D^*及f均与局部晚期宫颈癌同步放化疗早期疗效无关。LIU等^[²⁹^]证实同步放化疗前K^trans与宫颈鳞状细胞癌肿瘤消退率呈正相关关系，可用于同步放化疗疗效预测，但Kep和Ve对于同步放化疗疗效无预测价值^[³⁰^]。本研究结果中K^trans升高和ADC升高是同步放化疗后OR的独立保护因素，D升高是同步放化疗后OR的独立危险因素，与上述研究结果一致。此外，本研究结果还显示f升高是同步放化疗后OR的独立保护因素，Ve升高是同步放化疗后OR的独立危险因素，与梁彬玲等^[²⁸^]、LU等^[³⁰^]结果存异，推测其原因是上述研究的样本量偏小，分析结果可能存在一定偶然性，后续将开展大样本、多中心研究予以验证。

3.2 血细胞参数在宫颈癌同步放化疗疗效预测中的应用

本研究结果显示MLR升高是同步放化疗后OR的独立危险因素。LI等^[³¹^]和TAGUCHI等^[³²^]证实NLR和MLB升高与宫颈癌患者总生存期和无进展生存期缩短有关。HUANG等^[³³^]和LIU等^[³⁴^]证实SII可预判宫颈癌生存情况。此外，还有研究^[³⁵^]显示宫颈癌同步放化疗期间中性粒细胞及淋巴细胞最低值与患者总生存期密切相关。目前，关于宫颈癌同步放化疗前血细胞参数与疗效的报道偏少，本研究结果显示MLR升高是同步放化疗后OR的独立危险因素，与既往报道^[³⁶^]结果一致；NLR、SII和SIRI与同步放化疗后OR无关，与赵玉瑶^[³⁶^]结果存异，推测该差异与样本量大小及纳入研究因素个数等有关。

3.3 基于MRI定量、病理及血细胞参数的宫颈癌同步放化疗疗效预测模型

目前，鲜有综合同步放化疗前IVIM-DWI及DCE-MRI定量参数、病理和血细胞参数的宫颈癌疗效预测模型。本研究结果显示，由FIGO分期、淋巴结转移、K^trans、Ve、ADC、D、f和MLR构成的模型F的C-index高于由K^trans、Ve、ADC、D和f构成的模型S和由FIGO分期、淋巴结转移和MLR构成的模型T，提示模型F的区分度更高；模型S的校准曲线与理想曲线重合度较模型F和模型T略高，模型F的MAE高于模型S和模型T，上述结果提示模型F的精准度略差；在全风险阈值范围内，模型F的净收益高于模型S和模型T，提示模型F的临床应用价值更高。外部数据验证结果显示，模型F的C-index高于模型S和模型T；模型F和模型S的校准曲线与理想曲线重合度较模型T高；模型F的MAE低于模型S和模型T；在全风险阈值范围内，模型F的净收益高于模型S和模型T。上述结果表明模型F对于ⅡB～Ⅲ期宫颈癌同步放化疗疗效预测有一定价值。

3.4 不足与展望

本研究尚存在一定不足：第一，模型未经多中心数据验证，后续将收集更多中心的外部验证数据，验证模型的效能；第二，本研究旨在尽可能快速预测同步放化疗疗效，仅纳入了同步放化疗前MRI定量参数、病理及血细胞参数，未将同步放化疗期间指标纳入研究进行分析，后续考虑将其纳入研究，探究是否可提高模型效能。

4 结论

综上所述，FIGO分期、淋巴结转移、K^trans、Ve、ADC、D、f和MLR与ⅡB～Ⅲ期宫颈癌同步放化疗疗效有关。基于上述指标构建的模型有助于预测同步放化疗疗效，其效能高于单纯MRI定量参数模型、病理和血细胞参数模型。

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