Construction and evaluation of radiotherapy effect prediction model for lung cancer patients: Based on tumor volume evaluation
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摘要:
目的 分析基于肿瘤体积的肺癌患者放射治疗效果预测模型的构建与评价。 方法 选择我院2019年1月~2021年12月收治的173例肺癌患者作为研究对象。受试者接受放疗方案进行干预治疗；治疗前及放疗结束后1月行影像学检查读取病灶体积，计算患者治疗前后最大直径减少率与体积减少率，扫描并分析患者病灶区Ve、Ktrans、Kep；治疗后对患者的临床疗效进行评估。利用Pearson检验对最大直径的减少率以及体积的减少率间的相关性给予分析，采用Logistic回归模型分析Ve、Ktrans、Kep联合应用预测患者基于肿瘤体积的疗效评估模型，利用ROC曲线对各指标的单独和联合诊断在疗效方面的价值给予预测。 结果 完全缓解+部分缓解组患者最大直径减少率和体积减少率均低于疾病稳定+疾病进展组（P < 0.05）；肿瘤最大直径减少率与体积减少率与肺癌患者治疗临床疗效呈正相关关系（P < 0.05）；完全缓解+部分缓解组Ve、Ktrans、Kep均高于疾病稳定+疾病进展组（P < 0.05）；采用MRI指标联合肿瘤体积和最大径预测患者临床疗效的多元回归预测模型为Log(P)=0.685×最大直径减少率+0.651×体检减少率+0.604×Ve+0.612×Ktrans+0.644×Kep+0.849；采用MRI指标联合肿瘤体积和最大径预测患者临床疗效模型的价值明显高于各指标单独应用（P < 0.05）。 结论 通过评估肺癌患者肿瘤体积及MRI扫描检查可有效分析肺癌患者的预后质量，具有较高的应用价值。 Abstract:Objective To analyze the construction and evaluation of radiotherapy effect prediction model for lung cancer patients based on tumor volume. Methods A total of 173 patients with lung cancer treated in our hospital from January 2019 to December 2021 were selected as the research objects. The subjects received radiotherapy regimen for intervention treatment. Imaging examination was performed before treatment and 1 month after radiotherapy to read the lesion volume, calculate the maximum diameter reduction rate and volume reduction rate before and after treatment. We scaned and analyzed the lesion areas Ve, Ktrans and Kep. After treatment, the clinical efficacy of the patients was evaluated. Pearson correlation test was used to analyze the correlation between maximum diameter reduction rate and volume reduction rate. Logistic regression model was used to analyze the efficacy evaluation model of Ve, Ktrans and Kep combined application to predict patients' tumor volume. ROC curve was drawn to analyze the value of each index alone and combined application to predict patients' efficacy. Results The maximum diameter reduction rate and volume reduction rate in CR+PR group were significantly lower than those in SD+PD group (P < 0.05). There was a significant positive correlation between the maximum diameter reduction rate and volume reduction rate and the clinical efficacy of lung cancer patients (P < 0.05). Ve, Ktrans and Kep in CR+PR group were significantly higher than those in SD+PD group (P < 0.05). The multiple regression prediction model of MRI combined with tumor volume and maximum diameter was log (P)=0.685× maximum diameter reduction rate+0.651×physical examination reduction rate+0.604×Ve+ 0.612×Ktrans+0.644×Kep+0.849; The value of using MRI index combined with tumor volume and maximum diameter to predict the clinical efficacy of patients was significantly higher than that of using each index alone (P < 0.05). Conclusion The evaluation of tumor volume and MRI scan in patients with lung cancer can effectively analyze the prognosis quality of patients with lung cancer. -
Key words:
- lung cancer /
- radiotherapy /
- prediction model /
- tumor volume
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图 1 典型案例图
A: 右上肺癌的MRI影像图（男性, 60岁, 右上肺癌, T1WI呈等信号, 信号欠均匀）; B: 左上肺癌胸部CT影像图（男性, 72岁, 增强扫描后左上肺病灶明显增强）.
Figure 1. Typical case diagrams.
表 1 不同疗效患者肿瘤最大直径减少率与体积减少率调查结果
Table 1. The survey results of tumor maximum diameter reduction rate and tumor volume reduction rate in patients with different curative effects(Mean±SD)
疗效 最大直径减少率（%） 体积减少率（%） CR+PR（n=101） 58.39±5.03 65.49±7.94 SD+PD（n=72） 28.93±4.39 32.83±6.95 t 30.580 21.870 P < 0.001 < 0.001 PD: 疾病进展; SD: 疾病稳定; PR: 部分缓解; CR: 完全缓解. 
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表 2 不同疗效患者MRI指标调查结果
Table 2. Survey results of MRI indicators in patients with different curative effects
疗效 Ve（%） Ktrans（min） Kep（min） CR+PR（n=101） 0.63±0.05 0.39±0.03 0.60±0.03 SD+PD（n=72） 0.51±0.04 0.31±0.03 0.51±0.04 t 14.251 13.353 16.130 P < 0.001 < 0.001 < 0.001
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表 3 MRI指标联合肿瘤体积和最大径预测病人临床疗效模型
Table 3. MRI indicators combined with tumor volume and maximum diameter to predict the clinical efficacy model of patients
指标 b SE χ2 P OR 95%CI 下限 上限 最大直径减少率 0.685 0.231 8.793 0.003 1.984 1.261 3.120 体积减少率 0.651 0.203 10.284 0.001 1.917 1.288 2.854 Ve 0.604 0.191 10.000 0.002 1.829 1.258 2.660 Ktrans 0.612 0.214 8.179 0.004 1.844 1.212 2.805 Kep 0.644 0.198 10.579 0.001 1.904 1.292 2.807 常数项 0.849 0.211 16.190 < 0.001 2.337 1.546 3.534
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表 4 各指标单独及联合应用预测患者临床疗效价值
Table 4. The individual and combined application of each index to predict the value of clinical curative effect of patients
指标 区域 标准误差 渐近显著性 95% CI 下限 上限 最大直径减少率 0.844 0.033 < 0.001 0.779 0.908 体积减少率 0.834 0.033 < 0.001 0.770 0.898 Ve 0.841 0.033 < 0.001 0.777 0.905 Ktrans 0.882 0.029 < 0.001 0.825 0.938 Kep 0.848 0.032 < 0.001 0.786 0.910 联合应用 0.948 0.020 < 0.001 0.910 0.987
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