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第46卷第8期       冯  婕,渠    强,雷心仪,等. 冠状动脉造影及介入治疗患者辐射剂量的影响因素分析及预测模型
                  2026年8月               构建[J]. 南京医科大学学报(自然科学版),2026,46(8):1218-1227,1268                ·1223 ·


                架最小直径、手术时间和透视时间。随机森林+最                            三酯、HDL⁃C、LVDd、LVEF、手术时间和透视时间。
                优子集回归模型纳入的候选变量为年龄、BMI、甘油                          随机森林+LASSO回归模型纳入的候选变量为BMI、

                                    表2 不同变量筛选和建模策略下辐射剂量预测模型的构建及性能比较
                Table 2  Development and performance comparison of radiation dose prediction models using different variable selection
                        and modeling strategies

                                                                                      Training set    Testing set
                     Algorithm         Initially included variables  Finally included variables
                                                                                  RMSE  MAE   R 2  RMSE  MAE  R 2
                Random forest algorithm  Age,BMI,SBP,neurologic symptoms,  -        -     -   -     -    -    -
                                   TC,TG,HDL⁃C,LDL⁃C,eGFR,
                                   hs⁃cTnT,LVDd,LVDs,LVEF,minimum
                                   stent diameter,procedure time,fluo⁃
                                   roscopy time
                Random forest algorithm+  BMI,TG,HDL⁃C,LVDd,LVDs,mini⁃ BMI,HDL ⁃ C,LVDd,proce⁃  289.5 168.7 0.38  174.1  139.7 0.51
                univariate linear regression mum stent diameter,procedure time, dure time,fluoroscopy time
                                   fluoroscopy time
                Random forest algorithm+  Age,BMI,TG,HDL⁃C,LVDd,LVEF, Age,BMI,TG,HDL⁃C,LVDd,  282.8  168.8 0.41  170.1  136.1 0.55
                best subset regression  procedure time,fluoroscopy time  LVEF,procedure time,fluoros⁃
                                                             copy time
                Random forest algorithm + BMI,neurologicsymptoms,TG,HDL⁃C, BMI,neurologic symptomsyes,  287.5  169.7 0.39  175.9  141.4 0.50
                LASSO regression   LVDd,procedure time,fluoroscopy HDL⁃C,LVDd,procedure time,
                                   time                      fluoroscopy time
                   BMI:body mass index;eGFR:estimated glomerular filtration rate;HDL⁃C:high⁃density lipoprotein cholesterol;hs⁃cTnT:high⁃sensitivity cardiac
                troponin T;LASSO:least absolute shrinkage and selection operator;LDL⁃C:low⁃density lipoprotein cholesterol;LVDd:left ventricular end⁃diastolic
                diameter;LVDs:left ventricular end⁃systolic diameter;LVEF:left ventricular ejection fraction;MAE:mean absolute error;RMSE:root mean square
                error;SBP:systolic blood pressure;TC:total cholesterol;TG:triglyceride.

                              Fluoroscopy time                                Fluoroscopy time
                               Procedure time                                        eGFR
                                    HDL⁃C                                           HDL⁃C
                                     LVDd                                      Procedure time
                                      BMI                                             SBP
                                   hs⁃cTnT                                           LVDd
                                       TG                                             BMI
                     Minimum luminal area stenosis                                   LVDs
                                       TC                                             TG
                                    LDL⁃C                                          hs⁃cTnT
                                     LVDs                                             Age
                           Neurologic symptoms                                       LVEF
                    Number of conventional balloons                                 Lp(a)
                              Total stent length                                  Heart rate
                         Minimum stent diameter                                        TC
                 Number of diseased coronary arteries                               CK⁃MB
                                Tube voltage                                         DBP
                         Other atypical symptoms                                    LDL⁃C
                                    Lp(a)                                          Glucose
                             ECG abnormalities                       Minimum luminal area stenosis
                                      DBP                             Special cardiac examinations
                                Beta⁃blocker                                    Tube voltage
                                      SBP                                     Duration of CAD
                             Cigarettes per day                              Cigarettes per day
                                      CCB                               Number of coronary stents
                                  Heart rate                                 Total stent length
                    Number of drug⁃coated balloons                         Neurologic symptoms
                                    CK⁃MB                         Number of treated coronary vessels
                      Special cardiac examinations                       Minimum stent diameter
                       Coronary artery calcification                              Palpitation
                                         0  2.5  5.0  7.5  10.0 12.5                     0  5  10 15 20 25 30 35
                                          Mean decrease in accuracy(%)                      Increase in node purity(×10 )
                                                                                                             5
                        A:Variable importance measured by mean decrease in accuracy. B:Variable importance measured by increase in node purity.
                                         图2 随机森林模型中辐射剂量潜在影响因素的重要性排序
                       Figure 2  Variable importance of potential predictors of radiation dose based on the random forest model
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