基于多b值擴散加權成像的多模型擬合在膠質瘤術前分級中的價值
發(fā)布時間:2018-05-15 20:09
本文選題:膠質瘤 + 磁共振; 參考:《南方醫(yī)科大學》2017年博士論文
【摘要】:目的DWI序列相關參數(shù)評價膠質瘤有很高價值,但是不同的擬合模型參數(shù)診斷之間有很大差異,不同的ROI勾畫方法也有很大差異。我們的研究目的是探討哪些參數(shù)、哪種ROI勾畫方法在膠質瘤術前分級中更有價值。方法46例經病理證實的膠質瘤患者,術前行磁共振常規(guī)序列檢查、波譜檢查、多b值擴散加權成像、DSC灌注檢查和常規(guī)序列增強。多b值DWI序列進行單指數(shù)、雙指數(shù)、拉伸指數(shù)和三指數(shù)的多模型擬合,ROI勾畫采用Hot spot法、2D法和3D法三種。比較各擬合模型參數(shù)不同ROI勾畫方法在術前鑒別膠質瘤高級別組與低級別組中的價值,篩選出敏感性和特異性較高的方案。同時比較各參數(shù)在鑒別膠質瘤各級之間的價值,篩選最佳方案。結果高級別與低級別膠質瘤波譜參數(shù)比較(以read1為例),腫瘤側代謝物參數(shù)在高級別與低級別組之間比較無統(tǒng)計學差異(P=0.412,NAA/Cr;P=0.148,Cho/Cr;P=0.306,Cho/NAA)。DSC灌注參數(shù)比較,腫瘤側高級別組與低級別組比較,有明顯統(tǒng)計學差異(P=0.042,rCBF-+CMax;P=0.030,rCBF-rCBFMax;P=0.002,rCBV-+CMax;P=0.001,rCBV-rCBVMax;P=0.001,MTT-+CMax;P=0.000,MTT-MTTMax)。單指數(shù)模型擬合Hot spot ROI比較,ADC-ADCmin值在高級別組與低級別組間有差異(P=0.001),ADC-+CMax值在組間比較無差異(P=0.273);2D ROI相關參數(shù)比較,ADC-P10-2D在組間有統(tǒng)計學差異(P=0.035),其余參數(shù)無統(tǒng)計學差異。3DROI 相關參數(shù)比較,ADC-mean-3D、ADC-P5-3D 和 ADC-P10-3D 在組間有統(tǒng)計學差異(P=0.041,ADC-mean-3D;P=0.009,ADC-P5-3D;P=0.005,ADC-P10-3D),其余參數(shù)無統(tǒng)計學差異。雙指數(shù)模型擬合HotspotROI比較,D-Dmin值和f-fMax在高級別組與低級別組間有差異(P=0.000,D-Dmin;P=0.002,f-fMax),其余參數(shù)在組間比較無差異;2D ROI相關參數(shù)比較,D-P5-2D、D-P10-2D、f-mean-2D、f-median-2D、f-P90-2D 和 f-skewness-2D 在組間有統(tǒng)計學差異(P=0.039,D-P5-2D;P=0.022,D-P10-2D;P=0.001,f-mean-2D;P=0.000,f-median-2D;P=0.016,f-P90-2D;P=0.014,f-skewness-2D),其余參數(shù)無統(tǒng)計學差異;3D ROI相關參數(shù)比較,D-mean-3D、D-P5-3D、D-P10-3D、f-mean-3D、f-median-3D 和 f-P90-3D 在組間有統(tǒng)計學差異(P=0.025,D-mean-3D;P=0.002,D-P5-3D;P=0.002,D-P10-3D;P=0.000,f-mean-3D;P=0.000,f-median-3D;P=0.043,f-P90-3D),其余參數(shù)無統(tǒng)計學差異。拉伸指數(shù)模型擬合Hot spot ROI比較,DDC-DDCmin值和α-αmin在高級別組與低級別組間有差異(P=0.001,DDC-DDCmin;P=0.000,α-αmin),其余參數(shù)在組間比較無差異;2D ROI相關參數(shù)比較,DDC-P5-2D、DDC-P10-2D、α-mean-2D 和 α-median-2D 在組間有統(tǒng)計學差異(P=0.033,DDC-P5-2D;P=0.017,DDC-P10-2D;P=0.009,α-mean-2D;P=0.004,α-median-2D),其余參數(shù)無統(tǒng)計學差異;3D ROI相關參數(shù)比較,DDC-mean-3D、DDC-median-3D、DDC-P5-3D、DDC-P10-3D、α-mean-3D、α-median-3D、α-P5-3D 和 α-P10-3D 在組間有統(tǒng)計學差異(P=0.067,DDC-mean-3D;P=0.047,DDC-median-3D;P=0.006,DDC-P5-3D;P=0.005,DDC-P10-3D;P=0.005,α-mean-3D;P=0.006,α-median-3D;P=0.033,α-P5-3D;P=0.014,α-P10-3D),其余參數(shù)無統(tǒng)計學差異。三指數(shù)模型擬合Hot spot ROI比較,Ff-+CMax值、Ds-Dsmin和Ff-FfMax在高級別組與低級別組間有差異(P=0.010,Ff-+CMax;P=0.005,Ds-Dsmin;P=0.007,Ff-FfMax),其余參數(shù)在組間比較無差異;2DROI相關參數(shù)比較,Ds-P5-2D、Ds-P10-2D、Ff-mean-2D、Ff-median-2D 和Ff-skewness-2D 在組間有統(tǒng)計學差異(P=0.030,Ds-P5-2D;P=0.009,Ds-P10-2D;P=0.007,Ff-mean-2D;P=0.015,Ff-median-2D;P=0.003,Ff-skewness-2D),其余參數(shù)無統(tǒng)計學差異;3D ROI相關參數(shù)比較,Ds-P5-3D、Ds-P10-3D、Ff-mean-3D、Ff-median-3D、Ff-skewness-3D、Fp-P90-3D、和 Fp-P95-3D 在組間有統(tǒng)計學差異(P=0.017,Ds-P5-3D;P=0.014,Ds-P10-3D;P=0.036,Ff-mean-3D;P=0.003,Ff-median-3D;P=0.013,Ff-skewness-3D;P=0.016,Fp-P90-3D;P=0.017,Fp-P95-3D),其余參數(shù)無統(tǒng)計學差異。用對側白質區(qū)內部校正后參數(shù)與校正前參數(shù)診斷效能比較,Hot spot ROI法比較,校正后參數(shù)診斷效能高于校正前;2D法和3D法校正后參數(shù)診斷效能低于校正前。各相關參數(shù)信度分析,2D和3D法相關參數(shù)信度高于Hot spot法,3D法略高于2D法;DSC灌注相關參數(shù)中以rCBV值組內相關系數(shù)最高(ICC=0.994,rCBV-+CMax;ICC=0.994,rCBV-rCBVMax);單指數(shù)模型擬合參數(shù)中以ADC-P10-3D和ADC-P5-3D組內相關系數(shù)最高(ICC=0.994,ADC-P10-3D;ICC=0.982,ADC-P5-3D);雙指數(shù)模型擬合參數(shù)中以 f-mean-3D 和 f-median-2D 組內相關系數(shù)最高(ICC=0.999,f-median-3D;ICC=0.998,f-median-2D);拉伸指數(shù)模型擬合參數(shù)中以α-median-3D和α-median-2D 組內相關系數(shù)最高(ICC=0.997,α-median-3D;ICC=0.997,α-median-2D);三指數(shù)模型擬合參數(shù)中以Ff-median-3D和Ff-median-2D組內相關系數(shù)最高(ICC=0.997,Ff-median-3D;ICC=0.997,Ff-median-2D)。各參數(shù)與膠質瘤病理分級相關性分析,DSC灌注參數(shù)中以rCBV-rCBVMax相關性最高(r=0.695);單指數(shù)模型中以ADC-P5-3D相關性最高(r=-0.456);雙指數(shù)模型中以f-fMax相關性最高(r=0.507);拉伸指數(shù)模型中以α-αmin相關性最高(r=-0.607);三指數(shù)模型中以Ff-+CMax相關性最高(r=0.437)。多模型擬合參數(shù)與DSC灌注參數(shù)相關性分析,以f-median-2D與rCBV-rCBVMax相關性最高(r=0.604);多模型擬合參數(shù)中擴散相關參數(shù)以ADC Vs DDC(r=0.968)和D Vs Ds(r=0.966)相關性最強。各參數(shù)鑒別不同級別能力比較,波譜參數(shù)在各級之間無統(tǒng)計學差異;DSC灌注相關參數(shù)中,rCBV-+CMax、rCBV-rCBVMax、MTT-+CMax 和 MTT-MTTMax 在各級之間有統(tǒng)計學差異(P=0.006,rCBV-+CMax;P=0.002,rCBV-rCBVMax;P=0.001,MTT-+CMax;P=0.000,MTT-MTTMax);單指數(shù)模型擬合相關參數(shù)中,ADC-ADCmin、ADC-P10-2D、ADC-P5-3D和ADC-P10-3D 在各級之間有統(tǒng)計學差異(P=0.003,ADC-ADCmin;P=0.046,ADC-P10-2D;P=0.009,ADC-P5-3D;P=0.015,ADC-P10-3D);雙指數(shù)模型擬合相關參數(shù)中,D-Dmin、f-fMax、D-P10-2D、f-mean-2D、f-median-2D、f-skewness-2D、D-P10-3D、f-mean-3D 和 f-median-3D 在各級之間有統(tǒng)計學差異(P=0.002,D-Dmin;P=0.003,f-fMax;P=0.049,D-P10-2D;P=0.002,f-mean-2D;P=0.001,f-median-2D;P=0.032,f-skewness-2D;P=0.002,D-P5-3D;P=0.005,D-P10-3D;P=0.002,f-mean-3D;P=0.000,f-median-3D);拉伸指數(shù)模型擬合相關參數(shù)中,DDC-DDCmin、α-αmin、DDC-P10-2D、α-mean-2D、α-median-2D、DDC-P5-3D、DDC-P10-3D、α-mean-3D 和 α-median-3D 在各級之間有統(tǒng)計學差異(P=0.005,DDC-DDCmin;P=0.000,α-αmin;P=0.045,DDC-P10-2D;P=0.021,α-mean-2D;P=0.012,α-median-2D;P=0.006,DDC-P5-3D;P=0.013,DDC-P10-3D;P=0.016,α-mean-3D;P=0.025,α-median-3D);三指數(shù)模型擬合相關參數(shù)中,Ff-+CMax、Ds-Dsmin、Ff-FfMax、Ds-P10-2D、Ff-mean-2D、Ff-median-2D、Ff-skewness-2D、Ds-P5-3D、Ds-P10-3D 和 Ff-median-3D 在各級之間有統(tǒng)計學差異(P=0.014,Ff-+CMax;P=0.018,Ds-Dsmin;P=0.021,Ff-FfMax;P=0.020,Ds-P10-2D;P=0.026,Ff-mean-2D;P=0.013,Ff-median-2D;P=0.016,Ff-skewness-2D;P=0.029,Ds-P5-3D;P=0.045,Ds-P10-3D;P=0.011,Ff-median-3D);各有價值參數(shù)在各級之間兩兩比較,Ⅱ級與Ⅲ級之間有統(tǒng)計學差異;Ⅱ級與Ⅳ級之間有統(tǒng)計學差異,但是Ⅲ級與Ⅳ級之間無統(tǒng)計學差異。結論1、多b值DWI序列中不同的擬合方案中有價值的參數(shù)不同,要根據(jù)選擇的擬合方案選擇合適的參數(shù),以雙指數(shù)模型診斷價值最高;2、各擬合方案中不同的ROI勾畫方法有價值參數(shù)不同,要根據(jù)不同的ROI勾畫方法選擇不同的參數(shù),以2D方法的診斷價值最高;3、各參數(shù)信度分析3D法相關參數(shù)最高,2D法次之,Hot spot法最低;4、各種相關參數(shù)中f值與DSC灌注相關參數(shù)相關性最高,能反映腫瘤內的灌注信息;4、彌散相關參數(shù)中,ADC值與DDC值相關性最高,D值與Ds值相關性最高;6、強化最明顯區(qū)域各參數(shù)值的診斷價值不及各參數(shù)圖極值區(qū)域參數(shù)值;7、各有價值參數(shù)能很好的鑒別Ⅱ級與Ⅲ級、Ⅱ級與Ⅳ級膠質瘤,但是鑒別Ⅲ級與Ⅳ級較難;8、三指數(shù)擬合模型相關參數(shù)在膠質瘤術前分級中有很大價值。
[Abstract]:Objective DWI sequence related parameters are of high value in evaluating glioma, but there is a great difference between the parameters of different fitting models and different ROI drawing methods. The purpose of this study is to discuss which parameters and which ROI method is more valuable in the preoperative grading of glioma. Method 46 cases of the pathologically confirmed glue Patients with stromal tumors underwent conventional magnetic resonance imaging, spectrum examination, multi B diffusion weighted imaging, DSC perfusion examination and routine sequence enhancement. Multiple b value DWI sequences were fitted with multiple models of single index, double index, tensile index and three index, and Hot spot method, 2D method and 3D method were used in ROI delineation. The parameters of each model were compared with ROI hook. The value of the high grade and low grade group of glioma was identified before the operation, and the high sensitivity and specificity were screened. At the same time, the value of each parameter in the identification of glioma was compared and the best scheme was screened. Results the ratio of high and low grade glioma spectrum parameters was compared with read1, and the parameter of tumor side metabolite was in the case of the high grade and low grade glioma. There was no statistical difference between the high and low level groups (P=0.412, NAA/Cr; P=0.148, Cho/Cr; P=0.306, Cho/NAA).DSC perfusion parameters, and there was a significant difference between the high level group and the low level group (P=0.042, rCBF-+CMax; P=0.030, rCBF-rCBFMax; P=0.002) TT-MTTMax). Compared with Hot spot ROI, the ADC-ADCmin value is different between the advanced group and the low level group (P=0.001), and the ADC-+CMax value is no difference between the groups (P=0.273); the 2D ROI related parameters are compared, and the ADC-P10-2D is statistically different between the groups (P=0.035), and the other parameters are not statistically different. 3D, ADC-P5-3D and ADC-P10-3D were statistically different between groups (P=0.041, ADC-mean-3D; P=0.009, ADC-P5-3D; P=0.005, ADC-P10-3D), and the rest of the parameters were not statistically different. The double exponential model fitted HotspotROI, D-Dmin and f-fMax were different between the advanced and low-level groups, and the rest of the parameters were in the inter group ratio. 2D ROI related parameters, D-P5-2D, D-P10-2D, f-mean-2D, f-median-2D, f-P90-2D and f-skewness-2D were statistically different between the groups (P=0.039, D-P5-2D; P=0.022, D-P10-2D; dialectical; dialectical; excluded), the other parameters were not statistically different; D-mean-3D, D-P5-3D, D-P10-3D, f-mean-3D, f-median-3D and f-P90-3D have statistical differences between the groups (P=0.025, D-mean-3D; P=0.002, D-P5-3D; P=0.002, D-P10-3D), and the rest of the parameters are not statistically different. There was a difference between the advanced group and the low level group (P=0.001, DDC-DDCmin; P=0.000, alpha - alpha min), and the other parameters were not different between the groups. The 2D ROI related parameters, DDC-P5-2D, DDC-P10-2D, alpha -mean-2D and alpha -median-2D were statistically different between the groups. There is no statistical difference in the residual parameters; DDC-mean-3D, DDC-median-3D, DDC-P5-3D, DDC-P10-3D, alpha -mean-3D, alpha -median-3D, alpha -P5-3D and alpha -P10-3D are statistically different in the 3D ROI correlation parameters. 33, alpha -P5-3D; P=0.014, alpha -P10-3D), the other parameters are not statistically different. The three index model fits the Hot spot ROI comparison, Ff-+CMax value, Ds-Dsmin and Ff-FfMax are different between the advanced group and the lower class group (P=0.010, Ff-+CMax; P=0.005, etc.), and the other parameters are not different between the groups. S-P10-2D, Ff-mean-2D, Ff-median-2D and Ff-skewness-2D have statistical differences between groups (P=0.030, Ds-P5-2D; P=0.009, Ds-P10-2D; P=0.007, Ff-mean-2D; P=0.015, Ff-median-2D; Ff-skewness-2D). 3D, and Fp-P95-3D were statistically different between groups (P=0.017, Ds-P5-3D; P=0.014, Ds-P10-3D; P=0.036, Ff-mean-3D; P=0.003, Ff-median-3D; P=0.013, Ff-skewness-3D; Ff-skewness-3D. The diagnostic efficiency of the corrected parameters is higher than that before the correction. The parameter diagnostic efficiency of the 2D and 3D methods is lower than that before the correction. The reliability of the relevant parameters is higher than the Hot spot method, and the 3D method is slightly higher than the 2D method, and the correlation coefficients of the DSC perfusion parameters are the highest in the rCBV value group. CBVMax); the correlation coefficients of the ADC-P10-3D and ADC-P5-3D groups in the single exponential model were the highest (ICC=0.994, ADC-P10-3D; ICC=0.982, ADC-P5-3D), and the correlation coefficients of the f-mean-3D and f-median-2D groups in the double exponential model were the highest (ICC=0.999, f-median-3D; ICC=0.998 and ADC-P5-3D), and the parameters of the tensile index model were alpha - The correlation coefficient of median-3D and alpha -median-2D was the highest (ICC=0.997, alpha -median-3D; ICC=0.997, alpha -median-2D). The correlation coefficient of Ff-median-3D and Ff-median-2D in the three exponential model was the highest (ICC=0.997, Ff-median-3D; ICC=0.997, Ff-median-2D). The correlation between the parameters and the pathological grading of glioma was analyzed. The rCBV-rCBVMax correlation is the highest (r=0.695); in the single exponential model, the ADC-P5-3D correlation is the highest (r=-0.456); the f-fMax correlation is the highest in the double exponential model (r=0.507); the tensile index model is the highest (r=-0.607) in the alpha - a min correlation; the three index model is the highest (r=0.437) in the Ff-+ CMax correlation. The correlation between f-median-2D and rCBV-rCBVMax is the highest (r=0.604), and the correlation parameter of the multiple model fitting parameters is the strongest correlation between the ADC Vs DDC (r=0.968) and D Vs Ds (r=0.966). There are statistical differences between X, MTT-+CMax and MTT-MTTMax at all levels (P=0.006, rCBV-+CMax; P=0.002, rCBV-rCBVMax; P=0.001, MTT-+CMax; P=0.000, MTT-MTTMax). 9, ADC-P5-3D; P=0.015, ADC-P10-3D); the two exponential models fit the relevant parameters, D-Dmin, f-fMax, D-P10-2D, f-mean-2D, f-median-2D, f-skewness-2D, D-P10-3D, f-mean-3D and f-median-3D. S-2D; P=0.002, D-P5-3D; P=0.005, D-P10-3D; P=0.002, f-mean-3D; P=0.000, f-median-3D); DDC-DDCmin, alpha min in the tensile exponential model. DDC-P10-2D; P=0.021, alpha -mean-2D; P=0.012, alpha -median-2D; P=0.006, DDC-P5-3D; P=0.013, DDC-P10-3D; P=0.016, alpha -mean-3D; P=0.025, and alpha. P=0.014 (Ff-+CMax; P=0.018, Ds-Dsmin; P=0.021, Ff-FfMax; P=0.020, Ds-P10-2D; P=0.026, Ff-mean-2D; P=0.013, Ff-median-2D; Ff-median-2D); there are statistical differences between the value parameters at all levels, between class II and grade III; class II and There are statistical differences between grade IV, but there is no statistical difference between grade III and grade IV. Conclusion 1, the value of different parameters in different fitting schemes of multiple b value DWI sequences are different. It is necessary to select the appropriate parameters according to the selected fitting scheme, and the value of the double exponential model is the highest. 2, the different ROI drawing methods in each fitting scheme have value reference. Different parameters should be selected according to different ROI methods, and the diagnostic value of 2D method is the highest. 3, the parameters reliability analysis 3D method has the highest correlation parameters, 2D method is the second, Hot spot method is the lowest; 4, the correlation parameter of F and DSC perfusion parameters is most high, can reflect the perfusion information within the tumor; 4, dispersion related parameters The correlation between the ADC value and the DDC value is the highest, the D value has the highest correlation with the Ds value; 6, the diagnostic value of each parameter in the most obvious region is less than the parameter value of the extreme value of the parameter graphs; 7, each valuable parameter can identify the grade II and III, grade II and grade IV glioma, but the discrimination of grade III and IV is more difficult; the 8, three index fitting model parameters It is of great value in preoperative grading of glioma.
【學位授予單位】:南方醫(yī)科大學
【學位級別】:博士
【學位授予年份】:2017
【分類號】:R445.2;R739.41
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