Predicting the pathological response to chemoradiotherapy of non-mucinous rectal cancer using pretreatment texture features based on intravoxel incoherent motion diffusion-weighted imaging

被引:20
|
作者
Liu, Siye [1 ,2 ]
Wen, Lu [1 ,2 ]
Hou, Jing [1 ,2 ]
Nie, Shaolin [3 ,4 ]
Zhou, Jumei [4 ,5 ]
Cao, Fang [4 ,6 ]
Lu, Qiang [1 ,2 ]
Qin, Yuhui [1 ,2 ]
Fu, Yi [4 ,7 ]
Yu, Xiaoping [1 ,2 ]
机构
[1] Cent S Univ, Xiangya Sch Med, Affiliated Canc Hosp, Dept Diagnost Radiol, 283 Tongzipo Rd, Changsha 410006, Hunan, Peoples R China
[2] Cent S Univ, Hunan Canc Hosp, 283 Tongzipo Rd, Changsha 410006, Hunan, Peoples R China
[3] Cent S Univ, Hunan Canc Hosp, Dept Colorectal Surg, Changsha 410006, Hunan, Peoples R China
[4] Cent S Univ, Affiliated Canc Hosp, Xiangya Sch Med, Changsha 410006, Hunan, Peoples R China
[5] Cent S Univ, Hunan Canc Hosp, Dept Radiotherapy, Changsha 410006, Hunan, Peoples R China
[6] Cent S Univ, Hunan Canc Hosp, Dept Pathol, Changsha 410006, Hunan, Peoples R China
[7] Cent S Univ, Hunan Canc Hosp, Dept Med Serv, Changsha 410006, Hunan, Peoples R China
关键词
Rectal cancer; Magnetic resonance imaging; Diffusion-weighted imaging; Texture analysis; Chemoradiotherapy; Treatment outcome; CONTRAST-ENHANCED-MRI; NEOADJUVANT CHEMORADIOTHERAPY; CHEMOTHERAPY RESPONSE; TUMOR HETEROGENEITY; CT TEXTURE; COEFFICIENT; THERAPY; BIOMARKER;
D O I
10.1007/s00261-019-02032-0
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
ObjectivesTo investigate the performance of the mean parametric values and texture features based on intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) on identifying pathological complete response (pCR) to neoadjuvant chemoradiotherapy (nCRT) in locally advanced rectal cancer (LARC).MethodsPretreatment IVIM-DWI was performed on 41 LARC patients receiving nCRT in this prospective study. The values of IVIM-DWI parameters (apparent diffusion coefficient, ADC; pure diffusion coefficient, D; pseudo-diffusion coefficient, D* and perfusion fraction, f), the first-order, and gray-level co-occurrence matrix (GLCM) texture features were compared between the pCR (n=9) and non-pathological responder (non-pCR, n=32) groups. Receiver operating characteristic (ROC) curves in univariate and multivariate logistic regression analysis were generated to determine the efficiency for identifying pCR.ResultsThe values of IVIM-DWI parameters and first-order texture features did not show significant differences between the pCR and non-pCR groups. The pCR group had lower Contrast and DifVarnc values extracted from the ADC, D, and D* maps, respectively, as well as lower Correlat(D) value. Higher Correlat(D*), Correlat(f), SumAverg(ADC), and SumAverg(D) values were observed in the pCR group. The area under the ROC curve (AUC) values for the individual predictors in univariate analysis ranged from 0.698 to 0.837, with sensitivities from 43.75% to 87.50% and specificities from 66.67 to 100.00%. In multivariate analysis, Correlat(D*) (P<0.001), DifVarnc(ADC) (P=0.024), and DifVarnc(D) (P<0.001) were the independent predictors to pCR, with an AUC of 0.986, a sensitivity of 93.75%, and a specificity of 100.00%.ConclusionPretreatment GLCM analysis based on IVIM-DWI may be a potential approach to identify the pathological response of LARC.
引用
收藏
页码:2689 / 2698
页数:10
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