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Clinical Article
Application study of MRI T2WI texture baseline predicting the efficacy of advanced rectal cancer transformation therapy for primary tumors
WANG Zheng  MENG Linghou  LI Qiang  LI Liya  TIAN Lianfen  LIANG Binling  ZHOU Chuanji 

Cite this article as: Wang Z, Meng LH, Li Q, et al. Application study of MRI T2WI texture baseline predicting the efficacy of advanced rectal cancer transformation therapy for primary tumors[J]. Chin J Magn Reson Imaging, 2022, 13(1): 42-47, 53. DOI:10.12015/issn.1674-8034.2022.01.009.


[Abstract] Objective To explore the predictive value of baseline magnetic resonance imaging (MRI) T2WI image texture analysis in the treatment of advanced rectal cancer for the primary tumor.Materials and Methods: Retrospective analysis of 66 patients with advanced rectal cancer confirmed clinically and pathologically. All patients underwent pelvic MRI scan, enhancement and diffusion weighted imaging (DWI) examinations before operation. According to the plain scan and enhanced images, the location and range of the tumor were identified, and the Mazda software was used to extract the region of interest (ROI) texture in the T2WI image, and linear discriminant analysis (LDA) and nonlinear discriminant analysis (linear discriminant analysis) were used respectively. Discriminant analysis (NDA) and principal component analysis (PCA) are three extraction methods for discriminative classification, and the best method is selected for texture extraction. Combined with postoperative pathology, the baseline morphological characteristics of the primary focus of patients with advanced rectal cancer were compared between the sensitive group and the insensitive group, and the texture characteristics of the T2WI sequence images of the two groups were compared to construct a curative effect prediction model.Results The pathological tumor regression grade (pTRG) of 66 patients with advanced rectal cancer showed that 9 cases were pTRG 0, 8 cases were pTRG 1, 35 cases were pTRG 2, and 14 cases were pTRG 3. Among them, 52 cases were in the sensitive group (pTRG 0~2) and 14 cases were in the insensitive group (pTRG 3). There was no significant difference between the two groups of patients between the primary tumor involving the intestinal segment, the relationship with the peritoneum reflexion, the length of the longitudinal involvement, the proportion of the circumference of the intestinal cavity, the maximum thickness of the oblique axis, and the distance between the lower edge of the tumor and the anal edge (all P>0.05); the NDA classification method under the Fisher texture feature extraction method has the lowest misjudgment rate, so this method is used to extract the image texture. The univariate analysis of texture characteristics in different treatment groups of the primary tumor of advanced rectal cancer showed: the first percentile (Perc 1%), S (2, 0) DifEntrp, S (3, 0) InvDfMom, S (3, -3) SumAverg, S (4, 0) InvDfMom, S (4, -4) SumAverg, S (5, 0) InvDfMom, S (5, -5) SumAverg, S (2, 2) SumVarnc, all indicators were statistically different (P<0.05), S (2, 2) SumVarnc, S (3, 0) DifEntrp were not statistically different (P=0.05, 0.052); the indicators with differences in univariate analysis were included in Logistic multivariate analysis of the model showed that Perc 1% and S (5, 0) InvDfMom were independent predictors of insensitivity to transformation treatment of primary tumors of advanced rectal cancer, and the above factors were used to construct the prediction of insensitivity of primary tumors of advanced rectal cancer to transformation therapy. The area under the curve (AUC) of the model is 0.812, the sensitivity is 92.90%, and the specificity was 60.80%.Conclusions T2WI image texture features extracted based on MRIFisher extraction method can help predict the efficacy of primary tumor transformation therapy for advanced rectal cancer, and provide valuable reference information for the formulation of individualized treatment plans for patients.
[Keywords] advanced rectal cancer;magnetic resonance imaging;translational therapy;pathological grading;texture analysis;curative effect prediction

WANG Zheng1, 2, 3   MENG Linghou1#   LI Qiang1, 2, 3*   LI Liya4   TIAN Lianfen4   LIANG Binling4   ZHOU Chuanji4  

1 Affiliated Cancer Hospital of Guangxi Medical University, Nanning 530021, China

2 Guangxi Imaging Medicine Clinical Medical Research Center, Nanning 530021, China

3 Key Clinical Specialties in Guangxi (Medical Imaging Department), Nanning 530021, China

4 Graduate School of Guangxi Medical University, Nanning 530021, China

Li Q, E-mail: 448954904@qq.com

Conflicts of interest   None.

ACKNOWLEDGMENTS Guangxi Medical and Health Appropriate Technology Development, Promotion and Application Project (No. S2020093); Guangxi Key Reseach and Development Project (No. AB19110015); Guangxi Medical and Health Self-financing Project (No. Z20200403, Z20200445, Z20210418); Guangxi Medical University Education and Teaching Reform Project (No. 2020XJGZ05, 2020XJGB16, 2021XJGA14, 2021XJGB56); Youth Science Fund Project of Guangxi Medical University (No. GXMUYSF202226).
Received  2021-05-20
Accepted  2021-11-09
DOI: 10.12015/issn.1674-8034.2022.01.009
Cite this article as: Wang Z, Meng LH, Li Q, et al. Application study of MRI T2WI texture baseline predicting the efficacy of advanced rectal cancer transformation therapy for primary tumors[J]. Chin J Magn Reson Imaging, 2022, 13(1): 42-47, 53. DOI:10.12015/issn.1674-8034.2022.01.009.

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