机构：[1]Department of Radiology, Fourth Hospital of Hebei Medical University, No.12 Jiankang Road, Shijiazhuang 050000, China.医技科室放射科河北医科大学第四医院[2]Central Research Institute, United Imaging Healthcare, Shanghai 201800, China.
Background: this study aimed to utilize various diffusion-weighted imaging (DWI) techniques, including mono-exponential DWI, intravoxel incoherent motion (IVIM), and diffusion kurtosis imaging (DKI), for the preoperative grading of rectal cancer. Methods: 85 patients with rectal cancer were enrolled in this study. Mann-Whitney U tests or independent Student's t-tests were conducted to identify DWI-derived parameters that exhibited significant differences. Spearman or Pearson correlation tests were performed to assess the relationships among different DWI-derived biological markers. Subsequently, four machine learning classifier-based models were trained using various DWI-derived parameters as input features. Finally, diagnostic performance was evaluated using ROC analysis with 5-fold cross-validation. Results: With the exception of the pseudo-diffusion coefficient (Dp), IVIM-derived and DKI-derived parameters all demonstrated significant differences between low-grade and high-grade rectal cancer. The logistic regression-based machine learning classifier yielded the most favorable diagnostic efficacy (AUC: 0.902, 95% Confidence Interval: 0.754-1.000; Specificity: 0.856; Sensitivity: 0.925; Youden Index: 0.781). Conclusions: utilizing multiple DWI-derived biological markers in conjunction with a strategy employing multiple machine learning classifiers proves valuable for the noninvasive grading of rectal cancer.
第一作者机构：[1]Department of Radiology, Fourth Hospital of Hebei Medical University, No.12 Jiankang Road, Shijiazhuang 050000, China.
共同第一作者：
通讯作者：
通讯机构：[1]Department of Radiology, Fourth Hospital of Hebei Medical University, No.12 Jiankang Road, Shijiazhuang 050000, China.
推荐引用方式(GB/T 7714)：
Song Mengyu,Wang Qi,Feng Hui,et al.Preoperative Grading of Rectal Cancer with Multiple DWI Models, DWI-Derived Biological Markers, and Machine Learning Classifiers[J].BIOENGINEERING-BASEL.2023,10(11):doi:10.3390/bioengineering10111298.
APA：
Song Mengyu,Wang Qi,Feng Hui,Wang Lijia,Zhang Yunfei&Liu Hui.(2023).Preoperative Grading of Rectal Cancer with Multiple DWI Models, DWI-Derived Biological Markers, and Machine Learning Classifiers.BIOENGINEERING-BASEL,10,(11)
MLA：
Song Mengyu,et al."Preoperative Grading of Rectal Cancer with Multiple DWI Models, DWI-Derived Biological Markers, and Machine Learning Classifiers".BIOENGINEERING-BASEL 10..11(2023)
