Preoperatively Grading Rectal Cancer with the Combination of Intravoxel Incoherent Motions Imaging and Diffusion Kurtosis Imaging. (12th October 2020)

• Record Type: Journal Article
• Authors: Geng, Zhijun; Zhang, Yunfei; Yin, Shaohan; Lian, Shanshan; He, Haoqiang; Li, Hui; Xie, Chuanmiao; Dai, Yongming
• Other Names: Ferro Flores Guillermina Academic Editor.
• Is Part Of: Contrast media & molecular imaging. Volume 2020(2020)
• Publication Date: 2020-10-12
• Subjects: Diagnostic imaging -- Periodicals; Magnetic resonance imaging -- Periodicals; Contrast media (Diagnostic imaging) -- Periodicals; Contrast Media -- Periodicals; Diagnostic Imaging -- Periodicals; Substances de contraste -- Périodiques; Diagnostics moléculaires -- Périodiques; Imagerie médicale; Substance de contraste; Périodique électronique (Descripteur de forme); Ressource Internet (Descripteur de forme); 616.0754
• DOI: 10.1155/2020/2164509
• Languages: English
• ISSNs: 1555-4309

Abstract

Abstract : Purpose . To combine Intravoxel Incoherent Motions (IVIM) imaging and diffusion kurtosis imaging (DKI) which can aid in the quantification of different biological inspirations including cellularity, vascularity, and microstructural heterogeneity to preoperatively grade rectal cancer. Methods . A total of 58 rectal patients were included into this prospective study. MRI was performed with a 3T scanner. Different combinations of IVIM-derived and DKI-derived parameters were performed to grade rectal cancer. Pearson correlation coefficients were applied to evaluate the correlations. Binary logistic regression models were established via integrating different DWI parameters for screening the most sensitive parameter. Receiver operating characteristic analysis was performed for evaluating the diagnostic performance. Results . For individual DWI-derived parameters, all parameters except the pseudodiffusion coefficient displayed the capability of grading rectal cancer (p < 0.05 ). The better discrimination between high- and low-grade rectal cancer was achieved with the combination of different DWI-derived parameters. Similarly, ROC analysis suggested the combination of D (true diffusion coefficient), f (perfusion fraction), and K app (apparent kurtosis coefficient) yielded the best diagnostic performance (AUC = 0.953, p < 0.001 ). According to the result of binary logistic analysis, cellularity-related D was the most sensitive predictor (odds ratio: 9.350 ± 2.239) for grading rectal cancer. Conclusion . The combination of IVIM and DKI holds great potential in accurately grading rectal cancer as IVIM and DKI can provide the quantification of different biological inspirations including cellularity, vascularity, and microstructural heterogeneity.