Author/Authors :
Geng, Zhijun Department of Radiology - Sun Yat-sen University Cancer Center - State Key Laboratory of Oncology in Southern China - Dongfeng East Road - Guangzhou, China , Zhang, Yunfei United Imaging Healthcare - Shanghai, China , Yin, Shaohan Department of Radiology - Sun Yat-sen University Cancer Center - State Key Laboratory of Oncology in Southern China - Dongfeng East Road - Guangzhou, China , Lian, Shanshan Department of Radiology - Sun Yat-sen University Cancer Center - State Key Laboratory of Oncology in Southern China - Dongfeng East Road - Guangzhou, China , He, Haoqiang Department of Radiology - Sun Yat-sen University Cancer Center - State Key Laboratory of Oncology in Southern China - Dongfeng East Road - Guangzhou, China , Li, Hui Department of Radiology - Sun Yat-sen University Cancer Center - State Key Laboratory of Oncology in Southern China - Dongfeng East Road - Guangzhou, China , Xie, Chuanmiao Department of Radiology - Sun Yat-sen University Cancer Center - State Key Laboratory of Oncology in Southern China - Dongfeng East Road - Guangzhou, China , Dai, Yongming United Imaging Healthcare - Shanghai, China
Abstract :
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 Kapp (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.