Yiqun Sun1,2,3, Qin Xiao1,2, Feixiang Hu1,2, Caixia Fu4, Huixun Jia2,5, Xu Yan6, Chao Xin1,2, Sanjun Cai2,7, Weijun Peng1,2, Xiaolin Wang3, Tong Tong8,9, Yajia Gu10,11. 1. Department of Radiology, Fudan University Shanghai Cancer Center, 270 Dong An Road, Shanghai, 200032, China. 2. Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China. 3. Shanghai Institute of Medical Imaging, Fudan University, Shanghai, China. 4. Siemens Shenzhen Magnetic Resonance Ltd., Shenzhen, China. 5. Department of Clinical Statistics Center, Fudan University Shanghai Cancer Center, Shanghai, China. 6. MR Collaboration NE Asia, Siemens Healthineer, Shanghai, China. 7. Department of Colorectal Surgery, Fudan University Shanghai Cancer Center, Shanghai, China. 8. Department of Radiology, Fudan University Shanghai Cancer Center, 270 Dong An Road, Shanghai, 200032, China. t983352@126.com. 9. Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China. t983352@126.com. 10. Department of Radiology, Fudan University Shanghai Cancer Center, 270 Dong An Road, Shanghai, 200032, China. cjr.guyajia@vip.163.com. 11. Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China. cjr.guyajia@vip.163.com.
Abstract
OBJECTIVES: Our goal was to investigate the correlation between histopathology and diffusion parameters by utilising the most repeatable region-of-interest (ROI) strategy for diffusion parameters in rectal cancer on a 3T scanner. METHODS: 113 patients underwent DKI-MR and 66 of these patients received surgery without neoadjuvant chemoradiotherapy. Two readers independently measured the parameters using three slice protocols including single slice, three slices and whole-tumour slice (WTS), combined with one of two ROIs, including outline and round ROI. ANOVA, Kruskal-Wallis, a paired sample t-test, interclass correlation coefficient (ICC), Bland-Altman, Student's t-tests, receiver operating characteristic curves and z statistic were used for statistical analysis. RESULTS: There were no significant differences among the three slice protocols in ADC values (p = 0.822, 0.987), K values (p = 0.842, 0.859) and D values (p = 0.917, 0.988) using round and outline ROI, respectively. The ADC and D values derived from outline ROIs were higher than those from round ROIs (all p < 0.001 for ADC, all p < 0.001 for D), while K values derived from outline ROIs were lower than those from round ROIs (p < 0.001, p = 0.001, p < 0.001) using three slice protocols, respectively. The WTS-outline ROI resulted in the best intra- and inter-observer ICC. Utilising the WTS-outline ROI method, the AUC for assessment of well-differentiated tumours was 0.871 by K and 0.809 by ADC; and the AUC for T2 was 0.768 by K. CONCLUSIONS: The most repeatable strategy was the WTS-outline ROI method. In addition to DWI, DKI also have diagnostic value for rectal cancer histopathological characteristics utilising the WTS-outline ROI on a 3T scanner. KEY POINTS: • DKI using a 3T scanner is feasible for assessing rectal cancer. • ROI and slice protocol show considerable influence on DKI parameters. • DKI parameters exhibit excellent repeatability using whole-tumour slice-outline ROI on 3T scanner. • DKI has considerable diagnostic value for the estimation of rectal cancer characteristics.
OBJECTIVES: Our goal was to investigate the correlation between histopathology and diffusion parameters by utilising the most repeatable region-of-interest (ROI) strategy for diffusion parameters in rectal cancer on a 3T scanner. METHODS: 113 patients underwent DKI-MR and 66 of these patients received surgery without neoadjuvant chemoradiotherapy. Two readers independently measured the parameters using three slice protocols including single slice, three slices and whole-tumour slice (WTS), combined with one of two ROIs, including outline and round ROI. ANOVA, Kruskal-Wallis, a paired sample t-test, interclass correlation coefficient (ICC), Bland-Altman, Student's t-tests, receiver operating characteristic curves and z statistic were used for statistical analysis. RESULTS: There were no significant differences among the three slice protocols in ADC values (p = 0.822, 0.987), K values (p = 0.842, 0.859) and D values (p = 0.917, 0.988) using round and outline ROI, respectively. The ADC and D values derived from outline ROIs were higher than those from round ROIs (all p < 0.001 for ADC, all p < 0.001 for D), while K values derived from outline ROIs were lower than those from round ROIs (p < 0.001, p = 0.001, p < 0.001) using three slice protocols, respectively. The WTS-outline ROI resulted in the best intra- and inter-observer ICC. Utilising the WTS-outline ROI method, the AUC for assessment of well-differentiated tumours was 0.871 by K and 0.809 by ADC; and the AUC for T2 was 0.768 by K. CONCLUSIONS: The most repeatable strategy was the WTS-outline ROI method. In addition to DWI, DKI also have diagnostic value for rectal cancer histopathological characteristics utilising the WTS-outline ROI on a 3T scanner. KEY POINTS: • DKI using a 3T scanner is feasible for assessing rectal cancer. • ROI and slice protocol show considerable influence on DKI parameters. • DKI parameters exhibit excellent repeatability using whole-tumour slice-outline ROI on 3T scanner. • DKI has considerable diagnostic value for the estimation of rectal cancer characteristics.
Entities:
Keywords:
Biomarkers; Diffusion magnetic resonance imaging; Feasibility studies; Rectal neoplasms; Reproducibility of results
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