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Published on: December 15, 2014
Correlations of Mean and Mimimum Apparent Diffusion Coefficient Values With the Clinicopathological Features in
Jinkai Liu1, Qiying Li1, Langlang Tang1
1From the Department of Radiology, Longyan First Hospital Affiliated to Fujian Medical University, No. 105 north 91 road, Xinluo District, Longyan, 364000, Fujian, China.
Rationale And Objective:
The study aimed to investigate the possible correlation between mean (MeanADC) and minimum (MinADC) apparent diffusion coefficient values with the clinicopathological features and evaluate the diagnostic potential of MinADC values and MeanADC values in predicting the behavior of rectal cancer.
Materials And Methods:
In total, 148 pathologically verified lesions that were subjected to conventional MR imaging and diffusion weighted imaging prior to operation were included. The MeanADC values and MinADC values were calculated and their correlation with clinicopathological characteristics were investigated.
Results:
Both MeanADC values and MinADC values correlated with T classification (MeanADC: t = 2.841, p = 0.005; MinADC: t = 2.356, p = 0.020), N classification (MeanADC: t = 3.468, p = 0.001; MinADC: t = 3.072, p = 0.003), tumor histological grade (MeanADC: F = 8.175, p = 0.000; MinADC: F = 22.038, p = 0.000), perineural invasion (MeanADC: t = 2.547, p = 0.012; MinADC: t = 3.081, p = 0.002), and extramural venous invasion (MeanADC: t = 2.157, p = 0.033; MinADC: t = 2.635, p = 0.009) in rectal cancer, but no significant correlation with gender, age, and tumor location (p > 0.05). The MinADC values showed a higher diagnostic efficacy in discriminating the well or poor differentiation of rectal cancer compared to MeanADC values, with a threshold value of ≥0.929 × 10-3 mm2/s (sensitivity, 80%; specificity, 88.1%) or ≤0.752 × 10-3 mm2/s (sensitivity, 94.1%; specificity, 74%).
Conclusion:
Both MeanADC values and MinADC values might be used as a quantitative parameter to evaluate the aggressiveness of rectal cancer. The MinADC values could be as the better predictor in identifying tumor differentiation compared to the MeanADC values.
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