Perfusion and Diffusion Weighted Magnetic Resonance Imaging in Rectal cancer: How is the Correlation between Multiple Methods?

Xiaojuan Xiao¹, Baolan Lu¹, Xinyue Yang¹, Shenping Yu¹, Yanhong Yang¹, and Xu Yan²

¹Department of Radiology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China, People's Republic of, ²MR Collaboration NE Asia, Siemens Healthcare, Shanghai, China, People's Republic of

Synopsis

DCE-MRI, IVIM and DKI are emerging as promising tools for tumor diagnositic or therapy-predictive purposes. We performed these three methods in patients with rectal cancer simultaneously to find out their correlations. Our results showed significant correlation between perfusion sensitive parameters of IVIM and DCE-MRI. In addition, DKI parameters were calculated from data with a low (0-1000) and high (200-2000) b-value range, and the parameters from low b-value range showed significant correlation with IVIM parameters, but not for the high b-value range.

Purpose

To find out the correlations between the various parameters derived from dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), diffusion imaging using intravoxel incoherent motion (IVIM) and diffusion kurtosis imaging (DKI) in patients with rectal cancer.

Methods

Thirty-seven newly diagnosed rectal cancer patients were prospectively enrolled and scanned on a 3T MR scanner (Siemens Healthcare, Erlangen, Germany) using a prototype diffusion sequence. Diffusion weighted images were acquired with 16 b-values 0, 5, 10, 20, 30, 40, 60, 80, 100, 150, 200, 400, 600, 1000, 1500, and 2000 s/mm²). DCE-MRI was performed in a total of 75 dynamic phases with a 4.25s phase interval. An in-house developed software based on MATLAB were used for both IVIM and DKI post-processing. The IVIM parameters including perfusion fraction (f), the pseudo-diffusion coefficient (D*) and true diffusion coefficient(D-IVIM) were calculated with a b values range of 0-1000 s/mm². DKI parameters, kurtosis(K) and apparent diffusion coefficient(D-DKI), were calculated using data from two b-value ranges 0-1000 and 200-2000 s/mm² respectively, denoted as K₁₀₀₀, D-DKI₁₀₀₀ and K₂₀₀₀, D-DKI₂₀₀₀. DCE-MRI parameters including transfer constant (K^trans), rate constant of back flux (K_ep) and extravascular extracellular space fractional volume (V_e) were calculated using Toft’s modeling on Siemens workstation. Correlations between IVIM, DKI and DCE-MRI parameters were analyzed respectively using Pearson's correlation coefficients.

Results

The correlation analysis showed that perfusion-sensitive parameters f and D* from IVIM were significantly correlated with DCE-MRI-derived parameter K^trans (r=0.510, p=0.001; r=0.352, p=0.033). DKI parameters showed no significant correlation with DCE-MRI parameters, while significant correlations were found between DKI and IVIM parameters. K₁₀₀₀ and D-DKI₁₀₀₀showed significant correlation with D* (r=0.431, p=0.008) and f (r=0.004, p=0.468) respectively, K₂₀₀₀ showed weak correlation with f (r=0.332, p=0.045), see Figure 2.

Discussion

Personalized treatment required functional MR imaging methods in addition to conventional morphologic MRI. In rectal caner, to predict or monitor individual response to neoadjuvant chemoradiotherapy (CRT) has become the main concern. Hence, multi-parametric MRI including DCE-MRI and DWI has emerged. Previous studies reported that: 1) K^trans derived from DCE-MRI was correlated with CRT treatment response or complete pathologic response (pCR) ^1,2; 2) In conventional DWI, relationship between ADC and treatment response are still controversial ^3-6. However, IVIM is able to not only get more precise diffusion coefficient, but also get perfusion parameter without contrast injection. IVIM was reported to be related with perfusion MR in several tumors ^7-9; 3) DKI could be more sensitive than conventional DWI for cancer detection and evaluation ¹⁰. Therefore, we designed this study to give a comprehensive understanding about these multi-parametric MRI in rectal cancer.

Our results showed that IVIM perfusion sensitive parameters was significantly correlated with K^transderived from DCE-MRI, which suggested IVIM could be used to reflect rectal cancer’s microvascular perfusion. DKI parameters of b-value range 0-1000 showed significant correlation with IVIM, which reflected non-gaussian property due to combination of perfusion and diffusion signals. While DKI parameters of b 0-2000 showed weak or no correlation with DCE-MRI and IVIM, which reflected non-gaussion property not from conventional diffusion and perfusion, but might due to restricted diffusion of cancer tissue, and could probablely provide additional information.

Conclusion

IVIM perfusion sensitive parameters showed significant correlations with DCE-MRI, which has great potential in tumor diagnosis and therapy monitoring of rectal cancer. DKI parameter at high b-value range may provide addition diffusion information other than conventional diffusion and perfusion. The correlation of DCE-MRI, IVIM and DKI with histology and immunohistochemistry will be conducted in future study.

Acknowledgements

This research is supported by Science and Technology Planning Project of Guangdong Province, China (No. 2014A020212126 ).

References

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Figures

Figure 1. DCE-MRI, IVIM and DKI measurement of a 42-year-old woman diagnosed with rectal cancer. a-d, DCE-MRI images: perfusion parameter map, dynamic enhanced image, T2-weighted image and histogram showing distribution of K^trans value of selected ROI; e-f, IVIM maps; i-l, DKI maps.

Figure 2. Correlations between DCE-MRI, IVIM and DKI parameters The data in the table includes p value and Pearson correlation coefficient r, presented as p(r).

Proc. Intl. Soc. Mag. Reson. Med. 24 (2016)

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