Diffusion MRI as an alternative for dynamic contrast MRI in evaluation of hepatocellular carcinoma

Shrouk Mohamed AwadallahBayomi;

Abstract


MRI provides highly accurate diagnostic modality for detection and characterization of HCC and there is rarely a need for percutaneous tumor biopsy using current guidelines.
Also for post-treatment follow-up which is usually accomplished with CT mainly due to low costcompared to MRI study, however, MRI is found to be superior in detecting residual or recurrent tumors after treatment.
DWI is an important sequence added to the routine MRI of the liver that helps in lesion quantification and characterization in a hope to increase the diagnostic accuracy to reach a final confident diagnosis.
Complementary to conventional MRI, a lesion on DWI is suspicious for HCC when it shows sustained, elevated signal relative to the surrounding liver parenchyma with increasing b values and low ADC compared to the background parenchyma.
The present study showed that hyperintensity on diffusion-weighted images is helpful in the diagnosis of HCC even for small lesions.
It also showed that: Diffusion restriction in diffusion-weighted imaging, arterial enhancement,venous/delayed washout +/- delayed capsular enhancement showed the most specific parameters to characterize HCC.
According to the present study it can be concluded that the diffusion-weighted MR imaging still has a limited role as an isolated technique as it is slightly inferior to dynamic contrast MRI in evaluation of HCC yet with better results in the post therapy assessment
Our results found that DWI currently cannot replace dynamic contrast MRI, but it increases the diagnostic accuracy and improves lesion detection and characterization especially for small lesions.


Other data

Title Diffusion MRI as an alternative for dynamic contrast MRI in evaluation of hepatocellular carcinoma
Other Titles دور الرنين المغناطيسى بإستخدام خاصية الإنتشار كبديل لفحص الرنين المغناطيسى بإستخدام الصبغة فى تقييم البؤر الكبدية السرطانية
Authors Shrouk Mohamed AwadallahBayomi
Issue Date 2017

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