Abstract

Background: In this article, we highlight the importance of utilizing multiple imaging modalities, including CT, MRI, and abdominal Doppler ultrasound, to accurately differentiate between atypical liver hemangiomas (LH) and metastases. Case report: We introduce a 57-year-old male patient who presented with severe abdominal pain. Initial CT scan findings showed hypodense liver lesions and a well-defined hypodense mass in the sub-diaphragmatic region, raising suspicion for metastatic liver lesions, and prompting further evaluation. To differentiate between atypical hemangiomas and metastases, an MRI scan was performed, revealing a hyperintense signal on T2-weighted images and a hypointense signal on T1-weighted images, consistent with the characteristics of LH. These characteristic signal intensities aided in ruling out metastatic liver lesions, which typically present with a more solid and homogeneous appearance. Contrast-enhanced MRI played a crucial role in confirming the diagnosis. The liver lesions demonstrated moderate vascularization during the early phase of contrast enhancement, followed by progressive centripetal filling during the portal venous and delayed phases. This enhancement pattern is consistent with the slow flow within the dilated vascular spaces of liver hemangiomas. The lesion in the right liver lobe is almost completely filled with contrast, further supporting the diagnosis of hemangioma. Abdominal Doppler ultrasound can provide additional information regarding the vascularity of liver lesions. In this case, the Doppler examination likely helped to further confirm the presence of a hemangioma, as these lesions typically demonstrate increased vascularity compared to metastatic lesions. Conclusion: The comprehensive imaging evaluation utilizing CT, MRI, and abdominal Doppler ultrasound allowed for the confident differentiation of atypical liver hemangiomas from metastatic liver lesions in this case. This emphasizes the importance of a multimodal imaging approach in cases of liver lesions with overlapping features, leading to improved patient management and outcomes.

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