Tomoelastography Distinguishes Noninvasively between Benign and Malignant Liver Lesions.

Patients with increased liver stiffness have a higher risk of developing cancer, however, the role of fluid-solid tissue interactions and their contribution to liver tumor malignancy remains elusive. Tomoelastography is a novel imaging method for mapping quantitatively the solid-fluid tissue properties of soft tissues in vivo. It provides high resolution and thus has clear clinical applications. In this work we used tomoelastography in 77 participants, with a total of 141 focal liver lesions of different etiologies, to investigate the contributions of tissue stiffness and fluidity to the malignancy of liver tumors. Shear-wave speed (c) as surrogate for tissue stiffness and phase-angle (φ) of the complex shear modulus reflecting tissue fluidity were abnormally high in malignant tumors and allowed them to be distinguished from nontumorous liver tissue with high accuracy [c: AUC = 0.88 with 95% confidence interval (CI) = 0.83-0.94; φ: AUC = 0.95, 95% CI = 0.92-0.98]. Benign focal nodular hyperplasia and hepatocellular adenoma could be distinguished from malignant lesions on the basis of tumor stiffness (AUC = 0.85, 95% CI = 0.72-0.98; sensitivity = 94%, 95% CI = 89-100; and specificity = 85%, 95% CI = 62-100), tumor fluidity (AUC = 0.86, 95% CI = 0.77-0.96; sensitivity = 83%, 95% CI = 72-93; and specificity = 92%, 95% CI = 77-100) and liver stiffness (AUC = 0.84, 95% CI = 0.74-0.94; sensitivity = 72%, 95% CI = 59-83; and specificity = 88%, 95% CI = 69-100), but not on the basis of liver fluidity. Together, hepatic malignancies are characterized by stiff, yet fluid tissue properties, whereas surrounding nontumorous tissue is dominated by solid properties. Tomoelastography can inform noninvasively on the malignancy of suspicious liver lesions by differentiating between benign and malignant lesions with high sensitivity based on stiffness and with high specificity based on fluidity. SIGNIFICANCE: Solid-fluid tissue properties measured by tomoelastography can distinguish malignant from benign masses with high accuracy and provide quantitative noninvasive imaging biomarkers for liver tumors. ©2019 American Association for Cancer Research.