The radiologic diagnosis of adrenal disease can be challenging in settings of atypical presentations, mimics of benign and malignant adrenal masses, and rare adrenal anomalies. Misdiagnosis may lead to suboptimal management and adverse outcomes. Adrenal adenoma is the most common benign adrenal tumor that arises from the cortex, whereas adrenocortical carcinoma (ACC) is a rare malignant tumor of the cortex. Adrenal cyst and myelolipoma are other benign adrenal lesions and are characterized by their fluid and fat content, respectively. Pheochromocytoma is a rare neuroendocrine tumor of the adrenal medulla. Metastases to the adrenal glands are the most common malignant adrenal tumors. While many of these masses have classic imaging appearances, considerable overlap exists between benign and malignant lesions and can pose a diagnostic challenge. Atypical adrenal adenomas include those that are lipid poor; contain macroscopic fat, hemorrhage, and/or iron; are heterogeneous and/or large; and demonstrate growth. Heterogeneous adrenal adenomas may mimic ACC, metastasis, or pheochromocytoma, particularly when they are 4 cm or larger, whereas smaller versions of ACC, metastasis, and pheochromocytoma and those with washout greater than 60% may mimic adenoma. Because of its nonenhanced CT attenuation of less than or equal to 10 HU, a lipid-rich adrenal adenoma may be mimicked by a benign adrenal cyst, or it may be mimicked by a tumor with central cystic and/or necrotic change such as ACC, pheochromocytoma, or metastasis. Rare adrenal tumors such as hemangioma, ganglioneuroma, and oncocytoma also may mimic adrenal adenoma, ACC, metastasis, and pheochromocytoma. The authors describe cases of adrenal neoplasms that they have encountered in clinical practice and presented to adrenal multidisciplinary tumor boards. Key lessons to aid in diagnosis and further guide appropriate management are provided. ^© RSNA, 2023 Online supplemental material is available for this article. Quiz questions for this article are available through the Online Learning Center.

Deep learning reconstruction CT algorithms can reduce image noise associated with lower radiation doses while preserving image texture and diagnostic performance, often overcoming the limitations of filtered backprojection and iterative reconstruction methods, and future DLR software developments combined with new CT hardware technologies such as photon-counting CT promise dramatically improved image quality.

Liver congestion is increasingly encountered in clinical practice and presents diagnostic pitfalls of which radiologists must be aware. The complex altered hemodynamics associated with liver congestion leads to diffuse parenchymal changes and the development of benign and malignant nodules. Distinguishing commonly encountered benign hypervascular lesions, such as focal nodular hyperplasia (FNH)-like nodules, from hepatocellular carcinoma (HCC) can be challenging due to overlapping imaging features. FNH-like lesions enhance during the hepatic arterial phase and remain isoenhancing relative to the background liver parenchyma but infrequently appear to wash out at delayed phase imaging, similar to what might be seen with HCC. Heterogeneity, presence of an enhancing capsule, washout during the portal venous phase, intermediate signal intensity at T2-weighted imaging, restricted diffusion, and lack of uptake at hepatobiliary phase imaging point toward the diagnosis of HCC, although these features are not sensitive individually. It is important to emphasize that the Liver Imaging Reporting and Data System (LI-RADS) algorithm cannot be applied in congested livers since major LI-RADS features lack specificity in distinguishing HCC from benign hypervascular lesions in this population. Also, the morphologic changes and increased liver stiffness caused by congestion make the imaging diagnosis of cirrhosis difficult. The authors discuss the complex liver macro- and microhemodynamics underlying liver congestion; propose a more inclusive approach to and conceptualization of liver congestion; describe the pathophysiology of liver congestion, hepatocellular injury, and the development of benign and malignant nodules; review the imaging findings and mimics of liver congestion and hypervascular lesions; and present a diagnostic algorithm for approaching hypervascular liver lesions. ^©RSNA, 2024 Test Your Knowledge questions for this article are available in the supplemental material.