Abstract
More than half of patients over 50 years of age have had at least one focal renal lesion detected as an incidental finding during an ultrasound, computed tomography, or magnetic resonance imaging examination. Although the majority of such lesions can be easily detected and correctly characterized, misdiagnoses may occur and are often related to methodological limitations, inappropriate imaging protocols, or misinterpretation. This pictorial essay provides recommendations on how to recognize benign and malignant renal processes that can be potentially missed or mischaracterized in imaging studies.
Highlights
Detection of incidental renal masses has grown exponentially due to widespread use of ultrasound, computed tomography (CT), and magnetic resonance imaging (MRI) for a variety of indications[1]
Cases were divided into two categories—errors in detection and errors in interpretation—and we propose two algorithms to avoid those pitfalls (Figures 1 and 2, respectively)
User-defined regions of interest (ROIs) may help characterize enhancement based on the relative increase in signal intensity between pre- and post-contrast images, assuming that the same acquisition parameters are used[9]
Summary
Detection of incidental renal masses has grown exponentially due to widespread use of ultrasound, computed tomography (CT), and magnetic resonance imaging (MRI) for a variety of indications[1]. There are pitfalls in the detection and characterization of such masses because of inherent methodological limitations or the use of inappropriate protocols[2]. Misinterpretation is another source of pitfalls, and recognizing potentially confounding situations allows radiologists to avoid misdiagnosis in the evaluation of renal masses. This pictorial essay illustrates several cases of misdiagnosis or near-missed diagnosis of renal lesions on ultrasound, CT, and MRI, obtained for review from our database. Cases were divided into two categories—errors in detection and errors in interpretation—and we propose two algorithms to avoid those pitfalls (Figures 1 and 2, respectively)
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