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An overview of non-invasive imaging modalities for diagnosis of solid and cystic renal lesions

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Abstract

Renal imaging is an essential investigative tool and preliminary task for determining a suitable sanative option for the treatment of kidney cancer. In recent decades, with the increasing usage of abdominal imaging, there is an upsurge in the number of adrenal incidentalomas. Among these accidentally revealed lesions, most of them are complex that warrant immediate aggressive treatment planning due to their malignant potential. The guidelines given by the American Urological Association (AUA), American College of Radiology (ACR), and European Association of Urology (EAU) vary concerning the use of ideal preliminary imaging modality to investigate the patients with suspected flank pain, hematuria, or palpable mass in the abdomen. Initially, an effort has been made to discriminate cystic and solid renal lesions which are helpful in separating benign and malignant nature as different imaging patterns are observed on distinct imaging modalities for solid and cystic renal lesions. Various attempts have been made to improve the accuracy of cancer diagnosis by employing different imaging modalities. The primary aim of this article is to study the capabilities of different imaging techniques for detecting and differentiating solid and cystic lesions to facilitate treatment planning based on computed tomography (CT), ultrasonography (US), magnetic resonance imaging (MRI), positron emission tomography (PET), and optical coherence tomography (OCT). Further, the advantages, disadvantages, new advancements, and future scope of each of the imaging modality have also been highlighted so that one can make a correct choice of imaging technique for diagnosis of a specific type of lesion. Additionally, some recommendations have also been mentioned by listing the requirements for the perfect imaging modality.

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Kaur, R., Juneja, M. & Mandal, A.K. An overview of non-invasive imaging modalities for diagnosis of solid and cystic renal lesions. Med Biol Eng Comput 58, 1–24 (2020). https://doi.org/10.1007/s11517-019-02049-z

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