Literature DB >> 31748942

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

Ravinder Kaur1, Mamta Juneja2, A K Mandal3.   

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. Graphical abstract.

Entities:  

Keywords:  CT; Cystic; Lesions; MRI; OCT; PET; Renal cancer; US

Year:  2019        PMID: 31748942     DOI: 10.1007/s11517-019-02049-z

Source DB:  PubMed          Journal:  Med Biol Eng Comput        ISSN: 0140-0118            Impact factor:   2.602


  131 in total

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Authors:  Jean-Michel Correas; Michel Claudon; François Tranquart; And Olivier Hélénon
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2.  Differentiation of papillary renal cell carcinoma subtypes on CT and MRI.

Authors:  Nathan D Egbert; Elaine M Caoili; Richard H Cohan; Matthew S Davenport; Isaac R Francis; L Priya Kunju; James H Ellis
Journal:  AJR Am J Roentgenol       Date:  2013-08       Impact factor: 3.959

3.  Renal papillary carcinoma: CT and MRI features.

Authors:  C Couvidat; D Eiss; V Verkarre; S Merran; J-M Corréas; A Méjean; O Hélénon
Journal:  Diagn Interv Imaging       Date:  2014-11       Impact factor: 4.026

4.  Computed Tomography Perfusion Measurements in Renal Lesions Obtained by Bayesian Estimation, Advanced Singular-Value Decomposition Deconvolution, Maximum Slope, and Patlak Models: Intermodel Agreement and Diagnostic Accuracy of Tumor Classification.

Authors:  Dominik Deniffel; Timothé Boutelier; Aissam Labani; Mickael Ohana; Daniela Pfeiffer; Catherine Roy
Journal:  Invest Radiol       Date:  2018-08       Impact factor: 6.016

5.  An In-vivo Prospective Study of the Diagnostic Yield and Accuracy of Optical Biopsy Compared with Conventional Renal Mass Biopsy for the Diagnosis of Renal Cell Carcinoma: The Interim Analysis.

Authors:  Mara Buijs; Peter G K Wagstaff; Daniel M de Bruin; Patricia J Zondervan; Cemile Dilara Savci-Heijink; Otto M van Delden; Ton G van Leeuwen; R Jeroen A van Moorselaar; Jean J M C H de la Rosette; Maria Pilar Laguna Pes
Journal:  Eur Urol Focus       Date:  2017-10-24

6.  Differentiation of Clear Cell Renal Cell Carcinoma From Other Subtypes and Fat-Poor Angiomyolipoma by Use of Quantitative Enhancement Measurement During Three-Phase MDCT.

Authors:  See Hyung Kim; Chan Sun Kim; Mi Jeong Kim; Jeong Yeon Cho; Seung Hyun Cho
Journal:  AJR Am J Roentgenol       Date:  2016-01       Impact factor: 3.959

7.  Renal pseudotumors.

Authors:  Shweta Bhatt; Gregory MacLennan; Vikram Dogra
Journal:  AJR Am J Roentgenol       Date:  2007-05       Impact factor: 3.959

8.  Renal masses: quantitative analysis of enhancement with signal intensity measurements versus qualitative analysis of enhancement with image subtraction for diagnosing malignancy at MR imaging.

Authors:  Elizabeth M Hecht; Gary M Israel; Glenn A Krinsky; Winnie Y Hahn; Danny C Kim; Ilana Belitskaya-Levy; Vivian S Lee
Journal:  Radiology       Date:  2004-06-23       Impact factor: 11.105

9.  Superb microvascular imaging is a rational choice for accurate Bosniak classification of renal cystic masses.

Authors:  Jie Mu; Yiran Mao; Fangxuan Li; Xiaojie Xin; Sheng Zhang
Journal:  Br J Radiol       Date:  2019-05-20       Impact factor: 3.039

10.  Diffusion-Weighted Imaging of Upper Abdominal Organs Acquired with Multiple B-Value Combinations: Value of Normalization Using Spleen as the Reference Organ.

Authors:  Bo Ram Kim; Ji Soo Song; Eun Jung Choi; Seung Bae Hwang; Hong Pil Hwang
Journal:  Korean J Radiol       Date:  2018-04-06       Impact factor: 3.500

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  1 in total

Review 1.  Artificial intelligence for renal cancer: From imaging to histology and beyond.

Authors:  Karl-Friedrich Kowalewski; Luisa Egen; Chanel E Fischetti; Stefano Puliatti; Gomez Rivas Juan; Mark Taratkin; Rivero Belenchon Ines; Marie Angela Sidoti Abate; Julia Mühlbauer; Frederik Wessels; Enrico Checcucci; Giovanni Cacciamani
Journal:  Asian J Urol       Date:  2022-06-18
  1 in total

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