Literature DB >> 16679114

Diagnosis of angiomyolipoma using computed tomography-region of interest < or =-10 HU or 4 adjacent pixels < or =-10 HU are recommended as the diagnostic thresholds.

E Simpson1, U Patel.   

Abstract

AIM: To study and compare the diagnostic accuracy of region of interest (ROI) density measurement and pixel mapping [computed tomography (CT) density of individual pixels] for the diagnosis of renal angiomyolipoma (AML) using CT.
MATERIALS AND METHODS: A study group of histologically proven AMLs was compared with a control group of histologically proven renal cell cancers, normal renal parenchyma, and simple renal cysts. The mean tissue density (ROI circle) and a pixel density map were recorded. The diagnostic accuracy of various thresholds of ROI and pixel mapping values were compared using receiver operating characteristic curves.
RESULTS: Twenty-two AMLs, 16 renal cell carcinomas (RCCs), 30 simple cysts, and 30 sites of renal parenchyma were evaluated. The mean (+/-1 SD) density of the AMLs was significantly lower [-15.2(20.8) units] than the three control groups [+36.0(8.1) units, +5.4(3.4) units and +22.2(46.5) units for RCC, renal cyst and parenchyma respectively; p < 0.001 (analysis of variance)]. The sensitivities and specificities of the ROI diagnostic thresholds of < or =0 units, < or =-10 units and < or =-20 units were 77 and 97%, 73 and 100% and 50 and 100%, respectively. Using pixel mapping [diagnostic thresholds of either a line of 4 pixels < or =-10 units or a square of 4 pixels < or =-10 units] the sensitivity improves to 86% with a specificity of 97%.
CONCLUSION: Although a ROI threshold value of < or =-10 units has a very high specificity (100% in the present study) the sensitivity is modest at only 73%. Pixel mapping is more sensitive for recognizing small clusters of fat. In practice, both methods can be recommended for the analysis of suspected AMLs. ROI density measurement is convenient when analysing large areas of suspected fat and < or =-10 units should be used as the diagnostic threshold. When faced with small lucent areas or indeterminate values after ROI analysis, pixel mapping is recommended using a line of 4 pixels < or =-10 units or a square of 4 pixels < or =-10 units as the discriminating thresholds.

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Year:  2006        PMID: 16679114     DOI: 10.1016/j.crad.2005.12.013

Source DB:  PubMed          Journal:  Clin Radiol        ISSN: 0009-9260            Impact factor:   2.350


  15 in total

1.  Radiomics of small renal masses on multiphasic CT: accuracy of machine learning-based classification models for the differentiation of renal cell carcinoma and angiomyolipoma without visible fat.

Authors:  Ruimeng Yang; Jialiang Wu; Lei Sun; Shengsheng Lai; Yikai Xu; Xilong Liu; Ying Ma; Xin Zhen
Journal:  Eur Radiol       Date:  2019-08-29       Impact factor: 5.315

Review 2.  Solid renal masses: what the numbers tell us.

Authors:  Stella K Kang; William C Huang; Pari V Pandharipande; Hersh Chandarana
Journal:  AJR Am J Roentgenol       Date:  2014-06       Impact factor: 3.959

3.  Selective arterial embolization of symptomatic and asymptomatic renal angiomyolipomas: a retrospective study of safety, outcomes and tumor size reduction.

Authors:  Florian Bardin; Olivier Chevallier; Aurélie Bertaut; Emmanuel Delorme; Morgan Moulin; Pierre Pottecher; Lucy Di Marco; Sophie Gehin; Eric Mourey; Luc Cormier; Christiane Mousson; Marco Midulla; Romaric Loffroy
Journal:  Quant Imaging Med Surg       Date:  2017-02

Review 4.  CT and MRI of small renal masses.

Authors:  Zhen J Wang; Antonio C Westphalen; Ronald J Zagoria
Journal:  Br J Radiol       Date:  2018-05-10       Impact factor: 3.039

5.  Angiomyolipoma being surgically excised for presumed kidney carcinoma.

Authors:  Weibin Hou; He Xiao; Guanghua Liu; Zhigang Ji
Journal:  Int Urol Nephrol       Date:  2015-05-05       Impact factor: 2.370

Review 6.  Imaging of Solid Renal Masses.

Authors:  Fernando U Kay; Ivan Pedrosa
Journal:  Radiol Clin North Am       Date:  2016-12-12       Impact factor: 2.303

7.  Pitfalls in the diagnosis and treatment of fat-poor angiomyolipoma of the renal pelvis mimicking urothelial carcinoma: report of three rare cases.

Authors:  Fang Xie; Jiming Zhao; Fajuan Cheng; Zhigang Yao; Bin Zheng; Zhihong Niu; Wei He
Journal:  Am J Transl Res       Date:  2022-07-15       Impact factor: 3.940

Review 8.  Imaging of Solid Renal Masses.

Authors:  Fernando U Kay; Ivan Pedrosa
Journal:  Urol Clin North Am       Date:  2018-06-15       Impact factor: 2.241

9.  Lipid-poor renal angiomyolipoma: Differentiation from clear cell renal cell carcinoma using wash-in and washout characteristics on contrast-enhanced computed tomography.

Authors:  Pingkun Xie; Zhihui Yang; Zheng Yuan
Journal:  Oncol Lett       Date:  2016-02-09       Impact factor: 2.967

10.  Clinically relevant imaging in tuberous sclerosis.

Authors:  Rupa Radhakrishnan; Sadhna Verma
Journal:  J Clin Imaging Sci       Date:  2011-07-27
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