Literature DB >> 23864062

MDCT-based scoring system for differentiating angiomyolipoma with minimal fat from renal cell carcinoma.

Mi-hyun Kim1, JungBok Lee, Gyunggoo Cho, Kyoung-Sik Cho, Jungmi Kim, Jeong Kon Kim.   

Abstract

BACKGROUND: Subtype-related various computed tomography (CT) features of renal cell carcinoma (RCC) are a confusing factor in differentiating angiomyolipoma with minimal fat (AMLmf) from RCC. To overcome RCC heterogeneity, a scoring system, which integrates multiple discrimitive parameters can be helpful for differentiating AMLmf from RCC.
PURPOSE: To develop a MDCT-based scoring system for differentiating AMLmf from RCC.
MATERIAL AND METHODS: In 407 patients with pathologically confirmed 48 AMLmfs and 359 RCCs (247 clear cell RCCs, 67 papillary RCCs, and 45 chromophobe RCCs), MDCT features (ratio of long-to-short diameter, enhancement characteristics, tumor attenuation on unenhanced scan, tumor margin, calcification), age, and sex were compared between AMLmf and RCCs. Based on logistic regression, a scoring system for diagnosing AMLmf over RCC was built, and its diagnostic accuracy was evaluated.
RESULTS: Scores suggesting AMLmf, i.e. the logit function as used in logistic regression analysis, were calculated as follows: Score = e(6.16.A-0.003.B+1.20.C+0.97.D+2.13.E-0.05.F)/1+e(6.16.A-0.003.B+1.20.C+0.97.D+2.13.E-0.05.F), where A = ratio of long-to-short diameter, B = enhancement amount in early excretory phase, C = homogeneous enhancement, D = tumor attenuation on unenhanced scan, E = sex, and F = age. Area under receiver-operating characteristics curve of scoring system was 0.919. With a score of 0.204 or higher, the scoring system yielded greatest accuracy (90%, 368/407) for diagnosing AMLmf over RCC, which was greater than that of any single MDCT or clinical parameter (53-85%) (P < 0.05). With a score of 0.317 or higher, sensitivity and specificity were 68% (32/48) and 95% (340/359).
CONCLUSION: MDCT-based scoring system can improve diagnostic performance of MDCT in differentiating AMLmf from RCC and help patients with AMLmf to avoid unnecessary surgery with high specificity.

Entities:  

Keywords:  Kidney neoplasm; angiomyolipoma; multidetector computed tomography; renal cell carcinoma

Mesh:

Year:  2013        PMID: 23864062     DOI: 10.1177/0284185113491087

Source DB:  PubMed          Journal:  Acta Radiol        ISSN: 0284-1851            Impact factor:   1.990


  6 in total

1.  Role of MRI in indeterminate renal mass: diagnostic accuracy and impact on clinical decision making.

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Review 2.  Renal angiomyolipoma: preoperative identification of atypical fat-poor AML.

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3.  Predictive Value of CT-Based Radiomics in Distinguishing Renal Angiomyolipomas with Minimal Fat from Other Renal Tumors.

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Review 4.  Imaging findings of common benign renal tumors in the era of small renal masses: differential diagnosis from small renal cell carcinoma: current status and future perspectives.

Authors:  Sungmin Woo; Jeong Yeon Cho
Journal:  Korean J Radiol       Date:  2015-01-09       Impact factor: 3.500

5.  Reproducibility of a novel computed-tomography based measurement of renal papillary density in the Framingham Heart Study.

Authors:  Aaron J Yeoh; Joe Massaro; Caroline S Fox; Udo Hoffmann; Brian H Eisner; Gearoid M McMahon
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6.  Low-dose gadobenate dimeglumine-enhanced MRI of the kidney for the differential diagnosis of localized renal lesions.

Authors:  Guenther Schneider; Thorsten Probst; Miles A Kirchin; Jonas Stroeder; Peter Fries; Arno Buecker
Journal:  Radiol Med       Date:  2015-06-19       Impact factor: 3.469

  6 in total

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