A comparative study of ultrasound and cross-sectional imaging for detection of small renal masses: anatomic factors and radiologist's experience

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2020
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Abstract
ABSTRACT Objective: To evaluate anatomic factors and radiologist's experience in the detection of solid renal masses on ultrasonography. Methods: We searched for solid renal masses diagnosed on cross-sectional imaging from 2007 to 2017 that also had previous ultrasonography from the past 6 months. The following features were evaluated: nodule size, laterality, location and growth pattern, patient body mass index and radiologist's experience in ultrasound. In surgically resected cases, pathologic reports were evaluated. Unpaired t test and χ2 test were used to evaluate differences among subgroups, using R-statistics. Statistical significance was set at p<0.05. Results: The initial search of renal nodules on cross-sectional imaging resulted in 428 lesions and 266 lesions were excluded. Final cohort included 162 lesions and, of those, 108 (67%) were correctly detected on ultrasonography (Group 1) and 54 (33%) were missed (Group 2). Comparison of Groups 1 and 2 were as follows, respectively: body mass index (27.7 versus 27.1; p=0.496), size (2.58cm versus 1.74cm; p=0.003), laterality (54% versus 59% right sided; p=0.832), location (27% versus 22% upper pole; p=0.869), growth pattern (25% versus 28% endophytic; p=0.131) and radiologist's experience (p=0.300). From surgically resected cases, histology available for Group 1 was clear cell (n=11), papillary (n=15), chromophobe (n=2) renal cell carcinoma, oncocytoma (n=1), and, for Group 2, clear cell (n=7), papillary (n=5) renal cell carcinoma, oncocytoma (n=2), angiomyolipoma, chromophobe renal cell carcinoma, and interstitial pyelonephritis (n=1, each). Conclusion: Size was the only significant parameter related to renal nodule detection on ultrasound.
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Authors Yamauchi, Fernando Ide;Paiva, Omir Antunes;Mussi, Thaís Caldara;Neto, Miguel José Francisco;Baroni, Ronaldo Hueb;
Journal einstein (sao paulo, brazil)
Year 2020
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