OBJECTIVE: The purpose of this study is to validate a multivariable predictive model previously developed to differentiate between renal cell carcinoma (RCC) and oncocytoma using CT parameters. METHODS AND MATERIALS: We included 100 renal lesions with final diagnosis of RCC or oncocytoma studied before surgery with 4-phase multidetector CT (MDCT). We evaluated the characteristics of the tumors and the enhancement patterns at baseline, arterial, nephrographic and excretory MDCT phases. RESULTS: Histopathologically 15 tumors were oncocytomas and 85 RCCs. RCCs were significantly larger (median 4.4 cm vs 2.8 cm, p = 0.006). There were significant differences in nodule attenuation in the excretory phase compared to baseline (median: 31 vs 42, p = 0.015), with RCCs having lower values. Heterogeneous enhancement patterns were also more frequent in RCCs (85.9% vs 60%, p = 0.027).Multivariable analysis showed that the independent predictors of malignancy were the enhancement pattern, with oncocytomas being more homogeneous in the nephrographic phase [Odds Ratio (OR) 0.16 (95% CI 0.03 to 0.75, p = 0.02)], nodule enhancement in the excretory phase compared to baseline, with RCCs showing lower enhancement [OR 0.96 (95% CI 0.93 to 0.99, p = 0.005)], and a size > 4 cm, with RCCs being larger [OR 5.89 (95% CI 1.10 to 31.58), p = 0.038]. CONCLUSION: The multivariable predictive model previously developed which combines different MDCT parameters, including lesion size > 4 cm, lesion enhancement in the excretory phase compared to baseline and enhancement heterogeneity, can be successfully applied to distinguish RCC from oncocytoma. ADVANCES IN KNOWLEDGE: This study confirms that multiparametric assessment using MDCT (including parameters such as size, homogeneity and enhancement differences between the excretory and the baseline phases) can help distinguish between RCCs and oncocytomas. While it is true that this multiparametric predictive model may not always correctly classify renal tumors such as RCC or oncocytoma, it can be used to determine which patients would benefit from pre-surgical biopsy to confirm that the tumor is in fact an oncocytoma, and thereby avoid unnecessary surgical treatments.
OBJECTIVE: The purpose of this study is to validate a multivariable predictive model previously developed to differentiate between renal cell carcinoma (RCC) and oncocytoma using CT parameters. METHODS AND MATERIALS: We included 100 renal lesions with final diagnosis of RCC or oncocytoma studied before surgery with 4-phase multidetector CT (MDCT). We evaluated the characteristics of the tumors and the enhancement patterns at baseline, arterial, nephrographic and excretory MDCT phases. RESULTS: Histopathologically 15 tumors were oncocytomas and 85 RCCs. RCCs were significantly larger (median 4.4 cm vs 2.8 cm, p = 0.006). There were significant differences in nodule attenuation in the excretory phase compared to baseline (median: 31 vs 42, p = 0.015), with RCCs having lower values. Heterogeneous enhancement patterns were also more frequent in RCCs (85.9% vs 60%, p = 0.027).Multivariable analysis showed that the independent predictors of malignancy were the enhancement pattern, with oncocytomas being more homogeneous in the nephrographic phase [Odds Ratio (OR) 0.16 (95% CI 0.03 to 0.75, p = 0.02)], nodule enhancement in the excretory phase compared to baseline, with RCCs showing lower enhancement [OR 0.96 (95% CI 0.93 to 0.99, p = 0.005)], and a size > 4 cm, with RCCs being larger [OR 5.89 (95% CI 1.10 to 31.58), p = 0.038]. CONCLUSION: The multivariable predictive model previously developed which combines different MDCT parameters, including lesion size > 4 cm, lesion enhancement in the excretory phase compared to baseline and enhancement heterogeneity, can be successfully applied to distinguish RCC from oncocytoma. ADVANCES IN KNOWLEDGE: This study confirms that multiparametric assessment using MDCT (including parameters such as size, homogeneity and enhancement differences between the excretory and the baseline phases) can help distinguish between RCCs and oncocytomas. While it is true that this multiparametric predictive model may not always correctly classify renal tumors such as RCC or oncocytoma, it can be used to determine which patients would benefit from pre-surgical biopsy to confirm that the tumor is in fact an oncocytoma, and thereby avoid unnecessary surgical treatments.
Authors: Stephanie A Lee-Felker; Ely R Felker; Nelly Tan; Daniel J A Margolis; Jonathan R Young; James Sayre; Steven S Raman Journal: AJR Am J Roentgenol Date: 2014-11 Impact factor: 3.959
Authors: Jeong Kon Kim; Tae Kyoung Kim; Han Jong Ahn; Chung Soo Kim; Kyu-Rae Kim; Kyoung-Sik Cho Journal: AJR Am J Roentgenol Date: 2002-06 Impact factor: 3.959
Authors: Jonathan R Young; Daniel Margolis; Steven Sauk; Allan J Pantuck; James Sayre; Steven S Raman Journal: Radiology Date: 2013-02-04 Impact factor: 11.105
Authors: R Houston Thompson; Jordan M Kurta; Matthew Kaag; Satish K Tickoo; Shilajit Kundu; Darren Katz; Lucas Nogueira; Victor E Reuter; Paul Russo Journal: J Urol Date: 2009-03-14 Impact factor: 7.450