ABSTRACT Objective: To compare enhancement patterns of typical adrenal adenomas, lipid-poor adenomas, and non-adenomas on magnetic resonance imaging (MRI). Materials and Methods: Evaluation of adrenal nodules larger than 1.0 cm, with at least 2-year follow-up, evaluated on MRI in January 2007 and December 2016. Two different protocols were included - upper abdomen MRI (delayed phase after 3 minutes) and abdomen and pelvis MRI (delayed phase after 7 minutes) – and nodules were divided in typical adenomas (characterized on out-of-phase MRI sequence), lipid-poor adenomas (based on follow-up imaging stability) and non-adenomas (based on pathological finding or follow-up imaging). T2-weighted and enhancement features were analyzed (absolute and relative washout and enhancement curve pattern), similarly to classic computed tomography equations. Results: Final cohort was composed of 123 nodules in 116 patients (mean diameter of 1.8 cm and mean follow up time of 4 years and 3 months). Of them, 98 (79%) nodules had features of typical adenomas by quantitative chemical shift imaging, and demonstrated type 3 curve pattern in 77%, mean absolute and relative washout of 29% and 16%, respectively. Size, oncologic history and T2-weighted features showed statistically significant differences among groups. Also, a threshold greater than 11.75% for absolute washout on MRI achieved sensitivity of 71.4% and specificity of 70.0%, in differentiating typical adenomas from non-adenomas. Conclusion: Calculating absolute washout of adrenal nodules on MRI may help identifying proportion of non-adenomas.

RESUMO Objetivo: Avaliar os fatores anatômicos e a experiência do radiologista na detecção de massas renais sólidas na ultrassonografia. Métodos: Buscamos massas renais sólidas diagnosticadas em imagens seccionais, de 2007 a 2017, que também tivessem ultrassonografia prévia nos últimos 6 meses. As seguintes características foram avaliadas: tamanho do nódulo, lateralidade, localização e padrão de crescimento, índice de massa corporal do paciente e experiência do radiologista em ultrassonografia. Nos casos com ressecção cirúrgica, os laudos de patologia foram analisados. O teste t não pareado e o teste χ2 foram utilizados para avaliar as diferenças entre os subgrupos, usando R-statistics. A significância estatística foi estabelecida em p<0,05. Resultados: A pesquisa inicial de nódulos renais achados em imagens seccionais resultou em 428 lesões, com 266 exclusões. A coorte final incluiu 162 lesões e, destas, 108 (67%) foram detectadas corretamente na ultrassonografia (Grupo 1), e 54 (33%) não foram identificadas (Grupo 2). A comparação dos Grupos 1 e 2 mostrou índice de massa corporal (27,7 versus 27,1; p=0,496), tamanho (2,58cm versus 1,74cm; p=0,003), lateralidade (54% versus 59% no lado direito; p=0,832), localização (27% versus 22% no polo superior; p=0,869), padrão de crescimento (25% versus 28% endofítico; p=0,131) e experiência do radiologista (p=0,300). A histologia disponível para o Grupo 1 foi carcinoma renal de células claras (n=11), papilar (n=15), cromófobo (n=2), oncocitoma (n=1), e, para o Grupo 2, carcinoma renal de células claras (n=7), papilar (n=5), oncocitoma (n=2), angiomiolipoma, cromófobo e pielonefrite intersticial (n=1, cada). Conclusão: O tamanho foi o único parâmetro significativo relacionado à detecção de nódulos renais no ultrassom.

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.

Raspberry Pi é um computador de baixo custo criado com propostas educativas. Utiliza o Linux e seus softwares são gratuitos, em sua maioria. Há softwares para visualização de imagens no formato DICOM. Com o uso de um monitor externo, a resolução suportada (1920 × 1200 pixels) permite a criação de estações de visualização simples de exames com custo reduzido.

Raspberry Pi is a low-cost computer created with educational purposes. It uses Linux and, most of times, freeware applications, particularly a software for viewing DICOM images. With an external monitor, the supported resolution (1920 × 1200 pixels) allows for the set up of simple viewing workstations at a reduced cost.