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Evaluation of a multiparametric renal CT algorithm for diagnosis of clear-cell renal cell carcinoma among small (≤ 4 cm) solid renal masses.
Eldihimi, Fatma; Walsh, Cynthia; Hibbert, Rebecca M; Nasibi, Khalid Al; Pickovsky, Jana Sheinis; Schieda, Nicola.
Afiliação
  • Eldihimi F; Department of Medical Imaging, The Ottawa Hospital, 1053 Carling Avenue, Room C159, Ottawa, ON, K1Y 4E9, Canada.
  • Walsh C; Department of Medical Imaging, The Ottawa Hospital, 1053 Carling Avenue, Room C159, Ottawa, ON, K1Y 4E9, Canada.
  • Hibbert RM; Department of Medical Imaging, The Ottawa Hospital, 1053 Carling Avenue, Room C159, Ottawa, ON, K1Y 4E9, Canada.
  • Nasibi KA; Department of Medical Imaging, The Ottawa Hospital, 1053 Carling Avenue, Room C159, Ottawa, ON, K1Y 4E9, Canada.
  • Pickovsky JS; Department of Medical Imaging, The Ottawa Hospital, 1053 Carling Avenue, Room C159, Ottawa, ON, K1Y 4E9, Canada.
  • Schieda N; Department of Medical Imaging, The Ottawa Hospital, 1053 Carling Avenue, Room C159, Ottawa, ON, K1Y 4E9, Canada. nschieda@toh.ca.
Eur Radiol ; 2023 Nov 16.
Article em En | MEDLINE | ID: mdl-37968475
ABSTRACT

OBJECTIVE:

To evaluate a recently proposed CT-based algorithm for diagnosis of clear-cell renal cell carcinoma (ccRCC) among small (≤ 4 cm) solid renal masses diagnosed by renal mass biopsy.

METHODS:

This retrospective study included 51 small renal masses in 51 patients with renal-mass CT and biopsy between 2014 and 2021. Three radiologists independently evaluated corticomedullary phase CT for the following heterogeneity and attenuation ratio (massrenal cortex), which were used to inform the CT score (1-5). CT score ≥ 4 was considered positive for ccRCC. Diagnostic accuracy was calculated for each reader and overall using fixed effects logistic regression modelling.

RESULTS:

There were 51% (26/51) ccRCC and 49% (25/51) other masses. For diagnosis of ccRCC, area under curve (AUC), sensitivity, specificity, and positive predictive value (PPV) were 0.69 (95% confidence interval 0.61-0.76), 78% (68-86%), 59% (46-71%), and 67% (54-79%), respectively. CT score ≤ 2 had a negative predictive value 97% (92-99%) to exclude diagnosis of ccRCC. For diagnosis of papillary renal cell carcinoma (pRCC), CT score ≤ 2, AUC, sensitivity, specificity, and PPV were 0.89 (0.81-0.98), 81% (58-94%), 98% (93-99%), and 85% (62-97%), respectively. Pooled inter-observer agreement for CT scoring was moderate (Fleiss weighted kappa = 0.52).

CONCLUSION:

The CT scoring system for prediction of ccRCC was sensitive with a high negative predictive value and moderate agreement. The CT score is highly specific for diagnosis of pRCC. CLINICAL RELEVANCE STATEMENT The CT score algorithm may help guide renal mass biopsy decisions in clinical practice, with high sensitivity to identify clear-cell tumors for biopsy to establish diagnosis and grade and high specificity to avoid biopsy in papillary tumors. KEY POINTS • A CT score ≥ 4 had high sensitivity and negative predictive value for diagnosis of clear-cell renal cell carcinoma (RCC) among solid ≤ 4-cm renal masses. • A CT score ≤ 2 was highly specific for diagnosis of papillary RCC among solid ≤ 4-cm renal masses. • Inter-observer agreement for CT score was moderate.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Ano de publicação: 2023 Tipo de documento: Article