Renal Lesion Characterization with Spectral CT: Determining the Optimal Energy for Virtual Monoenergetic Reconstruction.
Radiology
; 287(3): 874-883, 2018 06.
Article
em En
| MEDLINE
| ID: mdl-29470937
ABSTRACT
Purpose To investigate the relationship between energy level of virtual monoenergetic (VM) imaging and sensitivity in the detection of minimally enhancing renal lesions. Materials and Methods Phantoms simulating unenhanced and contrast material-enhanced renal parenchyma were equipped with inserts containing different concentrations of iodine (range, 0-1.15 mg iodine per milliliter). A total of 180 patients (117 men; mean age, 65.2 years ± 13.0 [standard deviation]) with 194 (62 solid, 132 cystic) renal lesions larger than 10 mm in diameter underwent unenhanced single-energy CT and contrast-enhanced dual-energy CT. VM imaging data sets were created for 70, 80, 90, and 100 keV. Renal lesions were measured, and enhancement was calculated. Area under the receiver operating characteristic curve (AUC) for renal lesion characterization was determined by using the DeLong method. Results The AUC was highest at 70 keV and decreased as energy increased toward 100 keV. AUC in the phantom decreased from 98% (95% confidence interval [CI] 95, 100) at 70 keV to 88% (95% CI 79, 96) at 100 keV (P = .004). AUC in patients decreased from 96% (95% CI 94, 98) at 70 keV to 79% (95% CI 71, 86) at 100 keV (P = .001). In patients with an enhancement threshold of 15 HU, sensitivity in the detection of solid renal lesions decreased between from 91% (49 of 62 [95% CI 78, 97]) at 70 keV to 48% (33 of 62 [95% CI 25, 71]) at 100 keV (P < .05), with no change in specificity (93% [120 of 132 {95% CI 87, 97}] at 70 keV, 97% [125 of 132 {95% CI 92, 99}] at 100 keV). Conclusion There is a reduction in diagnostic accuracy for renal lesion characterization with increasing VM imaging energy. The 70-keV setting may provide an optimal trade-off between sensitivity and specificity. © RSNA, 2018 Online supplemental material is available for this article.
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1
Bases de dados:
MEDLINE
Assunto principal:
Processamento de Imagem Assistida por Computador
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Interpretação de Imagem Radiográfica Assistida por Computador
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Intensificação de Imagem Radiográfica
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Tomografia Computadorizada por Raios X
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Meios de Contraste
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Neoplasias Renais
Tipo de estudo:
Diagnostic_studies
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Observational_studies
Limite:
Aged
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Female
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Humans
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Male
Idioma:
En
Revista:
Radiology
Ano de publicação:
2018
Tipo de documento:
Article