Discrimination of Malignant versus Benign Mediastinal Lymph Nodes Using Diffusion MRI with an IVIM Model.
Eur Radiol
; 28(3): 1301-1309, 2018 Mar.
Article
em En
| MEDLINE
| ID: mdl-28929210
OBJECTIVES: To investigate the value of an intravoxel incoherent motion (IVIM) diffusion model for discriminating malignant versus benign mediastinal lymph nodes (MLN). METHODS: Thirty-five subjects with enlarged MLN were scanned at 1.5 Tesla. Diffusion-weighted imaging was performed with eight b-values. IVIM parameters D, D*, and f, as well as apparent diffusion coefficient (ADC) from a mono-exponential model were obtained. 91 nodes (49 malignant and 42 benign) were analysed with pathologic (n=90) or radiologic (n=1) confirmations. Receiver operating characteristic (ROC) analysis was used to evaluate the diagnostic performance. RESULTS: The mean values of D, ADC, and f for the malignant group were significantly lower than those for the benign group (p<0.001), while D* showed no significant difference (p=0.281). In the ROC analysis, the combination of D and f produced the largest area under the curve (0.953) compared to ADC or other individual IVIM parameters, leading to the best specificity (92.9%) and diagnostic accuracy (90.1%). CONCLUSION: This study demonstrates that the combination of IVIM parameters can improve differentiation between malignant and benign MLN as compared to using ADC alone. KEY POINTS: ⢠Diffusion MRI is useful for non-invasively discriminating malignant versus benign lymph nodes. ⢠A mono-exponential model is not adequate to characterise diffusion process in lymph nodes. ⢠IVIM model is advantageous over mono-exponential model for assessing lymph node malignancy. ⢠Combination of IVIM parameters improves differentiation of malignant versus benign lymph nodes.
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Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Imagem de Difusão por Ressonância Magnética
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Linfadenopatia
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Linfonodos
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Neoplasias do Mediastino
Tipo de estudo:
Diagnostic_studies
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Prognostic_studies
Limite:
Adult
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Aged
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Female
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Humans
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Male
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Middle aged
Idioma:
En
Ano de publicação:
2018
Tipo de documento:
Article