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DOI 10.4103/jcis.jcis_84_16

Медицинская библиотека · Journal of clinical imaging science · 2017

Apparent Diffusion Coefficient Measurement in Mediastinal Lymphadenopathies: Differentiation between Benign and Malignant Lesions.

Ustabasioglu Fethi Emre, Samanci Cesur, Alis Deniz, Samanci Nilay Sengul, Kula Osman, Olgun Deniz Cebi

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Аннотация

OBJECTIVES

We aimed to prospectively assess the diagnostic value of apparent diffusion coefficient (ADC) measurement in the differentiation of benign and malignant mediastinal lymphadenopathies.

MATERIALS AND

METHODS

The study included 63 consecutive patients (28 women, 35 men; mean age 59.3 years) with 125 mediastinal lymphadenopathies. Echoplanar diffusion-weighted magnetic resonance imaging of the mediastinum was performed with b-factors of 0 and 600 mm2/s before mediastinoscopy and mediastinotomy, and ADC values were measured. The ADC values were compared with the histological results, and statistical analysis was done. P < 0.05 was considered statistically significant.

RESULTS

The mean ADC value of malignant mediastinal lymphadenopathy (1.030 ± 0.245 × 10-3 mm2/s) was significantly lower (P < 0.05) when compared to benign lymphadenopathies (1.571 ± 0.559 × 10-3 mm2/s). For differentiating malignant from benign mediastinal lymphadenopathy, the best result was obtained when an ADC value of 1.334 × 10-3 mm2/s was used as a threshold value; area under the curve 0.848, accuracy 78.4%, sensitivity 66%, specificity of 86%, positive predictive value 76.7%, and negative predictive value of 79.2%. Interobserver agreement was excellent for ADC measurements.

CONCLUSIONS

ADC measurements could be considered an important supportive method in differentiating benign from malignant mediastinal lymphadenopathies.

Для цитирования: Ustabasioglu Fethi Emre, Samanci Cesur, Alis Deniz, Samanci Nilay Sengul, Kula Osman, Olgun Deniz Cebi. Apparent Diffusion Coefficient Measurement in Mediastinal Lymphadenopathies: Differentiation between Benign and Malignant Lesions.. Journal of clinical imaging science. 2017. DOI: 10.4103/jcis.jcis_84_16.
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