وثيقة

Identification of sonographic features for predicting benign versus malignant mediastinal or hilar lymph nodes using endobronchial ultrasound.

مؤلف
المساهمون
الناشر
Oman Medical Specialty Board.
ميلادي
2020-03
اللغة
الأنجليزية
الملخص الإنجليزي
Objectives: In countries with a high prevalence of tuberculosis, such as Iran, the differentiation of malignant from non-malignant tumors is crucial. We attempted to find a reliable model in determining malignant nodes by investigating the sonographic characteristics of lymph nodes (LNs). Methods: In this prospective study, the morphologic characteristics of LNs, including size, shape, vascular pattern, echogenicity, margin, coagulation necrosis sign, calcification, and central hilar structure, which had been obtained during endobronchial ultrasound-guided transbronchial needle aspiration, were compared with the final pathology results. Results: We examined 253 LNs from 93 patients. Round shape, non-hilar vascular pattern, heterogeneous echogenicity, hyperechogenicity, distinct margin, and the existence of necrosis signs were significantly higher in malignant nodes. On the other hand, the existence of calcification, as well as the presence of central hilar structure, were highly suggestive of benign nodes (p < 0.050). Multivariate logistic regression revealed that size > 1 cm, heterogeneous echogenicity, hyperechogenicity, the existence of necrosis signs, and the lack of central hilar structure are independent predictive factors for malignancy. The accuracy of each of the aforementioned characteristics are 42.3%, 71.5%, 71.9%, 73.5%, and 65.6%, respectively. Of 74 malignant LNs, 100% had at least one of these independent factors. Conclusions: The morphological features of LNs based on endobronchial ultrasound-guided transbronchial needle aspiration can play a role in predicting malignancy.
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Abedini, Atefeh, Razavi, Fatemeh, Mehravaran, Hossein, Toutkaboni, Mihan Pourabdollah, Kashefizadeh, Alireza, Emami, Habib, Dizaji, Mehdi Kazempour, Farahani, Mehrdad, & Kiani, Arda (2020). Identification of sonographic features for predicting benign vers
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مواد أخرى لنفس الموضوع

المجلات والدوريات
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Zeinali, Tayebeh.
Oman Medical Specialty Board.
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Miri, Mohammad Reza.
Oman Medical Specialty Board.
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Albasoos, Hani.
جامعة السلطان قابوس. كلية الآداب والعلوم الاجتماعية
2019
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Al-Riyami, Salim.
Oman Medical Specialty Board.
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Orah, Nnamdi O.
College of Medicine, Sultan Qaboos University.
2017-10
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Basir, Norwani.
Oman Medical Specialty Board.
2012-11