Endoscopic ultrasound in the diagnosis of
mediastinal diseases

Wang, Zhiguo; Jiang, Chunmeng

doi:10.1515/med-2015-0095

Cited by 7 publications

(4 citation statements)

References 65 publications

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“…EUS is considered a valuable tool for detecting metastatic LNs in patients in whom this could affect cancer staging and further management. [ 18 ] Many neoplasms metastasize to mediastinal LNs. The most commonly encountered in everyday practice are lung (especially NSCLCs), esophagus, breast, thyroid, and renal cell cancer.…”

Section: Clinical Implications Of Eus Mediastinal Examinationmentioning

confidence: 99%

Practical approach to linear EUS examination of the mediastinum

Okasha¹,

Elmeligui²,

Pawlak³

et al. 2021

Endoscopic Ultrasound

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EUS has become a substantial diagnostic and therapeutic modality for many anatomical regions. The extent of endosonographic assessment is wide, and among others, allows for the evaluation of the mediastinal anatomy and related pathologies such as mediastinal lymphadenopathy and staging of central malignant lung lesions. Moreover, EUS assessment has proved more accurate in detecting small lesions missed by standard imaging examinations such as computed tomography or magnetic resonance. Endosonographically, various mediastinal anatomical landmarks and stations can be visualized by transesophageal scanning, thus providing arranged systematic examination of the mediastinum. In addition, the correct position during the examination is crucial for EUS-guided procedures such as tissue sampling and drainage of mediastinal abscesses. The evolution of EUS-guided diagnostic and interventional procedures has contributed to the increasing importance of understanding the mediastinal anatomy during the EUS examination.

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Section: Clinical Implications Of Eus Mediastinal Examinationmentioning

confidence: 99%

Practical approach to linear EUS examination of the mediastinum

Okasha¹,

Elmeligui²,

Pawlak³

et al. 2021

Endoscopic Ultrasound

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“…Ultrasound frequently reveals a typical pattern of isoechoic or hypoechoic lymph nodes, sometimes with prominent vessels and sometimes with a central hyperechoic strand within these nodes. However, these EUS characteristics are not distinctive of sarcoidosis, and cannot be used to distinguish these lesions from tuberculosis or malignancy [57].…”

Section: Recent Bronchoscopic Techniquesmentioning

confidence: 99%

“…Unlike EBUS-TBNA or cTBNA, additional procedures, such as TBLB or EBB, cannot be performed at the same time as EUS-FNA [60]. EUS-FNA is better tolerated than EBUS-TBNA, and is usually associated with fewer doses of anesthetics and sedatives, shorter procedure times and fewer oxygen desaturations [57]. It is also a good choice in cases of poor respiratory reserve and/or intractable cough [16].…”

Section: Recent Bronchoscopic Techniquesmentioning

confidence: 99%

Role of Bronchoscopic Techniques in the Diagnosis of Thoracic Sarcoidosis

Pedro

Melo

Bastos

et al. 2019

JCM

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The diagnosis of sarcoidosis relies on clinical and radiological presentation, evidence of non-caseating granulomas in histopathology and exclusion of alternative causes of granulomatous inflammation. Currently, a proper diagnosis, with a high level of confidence, is considered as key to the appropriate diagnosis and management of the disease. In this sense, this review aims to provide a brief overview on the role of bronchoscopy in the diagnosis of thoracic sarcoidosis, incorporating newer techniques to establish, including endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA), endoscopic ultrasound-guided fine-needle aspiration (EUS-FNA), transesophageal ultrasound-guided needle aspiration with the use of an echo bronchoscope (EUS-B-FNA) and transbronchial lung cryobiopsy (TBLC). Most of the literature reports the diagnostic superiority of endosonographic techniques, such as EBUS-TBNA alone or in combination with EUS-FNA, over conventional bronchoscopic modalities in diagnosing Scadding stages I and II of the disease. Moreover, TBLC may be considered a useful and safe diagnostic tool for thoracic sarcoidosis, overcoming some limitations of transbronchial lung biopsy (TBLB), avoiding more invasive modalities and being complementary to endosonographic procedures such as EBUS-TBNA.

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“…Satisfactory sampling is essential for diagnosis and classification of malignant lymphoma. Fundamental steps are identification of the best site, the easiest access, and the choice of the most appropriate technique, to avoid inconclusive results [9][10][11]. The surgically excised tissue biopsy is widely accepted as the gold standard for the diagnosis of lymphoma based upon the current international guidelines, however it probes only confined parts of the tumor, especially in bulky disease [1,3].…”

Section: Introductionmentioning

confidence: 99%

Machine-Learning Approach Using FDG-PET-Based Radiomics in the Characterization of Mediastinal Bulky Lymphomas.

Abenavoli

Linguanti

Barbetti

et al. 2022

Preprint

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Purpose: Mediastinal bulky involvement is common in lymphomas, particularly in classical Hodgkin lymphoma (cHL), primary mediastinal B-cell lymphoma (PMBCL) and grey zone lymphoma (GZL). Despite advanced methods of assessment, traditional imaging appears insufficient in differentiating histology. This study tested the diagnostic value of 18F-FDG PET/CT volumetric and texture parameters in the histological differentiation of mediastinal bulky due to GZL, PMBCL and cHL, also using a machine-learning approach. Methods: We retrospectively reviewed patients with mediastinal bulky disease with a histopathological diagnosis of cHL, PMBCL or GZL who underwent pre-treatment 18F-FDG PET/CT. Lesions were delineated using a fully automated preselection of 18F-FDG avid structures defined by a threshold SUV ≥ 2.5. Volumetric and radiomic parameters were measured using LIFEx software both for bulky lesion (BL) and for all lesions (AL) on 18F-FDG PET/CT. Analysis of selected radiomic features was performed with Machine Learning classifiers based on Logistic Regression. Results: We reviewed 117 patients (29 PMBCL, 80 cHL, 8 GZL). The analysis showed significant differences between the 3 lymphoma groups regarding SUVmax, SUVmean, BL/AL-MTV and BL/AL-TLG. Several PET textural features both of first order and of second order grey-level showed significant differences between the 3 groups. Finally, machine-learning classifier provided good accuracy in the discrimination between groups. Logistic Regression showed good performance, confirming true positive rate (TPR) and true negative rate (TNR) greater than 80% in the characterization of PMBCL and cHL. The multiclass classifier showed TPR greater than 70% and TNR lower 5% in the identification of PMBCL and cHL and TPR of 44% in GZL. Conclusion: Mediastinal bulky involvement from different histologies showed diverse 18F-FDG-PET radiomic features and the machine-learning approach successfully identified the different subtypes. Our results support the potential of metabolic heterogeneity as an imaging biomarker, and the use of radiomic features for early characterization of mediastinal bulky lymphoma.

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Endoscopic ultrasound in the diagnosis of mediastinal diseases

Cited by 7 publications

References 65 publications

Practical approach to linear EUS examination of the mediastinum

Practical approach to linear EUS examination of the mediastinum

Role of Bronchoscopic Techniques in the Diagnosis of Thoracic Sarcoidosis

Machine-Learning Approach Using FDG-PET-Based Radiomics in the Characterization of Mediastinal Bulky Lymphomas.

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