Usefulness of 18-F FDG PET/CT in the pre-treatment evaluation of thymic epithelial neoplasms-Reference-Cited by-同舟云学术

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Usefulness of 18-F FDG PET/CT in the pre-treatment evaluation of thymic epithelial neoplasms

Published:2011-11 Issue:2 Volume:74 Page:239-243
ISSN:0169-5002
Container-title:Lung Cancer
language:en
Short-container-title:Lung Cancer

Author:

Terzi Alberto,Bertolaccini Luca,Rizzardi Giovanna,Luzzi Luca,Bianchi Andrea,Campione Andrea,Comino Alberto,Biggi Alberto

Publisher

Elsevier BV

Subject

Cancer Research,Pulmonary and Respiratory Medicine,Oncology

Reference22 articles.

1. New WHO histologic classification predicts prognosis of thymic epithelial tumors: a clinicopathologic study of 200 thymoma cases from China;Chen;Cancer,2002

2. Histological typing of tumors of the thymus;Rosai,1999

3. The World Health Organization histologic classification system reflects the oncologic behavior of thymoma: a clinical study of 273 patients;Okumura;Cancer,2002

4. Thymoma: a clinicopathologic study based on the new World Health Organization classification;Nakagawa;J Thorac Cardiovasc Surg,2003

5. Using the World Health Organization Classification of thymic epithelial neoplasms to describe CT findings;Tomiyama;Am J Roentgenol,2002

Cited by 41 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Development and Validation of A Diagnostic Nomogram Based on PET/CT and Clinical Characteristics: Differentiating mediastinal lymphomas from aggressive thymic epithelial tumors;2024-01-03

2. The International Association for the Study of Lung Cancer Thymic Epithelial Tumor Staging Project: A Re-Assessment of the International Thymic Malignancy Interest Group/International Association for the Study of Lung Cancer Lymph Node Map for Thymic Epithelial Tumors for the Forthcoming Ninth Edition of the TNM Classification of Malignant Tumors;Journal of Thoracic Oncology;2023-12

3. Superiority of [68Ga]Ga-DOTA-FAPI-04 PET/CT to [18F]FDG PET/CT in the evaluation of thymic epithelial tumours;European Journal of Nuclear Medicine and Molecular Imaging;2023-06-15

4. The efficacy of ¹⁸F-FDG-PET-based radiomic and deep-learning features using a machine-learning approach to predict the pathological risk subtypes of thymic epithelial tumors;The British Journal of Radiology;2022-06-01

5. Multiparametric MRI radiomics nomogram for predicting lymph-vascular space invasion in early-stage cervical cancer;The British Journal of Radiology;2022-06-01

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