Korean Journal of Radiology

The Korean Society of Radiology (대한영상의학회)
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MRI-Based Stepwise Approach to Anterior Mediastinal Cystic Lesions for Diagnosis and Further Management

  • Jong Hee Kim (Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine) ;
  • Jooae Choe (Department of Thoracic and Cardiovascular Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine) ;
  • Hong Kwan Kim (Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center) ;
  • Ho Yun Lee (Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine)
  • Received : 2022.08.19
  • Accepted : 2022.10.22
  • Published : 2023.01.01
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Abstract

As the majority of incidentally detected lesions in the anterior mediastinum is small nodules with soft tissue appearance, the differential diagnosis has typically included thymic neoplasm and prevascular lymph node, with benign cyst. Overestimation or misinterpretation of these lesions can lead to unnecessary surgery for ultimately benign conditions. Diagnosing mediastinal cysts using MRI serves as a problem-solving modality in distinguishing between surgical and nonsurgical anterior mediastinal lesions. The pitfalls of MRI evaluation for anterior mediastinal cystic lesions are as follows: first, we acknowledge the limitation of T2-weighted images for evaluating benign cystic lesions. Due to variable contents within benign cystic lesions, such as hemorrhage, T2 signal intensity may be variable. Second, owing to extensive necrosis and cystic changes, the T2 shine-through effect may be seen on diffusion-weighted images (DWI), and small solid portions might be missed on enhanced images. Therefore, both enhancement and DWI with apparent diffusion coefficient values should be considered. An algorithm will be suggested for the diagnostic evaluation of anterior mediastinal cystic lesions, and finally, a management strategy based on MRI features will be suggested.

Keywords

Acknowledgement

This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No. NRF-2022R1A2C1003999, No. NRF-2021R1A4A5032806).

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