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Updated: Apr 16, 2026

Minimal Invasive Resection of Large Retrosternal Thyroid Goiter
Published on: September 20, 2024
Imaging-based criteria for minimally invasive versus open surgery in thymic tumors: a narrative review
Takashi Kanou1, Yasushi Shintani1
1Department of General Thoracic Surgery, The University of Osaka, Osaka, Japan.
Background And Objective:
Thymic epithelial tumors (TETs) require precise preoperative assessment to achieve complete resection and optimal long-term outcomes. With the expanding use of minimally invasive surgery, imaging has become central not only for diagnosis but also for surgical decision-making. This narrative review aims to summarize current evidence on how metabolic, morphologic, and computed tomography (CT)-based imaging parameters can be integrated to guide surgical strategies for TETs.
Methods:
A comprehensive literature search was conducted using PubMed and Web of Science for studies published between January 2001 and August 2025. Original clinical studies, multicenter analyses, systematic reviews, and major guidelines published in English were reviewed, with an emphasis on imaging-based surgical decision-making.
Key Content And Findings:
Tumor size (TS) consistently predicts invasiveness and surgical complexity, with thresholds of approximately 5-6 cm influencing the choice between minimally invasive and open approaches. Positron emission tomography-derived parameters, particularly maximum standardized uptake value (SUVmax) and the SUVmax-to-TS ratio, correlate with histological aggressiveness and prognosis. CT features, including capsular disruption, calcification, and vascular abutment, further refine risk stratification. Emerging modalities such as volumetry, novel positron-emission tomography (PET) tracers, and artificial intelligence (AI)-based radiomics show promise in enhancing individualized surgical planning.
Conclusions:
Integrating PET metrics, TS, and CT features provides a comprehensive framework for tailoring surgical strategies in TETs. Future incorporation of volumetric and AI-driven imaging analyses into clinical guidelines may further optimize surgical outcomes and personalized care.

