Combination of ultrasonography and MRI for preoperative prediction of lymph node metastasis in tongue squamous cell carcinoma: An exploratory study
Hiroshi Hijioka, Hiroaki Tabata

TL;DR
This study explores combining ultrasound and MRI to better predict lymph node metastasis in tongue cancer before surgery.
Contribution
The novel contribution is proposing a conditional imaging strategy that uses ultrasound for shallow tumors and MRI for deeper ones to improve metastasis prediction.
Findings
US-derived DOI showed smaller measurement bias compared to MRI-derived DOI.
A combined strategy using US for DOI ≤7 mm and MRI for DOI >7 mm improved CLNM prediction accuracy.
The combined approach achieved a higher AUC (0.694) than either modality alone.
Abstract
Preoperative depth of invasion (DOI) is a critical predictor of cervical lymph node metastasis (CLNM) in tongue squamous cell carcinoma (TSCC). Ultrasonography (US) offers high accuracy for shallow tumors, whereas magnetic resonance imaging (MRI) provides superior visualization of deeper structures. However, each modality has limitations. This retrospective, exploratory study aimed to investigate a combined strategy leveraging the complementary strengths of both modalities to improve preoperative CLNM prediction. The study included 46 patients with TSCC who underwent radical surgery between September 2014 and August 2019. Correlations between US-derived DOI (usDOI), MRI-derived DOI (mrDOI), and pathological DOI (pDOI) were assessed using Pearson’s product-moment correlation. Agreement was evaluated by Bland–Altman analysis. A grid search approach identified the optimal usDOI threshold…
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Taxonomy
TopicsHead and Neck Cancer Studies · Esophageal Cancer Research and Treatment · Radiomics and Machine Learning in Medical Imaging
