Computed tomography/magnetic resonance imaging for mandibular boundary invasion of oral squamous cell carcinoma assessment

BMC Oral Health(2024)

引用 0|浏览2
暂无评分
摘要
Background The range of mandibular invasion by a tumour needs to be determined accurately to minimize unnecessary damage to the mandible. This study aimed to compare tumour boundary lines on computed tomography/magnetic resonance (CT/MR) images with those from pathological findings during the preoperative assessment of mandibular invasion by oral squamous cell carcinoma (OSCC). By comparing the methods, the potential of CT/MR for this application could be further elucidated. Methods Eight patients with OSCC were imaged with CT/MR, mandibular specimens were collected, and the material site was measured. Haematoxylin–eosin staining was used for histopathological assessment. The presence and boundaries of bone invasion were evaluated. The CT/MR and histopathological boundaries of bone invasion were delineated and merged to compare and calculate the deviation of CT/MR and histopathological boundaries using the Fréchet distance. Results The mean Fréchet distance between the CT and pathological tumour boundaries was 2.69 mm (standard error 0.46 mm), with a minimum of 1.18 mm, maximum of 3.64 mm, median of 3.10 mm, and 95% confidence interval of 1.40–3.97 mm. The mean Fréchet distance between the tumour boundaries on the MR and pathological images was 3.07 mm (standard error 0.56 mm), with a minimum of 1.53 mm, maximum of 4.74 mm, median of 2.90 mm, and 95% confidence interval of 1.53–4.61 mm. Conclusions CT/MR imaging can provide an effective preoperative assessment of mandibular invasion of OSCC. Pathology images can be positioned on CT/MR scans with the help of computer software to improve the accuracy of the findings. The introduction of the Fréchet distance to compare tumour boundary lines is conducive to computer image diagnosis of tumour invasion of jaw boundaries.
更多
查看译文
关键词
Diagnostic imaging,Epithelial neoplasm,Fréchet distance,Mandible,Mouth cancer,Tumour boundary
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要