MRI evaluation of hyperostosis frontalis interna: differentiation and diagnostic insights.

IF 2.6 3区 医学 Q2 CLINICAL NEUROLOGY
Anish Bhandari, Samuel N Rogers, Srinivasan Vedantham, Richard Joseph Wruble, Unni Udayasankar, Hasan Ozgur, Raza Mushtaq
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引用次数: 0

Abstract

Introduction: To delineate the MRI characteristics of Hyperostosis Frontalis Interna (HFI) and evaluate its imaging features to aid in accurate diagnosis and differentiation from other pathologies, particularly metastatic disease.

Methods: A retrospective analysis of 74 patients with HFI was conducted. MRI sequences, including pre-contrast T1-weighted, post-contrast T1-weighted, and T2-weighted fat-saturation imaging, were evaluated. Quantitative and qualitative assessments of HFI signal intensity and enhancement patterns were performed. The Hershkovitz classification categorized the extent of HFI.

Results: Pre-contrast T1-weighted imaging showed varied signal intensities, with hypointense regions more common in advanced HFI stages. Hypointense HFI was associated with a lower likelihood (OR: 0.303, CI: 0.113-0.808) and heterogeneous distribution was associated with a higher likelihood (OR: 5.128, CI: 1.982-13.265) of higher Hershkovitz classification (P = 0.0008). Post-contrast T1-weighted imaging revealed that 31% of subjects demonstrated enhancement, with focal geographic enhancement associated with lower CT attenuation values (P = 0.0138), indicating higher fat content. T2-weighted fat-saturation imaging supported the correlation between hypointense signals on pre-contrast T1 imaging and lower T2 signal intensities (P = 0.0022). No significant differences were found in enhancement patterns between different MRI sequences (P > 0.1326).

Conclusions: HFI demonstrates varying appearances on pre- and post-contrast MRI sequences, crucial for differentiating benign HFI from metastatic lesions. Understanding these imaging characteristics can enhance diagnostic accuracy, reduce the risk of misdiagnosis, and improve patient management. Future studies should focus on larger, more diverse populations and explore advanced MRI techniques to further understand HFI.

额内肥大症的MRI评价:鉴别和诊断见解。
前言:描述额内肥厚症(Hyperostosis Frontalis Interna, HFI)的MRI特征,并评估其影像学特征,以帮助准确诊断和鉴别其他病理,特别是转移性疾病。方法:对74例HFI患者进行回顾性分析。评估MRI序列,包括对比前t1加权、对比后t1加权和t2加权脂肪饱和度成像。对HFI信号强度和增强模式进行定量和定性评估。赫什科维茨分类法对HFI的程度进行了分类。结果:对比前t1加权成像显示不同的信号强度,低信号区在HFI晚期更为常见。低强度HFI与较低的可能性相关(OR: 0.303, CI: 0.113-0.808),而异质性分布与较高的可能性相关(OR: 5.128, CI: 1.982-13.265) (P = 0.0008)。对比后t1加权成像显示31%的受试者表现为增强,病灶地理增强与较低的CT衰减值相关(P = 0.0138),表明脂肪含量较高。T2加权脂肪饱和度成像支持对比前T1低信号与T2低信号强度的相关性(P = 0.0022)。不同MRI序列间增强模式差异无统计学意义(P < 0.1326)。结论:HFI在造影前和造影后的MRI序列上表现出不同的外观,这对于区分良性HFI和转移性病变至关重要。了解这些影像学特征可以提高诊断准确性,降低误诊风险,改善患者管理。未来的研究应关注更大、更多样化的人群,并探索先进的MRI技术,以进一步了解HFI。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Neuroradiology
Neuroradiology 医学-核医学
CiteScore
5.30
自引率
3.60%
发文量
214
审稿时长
4-8 weeks
期刊介绍: Neuroradiology aims to provide state-of-the-art medical and scientific information in the fields of Neuroradiology, Neurosciences, Neurology, Psychiatry, Neurosurgery, and related medical specialities. Neuroradiology as the official Journal of the European Society of Neuroradiology receives submissions from all parts of the world and publishes peer-reviewed original research, comprehensive reviews, educational papers, opinion papers, and short reports on exceptional clinical observations and new technical developments in the field of Neuroimaging and Neurointervention. The journal has subsections for Diagnostic and Interventional Neuroradiology, Advanced Neuroimaging, Paediatric Neuroradiology, Head-Neck-ENT Radiology, Spine Neuroradiology, and for submissions from Japan. Neuroradiology aims to provide new knowledge about and insights into the function and pathology of the human nervous system that may help to better diagnose and treat nervous system diseases. Neuroradiology is a member of the Committee on Publication Ethics (COPE) and follows the COPE core practices. Neuroradiology prefers articles that are free of bias, self-critical regarding limitations, transparent and clear in describing study participants, methods, and statistics, and short in presenting results. Before peer-review all submissions are automatically checked by iThenticate to assess for potential overlap in prior publication.
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