基于mri的机器学习和放射组学方法评估轻度脊髓型颈椎病患者脊髓功能。

IF 3.8 3区医学 Q2 ENGINEERING, BIOMEDICAL

Bioengineering Pub Date : 2025-06-17 DOI:10.3390/bioengineering12060666

He Wang, Kai Wang, Yutian Wang, Zhenlei Liu, Lei Zhang, Shanhang Jia, Kun He, Xiangyu Zhang, Hao Wu

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引用次数: 0

摘要

(1)背景：轻度脊髓型颈椎病（CSM）患者延迟手术风险进展。虽然PET评估脊髓功能，但其成本和辐射限制了其使用。(2)方法：在本前瞻性研究中，对轻度颈椎病患者术前行18F-FDG PET-MRI检查。根据SUVmax是否降低对椎管水平变窄进行分类。进行了后续评估。开发了两种基于MRI t2放射组学的机器学习模型来识别狭窄水平和SUVmax降低。(3)结果：SUVmax正常的患者症状改善更大。放射组学模型表现良好，狭窄检测的auc为0.981/0.962（训练/测试），预测SUVmax下降的auc为0.830/0.812。该模型在预测SUVmax下降方面优于临床医生，AUC提高了10%。(4)结论：保留SUVmax患者预后较好。基于mri的放射组学显示出在术前评估中识别狭窄和预测脊髓功能变化的潜力，尽管需要更大规模的研究来验证其临床应用。

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MRI-Based Machine Learning and Radiomics Methods for Assessing Spinal Cord Function in Patients with Mild Cervical Spondylotic Myelopathy.

(1) Background: Patients with mild cervical spondylotic myelopathy (CSM) who delay surgery risk progression. While PET evaluates spinal cord function, its cost and radiation limit its use. (2) Methods: In this prospective study, patients with mild cervical spondylosis underwent preoperative 18F-FDG PET-MRI. Narrowed spinal levels were classified based on whether SUV_max was decreased. Follow-up assessments were conducted. Two machine learning models using MRI T2-based radiomics were developed to identify stenotic levels and decreased SUV_max. (3) Results: Patients with normal SUV_max showed greater symptom improvement. The radiomics models performed well, with AUCs of 0.981/0.962 (training/testing) for stenosis detection and 0.830/0.812 for predicting SUV_max decline. The model outperformed clinicians in predicting SUV_max decline, improving the AUC by 10%. (4) Conclusion: Patients with preserved SUV_max have better outcomes. MRI-based radiomics shows potential for identifying stenosis and predicting spinal cord function changes for preoperative assessment, though larger studies are needed to validate its clinical utility.

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来源期刊

Bioengineering Chemical Engineering-Bioengineering

CiteScore

4.00

自引率

8.70%

发文量

661

期刊介绍： Aims Bioengineering (ISSN 2306-5354) provides an advanced forum for the science and technology of bioengineering. It publishes original research papers, comprehensive reviews, communications and case reports. Our aim is to encourage scientists to publish their experimental and theoretical results in as much detail as possible. All aspects of bioengineering are welcomed from theoretical concepts to education and applications. There is no restriction on the length of the papers. The full experimental details must be provided so that the results can be reproduced. There are, in addition, four key features of this Journal: ● We are introducing a new concept in scientific and technical publications “The Translational Case Report in Bioengineering”. It is a descriptive explanatory analysis of a transformative or translational event. Understanding that the goal of bioengineering scholarship is to advance towards a transformative or clinical solution to an identified transformative/clinical need, the translational case report is used to explore causation in order to find underlying principles that may guide other similar transformative/translational undertakings. ● Manuscripts regarding research proposals and research ideas will be particularly welcomed. ● Electronic files and software regarding the full details of the calculation and experimental procedure, if unable to be published in a normal way, can be deposited as supplementary material. ● We also accept manuscripts communicating to a broader audience with regard to research projects financed with public funds. Scope ● Bionics and biological cybernetics: implantology; bio–abio interfaces ● Bioelectronics: wearable electronics; implantable electronics; “more than Moore” electronics; bioelectronics devices ● Bioprocess and biosystems engineering and applications: bioprocess design; biocatalysis; bioseparation and bioreactors; bioinformatics; bioenergy; etc. ● Biomolecular, cellular and tissue engineering and applications: tissue engineering; chromosome engineering; embryo engineering; cellular, molecular and synthetic biology; metabolic engineering; bio-nanotechnology; micro/nano technologies; genetic engineering; transgenic technology ● Biomedical engineering and applications: biomechatronics; biomedical electronics; biomechanics; biomaterials; biomimetics; biomedical diagnostics; biomedical therapy; biomedical devices; sensors and circuits; biomedical imaging and medical information systems; implants and regenerative medicine; neurotechnology; clinical engineering; rehabilitation engineering ● Biochemical engineering and applications: metabolic pathway engineering; modeling and simulation ● Translational bioengineering