医学
腰椎间盘突出症
磁共振成像
放射科
诊断准确性
科克伦图书馆
荟萃分析
腰椎
医学物理学
病理
作者
Turki Khulaif Alanazi,Abdulaziz Turki Hamad Al-Anzi,Abdullah Naffaa Alsafari,Ahmed Maashi Al Enezi,Faisal Hussain Alanazi,Mohammed Maashi Q. Alanazi,Mohamed Hakem Almolhem,Abdullah Mohammed Alanazi,Abdulaziz Hassan Alanzi,Mohammad Khulaife Alabdali,Fhad Ahmad Alanazi,Miznah Mohammad Alenezi
出处
期刊:Journal of advances in medicine and medical research
[Sciencedomain International]
日期:2022-12-20
卷期号:: 22-30
被引量:1
标识
DOI:10.9734/jammr/2022/v34i244900
摘要
Background: Magnetic resonance imaging (MRI) is the technique of choice for diagnosing lumbar disc herniation (LDH). This systematic review aims to investigate the recently published literature regarding the updates of MRI for LDH diagnosis.
Methodology: PubMed, Web of Science, Science Direct, EBSCO, and Cochrane library were searched. Study articles were screened by title and abstract using Rayyan QCRI then a full-text assessment was implemented.
Results: Nine studies were included, with 1064 patients with LDH. All the included studies reported that MRI is valuable in diagnosing and detecting the acuity of LDH. Other diagnostic modalities were used along with MRI to increase the results' accuracy, including the clinical findings, MRM, and QST.
Conclusion: MRI is considered suitable for predicting symptom severity in patients with LDH and, when used in combination with clinical findings, improves diagnostic accuracy. This review showed that deep learning can be used on small data sets containing only a few medical images. Impressive results were obtained in terms of detection of findings and improved accuracy of LDH diagnosis. Electrophysiological studies, QST, weight bearing, and MRM have been used as diagnostic methods for his LDH along with MRI, with good and accurate results reported.
科研通智能强力驱动
Strongly Powered by AbleSci AI