Neuroimaging diagnosis for cerebral infarction: An 8-year bibliometric analysis

脑梗死的神经影像学诊断:一项为期8年的文献计量分析

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Abstract

OBJECTIVE: To identify global research trends in neuroimaging diagnosis for cerebral infarction using a bibliometric analysis of the Web of Science. DATA RETRIEVAL: We performed a bibliometric analysis of data retrieval for neuroimaging diagnosis for cerebral infarction containing the key words "CT, magnetic resonance imaging, MRI, transcranial Doppler, transvaginal color Doppler, digital subtraction angiography, and cerebral infarction" using the Web of Science. SELECTION CRITERIA: Inclusion criteria were: (a) peer-reviewed articles on neuroimaging diagnosis for cerebral infarction which were published and indexed in the Web of Science; (b) original research articles and reviews; and (c) publication between 2004-2011. Exclusion criteria were: (a) articles that required manual searching or telephone access; and (b) corrected papers or book chapters. MAIN OUTCOME MEASURES: (1) Annual publication output; (2) distribution according to country; (3) distribution according to institution; (4) top cited publications; (5) distribution according to journals; and (6) comparison of study results on neuroimaging diagnosis for cerebral infarction. RESULTS: Imaging has become the predominant method used in diagnosing cerebral infarction. The most frequently used clinical imaging methods were digital subtraction angiography, CT, MRI, and transcranial color Doppler examination. Digital subtraction angiography is used as the gold standard. However, it is a costly and time-consuming invasive diagnosis that requires some radiation exposure, and is poorly accepted by patients. As such, it is mostly adopted in interventional therapy in the clinic. CT is now accepted as a rapid, simple, and reliable non-invasive method for use in diagnosis of cerebrovascular disease and preoperative appraisal. Ultrasonic Doppler can be used to reflect the hardness of the vascular wall and the nature of the plaque more clearly than CT and MRI. CONCLUSION: At present, there is no unified standard of classification of cerebral infarction imaging. Detection of clinical super-acute cerebral infarction remains controversial due to its changes on imaging, lack of specificity, and its similarity to a space-occupying lesion. Neuroimaging diagnosis for cerebral infarction remains a highly active area of research and development.

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