Tate Anne R, Underwood Joshua, Acosta Dionisio M, Julià-Sapé Margarida, Majós Carles, Moreno-Torres Angel, Howe Franklyn A, van der Graaf Marinette, Lefournier Virginie, Murphy Mary M, Loosemore Alison, Ladroue Christophe, Wesseling Pieter, Luc Bosson Jean, Cabañas Miquel E, Simonetti Arjan W, Gajewicz Witold, Calvar Jorge, Capdevila Antoni, Wilkins Peter R, Bell B Anthony, Rémy Chantal, Heerschap Arend, Watson Des, Griffiths John R, Arús Carles
St George's, University of London, Cranmer Terrace, London SW17 0RE, UK.
NMR Biomed. 2006 Jun;19(4):411-34. doi: 10.1002/nbm.1016.
A computer-based decision support system to assist radiologists in diagnosing and grading brain tumours has been developed by the multi-centre INTERPRET project. Spectra from a database of 1H single-voxel spectra of different types of brain tumours, acquired in vivo from 334 patients at four different centres, are clustered according to their pathology, using automated pattern recognition techniques and the results are presented as a two-dimensional scatterplot using an intuitive graphical user interface (GUI). Formal quality control procedures were performed to standardize the performance of the instruments and check each spectrum, and teams of expert neuroradiologists, neurosurgeons, neurologists and neuropathologists clinically validated each case. The prototype decision support system (DSS) successfully classified 89% of the cases in an independent test set of 91 cases of the most frequent tumour types (meningiomas, low-grade gliomas and high-grade malignant tumours--glioblastomas and metastases). It also helps to resolve diagnostic difficulty in borderline cases. When the prototype was tested by radiologists and other clinicians it was favourably received. Results of the preliminary clinical analysis of the added value of using the DSS for brain tumour diagnosis with MRS showed a small but significant improvement over MRI used alone. In the comparison of individual pathologies, PNETs were significantly better diagnosed with the DSS than with MRI alone.
多中心INTERPRET项目开发了一种基于计算机的决策支持系统,以协助放射科医生诊断和分级脑肿瘤。利用自动模式识别技术,对来自四个不同中心的334例患者体内获取的不同类型脑肿瘤的1H单体素光谱数据库中的光谱,根据其病理进行聚类,并使用直观的图形用户界面(GUI)将结果呈现为二维散点图。执行了正式的质量控制程序,以规范仪器性能并检查每个光谱,专家神经放射学家、神经外科医生、神经科医生和神经病理学家团队对每个病例进行了临床验证。在一个由91例最常见肿瘤类型(脑膜瘤、低级别胶质瘤和高级别恶性肿瘤——胶质母细胞瘤和转移瘤)组成的独立测试集中,原型决策支持系统(DSS)成功分类了89%的病例。它还有助于解决临界病例的诊断困难。当放射科医生和其他临床医生对该原型进行测试时,得到了好评。使用DSS结合磁共振波谱(MRS)进行脑肿瘤诊断的附加值的初步临床分析结果显示,与单独使用磁共振成像(MRI)相比有小幅但显著的改善。在对个体病理的比较中,DSS对原始神经外胚层肿瘤(PNETs)的诊断明显优于单独使用MRI。