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使用体内磁共振成像和光谱学联合技术对脑肿瘤进行无创诊断评估。

Noninvasive diagnostic assessment of brain tumors using combined in vivo MR imaging and spectroscopy.

作者信息

Galanaud Damien, Nicoli François, Chinot Olivier, Confort-Gouny Sylviane, Figarella-Branger Dominique, Roche Pierre, Fuentès Stéphane, Le Fur Yann, Ranjeva Jean-Philippe, Cozzone Patrick J

机构信息

Centre de Résonance Magnétique Biologique et Médicale, UMR CNRS 6612, Faculté de Médecine, Université de la Méditerranée and Hôpital de La Timone, Marseille, France.

出版信息

Magn Reson Med. 2006 Jun;55(6):1236-45. doi: 10.1002/mrm.20886.

Abstract

To determine the potential value of multimodal MRI for the presurgical management of patients with brain tumors, we performed combined magnetic resonance imaging (MRI) and proton MR spectroscopy (MRS) in 164 patients who presented with tumors of various histological subtypes confirmed by surgical biopsy. Univariate statistical analysis of metabolic ratios carried out on the first 121 patients demonstrated significant differences in between-group comparisons, but failed to provide sufficiently robust classification of individual cases. However, a multivariate statistical approach correctly classified the tumors using linear discriminant analysis (LDA) of combined MRI and MRS data. After initial separation of contrast-enhancing and non-contrast-enhancing lesions, 91% of the former and 87% of the latter were correctly classified. The results were stable when this diagnostic strategy was tested on the additional 43 patients included for validation after the initial statistical analysis, with over 90% of correct classification. Combined MRI and MRS had superior diagnostic value compared to MRS alone, especially in the contrast-enhancing group. This study shows the clinical value of a multivariate statistical analysis based on multimodal MRI and MRS for the noninvasive evaluation of intracranial tumors.

摘要

为了确定多模态磁共振成像(MRI)在脑肿瘤患者术前管理中的潜在价值,我们对164例经手术活检证实患有各种组织学亚型肿瘤的患者进行了联合磁共振成像(MRI)和质子磁共振波谱(MRS)检查。对前121例患者进行的代谢率单变量统计分析显示,组间比较存在显著差异,但未能对个体病例进行足够可靠的分类。然而,一种多变量统计方法使用联合MRI和MRS数据的线性判别分析(LDA)对肿瘤进行了正确分类。在初步区分强化和非强化病变后,前者的91%和后者的87%被正确分类。当在初步统计分析后纳入用于验证的另外43例患者中测试这种诊断策略时,结果是稳定的,正确分类率超过90%。联合MRI和MRS相比单独的MRS具有更高的诊断价值,尤其是在强化组。这项研究表明了基于多模态MRI和MRS的多变量统计分析对颅内肿瘤进行无创评估的临床价值。

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