Imaging of meningioma progression by matrix-assisted laser desorption ionization time-of-flight mass spectrometry.
Imaging of meningioma progression by matrix-assisted laser desorption ionization time-of-flight mass spectrometry.
复制标题
DOI：
10.1021/ac100113w
复制
发表时间：
2010-04-01
影响因子：
7.4
通讯作者：
Blacks, Peter M.
中科院分区：
文献类型：
--
作者：
Agar, Nathalie Y. R.;Malcolm, James G.;Mohan, Vandana;Yang, Hong W.;Johnson, Mark D.;Tannenbaum, Allen;Agar, Jeffrey N.;Blacks, Peter M.
脑膜瘤通常被认为是良性的，占颅内肿瘤的32%，根据WHO组织学分类定义为3级恶性。恶性脑膜瘤的中位生存期少于2年。无法预测脑膜瘤的复发和进展引起患者的显着焦虑，并限制了医生在实施预防性治疗方法。本报告提出了一种基于MALDI TOF质谱成像（MSI）的组织表征分析方法，该方法旨在建立一个用于脑肿瘤预测分类的参考数据库。这一试点研究旨在评价这种方法的潜力，并开始解决目前方法的局限性。选择5例复发性和进展性脑膜瘤，其手术标本可从原始和进展等级中获得，并与非进展性高级别脑膜瘤、高级别胶质瘤和非肿瘤脑标本进行对比。将数据采集的常见剖面法与成像法进行了比较，发现在空间分辨采集方面具有显著的优势，可提高光谱清晰度。基于支持向量机的初步分类器显示了区分脑膜瘤图像光谱与非肿瘤脑和胶质瘤（一种不同类型的脑肿瘤）的能力，并使手术组织的类成像成为可能。虽然分类器的发展被证明是敏感的数据准备参数，如重新校准和峰值拾取标准，它也表明了成熟的预测算法的潜力，如果提供了更大的一系列明确的情况下。
Often considered benign, meningiomas represent 32% of intracranial tumors with 3 grades of malignancy defined by the WHO histology based classification. Malignant meningiomas are associated with less than 2 years median survival. The inability to predict recurrence and progression of meningiomas induces significant anxiety for patients and limits physicians in implementing prophylactic treatment approaches. This report presents an analytical approach to tissue characterization based on MALDI TOF mass spectrometry imaging (MSI) which is introduced in an attempt to develop a reference database for predictive classification of brain tumors. This pilot study was designed to evaluate the potential of such approach and to begin to address limitations of the current methodology. Five recurrent and progressive meningiomas for which surgical specimens were available from the original and progressed grades were selected and tested against non-progressive high-grade meningiomas, high-grade gliomas, and non-tumor brain specimens. The common profiling approach of data acquisition was compared to imaging and revealed significant benefits in spatially resolved acquisition for improved spectral definition. A preliminary classifier based on support vector machine showed the ability to distinguish meningioma image spectra from non-tumor brain and from gliomas, a different type of brain tumors, and to enable class imaging of surgical tissue. Although the development of classifiers was shown to be sensitive to data preparation parameters such as recalibration and peak picking criteria, it also suggested the potential for maturing into a predictive algorithm if provided with larger series of well-defined cases.
登录
查看更多内容
DOI：
10.1073/pnas.0801374105
发表时间：
2008-11-25
影响因子：
11.1
作者：
Seeley, Erin H.;Caprioli, Richard M.
通讯作者：
Caprioli, Richard M.
影响因子：
7.4
作者：
GUSEV, AI;VASSEUR, OJ;HERCULES, DM
通讯作者：
HERCULES, DM
影响因子：
11.5
作者：
Roessler, M;Rollinger, W;Tacke, M
通讯作者：
Tacke, M
影响因子：
6.4
作者：
Korshunov, A;Shishkina, L;Golanov, A
通讯作者：
Golanov, A
影响因子：
7.4
作者：
Chaurand, P;Schwartz, SA;Caprioli, RM
通讯作者：
Caprioli, RM