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Ambient Mass Spectrometry for the Intraoperative Molecular Diagnosis of Human Brain Tumors

Institution:
1Department of Chemistry and Center for Analytical Instrumentation Development, Purdue University, West Lafayette, IN, USA.
2Department of Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
3Department of Pathology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
4Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
Publication Date:
Jan-2013
Journal:
Proc Natl Acad Sci U S A
Volume Number:
110
Issue Number:
5
Pages:
1611-6
Citation:
Proc Natl Acad Sci U S A. 2013 Jan 29;110(5):1611-6.
Links:
http://dx.doi.org/10.1073/pnas.1215687110
PubMed ID:
23300285
PMCID:
PMC3562800
Appears in Collections:
NCIGT, SLICER, SMIL
Sponsors:
R25 CA089017/CA/NCI NIH HHS/United States
DP2 OD007383/OD/NIH HHS/United States
R21 EB009459/EB/NIBIB NIH HHS/United States
K08 NS064168/NS/NINDS NIH HHS/United States
P41 EB015898/EB/NIBIB NIH HHS/United States
P41 RR019703/RR/NCRR NIH HHS/United States
Generated Citation:
Eberlin L.S., Norton I., Orringer D., Dunn I.F., Liu X., Ide J.L., Jarmusch A.K., Ligon K.L., Jolesz F.A., Golby A.J., Santagata S., Agar N.Y.R., Cooks R.G. Ambient Mass Spectrometry for the Intraoperative Molecular Diagnosis of Human Brain Tumors. Proc Natl Acad Sci U S A. 2013 Jan 29;110(5):1611-6. PMID: 23300285. PMCID: PMC3562800.
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The main goal of brain tumor surgery is to maximize tumor resection while preserving brain function. However, existing imaging and surgical techniques do not offer the molecular information needed to delineate tumor boundaries. We have developed a system to rapidly analyze and classify brain tumors based on lipid information acquired by desorption electrospray ionization mass spectrometry (DESI-MS). In this study, a classifier was built to discriminate gliomas and meningiomas based on 36 glioma and 19 meningioma samples. The classifier was tested and results were validated for intraoperative use by analyzing and diagnosing tissue sections from 32 surgical specimens obtained from five research subjects who underwent brain tumor resection. The samples analyzed included oligodendroglioma, astrocytoma, and meningioma tumors of different histological grades and tumor cell concentrations. The molecular diagnosis derived from mass-spectrometry imaging corresponded to histopathology diagnosis with very few exceptions. Our work demonstrates that DESI-MS technology has the potential to identify the histology type of brain tumors. It provides information on glioma grade and, most importantly, may help define tumor margins by measuring the tumor cell concentration in a specimen. Results for stereotactically registered samples were correlated to preoperative MRI through neuronavigation, and visualized over segmented 3D MRI tumor volume reconstruction. Our findings demonstrate the potential of ambient mass spectrometry to guide brain tumor surgery by providing rapid diagnosis, and tumor margin assessment in near-real time.

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