Analysis in Real Time Helps Brain Surgeons Remove More Cancerous Tissue

A combination of surgical aspiration and mass spectrometry can determine whether brain tissue is normal or cancerous while surgery is underway, according to a new study.

Researchers at Justus Liebig University (JLU; Giessen, Germany), the University of Debrecen (Hungary), and other institutions used a direct combination of a cavitron ultrasonic surgical aspirator (CUSA) and a venturi easy ambient sonic-spray ionization (V-EASI) source to nebulize efficiently suspended tissue material for gas phase ion production. Positive and negative ionization spectra were identified using mass spectrometry, which featured predominantly complex lipid-type constituents in both ion polarity modes. Multiply charged peptide anions were also detected. The spectra of the intact tissue specimens were found to be highly specific to the histological tissue type.


The researchers then examined the influence of instrumental settings, using standard solutions of phospholipids and peptides to test the dynamic range, sensitivity, and suppression effects in detail. Venturi pump geometry and flow parameters were found to be critically important in ionization efficiency. The researchers subsequently developed a real-time tissue identification method for the surgical environment, using principal component analysis (PCA) and linear-discriminant analysis (LDA) based data to identify the margin between cancerous and healthy tissue in half the time previously needed. The study was published in the October 15, 2011, issue of Analytical Chemistry.

“The method has been successfully tested on postmortem and ex vivo human samples including astrocytomas, meningeomas, metastatic brain tumors, and healthy brain tissue,” wrote corresponding author Zoltan Takats, PhD, of the JLU Institute for Inorganic und Analytical Chemistry, and colleagues. “Besides brain surgery, the method has application potential in the field of the surgery of organs including liver, pancreas, or kidney.”

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Justus Liebig University
University of Debrecen