Using Infrared Spectroscopy for Real-Time Diagnostics During Brain Surgery - - Spectroscopy
 Home   Mass Spectrometry   ICP-MS   Infrared   FT-IR   UV-Vis   Raman   NMR   X-Ray   Fluorescence  
Home
Magazine
Issue Archive
Subscribe/Renew
Special Issues
Reprints
The Application Notebook
Current Issue
Archive
Submission Guidelines
Training
SpecAcademy
E-solutions
Digital Edition
Subscribe to the Digital Edition
The Wavelength
Subcribe to The Wavelength
Subscribe to the MS E-news
Resources
Market Profiles
Information for Authors
SpecTube
Webcasts
Advertiser services
Contact Us
Columns
Atomic Perspectives
Chemometrics in Spectroscopy
Focus on Quality
Laser and Optics Interface
Mass Spectrometry Forum
The Baseline
Molecular Spectroscopy Workbench

Using Infrared Spectroscopy for Real-Time Diagnostics During Brain Surgery

Spectroscopy
Volume 29, Issue 6, pp. 28,29,56

What if the decisions neurosurgeons make during surgery — such as about how much tissue to remove — could be guided by immediate results from spectroscopic methods? A number of spectroscopy researchers are seeking to advance methods to make that both possible and practical. One such researcher is Allison Stelling, who recently completed her PhD under Professor Peter Tonge at Stony Brook University in New York. Stelling is currently at the Center for Materials Genomics at Duke University, in Durham, North Carolina, working under Professor Stefano Curtarolo. Previously, during a post as a scientific research associate in the Clinical Sensing and Monitoring department in the Faculty of Medicine at Dresden University of Technology, in Dresden, Germany, Stelling and colleagues studied the use of infrared (IR) spectroscopy for use in intraoperative diagnostics during brain surgery. Spectroscopy recently spoke to Stelling about that work, which was published in the journal PLoS ONE (1).

When using IR spectroscopy to examine freshly resected brain tissue in an operating room, what are you trying to achieve?


TOM FULLUM/GETTY IMAGES
The end goal is to be able to detect the hard-to-see tumor borders during operations, because incomplete removal is linked to recurrence in many brain tumors. In soft tissues like the brain, these borders shift during the operation from preoperative magnetic resonance imaging (MRI) images. IR can give contrast in these low-contrast situations, and thus aid in reducing the number of surgeries a patient must endure. This initial study was focused more on determining where reliable spectral differences are between normal and tumor in fully hydrated tissue. Further studies will be needed to see how the identified signals "titrate" between normal and tumor tissue.

When analyzing brain tumors with IR spectroscopy, what biomarkers are you measuring? How precisely can these markers be differentiated in healthy and cancerous tissue, and to what extent do individual variances occur? Have the biomarkers been validated?

Chemicals produced by the tumor itself and then sensed by IR serve as the biomarkers. In the attenuated total reflectance Fourier transform infrared (ATR-FTIR) spectra from tumor tissues, this results in fairly dramatic shifts in frequency and changes in absorbance. While full interpretation on a chemical level must await purification and structural characterization studies, it is apparent that there do seem to be reasonably large changes in the ATR-FTIR between the control brain tissues and the tumor ones.

In our recent study, we found a particular region that contains signals from extracellular molecules like collagen, whose triple helix structures give it a very distinctive IR signal. Collagens are overexpressed in many tumors, resulting in large changes in the IR. These changes were plotted in the recent paper we published in PLoS ONE (1). Dr. Deirdre Toher, a statistician at the University of the West of England in Bristol, helped me with some of the basic spectral preprocessing in large batches for the study.

A major lesson I gained from this trial — and when doing my literature survey for the recent publication — addresses your question about how to identify so-called "spectral biomarkers" or "fingerprints" for disease. Doing controls with healthy tissues and comparing and contrasting them with diseases can allow us to first determine where reliable differences occur. Comparison with tissues known to overexpress certain chemicals can help assign bands and determine roughly their percent contribution to the overall tissue spectrum.

Inter-individual variance for this measurement was something I was quite concerned about, which is why Dr. Ordtrud Uckermann, a neuroscientist at the Department of Neurosurgery in the Dresden University Hospital, and I designed a small control study to obtain the IR signals from normal, healthy mouse brains. The variation among the five individual animals was much lower than I expected it to be (particularly for waterlogged materials), and forthcoming manuscripts on this trial will illuminate this point.

What will be most interesting to see is how the IR spectra change between patients with the same diagnosis using traditional histochemistry. IR shall likely be much more sensitive to intrinsic, biochemical-level inter-individual differences in the phenotype of the tumor than any morphology-based method. This information will help biomedical scientists in the future design personalized treatments with physicians based on a patient's unique biochemistry.

This is the preclinical trial, so validation is the next step. These initial results are reasonably promising, however, and illustrate that the core idea is sound.


Rate This Article
Your original vote has been tallied and is included in the ratings results.
View our top pages
Average rating for this page is: 0
Headlines from LCGC North America and Chromatography Online
Emerging Trends in Pharmaceutical Analysis
Detection of Low-Level Sulfur Compounds in Spearmint Oil
Pittcon 2015 Announces Award Recipients for Outstanding Achievements in Analytical Chemistry and Applied Spectroscopy
Differential Analysis of Olive Oils with Pegasus® GC-HRT and ChromaTOF-HRT® Reference Feature
Water for GC-MS Analysis of VOCs
Source: Spectroscopy,
Click here