New tool to help brain surgeons one step closer to operating room

January 09, 2013 − by wpengine − in Archived − Comments Off on New tool to help brain surgeons one step closer to operating room

January 9, 2013

Livia Eberlin DESI technology

graduate student Livia Eberlin uses DESI technology to analyze a sample. A team
led by R. Graham Cooks, Purdue’s Henry Bohn Hass Distinguished Professor of
Chemistry, used DESI to create a tool that could allow for faster, more
comprehensive testing of brain tissue during cancer surgery. (Purdue University
photo/Steve Scherer)

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WEST LAFAYETTE, Ind. – A new tool that could allow for
faster, more comprehensive testing of brain tissue during surgery successfully
identified the cancer type, grade and tumor margins in five brain surgery
patients, according to a Purdue University and Brigham and Women’s Hospital

The tool sprays a microscopic stream of charged solvent
onto the tissue surface to gather information about its molecular makeup and
produces a color-coded image that reveals the nature and concentration of tumor

Researchers analyzed specimens removed from the patients,
but the goal is to one day be able to perform the analysis on intact brain
tissue during surgery, said R. Graham Cooks, the Purdue professor who co-led
the research team.

“We hope to eventually be able to perform this
analysis during surgery to help guide brain surgeons so that the borders of
tumors can be identified and the cancer status of a site can be established
before any tissue is removed,” said Cooks, who is the Henry Bohn Hass
Distinguished Professor of Chemistry. “We aren’t there yet, but this was a
critical step in the process. It shows we’ve found easily identifiable
molecular patterns that can be used to diagnose the type and concentration of
cancer cells.”

Purdue researchers designed the tool and collaborated with
researchers and physicians at Brigham and Women’s Hospital at Harvard Medical
School to perform the study. The brain surgery was performed in the Advanced
Multi-Modality Image Guided Operating suite, or AMIGO, and in standard
operating rooms at Brigham and Women’s Hospital. A paper detailing the results
will be published in an upcoming issue of the Proceedings of the National Academy of Sciences and is published

Dr. Nathalie Agar, director of the Surgical Molecular
Imaging Laboratory within the neurosurgery department at Brigham and Women’s
Hospital, said the findings showed the analysis method’s potential and achieved
an important step in the path to assessing its value in improving patient care.

“This approach could lead to real-time, image-guided
surgery without interference with surgical care and without the administration
of labeling agents,” said Agar, who co-led the study. “Such extensive
and detailed information about the tissue was previously unavailable to
surgeons and could lead to more precise tumor removal. In addition, having
access to a detailed diagnosis on the day of surgery could help the oncologist
more efficiently design the course of adjuvant therapy.”

DESI mass spectrometry

A shows DESI mass spectrometry imaging from a surgical sample of a meningioma
tumor and an optical image of a stained serial section. The distribution of
meningioma cells observed by microscopy correlates with that identified through
the DESI analysis. Image B shows the mass spectrum of meningioma region of the
tissue section and illustrates the characteristic meningioma lipid profile.
(PNAS image, pnas.1215687110, Jan. 8 early edition/courtesy of Cooks’

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Dr. Alexandra Golby, director of Image-Guided Neurosurgery
in Brigham and Women’s Hospital’s neurosurgery department and paper co-author,
said brain tumors are particularly challenging to remove.

“Tumor tissue within the brain often closely
resembles normal brain tissue and may have indistinct boundaries, so it is
difficult to determine where the tumor ends and the normal brain tissue
begins,” said Golby, who also is the clinical co-director of AMIGO. “We
want to preserve as much functional brain tissue as possible, especially when a
tumor is in a critical area of the brain, like that which supports movement,
speaking or vision.”

Current surgical methods rely on the surgeon’s trained eye
with the help of an operating microscope and imaging from scans performed
before surgery. 

Pathological examination of specimens taken from the brain
during surgery provides the most specific information about the tissue and
diagnosis of the cancer. However, this examination of frozen sections takes
about half an hour, which is too long for it to be useful in examining multiple
samples and guiding surgery, said Dr. Sandro Santagata, a pathologist at
Brigham and Women’s Hospital who participated in the research.

“The new tool is able – in a matter of seconds – to
identify and classify glioma and meningioma tumors and recognize the tumor
grade,” Santagata said. “It is able to establish the same type of
assessment the pathology offers, but at a pace that is compatible with surgery.”

Surgeons removed 32 specimens from the patients during
surgery, which were later analyzed by both the new tool and standard pathology
methods to test its accuracy. The results for the patient samples were in very
good agreement with standard pathology, Cooks said.

The tool relies on an ambient mass spectrometry analysis
technique developed by Cooks and his colleagues called desorption electrospray
ionization, or DESI.

Mass spectrometry works by first turning molecules into
ions, or electrically charged versions of themselves, so that they can be
identified by their mass. Through mass analysis of the ions the contents of a
sample can be identified.

Conventional mass spectrometry requires chemical
separations, manipulations of samples and containment in a vacuum chamber for
ionization and analysis. The DESI technique eliminates these requirements by
performing the ionization step directly on surfaces outside of the mass
spectrometers, making the process much simpler, faster and more applicable to
surgical settings.

The researchers used DESI to evaluate the distribution and
amounts of fatty substances called lipids within the brain tissue. A software
program the team developed then used the results to characterize the brain
tumors and detect boundaries between healthy and cancerous tissue. The
researchers identified lipid patterns that corresponded to the different types
and grades of cancer and concentrations of tumor cells through earlier studies
of banked brain tumor tissue.

Livia Eberlin, who was a graduate student at Purdue at the
time of the study and participated in the research, said the team expanded and
improved the classification system for brain cancers by adding the meningioma
tumor type, prior to the study.

“The classifier includes the two most common types of
brain tumors, gliomas and meningiomas, which combined account for about 65
percent of all brain tumors,” said Eberlin, who is now a postdoctoral
researcher at Stanford University. “The molecular information that is
obtained from this kind of imaging technology allows for an analysis that is
much more detailed than what other techniques can offer. We hope that it can
one day help the thousands of people affected by brain cancer every year.”

The classification results for brain tumor type in the validation
studies of banked tissue agreed with standard pathology methods 100 percent of
the time. The researchers found that the results of the mass spectrometry
analysis of samples taken from the patients during surgery agreed with
pathology with very few exceptions, despite the complexity and heterogeneity of
the surgical samples. The composition of samples taken from different regions
of an individual tumor can differ and tumor cell concentrations are especially
variable, Eberlin said.

The team plans to continue to add to and improve the
classification software and to develop a miniature mass spectrometer that could
be used during surgery, Cooks said. The team also will continue to examine the
molecular patterns of cancerous tissue.

“Ambient ionization mass spectrometry allows us to
look directly at unmanipulated tissue, just as a surgeon does, and get simple
but extremely valuable molecular information,” Cooks said. “These
molecules have a story to tell not just in terms of aiding diagnosis, but also
perhaps in terms of prognosis and our understanding of this devastating

Brigham and Women’s Hospital has set up a mass
spectrometer in the AMIGO suite and plans to begin testing the methodology for
the detection of brain and breast cancer margins during surgery, Agar said.

In addition to Cooks and Eberlin, co-authors of the paper
from Purdue include graduate student Alan Jarmusch. In addition to Agar and
Golby, co-authors from Brigham and Women’s Hospital include Isaiah Norton,
Daniel Orringer, Ian Dunn, Xiaohui Liu and Jennifer Ide of the Department of
Neurosurgery; Keith Ligon and Sandro Santagata of the Department of Pathology;
and Ferenc Jolesz of the Department of Radiology.

The National Institutes of Health, James S. McDonnell
Foundation, Brain Science Foundation and the Daniel E. Ponton Fund for the
Neurosciences, and the Klarman Family Foundation funded this research.

Brigham and Women’s Hospital is a nonprofit teaching
affiliate of Harvard Medical School and a founding member of Partners HealthCare. Through investigation and
discovery conducted at its Biomedical Research
the hospital is an international leader in basic, clinical
and translational research on human diseases.

Writer: Elizabeth K. Gardner, 765-494-2081,
[email protected]

Sources: R. Graham
Cooks, 765-494-5263, [email protected]

Eberlin, [email protected]

Additional media contact: Marjorie
Montemayor-Quellenberg, Brigham and Women’s Hospital communication and public affairs,
617-534-2208, [email protected]


Mass Spectrometry for the Intraoperative Molecular Diagnosis of Human Brain

S. Eberlin, Isaiah Norton, Daniel Orringer, Ian F. Dunn, Xiaohui Liu, Jennifer
L. Ide, Alan K. Jarmusch, Keith L. Ligon, Ferenc A. Jolesz, Alexandra J. Golby,
Sandro Santagata, Nathalie Y. R. Agar and R. Graham Cooks

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. The real challenge for the
neurosurgeon is determining where one should stop tumor resection when
infiltrative tumors seamlessly invade normal brain tissue. 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 new 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 miningioma 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 the stereotactically
registered samples were correlated to pre-operative 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.

This research was
funded in part by National Institutes of Health, grants numbers
1DP2OD007383-01, K08NS064168, 1R21EB009459, P41EB015898 and P41RR019703.

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