Cancer Imaging in ‘The Dartmouth’

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Researchers from Dartmouth-Hitchcock Medical Center and the Thayer School of Engineering have developed a quantitative imaging system to detect low-grade brain cancer cells and make tumor removal more precise, according to Thayer School professor and research group co-leader Keith Paulsen.

The technology consists of a drug, taken pre-operatively, which is broken down, processed and moved into brain tumor tissue.

The fluorescent compound accumulates most intensely in high-grade brain tumor cells, which are not curable by surgery, according to Paulsen. Low-grade tumor cells that are potentially curable, however, accumulate a lower percentage of the compound.

To learn more about this collaborative research project, read Elizabeth Mc Nally’s article in The Dartmouth


Brain Imaging on WCAX

On December 27, 2012, WCAX–a television station based out of Burlington, VT–aired a news segment on a collaborative research project between the Thayer School of Engineering, the Norris Cotton Cancer Center, and the Dartmouth-Hitchcock Medical Center. The segment explains a new cancer imaging technique developed at Dartmouth that makes small brain tumors easier to see during treatment. Before surgery, patients take an oral drug which makes tumors fluoresce under blue light.

In the segment, graduate student Kolbein Kolste explains how the imaging technique that he developed with PhD/MD candidate Pablo Valdes, Dr. David Roberts, and the directors of the Optics in Medicine Lab work in practice. The research project is being funded by a grant from the National Science Foundation, and the optical probe is being developed through a research collaboration with the University of Michigan.

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Link to Video

To learn more about this research collaboration, visit the press release published on the WCAX website.

BEM-based Meshing

Hamid Ghadyani

On February 7th, 2013, Professor Brian Pogue, research scientist Scott Davis, and former Optics in Medicine post doc Hamid Dehghani are teaching an introductory workshop on Near-Infrared Fluorescence and Spectral Tomography (NIRFAST) at the Society of Photo-Optical Instrumentation Engineers (SPIE) Photonics West conference in San Francisco. Developed by the Optics in Medicine Laboratory, Nirfast is used in hospitals and research institutions across the US to model Near-Infrared light transport in tissue. Nirfast is an open source software package that can be downloaded for free, and customized to work with a laboratory’s imaging equipment.

For the duration of his post doctoral position in Dartmouth’s Optics in Medicine Laboratory, research fellow Hamid Ghadyani has improved Nirfast’s meshing capabilities, and added a number of much needed functions to the software package. Hamid received his Bachelors of Science in Mechanical Engineering from Sharif University of Technology in Tehran, Iran, started his masters degree at Temple University, PA, and completed both his masters and doctoral degrees in Mechanical Engineering at Worcester Polytechnic Institute (WPI). In 2010, Hamid presented the Boundary Element Method (BEM) computational work he was doing on Nirfast at the SPIE Optics + Photonics conference in San Diego, and later published the research as “Characterizing accuracy of total hemoglobin recovery using contrast-detail analysis in 3D image-guided near infrared spectroscopy with the boundary element method” in Optics express, 07/2010; 18(15): 15917-35.

While the Finite Element Method (FEM) approximates a partial differential equation  (PDE) over many smaller regions of the entire domain, BEM solves partial differential equations that Green’s function—a function used to solve differential equations with boundary conditions—can be calculated for. In conjunction with Green’s function, boundary conditions are used to solve PDE on the boundary of the domain. The integration of this computational method into Nirfast enables the software bundle to quickly solve a light transport equation without a full-blown step of solid mesh generation.

“The real advantage of BEM is that it simplifies the meshing step. In FEM, mesh creation can account for up to 75 percent of a model’s computational efforts,” explains Hamid. “At the SPIE Optics + Photonics 2010 conference in San Diego, I explained how the Optics in Medicine Laboratory was using BEM-based imaging to model smaller cancer tumors that, in some situations, FEM meshing was unable to detect.”

Through a collaboration with the University of Texas at Austin (UT Austin), Hamid used Dartmouth’s Discovery cluster—a 1704 processor RedHat 5.8 super computer with AMD, Intel, and Nvidia CPUs—to research how small of a tumor Nirfast was able to image. With a software package developed at UT Austin, Hamid ran a simulation on the Discovery cluster that used an impressive 127 GB of Random-access memory (RAM). This research was presented at last year’s Optics Society of America’s (OSA) Miami conference.

A 3D solid mesh is generated using two-dimensional segmented MR images. The cross section shows the location of the tumor in the model.

“My main research interest is developing computational tools that help researchers in biomedical fields harness the power of the FEM method. This involves developing mesh generation algorithms, and high-performance parallel numerical methods,” explains Hamid. “FEM is based on the idea of simplifying PDEs over much smaller sub-regions. The creation of these sub-regions is an important step in any Finite Element analysis as it can affect the accuracy and reliability of solutions. I have streamlined and added advanced features to mesh generation capabilities of Nirfast so that users with almost no background can use meshing tools in their research. This cuts down both the computational time of mesh generation, and the time spent preparing the model significantly.”

Ghadyani has conducted his mesh generation study with current graduate students Kelly Michalsen and Michael Mastanduno, as well as former lab members Amir Golnabi and Xiahxayo Fan. The tools developed by Ghadyani and his collaborators is used by engineers, as well as other professionals who utilize mesh-generation in imaging on a regular basis, including those involved with Electro-Imdepdence tomography, Magnetic Resonance Elastography, and Microwave Imaging Spectroscopy.

Microwave Imaging

Collaborative project of Optics in Medicine Director Keith Paulsen, Dartmouth Engineering Professor Paul Meaney, and researchers at both Dartmouth-Hitchcock Medical Center and the Geisel School of Medicine featured in Focus.

Researchers at the Cancer Imaging and Radiobiology Research Program (CIR) at Dartmouth-Hitchcock’s Norris Cotton Cancer Center study and test new ways to get good images using techniques that exploit different properties of tissue. This research program includes a collaborative team of engineers, family physicians, oncologists, and radiologists.

A semi-transparent CT view of one a study participant’s heel and ankle. The horizontal line overlays indicate where scientists will set the microwave imaging planes.

Microwave imaging has been shown reliable in detecting breast tumors

One area we are exploring is microwave technology: the same basic technology used in microwave ovens can be used to create an image of breast tissue. By sending very low levels (1,000 times less than a cell phone) of microwave energy through tissue, researchers can form a three-dimensional image. These images capture the dielectric properties — electrical conductivity and permittivity (electrical resistance) — of the tissue, which translates into detecting anomalies, such as tumors or other aberrations.

Paul Meaney, a professor at Dartmouth’s Thayer School of Engineering, has been working on microwave engineering for more than 15 years, primarily with Keith Paulsen, the co-director of the CIR, and also the Robert A. Pritzker Professor of Biomedical Engineering at Dartmouth’s Thayer School of Engineering; professor of radiology at the Geisel School of Medicine at Dartmouth; and director of the Dartmouth Advanced Imaging Center at Dartmouth-Hitchcock Medical Center.

For full article, please visit Focus by the Norris Cotton Cancer Center (NCCC).

DCCNE Deadline on 11/26

On Saturday, December 1st the Dartmouth Center of Cancer Nanotechnology Excellence is hosting Cancer Nanotechnology Conference: Mechanisms in Nanoparticle Hyperthermia at the Thayer School of Engineering at Dartmouth. The conference’s keynote speakers will discuss the applications of nanoparticle delivered hyperthermia mechanisms in both research and treatment regimes. The conference will also feature two panel discussions—one focusing on “hyperthermia mechanisms” and the other exploring “nano particle targeting”—as well as poster presentations from current students in Thayer’s GlycoFi Atrium at 4:30 PM.

Kathy Burnham, Administrative Assistant in the Optics in Medicine Laboratory and one of the conference’s coordinators, is still accepting proposals for student posters. Due to the Thanksgiving holiday, the application deadline for both conference attendance and the poster presentation has been extended to Monday, November 26th.  To register, please fill out the form on the conference’s website and also submit  a 200-word poster abstract online. Abstracts of selected posters will be published on the conference’s website a few weeks before Cancer Nanotechnology Conference: Mechanisms in Nanoparticle Hyperthermia.

The conference is sponsored by the Thayer School of Engineering at Dartmouth, the Dartmouth-Hitchcock Norris Cotton Cancer Center, and the Dartmouth Center of Cancer Nanotechnology Excellence.





Michael Jermyn

Written by Hamid Dehghani in 2001, Near-Infrared Fluorescence and
Spectral Tomography (NIRFAST) is an open source software package that allows users to model Near-Infrared light transport in tissue. Currently, Michael Jermyn, a graduate student in Dartmouth’s Optics in Medicine Laboratory, is moving the program to an open source platform and developing a number of new user interfaces and tools.

Since the first version of Nirfast was released, members of the Optics in Medicine Laboratory have modified the software package to increase performance, reliability, usability, and flexibility to different systems. Both the functional information provided by Nirfast and the visualization of detailed anatomic information can allow for better assessment of cancerous tumors in vivo. This information improves the prognosis for patients diagnosed with breast cancer by increasing the effectiveness of preliminary treatment methods.

Nirfast screenshot

While a number of graduate students have contributed to the development of Nirfast, Jermyn worked to refine the interface of the program by improving its PYTHON based tools as a 2011-12 Neukom Graduate Fellow. Last year, Jermyn also transferred the program to a truly open source shareware mode. Now, developers from around the world are able to download the software package for free, modify its source code, and upload patches to the Nirfast website.

“Though I’m currently researching photodynamic therapy light dose modeling, I still work on Nirfast regularly. This fall, we improved the program’s segmentation and mesh creation.” says Jermyn. “Also, I’ve reviewed the feedback our lab gathered at a Nirfast workshop that we ran at last year’s Optics Society of America (OSA) annual conference, which was held in Miami, FL. I compiled both the feedback from the conference and the patches submitted to our open-source site this summer, and released Nirfast version 7.2 online this September.”

Version 7.2 of Nirfast features improved mesh creation and mesh optimization, progress bars that track the status of the system as it renders data, added features to the program’s 3D visualization, and increased permission security.

While Nirfast was designed as a tool for imaging breast cancer, the Optics in Medicine Laboratory have used the program’s mesh generation for many projects including Fluorescence Tomography, as explained by the research group in a video published in the Journal of Visualized Experiments (JoVE) this July. When designing the program, graduate students in Opt Med lab purposely developed Nirfast to allow users to easily modify Nirfast and integrate the program into the operating systems installed on their laboratory’s imaging equipment. This design feature has enabled Nirfast users to customize the program, and effectively use its imaging capabilities for their research needs.

Michael on JoVE

At this February’s Society of Photo-Optical Instrumentation Engineers’ (SPIE) Photonics West conference in San Francisco Professor Brian Pogue, Research Scientist Scott Davis, and former Optics in Medicine post doc Hamid Dehghani are teaching an introductory Nirfast workshop. This workshop is intended to help participants model multi-spectral and luminescent diffuse light propagation in both 2D and 3D geometries and incorporate Digital Imaging and Communications in Medicine (DICOM) images into detailed data models. The workshop costs $525.00 for SPIE members and $635.00 for non-members.