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 CancerNanotechnology Conference: Mechanisms in Nanoparticle Hyperthermia.
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.
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.
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.
Molecular Therapy has the potential to improve the prognosis for difficult to treat cancer types, including glioblastoma multiform and pancreatic cancer. By targeting tumors, this non-invasive form of treatment delivers drugs directly to cancerous cells without damaging healthy tissue. Currently, this approach to molecular imaging is being tested at the Dartmouth Hitchcock Medical Center (DHMC). Through improving the accuracy and effectiveness of this new type of therapy, the Optics in Medicine Laboratory hopes to increase the survival rate for these types of cancers that, once diagnosed, are often fatal.
Robert Holt, a fourth-year graduate student in the Optics in Medicine Laboratory, is improving the fluorescence tomography imaging methods of a system that was built by the lab several years ago. Designed to image small animals, the machine is housed in the new animal-imaging suite at DHMC. While the imaging methods that the machine utilizes were developed on small animals, the lab members are hopeful that in the future these techniques can be used to increase the effectiveness of molecular therapy in humans by providing radiologist more detailed images of tumors.
Built under the guidance of Ken Tichauer, a Dartmouth post doc and a fellow of the Canadian Institutes of Health Research (CIHR), this machine uses laser light to recover the distribution of fluorescent molecules in tissue. Currently, Holt and Tichauer are developing a method to improve image reconstruction of tracer uptake quantification, and are optimizing the placement of imaging detectors in the machine. As the two researchers develop these methods, second-year graduate student Fadi El-Ghussein updates the machine’s software so that the imaging system is able to test these new methods.
“It’s been great working with Ken and Fadi on this project. A number of the ideas that our team has incorporated into the machine came out of a paper that Ken and I drafted together. The paper explored the uptake characteristics of fluorescence tracers, and examined how best to reconstruct their uptakes of tracers,” explains Robert. “Ken motivated this study from a biological standpoint, and I worked on the mathematics of how to make it work. After Ken and I calculate an imaging method that we want to test, we tell Fadi about the idea so that he can rewrite the software that runs the system’s instrumentation. Once the software is updated, we then conduct imaging trials on small animals to see how well our methods work.”
Being a non-invasive procedure, fluorescence tomography images tumors without harming non-infected cells. For dangerous cancers located in sensitive areas—like giloma, a type of tumor that forms in the brain and spine—this type of therapy has the potential to significantly increase the survival rates of patients diagnosed with these tumors.
While screen-film mammography has been proven to reduce the mortality of the disease, the screening method has its limitations. As Professor Keith Paulsen explains in this video published by the Thayer School of Engineering, doctors often find the images created by mammography difficult to read due to “tissue overlap”—a type of distortion that occurs when a complex, 3D object is rendered as a 2D image:
Approved for use by the FDA in 2011, tomosythesis collects imaging data much like an MRI scan, except that the X-ray generator rotates around the patient and then mathematically reconstructs this data into a 3D model. Currently, MD/PhD student Kelly Michaelsen and Professor Venkataramanan Krishnaswamy are developing a screening system that combines near infrared spectral tomography (NIRST) with the high-resolution 3D structural information of breast tomosythesis (BTS) into a singular breast-cancer detection method. This research is being conducted with both Hologic, Inc—the commercial leader in the development of breast tomosythesis (BTS) technology—and the University of Massachusetts Medical School.
The first prototype of this imaging system is currently being tested at the Dartmouth Hitchcock Medical Center (DHMC). After calibrating its components on a series of tissue phantoms, Michaelsen and her advisor started conducting pre-clinical imaging trials on patients at DHMC. With the data collected from these trials, the research group identified aspects of the system that could be improved, and began constructing a second-generation prototype of the imaging machine. Once this second-generation prototype is completed, the original machine will be moved to the University of Massachusetts Medical School where researchers will collect clinical data in another series of pre-clinical trials.
“In 2010, the fatality rate for females diagnosed with breast cancer in the US was just over 19 percent,” says Michaelsen. “The combined imaging system that our lab is developing is aimed at decreasing the number of women who go through invasive biopsy procedures. Through improving the early stages of breast cancer detection, we hope to decrease the fatality rate of this disease.”
The research being conducted at all of the institutions involved in this project has been made possible by a funding opportunity provided by the National Institute of Health (NIH) and its National Cancer Institute (NCI) that seeks to develop new in vivo imaging systems. The partnership between Dartmouth, the University of Massachusetts, and Hologic, Inc aims to integrate the two systems into a singular detection method, and to establish the clinical potential of this combined imaging approach.
DCCNE is funded by $12.8 million grant from the National Cancer Institute (NCI). Each year, members of the Optics in Medicine Laboratory participate in the center’s educational programs, and conduct interdepartmental research thanks to the funding provided by the NCI.