Medical physics research projects
Department of Radiation Oncology, University of Washington
Medical physics research at the UW includes:
- Algorithms for automatic generation of clinical
target volumes in head and neck cancer
(Ira Kalet, Mary
Austin-Seymour)
The success of radiation therapy depends critically on
accurately delineating the target volume, which is the region of known
or suspected disease in a patient. Methods that can compute a contour
set defining a target volume on a set of patient images will
contribute greatly to the success of radiation therapy and
dramatically reduce the workload of radiation oncologists, who
currently draw the target by hand on the images using simple computer
drawing tools. The most challenging part of this process is to
estimate where there is microscopic spread of disease. We are
developing methods for automatically selecting and adapting
standardized regions of tumor spread based on the location of lymph
nodes in a standard or reference case, together with image
registration techniques. The best available image registration
techniques (deformable transformations computed using ``mutual
information'' optimization) appear promising but will need to be
supplemented by anatomic knowledge-based methods to achieve a
clinically acceptable match. This project also involves collaboration
from Mark Whipple, Otolaryngology/Head and Neck Surgery, Linda Shapiro,
Computer Science and Engineering/Electrical Engineering, and Chia-Chi
Teng, Electrical Engineering graduate student.
- Intraoperative Dose Optimization For Prostate
Brachytherapy
(Paul Cho)
While brachythearpy has proven to be an effective treatment
modality for early-stage prostate cancer, local failure and
recurrence do occur. Based on the post-implant analysis
correlating the PSA level and the principal dosimetric parameters,
it is evident that the probability of cure increases with
improved dose distribution. The primary objective of the proposed
research is to develop an intraoperative method to measure and
modify dose distribution for optimal outcome. Specific aims
include: (1) automated detection and localization of seeds from
multiple fluoroscopy projections, (2) semi-automated segmentation
of prostate volume from ultrasound, (3) automated registration of
seeds and prostate volume, (4) development of dose modification
supervisor, and (5) clinical evaluation of the target system.
The project is funded by NIH/NCI and DoD.
- Advanced Inverse Planning Algorithm For IMRT
(Paul Cho)
It has been shown that the inverse problem in IMRT is severly
ill-conditioned. The mathematical limitation inherent in inverse
planning algorithms has not yet been quantified and properly
regulated. The present research exploits the power of singular
value decomposition to characterize and regulate the dose matrices
for optimal convergence to a feasible solution. Tikhonov method
combined with convex projection is being investigated.
- Image Guided Therapy
(Mark Phillips, Paul Cho, Juergen Meyer)
Advances in imaging physiological processes, e.g. hypoxia, are an
important development in targetting tissues for radiation therapy as
well as assessing response to treatment. A collaboration with the
Nuclear Medicine/PET group at UWMC is working to develop and apply
deformable image registration for two separate clinical studies. The
first is to use PET-FDG to reduce the size of target volumes in head
and neck cancer, and thus reduce morbidity. The other is to use
PET-FMISO to image hypoxia in head and neck tumors and to use the
information to design IMRT treatments and to assess the response of
the hypoxic regions to radiation therapy. This work is being
performed in conjunction with the Nuclear Medicine Department (Paul
Kinahan, Joseph Rajendran) and VA-Puget Sound (Eric Ford, David
Schwartz).
- Improvements in Radiation Therapy Plan Optimization
(Mark Phillips, Juergen Meyer, Ira Kalet)
Treatment planning optimization has recently received much attention
due to the advent of inverse planning techniques for IMRT. As useful
as these algorithms are, they all have difficulty in handling the
predominant situations in radiation therapy. These problems include
decisions based on models formulated with incomplete data, incomplete
and qualitative presriptions, and mutually contradictory
constraints/objectives. Our project is aimed at using belief nets
(also known as Bayes' nets) to provide better methods at guiding the
optimization process and choosing the most clinically appropriate
solution.
- Improved Seeds for Permanent Seed Implants for
Prostate Cancer
(Mark Phillips)
Classic radiation biology has always categorized tumor response as
having a high alpha/beta ratio, similar to that of acutely responding
tumors. This has resulted in treatment strategies that make use of
prolonged fractionation schedules in order to achieve the most
separation between the tumor response and dose-limiting late
responding tumors. Recent clinical results have indicated that for
prostate tumors the alpha/beta ratio is probably less than 3, similar
to late responding tissues. In addition, recently published data
indicate that repair is much slower than previous thought. In a
project done in collaboration with IsoRay, Inc., a company designing
and developing novel isotope-seed combinations, I am investigating the
potential advantages that would result from a shorter half-life
isotope for permanent seed implants in light of the profound changes
in the radiobiological modelling of prostate cancer.
ikalet@u.washington.edu