Colloquium: Yuriy Zinchenko (U. Calgary)

When:
May 3, 2017 @ 3:00 pm – 4:00 pm
2017-05-03T15:00:00-10:00
2017-05-03T16:00:00-10:00
Where:
Keller 401

TITLE
Dose-volume requirements modeling for radiotherapy optimization

ABSTRACT
Radiation therapy is an important modality in cancer treatment. To find a good treatment plan, optimization models
and methods are typically used, while dose-volume requirements play an important role in plan’s quality evaluation.
We compare four different optimization approaches to incorporate the so-called dose-volume constraints into the
fluence map optimization problem for intensity modulated radiotherapy. Namely, we investigate (1) conventional
emph{Mixed Integer Programming} (MIP) approach, (2) emph{Linear Programming} (LP) approach to partial volume
constraints, (3) emph{Constrained Convex Moment} (CCM) approach, and (4) emph{Unconstrained Convex Moment
Penalty} (UCMP) approach. The performance of the respective optimization models is assessed using anonymized data
corresponding to eight previously treated prostate cancer patients. Several benchmarks are compared, with the goal
to evaluate the relative effectiveness of each method to quickly generate a good initial plan, with emphasis on
conformity to DVH-type constraints, suitable for further, possibly manual, improvement.

BIO
Dr. Zinchenko received his PhD from Cornell University on 2005 under supervision of Prof. James Renegar.
From 2005 to 2008 he held a PDF position at the Advanced Optimization Lab at McMaster University, working
with Prof. Tamas Terlaky and Prof. Antone Deza, and spent portion of his fellowship with radiation oncology group
at the Princess Margaret Hospital in Toronto. Currently, Yuriy is an Associate Professor of Mathematics & Stat at the
University of Calgary.
Dr. Zinchenko’s primary research interest lies in convex optimization, and particularly, the curvature of the central path for
interior-point methods, and applications. Yuriy’s work on optimal radiotherapy design was recognized by 2008 MITACS
Award for Best Novel Use of Mathematics in Technology Transfer, and in 2012-2015 he served as one of the PIs for
PIMS Collaborative Research Group grant on optimization.