Martin Bues

Dr. Martin Bues

orcid

Research Focus & Metrics

Academic Career Length

27Years (2000-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 March 2004 in International Journal of Radiation Oncology, Biology, Physics
Verified
Journal Article
Closed access
WCW.H St. Clair
W.H St. Clair
JAJ.A Adams
J.A Adams
MBMartin Bues
Martin Bues
BFB.C Fullerton
B.C Fullerton
SSSean La Shell
Sean La Shell
NTN.J Tarbell
N.J Tarbell

4 December 2009 in Medical Physics
Verified
Journal Article
Closed access
MGMichael Gillin
Michael Gillin
NSNarayan Sahoo
Narayan Sahoo
MBMartin Bues
Martin Bues
GCGeorge Ciangaru
George Ciangaru
GSGabriel Sawakuchi
Gabriel Sawakuchi
XZX. Ronald Zhu
X. Ronald Zhu

12 August 2009 in Medical Physics
Verified
Journal Article
Closed access
ASAlfred Smith
Alfred Smith
MGMichael Gillin
Michael Gillin
MBMartin Bues
Martin Bues
XZX. Ronald Zhu
X. Ronald Zhu
KSKazumichi Suzuki
Kazumichi Suzuki
KMKoji Matsuda
Koji Matsuda

1 May 2016 in International Journal of Radiation Oncology, Biology, Physics
Verified
Journal Article
Closed access
WLWei Liu
Wei Liu
SSSteven E. Schild
Steven E. Schild
JCJoe Y. Chang
Joe Y. Chang
ZLZhongxing Liao
Zhongxing Liao
YCYu-Hui Chang
Yu-Hui Chang
MBMartin Bues
Martin Bues

1 March 2015 in Practical Radiation Oncology
Verified
Journal Article
Closed access
WLWei Liu
Wei Liu
ZLZhongxing Liao
Zhongxing Liao
SSSteven E. Schild
Steven E. Schild
ZLZhong Liu
Zhong Liu
HLHeng Li
Heng Li
RMRadhe Mohan
Radhe Mohan

4 October 2017 in Medical Physics
Verified
Journal Article
Open access
PDF file
YAYu An
Yu An
JSJie Shan
Jie Shan
SPSamir H. Patel
Samir H. Patel
WWWilliam Wong
William Wong
SSSteven E. Schild
Steven E. Schild
WLWei Liu
Wei Liu
Purpose: We propose a robust treatment planning model that simultaneously considers proton range and patient setup uncertainties and reduces high linear energy transfer (LET) exposure in organs at risk (OARs) to minimize the relative biological effectiveness (RBE) dose in OARs for intensity‐modulated proton therapy (IMPT). Our method could potentially reduce the unwanted damage to OARs.Methods: We retrospectively generated plans for 10 patients including two prostate, four head and neck, and four lung cancer patients. The “worst‐case robust optimization” model was applied. One additional term as a “biological surrogate (BS)” of OARs due to the high LET‐related biological effects was added in the objective function. The biological surrogate was defined as the sum of the physical dose and extra biological effects caused by the dose‐averaged LET. We generated nine uncertainty scenarios that considered proton range and patient setup uncertainty. Corresponding to each uncertainty scenario, LET was obtained by a fast LET calculation method developed in‐house and based on Monte Carlo simulations. In each optimization iteration, the model used the worst‐case BS among all scenarios and then penalized overly high BS to organs. The model was solved by an efficient algorithm (limited‐memory Broyden–Fletcher–Goldfarb–Shanno) in a parallel computing environment. Our new model was benchmarked with the conventional robust planning model without considering BS. Dose–volume histograms (DVHs) of the dose assuming a fixed RBE of 1.1 and BS for tumor and organs under nominal and uncertainty scenarios were compared to assess the plan quality between the two methods.Results: For the 10 cases, our model outperformed the conventional robust model in avoidance of high LET in OARs. At the same time, our method could achieve dose distributions and plan robustness of tumors assuming a fixed RBE of 1.1 almost the same as those of the conventional robust model.Conclusions: Explicitly considering LET in IMPT robust treatment planning can reduce the high LET to OARs and minimize the possible toxicity of high RBE dose to OARs without sacrificing plan quality. We believe this will allow one to design and deliver safer proton therapy.