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In recent years, volumetric modulated arc therapy (VMAT) has been becoming a more and more important radiation technique widely used in clinical application for cancer treatment. One of the key problems in VMAT is treatment plan…

Medical Physics · Physics 2016-01-06 Yu Yang , Bin Dong , Zaiwen Wen

We present a novel application of Tensor Network methods in cancer treatment as a potential tool to solve the dose optimization problem in radiotherapy. In particular, the Intensity-Modulated Radiation Therapy (IMRT) technique - that allows…

Medical Physics · Physics 2021-08-11 Samuele Cavinato , Timo Felser , Marco Fusella , Marta Paiusco , Simone Montangero

Financial portfolios are often optimized for maximum profit while subject to a constraint formulated in terms of the Conditional Value-at-Risk (CVaR). This amounts to solving a linear problem. However, in its original formulation this…

Optimization and Control · Mathematics 2014-08-13 Georg Hofmann

Intensity-modulated radiation therapy (IMRT) allows for the design of customized, highly-conformal treatments for cancer patients. Creating IMRT treatment plans, however, is a mathematically complex process, which is often tackled in…

Optimization and Control · Mathematics 2022-03-18 Danielle A. Ripsman , Thomas G. Purdie , Timothy C. Y. Chan , Houra Mahmoudzadeh

Conventional planning objectives in optimization of intensity-modulated radiotherapy treatment (IMRT) plans are designed to minimize the violation of dose-volume histogram (DVH) thresholds using penalty functions. Although successful in…

Medical Physics · Physics 2023-07-19 Lovisa Engberg , Kjell Eriksson , Anders Forsgren , Björn Hårdemark

A split feasibility formulation for the inverse problem of intensity-modulated radiation therapy (IMRT) treatment planning with dose-volume constraints (DVCs) included in the planning algorithm is presented. It involves a new type of…

Medical Physics · Physics 2017-04-26 S. Penfold , R. Zalas , M. Casiraghi , M. Brooke , Y. Censor , R. Schulte

In radiation therapy, mathematical methods have been used for optimizing treatment planning for delivery of sufficient dose to the cancerous cells while keeping the dose to critical surrounding structures minimal. This optimization problem…

Medical Physics · Physics 2015-06-16 Hamed Yarmand , David Craft

Radiation therapy (RT) is a medical treatment to kill cancer cells or shrink tumors. To manually schedule patients for RT is a time-consuming and challenging task. By the use of optimization, patient schedules for RT can be created…

Optimization and Control · Mathematics 2023-05-04 Sara Frimodig , Per Enqvist , Mats Carlsson , Carole Mercier

In the past decades mathematical optimization has found its way into radiation therapy and has made profound practice changing impact. Today, virtually all advanced treatment delivery methods, such as IMRT, VMAT, tomotherapy, LDR/HDR…

Medical Physics · Physics 2018-10-31 Bram L. Gorissen , Jan Unkelbach , Thomas R. Bortfeld

Fluence map optimization for intensity-modulated radiation therapy planning can be formulated as a large-scale inverse problem with competing objectives and constraints associated with the tumors and organs-at-risk. Unfortunately,…

Optimization and Control · Mathematics 2022-02-17 Kelsey Maass , Minsun Kim , Aleksandr Aravkin

Radiotherapy (RT) is a critical cancer treatment, with volumetric modulated arc therapy (VMAT) being a commonly used technique that enhances dose conformity by dynamically adjusting multileaf collimator (MLC) positions and monitor units…

Medical Physics · Physics 2025-06-26 Stefanos Achlatis , Efstratios Gavves , Jan-Jakob Sonke

Purpose: There is growing interest in the use of modern 3D printing technology to implement intensity-modulated radiation therapy (IMRT) on the preclinical scale which is analogous to clinical IMRT. However, current 3D-printed IMRT methods…

We study risk-sensitive Reinforcement Learning (RL), where we aim to maximize the Conditional Value at Risk (CVaR) with a fixed risk tolerance $\tau$. Prior theoretical work studying risk-sensitive RL focuses on the tabular Markov Decision…

Machine Learning · Computer Science 2023-11-21 Yulai Zhao , Wenhao Zhan , Xiaoyan Hu , Ho-fung Leung , Farzan Farnia , Wen Sun , Jason D. Lee

Radiation treatment planning involves optimization over a large number of voxels, many of which carry limited information about the clinical problem. We propose an approach to reduce the large optimization problem by only using a…

Medical Physics · Physics 2024-08-12 Sebastian Mair , Anqi Fu , Jens Sjölund

We present a method for handling dose constraints as part of a convex programming framework for inverse treatment planning. Our method uniformly handles mean dose, maximum dose, minimum dose, and dose-volume (i.e., percentile) constraints…

Medical Physics · Physics 2019-03-05 Anqi Fu , Baris Ungun , Lei Xing , Stephen Boyd

Purpose: This study quantifies the variation in dose-volume histogram (DVH) and normal tissue complication probability (NTCP) metrics for head-and-neck (HN) cancer patients when alternative organ-at-risk (OAR) delineations are used for…

Iterative image reconstruction (IIR) algorithms in Computed Tomography (CT) are based on algorithms for solving a particular optimization problem. Design of the IIR algorithm, therefore, is aided by knowledge of the solution to the…

Medical Physics · Physics 2013-02-22 Emil Y. Sidky , Jakob S. Jørgensen , Xiaochuan Pan

The challenge of removing cancerous cells lies in the limitation of organ at risk, which restricts the ability to increase the radiation dose adequately for enhancing treatment effectiveness. This survey provides a comprehensive overview of…

Medical Physics · Physics 2023-07-27 Amir Moslemi , Navid Khaledi

The radiotherapy of malignant diseases has reached much progress during the past decade. Thus, intensity modulated radiation therapy (IMRT) and VMAT (Rapidarc) now belong to the standard modalities of tumor treatment with high energy…

Medical Physics · Physics 2016-11-15 W. Ulmer , A. Carabe-Fernandez

We study the restricted inverse optimal value problem on linear programming under weighted $l_1$ norm (RIOVLP $_1$). Given a linear programming problem $LP_c: \min \{cx|Ax=b,x\geq 0\}$ with a feasible solution $x^0$ and a value $K$, we aim…

Optimization and Control · Mathematics 2023-08-22 Junhua Jia , Xiucui Guan , Xinqiang Qian , Panos M. Pardalos
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