Article
Management
P. Carrasqueira, H. Rocha, J. M. Dias, T. Ventura, B. C. Ferreira, M. C. Lopes
Summary: This study presents an automated framework for optimizing noncoplanar arc trajectories in radiation therapy, which can generate high-quality treatment plans and improve treatment planning quality compared to coplanar techniques. The experiments conducted on difficult tumor cases demonstrated the effectiveness of the optimized noncoplanar arc trajectories.
INTERNATIONAL TRANSACTIONS IN OPERATIONAL RESEARCH
(2023)
Article
Radiology, Nuclear Medicine & Medical Imaging
Charles Huang, Yong Yang, Lei Xing
Summary: The NC-POPS algorithm provides a modular approach for fully automated treatment planning of NC IMRT cases, with the potential to substantially improve treatment planning workflow and plan quality.
Article
Radiology, Nuclear Medicine & Medical Imaging
Christian Harrer, Wolfgang Ullrich, Jan J. Wilkens
Summary: This study used machine learning models trained on a database of pre-optimized treatment plans to identify relevant optimization parameter ranges and predict their impact on dosimetric plan quality criteria. Successfully identifying parameter regions resulting in significant variability of dosimetric plan properties depended on geometry features, treatment indication, and plan property under investigation. Model assessment showed AUC values between 0.82 and 0.99, with the best average precision values ranging from 0.71 to 0.99.
PHYSICA MEDICA-EUROPEAN JOURNAL OF MEDICAL PHYSICS
(2021)
Article
Radiology, Nuclear Medicine & Medical Imaging
Franklin Okoli, Julien Bert, Salih Abdelaziz, Nicolas Boussion, Dimitris Visvikis
Summary: This study aimed to optimize beam selection in noncoplanar VMAT using simulated annealing method, leading to better organ avoidance. The proposed method was compared to standard approaches and showed better organ protection in specific patient cases.
IEEE TRANSACTIONS ON RADIATION AND PLASMA MEDICAL SCIENCES
(2022)
Article
Radiology, Nuclear Medicine & Medical Imaging
L. Placidi, M. Nardini, D. Cusumano, L. Boldrini, G. Chiloiro, A. Romano, C. Votta, M. Antonelli, V. Valentini, L. Indovina
Summary: The study evaluated an innovative VMAT-like (VML) delivery technique, showing potential in locally advanced pancreas treatments. VML plans met all OAR constraints and generally had better PTV coverage compared to IMRT plans.
PHYSICA MEDICA-EUROPEAN JOURNAL OF MEDICAL PHYSICS
(2021)
Article
Engineering, Biomedical
Yimin Ni, Shufei Chen, Lyndon Hibbard, Peter Voet
Summary: This study developed and evaluated a deep learning based fast volumetric modulated arc therapy (VMAT) plan generation method. The results showed that the VMAT plans generated based on the deep learning prediction had no significant difference compared to the plans generated with a previously validated automated treatment planning method. Moreover, the deep learning prediction method reduced the optimization time by 29.3%.
PHYSICS IN MEDICINE AND BIOLOGY
(2022)
Article
Multidisciplinary Sciences
Chen-Xiong Hsu, Kuan-Heng Lin, Shan-Ying Wang, Wei-Ta Tsai, Chiu-Han Chang, Hui-Ju Tien, Pei-Wei Shueng, Tung-Hsin Wu, Greta S. P. Mok
Summary: This study successfully applied an optimized partial arcs (OPA) angle based on the volume-based algorithm (VBA) to the radiotherapy treatment planning for esophageal cancer patients. Compared to traditional methods, the use of VBA reduced lung dose and delivery time, providing better protection for lung tissues during treatment.
SCIENTIFIC REPORTS
(2022)
Article
Oncology
Laurence Delombaerde, Saskia Petillion, Caroline Weltens, Tom Depuydt
Summary: This study evaluated the reproducibility and stability of breath-hold breast treatments on a closed-bore gantry linac, showing minimal systematic and random variability in breath-hold amplitude. There was a limited correlation between portal images and surface monitoring deviations.
RADIOTHERAPY AND ONCOLOGY
(2021)
Article
Oncology
Heleen Bollen, Julie van der Veen, Annouschka Laenen, Sandra Nuyts
Summary: IMRT and VMAT have become standard of care in treating head and neck cancer. By analyzing treatment failure patterns, this study indirectly investigated the quality of target volume delineation and treatment delivery, which were performed accurately with few recurrences outside high-dose regions and no marginal failures observed.
FRONTIERS IN ONCOLOGY
(2021)
Article
Radiology, Nuclear Medicine & Medical Imaging
C. Arilli, M. Zani, L. Marrazzo, S. Scoccianti, M. Casati, A. Compagnucci, C. Talamonti, L. Livi, S. Pallotta
Summary: The study successfully implemented an automatic planning technique for VMAT treatment of GBM, improving efficiency and providing better protection for critical structures. The AutoPlanning module showed statistically significant improvements in critical structure sparing, providing a reliable tool for treatment planning efficiency.
PHYSICA MEDICA-EUROPEAN JOURNAL OF MEDICAL PHYSICS
(2021)
Article
Biology
Sophie Wuyckens, Michael Saint-Guillain, Guillaume Janssens, Lewei Zhao, Xiaoqiang Li, Xuanfeng Ding, Edmond Sterpin, John A. Lee, Kevin Souris
Summary: Arc proton therapy (ArcPT) is an emerging modality in cancer treatments. This paper investigates three distinct problem statements in order to solve the ArcPT optimization problem. The results show that mixed-integer programming (MIP) performs the best in terms of dose quality and time delivery efficiency, especially for low scale problems.
COMPUTERS IN BIOLOGY AND MEDICINE
(2022)
Article
Oncology
Fady Samir, Talaat M. Meaz, Fathi AEl Hussiny, Ahmed A. Ahmed, Amr A. Mahmoud, Tamer Refaat, Ahmed Gawish, Mohamed Abouegylah
Summary: The study compared four techniques in prostate treatment to find the preferred technique. Plans were created for 30 prostate cancer patients using different techniques, and the quality of the plans was assessed by comparing target coverage, organs at risk, monitor units, homogeneity, and conformity among the techniques.
JOURNAL OF CANCER RESEARCH AND CLINICAL ONCOLOGY
(2023)
Article
Medicine, General & Internal
Fabrizio Tonetto, Alessandro Magli, Eugenia Moretti, Andrea Emanuele Guerini, Annarita Tullio, Chiara Reverberi, Tino Ceschia, Luigi Spiazzi, Francesca Titone, Agnese Prisco, Marco Andrea Signor, Michela Buglione, Gioacchino De Giorgi, Marco Trovo, Luca Triggiani
Summary: This study compares gastrointestinal (GI) and genitourinary (GU) toxicity rates among prostate cancer patients treated with image-guided volumetric modulated arc therapy (IG-VMAT) and IG-3D conformal radiation therapy (IG-3DCRT). Results show lower late GI and GU toxicity rates in the VMAT group, with overall low rates of G >= 2 toxicities. VMAT allowed for dose reduction to organs at risk, showing promising results in terms of organ sparing and reduced toxicity.
JOURNAL OF CLINICAL MEDICINE
(2022)
Article
Engineering, Biomedical
Lydia J. Wilson, Wayne D. Newhauser
Summary: This study developed an outcome-based objective function to directly optimize projected health outcomes, showing that outcome-optimized radiotherapy (OORT) was superior to dose-optimized radiotherapy (DORT) in improving projected health outcomes for prostate cancer patients. The results were consistent across treatment modalities, late-risk models, and individual patients, suggesting the feasibility of optimizing longitudinal health outcomes associated with total absorbed dose in all tissues for cancer patients. This approach offers a simpler, more direct way to realize the full beneficial potential of cancer radiotherapy.
PHYSICS IN MEDICINE AND BIOLOGY
(2021)
Article
Oncology
Wuji Sun, Yinghua Shi, Yu Li, Chao Ge, Xu Yang, Wenming Xia, Kunzhi Chen, Libo Wang, Lihua Dong, Huidong Wang
Summary: This study investigates the dosimetric effect and delivery reliability of jaw tracking (JT) for lung stereotactic body radiation therapy (SBRT). A threshold of PTV is proposed as a selection criterion between JT and fixed-jaw (FJ) techniques. Results show that JT plans have significant dosimetric improvements compared to FJ plans, and the PTV is correlated with the differences in lung dose values. The study concludes that JT can be selected based on a PTV threshold to ensure delivery reliability for lung SBRT.
FRONTIERS IN ONCOLOGY
(2022)
Article
Radiology, Nuclear Medicine & Medical Imaging
Patryk Hejduk, Magda Marcon, Jan Unkelbach, Alexander Ciritsis, Cristina Rossi, Karol Borkowski, Andreas Boss
Summary: This study developed a post-processing technique based on deep convolutional neural networks (dCNNs) for detection and classification of lesions in automated breast ultrasound (ABUS) according to the BI-RADS atlas. The results showed that the dCNN achieved similar accuracy as experienced radiologists in detecting and distinguishing lesions in ABUS.
EUROPEAN RADIOLOGY
(2022)
Article
Radiology, Nuclear Medicine & Medical Imaging
Florian Amstutz, Silvia Fabiano, Louise Marc, Damien Charles Weber, Antony John Lomax, Jan Unkelbach, Ye Zhang
Summary: Optimally combined proton-photon plans have been shown to improve treatment plan quality compared to IMRT alone, potentially reducing the risk of toxicity while also allowing for increased accessibility to proton therapy for NSCLC patients.
Article
Oncology
Roman Ludwig, Jean-Marc Hoffmann, Bertrand Pouymayou, Martina Broglie Dappen, Gregoire Morand, Matthias Guckenberger, Vincent Gregoire, Panagiotis Balermpas, Jan Unkelbach
Summary: This study investigated the lymphatic progression patterns in head and neck squamous cell carcinomas (HNSCC) and analyzed the risk of metastases in different lymph node levels (LNL) based on the involvement of upstream LNLs, T-category, HPV status, and other risk factors. The findings provide valuable insights for the personalization of CTV-N definition in the future.
RADIOTHERAPY AND ONCOLOGY
(2022)
Article
Multidisciplinary Sciences
Roman Ludwig, Jean-Marc Hoffmann, Bertrand Pouymayou, Gregoire Morand, Martina Broglie Dappen, Matthias Guckenberger, Vincent Gregoire, Panagiotis Balermpas, Jan Unkelbach
Summary: The dataset provides detailed information on lymph node involvement in patients with oropharyngeal squamous cell carcinoma. It can be used to build quantitative models for predicting lymphatic metastasis and personalize the clinical target volume definition and neck dissection range in radiation therapy and surgical treatment.
Article
Radiology, Nuclear Medicine & Medical Imaging
Jan Unkelbach, Silvia Fabiano, Amit Ben Antony Bennan, Silvan Mueller, Mark Bangert
Summary: This article investigates the optimal combination of photons and particles for radiotherapy treatments. By simultaneously optimizing multiple radiation modalities, such as electron-photon combinations, proton-photon combinations, and carbon-photon combinations, the distinct characteristics of different radiation types can be exploited to improve upon single-modality treatments.
IEEE TRANSACTIONS ON RADIATION AND PLASMA MEDICAL SCIENCES
(2022)
Article
Radiology, Nuclear Medicine & Medical Imaging
Sojin Shim, Davide Cester, Lisa Ruby, Christian Bluethgen, Magda Marcon, Nicole Berger, Jan Unkelbach, Andreas Boss
Summary: This study proposes an automated segmentation method for breast CT images, utilizing optimized seeded watershed and region growing algorithms. The method demonstrates excellent performance in qualitative and quantitative evaluations, enabling accurate quantification of breast density and glandular tissue volume, which are essential for breast cancer risk assessment.
JOURNAL OF APPLIED CLINICAL MEDICAL PHYSICS
(2022)
Article
Radiology, Nuclear Medicine & Medical Imaging
David Papp, Jan Unkelbach
Summary: This study addresses the situation where a radiotherapy clinic has a limited number of proton therapy slots available each day. By extending the normal tissue complication probability model, the researchers use Markov decision process methodology to determine the optimal thresholds for selecting patients for proton therapy, maximizing the benefit of limited resources.
Article
Engineering, Biomedical
Silvia Fabiano, Nathan Torelli, David Papp, Jan Unkelbach
Summary: A novel stochastic optimization method was developed to incorporate uncertainties into proton-photon treatment planning. By considering the expected value and standard deviation of cumulative BED in each voxel, the method aims to produce robust combined treatment plans for optimal tumor coverage and sparing of healthy tissues. This approach addresses concerns about range and setup errors in optimized proton-photon radiotherapy without explicitly considering all error scenarios.
PHYSICS IN MEDICINE AND BIOLOGY
(2022)
Article
Mathematics, Applied
Maria M. Davis, David Papp
Summary: In this paper, we study the problem of computing weighted sum-of-squares (WSOS) certificates for positive polynomials over a compact semialgebraic set. We introduce the concept of dual certificates and provide a new short proof of Powers's theorems on the existence of rational WSOS certificates. We also propose an algorithm for computing the optimal WSOS lower bound of a given polynomial along with a rational dual certificate.
SIAM JOURNAL ON OPTIMIZATION
(2022)
Article
Computer Science, Theory & Methods
David Papp
Summary: Circuit polynomials are used to compute global lower bounds efficiently. However, finding the best combination of circuits is a challenging task. We propose an efficient method to compute the optimal lower bound by iteratively identifying the optimal circuits.
JOURNAL OF SYMBOLIC COMPUTATION
(2023)
Article
Radiology, Nuclear Medicine & Medical Imaging
Nathan Torelli, David Papp, Jan Unkelbach
Summary: This study investigates the potential of spatiotemporal fractionation schemes to reduce the healthy brain's received biological dose in the treatment of brain metastases (BMs). The spatiotemporal fractionation schemes involve partial hypofractionation in the metastases and more uniform fractionation in the healthy brain. A constrained approach to spatiotemporal fractionation (cSTF) is proposed for patients with multiple brain metastases, which is more robust against uncertainties. The results show that spatiotemporal fractionation schemes can effectively reduce the healthy brain's biological dose.
Article
Management
David Papp, Krisztina Regos, Gabor Domokos, Sandor Bozoki
Summary: In the study of monostatic polyhedra, the main question is to construct an object with the minimal number of faces and vertices. Despite establishing upper and lower bounds on the necessary numbers, none of the questions have been resolved.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2023)
Article
Computer Science, Interdisciplinary Applications
David Papp, Sercan Yildiz
Summary: The paper introduces an open-source Matlab package called alfonso for solving conic optimization problems over nonsymmetric convex cones. This software is unique in that it allows optimization over any convex cone as long as a suitable barrier function is available, expanding the range of applicable cones compared to other conic optimization software. Furthermore, it offers comparable efficiency to state-of-the-art interior-point methods for symmetric cones and can outperform existing software for problems with specific characteristics that can be leveraged in barrier computation.
INFORMS JOURNAL ON COMPUTING
(2022)