Optimal marker placement in hadrontherapy: Intelligent optimization strategies with augmented Lagrangian pattern search

PURPOSE In high precision photon radiotherapy and in hadrontherapy, it is crucial to minimize the occurrence of geometrical deviations with respect to the treatment plan in each treatment session. To this end, point-based infrared (IR) optical tracking for patient set-up quality assessment is performed. Such tracking depends on external fiducial points placement. The main purpose of our work is to propose a new algorithm based on simulated annealing and augmented Lagrangian pattern search (SAPS), which is able to take into account prior knowledge, such as spatial constraints, during the optimization process. MATERIAL AND METHODS The SAPS algorithm was tested on data related to head and neck and pelvic cancer patients, and that were fitted with external surface markers for IR optical tracking applied for patient set-up preliminary correction. The integrated algorithm was tested considering optimality measures obtained with Computed Tomography (CT) images (i.e. the ratio between the so-called target registration error and fiducial registration error, TRE/FRE) and assessing the marker spatial distribution. Comparison has been performed with randomly selected marker configuration and with the GETS algorithm (Genetic Evolutionary Taboo Search), also taking into account the presence of organs at risk. RESULTS The results obtained with SAPS highlight improvements with respect to the other approaches: (i) TRE/FRE ratio decreases; (ii) marker distribution satisfies both marker visibility and spatial constraints. We have also investigated how the TRE/FRE ratio is influenced by the number of markers, obtaining significant TRE/FRE reduction with respect to the random configurations, when a high number of markers is used. CONCLUSIONS The SAPS algorithm is a valuable strategy for fiducial configuration optimization in IR optical tracking applied for patient set-up error detection and correction in radiation therapy, showing that taking into account prior knowledge is valuable in this optimization process. Further work will be focused on the computational optimization of the SAPS algorithm toward fast point-of-care applications.

[1]  S. Dreyfus,et al.  Thermodynamical Approach to the Traveling Salesman Problem : An Efficient Simulation Algorithm , 2004 .

[2]  Marcel Zeelenberg,et al.  Data analysis 2 , 2016 .

[3]  Robert Michael Lewis,et al.  A Globally Convergent Augmented Lagrangian Pattern Search Algorithm for Optimization with General Constraints and Simple Bounds , 2002, SIAM J. Optim..

[4]  Michael F. Ochs,et al.  Knowledge-based data analysis comes of age , 2010, Briefings Bioinform..

[5]  S. Rossi,et al.  The status of CNAO , 2011 .

[6]  G Baroni,et al.  Genetic evolutionary taboo search for optimal marker placement in infrared patient setup , 2007, Physics in medicine and biology.

[7]  W. Schlegel,et al.  Accuracy of a commercial optical 3D surface imaging system for realignment of patients for radiotherapy of the thorax , 2007, Physics in medicine and biology.

[8]  Luigi E. Picasso,et al.  On the Weyl algebra for a particle on a sphere , 2011 .

[9]  Alberto L. Sangiovanni-Vincentelli,et al.  A Parallel Simulated Annealing Algorithm for the Placement of Macro-Cells , 1987, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems.

[10]  Daniel R. Greening,et al.  Parallel simulated annealing techniques , 1990 .

[11]  Marco Riboldi,et al.  Real-time tumour tracking in particle therapy: technological developments and future perspectives. , 2012, The Lancet. Oncology.

[12]  G Baroni,et al.  Enhanced Surface Registration Techniques for Patient Positioning Control in Breast Cancer Radiotherapy , 2004, Technology in cancer research & treatment.

[13]  Mehmet Korürek,et al.  A new arrhythmia clustering technique based on Ant Colony Optimization , 2008, J. Biomed. Informatics.

[14]  Jay B. West,et al.  Fiducial Point Placement and the Accuracy of Point-based, Rigid Body Registration , 2001, Neurosurgery.

[15]  Nicholas I. M. Gould,et al.  A globally convergent Lagrangian barrier algorithm for optimization with general inequality constraints and simple bounds , 1997, Math. Comput..

[16]  J. Chavaudra,et al.  Prescribing, Recording, And Reporting Photon Beam Therapy Presentation Of The ICRU Report # 50 , 1992 .

[17]  Hilke Vorwerk,et al.  Interfractional and intrafractional accuracy during radiotherapy of gynecologic carcinomas: a comprehensive evaluation using the ExacTrac system. , 2003, International journal of radiation oncology, biology, physics.

[18]  Hao Chen,et al.  Parallel Simulated Annealing and Genetic Algorithms: a Space of Hybrid Methods , 1994, PPSN.

[19]  Stephen J. Wright,et al.  Numerical Optimization , 2018, Fundamental Statistical Inference.

[20]  C. D. Gelatt,et al.  Optimization by Simulated Annealing , 1983, Science.

[21]  Leo Joskowicz,et al.  Optimal landmarks selection and fiducial marker placement for minimal target registration error in image-guided neurosurgery , 2009, Medical Imaging.

[22]  V. Torczon,et al.  A GLOBALLY CONVERGENT AUGMENTED LAGRANGIAN ALGORITHM FOR OPTIMIZATION WITH GENERAL CONSTRAINTS AND SIMPLE BOUNDS , 2002 .

[23]  Xiaohui Liu,et al.  Optimal Search Space for Clustering Gene Expression Data via Consensus , 2007, J. Comput. Biol..

[24]  R Bellazzi,et al.  Intelligent Data Analysis – Special Issue , 2001, Methods of Information in Medicine.

[25]  Niels Peek,et al.  Intelligent Data Analysis for Knowl edge Discovery, Patient Monitoring and Quality Assessment , 2012, Methods of Information in Medicine.

[26]  Virginia Torczon,et al.  On the Convergence of Pattern Search Algorithms , 1997, SIAM J. Optim..

[27]  Charles Audet,et al.  Analysis of Generalized Pattern Searches , 2000, SIAM J. Optim..

[28]  Yan Yu,et al.  Optimal marker placement in photogrammetry patient positioning system. , 2003, Medical physics.

[29]  Alex Alexandridis,et al.  A medical diagnostic tool based on radial basis function classifiers and evolutionary simulated annealing , 2014, J. Biomed. Informatics.

[30]  Marco Riboldi,et al.  A comparative study between the imaging system and the optical tracking system in proton therapy at CNAO , 2013, Journal of radiation research.

[31]  G Ferrigno,et al.  Real-time three-dimensional motion analysis for patient positioning verification. , 2000, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[32]  Jay B. West,et al.  Predicting error in rigid-body point-based registration , 1998, IEEE Transactions on Medical Imaging.

[33]  Allan Paterson,et al.  Intelligent Data Analysis to Model and Understand Live Cell Time-lapse Sequences , 2012, Methods of Information in Medicine.

[34]  John H. Holmes,et al.  Intelligent data analysis in biomedicine , 2007, J. Biomed. Informatics.

[35]  D. Dinevski,et al.  Intelligent Data Analysis for the Diagnosis of Alcohol Dependence Syndrome , 2011, The Journal of international medical research.

[36]  Icru.  Prescribing, recording, and reporting photon beam therapy , 1993 .

[37]  Jay B. West,et al.  The distribution of target registration error in rigid-body point-based registration , 2001, IEEE Transactions on Medical Imaging.

[38]  C Bert,et al.  Motion in radiotherapy: particle therapy , 2011, Physics in medicine and biology.

[39]  Blaz Zupan,et al.  Knowledge-based data analysis and interpretation , 2006, Artif. Intell. Medicine.

[40]  K. Langen,et al.  Organ motion and its management. , 2001, International journal of radiation oncology, biology, physics.

[41]  Marco Krengli,et al.  Reproducibility of patient setup by surface image registration system in conformal radiotherapy of prostate cancer , 2009, Radiation oncology.

[42]  Robert J. Maciunas,et al.  Registration of head volume images using implantable fiducial markers , 1997, IEEE Transactions on Medical Imaging.

[43]  Dirk Verellen,et al.  Initial clinical experience with infrared-reflecting skin markers in the positioning of patients treated by conformal radiotherapy for prostate cancer. , 2002, International journal of radiation oncology, biology, physics.