Robust plan optimization using edge-enhanced intensity for intrafraction organ deformation in prostate intensity-modulated radiation therapy

This study evaluated a method for prostate intensity-modulated radiation therapy (IMRT) based on edge-enhanced (EE) intensity in the presence of intrafraction organ deformation using the data of 37 patients treated with step-and-shoot IMRT. On the assumption that the patient setup error was already accounted for by image guidance, only organ deformation over the treatment course was considered. Once the clinical target volume (CTV), rectum, and bladder were delineated and assigned dose constraints for dose optimization, each voxel in the CTV derived from the DICOM RT-dose grid could have a stochastic dose from the different voxel location according to the probability density function as an organ deformation. The stochastic dose for the CTV was calculated as the mean dose at the location through changing the voxel location randomly 1000 times. In the EE approach, the underdose region in the CTV was delineated and optimized with higher dose constraints that resulted in an edge-enhanced intensity beam to the CTV. This was compared to a planning target volume (PTV) margin (PM) approach in which a CTV to PTV margin equivalent to the magnitude of organ deformation was added to obtain an optimized dose distribution. The total monitor units, number of segments, and conformity index were compared between the two approaches, and the dose based on the organ deformation of the CTV, rectum, and bladder was evaluated. The total monitor units, number of segments, and conformity index were significantly lower with the EE approach than with the PM approach, while maintaining the dose coverage to the CTV with organ deformation. The dose to the rectum and bladder were significantly reduced in the EE approach compared with the PM approach. We conclude that the EE approach is superior to the PM with regard to intrafraction organ deformation.

[1]  Indrin J Chetty,et al.  Quantifying the interplay effect in prostate IMRT delivery using a convolution-based method. , 2008, Medical physics.

[2]  Niko Papanikolaou,et al.  Consequences of anorectal cancer atlas implementation in the cooperative group setting: radiobiologic analysis of a prospective randomized in silico target delineation study. , 2014, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[3]  A Brahme,et al.  Tumour and normal tissue responses to fractionated non-uniform dose delivery. , 1992, International journal of radiation biology.

[4]  S. Morita,et al.  Rectal content and intrafractional prostate gland motion assessed by magnetic resonance imaging. , 2011, Journal of radiation research.

[5]  A. Hanlon,et al.  Radiation therapy dose escalation for prostate cancer: a rationale for IMRT , 2003, World Journal of Urology.

[6]  T. Eade,et al.  Determining optimal planning target volume and image guidance policy for post-prostatectomy intensity modulated radiotherapy , 2015, Radiation oncology.

[7]  Y. Yoshioka,et al.  Evaluation of the radiobiological gamma index with motion interplay in tangential IMRT breast treatment , 2016, Journal of radiation research.

[8]  International Commission on Radiation Units and Measurements , 2019 .

[9]  Lei Dong,et al.  Dose-response characteristics of low- and intermediate-risk prostate cancer treated with external beam radiotherapy. , 2004, International journal of radiation oncology, biology, physics.

[10]  G. Geoffrey Vining,et al.  Applied Statistics for Engineers and Physical Scientists (2nd ed.). , 1993 .

[11]  Indra J. Das,et al.  On correlations in IMRT planning aims , 2016, Journal of applied clinical medical physics.

[12]  John N Tsitsiklis,et al.  Optimal margin and edge-enhanced intensity maps in the presence of motion and uncertainty , 2010, Physics in medicine and biology.

[13]  S. Henderson,et al.  Robust optimization for intensity modulated radiation therapy treatment planning under uncertainty , 2005, Physics in medicine and biology.

[14]  J. Keyriläinen,et al.  Implementation of adaptive radiation therapy for urinary bladder carcinoma: Imaging, planning and image guidance , 2013, Acta oncologica.

[15]  Prescribing, Recording, and Reporting Photon-Beam Intensity-Modulated Radiation Therapy (IMRT) , 2010 .

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

[17]  Rasmus Bokrantz,et al.  The scenario-based generalization of radiation therapy margins , 2015, Physics in medicine and biology.

[18]  W. Tomé,et al.  Risk-adaptive optimization: selective boosting of high-risk tumor subvolumes. , 2006, International journal of radiation oncology, biology, physics.

[19]  Paul J Keall,et al.  Toward the development of intrafraction tumor deformation tracking using a dynamic multi-leaf collimator. , 2014, Medical physics.

[20]  J. E. Scaife,et al.  Random variation in rectal position during radiotherapy for prostate cancer is two to three times greater than that predicted from prostate motion , 2014, The British journal of radiology.

[21]  Uwe Oelfke,et al.  Incorporating organ movements in IMRT treatment planning for prostate cancer: minimizing uncertainties in the inverse planning process. , 2005, Medical physics.

[22]  Eric R. Ziegel,et al.  Applied Statistics for Engineers and Physical Scientists , 1992 .

[23]  R. Mohan,et al.  Optimization of intensity-modulated radiotherapy plans based on the equivalent uniform dose. , 2002, International journal of radiation oncology, biology, physics.

[24]  F Foppiano,et al.  Fitting late rectal bleeding data using different NTCP models: results from an Italian multi-centric study (AIROPROS0101). , 2004, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[25]  U Oelfke,et al.  Simulation and visualization of dose uncertainties due to interfractional organ motion. , 2006, Physics in medicine and biology.

[26]  J. Lebesque,et al.  The simultaneous boost technique: the concept of relative normalized total dose. , 1991, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[27]  A. Garden,et al.  Anisotropic margin expansions in 6 anatomic directions for oropharyngeal image guided radiation therapy. , 2013, International journal of radiation oncology, biology, physics.

[28]  Steve B. Jiang,et al.  Effects of intra-fraction motion on IMRT dose delivery: statistical analysis and simulation. , 2002, Physics in medicine and biology.

[29]  J. Siebers,et al.  Coverage-based treatment planning to accommodate delineation uncertainties in prostate cancer treatment. , 2015, Medical physics.

[30]  M. V. van Herk,et al.  Prostate gland motion assessed with cine-magnetic resonance imaging (cine-MRI). , 2005, International journal of radiation oncology, biology, physics.

[31]  Joos V Lebesque,et al.  Inclusion of geometric uncertainties in treatment plan evaluation. , 2002, International journal of radiation oncology, biology, physics.

[32]  Steve B. Jiang,et al.  Effects of motion on the total dose distribution. , 2004, Seminars in radiation oncology.

[33]  Individualized margins for prostate patients using a wireless localization and tracking system , 2011, Journal of applied clinical medical physics.

[34]  Dr. P. Madhan Kumar.  3. Special Considerations regarding Absorbed-Dose and Dose–Volume Prescribing and Reporting in IMRT , 2010, Journal of the ICRU.

[35]  N. Ferris,et al.  Seminal vesicle intrafraction motion analysed with cinematic magnetic resonance imaging , 2014, Radiation oncology.

[36]  J. Battista,et al.  Limitations of a convolution method for modeling geometric uncertainties in radiation therapy. I. The effect of shift invariance. , 2003, Medical physics.

[37]  Steve B. Jiang,et al.  Temporo-spatial IMRT optimization: concepts, implementation and initial results , 2005, Physics in medicine and biology.