What is an acceptably smoothed fluence? Dosimetric and delivery considerations for dynamic sliding window IMRT

BackgroundThe study summarised in this report aimed to investigate the interplay between fluence complexity, dose calculation algorithms, dose calculation spatial resolution and delivery characteristics (monitor units, effective field width and dose delivery against dose prediction agreement) was investigated. A sample set of complex planning cases was selected and tested using a commercial treatment planning system capable of inverse optimisation and equipped with tools to tune fluence smoothness.MethodsA set of increasingly smoothed fluence patterns was correlated to a generalised expression of the Modulation Index (MI) concept, in nature independent from the specific planning system used that could therefore be recommended as a predictor to score fluence "quality" at a very early stage of the IMRT QA process. Fluence complexity was also correlated to delivery accuracy and characteristics in terms of number of MU, dynamic window width and agreement between calculation and measurement (expressed as percentage of field area with a γ > 1 (%FA)) when comparing calculated vs. delivered modulated dose maps. Different resolutions of the calculation grid and different photon dose algorithms (pencil beam and anisotropic analytical algorithm) were used for the investigations.Results and Conclusioni) MI can be used as a reliable parameter to test different approaches/algorithms to smooth fluences implemented in a TPS, and to identify the preferable default values for the smoothing parameters if appropriate tools are implemented; ii) a MI threshold set at MI < 19 could ensure that the planned beams are safely and accurately delivered within stringent quality criteria; iii) a reduction in fluence complexity is strictly correlated to a corresponding reduction in MUs, as well as to a decrease of the average sliding window width (for dynamic IMRT delivery); iv) a smoother fluence results in a reduction of dose in the healthy tissue with a potentially relevant clinical benefit; v) increasing the smoothing parameter s, MI decreases with %FA: fluence complexity has a significant impact on the accuracy of delivery and the agreement between calculation and measurements improves with the advanced algorithms.

[1]  S Webb,et al.  Use of a quantitative index of beam modulation to characterize dose conformality: illustration by a comparison of full beamlet IMRT, few-segment IMRT (fsIMRT) and conformal unmodulated radiotherapy. , 2003, Physics in medicine and biology.

[2]  R Mohan,et al.  The impact of fluctuations in intensity patterns on the number of monitor units and the quality and accuracy of intensity modulated radiotherapy. , 2000, Medical physics.

[3]  S. Spirou,et al.  Generation of arbitrary intensity profiles by dynamic jaws or multileaf collimators. , 1994, Medical physics.

[4]  C C Ling,et al.  Delivery of intensity-modulated radiation therapy with a conventional multileaf collimator: comparison of dynamic and segmental methods. , 2001, Medical physics.

[5]  S Webb,et al.  An optimization algorithm that incorporates IMRT delivery constraints. , 2002, Physics in medicine and biology.

[6]  Nesrin Dogan,et al.  Assessment of different IMRT boost delivery methods on target coverage and normal-tissue sparing. , 2003, International journal of radiation oncology, biology, physics.

[7]  D. Convery,et al.  The generation of intensity-modulated fields for conformal radiotherapy by dynamic collimation , 1992 .

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

[9]  S. Webb.  The physical basis of IMRT and inverse planning. , 2003, The British journal of radiology.

[10]  M Goitein,et al.  Intensity modulated therapy and inhomogeneous dose to the tumor: a note of caution. , 1996, International journal of radiation oncology, biology, physics.

[11]  P. Teo,et al.  Intensity-modulated radiotherapy in nasopharyngeal carcinoma: dosimetric advantage over conventional plans and feasibility of dose escalation. , 2003, International journal of radiation oncology, biology, physics.

[12]  Sebastiaan Breedveld,et al.  Fast, multiple optimizations of quadratic dose objective functions in IMRT , 2006, Physics in medicine and biology.

[13]  B. Emami,et al.  Assessment of different methods of boost delivery (IMRT vs. 3-D conformal) on target coverage and normal tissue sparing , 2001 .

[14]  Luca Cozzi,et al.  IMRT with the sliding window: comparison of the static and dynamic methods. Dosimetric and spectral analysis. , 2005, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[15]  Lijun Ma,et al.  Smoothing intensity-modulated treatment delivery under hardware constraints. , 2002, Medical physics.

[16]  Application of the inverse Monte Carlo treatment planning system IKO for an inhomogeneous dose prescription in the sense of dose painting. , 2006, Zeitschrift fur medizinische Physik.

[17]  D. Low,et al.  A technique for the quantitative evaluation of dose distributions. , 1998, Medical physics.

[18]  M. Langer,et al.  Improved leaf sequencing reduces segments or monitor units needed to deliver IMRT using multileaf collimators. , 2001, Medical physics.

[19]  F. Lohr,et al.  Comparison of intensity-modulated radiotherapy with conventional conformal radiotherapy for complex-shaped tumors. , 2000, International journal of radiation oncology, biology, physics.

[20]  Radhe Mohan,et al.  Incorporating multi-leaf collimator leaf sequencing into iterative IMRT optimization. , 2002, Medical physics.

[21]  S. Spirou,et al.  Dose calculation for photon beams with intensity modulation generated by dynamic jaw or multileaf collimations. , 1994, Medical physics.

[22]  Alessandra Bolsi,et al.  Comparative analysis of intensity modulation inverse planning modules of three commercial treatment planning systems applied to head and neck tumour model. , 2003, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[23]  Benedick A Fraass,et al.  Reduction of IMRT beam complexity through the use of beam modulation penalties in the objective function. , 2007, Medical physics.

[24]  Dietrich Harder,et al.  Applications of a Triple Gaussian Pencil Beam Model for Photon Beam Treatment Planning , 1996 .

[25]  E. Hall,et al.  Radiation-induced second cancers: the impact of 3D-CRT and IMRT. , 2003, International journal of radiation oncology, biology, physics.

[26]  S. Spirou,et al.  A gradient inverse planning algorithm with dose-volume constraints. , 1998, Medical physics.

[27]  Benedick A Fraass,et al.  Improving IMRT delivery efficiency using intensity limits during inverse planning. , 2005, Medical physics.

[28]  Dietrich Harder,et al.  A Triple Gaussian Pencil beam Model for Photon beam Treatment Planning , 1995 .

[29]  Ping Xia,et al.  A new smoothing procedure to reduce delivery segments for static MLC-based IMRT planning. , 2004, Medical physics.

[30]  L Xing,et al.  Minimizing delivery time and monitor units in static IMRT by leaf-sequencing. , 2002, Physics in medicine and biology.

[31]  J Yang,et al.  Smoothing intensity-modulated beam profiles to improve the efficiency of delivery. , 2001, Medical physics.

[32]  Luca Cozzi,et al.  GLAaS: an absolute dose calibration algorithm for an amorphous silicon portal imager. Applications to IMRT verifications. , 2006, Medical physics.

[33]  Luca Cozzi,et al.  Comparison of dose calculation algorithms for treatment planning in external photon beam therapy for clinical situations , 2006, Physics in medicine and biology.

[34]  M. Goitein.  The cell's-eye view: assessing dose in four dimensions. , 2005, International journal of radiation oncology, biology, physics.

[35]  S Webb,et al.  A simple method to control aspects of fluence modulation in IMRT planning. , 2001, Physics in medicine and biology.

[36]  W. Ulmer,et al.  The inverse problem of a Gaussian convolution and its application to the finite size of the measurement chambers/detectors in photon and proton dosimetry. , 2003, Physics in medicine and biology.