Improving IMRT delivery efficiency using intensity limits during inverse planning.
Inverse planned intensity modulated radiotherapy (IMRT) fields can be highly modulated due to the large number of degrees of freedom involved in the inverse planning process. Additional modulation typically results in a more optimal plan, although the clinical rewards may be small or offset by additional delivery complexity and/or increased dose from transmission and leakage. Increasing modulation decreases delivery efficiency, and may lead to plans that are more sensitive to geometrical uncertainties. The purpose of this work is to assess the use of maximum intensity limits in inverse IMRT planning as a simple way to increase delivery efficiency without significantly affecting plan quality. Nine clinical cases (three each for brain, prostate, and head/neck) were used to evaluate advantages and disadvantages of limiting maximum intensity to increase delivery efficiency. IMRT plans were generated using in-house protocol-based constraints and objectives for the brain and head/neck, and RTOG 9406 dose volume objectives in the prostate. Each case was optimized at a series of maximum intensity ratios (the product of the maximum intensity and the number of beams divided by the prescribed dose to the target volume), and evaluated in terms of clinical metrics, dose-volume histograms, monitor units (MU) required per fraction (SMLC and DMLC delivery), and intensity map variation (a measure of the beam modulation). In each site tested, it was possible to reduce total monitor units by constraining the maximum allowed intensity without compromising the clinical acceptability of the plan. Monitor unit reductions up to 38% were observed for SMLC delivery, while reductions up to 29% were achieved for DMLC delivery. In general, complicated geometries saw a smaller reduction in monitor units for both delivery types, although DMLC delivery required significantly more monitor units in all cases. Constraining the maximum intensity in an inverse IMRT plan is a simple way to improve delivery efficiency without compromising plan objectives.
Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan 48109, USA. mcoselmo@med.umich.edu
Martha M
MM
Coselmon
Jean M
JM
Moran
Jeffrey D
JD
Radawski
Benedick A
BA
Fraass
D001822:Body Burden; D003198:Computer Simulation; D004307:Dose-Response Relationship, Radiation; D006801:Humans; D008954:Models, Biological; D009369:Neoplasms / Q000532:radiotherapy*; D011832:Radiation Injuries / Q000517:prevention & control; D011874:Radiometry / Q000379:methods*; D011879:Radiotherapy Dosage; D011880:Radiotherapy Planning, Computer-Assisted / Q000379:methods*; D020266:Radiotherapy, Conformal / Q000009:adverse effects / Q000379:methods*; D012062:Relative Biological Effectiveness; D018570:Risk Assessment / Q000379:methods*; D012307:Risk Factors; D016896:Treatment Outcome