Moyed M. Miften

A dose-volume based tool for evaluating and ranking IMRT treatment plans

Advances in the fields of IMRT and functional imaging have greatly increased the prospect of escalating the dose to highly active or hypoxic tumour sub-volumes and steering the dose away from highly functional critical structure regions. However, current clinical treatment planning and evaluation tools assume homogeneous activity/function status in the tumour/critical structures. A method was developed to incorporate tumour/critical structure heterogeneous functionality in the generalized concept of equivalent uniform dose (EUD). The tumour and critical structures functional EUD (FEUD) values were calculated from the dose-function histogram (DFH), which relates dose to the fraction of total function value at that dose. The DFH incorporates flouro-deoxyglucose positron emission tomography (FDG-PET) functional data for tumour, which describes the distribution of metabolically active tumour clonogens, and single photon emission computed tomography (SPECT) perfusion data for critical structures. To demonstrate the utility of the method, the lung dose distributions of two non-small cell lung cancer patients, who received 3D conformal external beam radiotherapy treatment with curative intent, were evaluated. Differences between the calculated lungs EUD and FEUD values of up to 50% were observed in the 3D conformal plans. In addition, a non-small cell lung cancer patient was inversely planned with a target dose prescription of 76 Gy. Two IMRT plans (plan-A and plan-B) were generated for the patient based on the CT, FDG-PET and SPECT treatment planning images using dose-volume objective functions. The IMRT plans were generated with the goal of achieving more critical structures sparing in plan-B than plan-A. Results show the target volume EUD in plan-B is lower than plan-A by 5% with a value of 73.31 Gy, and the FEUD in plan-B is lower than plan-A by 2.6% with a value of 75.77 Gy. The FEUD plan-B values for heart and lungs were lower than plan-A by 22% and 18%, respectively. While EUD values show plan-A is marginally better than plan-B in terms of target volumetric coverage, the FEUD plan-B values show adequate target function coverage with significant critical structure function sparing. In conclusion, incorporating functional data in the calculation of EUD is important in evaluating the biological merit of treatment plans.

A steepest‐descent gradient algorithm is developed to optimize the stepping of aradiation source train (RST) for intravascular brachytherapy (IVB). The objective function is to deliver a uniform dose in a coronary target vessel and minimize the dose in adjacent normal vessel tissue at the proximal and distal edges of the coronary target vessel. Based on the target length and number of dwell points (number of steps), the algorithm modulates the dwell times and corresponding dwell positions that optimize the weighted addition of staggeredEGS4Monte Carlo (MC) calculated dose distribution from a single RST. Stepping treatment plans are generated for target vessel lengths of 3.0, 3.3, and 3.8 cm. For both the unoptimized and optimized plans, the dose heterogeneity in the target vessel wall, and length of nontarget vessel receivingis assessed to compare plans. Optimization results show a 14% dose uniformity within the target is achievable for all vessel lengths. Further, the dose in the adjacent normal tissue is lower in the optimized plans than the unoptimized plans. The work presented in this paper provides a model to address the finite length of RST in IVB treatments. While the results presented are specific to theRST, the methods should apply to other finite length RSTs.

Therapeutic treatment plan evaluation is often based on examining the radiotherapy treatment planning (RTP) system dose distributions in the target and surrounding normal structures. To study the effects of tissue inhomogeneities on photon dose distributions, we compared FOCUS RTP system dose distributions from the measurement‐based Clarkson and model‐based MultiGrid Superposition (MGS) algorithms with those from thebeamMonte Carlo code system in a set of heterogeneous phantoms. The phantom inhomogeneities mimic relevant clinical treatment sites, which include lung slab, lung‐bone slab, bone‐lung slab, mediastinum, and tumor geometries. The benchmark comparisons were performed in lung densities of 0.20 and, and a bone density offorandand 15‐MV photon beams. Benchmark comparison results show that the MGS model andbeamdoses match better than 3% or 3 mm, and the MGS model is more accurate than the Clarkson model in all phantoms. The MGS model, unlike the Clarkson model, predicts the build‐down and build‐up of dose near tissue interfaces and penumbra broadening in lung associated with high energy beams. The Clarkson model overestimates the dose in lung by a maximum of 10% compared tobeam. Dose comparisons suggest turning‐off the effective path length inhomogeneity correction in the Clarkson model for lung treatments.PACS number(s): 87.53.–j, 87.53.Bn