Inverse optimization of low-cost kilovoltage x-ray arc therapy plans

Category Primary study
JournalMedical Physics
Year 2018
Purpose: The objective of this work was to investigate the benefits of using inverse optimization treatment planning for kilovoltage arc therapy (KVAT) and to assess the dosimetric limitations of KVAT. Methods: Monte Carlo (MC) calculated, inversely optimized KVAT plans of spherical, idealized breast, lung, and prostate lesions were calculated using the EGSnrc/BEAMnrc and DOSXYZnrc MC codes. The dose delivered with the KVAT system, which generates 200–225 kV photon beamlets, was calculated and inversely optimized using an optimization framework developed at McGill University. KVAT dose distributions were compared with inversely optimized and MC generated megavoltage (MV) volumetric modulated arc therapy (VMAT) plans as a reference. Prescription doses delivered to 95% of the planning target volume (PTV) were 38.5 (10 fractions), 60 (30 fractions) and 73.8 (41 fractions) Gy for the breast, lung and prostate patients, respectively. Dose distributions, dose volume histograms, and PTV homogeneity indices were used to evaluate KVAT and VMAT plans based on RTOG protocols. Results: All organ-at-risk (OAR) doses were within prescribed dose limits for KVAT and VMAT plans. Generally, KVAT plans delivered higher doses to OARs. For example, due to the lower energy of KVAT, 50% of the rib volume received 12.9 Gy from KVAT while only receiving 2.5 Gy from VMAT. OAR doses were especially high for the KVAT prostate plan due to the presence of large volumes of bony anatomy, which illustrates a limitation of the KVAT system. The KVAT treatment times per fraction for the breast, lung and prostate patients were 2.8, 2.6 and 5.5 min, respectively. Conclusions: The inversely optimized KVAT plans presented in this work have demonstrated the ability of our novel low-cost, kilovoltage x-ray therapy system to safely treat deep-seated spherical lesions in breast and lung patients while meeting RTOG dose constraints on OARs.
Epistemonikos ID: 86ec58c304d8a9ff9acbb025674079eb5fa4af6c
First added on: Jun 14, 2024