Inverse 4D conformal planning for lung SBRT using particle swarm optimization. (1st August 2016)

• Record Type: Journal Article
• Authors: Modiri, A; Gu, X; Hagan, A; Bland, R; Iyengar, P; Timmerman, R; Sawant, A
• Is Part Of: Physics in medicine & biology. Volume 61:Number 16(2016:Aug.)
• Page Start: 6181
• Page End: 6202
• Publication Date: 2016-08-01
• Subjects: 4D treatment planning -- lung SBRT -- stochastic optimization; Biophysics -- Periodicals; Medical physics -- Periodicals; 610.153
• DOI: 10.1088/0031-9155/61/16/6181
• Languages: English
• ISSNs: 0031-9155

Abstract

Abstract: A critical aspect of highly potent regimens such as lung stereotactic body radiation therapy (SBRT) is to avoid collateral toxicity while achieving planning target volume (PTV) coverage. In this work, we describe four dimensional conformal radiotherapy using a highly parallelizable swarm intelligence-based stochastic optimization technique. Conventional lung CRT-SBRT uses a 4DCT to create an internal target volume and then, using forward-planning, generates a 3D conformal plan. In contrast, we investigate an inverse-planning strategy that uses 4DCT data to create a 4D conformal plan, which is optimized across the three spatial dimensions (3D) as well as time, as represented by the respiratory phase. The key idea is to use respiratory motion as an additional degree of freedom. We iteratively adjust fluence weights for all beam apertures across all respiratory phases considering OAR sparing, PTV coverage and delivery efficiency. To demonstrate proof-of-concept, five non-small-cell lung cancer SBRT patients were retrospectively studied. The 4D optimized plans achieved PTV coverage comparable to the corresponding clinically delivered plans while showing significantly superior OAR sparing ranging from 26% to 83% for D max heart, 10%–41% for D max esophagus, 31%–68% for D max spinal cord and 7%–32% for V 13 lung.