Reducing MRI-guided radiotherapy planning and delivery times via efficient leaf sequencing and segment shape optimization algorithms

Abstract

Objective: Extended treatment session times are an operational limitation in magnetic resonance imaging guided adaptive radiotherapy (MRIgRT). In this study a novel leaf sequencing algorithm called optimal fluence levels (OFL) and an optimization algorithm called pseudo gradient descent (PGD) are evaluated with respect to plan quality, beam complexity, and the ability to reduce treatment session times on the Elekta Unity MRIgRT system. Approach: Ten total patients were evaluated on this Institutional Review Board approved study: three with prostate cancer, three with oligometastases, two with pancreatic cancer, and two with liver cancer. Plans were generated using the clinical Monaco Hyperion optimizer and leaf sequencer and then re-optimized using OFL and PGD (OFL+PGD) while holding all IMRT constraints and planning parameters constant. All plans were normalized to ensure 95% of the PTV received the prescription dose. A paired t-test was used to evaluate statistical significance. Main Results: Plan quality in terms of dosimetric OAR sparing was found to be equivalent between the OFL+PGD and conventional Monaco Hyperion optimizer plans. The OFL+PGD plans had a reduction in optimization time of 51.4% ± 5.0% (p = 0.002) and reduction in treatment delivery time of 10.6% ± 7.5% (p = 0.005). OFL+PGD generated plans had on average 13.2% ± 12.6% fewer multi-leaf collimator (MLC) segments (p = 0.009) and 0.1 ± 0.1 lower plan averaged beam modulation (PM) (p = 0.004) relative to the Monaco Hyperion plans. Significance: The OFL+PGD algorithms more quickly generate Unity treatment plans that are faster to deliver than with the conventional approach and without compromising dosimetric plan quality. This is likely due to a delivery complexity reduction enabled by OFL+PGD relative to the Monaco Hyperion plans.

A Technique to Enable Efficient Adaptive Radiation Therapy: Automated Contouring of Prostate and Adjacent Organs

“…Algorithms such as Deep LOGISMOS + JEI are expected to reduce one of the main operational challenges of MRIgART, which is the extended treatment session times compared with conventional cone beam computed tomography–based image guidance on traditional linear accelerators. 2 , 23 Contouring continues to be a time-consuming manual process, which is a major contributor to the treatment time and reduced patient throughput on MR linear accelerators. This work presents a more efficient and less user-intensive workflow which will increase throughput and may aid in accelerating the adoption of MRIgART in the broader radiation therapy community.…”

Intra-fraction motion of pelvic oligometastases and feasibility of PTV margin reduction using MRI guided adaptive radiotherapy

“…MRIgRT provides the ability to adapt for inter-fraction anatomical variations and thus may enable PTV margin reductions. However, MRIgRT also requires significantly longer treatment session times as compared to VMAT ( 34 ). MRIgRT treatment session times on the order of 60 minutes have been reported and these extended times lead to increased intra-fraction motion ( 28 , 37 , 39 ).…”

“…However, the application of baseline corrections can prevent such excursions and improve the GTV coverage as compared to treatments delivered without intra-fraction corrections. In the future, methods to reduce treatment session times such as more efficient contouring methods, faster dose optimization, and volumetric modulated arc therapy treatment deliveries are desirable as these will further reduce the number of intra-fraction adaptions needed ( 34 , 43 , 44 ).…”

“…The OARs and GTV were manually edited as needed. In the clinical setting, the Hyperion optimizer in the Monaco TPS was used to generate a fully adapted plan starting from fluence ( 34 ). Following the completion of the adapted plan, online quality assurance procedures were performed and MRI cine motion monitoring images were acquired throughout the duration of treatment ( 32 ).…”

ICRU REPORT 97: MRI-Guided Radiation Therapy Using MRI-Linear Accelerators

“…Simplified optimization methods such as segment weight optimization were found to achieve plan dosimetry comparable to the full-optimized plans with a significant reduction of optimization time, although full-optimization was still deemed necessary in some patients and fractions when large anatomic changes occurred (van Timmeren et al , 2021). Novel leaf sequencing and fluence optimization algorithms have been developed resulting in shorter optimization time and faster beam delivery without compromising dosimetric plan quality (Snyder et al , 2022). Artificial intelligence–based methods have been investigated to help generate high-quality base plans for MRI-guided ART for locally advanced pancreatic cancers (Bohoudi et al , 2017).…”