Implementation of a Knowledge-Based Treatment Planning Model for Cardiac-Sparing Lung Radiation Therapy

Harms, Joseph; Zhang, Jiahan; Kayode, Oluwatosin; Wolf, Jonathan; Tian, Sibo; McCall, Neal S.; Higgins, Kristin; Castillo, Richard; Yang, Xiaofeng

doi:10.1016/j.adro.2021.100745

Cited by 8 publications

(1 citation statement)

References 27 publications

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“…Our results first showed that creation of an Auto model from our manually optimised plans using 21 patient plans is feasible. Historically, the number of cases required to create an automated RapidPlan model varied, ranging from 20 to almost 200 (11,(19)(20)(21)(22)(23)(24), with number of cases likely at least partially dependent on the subsite being assessed. Ueda et al (20) suggested that only 20 cases might be enough to create a model if large variations existed in the (25).…”

Section: Discussionmentioning

confidence: 99%

Hippocampal avoidance whole brain radiotherapy: developing a RapidPlan model

Lo¹,

Estoesta²,

Mackonis³

et al. 2022

Ther Radiol Oncol

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Background: Hippocampal-avoidance whole brain radiotherapy (HA-WBRT) has emerged as an approach to retain intracranial tumour control while minimizing cognitive decline. However, the contouring and planning requirements are more complex and time consuming compared to standard WBRT. RapidPlan is an automated treatment planning software that is designed to increase planning efficiency whilst maintaining plan quality. Our group developed an automated HA-WBRT RapidPlan model (Auto) and compared it to a manually optimised standard template (Manual) to assess plan quality and planning efficiency.Methods: A Radiation Oncologist first contoured the hippocampi on 31 patient CT brain data sets fused with MRI with a brain planning target volume (PTV) minus hippocampal avoidance structure, optic chiasm, optic nerve, and lens structures also created. Manual standard template plans were created by an experienced radiation therapist for the first 21 patients with all plans needing to achieve Radiation Therapy Oncology Group (RTOG) 0933 protocol requirements prior to inclusion for creation of the automated RapidPlan model. This Auto model was then tested on a set of 10 separate patients and compared with a Manual plan.The dosimetric parameters and number of optimisations required to achieve protocol requirements were recorded for both.Results: Both the Auto and Manual plans achieved protocol requirements with Auto plans able to achieve these requirements on 1st optimisation for all 10 patients. In contrast, Manual plans were only able to produce acceptable plans in a single optimisation for 5 patients, with 4 patients requiring 2 optimisations and 1 patient requiring 3 optimisations. PTV coverage met RTOG recommendations for all plans but Auto plans were able to achieve lower doses to the organs at risk (OARs) compared to Manual plans, including significantly lower doses to the hippocampi. Independent dose calculation and patient specific dosimetry measurement had a greater than 99% pass rate.Conclusions: A department-created automated HA-WBRT RapidPlan model is feasible and allows for more efficient plan creation with significantly better hippocampal doses compared manually optimised plans and physics check confirming deliverability. Auto plans were able to be created with reduced planning time and resource utilization compared to manual plan creation, allowing for streamlining of workflow and reduced time to treatment for patients.

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Section: Discussionmentioning

confidence: 99%

Hippocampal avoidance whole brain radiotherapy: developing a RapidPlan model

Lo¹,

Estoesta²,

Mackonis³

et al. 2022

Ther Radiol Oncol

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Development and first implementation of a novel multi‐modality cardiac motion and dosimetry phantom for radiotherapy applications

Gregg,

Ruff,

Koenig

et al. 2024

Medical Physics

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BackgroundCardiac applications in radiation therapy are rapidly expanding including magnetic resonance guided radiation therapy (MRgRT) for real‐time gating for targeting and avoidance near the heart or treating ventricular tachycardia (VT).PurposeThis work describes the development and implementation of a novel multi‐modality and magnetic resonance (MR)‐compatible cardiac phantom.MethodsThe patient‐informed 3D model was derived from manual contouring of a contrast‐enhanced Coronary Computed Tomography Angiography scan, exported as a Stereolithography model, then post‐processed to simulate female heart with an average volume. The model was 3D‐printed using Elastic50A to provide MR contrast to water background. Two rigid acrylic modules containing cardiac structures were designed and assembled, retrofitting to an MR‐safe programmable motor to supply cardiac and respiratory motion in superior‐inferior directions. One module contained a cavity for an ion chamber (IC), and the other was equipped with multiple interchangeable cavities for plastic scintillation detectors (PSDs). Images were acquired on a 0.35 T MR‐linac for validation of phantom geometry, motion, and simulated online treatment planning and delivery. Three motion profiles were prescribed: patient‐derived cardiac (sine waveform, 4.3 mm peak‐to‐peak, 60 beats/min), respiratory (cos4 waveform, 30 mm peak‐to‐peak, 12 breaths/min), and a superposition of cardiac (sine waveform, 4 mm peak‐to‐peak, 70 beats/min) and respiratory (cos4 waveform, 24 mm peak‐to‐peak, 12 breaths/min). The amplitude of the motion profiles was evaluated from sagittal cine images at eight frames/s with a resolution of 2.4 mm × 2.4 mm. Gated dosimetry experiments were performed using the two module configurations for calculating dose relative to stationary. A CT‐based VT treatment plan was delivered twice under cone‐beam CT guidance and cumulative stationary doses to multi‐point PSDs were evaluated.ResultsNo artifacts were observed on any images acquired during phantom operation. Phantom excursions measured 49.3 ± 25.8%/66.9 ± 14.0%, 97.0 ± 2.2%/96.4 ± 1.7%, and 90.4 ± 4.8%/89.3 ± 3.5% of prescription for cardiac, respiratory, and cardio‐respiratory motion profiles for the 2‐chamber (PSD) and 12‐substructure (IC) phantom modules respectively. In the gated experiments, the cumulative dose was <2% from expected using the IC module. Real‐time dose measured for the PSDs at 10 Hz acquisition rate demonstrated the ability to detect the dosimetric consequences of cardiac, respiratory, and cardio‐respiratory motion when sampling of different locations during a single delivery, and the stability of our phantom dosimetric results over repeated cycles for the high dose and high gradient regions. For the VT delivery, high dose PSD was <1% from expected (5–6 cGy deviation of 5.9 Gy/fraction) and high gradient/low dose regions had deviations <3.6% (6.3 cGy less than expected 1.73 Gy/fraction).ConclusionsA novel multi‐modality modular heart phantom was designed, constructed, and used for gated radiotherapy experiments on a 0.35 T MR‐linac. Our phantom was capable of mimicking cardiac, cardio‐respiratory, and respiratory motion while performing dosimetric evaluations of gated procedures using IC and PSD configurations. Time‐resolved PSDs with small sensitive volumes appear promising for low‐amplitude/high‐frequency motion and multi‐point data acquisition for advanced dosimetric capabilities. Illustrating VT planning and delivery further expands our phantom to address the unmet needs of cardiac applications in radiotherapy.

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