Feasibility of function-guided lung treatment planning with parametric response mapping.

PURPOSE: Recent advancements in functional lung imaging have been developed to improve clinicians' knowledge of patient pulmonary condition prior to treatment. Ultimately, it may be possible to employ these functional imaging modalities to tailor radiation treatment plans to optimize patient outcome and mitigate pulmonary complications. Parametric response mapping (PRM) is a computed tomography (CT)-based functional lung imaging method that utilizes a voxel-wise image analysis technique to classify lung abnormality phenotypes, and has previously been shown to be effective at assessing lung complication risk in diagnostic applications. The purpose of this work was to demonstrate the implementation of PRM guidance in radiotherapy treatment planning. METHODS AND MATERIALS: A retrospective study was performed with 18 lung cancer patients to test the incorporation of PRM into a radiotherapy planning workflow. Paired inspiration/expiration pretreatment CT scans were acquired and PRM analysis was utilized to classify each voxel as normal, parenchymal disease, small airway disease, and emphysema. Density maps were generated for each PRM classification to contour high density regions of pulmonary abnormalities. Conventional volumetric-modulated arc therapy and PRM-guided treatment plans were designed for each patient. RESULTS: PRM guidance was successfully implemented into the treatment planning process. The inclusion of PRM priorities resulted in statistically significant (p < 0.05) improvements to the V20Gy within the PRM avoidance contours. On average, reductions of 5.4% in the V20Gy(%) were found. The PRM-guided treatment plans did not significantly increase the dose to the organs at risk or result in insufficient planning target volume coverage, but did increase plan complexity. CONCLUSIONS: PRM guidance was successfully implemented into a treatment planning workflow and shown to be effective for dose redistribution within the lung. This work has provided a framework for the potential clinical implementation of PRM-guided treatment planning.

Evaluation of a commercial deformable image registration algorithm for dual-energy CT processing.

PURPOSE: Several dual-energy computed tomography (DECT) techniques require a deformable image registration to correct for motion between the acquisition of low and high energy data. However, current DECT software does not provide tools to assess registration accuracy or allow the user to export deformed images, presenting a unique challenge for image registration quality assurance (QA). This work presents a methodology to evaluate the accuracy of DECT deformable registration and to quantify the impact of registration errors on end-product images. METHODS: The deformable algorithm implemented in Siemen Healthineers's Syngo was evaluated using a deformable abdomen phantom and a rigid phantom to mimic sliding motion in the thorax. Both phantoms were imaged using sequential 80 and 140 kVp scans with motion applied between the two scans. Since Syngo does not allow the export of the deformed images, this study focused on quantifying the accuracy of various end-product, dual-energy images resulting from processing of deformed images. RESULTS: The Syngo algorithm performed well for the abdomen phantom with a mean registration error of 0.4 mm for landmark analysis, Dice similarity coefficients (DSCs) > 0.90 for five organs contoured, and mean iodine concentrations within 0.2 mg/mL of values measured on static images. For rigid sliding motion, the algorithm performed poorer and resulted in noticeable registration errors toward the superior and inferior scan extents and DSCs as low as 0.41 for iodine rods imaged in the phantom. Additionally, local iodine concentration errors in areas of misregistration exceeded 3 mg/mL. CONCLUSIONS: This work represents the first methodology for DECT image registration QA using commercial software. Our data support the clinical use of the Syngo algorithm for abdominal sites with limited motion (i.e., pancreas and liver). However, dual-energy images generated with this algorithm should be used with caution for quantitative measurements in areas with sliding motion.

Deformable abdominal phantom for the validation of real-time image guidance and deformable dose accumulation.

PURPOSE: End-to-end testing with quality assurance (QA) phantoms for deformable dose accumulation and real-time image-guided radiotherapy (IGRT) has recently been recommended by American Association of Physicists in Medicine (AAPM) Task Groups 132 and 76. The goal of this work was to develop a deformable abdominal phantom containing a deformable three-dimensional dosimeter that could provide robust testing of these systems. METHODS: The deformable abdominal phantom was fabricated from polyvinyl chloride plastisol and phantom motion was simulated with a programmable motion stage and plunger. A deformable normoxic polyacrylamide gel (nPAG) dosimeter was incorporated into the phantom apparatus to represent a liver tumor. Dosimeter data were acquired using magnetic resonance imaging (MRI). Static measurements were compared to planned dose distributions. Static and dynamic deformations were used to simulate inter- and intrafractional motion in the phantom and measurements were compared to baseline measurements. RESULTS: The statically irradiated dosimeters matched the planned dose distribution with an average γ pass rates of 97.0 ± 0.5% and 97.5 ± 0.2% for 3%/5 mm and 5%/5 mm criteria, respectively. Static deformations caused measured dose distribution shifts toward the phantom plunger. During the dynamic deformation experiment, the dosimeter that utilized beam gating showed an improvement in the γ pass rate compared to the dosimeter that did not. CONCLUSIONS: A deformable abdominal phantom apparatus which incorporates a deformable nPAG dosimeter was developed to test real-time IGRT systems and deformable dose accumulation algorithms. This apparatus was used to benchmark simple static irradiations in which it was found that measurements match well to the planned distributions. Deformable dose accumulation could be tested by directly measuring the shifts and blurring of the target dose due to interfractional organ deformation and motion. Dosimetric improvements were achieved from the motion management during intrafractional motion.

Knowledge-Based Quality Assurance and Model Maintenance in Lung Cancer Radiation Therapy in a Statewide Quality Consortium of Academic and Community Practice Centers.

PURPOSE: Locally advanced lung cancer (LALC) treatment planning is often complex due to challenging tradeoffs related to large targets near organs at risk, making the judgment of plan quality difficult. The purpose of this work was to update and maintain a multi-institutional knowledge-based planning (KBP) model developed by a statewide consortium of academic and community practices for use as a plan quality assurance (QA) tool. METHODS AND MATERIALS: Sixty LALC volumetric-modulated arc therapy plans from 2021 were collected from 24 institutions. Plan quality was scored, with high-quality clinical (HQC) plans selected to update a KBP model originally developed in 2017. The model was validated via automated KBP planning, with 20 cases excluded from the model. Differences in dose-volume histogram metrics in the clinical plans, 2017 KBP model plans, and 2022 KBP model plans were compared. Twenty recent clinical cases not meeting consortium quality metrics were replanned with the 2022 model to investigate potential plan quality improvements. RESULTS: Forty-seven plans were included in the final KBP model. Compared with the clinical plans, the 2022 model validation plans improved 60%, 65%, and 65% of the lung V20Gy, mean heart dose, and spinal canal D0.03cc metrics, respectively. The 2022 model showed improvements from the 2017 model in hot spot management at the cost of greater lung doses. Of the 20 recent cases not meeting quality metrics, 40% of the KBP model-replanned cases resulted in acceptable plans, suggesting potential clinical plan improvements. CONCLUSIONS: A multi-institutional KBP model was updated using plans from a statewide consortium. Multidisciplinary plan review resulted in HQC model training plans and model validation resulted in acceptable quality plans. The model proved to be effective at identifying potential plan quality improvements. Work is ongoing to develop web-based training plan review tools and vendor-agnostic platforms to provide the model as a QA tool statewide.

Direct incorporation of patient-specific efficacy and toxicity estimates in radiation therapy plan optimization.

PURPOSE: Current radiation therapy (RT) treatment planning relies mainly on pre-defined dose-based objectives and constraints to develop plans that aim to control disease while limiting damage to normal tissues during treatment. These objectives and constraints are generally population-based, in that they are developed from the aggregate response of a broad patient population to radiation. However, correlations of new biologic markers and patient-specific factors to treatment efficacy and toxicity provide the opportunity to further stratify patient populations and develop a more individualized approach to RT planning. We introduce a novel intensity-modulated radiation therapy (IMRT) optimization strategy that directly incorporates patient-specific dose response models into the planning process. In this strategy, we integrate the concept of utility-based planning where the optimization objective is to maximize the predicted value of overall treatment utility, defined by the probability of efficacy (e.g., local control) minus the weighted sum of toxicity probabilities. To demonstrate the feasibility of the approach, we apply the strategy to treatment planning for non-small cell lung cancer (NSCLC) patients. METHODS AND MATERIALS: We developed a prioritized approach to patient-specific IMRT planning. Using a commercial treatment planning system (TPS), we calculate dose based on an influence matrix of beamlet-dose contributions to regions-of-interest. Then, outside of the TPS, we hierarchically solve two optimization problems to generate optimal beamlet weights that can then be imported back to the TPS. The first optimization problem maximizes a patient's overall plan utility subject to typical clinical dose constraints. In this process, we facilitate direct optimization of efficacy and toxicity trade-off based on individualized dose-response models. After optimal utility is determined, we solve a secondary optimization problem that minimizes a conventional dose-based objective subject to the same clinical dose constraints as the first stage but with the addition of a constraint to maintain the optimal utility from the first optimization solution. We tested this method by retrospectively generating plans for five previously treated NSCLC patients and comparing the prioritized utility plans to conventional plans optimized with only dose metric objectives. To define a plan utility function for each patient, we utilized previously published correlations of dose to local control and grade 3-5 toxicities that include patient age, stage, microRNA levels, and cytokine levels, among other clinical factors. RESULTS: The proposed optimization approach successfully generated RT plans for five NSCLC patients that improve overall plan utility based on personalized efficacy and toxicity models while accounting for clinical dose constraints. Prioritized utility plans demonstrated the largest average improvement in local control (16.6%) when compared to plans generated with conventional planning objectives. However, for some patients, the utility-based plans resulted in similar local control estimates with decreased estimated toxicity. CONCLUSION: The proposed optimization approach, where the maximization of a patient's RT plan utility is prioritized over the minimization of standardized dose metrics, has the potential to improve treatment outcomes by directly accounting for variability within a patient population. The implementation of the utility-based objective function offers an intuitive, humanized approach to biological optimization in which planning trade-offs are explicitly optimized.

3D dosimetric validation of ultrasound-guided radiotherapy with a dynamically deformable abdominal phantom.

OBJECTIVES: The purpose of this study was to dosimetrically benchmark gel dosimetry measurements in a dynamically deformable abdominal phantom for intrafraction image guidance through a multi-dosimeter comparison. Once benchmarked, the study aimed to perform a proof-of-principle study for validation measurements of an ultrasound image-guided radiotherapy delivery system. METHODS: The phantom was dosimetrically benchmarked by delivering a liver VMAT plan and measuring the 3D dose distribution with DEFGEL dosimeters. Measured doses were compared to the treatment planning system and measurements acquired with radiochromic film and an ion chamber. The ultrasound image guidance validation was performed for a hands-free ultrasound transducer for the tracking of liver motion during treatment. RESULTS: Gel dosimeters were compared to the TPS and film measurements, showing good qualitative dose distribution matches, low γ values through most of the high dose region, and average 3%/5 mm γ-analysis pass rates of 99.2%(0.8%) and 90.1%(0.8%), respectively. Gel dosimeter measurements matched ion chamber measurements within 3%. The image guidance validation study showed the measurement of the treatment delivery improvements due to the inclusion of the ultrasound image guidance system. Good qualitative matching of dose distributions and improvements of the γ-analysis results were observed for the ultrasound-gated dosimeter compared to the ungated dosimeter. CONCLUSIONS: DEFGEL dosimeters in phantom showed good agreement with the planned dose and other dosimeters for dosimetric benchmarking. Ultrasound image guidance validation measurements showed good proof-of-principle of the utility of the phantom system as a method of validating ultrasound-based image guidance systems and potentially other image guidance methods.

An improved abdominal phantom for intrafraction image guidance validation.

A dynamically compressible phantom of the human abdomen that simulates organ motion with breathing is being developed for possible testing of image-gated beam delivery in radiotherapy. The polyvinyl chloride plastisol (PVCP) phantom features a cavity that can contain a deformable normoxic polyacrylamide gel (nPAG) dosimeter that is intended for use with MRI to provide dosimetric data. The phantom has been improved by the inclusion of new components that are more realistic anatomically and exhibit CT values similar to those of the tissues they mimic. Component organs were made from 3D-printed molds developed from CT contours of a real patient and their radiodensities adjusted by varying the mass ratios of the PVCP hardener and softener during manufacture. To make the phantom more compatible with ultrasound imaging a graphite scatterer was mixed into some of the phantom components to produce a background speckle pattern. This provided contrast between the body and a moving anatomical target intended for motion tracking. Phantom insert motion magnitude and repeatibility was assessed using CT by imaging two phantom inserts, one containing fiducial markers and the other containing iodinated gelatin, at the same position after repeated cycles of deformation. The maximum motion of a phantom fiducial at the position of the phantom treatment target was found to be 12.2 mm. The phantom design resulted in dosimeter motion with a point-to-point repatability within 0.3 mm on average and contour repeatability resulting in Dice coefficients exceeding 0.98 on average.

Technical Note: Characterization of clinical linear accelerator triggering latency for motion management system development.

PURPOSE: Latencies for motion management systems have previously been presented as guidelines for system development and implementation. These guidelines consider the overall system latency, including data acquisition, algorithm processing, and linac triggering time. However, during system development, the triggering latency of the clinical linear accelerator is often considered fixed. This paper presents a method to decouple the linac-only triggering latency from the total system latency such that latency can be considered in terms of only the linac-independent aspects of the system. METHODS: The linac-only latency was investigated by considering the time at which a linac response was observed relative to the time at which a beam-on/off triggering signal was sent to the linac. The relative time between the two signals was analyzed using a multichannel oscilloscope with input signals from a custom gating box to manually trigger the beam state as well as a diode positioned at beam isocenter to monitor the linac response. The beam-on/off latency was measured at multiple energies (6/18 MV) and repetition rates (100-600 MU/min) to investigate beam setting dependencies. RESULTS: The measured latency was observed to be dependent on the accelerator settings for repetition rate and energy, with beam-on latencies decreasing with increasing repetition rate and decreasing energy. In contrast, the opposite trend was present for the observed beam-off latency. At 600 MU/min, beam-on/off latencies were observed to be 3.37/1.45 ms for a 6 MV beam and 6.02/0.73 ms for an 18 MV beam. Negative latencies were possible for beam-off measurements due to the mechanical latency being less than the pulse separation at given repetition rates. CONCLUSIONS: The linac latency associated with triggering the beam-on/off was determined to have a minor contribution to the total allowable system latency; thus, the majority of the total system latency can be attributed to linac-independent factors.