Transitioning from measurement-based to combined patient-specific quality assurance for intensity-modulated proton therapy

Development of a three-dimensional scintillation detector for pencil beam verification in proton therapy patient-specific quality assurance

BACKGROUND

Pencil Beam Scanning proton therapy has many advantages from a therapeutic point of view, but raises technical constraints in terms of treatment verification. The treatment relies on a large number of planned pencil beams (PB) (up to thousands), whose delivery is divided in several low-intensity pulses delivered a high frequency (1 kHz in this study).

PURPOSE

The purpose of this study was to develop a three-dimensional quality assurance system allowing to verify all the PBs' characteristics (position, energy, intensity in terms of delivered monitor unit-MU) of patient treatment plans on a pulse-by-pulse or a PB-by-PB basis.

METHODS

A system named SCICOPRO has been developed. It is based on a 10 × 10 × 10 cm3 scintillator cube and a fast camera, synchronized with beam delivery, recording two views (direct and using a mirror) of the scintillation distribution generated by the pulses. A specific calibration and analysis process allowed to extract the characteristics of all the pulses delivered during the treatment, and consequently of all the PBs. The system uncertainties, defined here as average value + standard deviation, were characterized with a customized irradiation plan at different PB intensities (0.02, 0.1, and 1 MU) and with two patient's treatment plans of three beams each. The system's ability to detect potential treatment delivery problems, such as positioning errors of the treatment table in this work (1° rotations and a 2 mm translation), was assessed by calculating the confidence intervals (CI) for the different characteristics and evaluating the proportion of PBs within these intervals.

RESULTS

The performances of SCICOPRO were evaluated on a pulse-by-pulse basis. They showed a very good signal-to-noise ratio for all the pulse intensities (between 2 × 10-3 MU and 150 × 10-3 MU) allowing uncertainties smaller than 580 µm for the position, 180 keV for the energy and 3% for the intensity on patients treatment plans. The position and energy uncertainties were found to be little dependent from the pulse intensities whereas the intensity uncertainty depends on the pulses number and intensity distribution. Finally, treatment plans evaluations showed that 98% of the PBs were within the CIs with a nominal positioning against 83% or less with the table positioning errors, thus proving the ability of SCICOPRO to detect this kind of errors.

CONCLUSION

The high acquisition rate and the very high sensitivity of the system developed in this work allowed to record pulses of intensities as low as 2 × 10-3 MU. SCICOPRO was thus able to measure all the characteristics of the spots of a treatment (position, energy, intensity) in a single measurement, making it possible to verify their compliance with the treatment plan. SCICOPRO thus proved to be a fast and accurate tool that would be useful for patient-specific quality assurance (PSQA) on a pulse-by-pulse or PB-by-PB verification basis.

Patient-specific quality assurance of dynamically-collimated proton therapy treatment plans

BACKGROUND

The dynamic collimation system (DCS) provides energy layer-specific collimation for pencil beam scanning (PBS) proton therapy using two pairs of orthogonal nickel trimmer blades. While excellent measurement-to-calculation agreement has been demonstrated for simple cube-shaped DCS-trimmed dose distributions, no comparison of measurement and dose calculation has been made for patient-specific treatment plans.

PURPOSE

To validate a patient-specific quality assurance (PSQA) process for DCS-trimmed PBS treatment plans and evaluate the agreement between measured and calculated dose distributions.

METHODS

Three intracranial patient cases were considered. Standard uncollimated PBS and DCS-collimated treatment plans were generated for each patient using the Astroid treatment planning system (TPS). Plans were recalculated in a water phantom and delivered at the Miami Cancer Institute (MCI) using an Ion Beam Applications (IBA) dedicated nozzle system and prototype DCS. Planar dose measurements were acquired at two depths within low-gradient regions of the target volume using an IBA MatriXX ion chamber array.

RESULTS

Measured and calculated dose distributions were compared using 2D gamma analysis with 3%/3 mm criteria and low dose threshold of 10% of the maximum dose. Median gamma pass rates across all plans and measurement depths were 99.0% (PBS) and 98.3% (DCS), with a minimum gamma pass rate of 88.5% (PBS) and 91.2% (DCS).

CONCLUSIONS

The PSQA process has been validated and experimentally verified for DCS-collimated PBS. Dosimetric agreement between the measured and calculated doses was demonstrated to be similar for DCS-collimated PBS to that achievable with noncollimated PBS.

Robustness and dosimetric verification of hippocampal-sparing craniospinal pencil beam scanning proton plans for pediatric medulloblastoma

Background and Purpose

Hippocampal-sparing (HS) is a method that can potentially reduce late cognitive complications for pediatric medulloblastoma (MB) patients treated with craniospinal proton therapy (PT). The aim of this study was to investigate robustness and dosimetric plan verification of pencil beam scanning HS PT.

Materials and Methods

HS and non-HS PT plans for the whole brain part of craniospinal treatment were created for 15 pediatric MB patients. A robust evaluation of the plans was performed. Plans were recalculated in a water phantom and measured field-by-field using an ion chamber detector at depths corresponding to the central part of hippocampi. All HS and non-HS fields were measured with the standard resolution of the detector and in addition 16 HS fields were measured with high resolution. Measured and planned dose distributions were compared using gamma evaluation.

Results

The median mean hippocampus dose was reduced from 22.9 Gy (RBE) to 8.9 Gy (RBE), while keeping CTV V95% above 95 % for all nominal HS plans. HS plans were relatively robust regarding hippocampus mean dose, however, less robust regarding target coverage and maximum dose compared to non-HS plans. For standard resolution measurements, median pass rates were 99.7 % for HS and 99.5 % for non-HS plans (p < 0.001). For high-resolution measurements, median pass rates were 100 % in the hippocampus region and 98.2 % in the surrounding region.

Conclusions

A substantial reduction of dose in the hippocampus region appeared feasible. Dosimetric accuracy of HS plans was comparable to non-HS plans and agreed well with planned dose distribution in the hippocampus region.

Deformed dose restoration to account for tumor deformation and position changes for adaptive proton therapy

BACKGROUND

Online adaptation during intensity-modulated proton therapy (IMPT) can minimize the effect of inter-fractional anatomical changes, but remains challenging because of the complex workflow. One approach for fast and automated online IMPT adaptation is dose restoration, which restores the initial dose distribution on the updated anatomy. However, this method may fail in cases where tumor deformation or position changes occur.

PURPOSE

To develop a fast and robust IMPT online adaptation method named "deformed dose restoration (DDR)" that can adjust for inter-fractional tumor deformation and position changes.

METHODS

The DDR method comprises two steps: (1) calculation of the deformed dose distribution, and (2) restoration of the deformed dose distribution. First, the deformable image registration (DIR) between the initial clinical target volume (CTV) and the new CTV were performed to calculate the vector field. To ensure robustness for setup and range uncertainty and the ability to restore the deformed dose distribution, an expanded CTV-based registration to maintain the dose gradient outside the CTV was developed. The deformed dose distribution was obtained by applying the vector field to the initial dose distribution. Then, the voxel-by-voxel dose difference optimization was performed to calculate beam parameters that restore the deformed dose distribution on the updated anatomy. The optimization function was the sum of total dose differences and dose differences of each field to restore the initial dose overlap of each field. This method only requires target contouring, which eliminates the need for organs at risk (OARs) contouring. Six clinical cases wherein the tumor deformation and/or position changed on repeated CTs were selected. DDR feasibility was evaluated by comparing the results with those from three other strategies, namely, not adapted (continuing the initial plan), adapted by previous dose restoration, and fully optimized.

RESULTS

In all cases, continuing the initial plan was largely distorted on the repeated CTs and the dose-volume histogram (DVH) metrics for the target were reduced due to the tumor deformation or position changes. On the other hand, DDR improved DVH metrics for the target to the same level as the initial dose distribution. Dose increase was seen for some OARs because tumor growth had reduced the relative distance between CTVs and OARs. Robustness evaluation for setup and range uncertainty (3 mm/3.5%) showed that deviation in DVH-bandwidth for CTV D_95% from the initial plan was 0.4% ± 0.5% (Mean ± S.D.) for DDR. The calculation time was 8.1 ± 6.4 min.

CONCLUSIONS

An online adaptation algorithm was developed that improved the treatment quality for inter-fractional anatomical changes and retained robustness for intra-fractional setup and range uncertainty. The main advantage of this method is that it only requires target contouring alone and saves the time for OARs contouring. The fast and robust adaptation method for tumor deformation and position changes described here can reduce the need for offline adaptation and improve treatment efficiency.

Flourish of Proton and Carbon Ion Radiotherapy in China

Proton and heavy ion therapy offer superior relative biological effectiveness (RBE) in the treatment of deep-seated tumors compared with conventional photon radiotherapy due to its Bragg-peak feature of energy deposition in organs. Many proton and carbon ion therapy centers are active all over the world. At present, five particle radiotherapy institutes have been built and are receiving patient in China, mainly including Wanjie Proton Therapy Center (WPTC), Shanghai Proton Heavy Ion Center (SPHIC), Heavy Ion Cancer Treatment Center (HIMM), Chang Gung Memorial Hospital (CGMH), and Ruijin Hospital affiliated with Jiao Tong University. Many cancer patients have benefited from ion therapy, showing unique advantages over surgery and chemotherapy. By the end of 2020, nearly 8,000 patients had been treated with proton, carbon ion or carbon ion combined with proton therapy. So far, there is no systemic review for proton and carbon ion therapy facility and clinical outcome in China. We reviewed the development of proton and heavy ion therapy, as well as providing the representative clinical data and future directions for particle therapy in China. It has important guiding significance for the design and construction of new particle therapy center and patients’ choice of treatment equipment.

A Review of the Robust Optimization Process and Advances with Monte Carlo in the Proton Therapy Management of Head and Neck Tumors

In intensity-modulated proton therapy, robust optimization processes have been developed to manage uncertainties associated with (1) range, (2) setup, (3) anatomic changes, (4) dose calculation, and (5) biological effects. Here we review our experience using a robust optimization technique that directly incorporates range and setup uncertainties into the optimization process to manage those sources of uncertainty. We also review procedures for implementing adaptive planning to manage the anatomic uncertainties. Finally, we share some early experiences regarding the impact of uncertainties in dose calculation and biological effects, along with techniques to manage and potentially reduce these uncertainties.