Lattice position optimization for LATTICE therapy

A novel treatment planning method via scissor beams for uniform-target-dose proton GRID with peak-valley-dose-ratio optimization

BACKGROUND

Proton spatially fractionated RT (SFRT) can potentially synergize the unique advantages of using proton Bragg peak and SFRT peak-valley dose ratio (PVDR) to reduce the radiation-induced damage for normal tissues. Uniform-target-dose (UTD) proton GRID is a proton SFRT modality that can be clinically desirable and conveniently adopted since its UTD resembles target dose distribution in conventional proton RT (CONV). However, UTD proton GRID is not used clinically, which is likely due to the lack of an effective treatment planning method.

PURPOSE

This work will develop a novel treatment planning method using scissor beams (SB) for UTD proton GRID, with the joint optimization of PVDR and dose objectives.

METHODS

The SB method for spatial dose modulation in normal tissues with UTD has two steps: (1) a primary beam (PB) is halved with interleaved beamlets, to generate spatial dose modulation in normal tissues; (2) a complementary beam (CB) is added to fill in previously valley-dose positions in the target to generate UTD, while the CB is angled slightly from the PB, to maintain spatial dose modulation in normal tissues. A treatment planning method with PVDR optimization via the joint total variation and L1 (TVL1) regularization is developed to jointly optimize PVDR and dose objectives. The plan optimization solution is obtained using an iterative convex relaxation algorithm.

RESULTS

The new methods SB and SB-TVL1 were validated in comparison with CONV. Compared to CONV of relatively homogeneous dose distribution, SB had modulated spatial dose pattern in normal tissues with UTD and comparable plan quality. Compared to SB, SB-TVL1 further maximized PVDR, with comparable dose-volume parameters.

CONCLUSIONS

A novel SB method is proposed that can generate modulated spatial dose pattern in normal tissues to achieve UTD proton GRID. A treatment planning method with PVDR optimization capability via TVL1 regularization is developed that can jointly optimize PVDR and dose objectives for proton GRID.

Simultaneous dose and dose rate optimization via dose modifying factor modeling for FLASH effective dose

BACKGROUND

Although the FLASH radiotherapy (FLASH) can improve the sparing of organs-at-risk (OAR) via the FLASH effect, it is generally a tradeoff between the physical dose coverage and the biological FLASH coverage, for which the concept of FLASH effective dose (FED) is needed to quantify the net improvement of FLASH, compared to the conventional radiotherapy (CONV).

PURPOSE

This work will develop the first-of-its-kind treatment planning method called simultaneous dose and dose rate optimization via dose modifying factor modeling (SDDRO-DMF) for proton FLASH that directly optimizes FED.

METHODS

SDDRO-DMF models and optimizes FED using FLASH dose modifying factor (DMF) models, which can be classified into two categories: (1) the phenomenological model of the FLASH effect, such as the FLASH effectiveness model (FEM); (2) the mechanistic model of the FLASH radiobiology, such as the radiolytic oxygen depletion (ROD) model. The general framework of SDDRO-DMF will be developed, with specific DMF models using FEM and ROD, as a demonstration of general applicability of SDDRO-DMF for proton FLASH via transmission beams (TB) or Bragg peaks (BP) with single-field or multi-field irradiation. The FLASH dose rate is modeled as pencil beam scanning dose rate. The solution algorithm for solving the inverse optimization problem of SDDRO-DMF is based on iterative convex relaxation method.

RESULTS

SDDRO-DMF is validated in comparison with IMPT and a state-of-the-art method called SDDRO, with demonstrated efficacy and improvement for reducing the high dose and the high-dose volume for OAR in terms of FED. For example, in a SBRT lung case of the dose-limiting factor that the max dose of brachial plexus should be no more than 26 Gy, only SDDRO-DMF met this max dose constraint; moreover, SDDRO-DMF completely eliminated the high-dose (V70%) volume to zero for CTV10mm (a high-dose region as a 10 mm ring expansion of CTV).

CONCLUSION

We have proposed a new proton FLASH optimization method called SDDRO-DMF that directly optimizes FED using phenomenological or mechanistic models of DMF, and have demonstrated the efficacy of SDDO-DMF in reducing the high-dose volume or/and the high-dose value for OAR, compared to IMPT and a state-of-the-art method SDDRO.

Biological optimization for hybrid proton-photon radiotherapy

Objective.Hybrid proton-photon radiotherapy (RT) is a cancer treatment option to broaden access to proton RT. Additionally, with a refined treatment planning method, hybrid RT has the potential to offer superior plan quality compared to proton-only or photon-only RT, particularly in terms of target coverage and sparing organs-at-risk (OARs), when considering robustness to setup and range uncertainties. However, there is a concern regarding the underestimation of the biological effect of protons on OARs, especially those in close proximity to targets. This study seeks to develop a hybrid treatment planning method with biological dose optimization, suitable for clinical implementation on existing proton and photon machines, with each photon or proton treatment fraction delivering a uniform target dose.Approach.The proposed hybrid biological dose optimization method optimized proton and photon plan variables, along with the number of fractions for each modality, minimizing biological dose to the OARs and surrounding normal tissues. To mitigate underestimation of hot biological dose spots, proton biological dose was minimized within a ring structure surrounding the target. Hybrid plans were designed to be deliverable separately and robustly on existing proton and photon machines, with enforced uniform target dose constraints for the proton and photon fraction doses. A probabilistic formulation was utilized for robust optimization of setup and range uncertainties for protons and photons. The nonconvex optimization problem, arising from minimum monitor unit constraint and dose-volume histogram constraints, was solved using an iterative convex relaxation method.Main results.Hybrid planning with biological dose optimization effectively eliminated hot spots of biological dose, particularly in normal tissues surrounding the target, outperforming proton-only planning. It also provided superior overall plan quality and OAR sparing compared to proton-only or photon-only planning strategies.Significance.This study presents a novel hybrid biological treatment planning method capable of generating plans with reduced biological hot spots, superior plan quality to proton-only or photon-only plans, and clinical deliverability on existing proton and photon machines, separately and robustly.

Computational Approach for Spatially Fractionated Radiation Therapy (SFRT) and Immunological Response in Precision Radiation Therapy

The field of precision radiation therapy has seen remarkable advancements in both experimental and computational methods. Recent literature has introduced various approaches such as Spatially Fractionated Radiation Therapy (SFRT). This unconventional treatment, demanding high-precision radiotherapy, has shown promising clinical outcomes. A comprehensive computational scheme for SFRT, extrapolated from a case report, is proposed. This framework exhibits exceptional flexibility, accommodating diverse initial conditions (shape, inhomogeneity, etc.) and enabling specific choices for sub-volume selection with administrated higher radiation doses. The approach integrates the standard linear quadratic model and, significantly, considers the activation of the immune system due to radiotherapy. This activation enhances the immune response in comparison to the untreated case. We delve into the distinct roles of the native immune system, immune activation by radiation, and post-radiotherapy immunotherapy, discussing their implications for either complete recovery or disease regrowth.

Assessing dosimetric advancements in spatially fractionated radiotherapy: From grids to lattices

Spatially fractionated radiotherapy (SFRT) techniques have undergone transformative evolution, encompassing physical GRID therapy, MLC-based grids, virtual TOMO GRIDs, and 3-dimensional high-dose lattices. Historical roots trace back to Alban Köhler's pioneering Spatially fractionated grid therapy (SFGRT), utilizing physical grids for dose modulation. Technological innovations introduced multi-leaf collimators (MLCs), enabling adaptable spatial fractionation and a shift to the broader term "SFRT." Physics and dosimetry-based studies have demonstrated the feasibility of computerized treatment planning and identified the potential to minimize the peripheral dose while using such high-dose therapy. Meanwhile, 3-dimensional high-dose lattices showed enhanced precision. The meticulous placement of high-dose volumetric spheres enables a reduction in the volume of high-dose spills. Advancements in 3-dimensional lattices through intensity-modulated radiotherapy and volumetric modulated arc therapy (VMAT) techniques offer enhanced therapeutic options. A database of SFRT studies identified 723 articles. This review shows the trajectory of SFRT from traditional grids to MLC-based approaches, virtual TOMO GRIDs, and innovative 3-dimensional lattices. Technological innovations, dosimetric advancements, and clinical feasibility have underscored the continual progress in refining spatially fractionated radiotherapy. The integration of MLCs and lattice techniques has demonstrated improved therapeutic outcomes, solidifying their relevance in modern radiation therapy protocols. Research has yet to reveal a clear correlation between treatment outcomes and dosimetric parameters. Additional investigations are necessary to assess the impact of various dosimetric parameters, such as EUD, peak-to-valley ratio (PVDR), D5%, D10%, D20%, D90%, etc., on the effectiveness of treatments.

Script-based implementation of automatic grid placement for lattice stereotactic body radiation therapy

Background and purpose

Spatially fractionated radiation therapy (SFRT) has demonstrated promising clinical response in treating large tumors with heterogeneous dose distributions. Lattice stereotactic body radiation therapy (SBRT) is an SFRT technique that leverages inverse optimization to precisely localize regions of high and lose dose within disease. The aim of this study was to evaluate an automated heuristic approach to sphere placement in lattice SBRT treatment planning.

Materials and methods

A script-based algorithm for sphere placement in lattice SBRT based on rules described by protocol was implemented within a treatment planning system. The script was applied to 22 treated cases and sphere distributions were compared with manually placed spheres in terms of number of spheres, number of protocol violations, and time required to place spheres. All cases were re-planned using script-generated spheres and plan quality was compared with clinical plans.

Results

The mean number of spheres placed excluding those that violate rules was greater using the script (13.8) than that obtained by either dosimetrist (10.8 and 12.0, p < 0.001 and p = 0.003) or physicist (12.7, p = 0.061). The mean time required to generate spheres was significantly less using the script (2.5 min) compared to manual placement by dosimetrists (25.0 and 29.9 min) and physicist (19.3 min). Plan quality indices were similar in all cases with no significant differences, and OAR constraints remained met on all plans except two.

Conclusion

A script placed spheres for lattice SBRT according to institutional protocol rules. The script-produced placement was superior to that of manually-specified spheres, as characterized by sphere number and rule violations.