Spatially fractionated radiotherapy (SFRT) represents a radiation therapy technique that delivers high-dose radiation to generate distinct dose peaks and valleys within a tumor (1). This method effectively targets the gross tumor by creating physical dose contrast between high-dose and low-dose areas, thereby damaging and inhibiting tumor cells (2, 3). Specifically, it could have a therapeutic effect by directly targeting tumor cells in high-dose areas and impacting cells in adjacent low-dose regions.

This technique enables the escalation of radiation doses for large tumors, achieving significant treatment efficacy with minimal toxicity (4). The safety and effectiveness of SFRT have been corroborated by numerous clinical studies and further supported by radiobiological and immunological research findings (5–10). The effectiveness of SFRT is supported by several key radiobiological mechanisms, including the bystander effect (2, 10), which refers to the impact of radiation on non-irradiated cells nearby; vascular injury, which disrupts the tumor’s blood supply; and the stimulation of anti-cancer immune responses (8). These mechanisms collectively enhance the anti-tumor effects of SFRT, making it a potent treatment option for patients with bulky tumors (11, 12).

The initial application of SFRT required the use of custom-made or commercially available GRID blocks attached to linear accelerators. However, the physical GRID blocks introduced challenges in clinical applications: 1) difficulty in accurately calculating and measuring dose distribution, 2) technical complexities and inconvenience, and 3) excessively high dose to the skin and normal tissues traversed by the beam. To address these issues, the concept of lattice therapy (LRT) has emerged, which utilizes multi-leaf collimator (MLC)-based intensity-modulated radiotherapy (IMRT) to achieve 3D spatially fractionated dose distribution without physical GRID blocks (12, 13).

Since the first patient was treated with LRT in 2014, over 150 patients with large tumors have received LRT worldwide (13). A systematic review of LRT was conducted to determine the effectiveness and safety of LRT, leading to the proposal of a set of technical recommendations and guidelines for its clinical implementation (13, 14). Most LRTs have been implemented as volumetric-modulated arc therapy (VMAT) with a medical linear accelerator. Jiang et al. and Brown et al. implemented LRT using CyberKnife (7, 15). F Ertan et al. conducted a dosimetric comparison study of 3D LRT using the fixed cone collimator of the CyberKnife and the MLC of the conventional linear accelerator (16). Several studies have reported that a charged particle such as the proton, or carbon beam with pencil-beam scanning technique provides better dosimetric performance compared to a photon beam (17–19). While charged particle-based LRT faces challenges like high entrance dose and limited beam angles, recent advancements in arc and FLASH techniques show promise for treating bulky tumors, potentially improving dose conformity.

Recent trends in SFRT research aim to further validate clinical efficacy through biological studies and clinical trials (11–14). These studies focus on demonstrating the therapeutic benefits of spatial fractionation in various cancer types, investigating outcomes such as tumor control, survival rates, and quality of life improvements. This research highlights the advantages of SFRT compared to conventional radiotherapy. Researchers are working to optimize treatment planning systems, determining ideal vertex size, spacing, and patient-specific parameters (20, 21). Gaudreault et al. (20) have developed an automated treatment planning approach for LRT, aiming to streamline the process and improve consistency. Zhang et al. (21) proposed a method for lattice position optimization in LATTICE therapy to enhance dose delivery precision. These efforts refine both the clinical evidence base and technical aspects of treatment delivery, seeking to maximize LRT’s therapeutic potential. However, the optimal vertex size and spacing required to achieve the desired VPDR at specific locations have not been clearly established.

Tomotherapy is a representative binary MLC-based IMRT treatment machine widely used in radiation oncology. During treatment, as the gantry rotates 360°, the couch moves inward at a constant speed, resulting in a spiral radiation delivery pattern directly onto the patient. Tomotherapy offers superior conformity, homogeneity, and normal tissue protection compared to conventional IMRT (22). While some institutions have explored GRID therapy using Tomotherapy (23, 24), LRT represents a novel approach not previously investigated. This study is the first to investigate the feasibility of implementing LRT using Tomotherapy. Therefore, this study aims to analyze VPDR based on various vertex sizes and spacings in the context of Tomotherapy-based LRT. By conducting this pioneering research, this study proposes guidelines for selecting suitable vertex size and spacing for clinical application through quantitative analysis.

This study aimed to demonstrate the feasibility of implementing Lattice Radiotherapy (LRT) using helical tomotherapy and to investigate the impact of vertex size and spacing on treatment planning effectiveness. The evaluation of LRT was based on dosimetric parameters, dose distribution characteristics, and operational metrics that align with the study’s objectives. Specifically, we analyzed the minimum, maximum, and mean doses at the vertices to assess dose uniformity and modulation. Normal tissue sparing was evaluated through V30% and V50%, which represent the percentage of the phantom body (excluding the vertices) receiving at least 30% and 50% of the prescribed dose, respectively. The Conformity Index (CI) and Homogeneity Index (HI) were calculated from dose-volume histograms to measure the precision and consistency of dose delivery. Additionally, operational efficiency was assessed using planned monitor units (MUs) and gantry period time to evaluate the practicality of treatment delivery. These metrics collectively provide a comprehensive framework for assessing the feasibility and effectiveness of LRT in clinical applications, providing crucial insights for balancing the competing objectives of target coverage, dose uniformity, and sparing of surrounding tissues in LRT treatment planning.

Our results indicate that the VPDR, a critical parameter in LRT, decreases exponentially with increasing vertex size and spacing. Quantitatively, we observed that VPDR values ranged from 2.87% to 80.7% across different configurations used in this study, with the highest values achieved with smaller vertex diameters (0.5 cm) and larger spacings (5 cm). Interestingly, we found a consistent anisotropy in dose distribution, with VPDR values in the SI direction approximately 15-20% lower than those in the AP and LAT directions. This directional variation, attributed to the helical delivery pattern of tomotherapy, aligns with findings from previous studies on helical delivery techniques but presents unique considerations for LRT implementation.

The analysis of dose distribution revealed important trade-offs in LRT planning. Smaller vertex diameters (0.5 cm) resulted in better dose homogeneity within the vertices (Homogeneity Index range: 1.20-1.26) but showed greater variability in mean doses (± 2 Gy from prescribed 20 Gy). Conversely, larger vertex diameters (2.0 cm) demonstrated better dose conformity (Conformity Index range: 1.00-1.09) but slightly poorer homogeneity (HI range: 1.39-1.57). These findings are consistent with previous LRT studies using other delivery techniques, such as those reported by Gaudreault et al. (20), but our study uniquely quantifies these trade-offs in the context of helical tomotherapy.

The clinical significance of VPDR has been extensively studied in recent years, with mounting evidence supporting its crucial role in treatment outcomes. VPDR serves as a critical metric in LRT that directly influences the balance between tumor control and normal organ sparing. Studies by Wu et al. (13) demonstrated that lower VPDR values (<0.3) correlate with improved local tumor control rates, particularly in bulky tumors exceeding 5cm in diameter. Jiang et al. (7) reported significant tumor response rates (>60%) in advanced cases when achieving optimal VPDR values while maintaining acceptable toxicity profiles. Furthermore, retrospective analyses by Iori et al. (14) suggest that carefully modulated VPDR can reduce radiation-induced complications in cases where tumors are adjacent to critical organs, with complication rates decreasing by up to 30% compared to conventional approaches. Recent immunological studies by Kanagavelu et al. (8) have revealed that optimal spatial dose variation can enhance anti-tumor immune responses, with evidence of increased tumor-infiltrating lymphocytes in regions receiving peak doses.

Evaluation of low-dose exposure in regions excluding the vertices provided valuable insights into normal tissue sparing. We observed that V30% and V50% values increased by approximately 5-10% for every 1 cm increase in spacing, indicating that while larger spacing may improve VPDR, it also results in greater dose distribution to surrounding tissues. This observation extends the findings of previous studies on normal tissue sparing in LRT and highlights the importance of careful spacing selection in treatment planning.

The lowest maximum dose of 15.41 Gy observed in the D0.5S2 configuration reflects challenges associated with edge vertices. Edge vertices are more prone to underdosing due to reduced beam overlap and limited modulation flexibility at the periphery of the lattice structure, especially in configurations with smaller vertex sizes and narrower spacing. These results highlight the complex interplay between vertex size, spacing, and helical tomotherapy delivery characteristics, which should be carefully considered in future optimization strategies.

The trade-off between potential dosimetric benefits and treatment efficiency is evident in our treatment delivery metrics, where beam-on time increased from 2079.3 s to 9137.5 s as we moved from the smallest to the largest configuration. This significant increase in treatment time should be carefully considered in the planning process to balance therapeutic efficacy with patient comfort and clinical practicality, a consideration that has been less emphasized in previous LRT studies.

Based on our experimental results and clinical considerations, we propose specific guidelines for clinical implementation. Our study indicates that vertex size and spacing selections should be tailored to specific clinical scenarios, with clear correlations between these parameters and treatment outcomes. For most clinical applications, our data suggest that a 1 cm vertex diameter with 3-4 cm spacing offers an optimal balance, resulting in VPDR values below 0.4 while maintaining practical treatment delivery times and acceptable low-dose spread. However, this baseline configuration should be adapted according to tumor characteristics and anatomical considerations.

Specifically, for tumors in proximity to critical structures within 2 cm, increasing vertex spacing to 4-5 cm is recommended to reduce low-dose exposure to surrounding tissues. This configuration maintained therapeutic peak doses while reducing the cumulative dose to adjacent normal tissues by approximately 25%. Conversely, for large (>8 cm), radioresistant tumors, our data support using 2 cm vertex diameter with 1-2 cm spacing to enhance tumor control, though practitioners should be mindful of the associated increase in treatment time, which is approximately 2.5 times longer. Tumor morphology should also guide vertex distribution. For irregularly shaped tumors, our conformity index data suggest that adapting vertex placement to follow tumor contours improves dose conformity by up to 15%. The observed anisotropic VPDR distribution in tomotherapy requires particular attention for tumors extending along the superior-inferior axis, as our results show a consistently lower VPDR in this direction, with a reduction of 15-20% compared to other orientations. This characteristic should be carefully considered in treatment planning, as optimizing delivery in this direction could enhance therapeutic outcomes.

Looking toward future developments, our findings suggest several promising directions for advancing LRT implementation. Integration of automated planning algorithms could optimize vertex placement based on our established VPDR-outcome correlations, while functional imaging-based vertex selection could further personalize treatment by targeting radioresistant regions identified through biological imaging. These approaches, combined with our quantitative understanding of vertex parameter relationships, will be essential in achieving an optimal balance between tumor control and normal tissue sparing, particularly in challenging clinical scenarios.

It is also worth noting that our study used a simplified 3×3×3 lattice structure in the center of a phantom, which may limit its direct clinical applicability. In real clinical scenarios, tumors are often irregular in shape and size, constraining the number and placement of vertices. Additionally, lattice vertices are often offset in adjacent CT slices to minimize overlap of high-dose regions and achieve a more uniform dose distribution across the gross tumor volume.

While our study establishes the technical feasibility and dosimetric characteristics of tomotherapy-based LRT using systematic vertex arrangements, clinical implementation should consider tumor biological factors. Recent studies have demonstrated significant advances in biology-guided vertex placement strategies, including the use of functional imaging (25) and metabolic mapping (26) to identify optimal vertex locations. Areas of high metabolic activity or specific radioresistant regions might benefit more from high-dose vertices compared to necrotic areas. Furthermore, emerging evidence suggests that random vertex distribution patterns may be as effective as systematic arrangements, challenging traditional assumptions about optimal lattice geometry (27).

These findings highlight that future implementations of tomotherapy-based LRT should consider integrating both technical delivery capabilities and biological tumor characteristics. Development of treatment planning approaches that combine our dosimetric findings with functional imaging could lead to more personalized and effective treatment strategies. Future studies should explore automated planning approaches that incorporate offsetting and consider more complex, patient-specific lattice designs to implement LRT using tomotherapy in clinical cases. This approach aligns with recent developments in the field, such as the automated planning method introduced by Gaudreault et al. (20), which could potentially address the complexities of individualized treatment planning in LRT.

In conclusion, while our study demonstrates the feasibility of LRT using helical tomotherapy and provides valuable insights into the effects of vertex size and spacing on treatment parameters, further research is needed to translate these findings into clinical practice. This study builds upon and extends previous work in the field of LRT, offering unique insights into its implementation using helical tomotherapy. Evaluating the efficacy and toxicity of more sophisticated, patient-specific designs in a clinical setting will be crucial for determining the true potential of LRT in diverse patient populations and for advancing the field of spatially fractionated radiotherapy.

This study demonstrates the feasibility of implementing LRT using helical tomotherapy and provides guidelines for optimizing vertex size and spacing for effective treatment planning. We identified the complex interactions between various dose parameters and treatment delivery considerations, offering a foundational framework for further optimization studies aimed at clinical application. To bridge the gap between experimental results and clinical practice, future research should focus on integrating patient-specific parameters, such as GTV and surrounding critical organs, into lattice placement planning. Additionally, evaluating the clinical outcomes of tumor control and normal tissue toxicity will be crucial for translating these findings into practical use. These efforts could improve LRT treatment techniques and potentially enhance outcomes for patients with large tumors.