Carbon-ion radiotherapy provides high dose conformity for lung cancer, but its benefit is limited by two sources of uncertainties: interplay between scanned beam delivery and tumor motion, and dose modulation from heterogeneous lung tissue. This study quantifies the separate and combined dosimetric impact of these effects using the GSI TRiP4D treatment planning system. Eighteen lung cancer 4DCT datasets from TCIA were analyzed. A modulation power ($P_{\mathrm{mod}}$) was assigned to lung voxels. Three values were sampled from a Gaussian distribution ($200μ\mathrm{m} \pm 67μ\mathrm{m}$), and an extreme value of $750μ\mathrm{m}$ was tested. Interplay doses were computed by combining scanned-beam delivery with patient-specific respiratory motion. Four scenarios were studied: static, static with modulation, interplay, and interplay with modulation. Metrics included $D95\%$, $V95\%$, homogeneity index (HI), lung $V16\mathrm{Gy}$, and heart $V20\mathrm{Gy}$. Interplay reduced target coverage by $5.2 \pm 1.5$ pp ($D95\%$), $12.1 \pm 5.9$ pp ($V95\%$), and $8.3 \pm 2.4$ pp (HI). Extreme $P_{\mathrm{mod}}$ alone caused small degradations. When combined with interplay, it partially compensated the loss. This effect decreased with 4D optimization. Fractionation mitigated interplay, leaving lung modulation as the main residual effect.
Particle Therapy (PT), characterized by highly conformal dose deposition, has developed as a promising alternative to conventional photon therapy [1]. With heavier ions, like carbon ions, the even sharper Bragg Peak (BP) depth dose deposition (DDD) also comes with enhanced radiobiological efficacy. Therefore, carbon radiotherapy (CIRT) has the potential to effectively treat radioresistant tumours, such as locally advanced non-small cell lung cancers (NSCLC) [2]. CRT, because of its physical and biological characteristics, requires extremely precise dose deposition in the target, which is impaired in thoracic treatments by range and energy uncertainties mainly deriving from setup uncertainties, breathing motion and lung tissue inhomogeneities. Lung tissue microstructure and its density variation are responsible for the so-called lung modulation effect, characterized by a substantial broadening of the BP [3], [4]. The superposition of pencil beam scanned motion and tissue motion, cause the interplay effect [5][6] [7], leading to highly heterogeneous dose distributions with sever over-and under-dosage regions in the target.
Intra-fractional motion dose degradation is a well-known problem in the PT community and multiple mitigation techniques (i.e. gating, breath-hold, tracking, rescanning) have been widely investigated and, with the exception on tracking, introduced in clinical practice [8] [9], [10] [11]. Patient-specific motion is accounted for in treatment planning with time resolved CT (4DCT), motion included target safety margins [12], [13] and advanced robust optimization (RO) techniques. Integrating motion management at the plan optimization stage, is defined as 4D optimization methods [14], [15], [16].
The modulating effect of heterogenous tissues has been investigated in multiple studies [17], [18], [4], particularly the impact of lung tissue density variations on the deposited dose have been studied in Monte Carlo (MC) simulations and experimentally verified on porous materials or porcine lung samples. Results show these heterogeneities cause DDD degradation in the distal fall-off, possibly leading to target underdosage and normal tissues overdosage in patient treatment plans [3], [19], [20].
The implementation of lung modulation effect in treatment planning is hindered by the standard clinical CT voxel dimension (mm), which does not resolve the lung heterogeneous microstructure [21] but shows the lung tissue as a low-density homogenous material. Titt et al. [22], Baumann et al. [19] and Ringbaek et al. [20] in their studies developed a model to analytically describe the lung modulation effect on a particle beam. This was implemented in MC based dose calculation. The mathematical model reproduced the DDD modulation by a convolution of the unperturbed DDD with a Gaussian distribution. The kernel of the Gaussian is defined as the Modulation Power (Pmod) quantity in water-equivalent thickness (WET) units.
Paz et al. [23] further improved the model to consider the lung modulation effect in RBE-weighted dose computations and implemented it in the analytical dose calculation algorithm of GSI’s in-house TPS TRiP98, which also enabled to consider this effect already in plan optimization. While for a carbon ion beam in homogeneous material, the RBE maximum would coincide well with the BP [24], Paz et al. demonstrated that the RBE maximum shifts to greater depth as a consequent of the modulation caused by tissue heterogeneities. This shift of high-LET particles, further investigated by Zhao et al [25], is potentially harmful for the normal tissues placed at the distal edge of the target.
The described methods were employed in phantom studies [26] and patient CT studies [17], [3], [23] to investigate lung modulation dose uncertainties in patient-representative scenarios. However, the RBE shift and carbon ion RBE-weighted dose distributions degradation have so far only been investigated in the study by Paz et al. and only for a single patient. Additionally, to fully model a realistic clinical scenario, the lung modulation effect needs to be considered also in the context of breathing motion, i.e., considering the interplay effect. To date, a treatment planning study considering both intra-fractional motion and tissue heterogeneities is still missing but is crucial to understand the importance of lung modulation in clinical CIRT of lung tumours. We therefore extended the lung modulation model to integrate it into the 4D dose calculation and plan optimization features of TRiP98 (TRiP4D) [27], [28], allowing us to perform such a dosimetric study.
In this work, we present the isolated as well as the combined effect of both the interplay and lung modulation effect on CIRT treatment plans for a cohort of eighteen patients. 3D and 4D optimizations and dose calculations were performed in TRiP4D investigating the impact of effect-specific parameters such as the strength of the Modulation Power and target depth in
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