Feasibility Study of Functional MRI-Based Biologically Guided Lattice Radiation Therapy

Lattice radiation therapy (LRT) is a promising approach for treating bulky tumors; however, current methods do not consider patient-specific tumor heterogeneity. Low apparent diffusion coefficient (ADC) regions, identified via diffusion-weighted magnetic resonance imaging, correspond to areas of high cellular density and radioresistance. Targeted dose escalation in these regions may enhance tumor control. Thus, we propose biologically guided lattice radiation therapy (BG-LRT), which optimizes lattice positioning based on the ADC map.

We retrospectively analyzed 20 patients with bulky tumors (>6 cm) who underwent diffusion-weighted magnetic resonance imaging and simulation computed tomography within 3 days. BG-LRT plans were created by aligning high-dose lattice regions with low-ADC areas and comparing them with hexagonal close-packed-LRT (HCP-LRT). Both techniques prescribed 60 Gy in lattice regions and 20 Gy to the gross tumor volume (GTV) over 5 fractions. The dosimetric evaluation included the peak-valley dose ratio (PVDR) and ablation dose ratio (ADR) within the GTV as well as dose distribution in ADC-defined tumor subregions (R_ADC10 to R_ADC50) and organs at risk (OARs).

BG-LRT achieved a higher PVDR (2.7 vs 2.4) and ADR (2.6% vs 1.7%) than HCP-LRT. ADR values across all ADC-defined tumor subregions (R_ADC10 to R_ADC50) were significantly higher for BG-LRT. OAR doses were comparable between methods, with no significant differences in mean dose (D_mean) to the heart, stomach, esophagus, kidneys, liver, and duodenum as well as the maximum doses (D_max) to the lens, eye, optic nerve, brainstem, and optic chiasm. Planning time, delivery time, monitor units, and gamma pass rates were similar between techniques.

BG-LRT improves PVDR and ADR in the GTV while focusing on dose escalation in biologically relevant tumor regions. This technique maintains low OAR doses and represents a promising step toward personalized LRT treatment planning.