The Role of Low-Energy Virtual Monoenergetic Images Derived From Dual-Energy Computed Tomography in Tumor Segmentation for Head and Neck Radiation Therapy: A Contouring Study.

Purpose: Accurate segmentation of head and neck (HN) tumors on computed tomography (CT) is made more challenging by limited soft-tissue contrast. Dual-energy CT (DECT), through virtual monoenergetic images (VMIs), offers improved tumor visualization, yet its impact on tumor segmentation remains underexplored. This study evaluates the effect of low-energy VMIs on the delineation of HN tumors within a multimodal imaging framework. Methods and Materials: VMIs were created at energies from 40 to 60 keV and were evaluated for optimal tumor visualization using contrast-to-noise ratio (CNR) metrics and qualitative physician preference assessments. The 50 keV VMI, identified as the optimal compromise between contrast and image quality, was incorporated into a contouring study involving 16 patients with HN cancers. Six physicians adjusted positron emission tomography-derived gross tumor volumes (GTVs) sequentially, incorporating the following images: 120 kVp-equivalent DECT (standard planning CT), 50 keV VMI CT, and magnetic resonance image (MRI). Inter- and intra-physician variability were assessed using Dice coefficients, Hausdorff distance, mean distance to agreement, and contour volume. Qualitative metrics, including tumor conspicuity, edge sharpness, and contouring confidence, were measured. Results: The 50 keV VMI demonstrated significantly higher CNR compared with the 120 kVp (CNR_50 keV = 1.99 vs CNR_120 kVp = 0.54, Conclusions: Low-energy DECT VMIs, particularly at 50 keV, enhance HN tumor visualization and lead to larger GTVs when compared with 120 kVp images alone, demonstrating consistency with MRI tumor delineation. These findings support the integration of VMIs into multimodal radiation therapy planning workflows to optimize target delineation accuracy.