Dosimetric Impact and Correction of Lipiodol Deposition on Photon-Beam Radiotherapy for Hepatocellular Carcinoma...

To evaluate the influence of Lipiodol area on radiotherapy dose distribution in the photon-beam treatment planning system (TPS) and develop a new simulation model of Lipiodol deposition in patients with hepatocellular carcinoma (HCC).

We developed a Lipiodol deposition simulation model (LDSM) using a Lipiodol-porcine liver mixture to simulate the Lipiodol area after transcatheter arterial chemoembolization (TACE). The dose calculated by the TPS (D_TPS) and the detected dose (D_DET) using 6 MV X-ray irradiation using different fractional doses (1-10 Gy/f) delivered by flattening-filter (FF) or flattening-filter-free (FFF) beams were compared. The computed tomography (CT) images of 60 patients with HCC who had undergone TACE were retrospectively reviewed and subjected to relative electron density (RED) correction and dosimetric evaluation. The dose deviation was evaluated across different TPS platforms and calculation algorithms.

In the Pinnacle³ TPS with the collapsed cone convolution algorithm, the LDSM revealed a dose underestimation due to Lipiodol area in the photon-beam TPS, with the dose deviation factor (δ) increasing with increasing Lipiodol concentration (p < 0.001). The effects of FF and FFF beams ranged from 0.3% to 4.3% and 0.5% to 5.7%, respectively, but dose deviation was not correlated with fractional dose. In patients' re-evaluated radiotherapy plans, the prescription dose coverage of gross tumor volume improved by a mean of 3.42% ± 0.92% (range, 2.00-4.99%). The 50% prescription dose coverage of normal liver increased by 0.72% ± 0.36% (range, 0-1.3%), and the maximum dose (D_MAX) to gastrointestinal tissue increased by 183.22 ± 138.80 cGy (range, 2.00-453.00 cGy). The shortest distance between the tumor and the gastrointestinal tissue was an independent predictor of gastrointestinal dosimetric deviation.

After TACE, Lipiodol area has a clinically significant dosimetric effect leading to the TPS underestimating the gastrointestinal D_MAX delivered by the photon-beam. The dosimetric deviations should be corrected, especially in the TPS with the convolution algorithm.