DCE-MRI functional NTCP modeling in SBRT for hepatocellular carcinoma
Christian Velten1, Megi Gjini2, Wolfgang A Tomé1
1Department of Radiation Oncology, Montefiore Medical Center, Bronx, NY, USA; Institute for Onco-Physics, Albert Einstein College of Medicine, Bronx, NY, USA.
Purpose:
To develop a function-guided normal tissue complication probability (NTCP) model to predict the risk of ALBI grade increases in patients treated with stereotactic body radiotherapy (SBRT) for hepatocellular carcinoma (HCC).
Methods:
Voxelized contrast kinetic modeling was performed on pre-treatment dynamic contrast enhanced (DCE) MRI employing gadoxetate disodium contrast to create volumetric maps correlated with liver function. Hepatic NTCP modeling was performed using a local-damage parallel-architecture model with ALBI grade increase as endpoint. Each voxel was assigned a damage probability (logistic function: EQD50,k). A weighted organ-average fraction of damaged subunits is calculated using the functional metric's cumulative distribution function. NTCPRTfrom SBRT is calculated using a shifted error function (µ, σ) and combined with baseline NTCP0.
Results:
NTCP modelling was performed using retrospective data from 68 patients. Local damage model parameters were obtained to be EQD50,k=17Gy2,1.68, while NTCP parameters were μ,σ,NTCP0=0.47,0.12,13%. The total number of observed ALBI grade increases were 11/68 patients (16 %). In 63 patients (93 %) the estimated damaged liver fraction was fdmg<0.3 with nine NTCP events (14.2 %). The remaining 5 patients accounted for two NTCP events (40 %).
Conclusions:
NTCP modelling using weighting of functional subunit damage probabilities has the potential to be superior in predicting ALBI grade increases after SBRT for HCC compared to function-agnostic modeling. 3D maps of surrogate quantities for liver function could, within limitations, guide external beam SBRT optimization.
