This work presents the dual-phase lag-based non-Fourier bioheat transfer model of brain tissue subjected to interstitial laser ablation. The finite element method has been utilized to predict the brain tissue's temperature distributions and ablation volumes. A sensitivity analysis has been conducted to quantify the effect of variations in the input laser power, treatment time, laser fiber diameter, laser wavelength, and non-Fourier phase lags. Notably, in this work, the temperature-dependent thermal properties of brain tissue have been considered. The developed model has been validated by comparing the temperature obtained from the numerical and ex vivo brain tissue during interstitial laser ablation. The ex vivo brain model has been further extended to in vivo settings by incorporating the blood perfusion effects. The results of the systematic analysis highlight the importance of considering temperature-dependent thermal properties of the brain tissue, non-Fourier behavior, and microvascular perfusion effects in the computational models for accurate predictions of the treatment outcomes during interstitial laser ablation, thereby minimizing the damage to surrounding healthy tissue. The developed model and parametric analysis reported in this study would assist in a more accurate and precise prediction of the temperature distribution, thus allowing to optimize the thermal dosage during laser therapy in the brain.