Background: Effective thermal ablation of liver tumors requires precise monitoring of the ablation zone. Computed tomography (CT) thermometry can non-invasively monitor lethal temperatures but suffers from metal artifacts caused by ablation equipment. Purpose: This study assesses spectral CT thermometry's applicability during microwave ablation, comparing the reproducibility, precision, and accuracy of attenuation-based versus physical density-based thermometry. Furthermore, it identifies optimal metal artifact reduction (MAR) methods: O-MAR, deep learning-MAR, spectral CT, and combinations thereof. Methods: Four gel phantoms embedded with temperature sensors underwent a 10- minute, 60 W microwave ablation imaged by dual-layer spectral CT scanner in 23 scans over time. For each scan attenuation-based and physical density-based temperature maps were reconstructed. Attenuation-based and physical density-based thermometry models were tested for reproducibility over three repetitions; a fourth repetition focused on accuracy. MAR techniques were applied to one repetition to evaluate temperature precision in artifact-corrupted slices. Results: The correlation between CT value and temperature was highly linear with an R-squared value exceeding 96 %. Model parameters for attenuation-based and physical density-based thermometry were −0.38 HU/°C and 0.00039 °C⁻¹, with coefficients of variation of 2.3 % and 6.7 %, respectively. Physical density maps improved temperature precision in presence of needle artifacts by 73 % compared to attenuation images. O-MAR improved temperature precision with 49 % compared to no MAR. Attenuation-based thermometry yielded narrower Bland-Altman limits-of-agreement (−7.7 °C to 5.3 °C) than physical density-based thermometry. Conclusions: Spectral physical density-based CT thermometry at 150 keV, utilized alongside O-MAR, enhances temperature precision in presence of metal artifacts and achieves reproducible temperature measurements with high accuracy.