This study evaluates the performance of quantitative anisotropy (QA) in improving deterministic fiber tracking using diffusion MRI. Two phantom studies were conducted to assess the sensitivity of fractional anisotropy (FA), generalized fractional anisotropy (GFA), and QA to partial volume effects and spatial resolution. An in vivo study tracked the arcuate fasciculus and compared the performance of QA-aided tractography with FA-aided, GFA-aided, and anatomy-aided tractographies. The results showed that QA is less sensitive to partial volume effects, leading to better resolution and fewer false tracks compared to FA and GFA. In the in vivo study, QA-aided tractography outperformed other methods, with fewer false tracks and better agreement with anatomical structures. The study concludes that QA-aided deterministic fiber tracking can improve the accuracy and reliability of brain connectivity mapping.This study evaluates the performance of quantitative anisotropy (QA) in improving deterministic fiber tracking using diffusion MRI. Two phantom studies were conducted to assess the sensitivity of fractional anisotropy (FA), generalized fractional anisotropy (GFA), and QA to partial volume effects and spatial resolution. An in vivo study tracked the arcuate fasciculus and compared the performance of QA-aided tractography with FA-aided, GFA-aided, and anatomy-aided tractographies. The results showed that QA is less sensitive to partial volume effects, leading to better resolution and fewer false tracks compared to FA and GFA. In the in vivo study, QA-aided tractography outperformed other methods, with fewer false tracks and better agreement with anatomical structures. The study concludes that QA-aided deterministic fiber tracking can improve the accuracy and reliability of brain connectivity mapping.