Percutaneous lung biopsy is a key diagnostic procedure for characterizing suspicious pulmonary nodules. However, CT-guided needle insertion is still mainly planned and performed using two-dimensional CT images displayed on external monitors, requiring the interventional radiologist to translate axial image information into a three-dimensional understanding of the lesion, surrounding anatomy, and planned needle trajectory. Augmented Reality (AR) can support this workflow by overlaying patient-specific three-dimensional anatomical models onto the operative field, improving spatial awareness and supporting more intuitive trajectory planning. This thesis presented the development of an AR guidance system for CT-guided lung biopsy using Meta Quest 3. The work extended a previous Microsoft HoloLens prototype and transferred the application to a more robust mixed reality platform, while improving planning, visualization, registration, and instrument guidance.