Bone turnover assessment and monitoring are essential for chronic kidney disease (CKD)-associated bone care. Patients with CKD suffer from significantly elevated fracture risk due to abnormally high or low bone turnover, which requires diametrically opposite treatments informed by patient-specific bone turnover data. However, a reliable, accessible, non-invasive bone turnover assessment and monitoring tool remains an unmet clinical need. Combining time-lapse (TL) analysis with high-resolution peripheral quantitative computed tomography (HR-pQCT) scans obtained over time allows for in vivo temporospatial bone remodeling assessment. This study aimed to evaluate the feasibility of applying TL HR-pQCT to assess and monitor local bone formation and resorption in patients with CKD. A customized TL HR-pQCT pipeline was developed on a second-generation HR-pQCT platform and optimized using ex vivo cadaveric phantom and in vivo scan-rescan HR-pQCT images. The annualized least significant change in bone formation and resorption were evaluated using in vivo longitudinal reproducibility images. Finally, the feasibility of the TL HR-pQCT pipeline in assessing and monitoring bone turnover was evaluated in patients with end stage kidney disease (ESKD; n = 9). We found that a 2-month time-lapse period was sufficient for the TL HR-pQCT pipeline to reliably assess and monitor local bone turnover in a cohort of patients with ESKD. We also demonstrated the importance of characterizing TL HR-pQCT precision metrics using longitudinal baseline/follow-up rather than short-term scan-rescan datasets. The TL HR-pQCT pipeline assessed a range of bone formation metrics consistent with the gold standard histomorphometric bone formation reported in the literature for patients with CKD and ESKD. Our findings highlight that TL HR-pQCT holds promise as a "virtual bone biopsy" that reliably assesses and monitors local bone turnover for CKD bone care. Subsequent work will focus on validating this TL HR-pQCT pipeline against the gold standard bone biopsy with quantitative histomorphometry.