Renal function reconstruction and modeling in dynamic scintigraphy

Abstract

Dynamic renal scintigraphy is a key imaging technique for assessing renal function using time-activity curves (TACs), which represent radiotracer uptake and clearance. TAC accuracy depends on the region of interest (ROI) selection and the modeling approach used. This study aims to: (i) Reconstruct TACs manually using gray-level values in scintigraphic images and compare them to machine-generated TACs using key kinetic parameters (T_max, T_1/2, and the 30-min min/max ratio); and (ii) evaluate the effectiveness of a one-compartment empirical mathematical model for TAC fitting and its physiological relevance. Twelve clinical cases were analyzed, with TACs reconstructed manually using a rectangular ROI selection method and compared to those automatically generated by the scintigraphy machine. An empirical mathematical fitting function was developed to improve TAC fitting. Manually reconstructed TACs showed better dynamic behavior and physiological accuracy over machine-generated TACs, particularly due to differences in ROI selection and signal processing. Using gray-level values instead of raw radioactive counts enhanced the depiction of kidney dynamics. The proposed mathematical model demonstrated a strong correlation (R² close to 1) and low error metrics, confirming its suitability for renal function assessment. While a free-hand ROI selection may improve accuracy, the rectangular method gives valuable results for the considered cases. This study highlights the importance of ROI selection in TAC reconstruction and demonstrates how manual methods and mathematical modeling can enhance renal functional assessment in clinical practice. Future work should validate these findings in larger datasets and assess the reproducibility of the proposed approach across different patient populations and imaging systems.

Keywords

Dynamic renal scintigraphy / Time-activity curve / Kinetic parameters / Mathematical modeling / Renal function assessment

Acknowledgments

None.

Funding

None.

Conflict of interest

The authors declare no conflicts of interest.

Author contributions

Conceptualization: Faycal Kharfi

Investigation: All authors

Methodology: Faycal Kharfi

Writing - original draft: Faycal Kharfi

Writing - review & editing: Faycal Kharfi

Ethics approval and consent to participate

Patient data were used anonymously in accordance with local ethical guidelines. The study does not involve clinical trials and does not require informed consent.

Consent for publication

Patient data were used anonymously and do not require consent for publication.

Availability of data

The data are not publicly available.