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Relative Ectopic Kidney Function Quantification Using DMSA Tomoscintigraphy Modality.

Ines Njeh^1,2, Kalil Chtourou³, Ahmed BenHamida^1,4

¹Advanced Technologies for Medicine and Signals (ATMS), Sfax, Tunisia.

Journal of Healthcare Engineering

|June 23, 2020

Summary

This study introduces an automated tool for estimating kidney function from DMSA scans, improving accuracy and efficiency over manual methods for ectopic kidneys. The advanced segmentation tool provides more precise relative renal function evaluation for clinical use.

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Area of Science:

Nuclear Medicine
Medical Imaging Analysis
Renal Physiology

Background:

Manual region of interest (ROI) extraction for ectopic renal function estimation is time-consuming and can impact clinical decisions.
Accurate assessment of renal function is crucial for diagnosing and managing kidney conditions, especially in cases of ectopic kidneys.

Purpose of the Study:

To develop and validate an advanced automated tool for evaluating renal function using dimercaptosuccinic acid (DMSA) kidney scintigraphy scans.
To improve the accuracy and efficiency of renal function estimation in patients with normal and ectopic kidneys.

Main Methods:

A novel segmentation approach optimizing cost functions with distribution matching and smoothness priors was applied to DMSA scans from 100 patients.
Validation employed Dice Metric (DM), Jaccard Index (JI), and correlation analysis, comparing results with manual segmentation and clinical routine planar projection methods.
Statistical validation included Bland-Altman plots and Interclass Correlation Coefficient (ICC) to assess agreement.

Main Results:

The automated segmentation achieved high Mean Dice Metric (MDM) and Jaccard Index (JI) values, deemed acceptable for clinical use compared to expert manual segmentation.
The evaluated relative renal function differed significantly from the standard planar projection method, suggesting improved accuracy.
The method effectively avoided background noise and attenuation phenomena, common sources of error in renal ectopia assessment.

Conclusions:

The proposed automated system efficiently extracts renal regions and provides more accurate relative renal function estimation.
The tool's ability to correct for background noise and attenuation enhances its reliability for ectopic kidney evaluation.
Clinical staff validated the results, recommending the tool for integration into routine clinical practice.