© 2016 Elsevier España, S.L.U. y SEMNIM Objectives The proposal and implementation of a computational framework for the quantification of structural renal damage from 99m Tc-dimercaptosuccinic acid (DMSA) scans. The aim of this work is to propose, implement, and validate a computational framework for the quantification of structural renal damage from DMSA scans and in an observer-independent manner. Materials and methods From a set of 16 pediatric DMSA-positive scans and 16 matched controls and using both expert-guided and automatic approaches, a set of image-derived quantitative indicators was computed based on the relative size, intensity and histogram distribution of the lesion. A correlation analysis was conducted in order to investigate the association of these indicators with other clinical data of interest in this scenario, including C-reactive protein (CRP), white cell count, vesicoureteral reflux, fever, relative perfusion, and the presence of renal sequelae in a 6-month follow-up DMSA scan. Results A fully automatic lesion detection and segmentation system was able to successfully classify DMSA-positive from negative scans (AUC = 0.92, sensitivity = 81% and specificity = 94%). The image-computed relative size of the lesion correlated with the presence of fever and CRP levels (p <0.05), and a measurement derived from the distribution histogram of the lesion obtained significant performance results in the detection of permanent renal damage (AUC = 0.86, sensitivity = 100% and specificity = 75%). Conclusions The proposal and implementation of a computational framework for the quantification of structural renal damage from DMSA scans showed a promising potential to complement visual diagnosis and non-imaging indicators.
|Journal||Revista Espanola de Medicina Nuclear e Imagen Molecular|
|Publication status||Published - 1 Mar 2017|
- DMSA scan
- Image processing
- Quantitative analysis
- Renal damage