%0 Journal Article
%T Computing quantitative indicators of structural renal damage in pediatric DMSA scans
%A Frederic Sampedro
%A Anna Domenech
%A Sergio Escalera
%A Ignasi Carrio
%J Revista Española de Medicina Nuclear e Imagen Molecular
%D 2017
%V 36
%N 2
%F Frederic Sampedro2017
%O HuPBA;MILAB; no menciona
%O exported from refbase (http://refbase.cvc.uab.es/show.php?record=2842), last updated on Wed, 23 May 2018 09:28:08 +0200
%X OBJECTIVES:The proposal and implementation of a computational framework for the quantification of structural renal damage from 99mTc-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.
%U http://dx.doi.org/10.1016/j.remn.2016.06.010
%P 72-77