ARAM: an automated image analysis software to determine rosetting parameters and parasitaemia in Plasmodium samples

Malaria Journal

Methodology

Kirsten Moll¹  Mats Wahlgren¹  Patrick Wolfgang Kudella²  Christoph Westerhausen³  Achim Wixforth³ 

[1] Department of Microbiology, Tumor and Cell Biology, Karolinska Institutet, Box 280, 171 77, Stockholm, Sweden;Experimental Physics I, University of Augsburg, Universitätsstraße 1, Augsburg, Germany;Experimental Physics I, University of Augsburg, Universitätsstraße 1, Augsburg, Germany;Nanosystems Initiative Munich, Schellingstraße 4, Munich, Germany;

关键词: Malaria;    Plasmodium falciparum;    Parasitaemia;    Rosetting;    Automatic analysis;    Software;    Image analysis;    Cell detection;   

DOI  :  10.1186/s12936-016-1243-4

 received in 2015-12-24, accepted in 2016-03-30,  发布年份 2016

来源: Springer

【 摘 要 】

BackgroundRosetting is associated with severe malaria and a primary cause of death in Plasmodium falciparum infections. Detailed understanding of this adhesive phenomenon may enable the development of new therapies interfering with rosette formation. For this, it is crucial to determine parameters such as rosetting and parasitaemia of laboratory strains or patient isolates, a bottleneck in malaria research due to the time consuming and error prone manual analysis of specimens. Here, the automated, free, stand-alone analysis software automated rosetting analyzer for micrographs (ARAM) to determine rosetting rate, rosette size distribution as well as parasitaemia with a convenient graphical user interface is presented.MethodsAutomated rosetting analyzer for micrographs is an executable with two operation modes for automated identification of objects on images. The default mode detects red blood cells and fluorescently labelled parasitized red blood cells by combining an intensity-gradient with a threshold filter. The second mode determines object location and size distribution from a single contrast method. The obtained results are compared with standardized manual analysis. Automated rosetting analyzer for micrographs calculates statistical confidence probabilities for rosetting rate and parasitaemia.ResultsAutomated rosetting analyzer for micrographs analyses 25 cell objects per second reliably delivering identical results compared to manual analysis. For the first time rosette size distribution is determined in a precise and quantitative manner employing ARAM in combination with established inhibition tests. Additionally ARAM measures the essential observables parasitaemia, rosetting rate and size as well as location of all detected objects and provides confidence intervals for the determined observables. No other existing software solution offers this range of function. The second, non-malaria specific, analysis mode of ARAM offers the functionality to detect arbitrary objects.ConclusionsAutomated rosetting analyzer for micrographs has the capability to push malaria research to a more quantitative and statistically significant level with increased reliability due to operator independence. As an installation file for Windows © 7, 8.1 and 10 is available for free, ARAM offers a novel open and easy-to-use platform for the malaria community to elucidate rosetting.

【 授权许可】

CC BY   
© Kudella et al. 2016