Current flow-based blood counting devices require expensive and centralized medical infrastructure and are not appropriate for field use. In this paper we report a method to count red blood cells, white blood cells as well as platelets through a low-cost and fully-automated blood counting system. The approach consists of using a compact, custom-built microscope with large field-of-view to record bright-field and fluorescence images of samples that are diluted with a single, stable reagent mixture and counted using automatic algorithms. Sample collection is performed manually using a spring loaded lancet, and volume-metering capillary tubes. The capillaries are then dropped into a tube of pre-measured reagents and gently shaken for 10-30 seconds. The sample is loaded into a measurement chamber and placed on a custom 3D printed platform. Sample translation and focusing is fully automated, and a user has only to press a button for the measurement and analysis to commence. Cost of the system is minimized through the use of custom-designed motorized components. We performed a series of comparative experiments by trained and untrained users on blood from adults and children. We compare the performance of our system, as operated by trained and untrained users, to the clinical gold standard using a Bland-Altman analysis, demonstrating good agreement of our system to the clinical standard. The system’s low cost, complete automation, and good field performance indicate that it can be successfully translated for use in low-resource settings where central hematology laboratories are not accessible.
Currently, one-third of humanity is still suffering from anemia. In China the most common forms of anemia are iron deficiency and Thalassemia minor. Differentiating these two is the key to effective treatment. Iron deficiency is caused by malnutrition and can be cured by iron supplementation. Thalassemia is a hereditary disease in which the hemoglobin β chain is lowered or absent. Iron therapy is not effective, and there is evidence that iron therapy may be harmful to patients with Thalassemia. Both anemias can be diagnosed using red blood cell morphology: Iron deficiency presents a smaller mean cell volume compared to normal cells, but with a wide distribution; Thalassemia, meanwhile, presents a very small cell size and tight particle size distribution. Several researchers have proposed diagnostic indices based on red cell morphology to differentiate these two diseases. However, these indices lack sensitivity and specificity and are constructed without statistical rigor. Using multivariate methods we demonstrate a new classification method based on red cell morphology that diagnoses anemia in a Chinese population with enough accuracy for its use as a screening method. We further demonstrate a low cost instrument that precisely measures red cell morphology using elastic light scattering. This instrument is combined with an automated analysis program that processes scattering data to report red cell morphology without the need for user intervention. Despite using consumer-grade components, when comparing our experimental results with gold-standard measurements, the device can still achieve the high precision required for sensing clinically significant changes in red cell morphology.