Abstract
We demonstrate a real-time blood testing system that can provide remote diagnosis with minimal human intervention in economically challenged areas. Our instrument combines novel advances in label-free optical imaging with parallel computing. Specifically, we use quantitative phase imaging for extracting red blood cell morphology with nanoscale sensitivity and NVIDIA’s CUDA programming language to perform real time cellular-level analysis. While the blood smear is translated through focus, our system is able to segment and analyze all the cells in the one megapixel field of view, at a rate of 40 frames/s. The variety of diagnostic parameters measured from each cell (e.g., surface area, sphericity, and minimum cylindrical diameter) are currently not available with current state of the art clinical instruments. In addition, we show that our instrument correctly recovers the red blood cell volume distribution, as evidenced by the excellent agreement with the cell counter results obtained on normal patients and those with microcytic and macrocytic anemia. The final data outputted by our instrument represent arrays of numbers associated with these morphological parameters and not images. Thus, the memory necessary to store these data is of the order of kilobytes, which allows for their remote transmission via, for example, the cellular network. We envision that such a system will dramatically increase access for blood testing and furthermore, may pave the way to digital hematology.
Highlights
Blood is a specialized fluid that circulates through the heart and blood vessels, delivering necessary nutrients and oxygen to the cells and carrying away metabolic waste products [1]
We demonstrate a quantitative phase imaging system dedicated to blood screening, which reconstructs phase images, analyzes and calculates a number of morphological parameters of red blood cells at single cell level, all in real time
The system is capable of very high throughput imaging and allows analyzing thousands of cells per sample
Summary
Blood is a specialized fluid that circulates through the heart and blood vessels, delivering necessary nutrients and oxygen to the cells and carrying away metabolic waste products [1]. Existing clinical technologies used to characterize blood samples such as impedance counters and flow cytometers are often accurate and offer high throughput. They are expensive and only provide limited information about the red blood cells: typically the mean corpuscular volume (MCV) and hemoglobin concentration (MCHC). The process of staining is time and labor intensive, and requires a dedicated infrastructure, i.e., specialized instruments, dyes, as well as trained personnel [2]. It is precisely the absence of technology and clinical expertise that prevents blood testing from becoming universally available. Testing the blood from transfusions is a problem of global importance: 39 out of the 159 countries, which collect 92 million blood donations every year, were not able to run blood screens [3]
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