Blood Test Predicts Sickle Cell Severity

The device measures how well blood samples flow through a microfluidic device, which could help doctors monitor sickle cell patients and determine the best course of treatment.

Scientists at Massachusetts Institute of Technology (MIT; Cambridge, MA, USA), collaborating with others, have developed a microfluidic system to measure changes in sickle cell blood flow after deoxygenation. The system included a microfluidic device with a capillary-sized channel that was diffusively coupled to a gas reservoir. This system allowed control over many parameters that mimic physiological conditions during vaso-occlusion, including channel size, blood pressure, and oxygen concentration.

The investigators compared blood samples taken from sickle cell patients who had or had not made an emergency trip to the hospital or received a blood transfusion within the previous 12 months. Tests were carried out with blood samples from 23 patients with severe disease and 6 patients with benign disease. They directed blood through a microchannel and lowered its oxygen concentration, which triggers sickle cells to jam and block blood flow. These conditions can produce a vaso-occlusive crisis.

Blood samples from patients with more benign disease showed a significantly slower decrease in the conductance after deoxygenation. Oxygen concentration of the gas phase was measured with a fiber optic sensor (Ocean Optics, Dunedin, FL, USA) connected to the outlet of the gas reservoir. No other existing measures of blood properties, including concentration of red blood cells, fraction of altered hemoglobin or white blood cell count, can make this kind of prediction of severe disease.

The authors concluded that the strong correlation between blood rheodynamics and the clinical outcomes in the study population provides a valuable tool for scientific discovery, drug development, and possibly for patient monitoring and clinical decision-making in sickle cell disease. The scientists have applied for a patent on the technology and are now working on developing it as a diagnostic tool. The study was published on February 29, 2012, in the journal Science Translational Medicine.

Related Links:
Massachusetts Institute of Technology
Ocean Optics