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Red blood cell (RBC) susceptibility to mechanically induced hemolysis, or RBC mechanical fragility (MF), is an important parameter in the characterization of erythrocyte membrane health. The rocker bead test (RBT) and associated calculated mechanical fragility index (MFI) is a simple method for the assessment of RBC MF. Requiring a minimum of 15.5 mL of blood and necessitating adjustment of hematocrit (Ht) to a “standard” value (40%), the current RBT is not suitable for use in most studies involving human subjects. To address these limitations, we propose a 6.5 mL reduced volume RBT and corresponding modified MFI (MMFI) that does not require prior Ht adjustment. This new method was assessed for i) correlation to the existing text, ii) to quantify the effect of Ht on MFI, and iii) validation by reexamining the protective effect of plasma proteins on RBC MF. The reduced volume RBT strongly correlated (r = 0.941) with the established large volume RBT at matched Hts, and an equation was developed to calculate MMFI: a numerical estimation (R2 = 0.923) of MFI if performed with the reduced volume RBT at “standard” (40%) Ht. An inversely proportional relationship was found between plasma protein concentration and RBC MF using the MMFI-reduced volume method, supporting previous literature findings. The new reduced volume RBT and modified MFI will allow for the measurement of RBC MF in clinical and preclinical studies involving humans or small animals.

Bench-top in vitro hemolysis testing is a fundamental tool during the design and regulatory safety evaluation of blood-contacting medical devices. While multiple published experimental protocols exist, descriptions of the test loop reservoir remain ambiguous. A critical fixture within the circuit, there is no readily available blood reservoir that ensures thorough mixing and complete air evacuation: two major factors which can affect results. As part of the Food and Drug Administration (FDA) Critical Path Initiative, we developed a three-piece reservoir consisting of a 3D-printed base, a plastic clamp set, and a medical-grade blood bag. This simple, reusable, and cost-effective design was used successfully in the hemolysis assessment of FDA benchmark nozzles and prototype rotary blood pumps, and may be useful as an integral component to any in vitro blood circulation loop.

Multilaboratory in vitro blood damage testing was performed on a simple nozzle model to determine how different flow parameters and blood properties affect device-induced hemolysis and to generate data for comparison with computational fluid dynamics-based predictions of blood damage as part of an FDA initiative for assessing medical device safety. Three independent laboratories evaluated hemolysis as a function of nozzle entrance geometry, flow rate, and blood properties. Bovine blood anticoagulated with acid citrate dextrose solution (2-80 h post-draw) was recirculated through nozzle-containing and paired nozzle-free control loops for 2 h. Controlled parameters included hematocrit (36 ± 1.5%), temperature (25 °C), blood volume, flow rate, and pressure. Three nozzle test conditions were evaluated (n = 26-36 trials each): (i) sudden contraction at the entrance with a blood flow rate of 5 L/min, (ii) gradual cone at the entrance with a 6-L/min blood flow rate, and (iii) sudden-contraction inlet at 6 L/min. The blood damage caused only by the nozzle model was calculated by subtracting the hemolysis generated by the paired control loop test. Despite high intralaboratory variability, significant differences among the three test conditions were observed, with the sharp nozzle entrance causing the most hemolysis. Modified index of hemolysis (MIHnozzle ) values were 0.292 ± 0.249, 0.021 ± 0.128, and 1.239 ± 0.667 for conditions i-iii, respectively. Porcine blood generated hemolysis results similar to those obtained with bovine blood. Although the interlaboratory hemolysis results are only applicable for the specific blood parameters and nozzle model used here, these empirical data may help to advance computational fluid dynamics models for predicting blood damage.