| Literature DB >> 22669502 |
Ivo C J H Post1, Marcel C Dirkes, Michal Heger, Rick Bezemer, Johan van 't Leven, Thomas M van Gulik.
Abstract
Intra-organ flow is the most critical parameter in machine-perfused organ preservation systems (MPS). Ultrasonic flow sensors (UFS) are commonly employed in MPS. However, UFS are sensitive to changes in fluid composition and temperature and require recalibration. Novel Coriolis-type mass flow sensors (CFS) may be more suitable for MPS because the measurement technique is not amenable to these factors. The effect of viscosity, colloids, temperature, pressure, and preservation solution on flow measurement accuracy of UFS and CFS was therefore investigated. A CFS-based MPS was built and validated for setpoint stability using porcine kidneys and the ability to reproduce different pressure and flow waveforms. The UFS exhibited a temperature- and preservation solution-dependent overestimation of flow rate compared to the CFS. The CFS deviated minimally from the actual flow rate and did not require recalibration. The CFS-based MPS conformed to the preprogrammed temperature, flow, pressure, and vascular resistance settings during 6-h kidney preservation. The system was also able to accurately reproduce different pressure and flow waveforms. Conclusively, CFS-based MPS are more suitable for organ preservation than UFS-based MPS. Our CFS-based MPS provides a versatile yet robust experimental platform for testing and validating different types of clinical and experimental MPS.Entities:
Mesh:
Substances:
Year: 2012 PMID: 22669502 PMCID: PMC3508271 DOI: 10.1007/s10439-012-0601-9
Source DB: PubMed Journal: Ann Biomed Eng ISSN: 0090-6964 Impact factor: 3.934
Composition of solutions used
| HTK | UW | PS | RL | DW | |
|---|---|---|---|---|---|
| Colloids (g L−1) | |||||
| PEG | 20 (35 kDa) | ||||
| HES | 50 | ||||
| Impermeants (mmol L−1) | |||||
| Mannitol | 38 | ||||
| Lactobionate | 100 | ||||
| Raffinose | 30 | 3.2 | |||
| Trehalose | 5.3 | ||||
| Sodium gluconate | 75 | ||||
| Potassium gluconate | 20 | ||||
| Buffers (mmol L−1) | |||||
| Histidine | 198 | 6.3 | |||
| KH2PO4 | 25 | ||||
| NaH2PO4 | 21.7 | ||||
| HEPES | 24 | ||||
| Electrolytes (mmol L−1) | |||||
| Calcium | 0.0015 | 1.5 | <2 | ||
| Chloride | 32 | 20 | 109 | <2 | |
| Magnesium | 4 | <2 | |||
| Magnesium sulfate | 5 | ||||
| Potassium | 9 | 120 | 15 | 4 | <2 |
| Sodium | 15 | 25 | 120 | 130 | <2 |
| Anti-oxidants (mmol L−1) | |||||
| Tryptophan | 2 | ||||
| Allopurinol | 1 | ||||
| Glutathione | 3 | 5.6 | |||
| Ascorbic acid | 0.11 | ||||
| Alpha-tocopherol | 5.4 × 10−5 | ||||
| Additives (mmol L−1) | |||||
| Ketoglutarate | 1 | ||||
| Adenosine | 5 | 5 | |||
| Vitamins | $ | ||||
| Amino acids | $$ | ||||
| Lactate | 28 | ||||
| Osmolarity (mOsm L−1) | 310 | 325 | 325 | 272 | <1 |
| pH | 7.02–7.2 | 7.4 | 7.4 | 6.5 | 7 |
HTK: Histidine-tryptophan-ketoglutarate; UW: University of Wisconsin solution; PS: Polysol; RL: Ringers lactate; DW: Demineralized water; PEG: Polyethylene glycol; HES: Hydroxyethyl starch
$(mmol L−1): ascorbic acid (0.11), biotin (0.21), Ca-pantothenate (0.004), choline chloride (0.01), inositol (0.07), ergocalciferol (3 × 10−4), folic acid (0.002), menadione (4 × 10−5), nicotinamide (0.01), nicotinic acid (0.004), pyridoxal (0.005), riboflavin (0.003), thiamine (0.03), vitamin A (3 × 10−4), vitamin B12 (1 × 10−4), and vitamin E (5 × 10−5)
$$(mmol L−1): alanine (1.01), arginine (1.18), asparagine (0.08), aspartic acid (0.23), cysteine (0.33), glutamic acid (0.34), leucine (0.57), glutamine (0.002), glycine (0.67), isoleucine (0.38), lysine (0.48), methionine (0.30), ornithine (2.00), phenylalanine (0.30), proline (0.78), serine (0.29), threonine (0.34), tryptophan (0.88), tyrosine (0.19), and valine (0.43)
Figure 1Schematic representation of the machine perfusion system. The perfusion solution in the reservoir passes a roller pump, filter, oxygenator, bubble trap, miniature membrane pump, mass flow transducer, heat exchanger, 2nd bubble trap, pressure sensor, and temperature couple prior to entering the organ’s artery
Figure 2Viscosity of UW (blue), PS (red), HTK (green), and RL (black) showing a clear temperature-dependent effect
Figure 3Bland–Altman plots [weighing scale—ultrasonic (US) or Coriolis (CS) vs. average] displaying overestimation of flow by the US technique in comparison to the CS technique
Statistical differences in measurement accuracy between solutions per temperature group
| Temperature (°C) | Solutions |
|
|---|---|---|
| Coriolis sensor | ||
| 20 | PS vs. UW | 0.014 |
| Ultrasonic sensor | ||
| 4 | PS vs. UW | <0.001 |
| PS vs. HTK | <0.001 | |
| PS vs. RL | <0.001 | |
| 15 | PS vs. UW | <0.001 |
| PS vs. HTK | <0.001 | |
| PS vs. RL | 0.034 | |
| UW vs. HTK | <0.001 | |
| HTK vs. RL | <0.001 | |
| 20 | PS vs. HTK | <0.001 |
| PS vs. RL | 0.001 | |
| UW vs. HTK | <0.001 | |
| UW vs. RL | <0.001 | |
| 28 | PS vs. HTK | <0.001 |
| PS vs. RL | <0.001 | |
| UW vs. HTK | <0.001 | |
| UW vs. RL | <0.001 | |
HTK: Histidine–tryptophan–ketoglutarate; UW: University of Wisconsin solution; PS: Polysol; RL: Ringers lactate; DW: Demineralized water
Machine perfusion system settings stability
| Temperature (°C) | Setpoint | Mean | SD |
|---|---|---|---|
| Flow (mL min−1) | |||
| 4 | 50 | 49.950 | 0.098 |
| 15 | 50 | 50.062 | 0.257 |
| 20 | 50 | 49.891 | 0.170 |
| 28 | 50 | 49.881 | 0.125 |
| 37 | 50 | 50.036 | 0.317 |
| Pressure (mmHg) | |||
| 30 | 30.005 | 0.022 | |
| 55 | 55.000 | 0.002 | |
| 75 | 75.001 | 0.003 | |
| 95 | 94.999 | 0.003 | |
| Temperature (°C) | |||
| 4 | 3.990 | 0.036 | |
| 15 | 14.819 | 0.411 | |
| 20 | 20.224 | 0.426 | |
| 28 | 28.040 | 0.120 | |
| 37 | 37.013 | 0.371 | |
SD: standard deviation
Figure 4The dynamics of temperature (a), flow (b), pressure (c), and vascular resistance (VR, d) during 6 h ex vivo machine perfusion preservation of 2 NHBD porcine kidneys at 28 °C
Figure 5Waveform generation in the experimental system simulating a sinusoidal (a), sawtooth (b), block waveform (c), and complex composed waveform (d). The red line represents measured pressure (mmHg) and the black line represents the setpoint given to the controller device. (e)–(h) show the associated flow patterns (mL min−1)
Figure 6Principle of the Coriolis mass flow measurement, illustrating the forces and flow tube torsion when flow is present
Figure 7Coriolis flow sensor in which ω is the torsion mode actuation vector, F c indicates the Coriolis force as a result of Φm, being mass flow