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Thermometry of red blood cell concentrate: magnetic resonance decoding warm up process.

Reiter G, Reiter U, Wagner T, Kozma N, Roland J, Schöllnast H, Ebner F, Lanzer G - PLoS ONE (2013)

Bottom Line: Mean time constants were τmean = 55.3±3.7 min, τsurface = 41.4±2.9 min and τcore = 76.8±7.1 min, mean relative time shifts were Δsurface = 0.07±0.02 and Δcore = 0.04±0.01.None of the constants correlated significantly with temperature differences between ambient and storage temperature.Independence of constants on differences between ambient and storage temperature suggests validity of models for arbitrary storage and ambient temperatures.

View Article: PubMed Central - PubMed

Affiliation: Healthcare Sector, Siemens AG, Graz, Austria. gert.reiter@siemens.com

ABSTRACT

Purpose: Temperature is a key measure in human red blood cell concentrate (RBC) quality control. A precise description of transient temperature distributions in RBC units removed from steady storage exposed to ambient temperature is at present unknown. Magnetic resonance thermometry was employed to visualize and analyse RBC warm up processes, to describe time courses of RBC mean, surface and core temperatures by an analytical model, and to determine and investigate corresponding model parameters.

Methods: Warm-up processes of 47 RBC units stored at 1-6°C and exposed to 21.25°C ambient temperature were investigated by proton resonance frequency thermometry. Temperature distributions were visualized and analysed with dedicated software allowing derivation of RBC mean, surface and core temperature-time courses during warm up. Time-dependence of mean temperature was assumed to fulfil a lumped capacitive model of heat transfer. Time courses of relative surface and core temperature changes to ambient temperature were similarly assumed to follow shifted exponential decays characterized by a time constant and a relative time shift, respectively.

Results: The lumped capacitive model of heat transfer and shifted exponential decays described time-dependence of mean, surface and core temperatures close to perfect (mean R(2) were 0.999±0.001, 0.996±0.004 and 0.998±0.002, respectively). Mean time constants were τmean = 55.3±3.7 min, τsurface = 41.4±2.9 min and τcore = 76.8±7.1 min, mean relative time shifts were Δsurface = 0.07±0.02 and Δcore = 0.04±0.01. None of the constants correlated significantly with temperature differences between ambient and storage temperature.

Conclusion: Lumped capacitive model of heat transfer and shifted exponential decays represent simple analytical formulas to describe transient mean, surface and core temperatures of RBC during warm up, which might be a helpful tool in RBC temperature monitoring and quality control. Independence of constants on differences between ambient and storage temperature suggests validity of models for arbitrary storage and ambient temperatures.

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Related in: MedlinePlus

Prediction of relative mean and core temperatures from relative surface temperature.Dependence of relative mean and core temperature differences θmean and θcore on relative surface temperature differences θsurface (solid lines) together with corresponding uncertainties (dotted lines) during warm up.
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pone-0057931-g007: Prediction of relative mean and core temperatures from relative surface temperature.Dependence of relative mean and core temperature differences θmean and θcore on relative surface temperature differences θsurface (solid lines) together with corresponding uncertainties (dotted lines) during warm up.

Mentions: Average dependencies of relative mean and core temperature differences θmean and θcore on relative surface temperature difference θsurface together with corresponding uncertainties are shown in Fig. 7. The influence of storage temperature Tstorage on the prediction of absolute mean or core temperature from absolute surface temperature is indicated in Fig. 8.


Thermometry of red blood cell concentrate: magnetic resonance decoding warm up process.

Reiter G, Reiter U, Wagner T, Kozma N, Roland J, Schöllnast H, Ebner F, Lanzer G - PLoS ONE (2013)

Prediction of relative mean and core temperatures from relative surface temperature.Dependence of relative mean and core temperature differences θmean and θcore on relative surface temperature differences θsurface (solid lines) together with corresponding uncertainties (dotted lines) during warm up.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3585280&req=5

pone-0057931-g007: Prediction of relative mean and core temperatures from relative surface temperature.Dependence of relative mean and core temperature differences θmean and θcore on relative surface temperature differences θsurface (solid lines) together with corresponding uncertainties (dotted lines) during warm up.
Mentions: Average dependencies of relative mean and core temperature differences θmean and θcore on relative surface temperature difference θsurface together with corresponding uncertainties are shown in Fig. 7. The influence of storage temperature Tstorage on the prediction of absolute mean or core temperature from absolute surface temperature is indicated in Fig. 8.

Bottom Line: Mean time constants were τmean = 55.3±3.7 min, τsurface = 41.4±2.9 min and τcore = 76.8±7.1 min, mean relative time shifts were Δsurface = 0.07±0.02 and Δcore = 0.04±0.01.None of the constants correlated significantly with temperature differences between ambient and storage temperature.Independence of constants on differences between ambient and storage temperature suggests validity of models for arbitrary storage and ambient temperatures.

View Article: PubMed Central - PubMed

Affiliation: Healthcare Sector, Siemens AG, Graz, Austria. gert.reiter@siemens.com

ABSTRACT

Purpose: Temperature is a key measure in human red blood cell concentrate (RBC) quality control. A precise description of transient temperature distributions in RBC units removed from steady storage exposed to ambient temperature is at present unknown. Magnetic resonance thermometry was employed to visualize and analyse RBC warm up processes, to describe time courses of RBC mean, surface and core temperatures by an analytical model, and to determine and investigate corresponding model parameters.

Methods: Warm-up processes of 47 RBC units stored at 1-6°C and exposed to 21.25°C ambient temperature were investigated by proton resonance frequency thermometry. Temperature distributions were visualized and analysed with dedicated software allowing derivation of RBC mean, surface and core temperature-time courses during warm up. Time-dependence of mean temperature was assumed to fulfil a lumped capacitive model of heat transfer. Time courses of relative surface and core temperature changes to ambient temperature were similarly assumed to follow shifted exponential decays characterized by a time constant and a relative time shift, respectively.

Results: The lumped capacitive model of heat transfer and shifted exponential decays described time-dependence of mean, surface and core temperatures close to perfect (mean R(2) were 0.999±0.001, 0.996±0.004 and 0.998±0.002, respectively). Mean time constants were τmean = 55.3±3.7 min, τsurface = 41.4±2.9 min and τcore = 76.8±7.1 min, mean relative time shifts were Δsurface = 0.07±0.02 and Δcore = 0.04±0.01. None of the constants correlated significantly with temperature differences between ambient and storage temperature.

Conclusion: Lumped capacitive model of heat transfer and shifted exponential decays represent simple analytical formulas to describe transient mean, surface and core temperatures of RBC during warm up, which might be a helpful tool in RBC temperature monitoring and quality control. Independence of constants on differences between ambient and storage temperature suggests validity of models for arbitrary storage and ambient temperatures.

Show MeSH
Related in: MedlinePlus