Blood platelet kinetics in normal subjects modelled by compartmental analysis

Platelets as Predictors of Vascular Risk: Is There a Practical Index of Platelet Activity?

Activated platelets play a role in the pathogenesis of coronary heart disease (CHD). Following activation, platelets change shape, aggregate, and release several bioactive substances. The aim of this review is to identify if there is a simple and cost-effective method that indicates platelet activation and predicts the risk of CHD and vascular events. The rationale for identifying high-risk patients is to reduce their risk of vascular events by administering appropriate and effective antiplatelet treatment, like aspirin, clopidogrel, or combination regimens. Many laboratory tests estimating platelet activity have been described. Some are relatively simple, such as spontaneous or agonist-induced platelet aggregation. Other tests include measuring the mean platelet volume (MPV) or plasma soluble P-selectin levels. Some more complex tests include flow cytometry to determine platelet GP Ilb/Illa receptors, platelet surface P-selectin, plateletmonocyte aggregates, and microparticles. Only few prospective studies assessed the predictive value of platelet activation in healthy individuals. Although the MPV seems an 'easy method, there are insufficient data supporting its ability to predict the risk of a vascular event in healthy adults. Platelet aggregation, in whole blood or in platelet-rich plasma was not consistently predictive of vascular risk. Soluble P-selectin measurement is a promising method but it needs further evaluation. Flow cytometry methods are costly, time-consuming, and need specialized equipment. Thus, they are unlikely to be useful in estimating the risk in large numbers of patients. There is as yet no ideal test for the detection of platelet activation. Each currently available test has merits and disadvantages. Simple methods such as the MPV and the determination of platelet release products need further evaluation.

Kinetics of 111In-labeled bleomycin in patients with brain tumors: compartmental vs. non-compartmental models

The kinetics of an indium-111 labeled bleomycin complex (111In-BLMC) after rapid intravenous injection in patients with brain tumors was quantified by using compartmental and non-compartmental models. The models were applied to data obtained from 10 glioma, one meningioma, and one adenocarcinoma brain metastasis patients. Blood and urine samples from all the patients and tumor samples from three patients were collected. The mean transit time of 111In-BLMC in the plasma pool was 14 +/- 7 min without and 1.8 +/- 0.6 h when accounting for recirculation, and 13 +/- 4 h in the total body pool. The mean plasma clearance of 111In-BLMC was 0.3 +/- 0.1 m/blood/min and the mean half-life in urine was 3.5 +/- 0.6 h. The mean transfer coefficients for the open three-compartmental model were: excretion from plasma = 0.02 +/- 0.01, from depot to plasma = (12 +/- 9)*10(-4), from plasma to depot = 0.01 +/- 0.01, from tumor to plasma = 0.39 +/- 0.19 and from plasma to tumor = 1.11 +/- 0.57, all in units minute-1. The mean turnover time from the tumor was 4.5 +/- 2.7 min and from the depot 20 +/- 8 h. It is concluded that both compartmental and non-compartmental models are sufficient to describe the kinetics of indium-111 labeled bleomycin complex. The non-compartmental model is more practical and to some extent more efficient in describing the in vivo behaviors of 111In-BLMC than the compartmental model. The compartmental model used provides estimates of both extraction and excretion from the plasma and tumor.

Increased reticulated platelets in dialysis patients

The purpose of this study was to measure the percent reticulated platelets and platelet counts in patients on chronic hemodialysis, peritoneal dialysis and normal volunteers. The relationship between the percent reticulated platelets and the platelet count can then be used to determine the rate of platelet turnover. Platelet rich plasma was obtained, platelets were fixed and incubated with thiazole orange and analyzed for the percent reticulated platelets by flow cytometry. Normal controls had a mean of 2.77 +/- 0.17% reticulated platelets while peritoneal dialysis patients had a mean percent reticulated platelets of 6.92 +/- 0.68 (P < 0.00001). Chronic hemodialysis patients had a mean percent reticulated platelets of 8.21 +/- 0.36 (P < 0.00001 vs. normal controls and P = 0.05 vs. peritoneal dialysis patients). Platelet counts did not differ significantly among the three groups. The identity of reticulated platelets was confirmed in experiments measuring platelet specific glycoproteins, experiments using RNase, and in mixing experiments with normal and uremic platelets and plasma. We conclude that dialysis patients have a marked increase in circulating reticulated platelets compared to normal controls, indicating accelerated platelet turnover. Increased platelet activation and turnover may contribute to the qualitative platelet dysfunction observed in dialysis patients.

Granulocyte margination in bone marrow: comparison with margination in the spleen and liver

The kinetics of radiolabelled granulocytes in the reticuloendothelial system were studied in order to evaluate granulocyte margination in bone marrow. A total of 34 patients took part in a two-part study. In the first part, bone marrow uptake of indium-111-labelled granulocytes was retrospectively analysed in early (3-h) and late (24-h) images in 26 patients, 13 with bronchiectasis and 13 with enclosed abdominal abscesses. The ratios between early and late counts from the bone marrow, spleen, liver and inflammatory lesion were used to quantify granulocyte margination in bone marrow, postulating that if the lesion to bone marrow ratio at 24 h exceeds the value at 3 h, then the "excess" bone marrow counts on the early images would represent margination. In the second part, this suggestion was prospectively tested using Rutland-Patlak graphical and deconvolution analysis of dynamic data, acquired in 8 patients undergoing routine scanning with technetium-99m HMPAO-labelled granulocytes. In the first part of the study, it appeared that the bone marrow is a regional site of granulocyte margination, like the spleen, with at least one-half of the 3-h marrow signal arising from marginated granulocytes, compared with about two-thirds from the spleen. In the second part, it was found that the gradient of the Patlak plot, based on spleen and marrow, continuously decreased, consistent with bi-directional movement of cells between these organs and the blood. Granulocyte pooling in the marrow was confirmed with deconvolution analysis, which generated biphasic retention functions for marrow and spleen. These curves were also consistent with two-way granulocyte exchange, and gave mean cell transit times in both organs of about 12 min and probabilities of extraction on each pass of 5-10%. We conclude that granulocytes marginate in bone marrow to an extent similar to that in the spleen.