An Integrative multi-lineage model of variation in leukopoiesis and acute myelogenous leukemia.

BACKGROUND: Acute myelogenous leukemia (AML) progresses uniquely in each patient. However, patients are typically treated with the same types of chemotherapy, despite biological differences that lead to differential responses to treatment. RESULTS: Here we present a multi-lineage multi-compartment model of the hematopoietic system that captures patient-to-patient variation in both the concentration and rates of change of hematopoietic cell populations. By constraining the model against clinical hematopoietic cell recovery data derived from patients who have received induction chemotherapy, we identified trends for parameters that must be met by the model; for example, the mitosis rates and the probability of self-renewal of progenitor cells are inversely related. Within the data-consistent models, we found 22,796 parameter sets that meet chemotherapy response criteria. Simulations of these parameter sets display diverse dynamics in the cell populations. To identify large trends in these model outputs, we clustered the simulated cell population dynamics using k-means clustering and identified thirteen 'representative patient' dynamics. In each of these patient clusters, we simulated AML and found that clusters with the greatest mitotic capacity experience clinical cancer outcomes more likely to lead to shorter survival times. Conversely, other parameters, including lower death rates or mobilization rates, did not correlate with survival times. CONCLUSIONS: Using the multi-lineage model of hematopoiesis, we have identified several key features that determine leukocyte homeostasis, including self-renewal probabilities and mitosis rates, but not mobilization rates. Other influential parameters that regulate AML model behavior are responses to cytokines/growth factors produced in peripheral blood that target the probability of self-renewal of neutrophil progenitors. Finally, our model predicts that the mitosis rate of cancer is the most predictive parameter for survival time, followed closely by parameters that affect the self-renewal of cancer stem cells; most current therapies target mitosis rate, but based on our results, we propose that additional therapeutic targeting of self-renewal of cancer stem cells will lead to even higher survival rates.

Variations in tumor size and position due to irregular breathing in 4D-CT: a simulation study.

PURPOSE: To estimate the position and volume errors in 4D-CT caused by irregular breathing. METHODS: A virtual 4D-CT scanner was designed to reproduce axial mode scans with retrospective resorting. This virtual scanner creates an artificial spherical tumor based on the specifications of the user, and recreates images that might be produced by a 4D-CT scanner using a patient breathing waveform. 155 respiratory waveforms of patients were used to test the variability of 4D-CT scans. Each breathing waveform was normalized and scaled to 1, 2, and 3 cm peak-to-peak motion, and artificial tumors with 2 and 4 cm radius were simulated for each scaled waveform. The center of mass and volume of resorted 4D-CT images were calculated and compared to the expected values of center of mass and volume for the artificial tumor. Intrasubject variability was investigated by running the virtual scanner over different subintervals of each patient's breathing waveform. RESULTS: The average error in the center of mass location of an artificial tumor was less than 2 mm standard deviation for 2 cm motion. The corresponding average error in volume was less than 4%. In the worst-case scenarios, a center of mass error of 1.0 cm standard deviation and volume errors of 30%-60% at inhale were found. Systematic errors were observed in a subset of patients due to irregular breathing, and these errors were more pronounced when the tumor volume is smaller. CONCLUSIONS: Irregular breathing during 4D-CT simulation causes systematic errors in volume and center of mass measurements. These errors are small but depend on the tumor size, motion amplitude, and degree of breathing irregularity.