Single-compartment Model Research Articles

Model-based estimation of negative inspiratory driving pressure in patients receiving invasive NAVA mechanical ventilation

BackgroundOptimisation of mechanical ventilation (MV) and weaning requires insight into underlying patient breathing effort. Current identifiable models effectively describe lung mechanics, such as elastance (E) and resistance (R) at the bedside in sedated patients, but are less effective when spontaneous breathing is present. This research derives and regularises a single compartment model to identify patient-specific inspiratory effort. MethodsConstrained second-order b-spline basis functions (knot width 0.05 s) are used to describe negative inspiratory drive (Pp, cmH2O) as a function of time. Breath-breath Pp are identified with single E and R values over inspiration and expiration from n = 20 breaths for N = 22 patients on NAVA ventilation. Pp is compared to measured electrical activity of the diaphragm (Eadi) and published results. ResultsAverage per-patient root-mean-squared model fit error was (median [interquartile range, IQR]) 0.9 [0.6–1.3] cmH2O, and average per-patient median Pp was -3.9 [-4.5– -3.0] cmH2O, with range -7.9 – -1.9 cmH2O. Per-patient E and R were 16.4 [13.6–21.8] cmH2O/L and 9.2 [6.4–13.1] cmH2O.s/L, respectively. Most patients showed an inspiratory volume threshold beyond which Pp started to return to baseline, and Pp at peak Eadi (end-inspiration) was often strongly correlated with peak Eadi (R2=0.25–0.86). Similarly, average transpulmonary pressure was consistent breath-breath in most patients, despite differences in peak Eadi and thus peak airway pressure. ConclusionsThe model-based inspiratory effort aligns with electrical muscle activity and published studies showing neuro-muscular decoupling as a function of pressure and/or volume. Consistency in coupling/dynamics were patient-specific. Quantification of patient and ventilator work of breathing contributions may aid optimisation of MV modes and weaning.

Towards an Algorithm-Based Tailored Treatment of Acute Neonatal Hyperammonemia.

Acute neonatal hyperammonemia is associated with poor neurological outcomes and high mortality. We developed, based on kinetic modeling, a user-friendly and widely applicable algorithm to tailor the treatment of acute neonatal hyperammonemia. A single compartmental model was calibrated assuming a distribution volume equal to the patient’s total body water (V), as calculated using Wells’ formula, and dialyzer clearance as derived from the measured ammonia time–concentration curves during 11 dialysis sessions in four patients (3.2 ± 0.4 kg). Based on these kinetic simulations, dialysis protocols could be derived for clinical use with different body weights, start concentrations, dialysis machines/dialyzers and dialysis settings (e.g., blood flow QB). By a single measurement of ammonia concentration at the dialyzer inlet and outlet, dialyzer clearance (K) can be calculated as K = QB∙[(Cinlet − Coutlet)/Cinlet]. The time (T) needed to decrease the ammonia concentration from a predialysis start concentration Cstart to a desired target concentration Ctarget is then equal to T = (−V/K)∙LN(Ctarget/Cstart). By implementing these formulae in a simple spreadsheet, medical staff can draw an institution-specific flowchart for patient-tailored treatment of hyperammonemia.

Analytical Solutions of a Two-Compartment Model Based on the Volume-Average Theory for Blood Toxin Concentration during and after Dialysis.

Accurate prediction of blood toxin concentration during and after dialysis will greatly contribute to the determination of dialysis treatment conditions. Conventional models, namely single-compartment model and two-compartment model, have advantages and disadvantages in terms of accuracy and practical application. In this study, we attempted to derive the mathematical model that predicts blood toxin concentrations during and after dialysis, which has both accuracy and practicality. To propose the accurate model, a new two-compartment model was mathematically derived by adapting volume-averaging theory to the mass transfer around peripheral tissues. Subsequently, to propose a practical model for predicting the blood toxin concentration during dialysis, an analytical solution expressed as algebraic expression was derived by adopting variable transformation. Furthermore, the other analytical solution that predicts rebound phenomena after dialysis was also derived through similar steps. The comparisons with the clinical data revealed that the proposed analytical solutions can reproduce the behavior of the measured blood urea concentration during and after dialysis. The analytical solutions proposed as algebraic expressions will allow a doctor to estimate the blood toxin concentration of a patient during and after dialysis. The proposed analytical solutions may be useful to consider the treatment conditions for dialysis, including the rebound phenomenon.

Dynamics Analysis of Firing Patterns in Pre-Bötzinger Complex Neurons Model.

Pre-Bötzinger complex (PBC) neurons located in mammalian brain are the necessary conditions to produce respiratory rhythm, which has been widely verified experimentally and numerically. At present, one of the two different types of bursting mechanisms found in PBC mainly depends on the calcium-activated of non-specific cation current (ICaN). In order to study the influence of ICaN and stimulus current Iexc in PBC inspiratory neurons, a single compartment model was simplified, and firing patterns of the model was discussed by using stability theory, bifurcation analysis, fast, and slow decomposition technology combined with numerical simulation. Under the stimulation of different somatic applied currents, the firing behavior of neurons are studied and exhibit multiple mix bursting patterns, which is helpful to further understand the mechanism of respiratory rhythms of PBC neurons.

Y-90 SIRT: evaluation of TCP variation across dosimetric models

IntroductionMuch progress has been made in implementing selective internal radiation therapy (SIRT) as a viable treatment option for hepatic malignancies. However, there is still much need for improved options for calculating the amount of activity to be administered. To make advances towards this goal, this study examines the relationship between predicted biological outcomes of liver tumors via tumor control probabilities (TCP) and parenchyma via normal tissue complication probabilities (NTCP) given variations in absorbed dose prescription methodologies.MethodsThirty-nine glass microsphere treatments in 35 patients with hepatocellular carcinoma or metastatic liver disease were analyzed using 99mTc-MAA SPECT/CT and 90Y PET/CT scans. Predicted biological outcomes corresponding to the single compartment (standard) model and multi-compartment (partition) dosimetry model were compared using our previously derived TCP dose-response curves over a range of 80–150 Gy prescribed absorbed dose to the perfused volume, recommended in the package insert for glass microspheres. Retrospective planning dosimetry was performed on the MAA SPECT/CT; changes from the planned infused activity due to selection of absorbed dose level and dosimetry model (standard or partition) were used to scale absorbed doses reported from 90Y PET/CT including liver parenchyma and lesions (N = 120) > 2 ml. A parameterized charting system was developed across all potential prescription options to enable a clear relationship between standard prescription vs. the partition model-based prescription. Using a previously proposed NTCP model, the change in prescribed dose from a standard model prescription of 120 Gy to the perfused volume to a 15% NTCP prescription to the normal liver was explored.ResultsAverage TCP predictions for the partition model compared with the standard model varied from a 13% decrease to a 32% increase when the prescribed dose was varied across the range of 80–150 Gy. In the parametrized chart comparing absorbed dose prescription ranges across the standard model and partition models, a line of equivalent absorbed dose to a tumor was identified. TCP predictions on a per lesion basis varied between a 26% decrease and a 81% increase for the most commonly chosen prescription options when comparing the partition model with the standard model. NTCP model was only applicable to a subset of patients because of the small volume fraction of the liver that was targeted in most cases.ConclusionOur retrospective analysis of patient imaging data shows that the choice of prescribed dose and which model to prescribe potentially contribute to a wide variation in average tumor efficacy. Biological response data should be included as one factor when looking to improve patient care in the clinic. The use of parameterized charting, such as presented here, will help direct physicians when transitioning to newer prescription methods.

264-OR: Glucagon Kinetics: Model from First-in-Humans with 13C15N Glucagon

We recently developed a novel stable glucagon tracer, [13C15N]-glucagon, to study glucagon kinetics and turnover in humans. Here, [13C15N]-glucagon was used to model glucagon kinetics during steady-state conditions in 5 nondiabetic subjects with complete data thus far (age 27±7 y; BMI 25.3±2.4 kg/m2, Mean±SD) who underwent two separate protocols: bolus injection (1497±564 pg/kg) and stop-from-constant infusion (138±33 pg/kg/min) of [13C15N]-glucagon. Arterialized blood was frequently sampled to measure the decay of [13C15N]-glucagon concentrations using tandem mass spectrometry. A linear, single compartment model was necessary and sufficient to reliably describe [13C15N]-glucagon kinetics and estimate both glucagon volume of distribution and clearance rate. The model well predicted the data (Fig. 1) and model parameters were estimated with precision (CV = 6±3 %). Volume of glucagon distribution was 37±9 mL/kg while clearance rate was 8.1±1.5 mL/kg/min. Results suggest that glucagon distributes in a single compartment with a volume of distribution approximately equal to the plasma volume. Additional nondiabetic and subjects with type 1 diabetes are currently under study. This model will be key to study postprandial glucagon turnover. Disclosure M. Schiavon: None. F. Ruchi: None. Y. R. Yadav: None. R. Basu: None. C. Cobelli: None. C. Dalla man: Research Support; Self; Becton, Dickinson and Company, Sanofi-Aventis Deutschland GmbH. A. Basu: None. Funding National Institutes of Health (DK085516 to A.B.), (DK029953 to R.B.); Italian Ministry of Education, University and Research (Law 232/2016 to M.S. and C.D.M.)

PHARMACOKINETIC SIMULATION AND OPTIMIZING GENTAMICIN DOSING IN PEDIATRICS

Aim: This study was conducted to optimize gentamicin (genta) use in paediatrics incorporating the estimation of serum drug concentrations and customized pharmacokinetic (PK) simulations. Method: 66 patients (age 1-144 month) were enrolled in the study. They received gentamicin 2-2.5 mg/kg every 8 hr. (TID regimen). Serum genta concentrations within one dosing interval of dose 3 and dose 4 were determined using an immunoassay; blood samples were collected at 30 minutes after the end of infusion while a trough level sample was collected just before the next dose. Customized PK simulation analysis was based on the following assumptions: Single-compartment model, first-order elimination, and repeated short time IV infusion. PK parameters and simulation of genta peak/trough levels after various regimens were estimated and compared statistically. Results: About 65% of the patients showed subtherapeutic peak genta levels (less than 6 ug/ml) during the dosing intervals. Potentially toxic trough levels (>1 ug/ml) were observed in two patients. Neonates (1-12 months) showed a relatively higher mean genta volume of distribution (Vd), 0.51±0.18 L/Kg, vs 0.37±0.13 (p 1-12 y). Half-life in both groups was comparable (about 3 h). Simulation suggests BID regimens will provide the best theoretically overall peak/trough targets. Discussion: In children, a higher volume of distribution of genta could be associated with the lower serum peak levels due to the conventional dosing regimen (TID). Conclusion: Optimal dosing regimen in pediatric patients can be designed to achieve target high peak, low trough levels based on simplified customized PK simulations.

Evaluation of Arterial Spin Labeling MRI-Comparison with 15O-Water PET on an Integrated PET/MR Scanner.

Cerebral blood flow (CBF) measurements are of high clinical value and can be acquired non-invasively with no radiation exposure using pseudo-continuous arterial spin labeling (ASL). The aim of this study was to evaluate accordance in resting state CBF between ASL (CBFASL) and 15O-water positron emission tomography (PET) (CBFPET) acquired simultaneously on an integrated 3T PET/MR system. The data comprised ASL and dynamic 15O-water PET data with arterial blood sampling of eighteen subjects (eight patients with focal epilepsy and ten healthy controls, age 21 to 61 years). 15O-water PET parametric CBF images were generated using a basis function implementation of the single tissue compartment model. Cortical and subcortical regions were automatically segmented using Freesurfer. Average CBFASL and CBFPET in grey matter were 60 ± 20 and 75 ± 22 mL/100 g/min respectively, with a relatively high correlation (r = 0.78, p < 0.001). Bland-Altman analysis revealed poor agreement (bias = −15 mL/100 g/min, lower and upper limits of agreements = −16 and 45 mL/100 g/min, respectively) with a negative relationship. Accounting for the negative relationship, the width of the limits of agreement could be narrowed from 61 mL/100 g/min to 35 mL/100 g/min using regression-based limits of agreements. Although a high correlation between CBFASL and CBFPET was found, the agreement in absolute CBF values was not sufficient for ASL to be used interchangeably with 15O-water PET.

Greater reductions in blood flow after anti-angiogenic treatment in non-small cell lung cancer patients are associated with shorter progression-free survival

To evaluate tumor blood flow using 15O-water positron emission tomography (PET) in patients with non-small cell lung cancer (NSCLC) before and after chemotherapy with bevacizumab, and to investigate the effects of bevacizumab on tumor blood flow changes and progression-free survival (PFS). Twelve patients with NSCLC were enrolled. Six patients underwent chemotherapy with bevacizumab and the other six without bevacizumab. 15O-water dynamic PET scans were performed within 1 week before the start of chemotherapy and within 1 week after the first day of chemotherapy. Tumor blood flow was analyzed quantitatively using a single one-tissue compartment model with the correction of pulmonary circulation blood volume and arterial blood volume via an image-derived input function. In the bevacizumab group, mean tumor blood flow was statistically significantly reduced post-chemotherapy (pre-chemotherapy 0.27 ± 0.14 mL/cm3/min, post-chemotherapy 0.18 ± 0.12 mL/cm3/min). In the no bevacizumab group, there was no significant difference between mean tumor perfusion pre-chemotherapy (0.42 ± 0.42 mL/cm3/min) and post-chemotherapy (0.40 ± 0.27 mL/cm3/min). In the bevacizumab group, there was a positive correlation between the blood flow ratio (tumor blood flow post-chemotherapy/tumor blood flow pre-chemotherapy) and PFS (correlation coefficient 0.94). Mean tumor blood flow decreases after bevacizumab administration and was positively correlated with longer PFS.

Measuring the mechanical input impedance of the respiratory system with breath-driven flow oscillations.

In recent years, the mechanical input impedance of the respiratory system (Zrs) determined using the technique known as oscillometry has been gaining traction as a clinical diagnostic tool to complement conventional spirometry. Nevertheless, despite currently approved oscillometry devices being relatively compact and portable, they are still too heavy and bulky to be used in an ambulatory hands-free setting, mostly because of the mass of the motor and power supply. We therefore explored the possibility of using the subject's own respiratory musculature as the power source for creating flow oscillations at the mouth. We measured reference Zrs in 8 normal volunteers by having them breathe tidally into a piston-driven oscillator powered by an external motor. We fit the measured Zrs to the single-compartment model of the respiratory system characterized by the three parameters resistance (Rrs), elastance (Ers), and inertance (Irs). We then compared these parameter values to those obtained with two commercially available mucus-clearing devices that generate oscillations when expiratory flow drives a flapper valve. The estimates of Rrs agreed mostly within ±1 cmH2O·s·L-1, which is usefully accurate for most clinical needs. Ers and Irs agreed less well because the breath-driven oscillators provided data at essentially a single frequency close to the resonant frequency of the respiratory system. Nevertheless, we conclude that perturbing respiratory airflow and pressure with a breath-driven oscillator has the potential to provide measurements of Zrs, possibly serving as the basis for a lightweight ambulatory oscillometry system.NEW & NOTEWORTHY The technique of oscillometry for measuring the mechanical input impedance of the respiratory system is gaining traction as a clinical diagnostic tool, but the portability of existing commercially available devices is limited by the size and weight of oscillator motors and power supplies. We show that impedance can be measured by oscillations in mouth pressure and flow generated by mucus-clearing devices that are powered by the subject's own respiratory flow.

RETRACTED: Embedded computer system in hospital and atomized intelligent monitoring of children's respiratory diseases

Single-compartment model described in the alveolar partial pressure of carbon dioxide in exhaled breath, since the recording time based on the scene design. Respiratory parameters, use this model to estimate, then the clinical status and obstructive pulmonary disease in a patient. Methods: consider appropriate assumptions, a derive the analytical solution of the model, described in the section for children breath. The proposed framework integrates three new technical contribution: active shape model using a weighted allocation, using the graph cut segmentation Asymmetry unexpected objects removed, and the use of heterogeneous information theory measures the severity of a medical system quantization lung segmentation. A simple mechanical model allows estimation of respiratory parameters from the subject children, and may be applied to the measurement of these variables and the diagnosis and monitoring of chronic reversible obstructive lung disease suction size, then through the same qualitative trend study night. The results showed that the derivative and tidal volume the size of the measure is to attract an agent on behalf of the original waveform breathing. Relative sizes of the tidal volume suction maturation degree by changing the sleep state may be maintained potentially be used for quantitative pathology, or respiratory control.

Automated Positive End-Expiratory Pressure Titration during Mechanical Ventilation

Abstract Optimizing the positive end-expiratory pressure remains challenging for any clinician treating a patient with acute respiratory distress syndrome. This paper presents an approach to automate a PEEP titration maneuver and identify the best PEEP according to maximal compliance. The respiratory system was modeled by a single-compartment model, and parameters were estimated using multiple linear regression. A classifier identified the best PEEP using the scaled relative change in compliance between PEEP levels based on empirical data from previous manual PEEP titrations. An experimental system allows the in vivo testing of the automated PEEP titration, including additional safety measures. The complete system was tested in a single animal experiment and correctly identified the best PEEP. The introduced system is a step closer towards an automated, standardized PEEP optimization and closed-loop control of mechanical ventilation.

B-spline modelling of inspiratory drive in NAVA-ventilated patients

Abstract Model-based approaches are often used to estimate mechanical properties of lungs, such as elastance (E) and airway resistance (R), during invasive and non-invasive mechanical ventilation (MV). Current models are less effective when spontaneous breathing is present. This analysis utilises b-spline functions within a single compartment model framework to identify patient-specific inspiratory driving pressure. A series of 2nd-order, constrained b-spline basis functions are used to identify inspiratory driving pressure breath to breath alongside single E and R using inspiration and expiration data from n=20 breaths for 10 patients ventilated using NAVA. Median [IQR] per patient RMS error for n = 20 breaths was 0.75 [0.6 – 0.9] cmH2O, with elastance ranging from 2.1 – 29.8 cmH20/L, and per-patient median peak driving pressure ranging from -1.9 to -7.9 cmH2O. Inspiratory driving pressure profiles matched esophageal pressures from literature and its value at peak nervous signal to the diaphragm (Eadi) was correlated with peak Eadi (R2=0.25-0.86). Average trans-pulmonary pressure remained consistent between breaths for each patient, despite differences in peak Eadi and peak airway pressure. Overall, the model-based approach resulted in physiologically reasonable inspiratory driving pressures, with trends with electrical activity and matched literature data showing neuro-muscular decoupling as a function of pressure and/or volume.

Excitation properties of computational models of unmyelinated peripheral axons.

Biophysically based computational models of nerve fibers are important tools for designing electrical stimulation therapies, investigating drugs that affect ion channels, and studying diseases that affect neurons. Although peripheral nerves are primarily composed of unmyelinated axons (i.e., C-fibers), most modeling efforts focused on myelinated axons. We implemented the single-compartment model of vagal afferents from Schild et al. (1994) (Schild JH, Clark JW, Hay M, Mendelowitz D, Andresen MC, Kunze DL. J Neurophysiol 71: 2338-2358, 1994) and extended the model into a multicompartment axon, presenting the first cable model of a C-fiber vagal afferent. We also implemented the updated parameters from the Schild and Kunze (1997) model (Schild JH, Kunze DL. J Neurophysiol 78: 3198-3209, 1997). We compared the responses of these novel models with those of three published models of unmyelinated axons (Rattay F, Aberham M. IEEE Trans Biomed Eng 40: 1201-1209, 1993; Sundt D, Gamper N, Jaffe DB. J Neurophysiol 114: 3140-3153, 2015; Tigerholm J, Petersson ME, Obreja O, Lampert A, Carr R, Schmelz M, Fransén E. J Neurophysiol 111: 1721-1735, 2014) and with experimental data from single-fiber recordings. Comparing the two models by Schild et al. (1994, 1997) revealed that differences in rest potential and action potential shape were driven by changes in maximum conductances rather than changes in sodium channel dynamics. Comparing the five model axons, the conduction speeds and strength-duration responses were largely within expected ranges, but none of the models captured the experimental threshold recovery cycle-including a complete absence of late subnormality in the models-and their action potential shapes varied dramatically. The Tigerholm et al. (2014) model best reproduced the experimental data, but these modeling efforts make clear that additional data are needed to parameterize and validate future models of autonomic C-fibers.NEW & NOTEWORTHY Peripheral nerves are primarily composed of unmyelinated axons, and there is growing interest in electrical stimulation of the autonomic nervous system to treat various diseases. We present the first cable model of an unmyelinated vagal nerve fiber and compare its ion channel isoforms and conduction responses with other published models of unmyelinated axons, establishing important tools for advancing modeling of autonomic nerves.

Computational modeling of NMDA receptor response in Alzheimer’s disease

N-methyl-d-aspartate receptors (NMDA) located on the postsynaptic terminal of CA1 pyramidal neuron plays an essential role in synaptic plasticity, and the calcium(Ca) current flowing through it drives several intracellular calcium mechanisms. We have developed a single-compartment model involving least mechanisms to study the NMDA receptor response to different input condition and to obtain the voltage-dependent relationship of magnesium (Mg) block in the NMDA receptor. Using this interdependence, we have replicated a pathological condition of Alzheimer’s diseases (AD) to obtain total NMDA receptor current in AD. The results obtained at different Mg concentration suggested that the blocking rate increases linearly with the Mg concentration. In AD there is dysfunction of Mg block which leads to the early opening of the NMDA receptor. So by using a drug which controls the blocking mechanism of Mg, which leads to control of NMDA receptor current. This results in the control of intracellular Ca current.

Simulations of Myenteric Neuron Dynamics in Response to Mechanical Stretch.

Background Intestinal sensitivity to mechanical stimuli has been studied intensively in visceral pain studies. The ability to sense different stimuli in the gut and translate these to physiological outcomes relies on the mechanosensory and transductive capacity of intrinsic intestinal nerves. However, the nature of the mechanosensitive channels and principal mechanical stimulus for mechanosensitive receptors are unknown. To be able to characterize intestinal mechanoelectrical transduction, that is, the molecular basis of mechanosensation, comprehensive mathematical models to predict responses of the sensory neurons to controlled mechanical stimuli are needed. This study aims to develop a biophysically based mathematical model of the myenteric neuron with the parameters constrained by learning from existing experimental data. Findings. The conductance-based single-compartment model was selected. The parameters in the model were optimized by using a combination of hand tuning and automated estimation. Using the optimized parameters, the model successfully predicted the electrophysiological features of the myenteric neurons with and without mechanical stimulation. Conclusions The model provides a method to predict features and levels of detail of the underlying physiological system in generating myenteric neuron responses. The model could be used as building blocks in future large-scale network simulations of intrinsic primary afferent neurons and their network.

Directional ablation in radiofrequency ablation using a multi-tine electrode functioning in multipolar mode: An in-silico study using a finite set of states

PurposeTo analyse the feasibility of directional ablation using a multi-tine electrode. MethodsA multi-tine electrode capable of operating in multipolar mode has been used to study the directional ablation. In addition to the basic design, similar to commercially available FDA approved multi-tine electrode, tines have been insulated from each other inside the probe base and tip using a thin insulating material of thickness 0.25 mm. A cylindrical single-compartment model of size 6 cm × 6 cm has been used to model normal liver tissue. The temperature-controlled radiofrequency ablation has been employed to maintain the tine-tips at different temperatures. Electro-thermal simulations have been performed by using a commercial multi-physics software package based on finite element methods. To make this study feasible a new approach to predict the ablations have been proposed and used in this study. ResultsAsymmetric ablation zone with up to 5 mm difference in ablation boundary between the intended and non-intended direction has been observed along the transverse direction. Reduction in ablation up to 5 mm along the axial direction in comparison to the monopolar mode has also been observed. ConclusionMulti-tine electrode modified to operate in multipolar mode can create directional ablations of different shapes and can be used to target position and shape specific tumours.

Planning dosimetry for 90 Y radioembolization with glass microspheres: Evaluating the fidelity of 99m Tc-MAA and partition model predictions.

99m Tc-MAA-SPECT/CT may be used in 90 Y-glass microsphere radioembolization treatment planning to assess perfused liver volumes and absorbed dose distributions. The partition model (PM) offers a more detailed planning dosimetry option beyond the single-compartment model more traditionally used in 90 Y radioembolization. As 90 Y radioembolization treatments shift toward activities and doses that aim to achieve tumor control, accurate and reliable treatment planning dosimetry for both tumors and normal liver (NL) becomes more critical. In this work, we explore the accuracy and precision of 90 Y dosimetry predictions from pretherapy 99m Tc-MAA and PM. Both PM and voxel dosimetry models were used to calculate tumor and NL mean doses using both planning 99m Tc-MAA and verification 90 Y-SPECT/CT in this retrospective analysis of hepatocellular carcinoma cases treated with glass microspheres (NCT01900002, n=32). Linear regression models were developed at first access, and then later correct, the estimates by (a) 99m Tc-MAA for 90 Y voxel dosimetry and (b) 99m Tc-MAA PM for voxel dosimetry, separately for both tumors and NL. Bland-Altman analysis was then used to evaluate the accuracy and precision of the regression model predictions with the mean bias and 95% prediction intervals (PI, ±1.96σ). Two categories of cases were stratified (catheter matched vs catheter unmatched) by establishing the level of 99m Tc-MAA and 90 Y catheter position alignment. Only catheter-matched cases were included in the 99m Tc-MAA vs 90 Y voxel dosimetry comparison, while all cases were used to compare dosimetry models (PM vs voxel). Half (16/32) of cases were deemed catheter matched. 99m Tc-MAA could reliably predict NL doses in catheter-matched cases after application of the linear model, with mean bias (PI) of -1% (±31%). PM was equivalent to voxel dosimetry for NL doses with mean bias (PI) of 0% (±1%). Even among catheter-matched cases, 99m Tc-MAA planning for 90 Y tumor voxel doses was poor, overestimating dose by an average of nearly 40%. Upon application of the linear model, 99m Tc-MAA predictions for 90 Y tumor voxel dose were only minimally biased (-4%) but possessed very large PI (±104%). PM predictions for tumor voxel dose using the linear model also showed small bias (-6%) but maintained similarly high PI of ±90%. Cases with tumors representing a large majority (>80%) of the total tumor volume demonstrated the best scenarios for 99m Tc-MAA and PM tumor dose predictions, with mean biases (PI) of -3% (±53%) and -4% (±21%), respectively. The unconditional use of 99m Tc-MAA to predict 90 Y dosimetry across all cases is not recommended due to: (a) demonstrated the risk of unmatched catheter positions between procedures, and (b) large bias and uncertainty in 99m Tc-MAA predictions in cases with matched catheter locations. However, NL voxel dose predictions with 99m Tc-MAA are clinically viable and either PM or voxel dosimetry can be used to produce equivalent predictions. Both 99m Tc-MAA and PM can provide tumor dose predictions with potential clinical utility, but only in catheter-matched cases and with tumors comprising a clear majority (>80%) of the total tumor volume. These findings stratify the predictive fidelity of 99m Tc-MAA- and PM-based treatment planning for 90 Y dosimetry in improving treatment outcomes.

Estimation of Viral Aerosol Emissions From Simulated Individuals With Asymptomatic to Moderate Coronavirus Disease 2019

Individuals with asymptomatic or mild coronavirus disease 2019 (COVID-19) have been reported to frequently transmit the disease even without direct contact. The severe acute respiratory syndrome coronavirus 2 has been found at very high concentrations in swab and sputum samples from such individuals. To estimate the virus levels released from individuals with asymptomatic to moderate COVID-19 into different aerosol sizes by normal breathing and coughing, and to determine what exposure could result from this in a room shared with such individuals. This mathematical modeling study combined the size-distribution of exhaled breath microdroplets for coughing and normal breathing with viral swab and sputum concentrations as approximation for lung lining liquid to obtain an estimate of emitted virus levels. Viral data were obtained from studies published as of May 20, 2020. The resulting emission data fed a single-compartment model of airborne concentrations in a room of 50 m3, the size of a small office or medical examination room. Modeling was used to estimate the viral load emitted by individuals breathing normally or coughing, and the concentrations expected in the simulated room at different ventilation rates. The mean estimated viral load in microdroplets emitted by simulated individuals while breathing regularly was 0.0000049 copies/cm3, with a range of 0.0000000049 to 0.637 copies/cm3. The corresponding estimates for simulated coughing individuals were a mean of 0.277 copies/cm3 per cough, with a range of 0.000277 to 36 030 copies/cm3 per cough. The estimated concentrations in a room with an individual who was coughing frequently were very high, with a maximum of 7.44 million copies/m3 from an individual who was a high emitter. However, regular breathing from an individual who was a high emitter was modeled to result in lower room concentrations of up to 1248 copies/m3. In this modeling study, breathing and coughing were estimated to release large numbers of viruses, ranging from thousands to millions of virus copies per cubic meter in a room with an individual with COVID-19 with a high viral load, depending on ventilation and microdroplet formation process. The estimated infectious risk posed by a person with typical viral load who breathes normally was low. The results suggest that only few people with very high viral load pose an infection risk in poorly ventilated closed environments. These findings suggest that strict respiratory protection may be needed when there is a chance to be in the same small room with an individual, whether symptomatic or not, especially for a prolonged period.

Quantifying Perfusion Properties with DCE-MRI Using a Dictionary Matching Approach

Perfusion properties can be estimated from pharmacokinetic models applied to DCE-MRI data using curve fitting algorithms; however, these suffer from drawbacks including the local minimum problem and substantial computational time. Here, a dictionary matching approach is proposed as an alternative. Curve fitting and dictionary matching were applied to simulated data using the dual-input single-compartment model with known perfusion property values and 5 in vivo DCE-MRI datasets. In simulation at SNR 60 dB, the dictionary estimate had a mean percent error of 0.4–1.0% for arterial fraction, 0.5–1.4% for distribution volume, and 0.0% for mean transit time. The curve fitting estimate had a mean percent error of 1.1–2.1% for arterial fraction, 0.5–1.3% for distribution volume, and 0.2–1.8% for mean transit time. In vivo, dictionary matching and curve fitting showed no statistically significant differences in any of the perfusion property measurements in any of the 10 ROIs between the methods. In vivo, the dictionary method performed over 140-fold faster than curve fitting, obtaining whole volume perfusion maps in just over 10 s. This study establishes the feasibility of using a dictionary matching approach as a new and faster way of estimating perfusion properties from pharmacokinetic models in DCE-MRI.