Vaccine development requires understanding the duration of vaccine-induced protection and whether it differs across demographic groups. Phase 2b and phase 3 efficacy trials are rarely powered to assess annual efficacy or subgroup differences in long-term protection, so these attributes can remain unevaluated until years after licensure, when observational effectiveness studies become available. However, late-stage clinical trials typically collect longitudinal immunogenicity data (for established or putative correlates of protection), which could be useful for predicting vaccine efficacy over time. To address this, a weighted cross-sectionally pooled logistic regression model was applied to immunogenicity substudies from two phase 3 trials to predict the durability of protection in specific subgroups: baseline dengue seronegative and seropositive individuals for dengue vaccine, and younger (≤ 69 years) and older (≥ 70 years) individuals for zoster vaccine. Incorporating time-dependent immunogenicity data increased the precision of time-varying efficacy estimates compared with traditional case-count methods. The modeling framework extends prior immune correlate analyses that used immunogenicity measured at a single timepoint post vaccination (without requiring an absolute or mechanistic correlate of protection). When time-dependent immune markers are sufficiently predictive of protection, the framework helps reveal trends in efficacy that would otherwise be obscured by sparse case counts or limited follow-up. Collecting and modeling annual immunogenicity data in clinical trials (whether from all participants, an immunogenicity cohort, or a case-cohort substudy) can thus accelerate understanding of the persistence of vaccine-induced protection (across and within subgroups) and guide efficient development of vaccines that are protective for years.

Objectives: Invasive pneumococcal disease incidence in children has decreased substantially since the introduction of pneumococcal conjugate vaccines (PCVs) against the 7 (PCV7) and, later, 6 more (PCV13) serotypes (STs) clinically relevant in the US. In the absence of placebo-controlled vaccine efficacy trials, new PCVs are evaluated based on the vaccine-induced, serotype-specific (SS) immune response levels (immunoglobulin G titers, IgGs), as they have been demonstrated to predict efficacy. New PCVs are approved if induced SS IgGs are non-inferior to those of PCVs with demonstrated efficacy. SS IgGs can decrease with increased PCV valency, so predicting vaccine effectiveness (VE) of new PCVs can be critical to supporting public health decisions. This work predicts (from IgGs) SS VEs for the 13 serotypes shared between earlier and new PCVs. Methods.The model-based meta-analysis combined real-world vaccine effectiveness (VE) data with IgG data from clinical trials. Reverse cumulative distribution curves (RCDCs) were simulated using SS IgGs observed in placebo, PCV7, and PCV13 recipients. These were combined with published SS VEs for PCV7 and PCV13 to derive the protective IgG “threshold” (“Cp”) for each of the 13 serotypes. SS IgGs from V114 and PCV20 recipients in clinical trials gave RCDCs for each of the 13 serotypes shared with PCV13. The RCDCs were combined with Cp values to predict, for V114 and PCV20, VEs for the 13 shared serotypes [1]. Post-primary series titers were used for predicting SS Cp and VE for both 2+1 and 3+1 dosing regimens (two or three infant doses, respectively, followed by a toddler dose). 2+1 predictions used V114 and PCV20 titers from clinical trials in EU, Russian, and Australian pediatric populations for which this regimen is routinely recommended; PCV13 VEs were from an EU pediatric population. 3+1 predictions used V114 and PCV20 titers from clinical trials in the US and Puerto Rico (where 3+1 is routinely recommended); PCV13 VEs were from a US pediatric population. Resampling the relevant distributions accounted for variability and uncertainty in the available data.Results: Predicted SS VEs against PCV13 serotypes are higher for V114 than PCV20, for both 2+1 and 3+1 dosing regimens, particularly for the still-prevalent serotype ST 3 (93% and 98% for V114, 47% and 64% for PCV20, respectively, for 2+1 and 3+1 dosing regimens). A V114 2+1 regimen had predicted VEs comparable to those of PCV13 for the other 12 shared serotypes, with VE for a V114 3+1 regimen predicted to be lower (than PCV13) for ST 6A and higher for ST 19F. The predictive power of this framework and its consistency (with observed data) is re-enforced with a vachette [2] visualization of the results considering serotype and regimen as covariates.Conclusions: The approach can provide informative VE predictions in the absence of placebo-controlled clinical trials, and vachette visualization can help understand the results across regimens and serotypes. Citations: [1] J Ryman, J Weaver, T Hu, DM Weinberger, KL Yee, JR Sachs, Predicting vaccine effectiveness against invasive pneumococcal disease in children using immunogenicity data. npj Vaccines 7, 140 (2022). https://doi.org/10.1038/s41541-022-00538-1 J Ryman, J Weaver, KL Yee, JR Sachs, Predicting effectiveness of the V114 vaccine against invasive pneumococcal disease in children. Expert Review of Vaccines, 21(10) (2022). https://doi.org/10.1080/14760584.2022.2112179 J Ryman, JR Sachs, KL Yee, N Banniettis, J Weaver, T Weiss, Predicted serotype-specific effectiveness of pneumococcal conjugate vaccines V114 and PCV20 against invasive pneumococcal disease in children. Expert Review of Vaccines, 23(1) (2024) https://doi.org/10.1080/14760584.2023.2292773J Ryman, JR Sachs, N Banniettis, T Weiss, M Ahsman, KL Yee, J Weaver. Potential serotype-specific effectiveness against IPD of pneumococcal conjugate vaccines V114 and PCV20 in children given a 2+1 dosing regimen. Expert Review of Vaccines, 23(1), (2024) https://doi.org/10.1080/14760584.2024.2335323 [2] https://certara.shinyapps.io/vachette/

Using pharmacometrics to inform drug discovery and development decisions requires effective communication of models and data to all stakeholders. The new “vachette” visualization method presented here enables modelers and non-modelers to see how a model integrates and represents all data across relevant subgroups, showing how the model “sees” the data when it accounts for covariates. Vachette starts with user-provided model simulations (“curves”), together with observations used in creating (or otherwise relevant to) the model. It automatically produces a single, intuitive plot overlaying all observations onto a user-selected reference curve, accounting for covariate effects and preserving remaining random effects. The method automatically identifies characteristic landmarks (e.g., minima, maxima, and inflection points) which are used to split each curve into segments. A transformation on both x- and y-axes is then applied to each segment and its corresponding observations, accounting for covariate effects by aligning the segments to the reference, allowing intuitive visualization in one plot of covariate effects and of model fit to the data, preserving the distance between model predictions and the observations. Vachette-transformed data can also be used to enhance the utility of model assessments such as visual predictive checks and residual plots. Model visualizations using vachette enable easier and more effective evaluation and communication of the pharmacometric results critical to informing key decisions. Here the vachette method is described and its utility and flexibility are demonstrated through application to multiple types of pharmacometrics models, suggesting that vachette is a useful addition to the pharmacometrician’s toolbox.

Objectives: Serum antibody (Ab) titers are thought to be a potential predictor for protection against symptomatic dengue infection. Despite extensive research on the relationship between vaccine-induced titers and protection, it remains unclear how to best estimate the risk of contracting dengue after natural infection. This study aims to quantify the effectiveness of natural immunity by assessing the relationship between post-natural infection (PNI) Ab titers and the probability of disease (PoD), i.e., the probability of contracting symptomatic dengue within a specified period. We propose a novel framework that allows us to compute PoD curves for various prediction periods (henceforth referred to as N-month PoD curves) given a longitudinal subject-level dataset of titers and disease status. Methods: We used generalized linear models (GLM) to infer the relationship between PNI Ab titers and symptomatic disease using data from a longitudinal cohort study in school children in Thailand [1]. We expanded on the previously established approach of using one time point as a predictor for disease outcome [2], and instead used all titer measurements taken prior to disease, or all measurements if disease was not observed. To qualify our approach, we conducted simulations based on a “true” PoD curve and assessed our ability to reproduce it. To overcome the limitation of the PoD prediction period being equal to the data sampling frequency, we propose three novel methods: subsampling data, a mathematical approximation based on the short-term PoD curve, and a weighted GLM approach. These methods allow us to extend the prediction period beyond the time in between sample collection. Results: We estimated the 3- and 12-month PoD curves for school children in Thailand between 1998 and 2003. The results indicate that PNI Ab titers can be used as a correlate of risk for symptomatic dengue. Using simulated data sampled every 3 months, we showed that our approach accurately estimates the parameters of the true 3-month PoD curve and consistently estimates a unique 12-month PoD curve, regardless of which method is used. These results provide compelling numerical evidence that multiple PoD curves can be estimated for different prediction periods on the same data set. Conclusions: This work enhances the understanding of dengue-related diseases by providing a framework for predicting risk based on time-dependent PNI Ab titers. These methodological advancements improve our ability to estimate PoD curves by utilizing the majority of a given dataset and enabling predictions further into the future. Better estimates of PNI Ab titer-based protection can also aid vaccine development by serving as a reference point, with which vaccine-induced protection can be compared. Whether used as a standalone or to compare PNI Ab titers to vaccine induced Ab titers, this work can be used for optimizing of dengue outbreak prevention strategies.Citations: [1] Salje, H. et al. Reconstruction of antibody dynamics and infection histories to evaluate dengue risk. Nature 557, 719–723 (2018).[2] Katzelnick, L. C. et al. Neutralizing antibody titers against dengue virus correlate with protection from symptomatic infection in a longitudinal cohort. PNAS 113, 3, 728-33 (2016).

BACKGROUND:Respiratory syncytial virus (RSV) is a leading cause of respiratory tract infection in infants and young children. The level of serum neutralizing antibodies (SNAs) is often used as a measure of protection against respiratory syncytial virus (RSV) infection. METHODS:A qualified, model-based, meta-analysis efficacy prediction framework was used to understand the maternal vaccination-induced fold-increase in SNA titers necessary to achieve, over several study observation periods and study populations, similar protection to that of the monoclonal antibody clesrovimab (MK-1654). RESULTS:Simulations indicated that 3-month and 6-month efficacy comparable to that predicted for passive immunization (clesrovimab) would require a maternal vaccine to increase SNA titers by 30- and 60-fold, respectively, higher than observed increases reported to date. Efficacy of maternal vaccination was predicted (for vaccines similar to those with published data) to be substantially lower for preterm infants compared to full-term infants, and substantially less over 6 months than over 3 months. Efficacy of passive immunization was predicted to be similar or higher in preterm infants than full-term infants and was similar for 3- and 6-month observation periods. CONCLUSIONS:Modeling can be used to reliably predict the efficacy of maternal vaccination for preventing RSV in infants. Passive immunization (e.g., with clesrovimab) is likely to provide more protection for preterm infants and for infants born outside the RSV season than that provided by current maternal vaccines. Maternal vaccination may provide partial protection from RSV disease to full-term infants born just prior to or during the RSV season.

BackgroundNext generation, higher valency pneumococcal conjugate vaccines (PCVs) are assessed and licensed by comparing the immune response across serotypes shared with the PCVs that are standard of care for prevention of pneumococcal disease.MethodsUsing a previously qualified method we predicted the serotype-specific vaccine effectiveness (VE) against invasive pneumococcal disease of V114 and PCV20 for the serotypes shared with PCV13 in an EU, Russian, and Australian pediatric population that is recommended to receive a 2 + 1 dosing regimen.ResultsThe estimated protective antibody concentrations ranged from 0.03 (serotype 23F) to 1.49 mu g/mL (serotype 19F). Predicted VE values for V114 ranged from 79% (serotype 5) to 100% (serotype 23F). V114 had comparable effectiveness to PCV13 for all but one of shared serotypes, with predicted higher effectiveness (in V114) against serotype 3 (93% vs. 65%). Predicted VE values for PCV20 ranged from 47% (serotype 3) to 91% (serotype 14). PCV20 predicted VE was lower than PCV13's for serotypes 4, 19F, 23F, 1, 3, 5, 6A, 7F, and 19A.ConclusionsPredicted serotype-specific VE values suggest that, with a 2 + 1 dosing regimen, V114 will have greater effectiveness than PCV20 against PCV13 serotypes, particularly for the still-prevalent serotype 3. Real-world VE studies will ultimately provide clarity on the effectiveness of novel PCVs and support further confidence in and/or improvements to modeling efforts. Pediatric pneumococcal conjugate vaccines (PCVs) were first introduced in Europe in the early 2000s and their incorporation into national immunization programs has helped decrease the incidence of invasive pneumococcal disease (IPD) in Europe and globally. However, some IPD persists, due both to the emergence of non-vaccine pneumococcal serotypes and to the persistence of certain vaccine-targeted serotypes. Higher valency vaccines have been developed to help prevent IPD arising from these serotypes. The goal of the present study is to employ a previously developed model to predict the serotype-specific vaccine effectiveness of higher valency PCVs in a pediatric population that is recommended to receive a 2 + 1 dosing schedule.

BACKGROUND:Vaccine efficacy (VE) assessed in a randomized controlled clinical trial can be affected by demographic, clinical, and other subject-specific characteristics evaluated as baseline covariates. Understanding the effect of covariates on efficacy is key to decisions by vaccine developers and public health authorities. METHODS:This work evaluates the impact of including correlate of protection (CoP) data in logistic regression on its performance in identifying statistically and clinically significant covariates in settings typical for a vaccine phase 3 trial. The proposed approach uses CoP data and covariate data as predictors of clinical outcome (diseased versus non-diseased) and is compared to logistic regression (without CoP data) to relate vaccination status and covariate data to clinical outcome. RESULTS:Clinical trial simulations, in which the true relationship between CoP data and clinical outcome probability is a sigmoid function, show that use of CoP data increases the positive predictive value for detection of a covariate effect. If the true relationship is characterized by a decreasing convex function, use of CoP data does not substantially change positive or negative predictive value. In either scenario, vaccine efficacy is estimated more precisely (i.e., confidence intervals are narrower) in covariate-defined subgroups if CoP data are used, implying that using CoP data increases the ability to determine clinical significance of baseline covariate effects on efficacy. CONCLUSIONS:This study proposes and evaluates a novel approach for assessing baseline demographic covariates potentially affecting VE. Results show that the proposed approach can sensitively and specifically identify potentially important covariates and provides a method for evaluating their likely clinical significance in terms of predicted impact on vaccine efficacy. It shows further that inclusion of CoP data can enable more precise VE estimation, thus enhancing study power and/or efficiency and providing even better information to support health policy and development decisions.

BACKGROUND. CT scanners' net scan state (i.e., image acquisition period) represents a potential target for energy savings through protocol adjustments. However, gauging CT energy savings is difficult without installing costly energy monitors. OBJECTIVE. The purpose of this article was to assess correlations between CT dose report metrics and energy consumption during the system net scan state and to compare theoretic energy savings from matching percentage reductions in energy consumption during net scan and idle system states. METHODS. Current sensors were installed on a single CT scanner. A phantom was scanned at varying kilovoltage settings and effective tube current-rotation time settings. A retrospective assessment was performed in 32 patients (mean age, 61.2 +/- 17.9 [SD] years; 17 men, 15 women) who underwent 32 single-energy noncontrast abdominopelvic CT examinations from September 22, 2021, to September 27, 2021, on the same scanner. Correlations between dose report metrics and net scan energy consumption were assessed in the phantom and clinical scans, and equations were generated to derive net scan energy consumption from DLP. An additional retrospective assessment was performed in 1355 patients (mean age, 59.3 +/- 16.9 years; 663 men, 692 women) who underwent 1728 single-energy noncontrast abdominopelvic CT examinations from January 1, 2021, through December 31, 2021, on the same scanner to estimate net scan energy consumption per examination. This information was integrated with literature-derived values to compare estimated annual national energy savings resulting from 20% reductions in net scan and idle state energy consumption. RESULTS. Net scan energy consumption in the phantom scans showed high linear correlation with DLP (R-2 = 0.87), and, in the clinical scans, high linear correlation with CTDI vol (R-2 = 0.89) and very high linear correlation with DLP (R-2 = 0.92). When combining mean DLP in examinations performed in the 1-year interval, an equation relating DLP and net scan energy consumption and literature values estimated that annual national energy savings was 14.9 times greater (40,437,870 kWh/2,704,000 kWh) by targeting the idle state rather than net scan state. CONCLUSION. CT net scan energy savings can be inferred from reductions in dose report metrics. However, targeting net scan energy consumption has modest impact relative to targeting idle state energy consumption. CLINICAL IMPACT. Environmental sustainability efforts should target the idle state energy consumption of CT.

Editor's Note.-RadioGraphics Update articles supplement or update information found in full-length articles previously published in RadioGraphics. These updates, written by at least one author of the previous article, provide a brief synopsis that emphasizes important new information such as technological advances, revised imaging protocols, new clinical guidelines involving imaging, or updated classification schemes.

Understanding potential differences in vaccine-induced protection between demographic subgroups is key for vaccine development. Vaccine efficacy evaluation across these subgroups in phase 2b or 3 clinical trials presents challenges due to lack of precision: such trials are typically designed to demonstrate overall efficacy rather than to differentiate its value between subgroups. This study proposes a method for estimating vaccine efficacy using immunogenicity (instead of vaccination status) as a predictor in time-to-event models. The method is applied to two datasets from immunogenicity sub-studies of vaccine phase 3 clinical trials for zoster and dengue vaccines. Results show that using immunogenicity-based estimation of efficacy in subgroups using time-to-event models is more precise than the standard estimation. Incorporating immune correlate data in time-to-event models improves precision in estimating efficacy (i.e., yields narrower confidence intervals), which can assist vaccine developers and public health authorities in making informed decisions.

Background: Next-generation, higher-valency pneumococcal conjugate vaccines (PCVs), 15-valent PCV V114 and 20-valent PCV (PCV20), have been assessed by comparing their immune responses across serotypes shared with the 13-valent PCV (PCV13). Without efficacy or real-world vaccine effectiveness (VE) it becomes important to relate IgG titers to VE to aid in the interpretation of the immune response elicited by V114 and PCV20.Methods: We estimated the protective antibody concentrations for each serotype in 7-valent PCV (PCV7) and PCV13 which were then used to predict the serotype-specific VE for each PCV7 and PCV13 non PCV7 serotype present in V114 and PCV20.Results: The predicted effectiveness of V114 was comparable to PCV7 and PCV13 for 11 of the 13 shared serotypes (1, 4, 5, 6B, 7F, 9 V, 14, 18C, 19A, 19F, and 23F), with improved effectiveness against serotype 3 and decreased effectiveness against serotype 6A. PCV20 had predicted effectiveness comparable to PCV7 and PCV13 for 7 of the 13 shared serotypes (5, 6A, 7F, 9 V, 18C, 19F, and 23F), with decreased effectiveness against the remaining serotypes (1, 3, 4, 6B, 14, and 19A).Conclusions: Prediction of serotype-specific VE values suggests that V114 retains greater effectiveness than PCV20 toward most serotypes present in PCV7 and PCV13.

Summary of results from the review of MTDs and approved doses

In vaccine efficacy trials, inaccurate counting of infection cases leads to systematic under-estimation-or "dilution"-of vaccine efficacy. In particular, if a sufficient fraction of observed cases are false positives, apparent efficacy will be greatly reduced, leading to unwarranted no-go decisions in vaccine development. Here, we propose a range of replicate testing strategies to address this problem, considering the additional challenge of uncertainty in both infection incidence and diagnostic assay specificity/sensitivity. A strategy that counts an infection case only if a majority of replicate assays return a positive result can substantially reduce efficacy dilution for assays with non-systematic (i.e., "random") errors. We also find that a cost-effective variant of this strategy, using confirmatory assays only if an initial assay is positive, yields a comparable benefit. In clinical trials, where frequent longitudinal samples are needed to detect short-lived infections, this "confirmatory majority rule" strategy can prevent the accumulation of false positives from magnifying efficacy dilution. When widespread public health screening is used for viruses, such as SARS-CoV-2, that have non-differentiating features or may be asymptomatic, these strategies can also serve to reduce unneeded isolations caused by false positives.

Additional details and examples referred to in article

All data used for quantitative analysis in review, with links to references and additional details

Human respiratory syncytial virus (RSV) causes a substantial proportion of respiratory tract infections worldwide. Although RSV reinfections occur throughout life, older adults, particularly those with underlying comorbidities, are at risk for severe complications from RSV. There is no RSV vaccine available to date, and treatment of RSV in adults is largely supportive. A correlate of protection for RSV has not yet been established, but antibodies targeting the pre-fusion conformation of the RSV F glycoprotein play an important role in RSV neutralization. We previously reported a Phase 1 study of an mRNA-based vaccine (V171) expressing a pre-fusion-stabilized RSV F protein (mDS-Cav1) in healthy adults. Here, we evaluated an mRNA-based vaccine (V172) expressing a further stabilized RSV pre-fusion F protein (mVRC1). mVRC1 is a single chain version of RSV F with interprotomer disulfides in addition to the stabilizing mutations present in the mDS-Cav1 antigen. The immunogenicity of the two mRNA-based vaccines encoding mVRC1 (V172) or a sequence-optimized version of mDS-Cav1 to improve transcriptional fidelity (V171.2) were compared in RSV-naïve and RSV-experienced African green monkeys (AGMs). V172 induced higher neutralizing antibody titers than V171.2 and demonstrated protection in the AGM challenge model. We conducted a Phase 1, randomized, placebo-controlled, clinical trial of 25 μg, 100 μg, 200 μg, or 300 μg of V172 in healthy older adults (60-79 years old; N = 112) and 100 μg, 200 μg, or 300 μg of V172 in healthy younger adults (18-49 years old; N = 48). The primary clinical objectives were to evaluate the safety and tolerability of V172, and the secondary objective was to evaluate RSV serum neutralization titers. The most commonly reported solicited adverse events were injection-site pain, injection-site swelling, headache, and tiredness. V172 was generally well tolerated in older and younger adults and increased serum neutralizing antibody titers, pre-fusion F-specific competing antibody titers, and RSV F-specific T-cell responses.

Respiratory syncytial virus (RSV) infection is a major cause of respiratory illness in infants and the elderly. Although several vaccines have been developed, none have succeeded in part due to our incomplete understanding of the correlates of immune protection. While both T cells and antibodies play a role, emerging data suggest that antibody-mediated mechanisms alone may be sufficient to provide protection. Therefore, to map the humoral correlates of immunity against RSV, antibody responses across six different vaccines were profiled in a highly controlled nonhuman primate-challenge model. Viral loads were monitored in both the upper and lower respiratory tracts, and machine learning was used to determine the vaccine platform-agnostic antibody features associated with protection. Upper respiratory control was associated with virus-specific IgA levels, neutralization, and complement activity, whereas lower respiratory control was associated with Fc-mediated effector mechanisms. These findings provide critical compartment -specific insights toward the rational development of future vaccines.

Pneumococcal conjugate vaccines (PCVs) have been on the market since the approval of the seven-valent PCV (PCV7) in 2000. PCV7 was subsequently replaced by higher valency vaccines. Higher valency vaccines provide broader serotype coverage against pneumococcal disease, but breakthrough invasive pneumococcal disease (IPD) has been observed [Balsells 2017, Kandasamy 2020] after PCV7 was replaced by PCV13. Furthermore, in clinical trials serotype-specific IgG geometric mean concentrations (GMCs) decreased from PCV7 to PCV13 for shared serotypes, which may contribute to decreased effectiveness observed after the introduction of PCV13 for shared serotypes. Our objective is to predict serotype-specific effectiveness of higher valency PCVs based on IgG concentrations and effectiveness of PCV7. The analysis predicted effectiveness against IPD in UK children for the shared serotypes: 4, 6B, 9V, 14, 18C, 19F, and 23F. First, serotype specific COPs were estimated based on the method of [Siber 2007] using reverse cumulative distribution curves (RCDCs) for IgG levels in placebo- and PCV7-administered subjects and reported serotype-specific PCV7 effectiveness [Andrews 2011]. Then the serotype-specific effectiveness for PCV13 was predicted based on the COPs and the RCDCs for IgG levels in placebo- and PCV13-administered subjects. Predicted serotype-specific COP and PCV13 effectiveness values were compared to those from literature. Similar force of infection and vaccine uptake were assumed. For each serotype, median and 95% prediction interval of COPs and effectiveness were calculated. Most overlapped with the reported median and 95% confidence intervals of COPs and effectiveness in Andrews et al., 2014 [Andrews 2014]. These results build upon what was previously published by Siber. We were able to establish serotype-specific COPs and use the COPs to predict serotype-specific vaccine effectiveness for PCV vaccines. The predicted vaccine effectiveness can be used to inform the public health impact of future vaccination strategies using health economic models.

Use of magnetic resonance (MR) imaging in the emergency department continues to increase. Although computed tomography is the first-line imaging modality for most head and neck emergencies, MR is superior in some situations and imparts no ionizing radiation. This article provides a symptom-based approach to nontraumatic head and neck pathologic conditions most relevant to emergency head and neck MR imaging, emphasizing relevant anatomy, "do not miss" findings affecting clinical management, and features that may aid differentiation from potential mimics. Essential MR sequences and strategies for obtaining high-quality images when faced with patient motion and other technical challenges are also discussed.