A global optimisation method for robust affine registration of brain images

Registration is an important component of medical image analysis and for analysing large amounts of data it is desirable to have fully automatic registration methods. Many different automatic registration methods have been proposed to date, and almost all share a common mathematical framework - one of optimising a cost function. To date little attention has been focused on the optimisation method itself, even though the success of most registration methods hinges on the quality of this optimisation. This paper examines the assumptions underlying the problem of registration for brain images using inter-modal voxel similarity measures. It is demonstrated that the use of local optimisation methods together with the standard multi-resolution approach is not sufficient to reliably find the global minimum. To address this problem, a global optimisation method is proposed that is specifically tailored to this form of registration. A full discussion of all the necessary implementation details is included as this is an important part of any practical method. Furthermore, results are presented for inter-modal, inter-subject registration experiments that show that the proposed method is more reliable at finding the global minimum than several of the currently available registration packages in common usage.

Segmentation of brain MR images through a hidden Markov random field model and the expectation-maximization algorithm

The finite mixture (FM) model is the most commonly used model for statistical segmentation of brain magnetic resonance (MR) images because of its simple mathematical form and the piecewise constant nature of ideal brain MR images. However, being a histogram-based model, the FM has an intrinsic limitation--no spatial information is taken into account. This causes the FM model to work only on well-defined images with low levels of noise; unfortunately, this is often not the the case due to artifacts such as partial volume effect and bias field distortion. Under these conditions, FM model-based methods produce unreliable results. In this paper, we propose a novel hidden Markov random field (HMRF) model, which is a stochastic process generated by a MRF whose state sequence cannot be observed directly but which can be indirectly estimated through observations. Mathematically, it can be shown that the FM model is a degenerate version of the HMRF model. The advantage of the HMRF model derives from the way in which the spatial information is encoded through the mutual influences of neighboring sites. Although MRF modeling has been employed in MR image segmentation by other researchers, most reported methods are limited to using MRF as a general prior in an FM model-based approach. To fit the HMRF model, an EM algorithm is used. We show that by incorporating both the HMRF model and the EM algorithm into a HMRF-EM framework, an accurate and robust segmentation can be achieved. More importantly, the HMRF-EM framework can easily be combined with other techniques. As an example, we show how the bias field correction algorithm of Guillemaud and Brady (1997) can be incorporated into this framework to achieve a three-dimensional fully automated approach for brain MR image segmentation.

Consistent resting-state networks across healthy subjects

Functional MRI (fMRI) can be applied to study the functional connectivity of the human brain. It has been suggested that fluctuations in the blood oxygenation level-dependent (BOLD) signal during rest reflect the neuronal baseline activity of the brain, representing the state of the human brain in the absence of goal-directed neuronal action and external input, and that these slow fluctuations correspond to functionally relevant resting-state networks. Several studies on resting fMRI have been conducted, reporting an apparent similarity between the identified patterns. The spatial consistency of these resting patterns, however, has not yet been evaluated and quantified. In this study, we apply a data analysis approach called tensor probabilistic independent component analysis to resting-state fMRI data to find coherencies that are consistent across subjects and sessions. We characterize and quantify the consistency of these effects by using a bootstrapping approach, and we estimate the BOLD amplitude modulation as well as the voxel-wise cross-subject variation. The analysis found 10 patterns with potential functional relevance, consisting of regions known to be involved in motor function, visual processing, executive functioning, auditory processing, memory, and the so-called default-mode network, each with BOLD signal changes up to 3%. In general, areas with a high mean percentage BOLD signal are consistent and show the least variation around the mean. These findings show that the baseline activity of the brain is consistent across subjects exhibiting significant temporal dynamics, with percentage BOLD signal change comparable with the signal changes found in task-related experiments.

Characterization and propagation of uncertainty in diffusion-weighted MR imaging

A fully probabilistic framework is presented for estimating local probability density functions on parameters of interest in a model of diffusion. This technique is applied to the estimation of parameters in the diffusion tensor model, and also to a simple partial volume model of diffusion. In both cases the parameters of interest include parameters defining local fiber direction. A technique is then presented for using these density functions to estimate global connectivity (i.e., the probability of the existence of a connection through the data field, between any two distant points), allowing for the quantification of belief in tractography results. This technique is then applied to the estimation of the cortical connectivity of the human thalamus. The resulting connectivity distributions correspond well with predictions from invasive tracer methods in nonhuman primate.

Temporal autocorrelation in univariate linear modeling of FMRI data

In functional magnetic resonance imaging statistical analysis there are problems with accounting for temporal autocorrelations when assessing change within voxels. Techniques to date have utilized temporal filtering strategies to either shape these autocorrelations or remove them. Shaping, or "coloring," attempts to negate the effects of not accurately knowing the intrinsic autocorrelations by imposing known autocorrelation via temporal filtering. Removing the autocorrelation, or "prewhitening," gives the best linear unbiased estimator, assuming that the autocorrelation is accurately known. For single-event designs, the efficiency of the estimator is considerably higher for prewhitening compared with coloring. However, it has been suggested that sufficiently accurate estimates of the autocorrelation are currently not available to give prewhitening acceptable bias. To overcome this, we consider different ways to estimate the autocorrelation for use in prewhitening. After high-pass filtering is performed, a Tukey taper (set to smooth the spectral density more than would normally be used in spectral density estimation) performs best. Importantly, estimation is further improved by using nonlinear spatial filtering to smooth the estimated autocorrelation, but only within tissue type. Using this approach when prewhitening reduced bias to close to zero at probability levels as low as 1 x 10(-5).

A single ataxia telangiectasia gene with a product similar to PI-3 kinase

A gene, ATM, that is mutated in the autosomal recessive disorder ataxia telangiectasia (AT) was identified by positional cloning on chromosome 11q22-23. AT is characterized by cerebellar degeneration, immunodeficiency, chromosomal instability, cancer predisposition, radiation sensitivity, and cell cycle abnormalities. The disease is genetically heterogeneous, with four complementation groups that have been suspected to represent different genes. ATM, which has a transcript of 12 kilobases, was found to be mutated in AT patients from all complementation groups, indicating that it is probably the sole gene responsible for this disorder. A partial ATM complementary DNA clone of 5.9 kilobases encoded a putative protein that is similar to several yeast and mammalian phosphatidylinositol-3' kinases that are involved in mitogenic signal transduction, meiotic recombination, and cell cycle control. The discovery of ATM should enhance understanding of AT and related syndromes and may allow the identification of AT heterozygotes, who are at increased risk of cancer.

Non-invasive mapping of connections between human thalamus and cortex using diffusion imaging

Evidence concerning anatomical connectivities in the human brain is sparse and based largely on limited post-mortem observations. Diffusion tensor imaging has previously been used to define large white-matter tracts in the living human brain, but this technique has had limited success in tracing pathways into gray matter. Here we identified specific connections between human thalamus and cortex using a novel probabilistic tractography algorithm with diffusion imaging data. Classification of thalamic gray matter based on cortical connectivity patterns revealed distinct subregions whose locations correspond to nuclei described previously in histological studies. The connections that we found between thalamus and cortex were similar to those reported for non-human primates and were reproducible between individuals. Our results provide the first quantitative demonstration of reliable inference of anatomical connectivity between human gray matter structures using diffusion data and the first connectivity-based segmentation of gray matter.

The Human Connectome Project: a data acquisition perspective

The Human Connectome Project (HCP) is an ambitious 5-year effort to characterize brain connectivity and function and their variability in healthy adults. This review summarizes the data acquisition plans being implemented by a consortium of HCP investigators who will study a population of 1200 subjects (twins and their non-twin siblings) using multiple imaging modalities along with extensive behavioral and genetic data. The imaging modalities will include diffusion imaging (dMRI), resting-state fMRI (R-fMRI), task-evoked fMRI (T-fMRI), T1- and T2-weighted MRI for structural and myelin mapping, plus combined magnetoencephalography and electroencephalography (MEG/EEG). Given the importance of obtaining the best possible data quality, we discuss the efforts underway during the first two years of the grant (Phase I) to refine and optimize many aspects of HCP data acquisition, including a new 7T scanner, a customized 3T scanner, and improved MR pulse sequences.

Community study of role of viral infections in exacerbations of asthma in 9-11 year old children

OBJECTIVE

To study the association between upper and lower respiratory viral infections and acute exacerbations of asthma in schoolchildren in the community.

DESIGN

Community based 13 month longitudinal study using diary card respiratory symptom and peak expiratory flow monitoring to allow early sampling for viruses.

SUBJECTS

108 Children aged 9-11 years who had reported wheeze or cough, or both, in a questionnaire.

SETTING

Southampton and surrounding community.

MAIN OUTCOME MEASURES

Upper and lower respiratory viral infections detected by polymerase chain reaction or conventional methods, reported exacerbations of asthma, computer identified episodes of respiratory tract symptoms or peak flow reductions.

RESULTS

Viruses were detected in 80% of reported episodes of reduced peak expiratory flow, 80% of reported episodes of wheeze, and in 85% of reported episodes of upper respiratory symptoms, cough, wheeze, and a fall in peak expiratory flow. The median duration of reported falls in peak expiratory flow was 14 days, and the median maximum fall in peak expiratory flow was 81 l/min. The most commonly identified virus type was rhinovirus.

CONCLUSIONS

This study supports the hypothesis that upper respiratory viral infections are associated with 80-85% of asthma exacerbations in school age children.

Reduced resting-state brain activity in the "default network" in normal aging

Normal aging is associated with cognitive decline. Functions such as attention, information processing, and working memory are compromised. It has been hypothesized that not only regional changes, but also alterations in the integration of regional brain activity (functional brain connectivity) underlie the observed age-related deficits. Here, we examined the functional properties of brain networks based on spontaneous fluctuations within brain systems using functional magnetic resonance imaging. We hypothesized that functional connectivity of intrinsic brain activity in the "default-mode" network (DMN) is affected by normal aging and that this relates to cognitive function. Ten younger and 22 older subjects were scanned at "rest," that is, lying awake with eyes closed. Our results show decreased activity in older versus younger subjects in 2 resting-state networks (RSNs) resembling the previously described DMN, containing the superior and middle frontal gyrus, posterior cingulate, middle temporal gyrus, and the superior parietal region. These results remain significant after correction for RSN-specific gray matter volume. The relevance of these findings is illustrated by the correlation between reduced activity of one of these RSNs and less effective executive functioning/processing speed in the older group.

fMRI resting state networks define distinct modes of long-distance interactions in the human brain

Functional magnetic resonance imaging (fMRI) studies of the human brain have suggested that low-frequency fluctuations in resting fMRI data collected using blood oxygen level dependent (BOLD) contrast correspond to functionally relevant resting state networks (RSNs). Whether the fluctuations of resting fMRI signal in RSNs are a direct consequence of neocortical neuronal activity or are low-frequency artifacts due to other physiological processes (e.g., autonomically driven fluctuations in cerebral blood flow) is uncertain. In order to investigate further these fluctuations, we have characterized their spatial and temporal properties using probabilistic independent component analysis (PICA), a robust approach to RSN identification. Here, we provide evidence that: i. RSNs are not caused by signal artifacts due to low sampling rate (aliasing); ii. they are localized primarily to the cerebral cortex; iii. similar RSNs also can be identified in perfusion fMRI data; and iv. at least 5 distinct RSN patterns are reproducible across different subjects. The RSNs appear to reflect "default" interactions related to functional networks related to those recruited by specific types of cognitive processes. RSNs are a major source of non-modeled signal in BOLD fMRI data, so a full understanding of their dynamics will improve the interpretation of functional brain imaging studies more generally. Because RSNs reflect interactions in cognitively relevant functional networks, they offer a new approach to the characterization of state changes with pathology and the effects of drugs.

Tankyrase, a poly(ADP-ribose) polymerase at human telomeres

Tankyrase, a protein with homology to ankyrins and to the catalytic domain of poly(adenosine diphosphate-ribose) polymerase (PARP), was identified and localized to human telomeres. Tankyrase binds to the telomeric protein TRF1 (telomeric repeat binding factor-1), a negative regulator of telomere length maintenance. Like ankyrins, tankyrase contains 24 ankyrin repeats in a domain responsible for its interaction with TRF1. Recombinant tankyrase was found to have PARP activity in vitro, with both TRF1 and tankyrase functioning as acceptors for adenosine diphosphate (ADP)-ribosylation. ADP-ribosylation of TRF1 diminished its ability to bind to telomeric DNA in vitro, suggesting that telomere function in human cells is regulated by poly(ADP-ribosyl)ation.

Transgenic plant aequorin reports the effects of touch and cold-shock and elicitors on cytoplasmic calcium

Methods for measuring plant cytoplasmic calcium using microelectrodes or microinjected fluorescent dyes are associated with extensive technical problems, so measurements have been limited to single or small groups of cells in tissue strips or protoplasts. Aequorin is a calcium-sensitive luminescent protein from the coelenterate Aequorea victoria (A. forskalea) which is formed from apoaequorin, a polypeptide of relative molecular mass approximately 22,000, and coelenterazine, a hydrophobic luminophore. Microinjected aequorin has been widely used for intracellular calcium measurement in animal cells, but its use in plants has been limited to exceptionally large cells. We show here that aequorin can be reconstituted in transformed plants and that it reports calcium changes induced by touch, cold-shock and fungal elicitors. Reconstituted aequorin is cytoplasmic and nonperturbing; measurements can be made on whole plants and a calcium indicator can be constituted in every viable cell. Now that apoaequorin can be targeted to specific organelles, cells and tissues, with the range of coelenterazines with differing calcium sensitivities and properties available, this new method could be valuable for determining the role of calcium in intracellular signalling processes in plants.

Purification and characterization of CAF-I, a human cell factor required for chromatin assembly during DNA replication in vitro

The purification and characterization of a replication-dependent chromatin assembly factor (CAF-I) from the nuclei of human cells is described. CAF-I is a multisubunit protein that, when added to a crude cytosol replication extract, promotes chromatin assembly on replicating SV40 DNA. Chromatin assembly by CAF-I requires and is coupled with DNA replication. The minichromosomes assembled de novo by CAF-I consist of correctly spaced nucleosomes containing the four core histones H2A, H2B, H3, and H4, which are supplied in a soluble form by the cytosol replication extract. Thus, by several criteria, the CAF-I-dependent chromatin assembly reaction described herein reflects the process of chromatin formation during DNA replication in vivo.

Changes in connectivity profiles define functionally distinct regions in human medial frontal cortex

A fundamental issue in neuroscience is the relation between structure and function. However, gross landmarks do not correspond well to microstructural borders and cytoarchitecture cannot be visualized in a living brain used for functional studies. Here, we used diffusion-weighted and functional MRI to test structure-function relations directly. Distinct neocortical regions were defined as volumes having similar connectivity profiles and borders identified where connectivity changed. Without using prior information, we found an abrupt profile change where the border between supplementary motor area (SMA) and pre-SMA is expected. Consistent with this anatomical assignment, putative SMA and pre-SMA connected to motor and prefrontal regions, respectively. Excellent spatial correlations were found between volumes defined by using connectivity alone and volumes activated during tasks designed to involve SMA or pre-SMA selectively. This finding demonstrates a strong relationship between structure and function in medial frontal cortex and offers a strategy for testing such correspondences elsewhere in the brain.

Task-free MRI predicts individual differences in brain activity during task performance

When asked to perform the same task, different individuals exhibit markedly different patterns of brain activity. This variability is often attributed to volatile factors, such as task strategy or compliance. We propose that individual differences in brain responses are, to a large degree, inherent to the brain and can be predicted from task-independent measurements collected at rest. Using a large set of task conditions, spanning several behavioral domains, we train a simple model that relates task-independent measurements to task activity and evaluate the model by predicting task activation maps for unseen subjects using magnetic resonance imaging. Our model can accurately predict individual differences in brain activity and highlights a coupling between brain connectivity and function that can be captured at the level of individual subjects.

Matrix metalloproteinase 13-deficient mice are resistant to osteoarthritic cartilage erosion but not chondrocyte hypertrophy or osteophyte development

OBJECTIVE

To investigate the role of matrix metalloproteinase 13 (MMP-13; collagenase 3) in osteoarthritis (OA).

METHODS

OA was surgically induced in the knees of MMP-13-knockout mice and wild-type mice, and mice were compared. Histologic scoring of femoral and tibial cartilage aggrecan loss (0-3 scale), erosion (0-7 scale), and chondrocyte hypertrophy (0-1 scale), as well as osteophyte size (0-3 scale) and maturity (0-3 scale) was performed. Serial sections were stained for type X collagen and the MMP-generated aggrecan neoepitope DIPEN.

RESULTS

Following surgery, aggrecan loss and cartilage erosion were more severe in the tibia than femur (P<0.01) and tibial cartilage erosion increased with time (P<0.05) in wild-type mice. Cartilaginous osteophytes were present at 4 weeks and underwent ossification, with size and maturity increasing by 8 weeks (P<0.01). There was no difference between genotypes in aggrecan loss or cartilage erosion at 4 weeks. There was less tibial cartilage erosion in knockout mice than in wild-type mice at 8 weeks (P<0.02). Cartilaginous osteophytes were larger in knockout mice at 4 weeks (P<0.01), but by 8 weeks osteophyte maturity and size were no different from those in wild-type mice. Articular chondrocyte hypertrophy with positive type X collagen and DIPEN staining occurred in both wild-type and knockout mouse joints.

CONCLUSION

Our findings indicate that structural cartilage damage in a mouse model of OA is dependent on MMP-13 activity. Chondrocyte hypertrophy is not regulated by MMP-13 activity in this model and does not in itself lead to cartilage erosion. MMP-13 deficiency can inhibit cartilage erosion in the presence of aggrecan depletion, supporting the potential for therapeutic intervention in established OA with MMP-13 inhibitors.

Effects of ramipril and vitamin E on atherosclerosis: the study to evaluate carotid ultrasound changes in patients treated with ramipril and vitamin E (SECURE)

BACKGROUND

Activation of the renin-angiotensin-aldosterone system and oxidative modification of LDL cholesterol play important roles in atherosclerosis. The Study to Evaluate Carotid Ultrasound changes in patients treated with Ramipril and vitamin E (SECURE), a substudy of the Heart Outcomes Prevention Evaluation (HOPE) trial, was a prospective, double-blind, 3x2 factorial design trial that evaluated the effects of long-term treatment with the angiotensin-converting enzyme inhibitor ramipril and vitamin E on atherosclerosis progression in high-risk patients.

METHODS AND RESULTS

A total of 732 patients >/=55 years of age who had vascular disease or diabetes and at least one other risk factor and who did not have heart failure or a low left ventricular ejection fraction were randomly assigned to receive ramipril 2.5 mg/d or 10 mg/d and vitamin E (RRR-alpha-tocopheryl acetate) 400 IU/d or their matching placebos. Average follow-up was 4.5 years. Atherosclerosis progression was evaluated by B-mode carotid ultrasound. The progression slope of the mean maximum carotid intimal medial thickness was 0.0217 mm/year in the placebo group, 0.0180 mm/year in the ramipril 2.5 mg/d group, and 0.0137 mm/year in the ramipril 10 mg/d group (P=0.033). There were no differences in atherosclerosis progression rates between patients on vitamin E and those on placebo.

CONCLUSIONS

Long-term treatment with ramipril had a beneficial effect on atherosclerosis progression. Vitamin E had a neutral effect on atherosclerosis progression.

Conservation of position and exclusive expression of mouse Xist from the inactive X chromosome

X-chromosome inactivation in mammals is a regulatory phenomenon whereby one of the two X chromosomes in female cells is genetically inactivated, resulting in dosage compensation for X-linked genes between males and females. In both man and mouse, X-chromosome inactivation is thought to proceed from a single cis-acting switch region or inactivation centre (XIC/Xic). In the human, XIC has been mapped to band Xq13 (ref. 6) and in the mouse to band XD (ref. 7), and comparative mapping has shown that the XIC regions in the two species are syntenic. The recently described human XIST gene maps to the XIC region and seems to be expressed only from the inactive X chromosome. We report here that the mouse Xist gene maps to the Xic region of the mouse X chromosome and, using an interspecific Mus spretus/Mus musculus domesticus F1 hybrid mouse carrying the T(X;16)16H translocation, show that Xist is exclusively expressed from the inactive X chromosome. Conservation between man and mouse of chromosomal position and unique expression exclusively from the inactive X chromosome lends support to the hypothesis that XIST and its mouse homologue are involved in X-chromosome inactivation.

Tensorial extensions of independent component analysis for multisubject FMRI analysis

We discuss model-free analysis of multisubject or multisession FMRI data by extending the single-session probabilistic independent component analysis model (PICA; Beckmann and Smith, 2004. IEEE Trans. on Medical Imaging, 23 (2) 137-152) to higher dimensions. This results in a three-way decomposition that represents the different signals and artefacts present in the data in terms of their temporal, spatial, and subject-dependent variations. The technique is derived from and compared with parallel factor analysis (PARAFAC; Harshman and Lundy, 1984. In Research methods for multimode data analysis, chapter 5, pages 122-215. Praeger, New York). Using simulated data as well as data from multisession and multisubject FMRI studies we demonstrate that the tensor PICA approach is able to efficiently and accurately extract signals of interest in the spatial, temporal, and subject/session domain. The final decompositions improve upon PARAFAC results in terms of greater accuracy, reduced interference between the different estimated sources (reduced cross-talk), robustness (against deviations of the data from modeling assumptions and against overfitting), and computational speed. On real FMRI 'activation' data, the tensor PICA approach is able to extract plausible activation maps, time courses, and session/subject modes as well as provide a rich description of additional processes of interest such as image artefacts or secondary activation patterns. The resulting data decomposition gives simple and useful representations of multisubject/multisession FMRI data that can aid the interpretation and optimization of group FMRI studies beyond what can be achieved using model-based analysis techniques.

The relationship between upper respiratory infections and hospital admissions for asthma: a time-trend analysis

We have shown that viruses are associated with 80 to 85% of asthma exacerbations in school-age children in the community. We hypothesize that viral infections are also associated with severe attacks of asthma precipitating hospital admissions. To investigate this, we conducted a time-trend analysis, comparing the seasonal patterns of respiratory infections and hospital admissions for asthma in adults and children. During a 1-yr study in the Southampton area of the United Kingdom, 108 school-age children monitored upper and lower respiratory symptoms and took peak expiratory flow rate (PEFR) recordings. From children reporting a symptomatic episode or a decrease in PEFR, samples were taken for detection of viruses and atypical bacteria. A total of 232 respiratory viruses and four atypical bacteria were detected. The half-monthly rates of upper respiratory infection were compared with the half-monthly rates for hospital admissions for asthma (International Classification of Diseases [ICD] code 493) for the same time period for the hospitals serving the areas from which the cohort of schoolchildren was drawn. The relationships of upper respiratory infections and hospital admissions for asthma with school attendance were studied. Strong correlations were found between the seasonal patterns of upper respiratory infections and hospital admissions for asthma (r = 0.72; p < 0.0001). This relationship was stronger for pediatric (r = 0.68; p < 0.0001) than for adult admissions (r = 0.53; p < 0.01). Upper respiratory infections and admissions for asthma were more frequent during periods of school attendance (87% of pediatric and 84% of total admissions), than during school holiday periods (p < 0.001). These relationships remained significant when allowance was made for linear trend and seasonal variation using multiple regression analysis (p < 0.01). Not surprisingly, school attendance, because it is a major factor in respiratory virus transmission, was found to be a major confounding variable in children. This study demonstrates that upper respiratory viral infections are strongly associated in time with hospital admissions for asthma in children and adults. Rhinoviruses were the major pathogen implicated, and the majority of viral infections and asthma admissions occurred during school attendance.

Large-scale temporal gene expression mapping of central nervous system development

We used reverse transcription-coupled PCR to produce a high-resolution temporal map of fluctuations in mRNA expression of 112 genes during rat central nervous system development, focusing on the cervical spinal cord. The data provide a temporal gene expression "fingerprint" of spinal cord development based on major families of inter- and intracellular signaling genes. By using distance matrices for the pair-wise comparison of these 112 temporal gene expression patterns as the basis for a cluster analysis, we found five basic "waves" of expression that characterize distinct phases of development. The results suggest functional relationships among the genes fluctuating in parallel. We found that genes belonging to distinct functional classes and gene families clearly map to particular expression profiles. The concepts and data analysis discussed herein may be useful in objectively identifying coherent patterns and sequences of events in the complex genetic signaling network of development. Functional genomics approaches such as this may have applications in the elucidation of complex developmental and degenerative disorders.

Generation of political priority for global health initiatives: a framework and case study of maternal mortality

Why do some global health initiatives receive priority from international and national political leaders whereas others receive little attention? To analyse this question we propose a framework consisting of four categories: the strength of the actors involved in the initiative, the power of the ideas they use to portray the issue, the nature of the political contexts in which they operate, and characteristics of the issue itself. We apply this framework to the case of a global initiative to reduce maternal mortality, which was launched in 1987. We undertook archival research and interviewed people connected with the initiative, using a process-tracing method that is commonly employed in qualitative research. We report that despite two decades of effort the initiative remains in an early phase of development, hampered by difficulties in all these categories. However, the initiative's 20th year, 2007, presents opportunities to build political momentum. To generate political priority, advocates will need to address several challenges, including the creation of effective institutions to guide the initiative and the development of a public positioning of the issue to convince political leaders to act. We use the framework and case study to suggest areas for future research on the determinants of political priority for global health initiatives, which is a subject that has attracted much speculation but little scholarship.