Mapping dopaminergic projections in the human brain with resting-state fMRI

The striatum receives dense dopaminergic projections, making it a key region of the dopaminergic system. Its dysfunction has been implicated in various conditions including Parkinson’s disease (PD) and substance use disorder. However, the investigation of dopamine-specific functioning in humans is problematic as current MRI approaches are unable to differentiate between dopaminergic and other projections. Here, we demonstrate that ‘connectopic mapping’ – a novel approach for characterizing fine-grained, overlapping modes of functional connectivity – can be used to map dopaminergic projections in striatum. We applied connectopic mapping to resting-state functional MRI data of the Human Connectome Project (population cohort; N = 839) and selected the second-order striatal connectivity mode for further analyses. We first validated its specificity to dopaminergic projections by demonstrating a high spatial correlation (r = 0.884) with dopamine transporter availability – a marker of dopaminergic projections – derived from DaT SPECT scans of 209 healthy controls. Next, we obtained the subject-specific second-order modes from 20 controls and 39 PD patients scanned under placebo and under dopamine replacement therapy (L-DOPA), and show that our proposed dopaminergic marker tracks PD diagnosis, symptom severity, and sensitivity to L-DOPA. Finally, across 30 daily alcohol users and 38 daily smokers, we establish strong associations with self-reported alcohol and nicotine use. Our findings provide evidence that the second-order mode of functional connectivity in striatum maps onto dopaminergic projections, tracks inter-individual differences in PD symptom severity and L-DOPA sensitivity, and exhibits strong associations with levels of nicotine and alcohol use, thereby offering a new biomarker for dopamine-related (dys)function in the human brain.

Levodopa-Induced Dyskinesia in Parkinson Disease Specifically Associates With Dopaminergic Depletion in Sensorimotor-Related Functional Subregions of the Striatum

PURPOSE

To determine whether the development of levodopa-induced dyskinesia (LID) in Parkinson disease (PD) specifically relates to dopaminergic depletion in sensorimotor-related subregions of the striatum.

METHODS

Our primary study sample consisted of 185 locally recruited PD patients, of which 73 (40%) developed LID. Retrospective 123I-FP-CIT SPECT data were used to quantify the specific dopamine transporter (DAT) binding ratio within distinct functionally defined striatal subregions related to limbic, executive, and sensorimotor systems. Regional DAT levels were contrasted between patients who developed LID (PD + LID) and those who did not (PD-LID) using analysis of covariance models controlled for demographic and clinical features. For validation of the findings and assessment of the evolution of LID-associated DAT changes from an early disease stage, we also studied serial 123I-FP-CIT SPECT data from 343 de novo PD patients enrolled in the Parkinson Progression Marker's Initiative using mixed linear model analysis.

RESULTS

Compared with PD-LID, DAT level reductions in PD + LID patients were most pronounced in the sensorimotor striatal subregion (F = 5.99, P = 0.016) and also significant in the executive-related subregion (F = 5.30, P = 0.023). In the Parkinson Progression Marker's Initiative cohort, DAT levels in PD + LID (n = 161, 47%) were only significantly reduced compared with PD-LID in the sensorimotor striatal subregion (t = -2.05, P = 0.041), and this difference was already present at baseline and remained largely constant over time.

CONCLUSION

Measuring DAT depletion in functionally defined sensorimotor-related striatal regions of interest may provide a more sensitive tool to detect LID-associated dopaminergic changes at an early disease stage and could improve individual prognosis of this common clinical complication in PD.

Exploration of High and Low Frequency Options for Subperception Spinal Cord Stimulation Using Neural Dosing Parameter Relationships: The HALO Study

OBJECTIVES

Subperception spinal cord stimulation (SCS) is described mostly utilizing waveforms that require high energy. However, the necessity of these waveforms for effective subperception has not been established. We aimed to explore whether effective subperception pain relief can be achieved using frequencies below 1 kHz.

MATERIALS AND METHODS

Thirty chronic pain patients implanted with SCS were enrolled as part of a multicenter, real-world, consecutive, observational case series. An effective stimulation location was determined using a novel electric field shape designed to preferentially modulate dorsal horn elements. Subsequently, programs at lower frequencies (600, 400, 200, 100, 50, and 10 Hz) were provided with pulse-width and amplitude adjusted to optimize response.

RESULTS

All tested frequencies (1 kHz down to 10 Hz) provided effective subperception relief, yielding a mean of 66-72% reduction in back, leg, and overall pain. It was found that to maintain analgesia, as frequency was decreased, the electrical or "neural" dose had to be adjusted according to parameter relationships described herein. With the reduction of frequency, we observed a net reduction of charge-per-second, which enabled energy savings of 74% (200 Hz) and 97% (10 Hz) relative to 1 kHz. Furthermore, pain reduction was sustained out to one year, with 85% of patients reporting a preference for frequencies of 400 Hz or below.

CONCLUSIONS

We have derived an electric field configuration and, along with previous learnings in the kHz range, a set of neural dosing parameter relationships (10-10,000 Hz), which enable the expansion of effective subperception SCS to low frequency and achieve major energy savings.

A Bayesian spatial model for neuroimaging data based on biologically informed basis functions

The dominant approach to neuroimaging data analysis employs the voxel as the unit of computation. While convenient, voxels lack biological meaning and their size is arbitrarily determined by the resolution of the image. Here, we propose a multivariate spatial model in which neuroimaging data are characterised as a linearly weighted combination of multiscale basis functions which map onto underlying brain nuclei or networks or nuclei. In this model, the elementary building blocks are derived to reflect the functional anatomy of the brain during the resting state. This model is estimated using a Bayesian framework which accurately quantifies uncertainty and automatically finds the most accurate and parsimonious combination of basis functions describing the data. We demonstrate the utility of this framework by predicting quantitative SPECT images of striatal dopamine function and we compare a variety of basis sets including generic isotropic functions, anatomical representations of the striatum derived from structural MRI, and two different soft functional parcellations of the striatum derived from resting-state fMRI (rfMRI). We found that a combination of ∼50 multiscale functional basis functions accurately represented the striatal dopamine activity, and that functional basis functions derived from an advanced parcellation technique known as Instantaneous Connectivity Parcellation (ICP) provided the most parsimonious models of dopamine function. Importantly, functional basis functions derived from resting fMRI were more accurate than both structural and generic basis sets in representing dopamine function in the striatum for a fixed model order. We demonstrate the translational validity of our framework by constructing classification models for discriminating parkinsonian disorders and their subtypes. Here, we show that ICP approach is the only basis set that performs well across all comparisons and performs better overall than the classical voxel-based approach. This spatial model constitutes an elegant alternative to voxel-based approaches in neuroimaging studies; not only are their atoms biologically informed, they are also adaptive to high resolutions, represent high dimensions efficiently, and capture long-range spatial dependencies, which are important and challenging objectives for neuroimaging data.

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A multivariate spatial model using brain parcellations as basis functions is proposed.

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Brain regions can be modeled as a superposition of multiscale basis functions.

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These basis functions are biologically meaningful and capture spatial dependencies.

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Our framework allows to develop accurate and parsimonious clinical models.

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The model is computationally efficient, enhances power and adapts to high resolutions.

Lower levels of uric acid and striatal dopamine in non-tremor dominant Parkinson's disease subtype

Parkinson’s disease (PD) patients who present with tremor and maintain a predominance of tremor have a better prognosis. Similarly, PD patients with high levels of uric acid (UA), a natural neuroprotectant, have also a better disease course. Our aim was to investigate whether PD motor subtypes differ in their levels of UA, and if these differences correlate with the degree of dopamine transporter (DAT) availability. We included 75 PD patients from whom we collected information about their motor symptoms, DAT imaging and UA concentration levels. Based on the predominance of their motor symptoms, patients were classified into postural instability and gait disorder (PIGD, n = 36), intermediate (I, n = 22), and tremor-dominant (TD, n = 17) subtypes. The levels of UA and striatal DAT were compared across subtypes and the correlation between these two measures was also explored. We found that PIGD patients had lower levels of UA (3.7 vs 4.5 vs 5.3 mg/dL; P<0.001) and striatal DAT than patients with an intermediate or TD phenotype. Furthermore, UA levels significantly correlated with the levels of striatal DAT. We also observed that some PIGD (25%) and I (45%) patients had a predominance of tremor at disease onset. We speculate that UA might be involved in the maintenance of the less damaging TD phenotype and thus also in the conversion from TD to PIGD. Low levels of this natural antioxidant could lead to a major neuronal damage and therefore influence the conversion to a more severe motor phenotype.

Antibiotics for preventing recurrent urinary tract infection in non-pregnant women

BACKGROUND

Urinary tract infection (UTI) is a common health care problem. Recurrent UTI (RUTI) in healthy non-pregnant women is defined as three or more episodes of UTI during a twelve month period. Long-term antibiotics have been proposed as a prevention strategy for RUTI.

OBJECTIVES

To determine the efficacy (during and after) and safety of prophylactic antibiotics used to prevent uncomplicated RUTI in adult non-pregnant women.

SEARCH STRATEGY

We searched MEDLINE (1966-April 2004), EMBASE (1980-January 2003), Cochrane Central Register of Controlled Trials( in The Cochrane Library Issue 1, 2004) and reference lists of retrieved articles

SELECTION CRITERIA

Any published randomised controlled trial where antibiotics were used as prophylactic therapy in RUTI.

DATA COLLECTION AND ANALYSIS

Two reviewers independently assessed trial quality and extracted data. Statistical analyses were performed using the random effects model and the results expressed as relative risk (RR) with 95% confidence intervals (CI).

MAIN RESULTS

Nineteen studies involving 1120 women were eligible for inclusion. Antibiotic versus antibiotic (10 trials, 430 women): During active prophylaxis the rate range of microbiological recurrence patient-year (MRPY) was 0 to 0.9 person-year in the antibiotic group against 0.8 to 3.6 with placebo. The RR of having one microbiological recurrence (MR) was 0.21 (95% CI 0.13 to 0.34), favouring antibiotic and the NNT was 1.85. For clinical recurrences (CRPY) the RR was 0.15 (95% CI 0.08 to 0.28). The NNT was 1.85. The RR of having one MR after prophylaxis was 0.82 (95% CI 0.44 to 1.53). The RR for severe side effects was 1.58 (95% CI 0.47 to 5.28) and for other side effects the RR was 1.78 (CI 1.06 to 3.00) favouring placebo. Side effects included vaginal and oral candidiasis and gastrointestinal symptoms. Antibiotic versus antibiotic (eight trials, 513 women): These trials were not pooled. Weekly pefloxacin was more effective than monthly. The RR for MR was 0.31(95% CI 0.19 to 0.52). There was no significant difference in MR between continuous daily and postcoital ciprofloxacin.

REVIEWERS' CONCLUSIONS

Continuous antibiotic prophylaxis for 6-12 months reduced the rate of UTI during prophylaxis when compared to placebo. After prophylaxis two studies showed nodifference between groups. There were more adverse events in the antibiotic group. One RCT compared postcoital versus continuous daily ciprofloxacin and found no significant difference in rates of UTIs, suggesting that postcoital treatment could be offered to woman who have UTI associated with sexual intercourse.