Are there differences between patients with unifocal nummular headache and those who progress to bifocal nummular headache? A retrospective observational study.

OBJECTIVES: This retrospective observational cohort study aimed to compare clinical characteristics and treatment responses in patients exclusively experiencing unifocal nummular headache (NH) with those who develop the bifocal variant. METHODS: A retrospective study was conducted on patients diagnosed with NH who attended a neurology (headache) outpatient clinic between January 2018 and December 2022. The cohort was divided into two groups: Group 1, exclusive unifocal NH; and Group 2, those developing a secondary focal area of pain, i.e., bifocal NH. Data were collected on demographic characteristics, clinical features, other headache comorbidities, and treatment-related information. RESULTS: A total of 23 patients were included in this study: 12 were categorized as unifocal NH (Group 1) and 11 as bifocal NH (Group 2). There were no differences between the two groups in terms of demographic characteristics, clinical features, or treatment response. Nonetheless, patients with bifocal NH exhibited spontaneous remission rates in the first pain area when compared to the unifocal NH group, with statistically significant differences (36% vs. 0%, p = 0.020). CONCLUSION: In our sample, patients with bifocal NH demonstrated spontaneous remission rates in the initial pain area, a phenomenon not observed in patients with unifocal NH. It is worth noting the limited sample size in the present study, highlighting the need for larger cohorts to validate and further explore our findings.

Brain perfusion imaging by multi-delay arterial spin labeling: Impact of modeling dispersion and interaction with denoising strategies and pathology.

PURPOSE: Arterial spin labeling (ASL) acquisitions at multiple post-labeling delays may provide more accurate quantification of cerebral blood flow (CBF), by fitting appropriate kinetic models and simultaneously estimating relevant parameters such as the arterial transit time (ATT) and arterial cerebral blood volume (aCBV). We evaluate the effects of denoising strategies on model fitting and parameter estimation when accounting for the dispersion of the label bolus through the vasculature in cerebrovascular disease. METHODS: We analyzed multi-delay ASL data from 17 cerebral small vessel disease patients (50 ± 9 y) and 13 healthy controls (52 ± 8 y), by fitting an extended kinetic model with or without bolus dispersion. We considered two denoising strategies: removal of structured noise sources by independent component analysis (ICA) of the control-label image timeseries; and averaging the repetitions of the control-label images prior to model fitting. RESULTS: Modeling bolus dispersion improved estimation precision and impacted parameter values, but these effects strongly depended on whether repetitions were averaged before model fitting. In general, repetition averaging improved model fitting but adversely affected parameter values, particularly CBF and aCBV near arterial locations in patients. This suggests that using all repetitions allows better noise estimation at the earlier delays. In contrast, ICA denoising improved model fitting and estimation precision while leaving parameter values unaffected. CONCLUSION: Our results support the use of ICA denoising to improve model fitting to multi-delay ASL and suggest that using all control-label repetitions improves the estimation of macrovascular signal contributions and hence perfusion quantification near arterial locations. This is important when modeling flow dispersion in cerebrovascular pathology.