Macrovascular blood flow and microvascular cerebrovascular reactivity are regionally coupled in adolescence.

Cerebrovascular imaging assessments are particularly challenging in adolescent cohorts, where not all modalities are appropriate, and rapid brain maturation alters hemodynamics at both macro- and microvascular scales. In a preliminary sample of healthy adolescents (n=12, 8-25 years), we investigated relationships between 4D flow MRI-derived blood velocity and blood flow in bilateral anterior, middle, and posterior cerebral arteries and BOLD cerebrovascular reactivity in associated vascular territories. As hypothesized, higher velocities in large arteries are associated with an earlier response to a vasodilatory stimulus (cerebrovascular reactivity delay) in the downstream territory. Higher blood flow through these arteries is associated with a larger BOLD response to a vasodilatory stimulus (cerebrovascular reactivity amplitude) in the associated territory. These trends are consistent in a case study of adult moyamoya disease. In our small adolescent cohort, macrovascular-microvascular relationships for velocity/delay and flow/CVR change with age, though underlying mechanisms are unclear. Our work emphasizes the need to better characterize this key stage of human brain development, when cerebrovascular hemodynamics are changing, and standard imaging methods offer limited insight into these processes. We provide important normative data for future comparisons in pathology, where combining macro- and microvascular assessments may better help us prevent, stratify, and treat cerebrovascular disease.

Physics-informed Deep Learning for Dual-Energy Computed Tomography Image Processing.

Dual-energy CT (DECT) was introduced to address the inability of conventional single-energy computed tomography (SECT) to distinguish materials with similar absorbances but different elemental compositions. However, material decomposition algorithms based purely on the physics of the underlying attenuation process have several limitations, leading to low signal-to-noise ratio (SNR) in the derived material-specific images. To overcome these, we trained a convolutional neural network (CNN) to develop a framework to reconstruct non-contrast SECT images from DECT scans. We show that the traditional physics-based decomposition algorithms do not bring to bear the full information content of the image data. A CNN that leverages the underlying physics of the DECT image generation process as well as the anatomic information gleaned via training with actual images can generate higher fidelity processed DECT images.

Effects of STN and GPi deep brain stimulation on impulse control disorders and dopamine dysregulation syndrome.

OBJECTIVE: Impulse control disorders (ICDs) and dopamine dysregulation syndrome (DDS) are important behavioral problems that affect a subpopulation of patients with Parkinson's disease (PD) and typically result in markedly diminished quality of life for patients and their caregivers. We aimed to investigate the effects of subthalamic nucleus (STN) and internal globus pallidus (GPi) deep brain stimulation (DBS) on ICD/DDS frequency and dopaminergic medication usage. METHODS: A retrospective chart review was performed on 159 individuals who underwent unilateral or bilateral PD DBS surgery in either STN or GPi. According to published criteria, pre- and post-operative records were reviewed to categorize patients both pre- and post-operatively as having ICD, DDS, both ICD and DDS, or neither ICD nor DDS. Group differences in patient demographics, clinical presentations, levodopa equivalent dose (LED), and change in diagnosis following unilateral/bilateral by brain target (STN or GPi DBS placement) were examined. RESULTS: 28 patients met diagnostic criteria for ICD or DDS pre- or post-operatively. ICD or DDS classification did not differ by GPi or STN target stimulation. There was no change in DDS diagnosis after unilateral or bilateral stimulation. For ICD, diagnosis resolved in 2 of 7 individuals after unilateral or bilateral DBS. Post-operative development of these syndromes was significant; 17 patients developed ICD diagnoses post-operatively with 2 patients with pre-operative ICD developing DDS post-operatively. CONCLUSIONS: Unilateral or bilateral DBS did not significantly treat DDS or ICD in our sample, even though a few cases of ICD resolved post-operatively. Rather, our study provides preliminary evidence that DDS and ICD diagnoses may emerge following DBS surgery.

Addiction-like manifestations and Parkinson's disease: a large single center 9-year experience.

OBJECTIVE: Characterize potential risk factors and the relationship of dopamine agonist (DA) withdrawal syndrome (DAWS), dopamine dysregulation syndrome (DDS), and impulse control disorders (ICDs) in Parkinson's disease (PD). METHODS: A retrospective chart review categorized cases into three groups: DAWS, DDS, and ICDs. RESULTS: A total of 1,040 subjects met inclusion criteria. There were 332 subjects with a history of tapering DAs and 26 (7.8%) developed DAWS. Fourteen (1.3%) and 89 (8.6%) met the criteria for both DDS and ICD. Subjects with DAWS, DDS, and ICDs had a higher baseline dose of DA, levodopa, and total dopaminergic medication (p < .05), compared to those without the three conditions. DDS was found to be related to the DAWS group (p < .001). When comparing to the PD population without DDS, younger age at onset of PD (p = .027), presence of DAWS (p < .001), ICDs (p = .003), and punding (p = .042) were all correlated with the DDS group, while male sex (p = .045), younger age at onset of PD (p < .001), presence of DAWS (p < .001), and presence of DDS (p = .001) and punding (p < .001) were related to the ICD group. CONCLUSIONS: There was a strong relationship between DAWS, DDS, and ICD in this large PD cohort. Dopaminergic therapy in a subset of PD patients was strongly associated with addiction-like behavioral issues.