Acute nicotinamide riboside supplementation increases human cerebral NAD+ levels in vivo.

PURPOSE: The purpose of this study was to determine the effect of acute nicotinamide riboside (NR) supplementation on cerebral nicotinamide adenine dinucleotide (NAD+) levels in the human brain in vivo by means of downfield proton MRS (DF 1H MRS). METHODS: DF 1H MRS was performed on 10 healthy volunteers in a 7.0 T MRI scanner with spectrally selective excitation and spatially selective localization to determine cerebral NAD+ levels on two back-to-back days: once after an overnight fast (baseline) and once 4 h after oral ingestion of nicotinamide riboside (900 mg). Additionally, two more baseline scans were performed following the same paradigm to assess test-retest reliability of the NAD+ levels in the absence of NR. RESULTS: NR supplementation increased mean NAD+ concentration compared to the baseline (0.458 ± 0.053 vs. 0.392 ± 0.058 mM; p < 0.001). The additional two baseline scans demonstrated no differences in mean NAD+ concentrations (0.425 ± 0.118 vs. 0.405 ± 0.082 mM; p = 0.45), and no difference from the first baseline scan (F(2, 16) = 0.907; p = 0.424). CONCLUSION: These preliminary results confirm that acute NR supplementation increases cerebral NAD+ levels in healthy human volunteers and shows the promise of DF 1H MRS utility for robust detection of NAD+ in humans in vivo.

Assessing the Stability of Photon-Counting CT: Insights from a Two-Year Longitudinal Study.

Background: Among the advancements in computed tomography (CT) technology, photon-counting computed tomography (PCCT) stands out as a significant innovation, providing superior spectral imaging capabilities while simultaneously reducing radiation exposure. Its long-term stability is important for clinical care, especially longitudinal studies, but is currently unknown. Purpose: This study sets out to comprehensively analyze the long-term stability of a first-generation clinical PCCT scanner. Materials and Methods: Over a two-year period, from November 2021 to November 2023, we conducted weekly identical experiments utilizing the same multi-energy CT protocol. These experiments included various tissue-mimicking inserts to rigorously assess the stability of Hounsfield Units (HU) and image noise in Virtual Monochromatic Images (VMIs) and iodine density maps. Throughout this period, notable software and hardware modifications were meticulously recorded. Each week, VMIs and iodine density maps were reconstructed and analyzed to evaluate quantitative stability over time. Results: Spectral results consistently demonstrated the quantitative stability of PCCT. VMIs exhibited stable HU values, such as variation in relative error for VMI 70 keV measuring 0.11% and 0.30% for single-source and dual-source modes, respectively. Similarly, noise levels remained stable with slight fluctuations linked to software changes for VMI 40 and 70 keV that corresponded to changes of 8 and 1 HU, respectively. Furthermore, iodine density quantification maintained stability and showed significant improvement with software and hardware changes, especially in dual-source mode with nominal errors decreasing from 1.44 to 0.03 mg/mL. Conclusion: This study provides the first long-term reproducibility assessment of quantitative PCCT imaging, highlighting its potential for the clinical arena. This study indicates its long-term utility in diagnostic radiology, especially for longitudinal studies.

Familial aggregation of seizure outcomes in four familial epilepsy cohorts.

OBJECTIVE: To assess the possible effects of genetics on seizure outcome by estimating the familial aggregation of three outcome measures: seizure remission, history of ≥4 tonic-clonic seizures, and seizure control for individuals taking antiseizure medication. METHODS: We analyzed families containing multiple persons with epilepsy in four previously collected retrospective cohorts. Seizure remission was defined as being 5 and 10 years seizure-free at last observation. Total number of tonic-clonic seizures was dichotomized at <4 and ≥4 seizures. Seizure control in patients taking antiseizure medication was defined as no seizures for 1, 2, and 3 years. We used Bayesian generalized linear mixed-effects model (GLMM) to estimate the intraclass correlation coefficient (ICC) of the family-specific random effect, controlling for epilepsy type, age at epilepsy onset, and age at last data collection as fixed effects. We analyzed each cohort separately and performed meta-analysis using GLMMs. RESULTS: The combined cohorts included 3644 individuals with epilepsy from 1463 families. A history of ≥4 tonic-clonic seizures showed strong familial aggregation in three separate cohorts and meta-analysis (ICC .28, 95% confidence interval [CI] .21-.35, Bayes factor 8 × 1016). Meta-analyses did not reveal significant familial aggregation of seizure remission (ICC .08, 95% CI .01-.17, Bayes factor 1.46) or seizure control for individuals taking antiseizure medication (ICC .13, 95% CI 0-.35, Bayes factor 0.94), with heterogeneity among cohorts. SIGNIFICANCE: A history of ≥4 tonic-clonic seizures aggregated strongly in families, suggesting a genetic influence, whereas seizure remission and seizure control for individuals taking antiseizure medications did not aggregate consistently in families. Different seizure outcomes may have different underlying biology and risk factors. These findings should inform the future molecular genetic studies of seizure outcomes.

Choroid plexus volume differentiates MS from its mimics.

This study aimed to determine whether choroid plexus volume (CPV) could differentiate multiple sclerosis (MS) from its mimics. A secondary analysis of two previously enrolled studies, 50 participants with MS and 64 with alternative diagnoses were included. CPV was automatically segmented from 3T magnetic resonance imaging (MRI), followed by manual review to remove misclassified tissue. Mean normalized choroid plexus volume (nCPV) to intracranial volume demonstrated relatively high specificity for MS participants in each cohort (0.80 and 0.76) with an area under the receiver-operator characteristic curve of 0.71 (95% confidence interval (CI) = 0.55-0.87) and 0.65 (95% CI = 0.52-0.77). In this preliminary study, nCPV differentiated MS from its mimics.

Sex Differences in Perihematomal Edema Volume and Outcome After Intracerebral Hemorrhage.

BACKGROUND: Although larger hematoma volume is associated with worse outcome after intracerebral hemorrhage (ICH), the association between perihematomal edema (PHE) volume and outcome remains uncertain, as does the impact of sex on PHE and outcome. Here we aimed to determine whether larger PHE volume is associated with worse outcome and whether PHE volume trajectories differ by sex. METHODS: We conducted a post hoc analysis of the Factor VIIa for Acute Hemorrhagic Stroke Treatment (FAST) trial, which randomized patients with ICH to receive recombinant activated factor VIIa or placebo. Computerized planimetry calculated PHE and ICH volumes on serial computed tomography (CT) scans (at baseline [within 3 h of onset], at 24 h, and at 72 h). Generalized estimating equations examined interactions between sex, CT time points, and FAST treatment arm on PHE and ICH volumes. Mixed and multivariable logistic models examined associations between sex, PHE, and outcomes. RESULTS: A total of 781 patients with supratentorial ICH (mean age 65 years) were included. Compared to women (n = 296), men (n = 485) had similar median ICH (14.9 vs. 13.6 mL, p = 0.053) and PHE volumes (11.1 vs. 10.5 mL, p = 0.56) at baseline but larger ICH and PHE volumes at 24 h (19.0 vs. 14.0 mL, p < 0.001; 22.2 vs. 15.7 mL, p < 0.001) and 72 h (16.0 vs. 11.8 mL, p < 0.001; 28.7 vs. 19.9 mL, p < 0.001). Men had higher absolute early PHE expansion (p < 0.001) and more hematoma expansion (growth ≥ 33% or 6 mL at 24 h, 33% vs. 22%, p < 0.001). An interaction between sex and CT time points on PHE volume (p < 0.001), but not on ICH volume, confirmed a steeper PHE trajectory in men. PHE expansion (per 5 mL, odds radio 1.19, 95% confidence interval 1.10-1.28), but not sex, was associated with poor outcome. CONCLUSIONS: Early PHE expansion and trajectory in men were significantly higher. PHE expansion was associated with poor outcomes independent of sex. Mechanisms leading to sex differences in PHE trajectories merit further investigation.

Combined Orbital and Cranial Vessel Wall Magnetic Resonance Imaging for the Assessment of Disease Activity in Giant Cell Arteritis.

OBJECTIVE: Acute visual impairment is the most feared complication of giant cell arteritis (GCA) but is challenging to predict. Magnetic resonance imaging (MRI) evaluates orbital pathology not visualized by an ophthalmologic examination. This study combined orbital and cranial vessel wall MRI to assess both orbital and cranial disease activity in patients with GCA, including patients without visual symptoms. METHODS: Patients with suspected active GCA who underwent orbital and cranial vessel wall MRI were included. In 14 patients, repeat imaging over 12 months assessed sensitivity to change. Clinical diagnosis of ocular or nonocular GCA was determined by a rheumatologist and/or ophthalmologist. A radiologist masked to clinical data scored MRI enhancement of structures. RESULTS: Sixty-four patients with suspected GCA were included: 25 (39%) received a clinical diagnosis of GCA, including 12 (19%) with ocular GCA. Orbital MRI enhancement was observed in 83% of patients with ocular GCA, 38% of patients with nonocular GCA, and 5% of patients with non-GCA. MRI had strong diagnostic performance for both any GCA and ocular GCA. Combining MRI with a funduscopic examination reached 100% sensitivity for ocular GCA. MRI enhancement significantly decreased after treatment (P < 0.01). CONCLUSION: In GCA, MRI is a sensitive tool that comprehensively evaluates multiple cranial structures, including the orbits, which are the most concerning site of pathology. Orbital enhancement in patients without visual symptoms suggests that MRI may detect at-risk subclinical ocular disease in GCA. MRI scores decreased following treatment, suggesting scores reflect inflammation. Future studies are needed to determine if MRI can identify patients at low risk for blindness who may receive less glucocorticoid therapy.

CD137+ tumor infiltrating lymphocytes predicts ovarian cancer survival.

OBJECTIVE: Ovarian cancer (OC) is the leading cause of death from gynecologic malignancy in the United States, and biomarkers of patient outcomes are limited. Data using immunohistochemical (IHC) analysis are mixed regarding whether and which tumor infiltrating lymphocytes (TILs) impact survival, and IHC does not adequately quantify rare cell populations, including CD137+ (4-1BB) tumor-reactive TILs. Our study investigates if a higher percentage of CD3+ CD137+ TILs is associated with improved overall survival (OS) in OC. METHODS: Flow cytometry was performed on viably banked OC digests. Chart review and statistical analysis were performed. Forty-seven patients were included, 40 of whom were diagnosed with high-grade serous ovarian carcinoma (HGSOC), papillary serous carcinoma, or undifferentiated histology. RESULTS: A high percentage of CD3+ CD137+ TILs correlated with improved OS (n = 40, r = 0.48, P = 0.0016). Subjects were divided into CD3+ CD137+ TIL high and low groups by the median. Subjects with high CD3+CD137+ TIL frequencies (>9.6%) had longer OS (Wilcoxon rank-sum test; P = 0.0032) and improved OS (logrank test; P = 0.007). Differences in CD3+ or CD3+ CD8+ TILs did not impact survival. CD3+ CD137+ TILs were predictive of OS regardless of germline mutation or debulking status. Analysis of subgroups including late stage HGSOC and late stage HGSOC with primary optimal cytoreduction indicated CD3+ CD137+ TILs correlated with improved OS after adjusting for age and PARP inhibitor use (P = 0.034 and P = 0.016, respectively). CONCLUSIONS: Prevalence of CD3+ CD137+ TILs in digested OC specimens is associated with improved OS, while general TIL markers are not. CD137 has the potential to be a novel biomarker for survival in OC.

Detection of Medication Taking Using a Wrist-Worn Commercially Available Wearable Device.

PURPOSE: Medication nonadherence is a persistent and costly problem across health care. Measures of medication adherence are ineffective. Methods such as self-report, prescription claims data, or smart pill bottles have been used to monitor medication adherence, but these are subject to recall bias, lack real-time feedback, and are often expensive. METHODS: We proposed a method for monitoring medication adherence using a commercially available wearable device. Passively collected motion data were analyzed on the basis of the Movelet algorithm, a dictionary learning framework that builds person-specific chapters of movements from short frames of elemental activities within the movements. We adapted and extended the Movelet method to construct a within-patient prediction model that identifies medication-taking behaviors. RESULTS: Using 15 activity features recorded from wrist-worn wearable devices of 10 patients with breast cancer on endocrine therapy, we demonstrated that medication-taking behavior can be predicted in a controlled clinical environment with a median accuracy of 85%. CONCLUSION: These results in a patient-specific population are exemplar of the potential to measure real-time medication adherence using a wrist-worn commercially available wearable device.

Multi-contrast high-field quality image synthesis for portable low-field MRI using generative adversarial networks and paired data.

Introduction: Portable low-field strength (64mT) MRI scanners promise to increase access to neuroimaging for clinical and research purposes, however these devices produce lower quality images compared to high-field scanners. In this study, we developed and evaluated a deep learning architecture to generate high-field quality brain images from low-field inputs using a paired dataset of multiple sclerosis (MS) patients scanned at 64mT and 3T. Methods: A total of 49 MS patients were scanned on portable 64mT and standard 3T scanners at Penn (n=25) or the National Institutes of Health (NIH, n=24) with T1-weighted, T2-weighted and FLAIR acquisitions. Using this paired data, we developed a generative adversarial network (GAN) architecture for low- to high-field image translation (LowGAN). We then evaluated synthesized images with respect to image quality, brain morphometry, and white matter lesions. Results: Synthetic high-field images demonstrated visually superior quality compared to low-field inputs and significantly higher normalized cross-correlation (NCC) to actual high-field images for T1 (p=0.001) and FLAIR (p<0.001) contrasts. LowGAN generally outperformed the current state-of-the-art for low-field volumetrics. For example, thalamic, lateral ventricle, and total cortical volumes in LowGAN outputs did not differ significantly from 3T measurements. Synthetic outputs preserved MS lesions and captured a known inverse relationship between total lesion volume and thalamic volume. Conclusions: LowGAN generates synthetic high-field images with comparable visual and quantitative quality to actual high-field scans. Enhancing portable MRI image quality could add value and boost clinician confidence, enabling wider adoption of this technology.