Hippocampal Volumes in Amnestic and Non-Amnestic Mild Cognitive Impairment Types Using Two Common Methods of MCI Classification.

OBJECTIVES: Mild cognitive impairment (MCI) types may have distinct neuropathological substrates with hippocampal atrophy particularly common in amnestic MCI (aMCI). However, depending on the MCI classification criteria applied to the sample (e.g., number of abnormal test scores considered or thresholds for impairment), volumetric findings between MCI types may change. Additionally, despite increased clinical use, no prior research has examined volumetric differences in MCI types using the automated volumetric software, Neuroreader™. METHODS: The present study separately applied the Petersen/Winblad and Jak/Bondi MCI criteria to a clinical sample of older adults (N = 82) who underwent neuropsychological testing and brain MRI. Volumetric data were analyzed using Neuroreader™ and hippocampal volumes were compared between aMCI and non-amnestic MCI (naMCI). RESULTS: T-tests revealed that regardless of MCI classification criteria, hippocampal volume z-scores were significantly lower in aMCI compared to naMCI (p's < .05), and hippocampal volume z-scores significantly differed from 0 (Neuroreader™ normative mean) in the aMCI group only (p's < .05). Additionally, significant, positive correlations were found between measures of delayed recall and hippocampal z-scores in aMCI using either MCI classification criteria (p's < .05). CONCLUSIONS: We provide evidence of correlated neuroanatomical changes associated with memory performance for two commonly used neuropsychological MCI classification criteria. Future research should investigate the clinical utility of hippocampal volumes analyzed via Neuroreader™ in MCI.

Memory Performance and Quantitative Neuroimaging Software in Mild Cognitive Impairment: A Concurrent Validity Study.

OBJECTIVE: This study examined the relationship between patient performance on multiple memory measures and regional brain volumes using an FDA-cleared quantitative volumetric analysis program - Neuroreader™. METHOD: Ninety-two patients diagnosed with mild cognitive impairment (MCI) by a clinical neuropsychologist completed cognitive evaluations and underwent MR Neuroreader™ within 1 year of testing. Select brain regions were correlated with three widely used memory tests. Regression analyses were conducted to determine if using more than one memory measures would better predict hippocampal z-scores and to explore the added value of recognition memory to prediction models. RESULTS: Memory performances were most strongly correlated with hippocampal volumes than other brain regions. After controlling for encoding/Immediate Recall standard scores, statistically significant correlations emerged between Delayed Recall and hippocampal volumes (rs ranging from .348 to .490). Regression analysis revealed that evaluating memory performance across multiple memory measures is a better predictor of hippocampal volume than individual memory performances. Recognition memory did not add further predictive utility to regression analyses. CONCLUSIONS: This study provides support for use of MR Neuroreader™ hippocampal volumes as a clinically informative biomarker associated with memory performance, which is a critical diagnostic feature of MCI phenotype.

Effects of Thresholding on Voxel-Wise Correspondence of Breath-Hold and Resting-State Maps of Cerebrovascular Reactivity.

Functional magnetic resonance imaging for presurgical brain mapping enables neurosurgeons to identify viable tissue near a site of operable pathology which might be at risk of surgery-induced damage. However, focal brain pathology (e.g., tumors) may selectively disrupt neurovascular coupling while leaving the underlying neurons functionally intact. Such neurovascular uncoupling can result in false negatives on brain activation maps thereby compromising their use for surgical planning. One way to detect potential neurovascular uncoupling is to map cerebrovascular reactivity using either an active breath-hold challenge or a passive resting-state scan. The equivalence of these two methods has yet to be fully established, especially at a voxel level of resolution. To quantitatively compare breath-hold and resting-state maps of cerebrovascular reactivity, we first identified threshold settings that optimized coverage of gray matter while minimizing false responses in white matter. When so optimized, the resting-state metric had moderately better gray matter coverage and specificity. We then assessed the spatial correspondence between the two metrics within cortical gray matter, again, across a wide range of thresholds. Optimal spatial correspondence was strongly dependent on threshold settings which if improperly set tended to produce statistically biased maps. When optimized, the two CVR maps did have moderately good correspondence with each other (mean accuracy of 73.6%). Our results show that while the breath-hold and resting-state maps may appear qualitatively similar they are not quantitatively identical at a voxel level of resolution.

Stable Intracerebral Transplantation of Neural Stem Cells for the Treatment of Paralysis Due to Ischemic Stroke.

NSI-566 is a stable, primary adherent neural stem cell line derived from a single human fetal spinal cord and expanded epigenetically with no genetic modification. This cell line is being tested in clinical trials in the U.S. for treatment of amyotrophic lateral sclerosis and spinal cord injury. In a single-site, phase I study, we evaluated the feasibility and safety of NSI-566 transplantation for the treatment of hemiparesis due to chronic motor stroke and determined the maximum tolerated dose for future trials. Three cohorts (n = 3 per cohort) were transplanted with one-time intracerebral injections of 1.2 × 107 , 2.4 × 107 , or 7.2 × 107 cells. Immunosuppression therapy with tacrolimus was maintained for 28 days. All subjects had sustained chronic motor strokes, verified by magnetic resonance imaging (MRI), initiated between 5 and 24 months prior to surgery with modified Rankin Scores [MRSs] of 2, 3, or 4 and Fugl-Meyer Motor Scores of 55 or less. At the 12-month visit, the mean Fugl-Meyer Motor Score (FMMS, total score of 100) for the nine participants showed 16 points of improvement (p = .0078), the mean MRS showed 0.8 points of improvement (p = .031), and the mean National Institutes of Health Stroke Scale showed 3.1 points of improvement (p = .020). For six participants who were followed up for 24 months, these mean changes remained stable. The treatment was well tolerated at all doses. Longitudinal MRI studies showed evidence indicating cavity-filling by new neural tissue formation in all nine patients. Although this was a small, one-arm study of feasibility, the results are encouraging to warrant further studies. Stem Cells Translational Medicine 2019;8:999-1007.

Classification and Extraction of Resting State Networks Using Healthy and Epilepsy fMRI Data.

Functional magnetic resonance imaging studies have significantly expanded the field's understanding of functional brain activity of healthy and patient populations. Resting state (rs-) fMRI, which does not require subjects to perform a task, eliminating confounds of task difficulty, allows examination of neural activity and offers valuable functional mapping information. The purpose of this work was to develop an automatic resting state network (RSN) labeling method which offers value in clinical workflow during rs-fMRI mapping by organizing and quickly labeling spatial maps into functional networks. Here independent component analysis (ICA) and machine learning were applied to rs-fMRI data with the goal of developing a method for the clinically oriented task of extracting and classifying spatial maps into auditory, visual, default-mode, sensorimotor, and executive control RSNs from 23 epilepsy patients (and for general comparison, separately for 30 healthy subjects). ICA revealed distinct and consistent functional network components across patients and healthy subjects. Network classification was successful, achieving 88% accuracy for epilepsy patients with a naïve Bayes algorithm (and 90% accuracy for healthy subjects with a perceptron). The method's utility to researchers and clinicians is the provided RSN spatial maps and their functional labeling which offer complementary functional information to clinicians' expert interpretation.

Multilayer modeling of reflectance pulse oximetry.

A multilayer tissue description was employed in Monte Carlo simulations of reflectance pulse oximetry to study the impact of assumptions made in previous studies employing homogeneous tissue models. Simulation results with a discrete layer of arterial pulsatility were similar to previous studies employing homogenous tissue models. However, the relationship of normalized pulse amplitude to emitter-detector spacing reiterates that spacing has a significant impact on pulse oximetry function. The effect of melanin content as a thin, superficial absorber was also simulated, with results supporting the general clinical observation that skin shade need not substantially compromise pulse oximeter accuracy.

Factors influencing fetal pulse oximetry performance.

Fetal pulse oximetry shares many problems with traditional pulse oximetry, but also poses unique challenges that may compromise accurate SpO2 determination and data availability. The purpose of this review is to characterize the factors that may influence fetal pulse oximetry and their relationship to sensor design. A review of the literature of pulse oximetry identifies the factors that have been shown to influence fetal pulse oximetry performance, as well as other factors from traditional pulse oximetry that may also be expected to have an effect. Sensor design choices, including monitoring site, wavelength, and configuration, are related to the incidence and mitigation of these factors. Sensor designs may be characterized by monitoring site, means of retention, and operating mode (reflectance versus transmission). The factors influencing fetal pulse oximetry may be categorized as follows: fetal physiology, tissue characteristics at the monitoring site, sensor-tissue interface, and external influences. Monitoring site selection is of paramount importance in reducing the impact of interfering factors on fetal pulse oximetry performance. Many factors of importance in traditional pulse oximetry have yet to be characterized as far as their potential for interference in fetal pulse oximetry.

The pulse in reflectance pulse oximetry: modeling and experimental studies.

OBJECTIVE: Reflectance pulse oximetry permits the use of alternative monitoring sites such as the face or torso, and is the approach commonly employed in fetal pulse oximetry systems. The purpose of this study is to investigate the impact of assumptions about the nature of arterial pulsatility on the calibration of such systems. METHODS: Monte Carlo simulations of reflectance pulse oximetry were run on a six-layer tissue model, varying depth and magnitude of the arterial pulse. SpO2 readings on and off the femoral artery obtained during desaturation studies in newborn piglets were compared to predictions. Results. Monte Carlo simulation results clarified the difference between deep and shallow pulsatility found with photon diffusion models, agreeing with earlier in vivo observations. Significant overestimation of SpO2 <75% and slight underestimation >75% is expected if a sensor is placed on a highly pulsatile site. The on- and off-artery SpO2 readings recorded during desaturation in the newborn piglet follow the model predictions. CONCLUSIONS: The sensitivity of reflectance pulse oximetry calibration to the depth and magnitude of arterial pulsatility reinforces the observation that monitoring site selection is of importance in optimizing reflectance pulse oximetry performance, particularly fetal pulse oximetry. Sites with palpable pulsatility should be avoided.