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Bobbi Sparks

Publications and source records attributed to Bobbi Sparks.

2 recordsLinked to original sources

Propofol sedation for longitudinal pediatric neuroimaging research.

There is disagreement about allowing propofol sedation for research magnetic resonance imaging/spectroscopy (MRI/MRS) in children. Our study is the first to provide relevant safety and efficacy data. With institutional approval, 108 research MRI/MRS procedures under propofol sedation were performed longitudinally on children at ages 3-4 years (N=59) and 6-7 years (N=49). Sedation parameters, physiological values, and outcome data were collected. Success rate for acquisition of satisfactory quality MRI/MRS during propofol sedation was compared with that in typically developing, age-matched sleeping children. Only 5 minor events (2 with need to insert an oral airway, 2 with premature termination of study, 1 with bradycardia not requiring treatment) and no major events occurred. These safety/efficacy data are equal to or better than previously reported with propofol for clinically indicated procedures. A high percentage of parents of children participating in MRI/MRS studies at 3-4 years of age returned with their child at 6-7 years of age, and longitudinal follow-up was not adversely impacted by their child's experience with sedation. The success rate of data acquisition was significantly higher during propofol sedation (98%) than during late-night sleep studies in typically developing children (30%-50%). We conclude that propofol sedation for research MRI/MRS is safe and effective when children of appropriate ASA class are selected, supplemental oxygen is delivered, and sedation and monitoring are done by an experienced anesthesiologist.

Aging↗

Quantitative image analysis: software systems in drug development trials.

Multi-dimensional image analysis is being used increasingly to arrive at surrogate end-points for drug development trials. Various imaging modalities such as computed tomography (CT), magnetic resonance imaging (MRI), positron emission tomography (PET) and ultrasound are used to analyze treatments for diseases such as cancer, multiple sclerosis, osteoarthritis, and Alzheimer's disease. However, extracting information from images can be tedious and is prone to high user variability. The medical image analysis community is moving towards advanced software systems specifically designed for drug development trials. These systems can automatically identify the anatomy of interest in medical images (segmentation methods), can compare the anatomy over time or between patients (registration methods) and allow the quantitative extraction of anatomical features and the integration of the data and results into a database management system, automatically tracking the changes made to the data (audit trail generation). In this article, we present a case study using a prototype system that is used for quantifying multiple sclerosis lesions from multivariate MRI.

Clinical Trials as Topic↗