Rapid-Sequence MRI of the Brain: A Distinct Imaging Study

Non-ionizing Imaging for the Emergency Department Assessment of Pediatric Minor Head Trauma

Minor blunt head trauma (MHT) represents a common reason for presentation to the pediatric emergency department (ED). Despite the low incidence of clinically important traumatic brain injuries (ciTBIs) following MHT, many children undergo computed tomography (CT), exposing them to the risk associated with ionizing radiation. The clinical predictions rules developed by the Pediatric Emergency Care Applied Research Network (PECARN) for MHT are validated accurate tools to support decision-making about neuroimaging for these children to safely reduce CT scans. However, a few non-ionizing imaging modalities have the potential to contribute to further decrease CT use. This narrative review provides an overview of the evidence on the available non-ionizing imaging modalities that could be used in the management of children with MHT, including point of care ultrasound (POCUS) of the skull, near-infrared spectroscopy (NIRS) technology and rapid magnetic resonance imaging (MRI). Skull ultrasound has proven an accurate bedside tool to identify the presence and characteristics of skull fractures. Portable handheld NIRS devices seem to be accurate screening tools to identify intracranial hematomas also in pediatric MHT, in selected scenarios. Both imaging modalities may have a role as adjuncts to the PECARN rule to help refine clinicians' decision making for children at high or intermediate PECARN risk of ciTBI. Lastly, rapid MRI is emerging as a feasible and accurate alternative to CT scan both in the ED setting and when repeat imaging is needed. Advantages and downsides of each modality are discussed in detail in the review.

Development, validation, and pilot MRI safety study of a high-resolution, open source, whole body pediatric numerical simulation model

Numerical body models of children are used for designing medical devices, including but not limited to optical imaging, ultrasound, CT, EEG/MEG, and MRI. These models are used in many clinical and neuroscience research applications, such as radiation safety dosimetric studies and source localization. Although several such adult models have been reported, there are few reports of full-body pediatric models, and those described have several limitations. Some, for example, are either morphed from older children or do not have detailed segmentations. Here, we introduce a 29-month-old male whole-body native numerical model, "MARTIN", that includes 28 head and 86 body tissue compartments, segmented directly from the high spatial resolution MRI and CT images. An advanced auto-segmentation tool was used for the deep-brain structures, whereas 3D Slicer was used to segment the non-brain structures and to refine the segmentation for all of the tissue compartments. Our MARTIN model was developed and validated using three separate approaches, through an iterative process, as follows. First, the calculated volumes, weights, and dimensions of selected structures were adjusted and confirmed to be within 6% of the literature values for the 2-3-year-old age-range. Second, all structural segmentations were adjusted and confirmed by two experienced, sub-specialty certified neuro-radiologists, also through an interactive process. Third, an additional validation was performed with a Bloch simulator to create synthetic MR image from our MARTIN model and compare the image contrast of the resulting synthetic image with that of the original MRI data; this resulted in a "structural resemblance" index of 0.97. Finally, we used our model to perform pilot MRI safety simulations of an Active Implantable Medical Device (AIMD) using a commercially available software platform (Sim4Life), incorporating the latest International Standards Organization guidelines. This model will be made available on the Athinoula A. Martinos Center for Biomedical Imaging website.

Maximizing Value While Volumes are Increasing

Radiologists are facing ever increasing volumes while trying to provide value-based care. There are several drivers of increasing volumes: increasing population size, aging population, increased utilization, gaps in evidence-based care, changes in the provider workforce, defensive medicine, and increasing case complexity. Higher volumes result in increased cognitive and systemic errors and contribute to radiologist fatigue and burnout. We discuss several strategies for mitigating high volumes including abbreviated MRI protocols, 24/7 radiologist coverage, reading room assistants, and other strategies to tackle radiologist burnout.