Factors and Labor Cost Savings Associated with Successful Pediatric Imaging without Anesthesia: a Single-Institution Study

White matter microstructure in school-age children with down syndrome

Down syndrome (DS) is the most common genetic cause of intellectual disability, but our understanding of white matter microstructure in children with DS remains limited. Previous studies have reported reductions in white matter integrity, but nearly all studies to date have been conducted in adults or relied solely on diffusion tensor imaging (DTI), which lacks the ability to disentangle underlying properties of white matter organization. This study examined white matter microstructural differences in 7- to 12-year-old children with DS (n = 23), autism (n = 27), and typical development (n = 50) using DTI as well as High Angular Resolution Diffusion Imaging, and Neurite Orientation and Dispersion Imaging. There was a spatially specific pattern of results that showed a dissociation between intra- and inter-hemispheric pathways. Intra-hemispheric pathways (e.g., inferior fronto-occipital fasciculus, superior longitudinal fasciculus) exhibited reduced organization and structural integrity. Inter-hemispheric pathways (e.g., corpus callosum projections) and motor pathways (e.g., corticospinal tract) showed denser neurite packing and lower neurite dispersion. The current findings provide early insight into white matter development in school-aged children with DS and have the potential to further elucidate microstructural differences and inform more targeted clinical trials than what has previously been observed through DTI models alone.

Update on Whole-Body MRI Surveillance for Pediatric Cancer Predisposition Syndromes

Whole-body MRI (WBMRI) is an integral part of screening infants, children, and adolescents for presymptomatic neoplasms in certain cancer predisposition syndromes, which include Li-Fraumeni and constitutional mismatch repair deficiency syndromes, among others. The list of syndromes in which WBMRI adds value, as part of a comprehensive surveillance protocol, continues to evolve in response to new evidence, growing experience, and more widespread adoption. In July 2023, the AACR reconvened an international, multidisciplinary panel to revise and update recommendations stemming from the 2016 AACR Special Workshop on Childhood Cancer Predisposition. That initial meeting resulted in a series of publications in Clinical Cancer Research in 2017, including "Pediatric Cancer Predisposition Imaging: Focus on Whole-Body MRI." This 2024 review of WBMRI in cancer predisposition syndrome updates the 2017 WBMRI publication, the revised recommendations derived from the 2023 AACR Childhood Cancer Predisposition Workshop based on available data, societal guidelines, and expert opinion. Different aspects of acquiring and interpreting WBMRI, including diagnostic accuracy, are discussed. The application of WBMRI in resource-poor environments, as well as integration of whole-body imaging techniques with emerging technologies, such as cell-free DNA ("liquid biopsies") and artificial intelligence/machine learning, is also considered.

Child life specialists predict successful MRI scanning in unsedated children 4 to 12 years old

BACKGROUND

It can be challenging for children to cooperate for a magnetic resonance imaging (MRI) exam. General anesthesia is often used to ensure a high-quality image. When determining the need for general anesthesia, many institutions use a simple age cutoff. Decisions on the necessity for anesthesia are often left to schedulers who lack training on determination of patient compliance.

OBJECTIVE

The study aimed to evaluate whether screening questions administered by certified child life specialists (CCLS) could successfully predict which children could complete an MRI without sedation.

MATERIALS AND METHODS

This is a retrospective, institutional review board approved study. Data was collected as part of a quality improvement program, where a CCLS screened 4- to 12-year-old children scheduled for MRI scanning using a questionnaire. Parent responses to the screening questions, CCLS's recommendation for scheduling the MRI awake, start and end time for the MRI scan, and scan success were recorded. A predictive model for the CCLS's recommendation was developed using the child's age, estimated scan length, scan difficulty, and the parent's responses to the screening questions. The primary outcome measure was a successfully completed MRI not requiring additional imaging under anesthesia.

RESULTS

Of the 403 screened children, 317 (79%) were recommended to attempt the MRI without anesthesia. The median age of participants was 7 (IQR 4-17) years. Overall, 309 of 317 (97.5%) participants, recommended by the CCLS for the program, met the primary outcome of successful MRI completion on their first attempt. The multivariable regression model which included clinical information about the child's age, estimated scan length, scan difficulty, and four of the six parent screening questions had excellent performance (area under the curve = 0.89).

CONCLUSION

Information collected by the CCLS via screening along with the child's age, the estimated scan length, and difficulty can help predict which children are likely to successfully complete a non-sedate MRI.

Automated neonatal nnU-Net brain MRI extractor trained on a large multi-institutional dataset

Brain extraction, or skull-stripping, is an essential data preprocessing step for machine learning approaches to brain MRI analysis. Currently, there are limited extraction algorithms for the neonatal brain. We aim to adapt an established deep learning algorithm for the automatic segmentation of neonatal brains from MRI, trained on a large multi-institutional dataset for improved generalizability across image acquisition parameters. Our model, ANUBEX (automated neonatal nnU-Net brain MRI extractor), was designed using nnU-Net and was trained on a subset of participants (N = 433) enrolled in the High-dose Erythropoietin for Asphyxia and Encephalopathy (HEAL) study. We compared the performance of our model to five publicly available models (BET, BSE, CABINET, iBEATv2, ROBEX) across conventional and machine learning methods, tested on two public datasets (NIH and dHCP). We found that our model had a significantly higher Dice score on the aggregate of both data sets and comparable or significantly higher Dice scores on the NIH (low-resolution) and dHCP (high-resolution) datasets independently. ANUBEX performs similarly when trained on sequence-agnostic or motion-degraded MRI, but slightly worse on preterm brains. In conclusion, we created an automatic deep learning-based neonatal brain extraction algorithm that demonstrates accurate performance with both high- and low-resolution MRIs with fast computation time.

A survey of non-sedate practices when acquiring pediatric magnetic resonance imaging examinations

BACKGROUND

Improving access to magnetic resonance imaging (MRI) in childhood can be facilitated by making it faster and cheaper and reducing need for sedation or general anesthesia (GA) to mitigate motion. Some children achieve diagnostic quality MRI without GA through the use of non- practices fostering their cooperation and/or alleviating anxiety. Employed before and during MRI, these variably educate, distract, and/or desensitize patients to this environment.

OBJECTIVE

To assess current utilization of non-sedate practices in pediatric MRI, including variations in practice and outcomes.

MATERIALS AND METHODS

A survey-based study was conducted with 1372 surveys emailed to the Society for Pediatric Radiology members in February 2021, inviting one response per institution.

RESULTS

Responses from 50 unique institutions in nine countries revealed 49/50 (98%) sites used ≥ 1 non-sedate practice, 48/50 (96%) sites in infants < 6 months, and 11/50 (22%) for children aged 6 months to 3 years. Non-sedate practices per site averaged 4.5 (range 0-10), feed and swaddle used at 47/49 (96%) sites, and child life specialists at 35/49 (71%). Average success rates were moderate (> 50-75%) across all sites and high (> 75-100%) for 20% of sites, varying with specific techniques. Commonest barriers to use were scheduling conflicts and limited knowledge.

CONCLUSION

Non-sedate practice utilization in pediatric MRI was near-universal but widely variable across sites, ages, and locales, with room for broader adoption. Although on average non-sedate practice success rates were similar, the range in use and outcomes suggest a need for standardized implementation guidelines, including patient selection and outcome metrics, to optimize utilization and inform educational initiatives.

Testing a Home Solution for Preparing Young Children for an Awake MRI: A Promising Smartphone Application

Thanks to its non-invasive nature and high-resolution imaging capabilities, magnetic resonance imaging (MRI) is a valuable diagnostic tool for pediatric patients. However, the fear and anxiety experienced by young children during MRI scans often result in suboptimal image quality and the need for sedation/anesthesia. This study aimed to evaluate the effect of a smartphone application called COSMO@home to prepare children for MRI scans to reduce the need for sedation or general anesthesia. The COSMO@home app was developed incorporating mini-games and an engaging storyline to prepare children for learning goals related to the MRI procedure. A multicenter study was conducted involving four hospitals in Belgium. Eligible children aged 4-10 years were prepared with the COSMO@home app at home. Baseline, pre-scan, and post-scan questionnaires measured anxiety evolution in two age groups (4-6 years and 7-10 years). Eighty-two children participated in the study, with 95% obtaining high-quality MRI images. The app was well-received by children and parents, with minimal technical difficulties reported. In the 4-6-year-old group (N = 33), there was a significant difference between baseline and pre-scan parent-reported anxiety scores, indicating an increase in anxiety levels prior to the scan. In the 7-10-year-old group (N = 49), no significant differences were observed between baseline and pre-scan parent-reported anxiety scores. Overall, the COSMO@home app proved to be useful in preparing children for MRI scans, with high satisfaction rates and successful image outcomes across different hospitals. The app, combined with minimal face-to-face guidance on the day of the scan, showed the potential to replace or assist traditional face-to-face training methods. This innovative approach has the potential to reduce the need for sedation or general anesthesia during pediatric MRI scans and its associated risks and improve patient experience.