Free induction decay navigator motion metrics for prediction of diagnostic image quality in pediatric MRI
| Autor: | Monet Dugan, Joanne Rispoli, Onur Afacan, Tess E. Wallace, Tobias Kober, Kristina Pelkola, Camilo Jaimes, Simon K. Warfield |
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| Rok vydání: | 2021 |
| Předmět: |
Adolescent
Full Papers—Imaging Methodology Computer science Image quality artifacts anesthesia Motion (physics) 030218 nuclear medicine & medical imaging Correlation Motion 03 medical and health sciences 0302 clinical medicine motion detection Humans Radiology Nuclear Medicine and imaging Sensitivity (control systems) head motion Child Retrospective Studies Full Paper business.industry Infant Newborn Brain Infant Pattern recognition Motion detection Magnetic Resonance Imaging free induction decay navigators Benchmarking Pediatric patient sedation pediatric neuroimaging Child Preschool Metric (unit) Artificial intelligence business Algorithms 030217 neurology & neurosurgery Motion monitoring |
| Zdroj: | Magnetic Resonance in Medicine |
| ISSN: | 1522-2594 0740-3194 |
| DOI: | 10.1002/mrm.28649 |
| Popis: | Purpose To investigate the ability of free induction decay navigator (FIDnav)-based motion monitoring to predict diagnostic utility and reduce the time and cost associated with acquiring diagnostically useful images in a pediatric patient cohort. Methods A study was carried out in 102 pediatric patients (aged 0-18 years) at 3T using a 32-channel head coil array. Subjects were scanned with an FID-navigated MPRAGE sequence and images were graded by two radiologists using a five-point scale to evaluate the impact of motion artifacts on diagnostic image quality. The correlation between image quality and four integrated FIDnav motion metrics was investigated, as well as the sensitivity and specificity of each FIDnav-based metric to detect different levels of motion corruption in the images. Potential time and cost savings were also assessed by retrospectively applying an optimal detection threshold to FIDnav motion scores. Results A total of 12% of images were rated as non-diagnostic, while a further 12% had compromised diagnostic value due to motion artifacts. FID-navigated metrics exhibited a moderately strong correlation with image grade (Spearman's rho >= 0.56). Integrating the cross-correlation between FIDnav signal vectors achieved the highest sensitivity and specificity for detecting non-diagnostic images, yielding total time savings of 7% across all scans. This corresponded to a financial benefit of $2080 in this study. Conclusions Our results indicate that integrated motion metrics from FIDnavs embedded in structural MRI are a useful predictor of diagnostic image quality, which translates to substantial time and cost savings when applied to pediatric MRI examinations. |
| Databáze: | OpenAIRE |
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