Improving diagnosis accuracy of brain volume abnormalities during childhood with an automated MP2RAGE-based MRI brain segmentation.

BACKGROUND AND PURPOSE: It can be challenging to depict brain volume abnormalities in the pediatric population on magnetic resonance imaging (MRI). The aim of the study was to evaluate the inter-radiologist reliability in brain MRI interpretation, including brain volume assessment and the efficiency of an automated brain segmentation. MATERIALS AND METHODS: We performed a single-center prospective study including 44 patients aged six months to five years recruited from the University Hospital, having a 1.5T brain MRI using a MP2RAGE sequence. All MRI were randomly and blindly reviewed by one junior and two senior pediatric radiologists. Inter-observer agreements were assessed using Fleiss' kappa coefficient. Brain volumetry (total intracranial volume (TIV), brain parenchyma, and cerebrospinal fluid volumes) was estimated using the MorphoBox prototype. Clinical head circumference (HC) and z scores were reported. A Pearson correlation coefficient was calculated between brain volumes with HC. RESULTS: Twenty-four brain MRI examinations were normal and twenty were pathological. Brain volume abnormalities were poorly detected by junior and senior radiologists: sensitivities 16.67% [confidence interval 4.7-44.8], 33.33% [13-60] and 30.7% [12-58] and specificities 93.75% [79-98], 84.38% [68-93] and 77% [60-88], respectively. Brain volume apart, interobserver kappa coefficients were 0.93 between junior and seniors as well as between seniors. Brain volumes were significantly correlated with HC (P<0.0001). In patients with normal MRI, brain parenchyma volumes increased regularly with age. Low brain volume was easier to identify with automated quantification. CONCLUSION: Brain volume was poorly appreciated by radiologists. The fully automated brain segmentation used can provide quantitative data to better diagnose, describe, and follow-up brain volume abnormalities.

Clinical equivalence assessment of T2 synthesized pediatric brain magnetic resonance imaging.

BACKGROUND AND PURPOSE: Automated synthetic magnetic resonance imaging (MRI) provides qualitative, weighted image contrasts as well as quantitative information from one scan and is well-suited for various applications such as analysis of white matter disorders. However, the synthesized contrasts have been poorly evaluated in pediatric applications. The purpose of this study was to compare the image quality of synthetic T2 to conventional turbo spin-echo (TSE) T2 in pediatric brain MRI. MATERIALS AND METHODS: This was a mono-center prospective study. Synthetic and conventional MRI acquisitions at 1.5 Tesla were performed for each patient during the same session using a prototype accelerated T2 mapping sequence package (TAsynthetic=3:07min, TAconventional=2:33min). Image sets were blindly and randomly analyzed by pediatric neuroradiologists. Global image quality, morphologic legibility of standard structures and artifacts were assessed using a 4-point Likert scale. Inter-observer kappa agreements were calculated. The capability of the synthesized contrasts and conventional TSE T2 to discern normal and pathologic cases was evaluated. RESULTS: Sixty patients were included. The overall diagnostic quality of the synthesized contrasts was non-inferior to conventional imaging scale (P=0.06). There was no significant difference in the legibility of normal and pathological anatomic structures of synthetized and conventional TSE T2 (all P>0.05) as well as for artifacts except for phase encoding (P=0.008). Inter-observer agreement was good to almost perfect (kappa between 0.66 and 1). CONCLUSIONS: T2 synthesized contrasts, which also provides quantitative T2 information that could be useful, could be suggested as an equivalent technique in pediatric neuro-imaging, compared to conventional TSE T2.