350 - Individual metabolite impairment in cerebral deep grey matter relates to outcome following neonatal encephalopathy

Poster Number: 350
Publication Number: 350.443

Alan Bainbridge, UCL Hospital, London, England, United Kingdom; Priyal Taribagil, Royal Free Foundation Trust, London, England, United Kingdom; Hannah Century, North Middlesex University Hospital NHS Trust, London, England, United Kingdom; Vinita Verma, University College London hospital, Watford, England, United Kingdom; Kelly Pegoretti Baruteau, University College London, Sidcup, England, United Kingdom; Latha Srinivasan, university college London, London, England, United Kingdom; Xavier Golay, University College London, London, England, United Kingdom; Francisco Torrealdea, Uclh, London, England, United Kingdom; Magdalena Sokolska, UCLH, London, England, United Kingdom; Giles S. Kendall, University College London, London, England, United Kingdom; Nicola J. Robertson, University College London, Bicester, England, United Kingdom; Subhabrata Mitra, Institute for Women's Health, University College London, London, England, United Kingdom

Background:
Neonatal encephalopathy (NE) continues to remain a significant cause of morbidity and mortality. Early prediction of neurodevelopmental outcome in babies with NE is important. Several MRI scoring systems and deep grey matter (DGM) Lac/NAA ratio are used as early surrogate outcome measures1.

Objective:
The objective of this study is to estimate the individual changes in metabolites following NE and relate to neurodevelopmental outcome.

Design/Methods:
Study was approved by the local REC and written informed consent was obtained before each study. Data were collected from 58 term neonates (corrected gestational age of 36-44 weeks) who underwent therapeutic hypothermia and were scanned in a 3T scanner within the first 2 weeks after birth. Conventional MR imaging was obtained along with MRS using single voxel positioned in the basal ganglia-thalamic region (PRESS, 64 averages, TR/TE = 2288ms/288ms, voxel size 15x15x15mm, scan time ∼7 min).  MRS data were analysed using Tarquin.  Metabolite ratios were calculated from the fitted data.  The data were further analysed using a combined reference method2:  metabolite signals were weighted inversely to the standard deviation of each metabolite within the cohort and then summed to generate a reference value (CRef) against which the metabolites of interest can be ratioed.  Metabolites with normal distributions within the cohort were included in CRef. The metabolites included in CRef were Aspartate, Creatine (Cr), total Choline(tCho), total NAA (tNAA), Taurine and Glutamate+glutamine (Glx). Threonine (Thr) was included in the Tarquin basis set to better fit the region around 1.3ppm – the sum of Lactate and threonine (Lac+T) was then analysed rather than the fitted lactate alone3.

Bayley III assessment was done at 2 years; infants were classified as normal if Bayley composite score was 85 or above and abnormal if died or motor composite score was < 85.

Results:
5 infants died, Bayley composite score < 85 was noted in – 6 infants in Motor, 10 infants in language and 9 infants in cognitive domain. tNAA was significantly different between the outcome groups in motor (p < 0.0001), cognitive (p=0.0002) and language (p=0.0018) outcome (fig 1). Differences in other metabolites between the outcome groups are presented in table 1.
Conclusion(s):
NE induces significant changes in cerebral energy metabolism. The combined reference method allows us to better elucidate the relationship of individual metabolites to the impact of NE. This methodology can be used during post processing  and doesn’t require increased length of scanning time, making it a clinically useful tool.

Figure1. Differences in tNAA (CRef) between good and poor outcome groups in different domains for neurodevelopment
Table 1. Differences in individual DGM metabolites between good and poor outcome groups