Tuesday, December 17, 2024
12/17/2024
Abstract Hypoxic Ischemic Encephalopathy (HIE) is a brain injury occurring in ~5/1000 newborns. In 2005, the NIH Neonatal Research Network (NRN) established therapeutic hypothermia (TH), cooling patients in the first 6 postnatal hours to 33-34°C for 72 hours, as the standard treatment for HIE in high-income countries. However, many patients still experience adverse outcomes (death or cognitive Bayley Scales of Infant Development <85) by 18-22 months. Thus, from 2008 to 2015, the NRN tested if deeper, longer, or later TH further reduced adverse outcomes, with two trials in 21 sites. Unfortunately, results were inconclusive and further progress has been slow, largely because adverse outcomes cannot be reliably assessed until 18-22 months. To expedite therapeutic innovations and assess the impact of novel therapies in a more timely manner, there is an urgent but unmet need to establish a neonatal biomarker of 18-22 month adverse outcomes. To address this gap, the NRN developed such a biomarker using neuroradiological expert scoring of brain injury on clinically acquired neonatal brain magnetic resonance images (MRIs), known as the NRN MRI score. In one dataset with one reader, sensitivity/specificity for adverse outcomes was 81%/78%. However, in another dataset with two readers, the inter-reader agreement was only moderate and specificity for adverse outcomes was only 56-69%. Questions arise for whether this subjective and time-consuming scoring system is reliable or fully characterizes complex HIE injury patterns. Also in many countries, there are no experts available to perform MRI scoring. Finally, important clinical data elements such as birth weight, sex, APGAR scores, socioeconomic status, and aspects of the clinical exam are not fully integrated into the scoring system. Our overall hypothesis is that Artificial Intelligence (AI) algorithms on neonatal brain MRI and clinical data elements can provide higher sensitivity and specificity than the expert NRN MRI scores in predicting adverse HIE outcomes by 18-22 months. Our R61 Aims are as follows: Aim 1, Compile a large HIE dataset (N=430) from two completed NRN multi-site HIE trials; Aim 2, Develop an AI biomarker of outcome using neonatal brain MRI, and compare with NRN scores with Aim 2a focusing on MRI injury patterns and Aim 2b focusing on whole brain MRI signal intensity patterns; and Aim 3, Develop an AI biomarker of outcome combining clinical and MRI data, and compare with NRN scores. Go/No- Go criteria for the R33 is if at least one biomarker (2a, 2b, or 3) outperforms NRN MRI scores in our N=430 cohort (p<0.05; DeLong Test of AUC). The R33 Aim 4 is to further evaluate accuracy and reliability in a new cohort (N=231). Deliverables: Publicly released data and the AI software. Impact: A brain MRI and clinical AI- powered neonatal prognostic biomarker could expedite therapeutic innovations in future HIE trials worldwide.
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