Hemibrain growth as a biomarker for whole-brain growth.

OBJECTIVE: Accurate estimation of CSF and brain volume is an important component in evaluating hydrocephalus treatments, including shunt and endoscopic third ventriculostomy procedures. While MRI-based segmentation typically provides precise measurements, metallic artifacts from implanted shunts in patients with hydrocephalus can impede accurate volume determination. This study introduces a method for assessing brain growth in hydrocephalus patients using artifact-affected MR images and presents an efficient, automated AI-based pipeline for hemibrain segmentation and subsequent volume assessment. METHODS: This study utilizes imaging data from the Endoscopic versus Shunt Treatment of Hydrocephalus in Infants trial. Pre- and postoperative T2-weighted MR images were obtained in 75 patients. Hemibrain growth curves for the artifact-free hemisphere are proposed to assess postoperative brain growth in MR images with metallic shunt artifacts. An AI-based hemibrain volume estimation pipeline was developed, consisting of a brain/CSF segmentation model and a hemibrain mask generator. Segmentation labels, including left/right hemibrain masks and brain/CSF segmentation maps, were created. The AI pipeline was trained and validated using a manually segmented data subset. The volumes of left and right brain hemispheres after surgery were calculated and analyzed. RESULTS: Postoperative hemisphere volume ratios approached the normal ratio and remained constant over time, confirming the feasibility of using hemibrain measurements as proxies for whole-brain volume assessment in the presence of metallic artifacts. Additionally, the AI-based pipeline demonstrated high accuracy in generating hemibrain masks and segmenting brain/CSF, effectively automating the process of hemibrain volume estimation. CONCLUSIONS: Hemibrain volume estimation of the unaffected hemisphere offers a feasible method for assessing brain growth over time. This process can be automated using a highly accurate AI pipeline, providing a valuable tool for monitoring brain growth in pediatric hydrocephalus patients with shunts.