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. 2024 Dec 1;95(6):1329-1337.
doi: 10.1227/neu.0000000000003015. Epub 2024 Jun 6.

Artificial Intelligence for Automatic Analysis of Shunt Treatment in Presurgery and Postsurgery Computed Tomography Brain Scans of Patients With Idiopathic Normal Pressure Hydrocephalus

S Shailja  1 , Christopher Nguyen  2 , Krithika Thanigaivelan  1 , Chandrakanth Gudavalli  1 , Vikram Bhagavatula  1 , Jefferson W Chen  2 , B S Manjunath  1
Affiliations

Artificial Intelligence for Automatic Analysis of Shunt Treatment in Presurgery and Postsurgery Computed Tomography Brain Scans of Patients With Idiopathic Normal Pressure Hydrocephalus

S Shailja et al. Neurosurgery. .

Abstract

Background and objectives: Ventriculo-peritoneal shunt procedures can improve idiopathic normal pressure hydrocephalus (iNPH) symptoms. However, there are no automated methods that quantify the presurgery and postsurgery changes in the ventricular volume for computed tomography scans. Hence, the main goal of this research was to quantify longitudinal changes in the ventricular volume and its correlation with clinical improvement in iNPH symptoms. Furthermore, our objective was to develop an end-to-end graphical interface where surgeons can directly drag-drop a brain scan for quantified analysis.

Methods: A total of 15 patients with 47 longitudinal computed tomography scans were taken before and after shunt surgery. Postoperative scans were collected between 1 and 45 months. We use a UNet-based model to develop a fully automated metric. Center slices of the scan that are most representative (80%) of the ventricular volume of the brain are used. Clinical symptoms of gait, balance, cognition, and bladder continence are studied with respect to the proposed metric.

Results: Fifteen patients with iNPH demonstrate a decrease in ventricular volume (as shown by our metric) postsurgery and a concurrent clinical improvement in their iNPH symptomatology. The decrease in postoperative central ventricular volume varied between 6 cc and 33 cc (mean: 20, SD: 9) among patients who experienced improvements in gait, bladder continence, and cognition. Two patients who showed improvement in only one or two of these symptoms had <4 cc of cerebrospinal fluid drained. Our artificial intelligence-based metric and the graphical user interface facilitate this quantified analysis.

Conclusion: Proposed metric quantifies changes in ventricular volume before and after shunt surgery for patients with iNPH, serving as an automated and effective radiographic marker for a functioning shunt in a patient with iNPH.

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