Glymphatic Function and Ventricular Volumetry in Radiosurgery Patients

Meng-Hsin Lin, Chao-Ya Yang, Chun-Chih Liao, Kuo-Wei Chen, Furen Xiao

Keywords: Glymphatic system, ALPS index, CSF volume, Lateral ventricle volume, Brain aging, Neuroaging, Hydrocephalus

Abstract:

[Purpose]
This study aimed to determine whether imaging biomarkers—specifically the ALPS index, cerebrospinal fluid (CSF) volume, and lateral ventricle (LV) volume—can serve as reliable predictors of brain aging and the tendency toward hydrocephalus, characterized by ventricular dilatation. We evaluated their individual and combined predictive power for age-related changes and early ventricular enlargement, offering a non-invasive imaging approach for clinical assessment.

[Materials and Methods]
A total of 707 subjects who underwent radiosurgery for brain tumors between 2022 and 2024 were included (male-to-female ratio: 1:1.7; mean age 61 ± 13 years). MRI datasets included diffusion tensor imaging (DTI) and high-resolution T1-weighted scans. The ALPS index was derived to quantify glymphatic pathway efficiency, while CSF and lateral ventricle volumes were automatically extracted using SynthSeg. Statistical analyses employed linear regression to assess the relationship between these imaging markers and chronological age. Combined models were used to evaluate potential additive effects among parameters. The same setup is applied to predicting lateral ventricle
volume.

[Results]
All three imaging parameters—ALPS index, CSF volume, and total lateral ventricle volume—showed significant correlations with age (r = 0.363–0.424, p < 0.001). Larger CSF and ventricular volumes corresponded to advancing age, while a lower ALPS index indicated reduced glymphatic function. Each parameter individually provided moderate predictive strength, but combining them yielded higher consistency and precision in estimating age (r = 0.499) and identifying subjects showing early ventricular enlargement.

Similarly, ALPS index, CSF volume, and age each contributed meaningfully to predicting lateral ventricle volume. Individually, age (r = 0.396), CSF (r = 0.460), and ALPS index (r = –0.566) showed moderate correlations with ventricular enlargement. A combined regression model achieved the strongest performance (r = 0.644), with ALPS index emerging as the most influential predictor. These results indicate that integrating glymphatic function with structural CSF metrics provides a more stable and biologically coherent estimate of ventricular volume than any single parameter alone.

[Conclusion]
The ALPS index, CSF volume, and lateral ventricle volume each reflect distinct yet interrelated facets of brain aging. Their integration enhances the prediction of age-related changes and the tendency toward hydrocephalus, suggesting that structural expansion and glymphatic decline are parallel hallmarks of neuroaging. These multimodal biomarkers hold promise for early, non-invasive evaluation of brain fluid and structural dynamics.

Primary Subject Area: Integration of Imaging and Clinical Data

Secondary Subject Area: Segmentation

Registration Requirement: Yes

Read CFP & Author Instructions: Yes

Originality Policy: Yes

Single-blind & Not Under Review Elsewhere: Yes

LLM Policy: Yes

Submission Number: 13