Longitudinal FreeSurfer Volumetric Analysis as a High‑sensitivity Radiographic Tool for Disease Progression in Rasmussen Syndrome
Prabhumallikarjun Patil1, Ekta Shah1, Madeleine Hebert McLaughlin1, Grace Gombolay1, Varun Kannan2, Shayan Monabatti3, Eswar Damaraju4, Adam Goldman - Yassen1, Kartik Reddy1
1Emory University SOM, CHOA, 2Emory/CHOA, 3Emory University SOM, 4CHOA
Background:
Rasmussen syndrome (RS) is an immune‑mediated, refractory epilepsy characterized by progressive unilateral cortical atrophy. Standard radiological surveillance relies on qualitative assessment and does not quantify volume loss as part of clinical care. Longitudinal analysis pipelines such as FreeSurfer (FS) use machine learning approaches to generate biologically meaningful metrics of disease progression by quantifying regional brain volume loss. The FS longitudinal pipeline constructs an unbiased within subject template across all time points, minimizing session to session variability and avoiding over regularization.
Design/Methods:
We conducted a single‑center retrospective case series of two patients with confirmed Rasmussen syndrome who underwent serial brain MRI. All imaging time points were processed using the Standard FreeSurfer 8.1 longitudinal pipeline.
Results:
Results: Patient 1 (10.2‑month follow‑up) demonstrated cumulative ipsilateral volume loss involving the thalamus (−32.2%; 5,376 → 3,645 mm³), hippocampus (−22.7%), caudate (−15.8%), and putamen (−13.8%), with relative contralateral thalamic stability (−0.7%). The thalamic asymmetry index (TAI) increased from −11.7% to −29.9%. During two intervals qualitatively reported as “no interval change” on standard radiology reports, FS 8.1 detected ipsilateral thalamic atrophy of −6.5% and −3.2%, along with caudate (−8.6%) and putaminal (−7.4%) volume loss.
Patient 2 (39.3‑month follow‑up) exhibited ipsilateral thalamic volume loss of −18.0% compared with −9.7% contralaterally and caudate loss of −17.7%. In a similarly reported “no‑change” interval on conventional MRI interpretation, FS 8.1 identified thalamic (−2.3%) and caudate (−2.8%) volume loss with contralateral stability. Across both cases, three radiology reports did not mention progression despite quantitatively demonstrable volume loss detected by FS analysis.
Conclusions:
Longitudinal FS volumetric analysis detected progressive brain volume loss and identified disease progression at three independent time points earlier to conventional radiological reporting. Incorporation of longitudinal quantitative volumetric analysis into routine imaging workflows may facilitate earlier detection of disease progression and inform medical and surgical decision making.
Generative AI Usage
No, did not use generative AI in the drafting or editing in this abstract.
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