Integrating Metabolic, Perfusion, and Microstructural Parameters for Quantitative Neuroimaging in Rare...

Background/Objectives: The use of quantitative neuroimaging to establish objective biomarkers in neurodegenerative diseases (NDD) has attracted increasing interest over the last decade. Advanced magnetic resonance imaging (MRI) such as arterial spin labeling (ASL) and diffusion tensor imaging (DTI), as well as [¹⁸F]fluorodeoxyglucose ([¹⁸F]FDG) positron emission tomography (PET), could provide clinically meaningful biomarkers and may support differential diagnosis. The aim of this investigator-initiated, single-center, retrospective comparative study was to implement a framework for multimodal neuroimaging to evaluate cases with rare NDD, using a methodological approach that integrates metabolic, perfusion, and microstructural parameters from simultaneous FDG-PET/MRI, and to investigate its potential to facilitate diagnosis. Methods: Three patients with pathological motor signs (1f/2m; 63, 73, and 52 years) and 19 control subjects with subjective cognitive deficits (SCDs) underwent combined FDG-PET/MRI with pseudo-continuous ASL and DTI. Standardized uptake values (SUVs), relative cerebral blood flow (rCBF), and fractional anisotropy (FA) were calculated to identify pattern alterations in individual patients based on parameterization mapping. The final diagnosis was corticobasal degeneration (CBD, n = 1) or primary lateral sclerosis (PLS, n = 2). Results: At the individual patient level, disease-specific changes in defined brain regions could be demonstrated and quantified compared to control subjects. All three patients showed significantly decreased FA, primarily along parts of the course of the corticospinal tract (CST). In the patient with CBD, asymmetric SUVR and rCBF decreases were observed, mostly overlapping with motor regions. In the two patients with PLS, SUVR revealed mostly unspecific findings (hypothetically due to a slow progression rate or due to potentially early disease stages), while ASL indicated decreased rCBF primarily overlapping within the motor cortex. Changes at the gray matter level were primarily located adjacent to changes in white matter, as indicated by the multimodal analysis approach using simultaneously acquired FDG-PET/MRI data. Conclusions: According to this proof-of-concept study, multimodal neuroimaging by the combination of quantitative MRI and FDG-PET has the potential to guide differential diagnosis in rare NDDs, especially if clinical diagnosis is not straightforward to achieve. Since particularly early diagnosis remains essential for patient counseling, effective treatment, and clinical management, the present framework appears helpful to be developed further until it aligns and integrates with clinical routine.