Alessandra Splendiani

Background/Objectives: Automated brain volumetry is increasingly integrated into the work-up of several neurological disorders, yet between-software variability may limit the interchangeability of absolute measures. This study aimed to assess inter-software variability, agreement, and interchangeability among four clinically available AI-based brain volumetry tools. Methods: We conducted a single-center, retrospective comparison of four clinically available tools (Neurophet AQUA^®, icobrain dm^®, mdbrain^®, Pixyl^®) applied to identical 3D T1-weighted MRI examinations (IR-FSPGR, 1 mm isotropic) acquired at 3 T in 47 adults referred for tremor evaluation. Absolute volumes (mL) were extracted for hippocampus, temporal, parietal, and frontal lobes, lateral ventricles, and total brain volume; the occipital lobe was analyzed where reported (three tools). Region-wise complete-case analyses were performed. Repeated-measures ANOVA with Bonferroni post hoc tests assessed systematic differences, and intraclass correlation coefficients (two-way mixed, consistency) were reported as single- and average-measure with 95% CIs to quantify agreement. Results: Across regions, all tests were significant (p < 0.001), indicating method-dependent scale offsets typically on the order of ~20–40%. A consistent pattern emerged: icobrain dm^® yielded the largest absolute volumes, Neurophet AQUA^® the lowest, mdbrain^® tended to be lower for parietal measurements, and Pixyl^® was generally intermediate. Agreement was structure-dependent: excellent for lateral ventricles (single-measure ICC ≈ 0.92 [0.85–0.96]; average-measure ICC ≈ 0.98 [0.96–0.99]); good-to-excellent for temporal and parietal lobes (average-measure ICC ≈ 0.83–0.84); moderate-to-good for hippocampus and total brain volume (TBV) (average-measure ICC ≈ 0.79–0.81), with only moderate single-measure agreement for TBV (ICC ≈ 0.51); and lowest for the frontal lobe (single-measure ICC ≈ 0.43 [0.23–0.65]; average-measure ICC ≈ 0.75 [0.54–0.88]). In the occipital lobe (three tools), Neurophet AQUA^® yielded substantially smaller values than icobrain dm^® and mdbrain^® (p < 0.0001). Conclusions: Overall, absolute volumetric outputs are not directly interchangeable across platforms, but relative subject ranking is largely preserved; platform-consistent analysis is advisable for longitudinal monitoring, and cross-site studies should implement calibration/harmonization before pooling data.

Purpose: This study investigated glymphatic function in tremor disorders using the diffusion tensor imaging–derived ALPS (analysis-along-the-perivascular-space) index, a non-invasive surrogate of perivascular fluid movement. Materials and Methods: Fourty-three patients with tremor-dominant Parkinson’s disease (PD, n=22) or essential tremor (ET, n=21), aged 50–75, were retrospectively compared with 18 age-matched healthy controls (HC) imaged with the same 3 T MRI protocol. Subjects with significant cognitive impairment, white matter disease, other CNS disorders, or poor-quality diffusion data were excluded. ALPS indices were calculated from projection and association fibre regions. Results: Both PD (mean ALPS = 1.34 ± 0.19) and ET ( 1.31 ± 0.13) groups exhibited 12 significantly lower ALPS values than HC ( 1.54±0.11 P < 0.05), but no difference was 13 found between PD and ET. In PD, lower ALPS correlated with greater tremor severity and older age, particularly in the right hemisphere (R²=0.80, p=0.003). ET showed weaker clinical associations though MoCA correlated positively with right-hemisphere ALPS (ρ=0.462, p=0.018). Conclusion: The findings indicate perivascular diffusivity is reduced in both tremor-dominant PD and ET, supporting a role for glymphatic dysfunction in their pathophysiology, though larger, prospective studies are needed to validate this observation.

Quantitative magnetic resonance imaging (qMRI) denotes MRI methods that estimate physical tissue parameters in units, rather than relative signal. Typical readouts include T1/T2 relaxation (ms; or R1/R2 in s⁻¹), proton density (%), diffusion metrics (e.g., ADC in mm²/s, FA), magnetic susceptibility (χ, ppm), perfusion (e.g., CBF in mL/100 g/min; rCBV; K^trans), and regional brain volumes (cm³; cortical thickness). This review synthesizes brain qMRI across T1/T2 relaxometry, myelin/MT (MWF, MTR/MTsat/qMT), diffusion (DWI/DTI/DKI/IVIM), susceptibility imaging (SWI/QSM), perfusion (DSC/DCE/ASL), and volumetry using a unified framework: physics and signal model, acquisition and key parameters, outputs and units, validation/repeatability, clinical applications, limitations, and future directions. Our scope is the adult brain in neurodegenerative, neuro-inflammatory, neuro-oncologic, and cerebrovascular disease. Representative utilities include tracking demyelination and repair (T1, MWF/MTsat), grading and therapy monitoring in gliomas (rCBV, K^trans), penumbra and tissue-at-risk assessment (DWI/DKI/ASL), iron-related pathology (QSM), and early dementia diagnosis with normative volumetry. Persistent barriers to routine adoption are protocol standardization, vendor-neutral post-processing/QA, phantom-based and multicenter repeatability, and clinically validated cut-offs. We highlight consensus efforts and AI-assisted pipelines, and outline opportunities for multiparametric integration of complementary qMRI biomarkers. As methodological convergence and clinical validation mature, qMRI is poised to complement conventional MRI as a cornerstone of precision neuroimaging.

Objectives: To develop a practical consensus for standardizing communication between rheumatologists and radiologists regarding magnetic resonance imaging (MRI) of the sacroiliac joints and spine in the diagnosis and management of axial spondyloarthritis (axSpA). Methods: A task force comprising six rheumatologists and five musculoskeletal radiologists with expertise in axSpA imaging reviewed the Assessment of SpondyloArthritis International Society (ASAS) framework to draft initial recommendations and define project goals. A broader expert panel (21 rheumatologists, 19 radiologists) then participated in a voting process to refine and validate these recommendations. Final endorsement was sought from the steering committees of the Italian Society of Medical and Interventional Radiology (SIRM) and the Italian Society of Rheumatology (SIR) using a modified Delphi method. Results: Thirty-one recommendations were validated, organized into eight domains. Domain 1 outlines five overarching principles. Domain 2 comprises recommendations on clinical features, symptoms, and risk factors. Additional domains address MRI technical parameters, including image quality and sequencing (Domain 3), and standardized reporting criteria. For the sacroiliac joints (Domains 4 and 5), five signs of inflammation and six of structural damage are defined. For the spine (Domains 6 and 7), five inflammatory and four structural features are specified. Domain 8 provides guidance on report conclusions. The recommendations were endorsed by SIRM/SIR with 88.5% approval. Conclusion: This consensus offers structured guidance for MRI requesting and reporting in axSpA, fostering clear communication between radiologists and rheumatologists. The standardized approach aims to improve diagnostic accuracy and patient outcomes.

Objective: This study aimed to explore the association between glymphatic function, as assessed by the diffusion tensor imaging along perivascular space (DTI‐ALPS) index, and headache frequency in individuals with migraine. Additionally, it evaluated whether sleep quality modulates this relationship. Background: Migraine has a complex pathophysiology involving genetic predispositions, comorbidities, and psychosocial factors. Emerging evidence highlights the glymphatic system—responsible for brain waste clearance—as a potential contributor to migraine pathogenesis. As poor sleep quality exacerbates glymphatic dysfunction, it might have an impact on migraine chronification. Methods: This cross‐sectional study included 106 individuals with migraine (80.2% female; median age: 45.0 years, interquartile range = 37.0–52.0) between June 2018 and February 2020. Glymphatic function was assessed using the DTI‐ALPS index derived from brain magnetic resonance imaging, whereas sleep quality was evaluated with the Pittsburgh Sleep Quality Index. First, we evaluated the association between DTI‐ALPS index and monthly headache days. A second model included the dichotomized Pittsburgh Sleep Quality Index score (“poor” vs. “good” sleepers) and its interaction with the DTI‐ALPS index to examine the moderating role of sleep quality in the relationship between glymphatic function and monthly headache days. Results: Higher DTI‐ALPS index values were associated with fewer monthly headache days in the overall sample while controlling for age and sex (adjusted Incidence Rate Ratio [IRR] = 0.37; 95% confidence interval [CI] = 0.16–0.86, p = 0.020). Additionally, there was a significant interaction between DTI‐ALPS index and sleep quality (adjusted IRR = 0.13; 95% CI = 0.02–0.76, p = 0.024) in predicting monthly headache days. We found an association between lower DTI‐ALPS and higher headache days only in participants with poor sleep quality (adjusted IRR = 0.21; 95% CI = 0.08–0.59, p = 0.003) whereas no association was found in good sleepers (adjusted IRR = 1.66; 95% CI = 0.38–7.16, p = 0.500). Results remained consistent after adjusting for clinical variables such as disease duration, medication overuse, cutaneous allodynia, aura status, and migraine subtype. Conclusion: Poor sleep quality moderates the association between glymphatic dysfunction and monthly headache days. The results highlight the potential importance of sleep interventions in managing migraine and improving brain glymphatic function.

Background: Reduced Temporal Muscle Thickness (TMT) has been proposed as a marker of sarcopenia in Parkinson’s Disease (PD) and Essential Tremor (ET). This study aimed to assess TMT measured on brain MRI in PD and ET patients undergoing unilateral Vim thalamotomy with MR-guided Focused Ultrasound (MRgFUS). Methods: This retrospective single-center study (2019–2023) included patients with tremor-dominant PD or ET refractory to medical therapy. Demographic data, disease duration, and tremor severity (Fahn-Tolosa-Marin scale) were collected. Brain MRI and clinical evaluations were performed at baseline and during follow-up (1 month, 6 months, 1 year, and 2 years). TMT was manually measured on axial T1-weighted MR images. Statistical analyses evaluated differences and correlations between TMT and clinical variables. Results: A total of 165 patients (69 PD, 96 ET) were analyzed. Disease duration was longer in ET patients ( p < 0.001), with no significant age difference. TMT did not differ significantly between PD and ET groups ( p = 0.08). In ET patients, TMT correlated nega-tively with age (r = −0.24, p = 0.03), while no correlation was found in PD patients. At 2 year follow-up, TMT negatively correlated with tremor reduction in both PD (r = −0.42, p = 0.03) and ET (r = −0.34, p = 0.05) groups. Conclusions: In our series, no significant differences emerged between ET and PD patients regarding TMT status as a surrogate marker of sarcopenia. Lower TMT may be associated with worse tremor outcomes after MRgFUS thalamotomy and could serve as a supportive imaging biomarker in patient assessment for tremor treatment.

Background: Accurate assessment of brain atrophy is essential in the diagnosis and monitoring of brain aging and neurodegenerative disorders. Radiological methods range from narrative reporting to semi-quantitative visual rating scales (VRSs) and fully automated volumetric software. However, their integration and consistency in clinical practice remain limited. Methods: In this retrospective study, brain MRI images of 43 patients were evaluated. Brain atrophy was assessed by extrapolating findings from narrative radiology reports, three validated VRSs (MTA, Koedam, Pasquier), and Pixyl.Neuro.BV, a commercially available volumetric software platform. Agreement between methods was assessed using intraclass correlation coefficients (ICCs), Cohen’s kappa, Spearman’s correlation, and McNemar tests. Results: Moderate correlation was found between narrative reports and VRSs (ρ = 0.55–0.69), but categorical agreement was limited (kappa = 0.21–0.30). Visual scales underestimated atrophy relative to software (mean scores: VRSs = 0.196; software = 0.279), while reports tended to overestimate. Agreement between VRSs and software was poor (kappa = 0.14–0.33), though MTA showed a significant correlation with hippocampal volume. Agreement between reports and software was lowest for global atrophy. Conclusions: Narrative reports, while common in practice, show low consistency with structured scales and quantitative software, especially in subtle cases. VRSs improve standardization but remain subjective and less sensitive. Integrating structured scales and volumetric tools into clinical workflows may enhance diagnostic accuracy and consistency in dementia imaging.

Several previous subjective- or interview-based reports indicated a reduced sleep quality and quantity as well as a great incidence of insomnia troubles in prisoners living in jail. The aim of the present study is to assess the quality and quantity of sleep by using, for the first time, actigraphy. A total of thirty male prisoners and thirty male control volunteers accepted to participate in this study: to this end, they filled in some questionnaires to assess state and trait anxiety, depression, sleep quality, and insomnia severity. In addition, their sleep was actigraphically recorded for seven consecutive nights. The main results indicate a worsened mood in prisoners than in controls (with increased anxiety and depression) as well as a subjectively reported low sleep quality (higher scores at PSQI) with a clinical presence of insomnia complaints (as indicated by ISI scores). Moreover, objectively assessed sleep by means of actigraphy exhibited some worrying results, namely a longer sleep onset and a reduced total sleep time was seen in prisoners with respect to controls. The results have been discussed in the light of potential effects of sleep quality and quantity as well as of mood symptoms on cognitive functioning, as well as with respect to prisoners’ health and well-being.