MAGNETIC RESONANCE IMAGING BY DIFFUSION TENSOR IMAGING- MICROSTRUCTURAL THALAMIC CHANGES IN PATIENTS WITH SYSTEMIC LUPUS ERYTHEMATOSUS
Bibliographic record
Abstract
PV041 / #676 Poster Topic: AS05 - CNS Lupus Background/Purpose Neuroimaging plays a crucial role in identifying neurological abnormalities in patients with Systemic Lupus Erythematosus (SLE), particularly in those with central nervous system involvement. Diffusion Tensor Imaging (DTI) is an advanced magnetic resonance imaging (MRI) technique that maps the brain’s microstructure by measuring fractional anisotropy (FA) and mean diffusivity (MD), providing additional insights beyond conventional MRI. DTI is especially useful when conventional MRI does not reveal significant findings, and it aids in both early disease detection and monitoring progression. Methods The study involved 58 childhood-onset SLE (cSLE) patients, 68 adult-onset SLE (aSLE) patients, and 60 healthy controls (HC). All participants underwent clinical, neurological, and laboratory evaluations, including disease activity and damage assessments using the SLE Disease Activity Index (SLEDAI) and Systemic Lupus International Collaborating Clinics (SLICC) scales. Mood and anxiety disorders were evaluated using the Beck Inventory, while cognitive function was assessed with the Montreal Cognitive Assessment (MoCA) (Table 1). MRI scans were performed using a Philips 3 Tesla scanner, with thalamus segmentation on T1-weighted images using FreeSurfer. Diffusion-weighted images (DWI) were analyzed using the FSL tool, and DTI scalar maps of FA, MD, Axial Diffusivity (AD), and Radial Diffusivity (RD) were generated. Mean and standard deviation values for these parameters were calculated for each thalamic region. A p-value ≤0.05 was considered statistically significant. Table 1. Demographic data, laboratory findings, neuropsychiatric manifestations, and treatment in cSLE, aSLE, and the controls. Results No significant difference in thalamic volume was found between cSLE (mean volume 12641.4mm³, SD=1571.9) and aSLE patients (mean volume 12521.3mm³, SD=1582.9). However, both groups showed significantly reduced thalamic volumes compared to the HC group (mean volume 13990.8mm³, SD=1621.8, p<0.001). DTI analysis revealed significant differences in FA, MD, RD, and AD values between the SLE groups and HC. We observed significantly lower FA values between the cSLE and HC groups in the following regions: left intralaminar (p=0.034), right anterolateral (p=0.09), right lateral caudal (p=0.005), right intralaminar (p=0.02) and right posterior (p=0.04). Significantly higher MD values between the cSLE and HC groups in the left anterolateral (p=0.047) and right anterolateral (p<0.001) regions; between the cSLE and aSLE groups in the right anterolateral region (p=0.02); and between the aSLE and HC groups in the left medial (p=0.038) and left posterior (p=0.05) regions. Significantly higher RD values between the cSLE and HC groups in the left anterolateral (p=0.046), right anterolateral (p<0.001), right caudal lateral (p=0.016), and right medial (p=0.037) regions; between the cSLE and aSLE groups in the right anterolateral region (p=0.03); and between the aSLE and HC groups in the left medial (p=0.039) and left posterior (p=0.01) regions. Significantly higher AD values between the cSLE and HC groups in the left medial region (p=0.047); and between the aSLE and HC groups in the left posterior region (p=0.006). Conclusions SLE patients exhibit reduced thalamic volume compared to HC, with more pronounced microstructural changes observed in cSLE patients compared to aSLE. These findings suggest that cSLE is associated with greater thalamic involvement and microstructural alterations. Longitudinal studies are needed to determine whether these microstructural changes are transient or permanent.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".