Corticobulbar Tract Involvement in Neuropsychiatric Systemic Lupus Erythematosus: A Case Report

Symmetric leukoencephalopathy associated with systemic lupus erythematosus: A systematic review of a distinctive neurorheumatologic syndrome

BACKGROUND

A symmetric leukoencephalopathy can occur in the context of systemic lupus erythematosus (SLE), often as a first manifestation of underlying rheumatologic disease. Recognition of this distinctive syndrome can prompt investigation for SLE when undiagnosed, or prompt treatment initiation when the diagnosis is already known. Earlier recognition of this syndrome could lead to more effective treatment of the disease.

METHODS

Clinical, laboratory, and radiographic features of three patients were described from an academic medical center in the United States with treatment dates between 2015 and 2022. A systematic review of literature from 1991 to 2023 yielded data for an additional 23 patients.

RESULTS

Twenty-six total patients with symmetric leukoencephalopathy were included in this study. The median age of the patients was 37 years (range 10-69), 22 patients (85 %) were female, and 4 (15 %) were male. Fourteen of 26 patients (54 %) had this as the first clinical manifestation of SLE. Contrast enhancement was present on MRI brain in 3/26 (88 %) patients. Twenty patients (77 %) were treated with pulse-dose steroids, and all but one patient received some immunomodulatory therapy. Seven patients (27 %) progressed to death. No meaningful predictive differences were found between patients who survived and those who did not.

CONCLUSIONS

In this case series and literature review patients developed symmetric leukoencephalopathy in systemic lupus erythematosus most often as the first clinical manifestation of SLE. Clinicians should consider this syndrome in any patient with acute onset of symmetric leukoencephalopathy on brain magnetic resonance imaging.

Role of F-18 FDG PET-CT in neuropsychiatric systemic lupus erythematosus

BACKGROUND

Neuropsychiatric systemic lupus erythematosus (NPSLE) is a major contributor to morbidity and mortality in systemic lupus erythematosus (SLE) patients. To date no single clinical, laboratory or imaging test has proven accurate for NPSLE diagnosis which is a testament to the intricate and multifactorial pathophysiological mechanisms suspected to exist. Functional imaging with FDG PET-CT has shown promise in NPSLE diagnosis, detecting abnormalities prior to changes evident on anatomical imaging. Research indicates that NPSLE may be more aggressive in people of African descent with higher mortality rates, making rapid and correct diagnosis even more important in the African context.

METHODS

In this narrative review, we provide a thorough appraisal of the current literature on the role of FDG PET-CT in NPSLE. Large, well-known databases were searched using appropriate search terms. Manual searches of references of retrieved literature were also included.

FINDINGS

A total of 73 article abstracts were assessed, yielding 26 papers that were directly relevant to the topic of FDG PET-CT in NPSLE. Results suggest that FDG PET-CT is a sensitive imaging test for NPSLE diagnosis and may play a role in assessing treatment response. It is complementary to routine anatomical imaging, particularly in diffuse manifestations of the disease. Newer quantitative analyses are commonly used for interpretation and can detect even subtle abnormalities, missed on visual inspection. Findings of group-wise analyses of FDG PET-CT scans in NPSLE patients are important in furthering our understanding of the complicated pathophysiological mechanisms involved. Limitations of FDG PET-CT include its lack of specificity, high cost and poor access.

CONCLUSION

FDG PET-CT is a sensitive test for NPSLE diagnosis but is hampered by lack of specificity. It is a valuable tool for clinicians managing SLE patients, particularly when anatomical imaging is negative. Its exact application will depend on the local context and clinical scenario.

Dysphagia prognosis prediction via corticobulbar tract assessment in lateral medullary infarction: a diffusion tensor tractography study

We investigated the capacity for dysphagia prognosis prediction using diffusion tensor tractography (DTT) to assess the state of the corticobulbar tract (CBT) during the initial period following lateral medullary infarction (LMI). Twenty patients with LMI and 20 control subjects were recruited for this study. The patients were classified into two subgroups: subgroup A (16 patients with nasogastric tube required for six months or less after LMI onset) and subgroup B (4 patients with nasogastric tube required for more than six months after onset). DTT was used to reconstruct the CBTs of each patient and control subject, and the fractional anisotropy (FA) and tract volume (TV) measurements were obtained. In the affected hemisphere, the FA value of the CBT was significantly lower in subgroup B than in subgroup A and the control group (p < 0.05), with no significant difference between subgroup A and the control group. In the affected and unaffected hemispheres, the TV values of CBT in subgroups A and B were lower than those of the control group (p < 0.05), with no significant difference between subgroups A and B. In addition, among the four patients of subgroup B, reconstruction of the CBT was not possible in three patients, and the remaining patients exhibited on old lesion in the corona radiate involving descending pathway of the CBT in the affected hemisphere. We found that the injury severity of the CBT in the affected hemisphere appeared to be related to a poor dysphagia prognosis following LMI. Our results suggest that evaluation of the CBT state during the early post-LMI could be useful for dysphagia prognosis prediction.

Broad Learning Enhanced 1H-MRS for Early Diagnosis of Neuropsychiatric Systemic Lupus Erythematosus

In this paper, we explore the potential of using the multivoxel proton magnetic resonance spectroscopy (¹H-MRS) to diagnose neuropsychiatric systemic lupus erythematosus (NPSLE) with the assistance of a support vector machine broad learning system (BL-SVM). We retrospectively analysed 23 confirmed patients and 16 healthy controls, who underwent a 3.0 T magnetic resonance imaging (MRI) sequence with multivoxel ¹H-MRS in our hospitals. One hundred and seventeen metabolic features were extracted from the multivoxel ¹H-MRS image. Thirty-three metabolic features selected by the Mann-Whitney U test were considered to have a statistically significant difference (p < 0.05). However, the best accuracy achieved by conventional statistical methods using these 33 metabolic features was only 77%. We turned to develop a support vector machine broad learning system (BL-SVM) to quantitatively analyse the metabolic features from ¹H-MRS. Although not all the individual features manifested statistics significantly, the BL-SVM could still learn to distinguish the NPSLE from the healthy controls. The area under the receiver operating characteristic curve (AUC), the sensitivity, and the specificity of our BL-SVM in predicting NPSLE were 95%, 95.8%, and 93%, respectively, by 3-fold cross-validation. We consequently conclude that the proposed system effectively and efficiently working on limited and noisy samples may brighten a noinvasive in vivo instrument for early diagnosis of NPSLE.