Susceptibility-Weighted Imaging Features Show Promise in Distinguishing AQP4-Negative-NMOSD From MS


A recent study highlighted the potential of susceptibility-weighted image features as imaging biomarkers to differentiate patients with multiple sclerosis from those with neuromyelitis optica spectrum disorder.

Fu-Dong Shi, MD, professor and chairman, chief neurologist, at Center for Neuroimmunology, Beijing Tiantan Hospital, Capital Medical University, in Beijing, China

Fu-Dong Shi, MD

Credit: APSNI

In a new analysis of a prospective cohort study (NCT0410683) published in Multiple Sclerosis and Related Disorders, findings showed that susceptibility-weighted image (SWI) imaging features had a high sensitivity and high specificity to distinguish multiple sclerosis (MS) from aquaporin 4 (AQP4)-immunoglobulin G (IgG)-negative neuromyelitis optica spectrum disorder (NMOSD). These results suggest SWI imaging features including paramagnetic rim and nodular lesions with signal intensity changes and central vein sign (CVS) could be potential imaging biomarkers for differentiating the 2 disorders.1

Among 160 patients (AQP4- NMOSD, n = 22; AQP4+ NMOSD, n = 65; MS, n =73), investigators observed paramagnetic rim lesion (0/120 lesions, 0 %) and nodular (1/120, 1 %) lesions with hypointense signals on SWI in the AQP4- NMOSD group. These characteristics were similar to those reported in patients with AQP4+ NMOSD (rim: 0/369 lesions, 0 %, P = 1.000; nodular: 10/369 lesions, 2.7 %, P = 1.000), but differed significantly from those observed in the MS group (rim: 162/1665 lesions, 9.7 %, P <.001; nodular: 392/1665 lesions, 23.5 %, P < 0.001).

Top Clinical Takeaways

  • SWI imaging features, such as paramagnetic rim and nodular lesions, exhibit high sensitivity and specificity in differentiating MS from AQP4-negative NMOSD.
  • Practitioners are advised to rely on SWI features for additional diagnostic guidance when faced with challenges in distinguishing MS from AQP4-negative NMOSD.
  • AQP4-negative NMOSD patients show heterogeneity, and the study suggests the need for future multicenter studies or independent validation to further support the utility of SWI features as imaging biomarkers.

“When challenged with ambiguous clinical presentation and difficulties in distinguishing MS from AQP4- NMOSD, we recommend that practitioners rely on the SWI features for additional diagnostic guidance, which achieve a high accuracy in distinguishing MS from APQ4- NMOSD and AQP4+ NMOSD,” senior author Fu-Dong Shi, MD, professor and chairman, chief neurologist, at Center for Neuroimmunology, Beijing Tiantan Hospital, Capital Medical University, in Beijing, China, and colleagues wrote.1

READ MORE: Non-P42 MOG-IgG Serotype Predicts Worsened Disease Progression, Relapse Rate in MOGAD

Investigators prospectively recruited NMOSD with AQP4-IgG-negative and IgG-positive, and participants with MS from the Clinical and Imaging Patterns of Neuroinflammation Diseases in China project between 2019 and 2021.2 The researchers analyzed SWI features including paramagnetic rim and nodular lesions with signal intensity changes and CVS and compared them among the groups. Authors noted that the sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were determined for differentiating patients with MS from AQP4- NMOSD.

In the analysis, authors observed that patients with AQP4- NMOSD showed fewer average CVS+ rate (12%) compared with patients who had MS (46%, P <.001), which was similar to AQP4+ NMOSD (13%, P = 1.000). The SWI imaging features denoting lesions with paramagnetic rim or nodular hypointense SWI signals demonstrated a 90.4% sensitivity, 95.5% specificity, 98.5% PPV, and 75% NPV. In addition, the criteria with at least 3 CVS lesions revealed a sensitivity of 91.8%, specificity of 90.9%, PPV of 97.1%, and NPV of 76.9% in distinguishing MS from AQP4- NMOSD.

All told, patients with AQP4- NMOSD presented great heterogeneity and their pathology had difficulty with determining certainty, thus these study patients may not be representative of this population. Additionally, investigators noted that not all data in the current study may come from the first available MRI carried out at the initial stage of the disease. Therefore, researchers suggested that analysis of early MRI data from the initial stage may be more useful for diagnosis. Authors noted the small sample size of the study and recommended future multicenter studies, or independent validation of data be conducted to further support the utility of SWI features as imaging biomarkers.

“In previous studies, only comparative studies of SWI features in AQP4+ NMOSD and MS were performed, and we analyzed SWI features in this group of AQP4- NMOSD for the first time. AQP4- NMOSD patients represent a diagnostic challenge for clinical practice, even NMO and MS experts often disagree on diagnoses formulated for these patients,” Shi et al noted.1 “AQP4- NMOSD patients are heterogeneous, often present features that overlap with those displayed by NMOSD and MS patients, and sometimes show monophasic disease.”

These findings are similar to another recent study where susceptibility-based imaging (SbI) demonstrated a high sensitivity and specificity to differentiate pediatric-onset multiple sclerosis (POMS) from pediatric myelin oligodendrocyte glycoprotein (MOG) antibody-associated disease (MOGAD). Published in the Multiple Sclerosis Journal, the results also suggest that CVS and paramagnetic rim lesions (PRLs) in SbI are highly specific markers for POMS which may be vital for early differentiation for treatment and disability prevention.3

Using SbI, the CVS-positive rate distinguished 26 cases of POMS (mean age, 13.7 years; women, 63%; median Expanded Disability Status Scale [EDSS], 1.5) from 14 cases of MOGAD (mean age, 10.8 years; women, 35%; mean EDSS, 1.0). Among these 40 cases of participants, investigators observed a receiver operator curve (ROC) equaled 1 (P <.0001), with a cutoff of 41% perfectly separating both groups. “This study shows that several biomarkers using SbI can be extremely helpful to discriminate between MS and MOG associated disease in children,” senior author Emmanuelle Waubant, MD, PhD, professor of neurology at University of California, San Francisco, told NeurologyLive®.

1. Gao C, Su L, Li H, et al. Susceptibility-weighted image features in AQP4-negative-NMOSD versus MS. Mult Scler Relat Disord. 2024;82:105406. doi:10.1016/j.msard.2023.105406
2. Xu Y, Ren Y, Li X, et al. Persistently Gadolinium-Enhancing Lesion Is a Predictor of Poor Prognosis in NMOSD Attack: a Clinical Trial. Neurotherapeutics. 2021;18(2):868-877. doi:10.1007/s13311-020-00973-9
3. Sacco S, Virupakshaiah A, Papinutto N, et al. Susceptibility-based imaging aids accurate distinction of pediatric-onset MS from myelin oligodendrocyte glycoprotein antibody-associated disease. Mult Scler. 2023;29(14):1736-1747. doi:10.1177/13524585231204414
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