Spectrum of Neuroradiological Findings in Novel High-risk Paraneoplastic Syndromes
Sema Akkus1, Mahmoud Elkhooly2, Suban Amatya3, Kriti Shrestha3, Yusuf Kagzi4, Shitiz Sriwastava5
1Istanbul University Cerrahpasa Medical Faculty, 2Department of Neurology, Southern Illinois university, 3Department of Medicine, Patan Academy of Health Sciences, 4Mahatma Gandhi Memorial Medical College, 5UT Health Houston
Objective:
To systematically review neuroradiological findings in patients positive for novel high-risk paraneoplastic antibodies - LUZP4-IgG, KLHL11, TRIM46, and PDE10A IgG.
Background:
Paraneoplastic neurological syndromes (PNS) demonstrate characteristic antibodies and imaging patterns reflecting the areas of immune-mediated damage. Recent studies have identified novel high-risk antibodies linked to distinct imaging findings that can facilitate recognition of these rare syndromes.
Design/Methods:
A systematic literature review was conducted for studies published between 2014-2023 reporting neuroimaging findings in patients with high-risk paraneoplastic antibodies. PubMed and Embase were searched, identifying 379 articles. After screening, 96 patients positive for the novel high-risk antibodies were included in the final analysis. Data was extracted on antibody subtype, associated tumor, clinical phenotype, and neuroradiological findings.
Results:
The review comprised 22 TRIM46, 40 PDE10A, 6 LUZP4, and 28 KLHL11-positive patients. Rhombencephalitis predominated in 61% of LUZP4 and 44% of KLHL11 cases. Cerebellar atrophy occurred in 64% of TRIM46 and 69% of KLHL11 cases. Temporal lobe/limbic abnormalities were seen in 22% of KLHL11 cases. Basal ganglia lesions typified 40% of PDE10A cases. High-risk antibodies associated with deep brain lesions, younger male patients, and 61% mortality.
Conclusions:
Specific neuroimaging patterns associate with these novel antibodies. Recognizing the distinctive radiological findings could enable timely PNS diagnosis and tumor detection. Further research on sensitivity, specificity, and testing algorithms is warranted. Appropriate neuroimaging is crucial to avoid delayed or missed PNS diagnoses.