AI-powered neuroimaging markers: a new era in paediatric Leigh syndrome diagnosis
Leigh syndrome is a severe pediatric mitochondrial disorder characterized by progressive neurological decline and epilepsy as a frequent manifestation. Traditional diagnostic approaches, including EEG and MRI, are often limited in their sensitivity and specificity, leading to diagnostic delays. Artificial intelligence (AI)-powered neuroimaging markers have emerged as promising tools that integrate multimodal patient data - including clinical history, imaging, and genetic sequencing - to enhance diagnostic precision and facilitate early intervention. Recent studies have demonstrated AI's ability to classify epilepsy subtypes, automate EEG interpretation, and detect early neurodegenerative changes, underscoring its clinical potential. However, challenges such as algorithm transparency, dataset bias, and ethical concerns remain. Integrating AI-driven neurotechnology with existing modalities may significantly improve the early diagnosis and prognosis of Leigh syndrome, offering a pathway toward precision neurodiagnostics in pediatric care.
Authors
- Muhammad Talha (ORCID: https://orcid.org/0009-0009-9202-2285)
- Faiza Imran
- Momina Khalid (ORCID: https://orcid.org/0009-0001-3413-2752)
- Aminath Waafira (ORCID: https://orcid.org/0009-0000-3283-1982)
- Raiha Yasser
Institutions
- King Edward Medical University (PK)
- Fatima Jinnah Medical University (PK)
- Jinnah Sindh Medical University (PK)
- Our Lady of Fatima Hospital (US)
- Maldives National University (MV)
Publication Details
- Journal
- Annals of Medicine and Surgery
- Published
- 2025-09-30
- DOI
- https://doi.org/10.1097/ms9.0000000000003999
- Primary Topic
- Obstructive Sleep Apnea Research
- Type
- article
- Field-Weighted Citation Impact
- 0.00