About us

Our story

From reading films to automated, auditable imaging

QSA's roots are in the MRI research unit at the UCL Queen Square Institute of Neurology, which has managed and analysed MS clinical trial imaging since the 1990s. Reading scans once meant examining films by hand. Today MRI is routine and image processing has advanced rapidly.

QSA combines UCL's expertise in imaging with services that automate receipt, processing and quality control, with a full audit trail. The work reaches beyond MS, from brain fingerprinting to ARIAEducation.eu, a training resource on imaging abnormalities seen with anti-amyloid treatment for Alzheimer's disease. QSA was incorporated in 2020 as a UCL spin-out, supported by UCL Ventures.

Technology

Subtyping neurological conditions by biology, not by symptoms

Neurological conditions are often classified by symptoms and clinical course, but the course does not map neatly onto the underlying biology. Treatments chosen on symptoms alone may miss mechanisms that drive the disease. Markers from brain images and blood reflect that biology more directly. MS is one example: around 2.8 million people worldwide live with it (Atlas of MS, 2020), and it is still labelled by clinical course.

QSA applies AI to imaging and blood measures to define data-driven subtypes and stages, using Subtype and Stage Inference (SuStaIn), built for neurodegenerative diseases. In MS, changes on MRI and in blood biomarkers can come before clinical worsening, so these subtypes may help identify patients at higher risk of disability progression. QSA works with data from trials, observational cohorts and routine care. The aim is to improve how patients are selected for trials and, in future, help clinicians choose the most suitable therapy for each patient.