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 medical imaging with industrial-grade services that automate image receipt, processing and quality control, with a full audit trail. QSA was incorporated in January 2020 as a UCL spin-out, supported by UCL Business (UCLB).

Technology

Subtyping MS by biology, not by symptoms

Around 2.8 million people worldwide live with multiple sclerosis (Atlas of MS, 2020), and it often causes disability early in adult life. Clinicians classify MS by its clinical course, but the clinical course does not map neatly onto the underlying disease biology. Treatments chosen on symptoms and course alone may therefore miss the mechanisms that drive the disease. Measurable markers from brain images and blood reflect that biology more directly.

Large datasets and artificial intelligence now make it possible to find patterns that could not be detected before. QSA applies AI to imaging and blood measures to define data-driven MS subtypes and stages. 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 clinical trials, observational cohorts and routine clinical care. The aim is to improve how patients are selected for clinical trials and, in future, to help clinicians choose the most suitable therapy for each patient.