AD/PD 2023 talk: SuStaIn in the A4 Study

I prerecorded the audio below (8 minutes) to go with these PDF slides for AD/PD 2023 in Gothenburg, Sweden.

Disease Progression Modelling on MRI data Identifies Subtypes with Cognitive Heterogeneity in A4 Study Preclinical Trial Cohort

TL;DR: We used SuStaIn to find MRI-based subtypes in the screening data of the A4 Study clinical trial (preclinical Alzheimer’s disease) and leveraged the ADNI observational dataset to link these subtypes to heterogeneous cognitive decline.

This could potentially wash out any treatment effect (if present) in the A4 study trial. This work was completed before the results of A4 were known.

AD/PD 2023 Talk

Relevant papers:

UCSD ADRC Neurodegeneration Seminar

It was my pleasure to present these slides remotely as part of the UCSD ADRC’s Neurodegeneration Seminar Series this morning (my evening!).

Thanks to Doug Galasko for the invitation.

New paper on data-driven progression subtypes in Alzheimer’s disease

Latest paper is an amazing collaboration led by the wonderful Jake Vogel that pulled together the largest database so far of tau PET imaging of Alzheimer’s pathology in the living brain, then unleashed Alex Young’s SuStaIn algorithm to discover four previously unknown/uncharacterised subtypes.

It turns out that these are quite common (as in not rare), and they have unique symptom profiles too.

I could dig in, but here’s what Jake had to say on twitter:

Vacancy: Research Assistant in Memory Clinic Image Computing

Apply Here (closing date: 23 May 2021)

I have a vacancy for a post-Masters / pre-PhD level person interested in medical image (MRI) data wrangling and analysis, including computational modelling of neurological diseases like Alzheimer’s and Lewy Body Disease.

One important goal for the project is to use existing computational methods (from the POND group) to build a differential diagnosis tool for dementias, Specifically Alzheimer’s Disease vs Lewy body Dementia.

This is exciting for two reasons in particular: we are looking at real world data from individuals in the prodromal stage of dementia.

If you’re not quite ready for a PhD and are interested in medical image computing, this could be the role for you. The ideal candidate would have a background in computer science, physics, maths, medical image computing, or a related field.

NISOx talks

I was invited to present today to the NeuroImaging Statistics Oxford (NISOx) reading group of Prof Thomas Nichols at the Oxford Big Data Institute.

I ended up giving two talks after my first talk (on TADPOLE Challenge) generated some interest in the event-based model!

Here are the slides:

Rosetrees Interdisciplinary workshop on neurodegenerative diseases of the brain

Many thanks to the organisers of the Rosetrees interdisciplinary workshop on neurodegenerative diseases of the brain yesterday (10 Feb, via Zoom).

I had a great time presenting my talk and discussing the physics of life, plus our work on disease progression modelling in the UCL POND group.

My slides are here:
Top-down and Bottom-up models of neurodegenerative disease progression

The recording of my talk is up on YouTube:

CompAge 2020

Here’s my poster:

AAIC 2020 presentations

Here are my presentations from AAIC 2020:

MRC-ULHA Zoom Seminar

Thanks to folks in the UCL MRC Unit for Lifelong Health and Ageing (and colleagues beyond) for hosting me for a Zoom seminar today (13 May 2020).

I very much appreciate the questions, discussion, and enthusiasm for my research.

Special thanks to Sarah-Naomi James for inviting me!

Here are the slides:

CMIC seminar

Thanks to colleagues in the UCL Centre for Medical Image Computing (CMIC) and Dementia Research Centre for turning out in force yesterday for my CMIC seminar (15 January 2020).

Looking forward to following up with new results as they come in now that my UKRI Future Leaders Fellowship has started!

Here are the slides: