UCL Centre for Medical Image Computing


Marco Battaglini - Stanley Durrleman - CMIC seminar series

23 January 2019, 1:00 pm–2:00 pm

Talks by Marco Battaglini and Stanley Durrleman - as part of our seminar series

Event Information

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Roberts LT 106
Roberts Building
Malet Place
United Kingdom

Stanley Durrleman, Co-Head, INRIA/ICM ARAMIS Lab

Title: Simulating Alzheimer's disease progression with personalised digital brain models

Abstract: Simulating the effects of Alzheimer's disease on the brain is essential to better understand, predict and control how the disease progresses in patients. Our limited understanding of how disease mechanisms lead to visible changes in brain images and clinical examination hampers the development of biophysical simulations.

Instead, we propose a statistical learning approach, where the repeated observations of several patients over time are used to synthesise personalised digital brain models. They provide spatiotemporal views of structural and functional brain alterations and associated scenarios of cognitive decline at the individual level.

We show that the personalisation of the models to unseen subjects reconstructs their progression with errors of the same order as the uncertainty of the measurements. Simulation of synthetic patients generalise the distributions of the data in the training cohort. The analysis of factors modulating disease progression evidences a prominent sexual dimorphism and probable compensatory mechanisms in APEO-$\varepsilon$4 carriers.

This first-of-its-kind simulator offers an unparalleled way to explore the heterogeneity of the disease's manifestation on the brain, and to predict its progression in each patient.



Marco Battaglini, Quantitative Neuroimaging Lab of Siena University (Italy)

Title: Pipeline developed at Quantitative Neuroimaging Lab for assessing atrophy rate and state


This seminar aims to describe the steps developed at Quantitative Neuroimaging Lab (QNL) to evaluate the atrophy rate and state from magnetic resonance imaging (MRI) of the brain, with particular focus on brain MRI of multiple sclerosis (MS) subject. It will be divided into 3 distinct sections.

In the first, I will provide an overall view of state of the art for assessing atrophy state and rate in MS: how big is the phenomenon to be detected, what are the strategies implemented to measure this and if, and at what extent, the atrophy assessment is really useful at clinical practice.

In the second, I will describe at higher level the whole pipeline created at Siena Imaging and in a bigger detail, the tools specifically developed for this (lesion_filling and siena-xl), their cons and pros.

Finally in the third section I will describe a new platform developed by Siena Imaging, (a baby start-up of which I am CEO) able to implement together all these tools with a DB and a new viewer, for helping the MD’s to obtain the atrophy assessment.