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This site is dedicated to scientific community working on ALS. Our aim is to optimize researchers time and efforts by providing updated, well organized information on novel findings, available resources and research support.
AriSLA - The Foundation for research on ALS - has been set up to make ALS research investments more effective and efficient, to speed up the clinical research impact e and to provide patients with better care, improved conditions and life expectancy. Its aim is to boost Italian excellencies in basic, clinical and technological research. The Foundation founders are Fondazione Cariplo, Fondazione Telethon, Fondazione Vialli and Mauro and AISLA.



New publication by the AriSLA funded project macLearnALS, Call 2013: advances in ALS diagnosis

Another important result was achieved by a pilot project funded by AriSLA Foundation (macLearnALS) and conducted by Dr. Federica Agosta, neurologist and researcher at IRCCS Ospedale San Raffaele Quantitative Neuroimaging Unit, directed by Prof. Massimo Filippi.



The article, published in "Neuroimage: Clinical", suggests that the combined use of multiple advanced magnetic resonance imaging (MRI) techniques can help the neurologist in the motoneuron disease diagnosis, particularly by distinguishing ALS from the various clinical presentations that can "mimic" ALS (so-called "ALS-mimic disorders").

The study is particularly important because ALS diagnosis is nowadays mainly driven by the neurologist confirmation of clinical or neurophysiological signs of damage of the first and second motor neurons .

Especially in early stages of the pathology, current El Escorial's diagnostic criteria have suboptimal sensitivity, as they allow to formulate ALS diagnosis approximately 12 months after the onset of symptoms (average).

These criteria do not include the use of biomarkers for the evaluation of the damage of the first motor neuron, that transmits the electrical impulses from the motor cortex to the spinal cord.

The analyses carried out by the researchers have shown that measurements of motor cortex thinning and corticospinal bundles damage (respectively identified by T1 MRI weighing and MRI diffusion tensor) can be used to develop an automatic classification algorithm with an accuracy of more than 90% in correctly identifying  the subjects with motoneuron disease,  differentiating them from both healthy controls and other ALS-mimic disorders .

"This discovery paves the way for new tools that will help in the early identification of motor neuron disease, enabling timely enrolment of patients in pharmacological studies aimed at changing the course of the disease, "explains Prof Massimo Filippi and Dr Federica Agosta.

For the full Article please follow this link



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