Our Story


The Quantitative Neuroimaging Laboratory called “QNL” is founded

The QNL led by Professor Nicola De Stefano, an opinion leader in the interpretation of structural damage in neurodegenerative diseases, is founded within the University of Siena. The research group, in collaboration with the University of Oxford and McGill University, develops brain imaging indices, software and volumetric analyses aimed at studying the development of neurodegenerative diseases such as Alzheimer's or Multiple Sclerosis. In collaboration with Oxford University's Neuroimaging Laboratory, SIENA (Structural Imaging Evaluation, using Normalization, of Atrophy) was born, the most widely used software to date for quantifying the rate of brain atrophy.


Marco Battaglini joins the QNL team

Marco Battaglini joins the Quantitative Neuroimaging Laboratory with the task of improving existing and developing new analysis software to quantify structural damage in brain MRI images. Over the next two years, Battaglini enhances his experience as a visiting student at McGill University in Montreal and at the University of Oxford, where he will periodically return over the years.


QNL is selected as centralized imaging laboratory for phase 2 clinical trial analysis

The Quantitative Neuroimaging Laboratory is assigned to manage, MRI-side, a phase 2 clinical trial. Specifically, QNL is in charge of training and enrollment of centers as well as MRI image analysis, implementing innovative procedures for longitudinal analysis of MRI images and ensuring better accuracy of quantifications.


QNL develops a new method for assessing brain volumes. Giacomo Demurtas joins the QNL team

Many international companies and pharmaceutical groups rely on the Research Laboratory to analyze, in an accurate and automated manner, longitudinal and cross-sectional brain changes. Giacomo Demurtas brings his expertise in devising and building hardware architectures capable of performing parallel image analysis. QNL publishes a new method that improves brain volume quantification.


QNL develops lesion filling, a new method to improve the assessment of brain volumes in MS patients

The software, developed in collaboration with the Oxford Neuroimaging Laboratory and freely available on the FSL academic library, has changed the analysis of atrophy quantification, making volumetric analyses of MS patients more accurate.


QNL develops a method for quantifying new lesions in MS patients, to reduce the work time for neurologists and improving the accuracy of analyses

Quantitative Neuroimaging Laboratory develops procedures for automated identification of new brain lesions in multiple sclerosis using SI.N.LES (Subtraction of Images).


Siena Imaging project is one of the finalists in the BioUpper start-up competition

The Siena Imaging project is ranked among the top ten companies out of more than 200 companies in Italy at BioUpper 2015, one of the most important national Life Sciences calls. At the end of the acceleration path, the company's business plan is drafted and the procedures for the establishment of the spin-off Siena Imaging begin.


Siena Imaging is founded

On June 12, Siena Imaging S.R.L, a start-up company of Siena University, was born.


Siena Imaging develops new SIENAX 2.0 software

Siena Imaging is selected as a centralized testing laboratory by two big pharma companies to conduct 2 clinical trials, one phase 4 and one phase 2, involving 400 MS patients. Siena Imaging is equipped with a new instrument, SIENA-XL, a software created for the analysis of volumetric changes in gray matter and white matter. New software is created for automatic separation of parenchyma from nonparenchyma in brain MRI images.


Siena Imaging's SInLAB project wins RocheHealthBuilders award

Siena Imaging wins the first edition of Roche HealthBuilders with the SInLAB platform, the virtualized MRI image analysis laboratory. Marco Battaglini and Nicola De Stefano lead a project, in scientific collaboration with major MS centers in Europe, to provide normative values of longitudinal variation in brain volumes. A new tool is thus created to measure pathological deviations in atrophy from reference values. Siena Imaging provides services for a research project sponsored by a pharmaceutical company where it applies a new biomarker developed as part of its internal research activities. Siena Imaging is selected as the centralized testing laboratory for another phase 2 trial.


SinLab is created

Siena Imaging development SInLAB, the web 2.0 brain MRI image analysis platform to support the clinical activities of neurology or neuroradiology physicians. The platform manages data, creating an Image Database; analyses through specific procedures to calculate the most commonly used radiological endpoints (e.g., lesions and new lesions; brain volumes and their variation over time); and reports. SInLAB simplifies evaluations of indices of focal damage (e.g., lesions)and automatically quantifies atrophic damage. Siena Imaging is selected as the centralized analysis laboratory for two new phase 2 trials and two new phase 4 trials.


SinLab is developed and put into service for the analysis of trials

Siena imaging is selected as a centralized laboratory in six new trials including two phase 3; two phase 4; one phase 2; and one phase 1.


The Quality, IT and Research Teams are formed in Siena Imaging

Chiara Gentile joins the Siena Imaging team to coordinate QM activities for trial analysis. Siena Imaging's first IT core is then formed, consisting of three experienced database professionals and systems engineers. In September, the research team is formed consisting of six researchers, two experts in artificial intelligence, three programmers with years of experience in the field of MRI image analysis, and a PhD in Neuroscience. The management of SIena Imaging decides to develop more decisively the research part, both sponsored and through national and international calls.


The BIANCA-MS software is created

Siena Imaging is providing services for a large research project, based on artificial intelligence, sponsored by a pharmaceutical company where it is applying for the first time its proprietary artificial intelligence libraries and new biomarkers developed for MRI image analysis. Siena Imaging gets a new tool, BIANCA-MS, a Machine-Learning based software that improves automatic segmentation of white matter lesions in MS.