#3 OCTOBER 2015-SEPTEMBER 2016 inlab.ibfm.cnr.it

NEWSLETTER the newsletter of the laboratory for Innovation & Integration in Molecular Medicine

October 2015-September 2016

HIGHLIGHT

A MACHINE LEARNING

APPROACH FOR EARLY

DIAGNOSIS OF ALZHEIMER’S

DISEASE THROUGH MAGNETIC

RISONANCE IMAGING

BIOMARKERS

R&D - NEW METHOD

HOW INTERACTING PATHWAYS

ARE REGULATED BY miRNAs IN

BREAST CANCER SUBTYPES

EVIDENCES

ALGORITHMIC METHODS TO

INFER THE EVOLUTIONARY

TRAJECTORIES IN CANCER

PROGRESSION

NEW PROJECT

IMAPRINT - OPENINNOVATION

THE EVENT

FISICA E INFORMATICA IN MEDICINA, SINERGIE

SCIENTIFICHE E TECNOLOGICHE IN

DIAGNOSI, TERAPIA E RIABILITAZIONE MEDICA

IITM - BICOCCA March 7-8th 2016, Milan, Italy

#3 OCTOBER 2015-SEPTEMBER 2016 inlab.ibfm.cnr.it

EVIDENCES ALGORITHMIC METHODS TO INFER THE EVOLUTIONARY TRAJECTORIES IN CANCER PROGRESSION In this study was developed an open-source pipeline, PICnic, a model of somatic evolution in cancer. PiCnIc is a versatile, modular, and customizable pipeline to extract ensemble-level progression models from cross-sectional sequenced cancer genomes. The pipeline has many translational implications because it involves state-of-the-art techniques for sample stratification, driver selection, identification of fitness-equivalent e-xclusive alterations, and progression model inference. We demonstrate PiCnIc's ability to 1) identify tumor subtypes, 2) select (epi)genomic events relevant to the progression, 3) identify groups of events that are likely to be observed as mutually exclusive; and 4) suggest progression models from groups and related data and annotate them with associated statistical confidence. For further details, please contact alex.graudenzi@ibfm.cnr.it

R&D - NEW METHOD HOW INTERACTING PATHWAYS ARE REGULA-TED BY miRNAs IN BREAST CANCER SU-BTYPES

A new in silico integrative approach was recently de-veloped by INLAB researchers, able to select a small number of miRNAs to be used as potential therapeutic targets in breast cancer. By integrating the information of differentially expressed genes in BC subtypes, their different cellular functions (pathways) and their regulatory miRNAs we devel-oped a new computational strategy. This strategy has been applied to four subtypes of BC, luminal-A, luminal-B, HER2-overexpressing and basal-like, ac-cording to St’Gallen guidelines. Overall, we identified a group of 30 miRNAs that regulate a network of pathways able to accurately classify BC subtypes.

For further details, please Claudia.cava@ibfm.cnr.it

NEWSLETTER the newsletter of the laboratory for Innovation & Integration in Molecular Medicine

HIGHLIGHTS A MACHINE LEARNING APPROACH FOR EARLY DIAGNOSIS OF ALZHEIMER’S DISEASE THROUGH MAGNETIC RISONANCE IMA-GING BIOMARKERS

An innovative artificial-intelligence algorithm was recently develo-ped by INLAB resear-chers, able to perform fully-automatic early d i a g n o s i s o f Alzheimer’s Disease (AD) by only means of structural Magnetic Resonance Imaging (MRI) biomarkers. Specifically, brain

structural MRI analyzed by the algorithm are acquired using standard cli-nical protocols (T1-weighted at 1.5 Tesla). The algorithm was tested on a cohort of 509 subjects, including 137 AD, 76 MCI converter to AD, 134 MCI not-converter to AD, and 162 healthy controls, with a follow-up of (at least) 24 months). Classification accuracy was 76% for AD vs CN, 72% for MCIc vs CN, and 66% for MCIc vs MCInc. The most important voxels influencing the classification between these AD-related pre-clinical pha-ses involved hippocampus, entorhinal cortex, basal ganglia, gyrus rectus, precuneus, and cerebellum, all critical regions known to be strongly invol-ved in the pathophysiological mechanisms of AD.

For further details, please contact Christian.salvatore@ibfm.cnr.it

#3 OCTOBER 2015-SEPTEMBER 2016 inlab.ibfm.cnr.it

EVENTS NeuroMI 2016. July 6-8th 2016. Bicocca, Milan, Italy INLAB attended the convention "NeuroMi PREDICTION AND PREVENTION OF DEMENTIA: NEW HOPE" July 6-8th 2016. Bicocca, Milan, Italy

IEEE—NSS/MIC October 29th—November 5rd 2016. Strasburg, France InLab will attend the IEEE Nuclear Science Symposium and Medical Imaging Conference and present the

work:

“An Automatic Segmentation Method for the Measurement of the Functional Volume of Onco-logical Lesions on MR ADC maps”. Gallivanone F., Panzeri M., Canevari C., Interlenghi M., Losio C., Gianolli L., De Cobelli F. and Castiglioni I.

“An anthropomorphic phantom for advance image processing of realistic 18F-FDG PET-CT oncological studies”. Gallivanone F., Interlenghi M., D’Ambrosio D., Fantinato D., Alberizzi L., Trifirò G. and Castiglioni I.

NEW PROJECT

IMAPRINT The technol-ogy of 3D printing is b e c o m i n g more and more rapidly part of every-one's daily life. Based on this reality, I M A P R I N T was founded with the aim of promoting the creation of a virtual community of interest on the subject of produc-tion through the new 3D and 4D printing technologies, also including support for production through advanced software for model processing and drawings of objects (static or dy-namic) to be produced with such technologies. On the regional platform Open Innovation, the IMAPRINT community aggregates the functional skills of the creation of an innovation ecosystem to accompany the development of new products / processes / services based on 3D and 4D printing driven by new needs. To this end, the main topics of the community concern technologies based on advanced algorithms of Image Proc-essing and knowledge extraction, and new materials to ex-periment for production. The community has carried out observatory activities of the emerging needs of the market with respect to the proposed themes and set up a context of fertilization for the develop-ment of innovative solutions that meet a real market de-mand.

For further details, please contact isabella.castiglioni@ibfm.cnr.it

THE EVENT INLAB ATTENDED THE WORKSHOP “FISICA E INFORMATICA IN MEDICINA, SINERGIE SCIENTIFICHE E TECNOLOGICHE IN DIAGNOSI, TERAPIA E RIABILITAZIONE MEDICA” - IITM - BI-COCCA. March 7-8th 2016, Milan, Italy 18F-FDG PET has gained an important role as functional diagno-stic techniques for cancer pathologies. Different quantitative para-meters can be extracted from PET images. Between Among them MTV can be considered as an important parameter supporting the planning of patient-personalized image-guided radiotherapy treat-ments. Several segmentation techniques were developed for MTV definition and most of them were validated in ideal condition (e.g. in spherical objects with uniform radioactivity concentration). Ne-vertheless the majority of cancer lesions does not present these features. INLAB presented a new segmentation technique vali-dated in realistic condition exploiting the 3D printing technology to produce non-spherical objects with heterogeneous distribution of radioactivity concentration

For further details, please contact: matteo.interlenghi@ibfm.cnr.it