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ECR_2016

www.newtom.it 5G XL. EXPANDED POTENTIAL EXTRA VISION ALL-ROUND DIAGNOSTIC CAPACITY UNEQUALLED PROSPECTS The NewTom 5G XL is the only CBCT with the patient in a lying down position that guarantees a combination of minimum X-ray exposure and unparalleled 3D image definition. It also allows 2D and X-ray video imaging. NewTom has now exceeded the limits posed by CT systems. • Minimum X-ray doses. • Specialist software. • Optimal lying down position. • Better diagnostic quality. Visit us at: ECR 2016 · Vienna - AUSTRIA, 02-06 March · Hall X1 Booth #537 EUROPEAN HOSPITAL  Vol 25 Issue 1/16 8 EH @ ECR The evolution of big data is enabling radiologists to acquire ever-larger amounts of information and exploit that detail to improve understanding and diagnoses, Mark Nicholls reports Big data and its role for radiology Big data has the potential to offer a better understanding of how to aggregate clinically relevant data on a large scale and deliver better com- puter aided diagnosis algorithms and tools. Yet there are still elements of risk in this evolving field. The growing importance and potential for radiologists is outlined in a number of presentations at ECR 2016, in Vienna, with a session posing the question ‘Big data: why should radiologists care?’ Dr Gianluigi Zanetti, who directs the Data-Intensive computing depart- ment at CRS4 (see profile) will focus primarily on aspects of big data sci- entific research in his presentation ‘Big data: Big Science’. Outlining the role of big data in radiology, Zanetti said: ‘The general trend is towards data aggregation and extraction of new information from the aggregated data. The trend now is towards cloud-based PACS. Apart from the obvious economic benefits of sharing computational and storage infrastructures, the inte- grated data set of radiological imag- es and associated clinical details is expected to be a perfect starting point for the automated training of computer aided diagnosis algorithm based on deep-learning technology. ‘Similarly, it becomes possible to directly use images to query for analogous cases on very large data- set. Another important advantage is A pioneer in cone beam com- puted tomography (CBCT) imag- ing, NewTom recently introduced the only CBCT system with an open gantry and supine position- ing, which the firm reports is ‘… ideal for a host of diagnostic needs. Exceeding the limits posed by CT systems, the NewTom 5G XL com- bines high diagnostic resolution with minimum patient exposure.’ Unlike its multi-slice CT (MSCT) counterpart, CBCT technology can generate ultra-high definition volu- metric images of bone tissues, with ‘native’ isotropic voxel resolution, non-overlapping sections and fewer artefacts, the firm adds. ‘A single cone beam scan, instead of a fan beam spiral scan, shortens examina- tion times and considerably reduces X-ray exposure with respect to other CT technologies, while cutting costs significantly.’ ‘The 5G XL opens the door to radiologists and specialist physi- cians who need the best possible diagnostic capabilities in ultimate quality 2-D and 3-D. With a wide native 21x19 cm FOV, the 5G XL is perfectly suited to an exten- sive range of disciplines, such as orthopaedics, otorhinolaryngol- ogy, maxillofacial surgery and dentistry. Furthermore, thanks to its motorised patient table and open gantry, the equipment is ideal for post-sur- gery or traumatised patients, reducing movement to a minimum.’ Reports the ‘out- standing diagnos- tic quality of the 5G XL’ the firm points out that this proves useful in multiple medical fields. ‘In addition to examination of dental- maxillofacial pathologies, it is also possible to exam- ine the internal ear, fully ana- lyse airways and maxillary sinuses that the image usually contains much more information than is actually directly relevant for the specific clini- cal question asked. ‘Their availability in large-scale col- lections should make it possible to extract important clinical facts that were not evident or relevant to the originating clinical question.’ The change has been consider- able in the last five years with big data technology moving from mostly research to industrial strength solu- tions. ‘Now it’s ready to be used in clinical applications as, for instance, analysis engines integrated in cloud based PACS,’ he added. Zanetti believes there are many driving factors behind the evolution towards large scale data aggregation, the main one being economic, but there are also other factors, such as the move towards cloud based PACS and precision medicine. He also says that, with wide data collections possibly coming from multiple sources and stored in data lakes, it is important that radiologists are aware of, and care about embrac- ing big data because of the benefits and advantages. Nonetheless, he does foresee areas of risk – the first related to privacy, similar to what happens when you have access to large amounts of genomic data and more profession- als are needed. Zanetti: ‘Once the data is available, which I expect it will be, it will not take long before a deep learning algorithm will become sophisticated enough to match human experience and train- ing, most likely on routine exams, and I assume that this will have an impact on the number of radiologists needed and on the definition of the specialty. ‘Judging from what it is happening with Next Generation Sequencing (NGS) it will not take long before modalities will directly talk with sophisticated cloud based systems that will do CAD.’ But patients will see benefits, because he believes precision medi- cine can be supported only by hav- ing ‘extremely precise ways to meas- ure a given person’s biology’ (and thus very data-intensive probes like NGS) and a large enough number of collected datasets to support the patient subgroups stratification need- ed to identify optimal treatments. Big data problems are now rel- evant to ‘standard’ scientific research, he said, where the latest genera- tion of data acquisition devices have data rates that overpower traditional analysis pipeline. ‘This is becom- ing particularly relevant in biology, which is increasingly a data-intensive science, with the new light sheet microscopes having data rates in the multiple gigabytes per second range, for example.’ As to the future, Zanetti sees big data in radiology offering ‘a better understanding on how to combine, at very large scale, clinically relevant data, while staying within reason- able privacy preserving boundaries, and, of course, much better com- puter aided diagnosis algorithms and tools.’ Also during the session Professor Myriam Hunink, Professor of Clinical Epidemiology and Radiology at the Erasmus University Medical Centre, Rotterdam, will look at the issue of ‘Big data: What’s in it for the patient?’, while Dr Bruce Hillman from Charlottesville, Virginia, will discuss ‘Big data: big business’. Closing panel discussion: ‘How to make best use of big data?’ Dr Gianluigi Zanetti is the director of the Data-Intensive computing department at CRS4, an Italian non-profit research organisation dedicated to research and development on IT technologies. His primary research interests focus on problems such as scalable computing pipelines and computable data-provenance, coming from data-intensive biology and now, increasingly, clinical research. ECR 2016 Wednesday 2 March 16:00–17:30 am. Room C. NH4 Big data and radiologists CBCT technology takes a step forward New CBCT for multidisciplinary dia

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