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H2020-Web

QUIBIM made huge strides in
AI-powered diagnosis thanks to EU H2020

Taking part in the EU’s H2020 initiative translated into huge strides in disease detection and diagnosis by QUIBIM, by enabling the development of tools powered by artificial intelligence (AI) that allow to extract patterns from medical images and significantly improve human performance.

The program, which came to a term on June 30th, culminated in QUIBIM PrecisionⓇ significantly expanding its network of customers and collaborators and an improved international brand awareness.  More recently the Chest X-Ray Classification tool, another solution in the QUIBIM PrecisionⓇ suite, also received CE clearance.

We are very happy we’ve completed the program in time and line with all our objectives, allowing us to add one more stepping stone to the development of AI-boosted healthcare,” QUIBIM CEO Angel Alberich Bayarri said.

QUIBIM, a high-tech SME based in Valencia, Spain, received a €1.25M grant from the European Union’s Horizon 2020 research and innovation program in 2017, to help advance its machine learning and image processing algorithms to extract imaging biomarkers from images generated on CT, MRI, X-ray, US, DXA and PET scans.

With the EU’s support, the Spanish company could finalize the development, validation and automation of new imaging biomarkers in the areas of brain, lung and oncology, as well as achieve the integration of the new computing performance and data visualization frameworks for the QUIBIM platform.

Thanks to the automated analysis of imaging biomarkers, results are ready just within minutes with the best accuracy and reproducibility, through a medically certified, cost-effective and user-oriented solution, which is available to any physician using image-based diagnosis.

QUIBIM allows physicians to make more accurate diagnosis by providing additional information extracted from the analysis of acquired imaging studies. Our technology uses algorithms that scout the image and extracts features as imaging biomarkers that can be compared to normative information in our database, based on patterns that are not easily visible to the human eye. The algorithms combine both AI data-driven techniques and model-driven approaches. As such, our products help to reduce costs of medical testing and misdiagnosis, especially from specialists,” Alberich said.

QUIBIM actively started in 2015 as a spinoff company of La Fe Hospital in Valencia, to help specialists including radiologists and pathologists make the most of AI in their everyday practice, by providing a one-stop-shop solution using imaging biomarkers and powerful algorithms.

More than 60 hospitals worldwide are currently working with QUIBIM tools, most of which have received CE marks and/or are FDA pending. The company has notably developed the new teaching platform of the European School of Radiology and has supplied its QUIBIM Precision® image analysis platform to the AI Precision Health Institute at the University of Hawai‘i Cancer Center in Honolulu.

QUIBIM has received €3.5m funding ever since its creation and has offices in Spain and the U.S. The company forecasts to generate revenues above €36 million and 150 direct jobs by 2023.

European Commision Flag QUIBIM Project

 

2019-06-26

QUIBIM to develop platform in leading research project to fight pediatric cancer

QUIBIM is helping to advance knowledge of the most lethal pediatric tumors through EU-funded program PRIMAGE, which exploits precision information from medical imaging to establish tumor prognosis, and expected treatment response using radiomics, imaging biomarkers and artificial intelligence (AI).

Pediatric cancer is a rare disease, but treatment remains challenging. Improving knowledge is key to adequately plan therapy and boost survival, and the latest AI techniques have the potential to harness unprecedented information from medical images.

A few months ago, the European Commission funded the PRIMAGE (1) project with over €10M, to help identify the most efficient treatment and a tumor’s main characteristics without the need for biopsy, by using computational processing of medical images on the cloud.

The PRIMAGE consortium will create a bank of images obtained through AI, using an open cloud-based platform to support decision-making in the clinical management of Neuroblastoma (NB), the most frequent solid cancer of early childhood, and Diffuse Intrinsic Pontine Glioma (DIPG), the leading cause of brain tumor-related death in children. The PRIMAGE platform will implement the latest advancement of in-silico imaging biomarkers and modeling of tumor growth towards a personalized diagnosis, prognosis and therapies follow-up.
The project involves 16 European partners, including internationally recognized institutions, and four leading industrial partners, including Spanish biotechnology company QUIBIM, all working under the aegis of the Imaging Biomedical Research Group (GIBI230) based in La Fe Hospital, Valencia.

181220_IISLAFE PRIMAGE kick offprimage-logo-transparent
Sharing high-end knowledge of AI tools

QUIBIM is responsible for the central task of developing the PRIMAGE platform’s architecture, adaptation and design. The company recently obtained CE mark for its Chest X-Ray Classification AI-Tool and its imaging biomarker analysis algorithms, zero footprint DICOM viewer and platform within the QUIBIM Precision platform.

QUIBIM researchers are now bringing their expertise in medical image post processing and management to PRIMAGE, by passing on their knowledge of clinical trials design and validation, imaging biomarkers extraction and validation, radiomics, data clustering and visualization, and development of AI-fueled tools, such as organ segmentation models.
“Much work remains to be done to improve our knowledge of pediatric brain cancer. NB and DIPG have a complex therapeutic approach and we need proper tools to improve survival. Extracting quantitative information from medical images with AI can help visualize tumor growth with extreme precision, and help to tailor therapy to each individual patient,” Ángel Alberich-Bayarri  said.

QUIBIM’s input will also help to define the methodologies and standards to be used in the different development areas, to facilitate interoperability between the platform ́s modules and for future interoperability with their cloud-based platforms for functionality add-ons.

Transferrable knowledge to other cancers

Cancer has a very low incidence among children and experts estimate that 500,000 EU citizens will be pediatric cancer survivors by 2020. Nonetheless, cancer remains the first cause of non-traumatic death among children.

Neuroblastoma is the most common extracraneal tumor in children, representing 8-10% of all pediatric cancers. In Europe, 35,000 new cases are diagnosed each year, 1,000 in Spain alone.

Diffuse Intrinsic Pontine Glioma is a very rare disease in childhood and is associated with low survival (10%), despite many existing treatments and on-going research. Treatment is not curative, only palliative, i.e. radiotherapy to improve the patient’s life. 16 new cases are diagnosed each year in Spain, accounting for 2.5% of oncological pediatric patients and 13% of pediatric tumors of the central nervous system.

Because of the peculiarities of computational approximation in these two types of tumors that are proper to childhood, investigation done in that area will also be applicable to other types of tumors. Because it will gather considerable scientific effort, PRIMAGE should also help advance research on other types of cancer.
(1): PRedictive In-silico Multiscale Analytics to support cancer personalized diaGnosis and prognosis, Empowered by imaging biomarkers (PRIMAGE)