Entradas Etiquetadas :

medical imaging

SMEInstrument

QUIBIM granted with the H2020 – SME Instrument Phase II

QUIBIM team is proud to announce that the beneficiaries of the European Commission SME Instrument Phase 2 have been recently published, and our project has been awarded in the Open Disruptive Innovation (ODI) topic.

QUIBIM’s project “QUIBIM Precision” has been granted with 1.25M€ for the scaling and development of the company business plan through our cloud platform QUIBIM Precision®. This funding will boost and accelerate the strategic plan of the company, bringing new disruptive solutions to our platform, including dedicated High Performance Computing resources for our Machine Learning processes, incorporating new visual analytics tools and helping validate new imaging biomarkers that have been recently developed.

QUIBIM Precision® is an innovative imaging biomarker analysis platform in the cloud allowing for:

  1. Automated analysis of imaging biomarkers (results are ready just within minutes) with the best accuracy and reproducibility.
  2. Medically certified: QUIBIM is medically valid to scientifically support decision making.
  3. Open to any physicians: Optimized User Interface (UI), user experience (UX) and imaging analysis functionalities.
  4. Cost-effective: QUIBIM helps reduce costs of medical testing and misdiagnosis.

Our technology based on machine learning and image processing algorithms scouts the image and compares it to similar images in our database with known ground-truth diagnosis, based on patterns not obvious to a human eye.

About QUIBIM
QUIBIM is a biotechnology company dedicated to advanced medical image analysis. It was one of the start-ups selected in the 3rd edition of the acceleration program “LANZADERA” and it’s a spin-off company of the Medical Research Institute Hospital La Fe. Recently the company closed an investment round to boost its growth, including Tech Transfer UPV, AYCE Capital, and BioInfoGate, as well as some company promoters . QUIBIM’s business model is based on the extraction of quantitative information from radiological and nuclear medicine imaging using original and advanced computational processing techniques.

In 2016, QUIBIM was also selected as one of the disruptive companies by the EU and granted with the first round of Horizon 2020 SME Instrument Phase I Program 2016 under the call: “SMEInst-01- 2016-2017: Open Disruptive Innovation Scheme”

SME instrument – Horizon 2020 call
The SME Instrument is divided into 3 phases covering different stages of the innovation cycle. Phase 1 aims to cover the assessment of technical feasibility and market potential of new ideas. The project will be supported by an investment of 50,000€ and the typical duration should be no longer than 6 months.

Phase 2 aims to cover R&D activities with a particular focus on demonstration activities (testing, prototype, scale-up studies, design, piloting innovative processes, products and services, validation, performance verification etc.) and market replication encouraging the involvement of end users or potential clients. Project funding should amount to no more than 2,500,000€ and the typical duration of this phase should range from 12 to 24 months.

3D_Full_Low_Both

Assessing the bone quality of your patients is just a few clicks away

Quibim is proud to introduce its new advanced methodolgy to assess bone quality and fracture risk: QTS (Quality of Trabecular Structure). The need for a reliable approach for the characterization of trabecular microarchitecture is evident, as conditions and diseases related to trabecular bone quality and structure are becoming a focal point of precision medicine. Millions of dollars are spent in bone fracture care and prevention, which in many cases represent a grave danger to the patient health. In this scenario, can we rely upon available methods to predict bone fractures? Regrettably, the answer is no. Or so it was. Before we introduce QTS in detail, let’s first review some of the available methods to evaluate fracture risk.

DEXA Bone Mineral Density (BMD) limitations as a fracture predictor are widely known. However, despite its glaring shortcomings it’s still considered as the gold standard in clinical practice. The WHO developed the FRAX tool hoping to improve the low ratio of success of BMD as a predictor, and, while it improves sensibility and specificity assessing fracture risk, it’s still not satisfactory enough for it to be used as a stand-alone predictor in clinical practice or clinical trials.

In an attempt to fill this void in the search of a reliable predictor, new imaging biomarkers that guarantee to provide the needed sensibility and specificity have been developed. Trabecular Bone Score (TBS®) by Medimaps is a fracture risk predictor using DEXA as a source. TBS® performs a gray level analysis (textures) on the DEXA images to determine bone integrity. But, is DEXA adequate for this task? Unlike regular XR, in which it’s possible to assess the trabecular structure, DEXA’s low radiation is not enough for trabeculae differentiation. In addition, DEXA (like XR) represents a 3D structure as a projection onto a plane, losing spatial information.

Other medical imaging modalities are much more adequate for bone analysis and the subsequent fracture risk evaluation. Thanks to advanced computing models, Quibim has developed a new imaging biomarker that uses either magnetic resonance (MR), computerized tomography (CT) or X-ray imaging for a detailed characterization of the trabecular structure. QTS (Quality of Trabecular Structure) by Quibim introduces several advantages over other analysis methods:

  • Real extraction of the trabecular bone microarchitecture: bone volume, trabecular thickness, trabecular separation…
  • Information of the complexity of the structure: fractal analysis
  • 3D spatial information, not only in plane (only CT and MR)
  • 3D reconstruction of the trabecular bone (only CT and MR)
  • Optional mechanical analysis (only CT and MR, with QTS+)
  • QTS Score comprises all this information in a single score for a rapid and accurate characterization of the bone structure.

This groundbreaking analysis method is already available at our cloud web platform: Quibim Precision. Below we detail how to analyze your study in a few simple steps.

Quibim Precision allows the upload of studies in Dicom format. The upload process is easy, intuitive and 100% secure, guaranteeing the patient confidentiality thanks to Quibim’s anonymization and encryption system. The whole process is performed without the need of installing any additional software. To start, click on the green “Upload Study” button to the right of the website.

00

The platform will then ask for Dicom studies selection. With Google Chrome, we can drag and drop the study folder directly to the dotted box. With any other browser, we need to select the Dicom files to be uploaded.

00b

Once the Dicom folders have been selected, Quibim Precision allows the pre-visualization of the study to choose which sequences we wish to upload. In this case, we need a CT, an X-ray or a 3D T1 MR.

After the selection, the files will be anonymized and encrypted. Quibim Precision will ask for an encryption password before the upload process starts. The user needs to preserve this password, as it’s needed for patient traceability.

00c

After the upload process is completed, we click on the “Analyze Study” button of the study we want to evaluate.

01

This will take us to the detailed view of the study, where we can perform all actions related to it. First of all, we will choose among all the available sequences the one to be analyzed and its Quibim standard name. In this case, the name of the sequence is “Linear Attenuation [1/cm] (3035)”, which corresponds to the standard name “High Resolution CT”.

02

Next, we open the embedded Dicom viewer by clicking on “View”. Thanks to this viewer we can draw the ROI that will be used for the analysis. The viewer allows drawing 3D ROIs, first drawing a 2D rectangular ROI, and then selecting the slices on which it should be replicated. Clicking on “Apply” and “Save and go back” will store the ROI and it will be used for the analysis.

04b

Finally, we should choose which analysis method we’ll use among all the available apps in Quibim Precision. In this case we’ll click on the “Start Analysis” button of the “3D Bone microarchitecture – QTS Score” app. The analysis process will then start, and the user doesn’t need to perform any other action than checking the results.

03

The results of the analysis are available on the view of the study. Once the analysis is completed we can check them by clicking on the “View Study” button on the “Processed Biomarkers” section.

05

We can examine the 3D reconstruction images and the numeric results of the extracted imaging biomarkers on the results view. Furthermore, we can download them and the structured report in pdf format, which includes all the generated data in a compact, easy to read way.

06

07b

08

All the benefits of QTS are just a few clicks away. Create an account on Quibim Precision and start offering a real added value with your imaging studies.

Try us for free!

Metrology for imaging biomarkers

Will metrology labs take charge of Imaging Biomarkers certification?

As the reader might know, Imaging Biomarkers are parameters obtained objectively from medical images, which represent and quantify a tissue property (structural, functional or biological) extracted after applying computational models to images of specific medical imaging modalities like computed tomography (CT), magnetic resonance imaging (MR), conventional radiography (CR) and so on.

One of the main challenges for Imaging Biomarkers integration in clinics and in clinical trials is the need for standardized image acquisition protocols  and  pipelines for the analysis of imaging biomarkers, including the processing, analysis and reporting of the results.

As specified in this publication from QIBA (Quantitative Imaging Biomarkers Alliance) team: “Most Biomarkers require a computation algorithm, which may be simple or highly complex. While there is a rich history of the development of biomarker techniques, there has been comparatively little attention paid to the evaluation and comparison of the algorithms used to produce the biomarker results. Estimation errors in algorithm output can arise from several sources during both image formation and the algorithmic estimation of the biomarker. These errors combine (additively or non-additively) with the inherent underlying biological variation of the biomarker. Studies are thus needed to evaluate the imaging biomarker assay with respect to bias, and precision. A recurring issue is the lack of reported estimation errors associated with the output of the biomarker. Another challenge is the inappropriate choice of biomarker metrics and/or parametric statistics. For example, tumor volume doubling time is sometimes used in studies as a biomarker. However, it may not be appropriate to use the mean as the parametric statistic for an inverted, non-normal, measurement space. Since a zero growth rate corresponds to a doubling time of infinity, it is easy to see that parametric statistics based on tumor volume doubling time (e.g. mean doubling time) may be skewed and/or not properly representative of the population. In addition, there may be discordance between what might be a superior metric statistically and what is clinically acceptable or considered clinically relevant. For example, a more precise measuring method will typically better predict the medical condition, but only until the measurement precision exceeds normal biological variation; further improvement in precision will offer no significant improvement in efficacy. Finally, when potentially improved algorithms are developed, data from previous studies are often not in a form that allows new algorithms to be tested against the original data.

A metrology-by-design strategy for imaging biomarkers design and implementation has still not been conceived, however, there is a clear need to fill this gap, since medical images are suffering a paradigm shift from being qualitatively interpreted by radiologists to become a powerful measurement instrument, that can provide a non-negligible and highly relevant information in many pathological processes.

Following the experience of our group and QUIBIM, with a model of success for the integration of quantitative image analysis in clinics, we published in 2012 our methodology for the integration of imaging biomarkers in clinics that was later supported by the European Society of Radiology in 2013, through the publication “ESR position on the stepwise development of imaging biomarkers” in Insights into Imaging. This paper was the former work of the ESR supporting the creation of the European Imaging Biomarkers Alliance (EIBALL) in 2015.

Now, several actions should be undertaken to allow for the implementation of biomarkers in clinical use and the evaluation of therapy response:

  • To determine the most significant sources of uncertainty for imaging biomarkers.
  • To establish a standard methodology for definition of the method and the protocol for image acquisition (Signal-to-noise ratio, contrast-to-noise ratio) for traceable measurements.
  • To harmonise calibration routes and methods for imaging biomarkers in European metrology institutes. This objective includes knowledge exchange and transfer and comparison measurements.
  • To provide metrology input and pre-normative research to the evolution of International (ISO, EN) standards concerning imaging biomarkers.
  • To engage with image device manufacturers to facilitate the take up of the technology and measurement systems developed, to support the development of new, innovative biomarkers, thereby enhancing the competitiveness of EU industry.

While researchers are dealing with these issues, there are specific entities that have been always in charge of supervision, validation and certification of measures: the National Metrology Institutes. The umbrella covering all National Metrology Institutes in Europe is EURAMET. Therefore, we should start to think in incorporating this metrology-by-design strategy in the process of creation, implementation and validation of imaging biomarkers. In QUIBIM we have already started this strategy, following QIBA recommendations and implementing new algorithms in a modular basis, identifying the sources of uncertainty in all the measurements that we perform with imaging biomarkers.

by Angel Alberich-Bayarri (@aalberich).

CEO & Founder of QUIBIM