Quibim Precision

MRS QUIBIM Analysis_2

QUIBIM now offering advanced MR spectroscopy analysis including 2-HG for IDH1 mutation detection

Continuing its focus in the field of Oncology, QUIBIM is proud to offer an advanced MR Spectroscopy analysis tool. This tool developed in house by QUIBIM will help oncologists to improve diagnosis and treatment of brain gliomas, a disease that has an incidence of 22.6 per 100.000 population in United States.

In order to have reproducible, reliable and accurate information from tumors, we provide physicians with quantification of the metabolite by analyzing Magnetic Resonance Spectroscopy (MRS) images. MRS is a non-invasive imaging technique widely used to obtain chemical information by detecting relevant metabolites concentration from a spectrum.

Even though it is possible to detect almost any metabolite in the body, QUIBIM is currently focusing on the detection of the 2-Hydroxyglurate (2HG) because of its influence in the prediction of low-grade brain gliomas. 2HG is a metabolite, normally present at very low levels in healthy cells and tissues because of the reduction of α-ketoglutarate (α-KG) catalyzed by isocitrate dehydrogenase (IDH) protein. The IDH enzyme mutation in low-grade brain gliomas produces an accumulation of 2-HG which makes the measurement of this oncometabolite crucial to distinguish IDH-mutant gliomas from other brain mass (Stefan, et al., 2010).

MRI quality assurance

The quality assurance of the Magnetic Resonance Imaging (MRI) images is important and mandatory to ensure consequent and reliable results from the MR analysis. For that reason, a qualitative evaluation of the images is performed by QUIBIM to guarantee a strict and standard control of the images by checking the accomplishment of the MRI acquisition protocol set and the absence of artifacts.

MRS quality assurance

The first technical information QUIBIM provides with, is the graphical representation of the voxel placement in the sagittal, axial and coronal view depicted in a structural image. This quality review is important in order to assure the correct position of the voxel in the MRS acquisition avoiding necrotic tissue or non-tumor substances what can affect MRS results.

MRS quantification

Once the quality check of the MRS acquisition is done, QUIBIM produces a technical structured report, quantitative and graphical information about the MRS analysis.

QUIBIM_MRS Structured report

The report, apart from the main images and quantitative information, includes a spectrum graph and the voxel placement. Each peak of the spectrum corresponds to a different substance or metabolite with a different resonance frequency. This difference is usually measured in an independent scale besides the principal magnetic field (parts per million). The intensity of each peak is related to the concentration of the substances in the studied volume (Sánchez, et al., 2001).

To perform the analysis, the voxel in the tumor area and a reference acquisition corresponding to water are required. An automatic analysis of the spectrum is done providing this information and setting the up and down boundary value in ppm according to the metabolite searched. Then, we automatically process the spectrum filtering the water peak in the time domain, reducing the spectrum noise, adjusting the ppm scale according to Creatine and Choline position, and correcting the phase of the signal in order to also correct the baseline offset level to ensure the reliability and accuracy of metabolites’ concentration (Martí-Bonmatí & Alberich-Bayarri, 2013).

Therefore, it is possible to obtain from the studied metabolite its absolute concentration, the percentage of standard deviation (%SD) and its relative concentration using Creatine as a reference value (/Cr), sometimes adding other reference metabolites like PCr as the example of Figure 1 (/Cr+PCr).

The information provided by the standard deviation is essential to read MRS results because absolute concentration reliability depends on them: metabolites with a %SD less than 50 are practically undetectable with this data whereas a %SD<20 is a rough criterion for estimates of acceptable reliability. In addition, the third column indicates ratio relative to /Cr. This quantitative information will appear in the lower part of the report followed by a space for the signature of the scientist from QUIBIM once the analysis is done.

MRS analysis is now available in QUIBIM Precision® Platform to support oncologists and radiologists in brain gliomas treatment and diagnosis.

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References

  • Francesca Branzoli, *. A. (2018). Highly specific determination of IDH status using edited in vivo magnetic resonance spectroscopy. Neuro-Oncology, 907-916.
  • Martí-Bonmatí, L., & Alberich-Bayarri, Á. (2013). Disease Biomarkers: Modelling MR Spectroscopy and Clinical Applications in Bioinformatics of Human Proteomics. Valencia: Springer.
  • Min Zhou, *. Y. (2018). Diagnostic accuracy of 2-hydroxyglutarate magnetic resonance spectroscopy in newly diagnosed brain mass and suspected recurrent gliomas. Neuro-Oncology, 1262-1271.
  • Sánchez, J., Santos, A., SantaMarta, C., Benito, C., Benito, M., & Desco, M. (2001). Herramienta de Análisis de Espectros de RM. CASEIB. Madrid.
  • Stefan, G., Rob A., C., Mark D., M., Edward M., D., Mark A., B., Hyun Gyung, J., . . . David P., S. (2010). Cancer-associated metabolite 2-hydroxyglutarate accumulates in acute myelogenous leukemia with isocitrate dehydrogenase 1 and 2 mutations. Journal of experimental Medicine, 207(2), 339–344.
boothecr

Meet us at ECR 2019

We are delighted to share that QUIBIM will attend the 25th European Congress of Radiology 2019 (ECR) from Wednesday, February 27th to Sunday, March 3rd, 2019. This year we have changed our standard location, now you can meet us at the AI Exhibition area (EXPO X1) booth #AI-15.

ECR attendees will have the opportunity to explore our latest version of the platform QUIBIM Precision® V3.0, focused on the Symbiosis of Radiology and Artificial Intelligence to seamlessly integrate imaging biomarkers into radiology workflows. Come and try our AI solutions and imaging biomarkers analysis!

Book a DEMO

Make sure not to miss our scientific contributions:

  • Wednesday, February 27:
    • 3D post-processing in 2019 – Dr. Ángel Alberich Bayarri.   |  Imaging Informatics, Artificial Intelligence and Machine Learning (Room N) – 16:00 – 17:30
    • Deeply supervised networks for the automated liver segmentation and quantification on MECSE-MRI – Ana Jiménez Pastor | EPOS
    • Stress testing a deep learning algorithm for normal/abnormal classification of Chest X-rays on a spectrum-biased abnormal – Rafael López Gónzalez  |  EPOS
      weighted dataset.
  • Thursday, February 28:
    • Functional imaging of the liver Chairperson’s introduction – Dr. Luis Martí Bonmatí. |  Abdominal Viscera, Contrast Media (Room M 5) – 10:30 – 12:00
    • AI PITCH – Dr. Ángel Alberich Bayarri.  |  Artificial Intelligence Exhibition (AIX) Theatre ( AIX Theatre) – 11:40
    • What to think about when writing a paper – Dr. Luis Martí Bonmatí. |  Education, General Radiology, Professional Issues (Room: C&T 3) – 14:00 – 15:00
    • Deep learning (DL) in medical imaging – Dr. Ángel Alberich Bayarri.   |  Education, General Radiology, Artificial Intelligence and Machine Learning (Room: M3) – 14:00 – 15:30
    • Quantification and evaluation of pre-post exercise femoral cartilage thickness and T2 changes in ultramarathon athletes – Fabio García Castro  |  Musculoskeletal, Imaging Methods (Room: O) – 14:00 – 15:30
    • How to manage critical reviews – Dr. Luis Martí Bonmatí. |  Education, General Radiology, Professional Issues (Room C&T 3) – 15:00 – 16:00
  • Friday, March 1:
    • ECR Academies: Radiology Leaders’ Bootcamp: Dream team Chairperson’s introduction –Dr. Luis Martí Bonmatí. |  Management/Leadership (Room M 2) – 10:30 – 12:00
    • Start-up in radiology – Dr. Ángel Alberich Bayarri.   |  Management/Leadership (Room M2) –  14:00 – 15:30
  • Saturday, March 2:
    • Automated Prostate multiregional segmentation in Magnetic Resonance using deeply supervised Convolutional Neural Networks – Rafael López González  |  Artificial Intelligence and Machine Learning, Oncologic Imaging, Imaging Informatics, Genitourinary, Physics in Medical Imaging (Room G) – 16:00 – 17:30
  • Sunday, March 3:
    • Automatic visceral fat characterization on CT scans through Deep Learning and CNN for the assessment of metabolic syndrome –  Ana Jiménez Pastor | Artificial Intelligence and Machine Learning, Abdominal Viscera, GI Tract, Oncologic Imaging, Imaging Informatics (Room D) – 14:00 – 15:30
    • Liver Case-Based Diagnosis Training – Dr. Luis Martí Bonmatí. |  Education, General Radiology, General Radiography (Radiographers) (Room E1) – 13:00 – 15:30

Join us at ECR 2019!

 For more information, get in touch with us at contact@quibim.com

QUIBIM CE MARK - ISO13485 2016

QUIBIM algorithms, viewer and platform get
CE Mark certification

Valencia, Spain – 11th January 2019. QUIBIM Precision® image analysis platform has received CE Mark certification as class IIa Medical Device, including the imaging biomarker analysis algorithms, the zero footprint DICOM viewer and the platform hosting these components and medical imaging data. With this milestone, the products are now ready for commercial deployment in European hospitals and diagnostic imaging centres.

The platform, which includes not only quantitative image analysis but also structured reporting capabilities, can be seamlessly integrated into the radiology workflow adding value to the specialists. In addition to the platform, this certification includes 15 algorithms grouped in the 5 main pillars of QUIBIM: Oncology (ADC Diffusion, IVIM Diffusion, Semiquantitative Perfusion, Pharmacokinetics Modeling, T1 mapping, T2 mapping) , Neurology (White matter lesions detection, Brain atrophy modules), Musculoskeletal (3D /2D Trabecular Bone Microarchitecture),  Liver (Liver fat and Iron quantification),  and Lung (Lung Emphysema and densities); Also included in the CE Mark certification is the DataMiner, which is designed to provide advanced visual analytics of large databases of patients for population health management and scientific exploitation, and the DICOM web viewer that enables the user to visualize the images of a sequence, draw ROIs or apply filters.

QUIBIM areas

“We are so proud of getting the ISO 13485:2016 and the CE certification by BSI, one of the most prestigious notified bodies. This allows QUIBIM to commercialize QUIBIM Precision® as a Medical Device in the European market, which is a major milestone for our company.”, states Ángel Alberich Bayarri, CEO & Co-founder of QUIBIM. He adds, “Since its inception, QUIBIM has done extensive research and validation for its products together with European, American, Indian, and South American partners, ranging from top academic and research hospitals & diagnostic centres to the leading pharmaceutical companies and CRO’s, sharing the results in publications in both national and international congresses. Now with the CE Mark approval, QUIBIM is excited to commercialize its efforts in Europe and the regions of the world where the CE Mark is accepted.” 

 “QUIBIM is a company committed to improving diagnosis, which has a huge impact on patients quality of life. Therefore, quality is one of the aspects we pursue the most in our company, not only by certifying the quality of our product with the CE Mark but also at the organizational level. This is why we have established our Quality Management System based on and certified by the ISO 13485:2016, a standard related to the quality management system applicable to medical devices.” pointed Belén Fos Guarinos, Quality Assurance And Regulatory Affairs Manager at QUIBIM.

About QUIBIM

QUIBIM is a company from Valencia (Spain) which applies artificial intelligence and advanced computational models to radiological images to objectively measure changes produced by a lesion or by a pharmacological treatment, offering additional quantitative information to the qualitative approach of radiology. QUIBIM Precision® is the image repository and analysis platform provided by the company and is increasingly being used by customers across hospitals, clinical trials, research projects, biobanks and educational institutions across the world. The company is member of the European Institute of Biomedical Imaging Research (EIBIR) and of the Avicenna Alliance and receives funding from the H2020 program of the European Commission.

More info at:

contact@quibim.com
+34 961 243 225
www.quibim.com

Download: QUIBIM algorithms, viewer and platform get CE Mark certification

QUIBIM_Symbiosis of Radiology and AI

QUIBIM at RSNA 2018!

We are happy to announce that QUIBIM will be attending this year’s annual meeting of the Radiological Society of North America – RSNA 2018. From November 25 to 29, many of our Quibimers will be in Chicago demoing, sharing and showing our Radiomic solution for Hospitals and Radiology departments.

This year, QUIBIM developments are focused on the Symbiosis of Radiology and Artificial Intelligence to seamlessly integrate imaging biomarkers into radiology workflows.

QUIBIM_RSNA BOOTH 7367G

Attendees can find us at the Machine Learning Showcase – Booth #7367G  (North Building Level 3), where anyone is welcome to come over and explore the latest version of our QUIBIM Precision® Platform for medical images processing and imaging biomarkers analysis.

WANT TO DISCOVER OUR PLATFORM?

demo

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QUIBIM will be also taking part in the Machine Learning Showcase through a communication from our CEO and Founder, Ángel Alberich-Bayarri, on November 25 at 12:30 pm. The communication is entitled “QUIBIM Precision 3.0: AI as a Means, Not an End, for Imaging Biomarkers Integration in Clinical Practice” and shares QUIBIM insights about the role of AI on imaging biomarkers integration.

RSNA 2018_AAB_QUIBIM

Furthermore, as members of the NVIDIA Inception Program, QUIBIM will be demoing at the NVIDIA booth #6568 on November 26 at 10:00 am. Don’t miss it!

nvidia banner

It is a great opportunity for QUIBIM to be engaged in such a recognised event and get in touch with professionals in the fields of radiology and medical imaging.

MEET US!

Presentation of QUIBIM Precision platform at PARENCHIMA meeting in Prague, October 2018

QUIBIM continua su liderazgo en imagen médica e inteligencia artificial gestionando los datos y los algoritmos de un proyecto europeo en 25 países

QUIBIM ha sido seleccionado como el socio principal para gestionar todos los datos de imagen médica y los algoritmos de análisis de la iniciativa PARENCHIMA, un proyecto europeo de la acción COST (European Cooperation in Science and Technology) que se inició en abril de 2017 con el objetivo de impulsar el uso de biomarcadores de imagen calculados con resonancia magnética para mejorar el manejo de pacientes con enfermedad renal crónica. Multiples Investigadores científicos de 25 países europeos, líderes en imagen médica y enfermedad renal, utilizarán en esta iniciativa la plataforma QUIBIM Precision® para la realización de análisis avanzados. Uno de los desafíos del proyecto es centralizar los datos de imágenes médicas y los algoritmos de todos los socios para permitir la comparación entre protocolos de adquisición y algoritmos computacionales en términos de calidad y precisión. El resultado del proyecto consistirá en dos nuevos estándares para la adquisición y análisis de imágenes de resonancia magnética en la enfermedad renal crónica.

En la pasada reunión anual en Praga, los días 4 y 5 de octubre, se formalizó el acuerdo entre los socios del consorcio PARENCHIMA y QUIBIM. La plataforma QUIBIM Precision fue seleccionada como el mejor sistema para la gestión de las imágenes y de integración de los nuevos algoritmos de análisis.

Steven Sourbron, profesor de resonancia magnética en la Universidad de Leeds y coordinador del proyecto, manifestó: “Estoy encantado de que QUIBIM haya elegido asociarse con PARENCHIMA para ayudarnos a mejorar los resultados en beneficio de los pacientes, al hacer accesibles estas innovadoras y prometedoras técnicas para su uso en ensayos clínicos y manejo asistencial del paciente”. Frank Zöllner, profesor adjunto de física médica en la Universidad de Heidelberg y líder del grupo de trabajo encargado de la base de datos y el software de PARENCHIMA, comentói que “QUIBIM tiene una gran experiencia en algoritmos de inteligencia artificial y gestión de datos de imagen médica y estamos seguros de que son el colaborador adecuado que necesita este proyecto”. Angel Alberich-Bayarri, CEO de QUIBIM expresó que “QUIBIM está orgulloso de ser parte de este proyecto donde se generarán nuevos estándares de adquisición y análisis de imágenes en la enfermedad renal crónica, un escenario clínico no abordado previamente de forma conjunta. El impacto de este estudio será global y mejorará la vida de millones de pacientes, ya que esta enfermedad afecta al 10% de la población mundial.”

 

Acerca de PARENCHIMA

Hoy en día, los biomarcadores de resonancia magnética renal están infrautilizados no sólo en la investigación, pero también en la práctica clínica, principalmente debido a la falta de difusión y a la necesidad de desarrollo de técnicas propias. Transferir soluciones a otros centros donde funcionen y estén validadas es, por lo tanto, un reto todavía no resuelto, lo que conlleva una replicación significativa de esfuerzos, una falta de estandarización en los métodos y dificultades para comparar los resultados entre los centros. Esto también limita la comercialización y dificulta la creación de ensayos multicéntricos y la traslación a la práctica clínica.

El objetivo general de PARENCHIMA es eliminar las principales barreras para un estudio clínico más extenso y la consiguiente explotación comercial de los biomarcadores de resonancia magnética renal.

PARENCHIMA coordinará la investigación de los principales grupos europeos en esta área para:

  • mejorar la reproducibilidad y estandarización de los biomarcadores de resonancia magnética renal;
  • aumentar su disponibilidad desarrollando un conjunto de herramientas de acceso abierto con herramientas software y datos;
  • demostrar la validez biológica y la utilidad clínica en un estudio clínico prospectivo multicéntrico.

Para aumentar el impacto de este proyecto, hemos decidido unir nuestros esfuerzos. Más información en: www.renalmri.org

 

Sobre QUIBIM

QUIBIM es una empresa de Valencia (España) que aplica inteligencia artificial y modelos computacionales avanzados a las imágenes radiológicas para medir de manera objetiva los cambios producidos por una lesión o por los tratamientos farmacológico, y ofrece información cuantitativa adicional al enfoque cualitativo de la radiología. La tecnología y los servicios de QUIBIM se aplican en la práctica clínica, los ensayos clínicos, la formación en radiología y los proyectos de investigación. Más información en: www.quibim.com

Presentation of QUIBIM Precision platform at PARENCHIMA meeting in Prague, October 2018

QUIBIM to manage imaging data and AI for European project PARENCHIMA across 25 countries

QUIBIM has been selected as the main partner to manage all imaging data and analysis algorithms of the PARENCHIMA initiative, a COST action project initiated in April 2017 with the objective of boosting the use of renal MRI biomarkers to improve the management of chronic kidney disease patients. The leading scientific researchers in medical imaging of the kidney from 25 European countries will be using QUIBIM Precision® platform for highly advanced image analysis. One of the challenges of the project is to centralize the medical imaging data and algorithms from all partners to allow for acquisition protocols and algorithms comparison in terms of quality and precision. The outcome of the project will consist of two new standards for image acquisition and analysis in MR of the kidney.

In the past annual meeting of the consortium in Prague, which took place on 4-5 October, an agreement was established between QUIBIM and PARENCHIMA consortium partners for the selection of QUIBIM Precision platform as the best system for images management and integration of new analysis algorithms.

Steven Sourbron, Lecturer in Magnetic Resonance Imaging at the University of Leeds and project coordinator, expressed “I am delighted that QUIBIM has chosen to partner with PARENCHIMA, helping us to improve outcomes for patients by opening up these promising new methods for use in clinical trials and patient management”. Frank Zöllner, adjunct Professor for medical physics at the University of Heidelberg and leader of working group for PARENCHIMA database and software said “QUIBIM has strong expertise in AI algorithms and managing data and we are confident that they are the right collaborator for this project”. Angel Alberich-Bayarri, CEO of QUIBIM said that ”QUIBIM is excited to be part of this project, which will lead to new standards of image acquisition and analysis in Chronic Kidney Disease (CKD), an unaddressed clinical scenario. I am confident that the impact of this study will be global and improve lives of millions of patients, since it is a disease affecting 10% of population worldwide”

 

About PARENCHIMA

Renal MRI biomarkers are today underused in research and in clinical practice due to the need for dedicated in-house expertise and development. Transferring solutions to other centres is therefore a challenge, and this leads to a significant duplication of efforts, a lack of standardisation in the methods, and difficulties in comparing results between centres. This also limits commercial exploitation, and hinders the set-up of multi-centre trials or translation into clinical practice.

The overall aim of PARENCHIMA is to eliminate the main barriers to the broader study, commercial exploitation and clinical use of renal MRI biomarkers.

PARENCHIMA will coordinate the research of leading European groups in this area to:

  • improve the reproducibility and standardisation of renal MRI biomarkers;
  • increase their availability by developing an open-access toolbox with software and data;
  • demonstrate biological validity and clinical utility in a prospective multicentre clinical study.

In order to increase the impact of this project we are reaching out to join the efforts. More info at: www.renalmri.org

 

About QUIBIM

QUIBIM is a company from Valencia (Spain) which applies artificial intelligence and advanced computational models to radiological images to objectively measure changes produced by a lesion or by a pharmacological treatment, offering additional quantitative information to the qualitative approach of radiology. QUIBIM technology and services are applied in clinical practice, clinical trials, radiology education and research projects. More info at: www.quibim.com

QUIBIM_chest_xray_classifier_logo3

New Chest X-Ray Classification Tool

Despite the technological evolution of imaging modalities like CT, US and MRI, conventional X-ray remains the most performed examination in radiology departments, and remains a fundamental tool for anatomical analysis in the detection and diagnosis of respiratory diseases and bone tissue alterations. However, radiology departments have limitations in reporting the X-Rays due to the limited resources available (link).

QUIBIM has developed a Chest X-Ray Classification Tool that offers a solution to this problem which can help radiology departments become even more efficient. This classifier developed in collaboration with Hospital Universitario y Politécnico La Fe, estimates the probability of chest X-Rays of having a pathology using Artificial Intelligence.

How does it work?

This tool makes use of fourteen Convolutional Neural Networks trained with a database of more than 100,000 images (NIH ChestXray14 dataset) to estimate the probability of presence of the following pathologies in chest X-Rays: atelectasis, cardiomegaly, effusion, infiltration, mass, nodule, pneumonia, pneumothorax, consolidation, edema, emphysema, fibrosis, pleural thickening and hernia. Afterwards, the probabilities are used by a Fully Connected Neural Network to get the final probability of the X-Ray of being abnormal.

XRAY chest

Because of this AI methodology the classifier understands the visual patterns that are most indicative of the different pathologies using the knowledge extracted from the large dataset of radiographs used to train the networks. QUIBIM’s Chest X-Ray Classification Tool is able to learn further using new images, which means that this system is continually improving and evolving with time.

 What information does it provide?

Once all the quantifications are performed this tool provides an intuitive Structured Report with the patient’s information, the abnormal probability of the radiographs analyzed and the representation of the findings. In addition, if the image is classified as abnormal, the report shows the three pathologies that are more likely to be found and a heatmap that highlights the most abnormal regions. This report is designed to be very user friendly, to assist the user in understanding the tool’s findings at a glance in order to make its usage highly efficient.

Why is this new tool so useful?

Using this technology it is possible to prioritize unreported, potentially pathological radiographs which allows radiologists to focus their efforts on studies that are more likely to have pathologies and thereby become more efficient. This tool essentially ensures that pathological findings, which could have been unreported due to the heavy workload of radiology departments, are correctly reported.

QUIBIM’s goal is to provide the radiology departments with an optimal solution for automatic reading of X-Rays without interfering in the  workflow of the department.

QUIBIM’S Chest X-Ray Analysis Tool is already available at QUIBIM Precision® Depending on the needs of the department, this tool is accessible through the cloud with just a few clicks  or  it can be fully integrated in the radiology department’s workflow as a local solution for  seamless interpretation of  chest X-Rays.

boton try quibim

QUIBIM se posiciona en el mercado americano analizando hábitats tumorales y enfermedades difusas hepáticas

Ha cerrado acuerdos con la compañía EnvoyAI y ha abierto oficina en Silicon Valley

QUIBIM sigue creciendo en el desarrollo de algoritmos de análisis de imágenes médicas basados en modelos biológicos y en inteligencia artificial. La compañía, que cerró el año 2017 con un crecimiento del 500% en sus métricas de negocio (número de análisis y facturación), ha avanzado con la expansión al mercado americano de sus algoritmos para cáncer y enfermedades difusas hepáticas. Entre los hitos más relevantes, además de la reciente apertura de oficina en Palo Alto (Silicon Valley, California), QUIBIM ha establecido una alianza con la empresa EnvoyAI, dedicada a la integración y distribución de algoritmos de inteligencia artificial para imágenes médicas. EnvoyAI fue adquirida el año 2016 por TeraRecon, empresa con un software de visualización radiológica que se encuentra actualmente instalado en el 85% de los hospitales de Estados Unidos.

Estos algoritmos de QUIBIM para el mercado americano, ahora mismo en proceso de certificación por la Food and Drug Administration (FDA), caracterizan tanto las diferentes subregiones o habitats internos de un tumor como analizan por biopsia virtual hepática las enfermedades difusas tipo esteatosis, sobrecarga de hierro, inflamación y fibrosis.

En el ámbito de la oncología, QUIBIM proporciona una metodología que extrae datos de textura, celularidad y proliferación vascular en los tumores, siendo aplicable en lesiones cerebrales, de mama, próstata, hígado y recto, entre los principales tumores sólidos. Esta metodología puede aplicarse a las imágenes de Resonancia Magnética y Tomografía Computarizada, proporcionando una información pronóstica sobre la evolución de los pacientes y su respuesta a los diferentes tratamientos.

En el ámbito de las enfermedades difusas hepáticas, QUIBIM proporciona un algoritmo para realizar una biopsia virtual hepática, sin dañar al paciente, a partir de las imágenes de Resonancia Magnética y extrayendo la proporción de grasa, concentración de hierro y proporciones de inflamación y fibrosis hepática. Este análisis es de especial relevancia para el estudio y seguimiento de la esteatohepatitis y la hemocromatosis, y en la evaluación de la historia natural y su modificación por el tratamiento en las hepatopatías crónicas y la cirrosis. Actualmente esta información se obtiene a partir de biopsias convencionales, lo que implica un riesgo para el paciente y un sesgo inherente al procedimiento dado que sólo se obtiene información del lugar de la punción, mientras que el algoritmo de QUIBIM permite obtener información de todo el hígado de manera segura.

En palabras de su CEO, el Dr. Ángel Alberich-Bayarri, resumiendo estos hitos “estamos en una fase muy intensa de la compañía y con un crecimiento significativo, y gracias al esfuerzo del equipo hemos podido acelerar varios hitos que teníamos previstos en fases más tardías, como por ejemplo la alianza con EnvoyAI, la solicitud a FDA y la apertura de oficina en EEUU. Los algoritmos que hemos seleccionado para este mercado aportan un valor diferencial que ya hemos podido verificar, recibiendo solicitudes desde algunos hospitales antes de iniciar acciones comerciales.”

QUIBIM es una empresa biotecnológica nacida en Valencia y está especializada en la extracción de información cuantitativa de las imágenes médicas radiológicas y de medicina nuclear, mediante técnicas originales y avanzadas de procesamiento computacional. Estos parámetros extraídos reciben el nombre de Biomarcadores de Imagen y aportan rasgos extraídos de las imágenes médicas, relacionadas con procesos biológicos normales, enfermedades o respuestas terapéuticas.

Además, el equipo ha desarrollado la plataforma QUIBIM Precision® de análisis de imágenes médicas en la nube, que puede instalarse en versiones privadas para hospitales y para compañías farmacéuticas que desarrollen ensayos clínicos. A partir de imágenes de rayos X, Ecografía, TAC, Resonancia Magnética o PET, QUIBIM es capaz de aplicar algoritmos avanzados de análisis con metodologías basadas en procesamiento por GPU (unidades de procesamiento gráfico), Machine Learning o Big Data. El software de QUIBIM permite aportar una mayor información en los diagnósticos y poder evaluar de forma temprana la respuesta a los tratamientos farmacológicos. La compañía fue seleccionada en 2017 para el programa SME Instrument Fase II de la Comisión Europea.

QUIBIM Imaging Biomarkers made transparent

QUIBIM, AI imaging disruption to showcase the value of Precision

We are in the era of Precision Medicine, and so is Radiology. Nowadays, main imaging modalities like X-ray, computed tomography (CT), magnetic resonance (MR), positron emission tomography (PET) and hybrid machines, among others, have become measurement instruments. Images are not only pictures anymore, but thanks to the application of computational analysis and artificial intelligence, they are data, as you can learn in this excellent manuscript in Radiology.

Nowadays, when radiologists perform measurements of different organs, tissues and lesion properties using a workstation, they are used to get a number (i.e. lesion volume or perfusion). If they take the same images and they get to analyze them in a workstation from another vendor (not straightforward), it is pretty sure that they will obtain different results. This issue has introduced a sense of lack of standardization and homogenization in the quantitative medical imaging field.

I like to say that value is to trust in the product, and we have decided to be the first company in the world to open the validation process and tests results of our imaging biomarkers. Every time we buy a measurement device for daily life purposes (i.e. thermometer) we know the degree of uncertainty, why wouldn’t we do the same in AI algorithms and quantitative imaging?

We are proud to make this announcement at ECR 2018: Now it is possible to see the precision, accuracy and clinical evaluation results of our imaging biomarkers. We provide the precision (through Coefficient of Variation, CoV) and accuracy (through relative error, e) values through the publication of QUIBIM Technical Datasheets that you can find in the resources section of our webpage.

With this strategy QUIBIM is going a step further by being the first multi-vendor, web-based and real precision Medicine company of the medical imaging & AI market.

Concerned by the accuracy of your measurements? Let’s work together.

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El proyecto QUIBIM recibe la ayuda del IVACE-PREPARACIÓN DE PROPUESTAS PARA CONVOCATORIAS H2020

QUIBIM es un proyecto empresarial de alto impacto social y sanitario, que extrae información cuantitativa de las imágenes médicas radiológicas, mediante técnicas innovadoras y avanzadas de procesado computacional, con el objetivo de mejorar los procesos de diagnóstico de enfermedades con alta incidencia y evaluar adecuadamente los cambios que producen los tratamientos farmacológicos en el organismo.

Durante 2016 el proyecto de internacionalización QUIBIM ha recibido la ayuda IVACE – PREPARACIÓN DE PROPUESTA PARA CONVOCATORIAS DEL PROGRAMA MARCO  H2020 DE INVESTIGACIÓN E INNOVACIÓN 2014-2020  (IMAPEA/2016/38) con el apoyo del Fondo Europeo de Desarrollo Regional (FEDER) con el objetivo de presentar nuestros servicios de diagnóstico y análisis avanzado de imagen médica y dar a conocer nuestra plataforma de análisis QUIBIM Precision® para el análisis de Biomarcadores de Imagen.

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