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Katherine Wilisch Ramírez

QUIBIM_chest_xray_classifier_logo3

QUIBIM’s AI-FUELED CHEST X-RAY CLASSIFIER GETS CE MARK

  • Chest X-ray classifier is added as a new CE cleared tool within QUIBIM Precision platform, which already received CE mark class IIa certification earlier in 2019.

  • QUIBIM’s Chest X-Ray Classification AI-Tool dynamically learns using new images, meaning the system is continuously evolving and improving over time.

Valencia, Spain – 27th May 2019. Spanish healthcare AI company QUIBIM today announced that its AI-powered Chest X-Ray Classification tool has received CE certification. The company already obtained the class IIa CE mark earlier this year for the imaging biomarker analysis algorithms, the zero footprint DICOM viewer and the platform within the QUIBIM Precision platform, becoming the first Spanish firm to ever receive the clearance.

QUIBIM applies machine learning and image processing techniques to extract imaging biomarkers from medical images in order to assist radiologists and physicians in daily practice. With its AI-based chest x-ray classifier, QUIBIM helps to detect pathological findings that could go unreported due to the heavy workload of radiology departments.

QuibimStructuredReport_Chest X Ray Classifier

“Our tool was designed to prioritize unreported, potentially pathological radiographs, to help radiologists be more efficient by focusing their efforts on studies that are more likely to have pathologies. We are sure this will have an impact in big healthcare systems,” Angel Alberich-Bayarri, QUIBIM CEO and founder, explained.

The solution makes use of a novel architecture based on referee networks combined with Convolutional Neural Networks that have been trained with a database of more than 500,000 images, to calculate the final probability of the X-Ray of being abnormal. Afterwards, the probabilities are used to estimate the presence of pathologies in chest X-Rays.

Because of this Artificial Intelligence 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,” Rafael López, Artificial Intelligence Engineer at QUIBIM, said.

QUIBIM’S Chest X-Ray Analysis Tool is already available at QUIBIM Precision®, 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.

Welcome post QUIBIM - José Gascón and José Sánchez 2

Our family keeps growing

We are proud to announce the incorporation of two new Quibimers in our growing team. Both excellent computer scientists, passionate about practising sport and named José!

José María Gascón Artal

In our Development Department, we welcome José Gascón Artal as Full Stack Web Developer. With nearly 4 years of previous experience in the IT sector working in the multinational technology consultancy as a Software Developer and in Communications agencies as Chief Technology Officer, he has joined our development team to help keep developing and improving the QUIBIM Precision Platform with new features.

Thanks to his great knowledge of JavaScript technology and his agile way of working we are sure he will play an important role in future QUIBIM’s milestones.

José is enthusiastic about developing his own apps with the technology stack MEAN and when he is not with his PC you can find him riding his motorbike, snowboarding or playing volleyball.

José Sánchez García

With a Bachelor’s and Master’s Degree in Telecommunication Engineering, both at the Polytechnic University of Valencia (UPV), and a specialization in Deep learning and Computer Vision algorithms, José Sánchez García has become part of our team as Data Scientist in the AI (Artificial Intelligence) area. A part-time job he combines with the role of Biomedical Engineer at the Fundación Hospital Provincial de Castellón, where he is in charge of new imaging biomarkers development and its integrations into QUIBIM Precision Platform.

Previous to join QUIBIM José has worked in Visia Solutions, where he lead image processing projects in Ford and SRG Global between others and he was also Intern Programmer in Everis. It was during his Master’s Thesis that he started to collaborate with us integrating Artificial Intelligence in Neuroimaging Analysis and when the synergy arose.

To achieve comprehensive success, as he says, he likes to combine his time at work with working out at the gym, doing Crossfit and a healthy diet not to mention that José is also really keen on doing song covers and playing tennis.

We wish you both a brilliant future in QUIBIM. We couldn’t be happier to welcome you as a new Quibimers!

Meet our team

OCT2019quibim

QUIBIM at the annual Outsourcing in Clinical Trials Europe 2019

We are very happy to share with you QUIBIM´s experience at the last Outsourcing in Clinical Trials Europe 2019 from 14th to 15th of May in Milan (Italy).

Clinical Trials Manager and Chief Strategy Officer, Irene Mayorga and Kabir Mahajan, joined this annual meeting to introduce the services that QUIBIM offers to CRO’s and pharmaceutical companies conducting imaging clinical trials. They had the pleasure of interacting with many novel drug development companies & CRO’s focusing on glioblastoma, pancreatic cancer, other cancers and diffused liver disease and had the chance to show QUIBIM´s experience on this front.

Also, we had the opportunity to discuss QUIBIM´s services as an imaging core lab, not only with the scientific and technical aspects, but also with the design and development of imaging documentation such as the imaging trial charter, the medical imaging validation and imaging acquisition quality control,  statistical analysis and other standard clinical trials management services.

If you did not have the chance to join us in Milan, you can meet Irene Mayorga Ruiz and Kabir Mahajan at the BIO Convention in Philadelphia from June 3- June 6, 2019 where they would be showing the latest developments in the QUIBIM Precision platform for managing clinical trials. You can use the following link to book a demo.

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QUIBIM team

La biotecnológica Quibim asume la gestión del banco de imágenes médicas del Pacífico e Italia

  • La empresa participada por Angels, la sociedad de inversión de Juan Roig, cierra un convenio para formar a 5.000 radiólogos tras adaptar su plataforma de extracción de biomarcadores Quibim Precision como herramienta educativa

  • La empresa, que abre nueva sede en Valencia, permite ahorrar tiempo y dinero al sector de los ensayos clínicos gracias a su sistema de cuantificar parámetros en radiología y medicina nuclear

València, 18 de abril de 2019.- La biotecnológica valenciana Quibim ha asumido la gestión del biobanco de imágenes médicas del Pacífico, tras cerrar un acuerdo con el centro de investigación del cáncer de la Universidad de Hawaii. La startup, participada por la sociedad de inversión de Juan Roig Angels, acaba de convertirse, además, en proveedor de este mismo servicio para imágenes médicas en Italia, gracias al sistema Quibim Precision, una plataforma de algoritmos de inteligencia artificial y análisis de imágenes radiológicas que fue desarrollado por esta joven empresa (fundada en 2012) con financiación del programa H2020 de la Comisión Europea.

El sistema Quibim Precision permite analizar imágenes médicas en la nube -aunque puede instalarse en versiones locales en hospitales o compañías- a partir de pruebas de rayos X, ecografías, TAC, resonancias magnéticas (RNM) o PET. Gracias a la aplicación de algoritmos de análisis, el software de Quibim posibilita extraer datos cuantitativos, que sirven para que el profesional médico haga el diagnóstico con más información.

Estos parámetros extraídos reciben el nombre de Biomarcadores de Imagen y aportan datos extraídos de imágenes médicas, relacionadas con procesos biológicos normales, enfermedades (por ejemplo tumores) o respuestas terapéuticas. Los modelos computacionales aplicados a las imágenes sirven para medir de manera objetiva los cambios producidos por una lesión o por tratamientos farmacológicos.

La tecnología Quibim se aplica en la práctica clínica, los ensayos clínicos, la formación en radiología y los proyectos de investigación. Con la adaptación de la plataforma al sector de la investigación se puede hacer una evaluación más temprana sobre la respuesta a los tratamientos en ensayos clínicos, con el consiguiente ahorro de tiempo y dinero, aspectos clave en cualquier proyecto de I+D+i.

Quibim ha cerrado un acuerdo con la Escuela Europea de Radiología (European School of Radiology, ESOR) para que su plataforma de apoyo al diagnóstico sirva como herramienta de formación para más de 5.000 radiólogos en todo el mundo. Ello gracias a que la plataforma ha sido adaptada como instrumento educativo. Actualmente, los radiólogos han de recurrir a meras imágenes proyectadas en power point en sus procesos formativos. La joven startup está inmersa en un proceso de expansión internacional. Hoy está ya presente en España, Reino Unido, Italia, Holanda, Dinamarca, Polonia, Portugal, Chile, Uruguay, Argentina, Estados Unidos, Taiwán, Japón e India.

Entre sus objetivos en este 2019, tras conseguir el marcado CE el pasado año, está conseguir la certificación FDA -un prestigioso sello médico para comercializar en Estados Unidos-  para consolidar una fuerte presencia en este país, ampliar la cobertura  a 60 hospitales y centros de diagnóstico y participar en una docena de nuevos ensayos clínicos de ámbito nacional e internacional.

Inaugura sede corporativa en Valencia

Quibim acaba de inaugurar nueva sede corporativa en Valencia, en el Edificio  Europa, uno de los hubs de negocio de la ciudad. La compañía biotecnológica ha crecido en los últimos cinco años hasta convertirse en una de las siete pymes que lidera mundialmente el desarrollo de tecnologías de postprocesado de imágenes médicas basadas en inteligencia artificial. Cuenta también con oficinas en Madrid y Palo Alto (California). En la compañía trabajan ya una veintena de profesionales.

Según Ángel Alberich-Bayarri, CEO y fundador de la compañía, “estas nuevas instalaciones representan un paso más para la compañía. Comenzamos de forma activa en 2014 con una idea dentro del programa Lanzadera y hoy celebramos con la inauguración de nuestra nueva oficina la evolución que ha tenido la empresa a lo largo de estos años, un gran hito para QUIBIM”.

Sobre Angels

Angels es la sociedad de inversión impulsada por el empresario Juan Roig que tiene como objetivo invertir en líderes emprendedores para desarrollar empresas sostenibles. Ofrece un modelo de gestión basado en el Modelo de Calidad Total, su red de contactos, así como toda la infraestructura necesaria para acompañar al emprendedor, comenzando por las oficinas situadas en el entorno del polo emprendedor Marina de Empresas.

Sobre TechTransfer UPV

Tech Transfer UPV es el primer fondo de transferencia de tecnología impulsado dentro del sistema universitario español que apuesta por proyectos de transferencia de tecnología y emprendimiento generados en la Universitat Politècnica de València para acompañarlos en su salida al mercado.

Dispone de un patrimonio de 3,9 millones de euros. El Fondo está participado por 28 empresarios y profesionales valencianos y de Castellón de diferentes sectores que, además de invertir, participan como validadores de los proyectos. Entre ellos, el Instituto Valenciano de Finanzas, Caixa Popular Productos Citrosol, Air Nostrum, Grupo IVI, Multiscan, ACAL, Arca Telecom, S2 Grupo, Miarco, La Unión Alcoyana Seguros, Nero Family, Blast of partners, Tecnopaking, Vik Consultoría o Ca&CCA ingeniería.

Parenchima workshop quibim

First QUIBIM Precision Hands-On Parenchima Cost Workshop

Valencia, March 14, 2019 –  Celebrating the World Kidney Day, QUIBIM, with the support of the Parenchima initiative, organized the first QUIBIM Precision Training Workshop for leading scientific researchers in medical imaging of kidney from 25 European countries.

On March 12th – 13th, QUIBIM hosted its first face-to-face workshop in Valencia (Spain) to train researchers and engineers who want to integrate medical image quantification algorithms in the Quibim Precision® platform. This is an initiative by QUIBIM with the objective of opening the platform to radiologists, clinicians and researchers who want to develop and implement their own MRI algorithms for chronic kidney disease.

QUIBIM was selected in the previous annual meeting of the Parenchima consortium in  Prague, (October 4th-5th, 2018), as the best system for medical imaging data management and integration of new analysis algorithms for the COST action project. Thanks to its ability to centralise, manage and store data extracted from the medical images from the different partner hospitals in a single platform, QUIBIM  offers the project to allow for acquisition protocols and algorithms comparison in terms of quality and precision, all at the same place.

PARENCHIMA WORKSHOP QUIBIM

The outcome of the project will consist of  new standards for image acquisition and analysis of MRI of the kidney for chronic kidney disease. QUIBIM’s team enjoyed hosting the workshop for the partners and are excited to be part of such a groundbreaking initiative.   

About PARENCHIMA

Renal MRI biomarkers are underused today 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

Welcome Mar Roca_QUIBIM

Mar Roca Sogorb joins QUIBIM as R&D projects Director

QUIBIM is growing rapidly! We are happy to announce the newest addition to our team. Mar Roca Sogorb has joined our company as Research and Development projects director. Due to her experience and background, she will help the research and innovation department with the upcoming projects and developments.

Mar received her formal training and defended her PhD thesis in astrophysics, but she decided to apply her knowledge in physics and in image processing tools to medical imaging.

Since then, she has been working on a large variety of topics related to magnetic resonance imaging (MRI) and spectroscopy (MRS). Mar has also developed dedicated algorithms for medical image denoising, segmentation and quantification for its integration into radiology workflow.

After a few years living in France, where she has been working as Research & Innovation Engineer at Olea Medical, Mar comes back to Valencia to join QUIBIM to support new algorithms development at the R&D department.

Congratulations! We officially welcome her and hope she has a prosperous career in the company.

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

Welcome Silvia Soler QUIBIM

New incorporation to QUIBIM Team!

We are happy to introduce you Mrs. Silvia Soler, who just joined the QUIBIM team as Executive Assistant & Team Coordinator.

Silvia has a degree in advertising and public relations by the University Rovira i Virgili (Tarragona) and a Master in Marketing and Sales Management by EFEM (Escuela de Formación Empresarial de Madrid). Her academic background provides a new perspective to QUIBIM and it will surely bring a wealth of knowledge and expertise in the fields of administration, management and communication.

Silvia has worked for many years as Administrative Assistant in one of the biggest Spanish hospital groups, so she is already familiarized with the healthcare environment. In QUIBIM, she will work closely to the Direction Department and will enhance the team coordination.

Beyond her professional side, Silvia likes running, going to the theater and hanging out with her friends. Her biggest passion is to travel around the globe and get to know other cultures. She will definitely become a Quibimer!

Congratulations! We officially welcome her and hope she has a prosperous career in the company.
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

Bianca Muresan

INTERVIEW | Quantification of body composition to detect malnutrition in oncological patients

Bianca Tabita Muresan, master in personalized and community nutrition by the University of Valencia and currently PhD student in nutrition and endocrinology, took time to answer some questions about the relation between malnutrition in oncology and quantitative imaging after her one week training period at QUIBIM.

Tell us about yourself and how did you come to know QUIBIM before your training period with us?

I am a PhD student at the Faculty of Medicine (University of Valencia) and my doctorate thesis is about the diagnosis of sarcopenia and measurement of body composition in cancer patients, using the CT scans previously done to the patient for the disease diagnose or the radiotherapy treatment planning. Specifically, I use the powerful information hidden in CT scans to detect malnutrition in those cancer patients with high risk of developing it, as for example happens in patients suffering from head and neck or lung cancer, or cancers that affects the digestive system.  After detecting malnourished cancer patients, I work together with the Endocrinology and Nutrition Department to translate nutrition goals for improving cancer treatment collateral effects (as for example fatigue, vomiting, diarrhea, dysphagia, among others), or to assist with nutritional supplements of feeding tubes to help keep up a patient’s strength during treatment.

Due to my Master practicum and some research projects I collaborate since four years ago with many investigators of La Fe Health Research Institute in Valencia. Moreover, my thesis director (Dr. Alegría Montoro Pastor), recommended me to contact QUIBIM and GIBI for a short internship during my university studies and I knew that could improve my performance at work, as well as help me to reach new skills about imaging biomarkers.

 

Your field of expertise is malnutrition in Oncology. The Quantitative Medical Imaging field has significantly increased in the last years, but in hospitals, we still use anthropometric mediations as for example body mass index (kg/m2) for evaluating body composition, so what do you think is the main reason for using medical imaging?

Anthropometric variables, as for example body mass index, are the most commonly employed measures for detecting nutritional status in epidemiology, because of their simplicity and easy data collection. The problem is that in clinical practice, these parameters have a significant inter and intra observer variability. Moreover, they don’t allow the detection of major body compartments (such as lean body mass or adipose tissue), the estimation of body composition or to description of body fat distribution, which have been proved to be highly correlated to different degrees of malnutrition and sarcopenic obesity. In those cases, medical imaging, as for example computed tomography (CT) and magnetic resonance imaging (MRI) would facilitate the quantification of body fat and muscle mass distribution. For this purpose, 3D image segmentation techniques are applied, which allow the differentiation of subcutaneous fat, visceral fat, muscles and fatty infiltration within the muscular tissue. As of today, most of the 3D image segmentation techniques require manual correction but new artificial intelligence (AI) algorithms based on Convolutional Neural Networks (CNN) are providing promising results in the field.

What means sarcopenia and sarcopenic obesity and which are the effects of these terms to oncological outcomes? How could you measure these terms with medical imaging?

Sarcopenia is defined as a loss of skeletal muscle mass and decrease muscle function with or without loss of body weight and body fat. This condition could also occur in patients who present overweight, coexisting both pathologies: sarcopenia and obesity. The prevalence of sarcopenia in cancer patients was found to be a bad prognostic factor for disease progression and survival, as well as a negative predictor of toxicity levels and treatment complications.

In clinical practice we use bio–impedance analysis (BIA) for the evaluation of lean body mass and total adipose tissue, and this could also be analyzed by dual x-ray absorptiometry (DEXA). In addition, CT and MRI have shown to be excellent tools in assessing muscle mass tissue and different fat areas inside the body (subcutaneous, visceral and intramuscular). In the last years, several studies have suggested different cut-off values for detecting low muscle mass and low muscle density.  With this information, we try to detect pathological processes as for example pre-sarcopenia (which means loss of muscle mass without loss of muscle strength), myosteatosis (which means fat within and around skeletal muscle) and visceral obesity. The evaluation of muscle function for the diagnosis of sarcopenia is completed by measuring handgrip strength.

Which indicators are you working with at present and which ones do you think are the best by incorporating quantitative imaging in the future to analyze body composition in hospitals?

At the moment, we measure skeletal muscle mass, intramuscular adipose tissue, visceral adipose tissue and subcutaneous adipose tissue in cancer patients before starting cancer treatment. On the other hand, we try to study full body composition before starting radio – chemotherapy. As being a nutritionist, this technique helps to improve my work using the best technology. Related to the quantification of these imaging biomarkers, we have already sent different communications to Spanish congresses and written scientific articles for my PhD thesis, which are now in review.  Moreover, our department also works trying to find out different anatomical locations with major loss of muscle mass before cancer treatment, as well as correlating the prevalence of sarcopenia with toxicity levels and quality of life after antineoplastic treatment.

 For the future, I believe it would be helpful to include bone measurements to identify patients with osteopenia and in those patients with MRI, determine fat concentration in the liver (steatosis) would also be important for detecting important nutritional problems.

Finally, tell us shortly how did you find the experience at QUIBIM and GIBI these days and how could this training period improve your work?

 First of all, I would like to thank all the teamwork of QUIBIM and GIBI for offering me the opportunity to learn about the most advanced technology. I have definitely improved my skills about discovering interesting quantitative imaging biomarkers as for example fat liver and iron concentration, which are very important for future nutrition researches. It was absolutely an enriching experience. Thank you! 

Thank you Bianca for your time!