Posts By :

Angel Alberich-Bayarri

ESGAR Conference CCD Dublin Ireland 2018.

Co-Founder Prof. Luis Martí-Bonmatí receives ESGAR Gold Medal

During the 29th Annual Meeting and Postgraduate Course of ESGAR (European Society of Gastrointestinal and Abdominal Radiology) held in Dublin, our co-founder, Prof. Luis Marti-Bonmati received the ESGAR Gold Medal, the society’s highest award for outstanding contributions to the scientific community.

All QUIBIM team is proud and honoured. We congratulate Prof. Martí-Bonmatí on this achievement.

ESGAR Conference CCD Dublin Ireland 2018.

ESGAR Conference CCD Dublin Ireland 2018.

Photo credit: Roger Kenny Photography

Photo legend (from left to right): Steve Halligan (ESGAR President), Luis Martí-Bonmatí (Gold Medallist), Celso Matos (ESGAR Past President), Helen Fenlon (ESGAR Meeting President 2018).

Link to Insights into Imaging post: https://www.i3-journal.org/news/esgar-goldmedal/

 

Ines Perea, Strategic Advisor at QUIBIM

Quibim’s Strategic Advisor Inés Perea discusses the radical disruptions that quantitative imaging analysis can provide to cancer research

Quibim’s Strategic Advisor Inés Perea discusses the radical disruptions that quantitative imaging analysis can provide to cancer research amongst other areas

Inés Perea is a Doctor that graduated with honors in the Pharmacy and Executive Business Program by Instituto de Empresa of Madrid. Mrs. Perea has extensive and versatile experience spanning more than 20 years in the Pharmaceutical industry working within different roles within the Medical, Access and Commercial (Marketing, Sales, Strategic Planning) areas and international experience in Global and regional teams. Her main area of expertise is oncology and biologics where she has been involved in the strategic planning and commercialization of more than 10 drugs/indications, most of them linked to some form of biomarker diagnosis.

How did you come to know QUIBIM before becoming their strategic advisor?

I was in contact with founder and CEO, Angel Bayarri months prior to my start with Quibim. A mutual friend of ours, a director of a large genetics biomarker laboratory in Spain was working specifically on oncology genetic biomarker testing and I would get involved with his organization in the arenas of strategic value and development, as those are two of my core competencies. I was involved in the development and strategic value of genetic/biologic biomarkers in clinical trials in oncology. It was back in the 90’s when biomarkers were a thing of science fiction. Well, he introduced me to Angel and I really thought he had a fantastic idea when it came to implementation of 3-d imaging biomarkers and using algorithms to quantitatively analyze tumors. Once I learned about Quibim’s technology, I knew that the growth could be exponential if he partnered with strategic partners.

Your field of expertise is Oncology. The Quantitative Medical Imaging field has evolved significantly but we still use RECIST criteria for evaluation of treatment responses, what do you think is the main reason for this? Standardization?

This is the foundation for therapeutic trials. It is a standard when examining patients, however, it has some practical limitations. For example, with the latest breakthrough area in oncology research, immunotherapy, many immuno-oncology drugs are known to cause fluctuations in tumor size, which when analyzed simply with RECIST criteria, would appear as an increase to the tumor size, but it is now understood that tumor fluctuations occur regularly during immunotherapy treatments, often causing the tumor to grow prior to cell DE progression, which is in fact a good sign that would be captured with RECIST criteria well after the fact. In those cases, RECIST does not allow for factoring in the context of the holistic viewpoint that quantitative digital image analysis would facilitate.

What therapeutic indications are best served by incorporating quantitative imaging analysis into clinical research trials?

There is a very simple answer to this question: any therapeutic indication where standardized radiological assessments are a primary or secondary safety or efficacy endpoint of a study. This includes solid tumors, liver diseases, brain diseases, lung diseases, and many others.

Let’s discuss costs. Quantitative imaging analysis sounds expensive. However, automation and extraction of biomarkers as soon as a hospital acquires and uploads images related to a clinical trial can and do have a macroeconomic effect of lowering costs, therefore long-term costs decrease. What do you respond with when someone brings up this objection?

You are right, it is a tremendous cost saver from a macroeconomic point of view. What will continue to help this cause are national health systems, private funding, insurers, and other payers to see the long-term cost savings and efficiencies that quantitative imaging analysis facilitates. Essentially, we need to get quantitative image analysis included in the health system reimbursement system much like traditional biomarkers of a decade ago. As a matter of fact, it took health systems quite a bit of time to include standard biomarkers that we have all grown accustomed to, included on their reimbursement schedules. While it essentially all boils down to payers and health authorities, us researchers and technology pioneers need to continue to prove medium and long-term efficiencies and validate it with radiologists, clinicians and imaging researchers. Once we are able to do that effectively, the market will adjust accordingly, it always does.

The value seems to be in real-time results that can help in both safety and efficacy outcomes. Please expand further on this thought.

Real time results are everything if you really think about it. The main benefit is obviously how this technology facilitates the real time patient care capabilities of healthcare practitioners. Safety and efficacy instant results from treatments are critical when analyzing real time clinical research data. Imaging biomarkers can and will play a tremendous role in improving patient standard of care, and ultimately can make a real impact on disease outcomes.

by: Dan Sfera, also available at: https://medium.com/quibim/quibims-strategic-advisor-in%C3%A9s-perea-discusses-the-radical-disruptions-that-quantitative-imaging-54cef3a3e082

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.

025-FEDER2-declaracion14-20

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.

IVACE_QUIBIM

Quibim Team

QUIBIM SIGUE CRECIENDO CON LA ENTRADA DE ANGELS EN SU CAPITAL

  • En 2015 fue una de las 27 startups aceleradas en la 3ª edición del programa Lanzadera.

  • Quibim es una Spin-Off del Instituto de Investigación Sanitaria La Fe.

Valencia, 28/07/17.- La empresa biotecnológica Quibim se refuerza mediante la entrada de Angels – la sociedad de inversión perteneciente a Marina de Empresas e impulsada por el empresario Juan Roig – en el capital social de la compañía.

Tras la ronda a finales de 2016 con el Fondo de Inversión Tecnológico Tech Transfer UPV, AYCE Capital, Bioinfogate y los promotores del proyecto; y la ayuda H2020 Instrumento Pyme Fase II, de la que ha sido beneficiaria recientemente; Quibim recibe el apoyo de Angels, que participa en la empresa mediante la capitalización del préstamo que la compañía tenía con Lanzadera.

Impulsada por Ángel Alberich Bayarri, CEO, y el Dr. Luis Martí Bonmatí, radiólogo de reconocido prestigio internacional, director del Área Clínica de Imagen Médica del Hospital Universitario y Politécnico La Fe de Valencia y actual director del Consejo Científico de la empresa; la compañía está formada en la actualidad por 11 personas.

Quibim es una empresa biotecnológica 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 avanzados algoritmos de análisis que incluyen 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.

Según afirma Ángel Alberich-Bayarri, “La entrada de Angels en la compañía es para nosotros una gran satisfacción, ya que se materializa la relación iniciada en nuestro paso por Lanzadera, cuya ayuda fue imprescindible para hacer este proyecto realidad”.

El Director General de Angels, Jaime Esteban, añade, “Contar con Quibim entre las participadas de Angels afianza lo que Marina de Empresas quiere significar para los emprendedores: un lugar donde recibir apoyo en cualquier momento de su carrera, desde la formación hasta la inversión”.

 

Sobre Angels

Angels es la sociedad de inversión perteneciente a Marina de Empresas e impulsada por el empresario Juan Roig con capital 100% privado. Desde su constitución en septiembre de 2013, ha aportado a diferentes proyectos emprendedores más de 12 millones de € para que estas empresas de nueva generación puedan crecer y desarrollar su actividad. En la actualidad, Angels participa además de en Quibim, en Codigames, Grupo Sothis, Instituto Valenciano del Pie (IVPie), Grupo Vintes (Bodega Torre Oria), viVood y PlayFilm.

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.

QUIBIM at BIO 2017

QUIBIM in BIO 2017

Our company was present again this year in the incredibly huge BIO International Convention in San Diego, California, from June 19th to 22nd. Our registration included both a booth at the Spanish pavilion and the access to the One-to-One partnering meetings.

We had 15 planned meetings and many other new contacts thanks to the interaction at our exhibitor space with agents interested in QUIBIM business model. We made several demonstrations of QUIBIM Precision platform and image analysis capabilities in clinical trials. From all the contacts and meetings performed at BIO, I wanted to point out the classification we found according to their profile:

  • Scientific parks and incubators (30%)
  • Investors in Life Sciences (20%)
  • CRO’s and Pharma companies (50%)

From our experience last year in San Francisco, in this edition there has been a higher interest from scientific parks and incubators beyond Boston and Silicon Valley to attract companies to their facilities, showing the benefits of establishing the companies in specific locations, specially in the different states of US. The number of investors stayed similar, but we have been an increasing interest in the field of Medical Devices. Regarding CRO’s and Pharma companies, most of them are progressively considering medical imaging in their clinical trials, and the best, considering us for their solutions. We are so proud to cover those unmet needs on advanced image analysis services for Clinical Trials, allowing pharma companies, CRO’s and Principal Investigators to follow-up in real time their study. In fact, one of the main trends at BIO this year was how data processing will change the way new drugs are developed and launched into market.

QUIBIM CEO (Angel Alberich-Bayarri) & Booth at BIO 2017

QUIBIM CEO (Angel Alberich-Bayarri) & Booth at BIO 2017

 

We were so glad to have this exhibitor space at the Spanish pavilion, and compared to previous editions, it was also the first time that the Valencia region had a dedicated area inside it (similar to Biocat from Catalonia and Biobasque from Basque Country). The Valencia area was organised by IVACE (Instituto Valenciano para la Competitividad Empresarial), and the organism was represented by Mrs. Mónica Payá (representative for foreign investment of IVACE). The Principe Felipe Research Centre (CIPF), was also represented by Oscar David Sánchez (Projects and Technology Transfer Manager).

Valencia region representatives at BIO 2017 in San Diego, Angel Alberich (QUIBIM), Mónica Payá (IVACE), Daniel Calvo (BIOPOLIS), Marisol Quintero (Biooncotech)

Valencia region representatives at BIO 2017 in San Diego, Angel Alberich (QUIBIM), Mónica Payá (IVACE), Daniel Calvo (BIOPOLIS), Marisol Quintero (Biooncotech)

 

Valencia region representatives at BIO 2017 in San Diego, Óscar David Sánchez (CIPF), Mónica Payá (IVACE), Daniel Calvo (BIOPOLIS), Angel Alberich-Bayarri (QUIBIM)

Valencia region representatives at BIO 2017 in San Diego, Óscar David Sánchez (CIPF), Mónica Payá (IVACE), Daniel Calvo (BIOPOLIS), Angel Alberich-Bayarri (QUIBIM)

 

All the days at BIO were so productive that there is a significant work to be done at home, contacting back with the people we met and following up these new relationships.

Obviously not everything is work and there is also some spare time for entertainment at BIO, in the following picture, a rock band playing at the middle of Gaslamp quarter in San Diego. The streets were closed to welcome BIO 2017 participants in a nice evening with food, drink and music, a nice experience!

Band performing at BIO 2017 in middle of Gaslamp quarter

Band performing at BIO 2017 in middle of Gaslamp quarter

Lymphatic system

Imaging Biomarkers in Lymphoma

Imaging has a crucial role in Lymphoma management nowadays. The main applications are based on the evaluation of disease extension in staging and in treatment response evaluation. Recently, thanks to the technology development of PET-CT and CT scanners, it has shown also a high utility in the evaluation of extra-nodular involvement, the early relapse and the transformation from indolent Lymphoma to an aggressive phenotype [1].

Evidence sets PET-CT and standard CT+contrast as the main imaging modalities for staging and treatment response evaluation. The most suitable modality will depend mainly on the aggressiveness and the FDG avidity of the lesion. Therefore, either for Hodgkin’s Lymphoma (HL), aggressive subtypes of non-Hodgkin’s Lymphoma (NHL) or for extra-nodal involvement evaluation in PET-CT will be the way to go for an appropriate staging. However, in cases of non-FDG avidity, mainly in indolent lymphomas (T-cell lymphoma and subtypes of NHL like Chronic Lymphocytic Leukemia, Marginal Zone Lymphoma, Lymphoplasmacytic Lymphoma), contrast enhanced CT is the main modality. Regarding response evaluation, a similar distribution of lymphoma subtypes per modalities is arrange, with the difference in the Follicular Lymphoma (FL), where PET-CT is the most suitable technique for those FL with a high tumoral burden, whereas low tumoral burden FL should be studied by CT with contrast when studying response. Up to now, Magnetic Resonance Imaging (MRI) has still not shown enough evidence in the management of lymphoma patiens beyond Primary Brain Lymphoma. PET-MR has a promising future in Lymphoma evaluation, specially in the current need for low dose follow-up studies that could be done with this modality.

Imaging Applications in Lymphoma

Imaging Applications in Lymphoma

 

Due to heterogeneities in FDG metabolic uptake in different Lymphoma subtypes, Deauville criteria were established to grade the avidity in comparison with mediastinum and liver. However, conventional PET-CT has limitations in the staging of nodular alterations, with the exception of FL, where PET-CT helps to increase the stage of Lymphoma by detecting additional disease in up to 29% of cases. Regarding response evaluation, PET-CT has been recently considered as the gold standard at end of treatment in FL. This is one of the main conclusions from GALLIUM study.

Despite the previous comments, we understand that the staging and response evaluation in PET-CT in patients under new treatments based on targeted therapies or immunotherapy can not be only based on SUVmax evaluations. New imaging biomarkers have been developed in order to evaluate complex clinical scenarios like indolent Lymphoma or reactive inflammatory changes at the end of treatment in patients that have responded to therapy.

In the following table, specific Imaging Biomarkers for different biological objectives are provided:

Objetive Modality Imaging Biomarker
Tumoral burden PET-CT Metabolic Tumor Volume (MTV)
Tumoral burden + Metabolic activity PET-CT Total Tumor Glycolisis (TTG)
Change in metabolic activity PET-CT Voxelwise Delta-SUV (ΔSUV)
Heterogeneity CT & PET-CT Textures

For Imaging Biomarkers implementation, we always follow the step-wise method that we developed and published and that was also considered in this European Society of Radiology guideline.

The first technical step of Imaging Biomarkers development workflow after an appropriate definition of the idea is the Images Acquisition. In PET-CT, European Association of Nuclear Medicine (EANM) guidelines should be followed, and centres should be ideally certified by EARL program.

Metabolic Tumor Volume (MTV)

The first Imaging Biomarker to be calculated is MTV. It is defined by consensus as those lesion voxels with a significant FDG uptake, that is >41% of SUVmax although different thresholds can be evaluated in practise. The typical units are cm^3. The analysis is performed semi-automatically by thresholding and manual correction.

Calculation of Metabolic Tumor Volume

Calculation of Metabolic Tumor Volume

 

Several studies have analysed MTV values in different types of lymphoma, in the following table from Schöder H. J Clin Onc 2016, a nice summary can be appreciated:

Schöder H, Moskowitz C. Metabolic Tumor Volume in Lymphoma: Hype or Hope? J Clin Oncol. 2016 Sep 6. pii: JCO693747. [Epub ahead of print] PubMed PMID: 27601547.

Schöder H, Moskowitz C. Metabolic Tumor Volume in Lymphoma: Hype or Hope? J
Clin Oncol. 2016 Sep 6. pii: JCO693747. [Epub ahead of print] PubMed PMID:
27601547.

The different thresholds used for MTV can be also appreciated (although 41% SUVmax is the one in the majority of them). Also, the wide range of MTV obtained show us the high heterogeneity of the disease and raises also the concern about treatment dose. Should we modulate the treatment given to patient by the MTV? or, on another way, does a patient with 600cm^3 of MTV have to receive the same treatment dose than a patient with 3000cm^3 ? Important research needs still to be done in this field.

Regarding MTV and Follicular Lymphoma, few studies have been performed. The most important one was a retrospective analysis from Meignan et al, where they calculated a MTV of 510cm^3 for 2-year Progression Free Survival (PFS). However, some controversy has arose mainly due to the fact that the inherent error in SUV measurements due to examination variability introduces a final MTV error in measurements around 20%, so the threshold should not be a single value, but a given range of MTV values that consider that error.

 

Total Tumor Glycolysis (TTG)

The TTG measurements is better applied for specific lesions rather than all lesion burden. Therefore, if we focus on specific lesions, the TTG combines information on the FDG avidity and the MTV of the lesion by the following equation:

TTG = MTV x SUVmean

 

Voxelwise delta-SUV 

The structural and anatomic information contained in the CT examination within the PET-CT acquisition can be used for spatial registration of scans of the same patient corresponding to different timepoints (e.g. registration of end-of-treatment CT on baseline CT). The idea behind this is to create a parametric map of the longitudinal SUV changes in the patient, and for that the deformation field resulting from spatial registration is applied to the end-of-treatment PET in order to convert it to the baseline geometry. After this process, the follow-up examination can be superimposed to the baseline and therefore even substracted to calculate the SUV difference between timepoints.

delta-SUV pipeline

delta-SUV pipeline

 

Textures analysis

The image regions can be also evaluated quantitatively by means of texture analysis. Texture analysis allows for the extraction of quantitative descriptors from voxel intensities relationships within an image or region. They are organised in first order (if directly extracted from histogram) or second order (if an additional step is required for their calculation). Texture analysis and specially heterogeneity biomarkers like the entropy and kurtosis have shown promising results in many different cancerous lesions, specially as a prognostic biomarker.

Texture analysis from lymphoma lesion in CT

Texture analysis from lymphoma lesion in CT

In lymphoma, a recent manuscript from Ganeshan B. et al. has shown excellent results in providing complimentary information to the interim PET as a prognostic biomarker.

However, texture analysis techniques can also be applied to other type of images such as the PET component, being able to determine the metabolic heterogeneity (MH) of the lesions. In this regard, lesions with different regional FDG avidity are having a worse prognosis than lesions with a homogeneous FDG uptake.

Metabolic Heterogeneity in FDG uptake in lymphoma

Metabolic Heterogeneity in FDG uptake in lymphoma

 

As you have discovered in this post, there are still many Quantitative Imaging Biomarkers that can be extracted from conventional FDG PET-CT examinations, and which are showing important relationship with lymphoma progression, according to recent investigations. In QUIBIM we are a committed team dedicated to the implementation of these techniques in clinical practise, research and clinical trials. If you want to collaborate with us in this field do not hesitate to contact us and potentially upload a case through our QUIBIM Precision® platform. It will be the best way to start working together in this emerging field.

 

 

Quibim Team

We are Hiring! Do you want to be a Quibimer?

We are excited to announce that we are seeking an Engineer to join our fantastic team in Valencia.

What do we need?

  • Enginner with 1-2 years of experience in the field of software development and medical imaging (biomedical, Computing, Electronics)
  • Experience as Java Developer
  • Experience with SQL databases
  • Experience in web development based on API-REST
  • Experience with GIT version control
  • Experience in application deployment with Apache Tomcat
  • Fluent english

Our ideal candidate’ Skills & Experience…

  • Experience with Spring or Jersey frames
  • Experience in integrating external APIs
  • Experience with the dcm4che library
  • Test Driven Development Experience (TDD / BDD)
  • Experience with the DICOM and HL7 standards
  • Experience in integration with PACS and RIS systems
  • Experience in developing CLI applications

What is a plus?

  • Experience with the C ++, Python or NodeJS languages
  • Experience as a FrontEnd
  • Experience with NoSQL databases
  • Experience with Microsoft Azure

If you are proactive, dynamic and forward thinking profile Apply Here