Quibim Precision

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_MIUC

MIUC
the new toolkit of QUIBIM Precision® platform to beat traditional workstations

Quibim has implemented a new toolkit named MIUC (Medical Imaging Universal Connector) to close the gap between hospital IT systems and the Cloud. Whereas the Cloud satisfies the processing requirements, Quibim Precision® handle the functionalities related to communications and management of DICOM objects among the hospitals and radiological centers.

Quibim Precision® allows users in hospitals and radiology departments to have a seamless integration of imaging biomarkers analysis within the radiological workflow, due to the MIUC capabilities combined by the Quibim Precision® Cloud computing environment and the interoperability features implemented in our system. Both image upload and data retrieval are fully automated and users only need to access the PACS when they are notified that a new biomarker report is available.

MIUC is placed inside the hospitals and clinics and it is responsible to establish all the required communications between the PACS and Quibim Precision®. During the analysis of imaging biomarkers, the study is anonymized, sent to the Cloud and analyzed. The final result is a one-page report which is sent back to the MIUC or can be directly visualized in the Quibim Precision® web interface. Furthermore, in clinical environments, the report is converted into DICOM objects and stored in the PACS as a new series within the original study. To identify the original study, the MIUC implements backward traceability in the client side to reidentify the anonymized studies.

Our platform is intended to be used by radiologists, either from a clinical environment, thanks to the MIUC, or as a final user using the web interface. In the clinical environment scenario, radiologists using Quibim Precision® do not have to worry about where the study or the report is. Instead, these issues are transparent to the user, who do not have to perform any action to launch a biomarker process, given that the MIUC rule engine does such work for them. The user will be notified by email when a new biomarker report is ready (and available in both the PACS and the Quibim Precision® web interface).

Nowadays, our Quibim Precision® platform is compliant with the DICOM standard at both communication level and data management and formatting level. Specifically, our platform receives imaging studies from hospitals, radiological centers or pharma companies. Then, the system analyzes the study and obtains quantitative measures, which are stored in a quantitative database and structured in a one-page report on a per-patient basis. Finally, this report is returned back as a result.  Quibim Precision® allows annotating biomarker reports using terms from RadLex and MeSH, enhancing the interoperability of its biomarker reports with other health information systems. In fact, the imaging platform is seamlessly integrated with the hospital PACS, being able to query and retrieve medical studies, processing them and storing the resulting biomarker reports as DICOM objects in the hospital PACS. On the other hand, the processing stage is performed on the Cloud, taking advantage of its benefits: high-performance computing and real-time hardware scalability on demand.

But, what has changed?

In previous updates of our platform, we improved the performance, capabilities and user settings view. With this new suite software QUIBIM Precision®- MIUC does query/retrieve the PACS, anonymizes the PACS responses and forwards them to Quibim Precision® in the Cloud. Furthermore, the MIUC leads our solution to a higher level of automation, given that it monitors the PACS querying for incoming studies. Once a new study reaches the PACS, the MIUC analyzes its header and determines whether a new biomarker analysis must be launched or not, depending on some DICOM elements in the study like imaging modalities, study description, series description or body part among others. For each biomarker analysis available in Quibim Precision®, there is a predefined set of rules that establishes which studies are susceptible to be processed by each analysis method. An incoming study matches a given analysis method whenever it fulfils the predefined set of rules for such analysis method. When this happens, the MIUC automatically sends the study to the Quibim Precision® Cloud processing platform, where it will be processed by the matching biomarker analysis pipeline. Once processed, a biomarker report is generated with the results and sent back to the MIUC. Finally, the MIUC stores the report in the PACS as a DICOM object, making the report available for the specialist who requested it. This way, the Cloud platform remains centralized and, at the same time, fully integrated with the hospital IT systems.

With the arrival of MIUC toolkit the need for conventional workstations with expensive licenses in radiology departments completely disappears. As in other business areas that are evolving from product to service, the Quibim image analysis technology was designed to be offered as the service that puts disruptive image analysis solutions at your fingertips.

025-FEDER2-declaracion14-20

El proyecto QUIBIM recibe el apoyo del FONDO EUROPEO DE DESARROLLO FEDER

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 (ITAPIN IT16 PLANES DE INTERNACIONALIZACIÓN PYME CV 2016) 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.

quibim map

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.

 

 

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Quibim Precision V2.0

It is a real pleasure for Quibim to announce the release of Precision 2.0. On this new version, we have focused on improving its performance, making it more powerful and user friendly. Keep reading to know how we did it…
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3D_Full_Low_Both

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

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

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

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

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

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

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

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

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

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

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

00c

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

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

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

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

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

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

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

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