contextflow & Neologica partner to bring comprehensive chest CT support to radiologists

News Press

2024-06-06

Vienna, Austria (June 5, 2024) – Neologica, the long-running developer of advanced medical imaging software solutions, and contextflow announce a commercial partnership to bring contextflow’s ADVANCE Chest CT solution to Neologica’s radiology base. 

Under the partnership, contextflow’s innovative computer-aided detection support for chest CT will be integrated into Neologica’s LogiPACS. Founded in 2002, Neologica develops a range of products, including a PACS server, DICOM viewer and online patient portal. All of the company’s products are developed in-house for maximum interoperability. By partnering with contextflow, Neologica can offer its users a powerful tool to detect lung cancer, ILD patterns and COPD on chest CT.

contextflow’s core technology is ADVANCE Chest CT, an AI-based medical device software that detects, visualizes and quantifies nodules and lung disease patterns to improve the speed and quality of radiology reporting with consistent, objective information. Its upcoming malignancy scoring feature has been shown to not only detect lung cancer sooner but also to reduce both false positives and false negatives (*Adams, Scott J et al., JACR September 2022). 

As Marco Sambin, CEO at Neologica explains, “It’s undeniable that the PACS market is expressing a strong demand for diagnostic decision support solutions through AI. Neologica’s partnership with contextflow is a response to this request within the realm of chest CT imaging. ADVANCE Chest CT is an extremely advanced (CE MDR certified) product for the detection of lung nodules and other lung pathologies. Users of our LogiPACS and RemotEye Viewer will have access to an AI-enhanced workflow with seamless integration into our software modules.”

In addition to increased access to clinical decision support for chest CT, the partnership aims to reduce false positives and patient stress in relation to lung cancer detection via malignancy scoring. Malignancy scoring is a newly released feature that enables a radiologist to compare suspicious nodules to thousands of others with known outcomes in order to indicate the probability that a given  nodule is malignant or benign. As contextflow Chief Commercial Officer Marcel Wassink puts it, “Malignancy scoring has been validated in a clinical study to reduce false positive nodule detection by 18% while detecting lung cancer up to one year earlier. We hope this level of certainty helps avoid patient anxiety and reduce unnecessary costs and work for radiologists.”

About contextflow 

contextflow is a spin-off of the Medical University of Vienna (MUW) and European research project KHRESMOI, supported by the Technical University of Vienna (TU). Founded by a team of AI and engineering experts in July 2016, the company has a strong interest in bringing state-of-the-art machine learning techniques to the market e.g. improved emphysema detection and lung segmentation. Its computer-aided detection software ADVANCE Chest CT is CE Marked and available for clinical use within Europe under the new MDR.

About Neologica

Neologica is an ISO 9001 and ISO 13485-certified company designing and developing advanced software solutions in the medical imaging field.

With more than 20 years of history and experience, and developing the initial goal of specializing in the DICOM field, today Neologica has a complete range of DICOM-compliant software products in the medical imaging field. This range is composed of software modules that the company has designed and developed in-house from the ground up, covering everything from visualization to archiving, from printing to data exchange. Today, Neologica continues to innovate with original ideas and a strong focus on the quality of its products.

With 5000+ installations across 40+ countries and 5 continents, along with a record of highly satisfied customers, Neologica is now a recognized actor in the medical imaging domain.

The professionalism and skills of its human resources are fundamental values for Neologica; exceeding customers’ expectations with its products is the company’s main objective.

For more information, contact: 

Julie Sufana, Chief Marketing Officer, contextflow, email: julie@contextflow.com 

Phone: +43 6769201032 

Marco Sambin, Chief Executive Officer, Neologica, email: marco.sambin@neologica.it

Phone: +39 019 505314 

contextflow targets early lung cancer detection by augmenting ADVANCE Chest CT with malignancy scoring from RevealDx

News Press

2024-05-02

Vienna, Austria (02.05.2024) – Chest CT experts contextflow GmbH have released a new version of their comprehensive computer-aided detection support tool, ADVANCE Chest CT. In addition to lung nodule detection, quantification, visualization and classification, the updated software now analyzes nodules for malignancy with the aim of detecting cancer early and reducing unnecessary procedures.

It’s widely known that lung cancer constitutes one of the leading causes of premature death, and thus early detection of cancer is crucial. For that very reason, contextflow has implemented a malignancy Similarity Index (mSI) feature into ADVANCE Chest CT, a clinical decision support tool that aids radiologists in the diagnosis of lung cancer, interstitial lung diseases (ILD) and chronic-obstructive pulmonary disease (COPD). 

A malignancy Similarity Index is a value from 0 to 1 that indicates the degree of similarity between a nodule in question and nodules with known outcomes in a reference set. In clinical practice, a high mSI would indicate “upgrading” followup of a nodule as compared to guideline recommendations because there is increased certainty that the nodule in question is malignant. Here, the goal is to detect cancer as early as possible in order to improve patient outcomes.

As contextflow CEO Markus Holzer puts it, “Detecting lung cancer is a challenging and time-consuming task for radiologists. Detection is not straightforward. All too often patients are scheduled for followups months after their initial exam without knowing whether they actually have cancer or not. This is extremely stressful, but thankfully we can start to change that.”

On the flip side, a low mSI score would indicate “downgrading” the nodule with the aim of reducing invasive, unnecessary procedures and patient stress. In a clinical study published in the Journal of the American College of Radiology, use of the RevealDx mSI feature was shown to detect cancer up to one year sooner in approximately 45% of cases while simultaneously reducing false positive detection rates by 18% (Adams, Scott J. et al. JACR September 2022).

As Chris Wood, CEO of RevealDx says, “Our integration with ADVANCE Chest CT simplifies the interpretation of lung nodules. Automatically detected nodules have their mSI scores calculated before the radiologist starts reading the exam, which should save time while providing clinical insight.”

The latest version of contextflow ADVANCE Chest CT also includes a nodule tracking report to visualize and quantify changes in nodules over time. contextflow ADVANCE Chest CT is a CE marked medical device under MDR. For more information, contact sales@contextflow.com or visit contextflow.com.

About contextflow 

contextflow is a spin-off of the Medical University of Vienna (MUW) and European research project KHRESMOI, supported by the Technical University of Vienna (TU). Founded by a team of AI and engineering experts in July 2016, the company has a strong interest in bringing state-of-the-art machine learning techniques to the market e.g. improved emphysema detection and lung segmentation. Its computer-aided detection software ADVANCE Chest CT is CE Marked and available for clinical use within Europe under the new MDR. Visit contextflow.com for more information. 

About RevealDx

RevealDx developed RevealAI-Lung, the world’s first CADx software for the characterization of lung nodules to receive the CE Mark. RevealAI-Lung has been validated in clinical studies that show improvement in diagnostic precision using our patented methods.  Results demonstrate the software can significantly accelerate lung cancer diagnosis and reduce unnecessary procedures. https://reveal-dx.com/

For more information, contact: 

Julie Sufana, Chief Marketing Officer, contextflow

Email: julie@contextflow.com 

Phone: +43 676 920 1032 

Chris Wood, CEO, RevealDx

Email: chris@reveal-dx.com

Phone: +01 425 895 2845

Blackford and contextflow Announce Commercial Partnership to Bring Comprehensive Chest CT Detection Software to Healthcare Providers

News Press

2023-11-16

Edinburgh, Scotland (November 16th, 2023) – Blackford, the pioneering strategic AI platform and solutions provider, and contextflow today announced a commercial partnership to bring contextflow’s ADVANCE Chest CT solution to healthcare professionals.

Under the partnership, contextflow’s innovative technology will be integrated with Blackford’s advanced enterprise AI platform. Blackford provides healthcare professionals access to an extensive portfolio of medical AI solutions designed to drive clinical efficiency and improve patient outcomes. By integrating contextflow’s advanced detection technology into the Blackford platform, Blackford can offer healthcare providers a powerful tool for detecting ILD, COPD and lung cancer on chest CTs.

“Blackford exists to improve the lives of patients and populations – we can do this by providing tailored AI solutions to healthcare providers around the world to help enhance therapy selection and treatment optimisation”, said Ben Panter, CEO of Blackford. “We are delighted to partner with contextflow to add their advanced tools for lung disease detection, quantification and monitoring of disease progression to our AI portfolio.” 

contextflow’s CE and UKCA marked technology, ADVANCE Chest CT, offers radiologists comprehensive computer-aided detection support for lung cancer, ILD, and COPD patients. The software detects, visualizes and quantifies nodules and lung disease patterns to enhance the speed and quality of radiology reports. Its upcoming malignancy scoring feature has been shown to not only detect lung cancer sooner but also to reduce both false positives and false negatives (*Adams, Scott J et al., JACR September 2022). 

As contextflow’s Chief Commercial Officer Marcel Wassink puts it, “Successful implementation of lung cancer screening programs will require the use of assistive AI to help with earlier detection and manage the workloads. We also understand that lung cancer is only one of many findings relevant to the patient’s wellbeing, and thus we are proud to offer comprehensive support for chest CT that goes beyond cancer to include ILD, COPD, and in the near future, incidental pulmonary embolism. Our partnership with Blackford will accelerate the adoption of this much-needed AI, increasing its accessibility to radiologists and patients alike.”

About Blackford 

Blackford are pioneers in the radiology AI space, with over a decade of experience working in partnership with leading hospitals and ground-breaking technology providers. We operate as a strategic AI partner, providing access to a tried-and-tested core platform, tailored services, and a portfolio of 100+ applications to help healthcare providers unlock the value of AI and improve patient outcomes. 

Our collaboration and recent arms-length acquisition by Bayer ensures that our customers and partners have the support and long-term security needed to underpin successful AI strategies. 

To learn more about Blackford’s tailored approach to AI solutions visit www.blackfordanalysis.com.  

About contextflow 

contextflow is a spin-off of the Medical University of Vienna (MUW) and European research project KHRESMOI, supported by the Technical University of Vienna (TU). Founded by a team of AI and engineering experts in July 2016, the company has a strong interest in bringing state-of-the-art machine learning techniques to the market e.g. improved emphysema detection and lung segmentation. Its computer-aided detection software ADVANCE Chest CT is CE Marked and available for clinical use within Europe under the new MDR. Visit contextflow.com for more information.

Always in the picture thanks to AI

News Press

2023-09-27

Evangelisches Klinikum Niederrhein introduces contextflow ADVANCE Chest CT in the Pulmonology Department

Lung diseases are among the most common as well as most diverse health problems worldwide. They require precise diagnoses and effective treatment strategies. In this context, artificial intelligence (AI) opens up a promising avenue for detecting a wide variety of disease conditions in affected patients as early as possible. Fanar Othman, head physician at the Clinic for Pulmonary and Bronchial Medicine at Johanniter Hospital Oberhausen, has also discovered the possibilities of deep learning-based technology for himself. He uses the CE certified software contextflow ADVANCE Chest CT to ensure that even when there is a lot to do, the pulmonologist no longer misses anything.

As part of the Lower Rhine Evangelical Hospital and Bethesda Hospital network, the department not only cares for around 3,000 patients a year in its own hospital, but also provides consultative care for three other sites in the western Ruhr region, including Dinslaken and Duisburg. As a former stronghold of the coal and steel industry, the region is also known as the “coal pot”. Particularly among the older generation, the doctors still see many patients whose health was severely affected by their work in the former mines, blast furnaces and factories. As a result, a not insignificant proportion of the medical care provided locally is for occupational lung diseases such as pneumoconiosis, silicosis, asbestosis and, unfortunately, the resulting late effects such as cancer and pleural mesothelioma. 

So there is a lot to do for the total of five pulmonologists under the direction of Fanar Othman. “We have a large catchment area and, simply because of the size of our association, we get to see a large number of rare pathologies in addition to the usual clinical findings,” says the chief physician. “In these cases, it can already become a challenge to make the correct diagnosis and initiate appropriate therapy.” In this context, a single disease may be associated with multiple radiological patterns. Precise characterization is often laborious and examiner-dependent.

Quick access to relevant knowledge

Since last year, contextflow’s AI solution has been providing a remedy for this problem. It takes over the sifting and provision of information from CT examinations that are relevant for diagnostics. The recognition software detects even small changes in the lung parenchyma and relates them to specific diseases. For nodules, it can even show progression. The resulting findings report is generated automatically and is available directly in the PACS viewer within a few minutes. In this way, the tool saves the diagnostician from having to work through thousands of image slices every day, and at the same time, prevents anything important from being overlooked. 

Using an AI system in his department is new territory for Fanar Othman. He was made aware of ADVANCE Chest CT by his physician colleague, the head of radiology, Prof. Dr. Jörg Michael Neuerburg, who has already been using the software successfully for some time. “From the beginning, I liked how affable and user-friendly the application was,” Othman recalls. “You have to take care of practically nothing. The findings generated by the AI are prepared in a simple and clearly understandable way, so you can adopt the results without time-consuming cross-checking. There is not enough time for anything else in daily practice. Everything has to be done in a jiffy.”

Progress controls at the push of a button

When the opportunity arose to take part in a product training course initiated by contextflow, the pulmonologist jumped at the chance. During the online training, he discovered that the software can do a lot more that is valuable for his work: “For example, the AI is able to compare different series of images taken at different points in time. This makes it possible to assess the size development of nodules, which is very important for determining further therapeutics.”

In addition to calculating the diameter in a plane, the system also applies 3D volumetric analysis to evaluate the total mass of a pulmonary nodule. The volumetric measurement method is becoming increasingly important because it offers a more accurate assessment of malignancy risk, or tumor grade, compared to linear measurement, and also helps to better monitor response to therapy – especially when it comes to determining tumor doubling time. This refers to the fact that in most malignant lesions, volume increases first, followed by size.

From the pattern of findings to differential diagnosis

The software solution is also used for texture analysis, e.g. for characterizing parenchymal changes such as ground-glass opacities, reticular pattern or honeycombing. In this context, the distribution of the changes in the lung allows decisive conclusions to be drawn about the underlying clinical picture. However, differential diagnosis is a difficult and complex task due to the sheer number of existing lung pathologies. In addition, it is often the small but subtle differences that matter. Even experienced experts sometimes reach their limits here. “Sometimes it’s difficult to decide with subtle changes in the lower lobe: is this an emphysema bullae or honeycombing? The AI can differentiate such structures incredibly well,” Fanar Othman is pleased to report.

What the Oberhausen head physician also likes is that the structural parenchymal changes can be displayed in percentage form with the help of ADVANCE Chest CT: “When a check-up is due, you can’t always tell with the naked eye whether it has improved after therapy or not. If the response is not that great, it’s helpful to know by what percentage it ultimately got better. A lot of patients ask us explicitly about that, too.” So such clear feedback can have a positive effect on doctor-patient communication.

Overall, the expert is very pleased with how AI has been able to reduce the workload in his department over the past year while increasing diagnostic accuracy. He says his team is also enthusiastic and has already asked him – or rather the AI – for advice in one or two tricky cases. Othman is not worried that a machine could one day outstrip him: “I see it as an opportunity – especially in view of the fact that there is a shortage of staff anyway. AI is therefore a helpful support in the diagnostic process that makes a lot of things easier. In the end, it is still us who bring it all together with the laboratory values, clinical data and samples and come to a decision. That remains the fine art and continues to be the physician’s task.”

Stets im Bild dank KI

News Press

2023-09-27

Evangelisches Klinikum Niederrhein führt contextflow ADVANCE Chest CT in der Pneumologie ein

Lungenerkrankungen gehören weltweit zu den am häufigsten auftretenden sowie vielfältigsten Gesundheitsproblemen. Sie erfordern präzise Diagnosen und effektive Behandlungsstrategien. In diesem Zusammenhang eröffnet Künstliche Intelligenz (KI) einen vielversprechenden Weg, um verschiedenste Krankheitsbilder bei betroffenen Patienten so früh wie möglich zu erkennen. Auch Fanar Othman, Chefarzt der Klinik für Lungen- und Bronchialheilkunde am Johanniter Krankenhaus Oberhausen, hat die Möglichkeiten von Deep-Learning-basierter Technologie für sich entdeckt. Im Bereich der computertomographischen Bildgebung nutzt er das CE-zertifizierte KI-Programm contextflow ADVANCE Chest CT. Selbst wenn viel zu tun ist, entgeht dem Pneumologen so nichts mehr.

Als Teil des Verbunds Evangelisches Klinikum Niederrhein und BETHESDA Krankenhaus Duisburg betreut die Abteilung nicht nur jährlich um die 3.000 Patienten im eigenen Haus, sondern übernimmt darüber hinaus noch die konsiliarische Mitbetreuung von drei weiteren Standorten im westlichen Ruhrgebiet, darunter Dinslaken und Duisburg. Als ehemalige Hochburg der Kohle- und Stahlindustrie ist die Region auch als „Kohlenpott“ bekannt. Besonders in der älteren Generation sehen die Ärzte bis heute viele Patienten, denen ihre Arbeit in den früheren Bergwerken, Hochöfen und Fabriken massiv auf die Gesundheit geschlagen ist. Daher entfällt ein nicht unwesentlicher Teil der medizinischen Versorgung vor Ort auf berufsbedingte Lungenerkrankungen wie Staublunge (Pneumokoniose), Silikosen, Asbestosen und leider auch die daraus resultierenden Spätfolgen wie Krebs und Pleuramesotheliome. 

Viel zu tun also für die insgesamt neun Ärzte unter der Leitung von Fanar Othman. „Wir haben ein großes Einzugsgebiet und bekommen allein aufgrund der Größe unseres Verbundes neben den gängigen Krankheitsbildern auch eine Vielzahl seltener Pathologien zu Gesicht, die nicht so alltäglich sind“, so der Chefarzt. „In diesen Fällen kann es schon zur Herausforderung werden, die richtige Diagnose zu stellen und eine entsprechende Therapie einzuleiten.“ Dabei kann eine einzelne Erkrankung mit mehreren radiologischen Mustern verbunden sein. Eine genaue Charakterisierung ist oft mühsam und untersucherabhängig.

Schneller Zugriff auf relevantes Wissen

Seit letztem Jahr schafft die KI-Lösung von contextflow Abhilfe bei diesem Problem. Sie übernimmt das Sichten und Bereitstellen von für die Diagnostik relevanten Informationen aus CT-Untersuchungen. Dabei spürt die Erkennungssoftware selbst kleine Veränderungen im Lungenparenchym auf und stellt sie in Zusammenhang mit bestimmten Erkrankungen und deren Verlauf. Der daraus resultierende Befundbericht wird automatisch generiert und steht innerhalb weniger Minuten direkt im PACS-Viewer zur Verfügung. Auf diese Weise erspart das Tool dem Befunder, sich täglich durch Tausende von Schichtbildaufnahmen zu arbeiten und verhindert gleichzeitig, dass wichtige Erkenntnisse übersehen werden. 

Der Einsatz eines KI-Systems in seiner Abteilung ist Neuland für Fanar Othman. Aufmerksam gemacht wurde er auf ADVANCE Chest CT von seinem Arztkollegen, dem Chefarzt der Radiologie, Prof. Dr. Jörg Michael Neuerburg, der die Software bereits seit längerer Zeit erfolgreich nutzt. „Mir gefiel von Anfang an, wie umgänglich und benutzerfreundlich die Anwendung ist“, erinnert sich Othman. „Man muss sich praktisch um nichts kümmern. Die von der KI erstellten Befunde sind einfach und klar verständlich aufbereitet, sodass man die Ergebnisse ohne aufwendige Gegenprüfung übernehmen kann. Für alles andere bleibt in der täglichen Praxis auch gar nicht die Zeit. Da muss alles zack, zack gehen.“

Verlaufskontrollen auf Knopfdruck

Als sich die Gelegenheit bot, an einer von contextflow initiierten Produktschulung teilzunehmen, zögerte der Pneumologe nicht lang und ergriff die Chance. Während des Onlinetrainings stellte er fest, dass die Software noch einiges mehr kann, was für seine Arbeit von Wert ist: „Zum Beispiel ist die KI in der Lage, unterschiedliche Serien von Aufnahmen, die zu verschiedenen Zeitpunkten gemacht wurden, miteinander zu vergleichen. Dies ermöglicht es, die Größenentwicklung von Rundherden zu beurteilen, was sehr wichtig für das weitere therapeutische Vorgehen ist.“

Neben der Berechnung des Durchmessers in einer Ebene wendet das System auch die 3D-Volumenanalyse an, um die Gesamtmasse einer Lungenläsion zu bewerten. Die volumetrische Messmethode gewinnt zunehmend an Bedeutung, da sie im Vergleich zur linearen Messung eine genauere Einschätzung des Malignitätsrisikos bzw. des Tumorgrads bietet und außerdem dabei hilft, die Reaktion auf eine Therapie besser zu überwachen – insbesondere, wenn es darum geht, die Tumorverdopplungszeit festzustellen. Damit ist gemeint, dass bei den meisten bösartigen Läsionen zuerst das Volumen zunimmt, dann die Größe.

Vom Befundmuster zur Differentialdiagnose

Des Weiteren kommt die Softwarelösung auch bei der Texturanalyse zum Einsatz, z. B. bei der Charakterisierung von Parenchymveränderungen wie Milchglastrübungen, netzartigen retikulären Mustern oder Honigwabenbildung. Dabei lässt die Verteilung der Veränderungen in der Lunge entscheidende Rückschlüsse auf das zugrunde liegende Krankheitsbild zu. Dennoch gestaltet sich die Differentialdiagnose allein aufgrund der schieren Masse an existierenden Lungenpathologien als schwierige und komplexe Aufgabe. Hinzukommt, dass es häufig die kleinen, aber feinen Unterschiede sind, auf die es ankommt. Selbst erfahrene Experten stoßen hier teilweise an ihre Grenzen. „Manchmal ist es schwierig, bei subtilen Veränderungen im Unterlappen zu entscheiden: Ist das ein Emphysembullae oder Honigwabenmuster? Solche Strukturen kann die KI unglaublich gut differenzieren“, freut sich Fanar Othman.

Was dem Oberhausener Chefarzt außerdem gefällt, ist, dass sich die strukturellen Parenchymveränderungen mithilfe von ADVANCE Chest CT in prozentualer Form darstellen lassen: „Wenn eine Kontrolluntersuchung ansteht, kann man nicht immer mit bloßem Auge erkennen, ob es nach der Therapie besser geworden ist oder nicht. Wenn das Ansprechen nicht so großartig ausfällt, ist es hilfreich zu wissen, um wie viel Prozent es letztendlich besser geworden ist. Viele Patienten fragen uns auch explizit danach.“ So ein eindeutiges Feedback kann sich also positiv auf die Arzt-Patienten-Kommunikation auswirken.

Insgesamt zeigt sich der Experte sehr zufrieden damit, wie die KI die Arbeitslast in seiner Abteilung im letzten Jahr reduzieren konnte und gleichzeitig die diagnostische Genauigkeit erhöht hat. Auch sein Team sei begeistert und habe ihn – oder besser gesagt die KI – in dem ein oder anderen kniffeligen Fall schon um Rat gefragt. Dass eine Maschine ihm eines Tages den Rang ablaufen könnte, darüber macht sich Othman keine Sorgen: „Ich empfinde es als Chance – gerade auch vor dem Hintergrund, dass ohnehin Personalmangel herrscht. Die KI stellt daher eine hilfreiche Unterstützung bei der Befundung dar, die vieles erleichtert. Am Ende sind es immer noch wir, die das Ganze mit den Laborwerten, klinischen Daten und Proben zusammenführen und zu einer Entscheidung kommen. Das bleibt die hohe Kunst und weiterhin Aufgabe des Arztes.“