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RSNA 2018 in Chicago: Halle Süd, Stand 4136
Nicht zur Veröffentlichung in den USA
Siemens Healthineers präsentiert auf dem Kongress der Radiologischen Gesellschaft Nordamerikas (RSNA 2018) in Chicago, USA, erstmalig einen intelligenten Software-Assistenten für die Radiologie, der Organe und eventuell krankheitsrelevante Veränderungen erkennen kann. Der AI-Rad Companion Chest CT* ist eine auf künstlicher Intelligenz (KI) basierende Software für die Computertomografie (CT). Die zugrundeliegenden Algorithmen wurden in Wissenschaftsteams bei Siemens Healthineers anhand von umfangreichen klinischen Datensätzen trainiert. Die Software kann auf CT-Aufnahmen des Thorax (Brustkorb) Strukturen voneinander unterscheiden, einzeln herausstellen und etwaige Auffälligkeiten kennzeichnen und messen. Dies gilt für Organe wie Herz oder Lunge, die Aorta sowie Wirbelkörper. Die Ergebnisse werden automatisch in einem Report aufbereitet.
AI-Rad Companion Chest CT ist die erste Anwendung auf der neuen Plattform AI-Rad Companion. Sie soll Radiologen helfen, die Interpretation von CT-Bildern schneller und präziser durchzuführen sowie die Dokumentation der Befunde zu beschleunigen. Siemens Healthineers, ein führendes Unternehmen bei Digitalisierung und KI, wird weitere intelligente Assistenten basierend auf AI-Rad Companion anbieten, um Anbieter im Gesundheitswesen beim Wandel hin zu einer wertebasierten Gesundheitsversorgung zu unterstützen.
„Mit dem AI-Rad Companion Chest CT steht ein Tool zur Verfügung, das tatsächlich Produktivität und Qualität in der radiologischen Diagnostik gleichzeitig erhöhen kann“, sagt André Hartung, Leiter Computed Tomography bei Siemens Healthineers. „Durch den intelligenten Assistenten erhalten Ärzte auch Hinweise auf möglicherweise krankheitsrelevante Veränderungen, die gar nicht im Fokus der ursprünglichen Untersuchung standen und somit nicht erkannt worden wären. Damit können sie – natürlich unter zusätzlicher Beachtung der klinischen Symptome des Patienten – zügiger zu einer präziseren und umfangreicheren Diagnose kommen.“
„Bereits seit 20 Jahren ist Siemens Healthineers ein Pionier in der Entwicklung von Anwendungen, die auf künstlicher Intelligenz basieren. Mit intelligenten Digital Companions wollen wir Gesundheitsversorgern unter anderem helfen, die Herausforderungen von steigenden Patientenzahlen bei gleichzeitiger Personalknappheit zu bewältigen“, sagt Yan Beynon, Leiter Digital Services bei Siemens Healthineers. „Künstliche Intelligenz wird den Radiologen nicht ersetzen, sondern ihm Routinetätigkeiten abnehmen, um Effizienz und Qualität in der der radiologischen Diagnostik zu erhöhen.“
In vielen Ländern steigt die Anzahl radiologischer Untersuchungen stetig, die Expertenzahl wächst jedoch nicht im selben Maße. In der Folge muss ein Radiologe nicht selten bis zu 100 Untersuchungen am Tag durchführen. Das bedeutet: Im Durchschnitt interpretiert ein Radiologe alle drei bis vier Sekunden ein klinisches Bild, und das täglich acht Stunden und mehr.1 Die CT-Thorax-Untersuchung ist ein im klinischen Alltag häufig eingesetztes Verfahren. Für Radiologen bedeutet das: Mehr Untersuchungen in nur begrenzter Zeit, und das typischerweise bei geringem Vergütungssatz.
Die radiologische Befundung des Brustkorbs als Multiorganbereich ist auch deshalb eine Herausforderung, weil viele unterschiedliche Informationen auf den Bildern vorhanden sind. Der Radiologe begutachtet die Bilder vor allem im Hinblick auf die vorliegende primäre Indikation, also das mögliche Krankheitsbild, aufgrund dessen die CT-Aufnahme veranlasst wurde. Die Algorithmen des AI-Rad Companion Chest CT berücksichtigen hingegen alle Bereiche des Brustkorbs gleichermaßen und können Normabweichungen auch in Regionen kennzeichnen, die der Arzt möglicherweise nicht so intensiv beachten würde. Das Ergebnis der KI-gestützten Analyse des Software-Assistenten ist ein standardisierter, reproduzierbarer und quantitativer Bericht.
Aktuell unterstützt der AI-Rad Companion Chest CT unterschiedliche Anwendungsbereiche, wie die Erkennung von Lungenläsionen und die Ermittlung des kardiovaskulären Risikos basierend auf einer Analyse der Koronararterien-Verkalkung auf nicht-EKG-getriggerten CT-Aufnahmen. In Zusammenarbeit mit der Medical University of South Carolina (MUSC) wurde außerdem nachgewiesen, dass sich die Aorta mit dem AI-Rad Companion Chest CT vermessen lässt – ein wichtiger Parameter für potentielle Aneurysmen. Die Ergebnisse hierzu werden auf dem RSNA 2018 präsentiert.2 Außerdem betrachtet der AI-Rad Companion Chest CT die Wirbelsäule im Brustraum des Patienten. Die einzelnen Wirbelkörper werden detektiert, segmentiert und hinsichtlich Knochendichte und möglicher Frakturen analysiert. Dies kann die Früherkennung osteoporotischer Veränderungen unterstützen.
Der AI-Rad Companion Chest CT ist cloudbasiert und nutzt die zertifizierte, sichere und sowohl HIPAA (Health Information Portability and Accountability Act, USA) wie EU-DSGVO (Datenschutz-Grundverordnung)-konforme Infrastruktur von teamplay**. Die Software integriert sich nahtlos in den existierenden klinischen Workflow und entspricht den DICOM (Digital Imaging and Communications in Medicine)-Standards. Die Bilder und alle unterstützenden Informationen können im PACS (Picture Archiving and Communication System) automatisch gemäß individueller Anforderungen des Radiologen verfügbar gemacht werden. Diese Lösung ist besonders bei zeitaufwändigen, grundlegenden und sich stets wiederholenden Aufgaben hilfreich.
Der AI-Rad Companion Chest CT ist herstellerunabhängig, kann Bilddaten aller CT-Hersteller auswerten und soll ab Frühjahr 2019 in verschiedenen Märkten, darunter USA und Europa verfügbar sein.
Siemens Healthineers als führendes Unternehmen in Digitalisierung und künstlicher Intelligenz
Künstliche Intelligenz eröffnet dank exponentiell ansteigender Rechenleistung, enormer Speicherkapazität und zunehmender Vernetzung ungeahnte Möglichkeiten. Siemens Healthineers nutzt künstliche Intelligenz, um Gesundheitsversorgern weltweit dabei zu helfen, im Sinne einer Präzisionsmedizin individuelle Prävention und Therapie durch präzise Diagnosen zu ermöglichen. Mit mehr als 500 Patenten im Bereich des maschinellen Lernens, 100 Grundpatenten im Bereich Deep Learning und über 40 KI-basierten Anwendungen hält Siemens Healthineers eine führende Position beim Einsatz der künstlichen Intelligenz in Bildgebung und Diagnostik. Als Datenbasis stehen dem Unternehmen derzeit bereits über 300 Millionen kuratierte klinische Bilder, Reports und Daten zur Verfügung. Weitere Erkenntnisse kommen regelmäßig über die weltweit 4.400 klinischen Kooperationen hinzu. Auf einem 16-PetaFLOPS TensorCore Supercomputer im Bundesstaat New Jersey, USA führen die Wissenschaftsteams von Siemens Healthineers täglich rund 400 KI-Experimente durch.
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(pdf, 175.70 KB)Technology, Trade and Local Media
* AI-Rad Companion Chest CT befindet sich in der Entwicklungsphase und ist deshalb noch nicht käuflich zu erwerben. Die zukünftige Verfügbarkeit kann nicht garantiert werden.
** teamplay ist in einigen Ländern noch nicht käuflich zu erwerben. Aufgrund von medizinproduktrechtlichen Vorgaben kann die zukünftige Verfügbarkeit nicht zugesagt werden. Detaillierte Informationen sind bei der jeweiligen Siemens-Organisation vor Ort erhältlich.
McDonald RJ, Schwartz KM, Eckel LJ, et al. The effects of changes in utilization and technological advancements of cross-sectional imaging on radiologist workload. Acad Radiol. 2015; 22(9):1191–8.
Branch CR, Charleston SC, Rapaka S, et al. Artificial Intelligence Based Aortic Diameter Quantification on Routine Unenhanced Chest CT. Scientific Session at RSNA 2018. Chicago, USA. Wednesday, Nov 28, 2018.
Reference Number: PR-20181125043SHS