AI-Pathway Companion Prostate Cancer from Siemens Healthineers approved for use in Europe as medical device

• Digital companion aggregates, correlates, and visualizes patient-specific information at all stages in the clinical pathway for prostate cancer.
  
• Supports multidisciplinary teams in their decision-making.
  
• Consideration of full patient context¹ facilitates individual treatment options.

AI-Pathway Companion Prostate Cancer², a digital companion from Siemens Healthineers to support clinical decision-making, has recently received the CE mark for use in the clinical pathway of prostate cancer, the second most common cancer (after lung cancer) affecting males worldwide.³ The conformity mark confirms that the application AI-Pathway Companion Prostate Cancer is CE-compliant in accordance with Directive 93/42/EEC and can therefore be marketed in the EU as a medical device.

The AI-Pathway Companion product suite uses Artificial Intelligence, including Natural Language Processing⁴, to bring together data on a patient’s disease and treatment status and presents it via an intuitive graphical user interface. AI-Pathway Companion Prostate Cancer also draws the physicians’ attention to the appropriate treatment recommendations¹ from the prostate cancer guidelines of the European Association of Urology and the National Comprehensive Cancer Network⁵ to suit the patient’s current treatment status.

“The AI-Pathway Companion helps multidisciplinary teams in particular with decision-making for diagnosis and treatment along the entire clinical pathway on the principles of evidence-based medicine. That means we can assist healthcare providers to put the individual patient at the center of the treatment process. We are very excited about AI-Pathway Companion as one of the first elements in our strategy of expanding to clinical decision making based on integrated diagnostics,” says André Hartung, head of Diagnostic Imaging at Siemens Healthineers.

Decision-making for treatment and the follow-up process for prostate cancer is extremely complex and time consuming, since many individual patient parameters must be considered. This includes the stage at which the disease was discovered, whether it is a first diagnosis, whether various treatments have already been applied, and whether the tumor has reappeared following an initial treatment success. Lab results, like the PSA (prostate-specific antigen) value, pathology findings from a prostate punch biopsy, or the PI-RADS (Prostate Imaging – Reporting and Data System) score, which identifies the probability of a clinically significant carcinoma, and the Gleason score, which classifies the aggressiveness of a prostate tumor, are other examples of criteria used by physicians to help determine the next stages of examination and treatment. In the process, the physicians use evidence-based international medical guidelines which generally may run to well over 100 pages and often recommend appropriate, scientifically justified, and up-to-date processes for diagnostics and treatment; these also include the prostate cancer guidelines of the European Association of Urology⁶ and the National Comprehensive Cancer Network⁷. It is not hard to see that the mass of data contained in both the results and guidelines can pose a major challenge to decision-making.

AI-Pathway Companion Prostate Cancer helps match the data available for the individual patient with the guidelines to identify the recommended treatment approach and facilitate the appropriate disease management. The digital companion searches the patient record and other sources, like the hospital information system or PACS (Picture Archiving and Communication System), and compiles the longitudinal data for the cancer patient in question.⁴ Natural Language Processing is used to extract and compile data relevant to the decision-making process from the radiology, pathology, genetics, and lab results, and present it via an intuitive user interface. The PI-RADS score is also automatically correlated with the Gleason score to help physicians estimate the aggressiveness of the tumor and determine the course of the disease on that basis. Algorithms search through the prostate cancer guideline for recommendations that suit the patient’s individual disease status based on his or her current available data. The algorithms automatically show where the patient is in the pathway and recommend next options, including any missing information that is required.⁸

Based on this data, AI-Pathway Companion Prostate Cancer displays the patient’s current clinical situation and offers guideline-based recommendations for further steps to provide treatment in accordance with the medical evidence. The digital companion can thus help multidisciplinary teams at tumor boards, for example, to make optimized decisions throughout the treatment process.

“Our multidisciplinary team (MDT) discussions can greatly vary in time. If a clinical decision support solution could integrate and display the patient context in a smart and standardized way, while providing evidence-based diagnosis and therapy recommendations, it could help make the discussions shorter and save time for all the MDT participants,” says Prof Helge Seifert, MD Chairman, Clinic for Urology at University Hospital Basel.⁹

„I spend a lot of time entering patient information manually in our MDT solution. If this information could be integrated automatically and in a smart and standardized way, it would save us a lot of time and let us focus on what's important: the patient,“ says Christian Wetterauer, MD Senior Urologist at University Hospital Basel.¹⁰

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