Siemens Healthineers New AI-Rad Companion Solution Gets Saudi FDA Approval

The demand for radiology imaging is increasing, resulting in patients waiting longer for their radiology procedures to be reported. Siemens Healthineers has responded to this by releasing the AI post-processing and reporting solution, AI-Rad Companion.
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Radiology, imaging, artificial intelligence, Siemens

Credit: AI-Rad Companion chest computed tomography 

The use of X-rays, computed tomography (CT) scanners and magnetic resonance imaging (MRI) is increasing rapidly due to technology improvements, new diagnostics guidelines, patient-generated demand, a rising prevalence of certain diseases and demographic shifts. While advances in resolution give physicians better insight into the human body and disease features, it also generates a vast amount of data that must be analysed and processed.

To fully leverage new possibilities for enhancing clinical outcomes, technology must address major healthcare challenges, including shortages of radiologists. In a report for example published in August 2020, the Royal College of Radiologists estimates current radiologist shortages in the UK at 27-37 per cent. This problem has also been recognised in the Kingdom of Saudi Arabia where the demand for healthcare is rising, driven by population growth, ageing and the burden of non-communicable diseases.

The COVID-19 pandemic has further exposed the bottlenecks in imaging diagnostics and the need for improving data management in hospitals.

AI-based software assistant for computed tomography

The Siemens Healthineers AI-Rad Companion – the family of AI-powered imaging solutions – helps to reduce the burden of repetitive tasks and can increase diagnostic precision when interpreting medical images, by providing automatic post-processing of imaging datasets through AI-powered algorithms.

The system has recently received The Saudi Food and Drug Authority (SFDA) approval, which confirms its high clinical quality and safety. The automation of routine workflows allows radiologists to focus on more critical issues. With its deep learning algorithms, AI-Rad Companion highlights abnormalities, segments anatomies, and compares results to reference values.

“We want to empower our customers with our latest innovations and we do believe that AI-Rad Companion will help our customers increase the quality of image reading, reduce variability and make the process more precise,” says Michel Atallah, CEO Siemens Healthcare Saudi Arabia.

High-quality outcomes in diagnostic decision-making

Secure processing of the imaging scans augments radiologists with new diagnostics capabilities. One example is Foch Hospital (France). “It is extremely helpful,” says Prof. Philippe Grenier, who is leading the implementation and development of AI at Foch Hospital (France). The Siemens Healthineers AI-Rad Companion facilitated the adoption of new imaging standards in oncology and cardiology, for example, the quantification score to measure the risk of coronary events among patients with cardiovascular diseases.

AI-Rad Companion is a modular solution supporting multi-modality and multi-organs. It performs automatic segmentation of the different brain areas, including an individual volumetric analysis. Regarding chest CT, the system detects and highlights lung nodules. Automatically after segmentation of the lung lesions, the volume, maximum 3D diameter and tumour burden are calculated.  By automatically analysing and highlighting abnormalities and incorporating the results in the PACS workflow, hospitals using Siemens Healthineers’ AI solution can better manage the high volume of Chest X-Ray exams. Another module, AI-Rad Companion Organs RT, automatically contours the organs at risk with the support of deep learning algorithms. It may reduce unwarranted variations with high-quality contours that approach the level of consensus-based contours.

Learn how to integrate AI into the radiology environment

For more details on the Siemens Healthineers AI-Rad Companion, please click here or visit the Siemens Healthineer booth at HIMSS & Health 2.0 Middle East Digital Health Conference & Exhibition (29 November – 2 December).

Topics: 
Imaging

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