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- What is a digital patient twin?
What is a digital patient twin?
In healthcare, the digital patient twin is being researched and developed for specific organs like the heart and liver. But what, in fact, is a digital patient twin? Let's look into what this could be, and which applications contribute to its concept.
There are several concepts of digital twins currently being used in healthcare. One central approach is digital patient twins: With their help, doctors are increasingly able to better predict how a person ages, when illnesses appear, what course they take, and what the most effective treatment is.
- <p>With the help of artificial intelligence, routine radiology processes can be fully automated, which may reduce image errors. Body and organ movements could be monitored with additional sensors, such as <a href="https://www.siemens-healthineers.com/magnetic-resonance-imaging/technologies-and-innovations/biomatrix-technology" target="_blank">BioMatrix MR</a> and <a href="https://www.siemens-healthineers.com/computed-tomography/technologies-and-innovations/fast-integrated-workflow" target="_blank">Fast3D Cam CT</a>, and evaluated with algorithms. Using this data, the computed tomography image may be (semi-)automatically planned to ensure optimal patient positions for image acquisition. This is particularly helpful for supporting a reliable diagnosis of clinicians. </p><p><br></p><p>Artificial intelligence also supports radiologists in evaluating large amounts of image data. Algorithms make it possible to systematize large numbers of image cases. Anatomies are automatically labeled, and the results are compared with reference values to highlight abnormalities (e.g., <a href="https://www.siemens-healthineers.com/en-us/medical-imaging-it" target="_blank">Syngo Carbon</a><sup>2</sup>). This allows the automatic extraction of “imaging biomarkers” and, for example, enables doctors to distinguish between benign and malignant structures. Artificial intelligence can routinely detect radiological abnormalities that are sometimes difficult or even impossible to see with the human eye and provide valuable assistance.</p>
- <p>Existing digital patient twin technology can also support doctors in preparing radiotherapies. With the help of artificial intelligence, tumor contrasts, borders, and volumes as well as tissue changes can be determined automatically. This saves up to one hour per patient when contouring the organs at risk. In fact, the best AI-based contouring results use specially derived raw data from the CT system that is not optimized for diagnoses by the human eye (e.g., <a href="https://www.siemens-healthineers.com/en-us/computed-tomography/technologies-and-innovations/admire" target="_blank">ADMIRE CT</a>, <a href="https://www.siemens-healthineers.com/magnetic-resonance-imaging/technologies-and-innovations/deep-resolve" target="_blank">MR Deep Resolve</a>). </p><p><br></p><p>Data models can be used to calculate whether and how patients will respond to radiation treatments. This allows the duration, dose, and frequency of the individual radiation treatments to be optimized, making the treatment of tumors even more efficient and effective. In a clinical study published in the journal Lancet in 2019, these advantages were demonstrated for the radiotherapy of lung cancer. The study showed that this method achieves a result that is up to 45 percent better than standard radiation treatments (Lou et. al. 2019). </p><p><br></p><p>AI and robot-assisted neuro interventions, based on digital patient twins, open new dimensions in the field of cerebrovascular therapy (e.g., <a href="https://www.siemens-healthineers.com/angio/artis-interventional-angiography-systems/artis-icono" target="_blank">Artis icono</a> and <a href="https://www.siemens-healthineers.com/endovascular-robotics" target="_blank">Corindus robots</a>). For the emergency treatment of strokes in the future, a catheter-based therapy such as a thrombectomy or coiling could be performed remotely to minimize the time between the first signs of the stroke and the therapeutic intervention.</p>
- <p>The translation and visualization of data into understandable findings, using artificial intelligence, is an important capability of digital patient twins. With cinematic rendering, a patient’s state of health can be presented realistically, and the treatment can be better prepared and carried out with the help of 3D organ models. </p><p><br></p><p>Thanks to virtual reality (VR) and augmented reality (AR), available clinical data can be interactively viewed, used, and edited. Surgeons already work with 3D glasses. Researchers have found that CT images created with cinematic rendering ensure a faster and more accurate understanding of a patient’s anatomy. With this method, surgeons were able to complete their work with greater accuracy and in roughly half the time. It is expected that this technique will also benefit surgical planning and related decision-making.</p>
The added value of digital patient twins
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Syngo Carbon consists of several products which are (medical) devices in their own right. Some products are under development and not commercially available. Future availability cannot be ensured.