Digital twins in cancer care

Summary

The podcast 'Healthcare Perspectives' by Siemens Healthineers explores the transformative impact of digital twins on cancer care. It discusses how early detection through non-invasive and cost-effective screening can improve prognosis. The episode delves into the potential of digital twins to offer personalized treatment strategies, enhance precision in radiotherapy, and facilitate better decision-making in clinical practice. The technology promises to optimize healthcare systems, improve patient outcomes, and pave the way for a more personalized approach to oncology.

Takeaways

• 🌐 Digital twins have the potential to revolutionize cancer care by providing a more personalized and precise approach to treatment.
• 🔍 Early detection of cancer is crucial, and digital twins can enable earlier and more effective screening methods, improving prognosis and outcomes.
• 📉 The integration of data from digital twins can help decrease the burden on healthcare systems by identifying diseases early and preventing more costly interventions later.
• 🧬 Digital twins can incorporate a wide range of data, including diagnostic imaging, genetic, and molecular information, leading to a more accurate patient representation.
• 💡 The use of digital twins allows clinicians to explore various treatment options and increase precision in treatment strategies, tailoring them to individual patient needs.
• 🛠️ Radiotherapy can benefit from digital twins by providing more precise tumor location data, which is essential for effective treatment planning and minimizing side effects.
• 🩺 Personalized medicine is enhanced by digital twins, as they enable doctors to move beyond population-based guidelines to individualized treatment plans for each patient.
• 🧐 Predictive capabilities of digital twins can help in identifying patient response to treatments before they are administered, potentially avoiding ineffective therapies and associated side effects.
• 🛑 Digital twins offer a 'sandbox' for clinicians to test different treatment protocols and predict outcomes, allowing for the selection of the most efficient treatment for a given patient.
• ✂️ Surgical planning can be aided by digital twins, providing surgeons with a detailed digital representation of the patient's anatomy to simulate and plan surgeries more effectively.
• 🔄 Follow-up care and management of cancer recurrence can be improved with digital twins, allowing for more informed decisions on re-irradiation and other treatments.

Q & A

What is the ideal characteristic of a cancer screening method according to the transcript?

The ideal cancer screening method should be quick, non-invasive, not expensive, and effective, allowing for easy performance everywhere in the world for early disease prediction.

Why is early detection of breast cancer tumors significant according to the guest Christian?

Early detection of breast cancer tumors is significant because the smaller the tumor size when detected, the better the prognosis, leading to more effective treatment outcomes.

How does Christian describe the impact of early disease detection on the healthcare system?

Christian suggests that early detection can ease the burden on the healthcare system by preventing diseases like breast cancer that can be avoided or detected early, which is crucial given the financial constraints many health systems face.

What role do digital twins play in improving cancer care according to the discussion?

Digital twins can decrease the amount of care necessary, improve outcomes, and free up more time, energy, and money for developments in technology, systems, methods, and diagnostics in oncology.

How can digital twins contribute to more accurate cancer diagnosis?

Digital twins enable a higher level of data integration, allowing doctors to explore various treatment options and increase precision in treatment by combining individual patient data with big data analysis from thousands of similar cases.

What is the potential of digital twins in terms of personalized therapy for cancer patients?

Digital twins offer the potential for more personalized therapy by providing detailed, patient-specific information that can help refine decision-making and select the best treatment for an individual patient at a particular moment in time.

How could digital twins assist in radiotherapy treatment planning?

Digital twins could allow for the collection and analysis of more precise data regarding tumor location, helping to increase tumor control while reducing toxicity by delivering high doses to the tumor while sparing surrounding healthy tissue.

What is the potential benefit of using a digital twin for predicting patient response to treatment?

A digital twin can predict whether a patient would respond to a treatment before it happens, using the entire clinical and genetic information about the patient, which can help in selecting more efficient therapy options and avoiding ineffective treatments.

How can digital twins assist in surgical planning for liver cancer?

A digital twin can provide a digital representation of the liver, allowing surgeons to evaluate tumor disposition related to healthy tissue, simulate the resection virtually, and compute the remaining liver function to decide if surgery is safe.

What is the potential impact of digital twins on patient recovery and quality of life?

By avoiding ineffective therapies and enabling less invasive treatment options, digital twins can contribute to faster patient recoveries, shorter hospital stays, and an improved quality of life.

What does Christian suggest about the future potential of digital twins in managing cancer recurrence?

Christian suggests that digital twins could estimate the risks of side effects or the possibility of re-irradiation before trying it on the patient, providing more precise predictions for patients and aiding in the development of more transparent and precise therapy strategies.

Outlines

00:00

🚀 Introduction to Digital Twins in Cancer Care

The first paragraph introduces the topic of digital twins in the context of cancer care, posing questions about their potential impact and current role in improving patient outcomes. It emphasizes the importance of early, non-invasive, and effective screening methods to detect diseases like cancer at an early stage, which can lead to better treatment results and reduce the burden on healthcare systems.

06:25

🌟 Early Detection and the Role of Mammography

In this paragraph, the focus is on the significance of early detection in breast cancer treatment. It discusses the benefits of mammography screening in detecting small tumors that might otherwise go unnoticed, leading to better prognoses. The paragraph also touches on the economic implications of early cancer detection and prevention, highlighting the need for efficient healthcare strategies to manage the financial strain on health systems.

11:26

🔬 The Power of Data Integration with Digital Twins

This section delves into the concept of digital twins, emphasizing their potential in integrating vast amounts of clinical data to enhance diagnostic accuracy and treatment precision. It presents a case study of a breast cancer patient, illustrating how digital twins can combine imaging data with big data analysis to provide actionable insights. The paragraph also discusses the benefits of this data integration for clinicians in making more informed decisions.

16:29

🛠️ Personalized Therapy and the Evolution of Digital Twins

The fourth paragraph explores the idea of personalized therapy made possible through digital twins. It discusses the evolution of digital twins, which can be enriched with new medical and personal information over time, providing a more accurate representation of individual patients. The potential for more precise radiotherapy planning and the avoidance of ineffective treatments are highlighted, emphasizing the importance of personalized medicine in optimizing patient care.

21:29

🛑 Surgical Planning and Follow-up with Digital Twins

This paragraph discusses the application of digital twins in surgical planning, particularly for liver cancer, and their role in follow-up care. It describes how surgeons can use digital twins to evaluate tumor disposition and simulate resection, as well as predict the effectiveness of interventions and potential side effects. The paragraph also touches on the potential of digital twins in managing recurrence and re-irradiation, offering a more transparent and precise approach to cancer treatment.

🌐 Transforming Cancer Care with Digital Twins

The final paragraph wraps up the discussion by highlighting the transformative potential of digital twins in cancer care. It speaks to the ability of digital twins to provide a sandbox for exploring different treatment scenarios and their outcomes, leading to optimized care for patients and healthcare teams. The paragraph also mentions the importance of continued exploration and development in this field, as well as the potential for digital twins to revolutionize the way cancer is treated and managed.

Keywords

💡Digital Twins

Digital Twins refer to virtual replicas of physical entities that can simulate real-world conditions and processes. In the context of healthcare, particularly oncology, they are used to create detailed models of patients that can help in early detection, diagnosis, and treatment planning. The script discusses how digital twins can impact cancer care by providing a more personalized and precise approach to treatment, using the example of a 46-year-old breast cancer patient where various imaging data were collected and integrated for a more accurate representation.

💡Mammography

Mammography is an imaging technique used to screen for breast cancer by using low-energy X-rays to examine the breast tissue. The script highlights the effectiveness of mammography in detecting tumors as small as a few millimeters, which is significantly smaller than the size of tumors typically felt by patients or detected by a gynecologist, emphasizing the importance of early detection for better prognosis.

💡Early Detection

Early Detection is the identification of diseases, such as cancer, at an early stage before they become more advanced and potentially more difficult to treat. The script emphasizes the importance of early detection for improving treatment outcomes and mentions that with technologies like mammography, tumors can be detected much earlier, leading to better prognoses.

💡Precision Medicine

Precision Medicine is an approach to patient care that allows doctors to select treatments that are most likely to help patients based on a genetic understanding of their disease. The script discusses how digital twins can contribute to precision medicine by integrating vast amounts of clinical data to support clinicians in decision-making, tailoring treatment to individual patient needs rather than relying on population-based guidelines.

💡Health Economics

Health Economics is the branch of economics that deals with issues related to efficiency, effectiveness, value, and behavior in the production and consumption of health and healthcare. The script mentions the burden on health economic systems and the importance of early disease detection to prevent further strain due to lack of financial power, illustrating the financial implications of healthcare decisions.

💡Radiotherapy

Radiotherapy, also known as radiation therapy, is a medical treatment that uses ionizing radiation to kill cancer cells and shrink tumors. The script discusses the potential of digital twins in radiotherapy to increase tumor control while reducing toxicity by delivering high doses to the tumor while sparing healthy tissue, highlighting the importance of precise data for effective treatment planning.

💡Stereotactic Body Radiation Therapy (SBRT)

Stereotactic Body Radiation Therapy (SBRT) is a type of radiotherapy that delivers high doses of radiation to a tumor in a precise manner. The script provides an example of SBRT as a standard treatment for lung cancer, noting that some patients respond well to it, while others do not. The potential of digital twins to predict patient response to SBRT before treatment could help in selecting more effective therapy options.

💡Personalized Therapy

Personalized Therapy is a medical approach that tailors treatment to the individual characteristics of each patient, taking into account genetic, environmental, and lifestyle factors. The script discusses the incredible potential of digital twins for personalized therapy, allowing doctors to perform multiple treatment scenarios on the twin and predict outcomes before physically treating the patient, thus optimizing treatment plans.

💡Data Integration

Data Integration is the process of combining data from different sources into a single, unified view. In the script, data integration is highlighted as a key feature of digital twins, enabling the combination of imaging, genetic, and molecular information to create a more accurate representation of patients and support clinicians in making more informed decisions.

💡Quality of Life

Quality of Life refers to an individual's overall well-being and satisfaction with various aspects of their life, including health, relationships, and environment. The script suggests that by avoiding ineffective therapies and enabling less invasive treatment options, digital twins could lead to faster recoveries, shorter hospital stays, and ultimately, an improved quality of life for cancer patients.

💡Re-irradiation

Re-irradiation is the process of administering radiation therapy to a tumor that has recurred after a previous course of radiation. The script discusses the potential of digital twins in estimating the risks and possibilities of re-irradiation, allowing doctors to make more informed decisions and potentially offering patients a second chance at longer survival in case of relapse.

Highlights

The ideal cancer screening should be quick, non-invasive, affordable, and effective for early detection worldwide.

Mammography can detect breast tumors as small as a few millimeters, significantly earlier than when felt by touch.

Early tumor detection improves prognosis and is crucial for easing the burden on healthcare systems.

Digital twins have the potential to decrease necessary care and improve outcomes, freeing up resources.

Data integration with digital twins can provide actionable insights, enhancing the precision of treatment strategies.

Digital twins can integrate a vast amount of clinical data, supporting clinicians with decision making in a broader context.

Digital twins offer personalized therapy options, increasing the precision of treatments like radiotherapy.

Personalized information from digital twins allows for treatment plans tailored to individual patient needs rather than population data.

Digital twins could predict patient response to treatments like SBRT for lung cancer, avoiding ineffective therapies.

Surgeons could use digital twins for precise evaluation and simulation of procedures like liver cancer surgery.

Digital twins enable clinicians to test different treatment protocols in advance, selecting the most efficient for each patient.

By simulating treatment responses, digital twins can help physicians understand potential side effects and limit them.

Digital twins can lead to faster patient recoveries, shorter hospital stays, and an improved quality of life.

Digital twins provide a sandbox for experimenting with different treatment scenarios and observing their outcomes.

Digital twins can assist in managing recurrence by estimating risks and possibilities for re-irradiation.

The implementation of digital patient twins could revolutionize precision medicine and transform cancer care.

Digital twin technology may allow medical professionals to observe treatment scenarios before any physical treatment, enhancing patient outcomes.

Transcripts

Welcome to Healthcare Perspectives, a podcast by  Siemens Healthineers about medical breakthroughs  

with the power to improve lives everywhere. Today: How can digital twins impact cancer  

care? Are they already changing the  lives of cancer patients? And what  

does this mean for the future of oncology? In a perfect world the screening, I believe should  

be quick, it should be non-invasive, it should not  be expensive and it should be effective. So that  

we have easy to perform everywhere in the world  early screening tools for everyone everywhere,  

the earlier the disease is predicted the  better the treatment outcome would be.

Christian what is your experience with  screening patients for breast cancer?

In my practice, every day I have a woman who  tells me that her tumor was detected with  

mammography screening. The researchers say that  if a woman is feeling the tumor in the breast,  

the typical average size is about 2.5  centimeters. And if a gynecologist is  

detecting the tumor, it's in average, two  centimeters, a little bit lower. But with  

the mammography, you can detect tumors  with, example, three or four millimeters.

And the earlier a tumor is  detected the better the prognosis.

It's really the best system to  get the data early. Don't wait  

until the tumor’s growing  and the outcome is worse.

For Christian, treating disease  early and effectively is also  

about easing the burden on the healthcare system:

It's a great challenge that we prevent diseases  like breast cancer, that can be avoided or  

detected early. It's important because all the  health economic systems are so burdened, so at the  

edge in the moment because of lack of financial  power, that we have to avoid these diseases.

Earlier detection empowered by digital  twins may decrease the amount of care  

necessary and improve outcomes. As such,  more time, energy, and money is freed up.

We need the money for all the developments  and all the new technology systems and  

methods and diagnostics, what we are talking  about, and this is the only chance we have.

An accurate diagnosis is crucial when creating  a treatment strategy for a cancer patient. With  

digital twins, the level of data-integration  possible could enable doctors to explore a  

variety of options and increase precision in  treatment. Christian shares his experience here:

Take a case for example, there is a breast cancer  patient, 46 years old, breast cancer detected in  

an advanced stage with the lymph nodes. This  situation is typical for about 20,000 patients  

in Germany every year. And then mammography,  MR-mammography, sonography, ultrasound were  

done and the data were collected. The first step  is to get very valid reports about the patients.

The next step is to combine this with big  

data analysis from thousands of  breast cancer patients worldwide.

Compared with the standard of care,  the data integration incorporated  

in digital twins could create  actionable insights, says Chloe:

In the standard clinical practice,  

physicians often read and integrate specific  data from medical reports or medical imaging,  

and from there they derive a diagnosis that is  as robust as possible. And having this in mind,  

digital twins can be viewed as the  next level of data integration,  

where the clinician would have the possibility  to create the statistical view of the data that  

involves a vast amount of clinical data that would  otherwise be impossible for a human to analyze.

And this could support clinicians  with decision making by putting  

each situation into the bigger picture:

These patient’s clinical conditions at this  specific moment in time can be integrated  

with diagnostic data from millions of previous  cases. And the range of value can be observed  

against the healthy population or a group  of patients suffering from the same disease.  

And by combining all those different data,  clinicians could determine more precisely  

your particular disease condition or particular  medication that is likely to help in this case.

Digital twins are not limited to diagnostic  imaging data. One could integrate for example  

genetic and molecular information into  the twins. As a result, practitioners  

would have get access to an even more accurate  representation of their patients. Over time the  

twins can be enriched with new medical and  personal information and evolve further. 

We want to represent the anatomy and the  physiology of specific patients. All those models,  

they need to be personalized using a specific  individual. And these models, they should also  

evolve over time, the digital twin needs to  represent accurately the patient at every point  

in time. So that we can update the model and can  represent more accurately at every time point.

Perhaps the most incredible potential from  the digital twin comes from the opportunity  

for more personalized therapy. For Christian as a  radiation oncologist, it’s all about the level of  

precision that the twin could make possible: In radio therapy we always say: Our beam  

is in submillimeters controlled by the radio  oncologist. But the main question is how good  

is the data where the tumor is located? And  I want to go step further. I would say the  

cooperation between the radiologist and the  radio therapist is essential to make the most  

accurate planning. We both need information  about the possibilities of the systems and so  

we can make a more precise diagnostics  and based on this a more precise planning.

In radiotherapy it’s key to be able to increase  tumor control while reducing toxicity. It is about  

delivering a high dose to the tumor while  sparing the healthy tissue surrounding it.

If the digital twin allows  us to collect more data,  

then it would be such a gain for  radiotherapy. We can analyze the  

data and answer these questions  more precisely than is now possible.

With personalized information,  doctors would no longer have to  

base therapeutic regimens on population data  but adapted to the individual patient needs.

The issue is that those guidelines, they are  based on statistics done on the entire population,  

but what is best on average might not be the  best treatment for a specific individual. So,  

because the patient’s condition only  determines ease or position on the  

guidelines, and therefore the recommended  therapy, this is very limited factor,  

the detailed knowledge of the patient clinical  data, the physiology, can help refining the  

decision making to select the best treatment  for one patient at a particular moment in time.

Chloe gives an example of a current standard  treatment option in the case of lung cancer:

There is one treatment option that is called  stereotactic body radiation therapy or SBRT.  

We observed that some patients do respond to these  treatments and when patients respond to it, it's  

a very effective treatment, but some patients  are non-responders. And usually when we observe  

that they are non-responders, it's  often too late to take other action.

If a digital twin would be  available for those patients,  

doctors could predict whether they would respond  to the treatment or not even before it happens!

Using the entire clinical information  about the patient, the genetic information,  

as well a patient’s specific physiological  model can actually help in the patient  

selection by differentiating a priori, the  patient response pattern, so, by identifying  

the patient that would respond to the one  that will not respond to the treatment. So,  

therefore, such model could help in selecting  early other therapy options for the patient  

whose digital twin predicted that they will  not respond and this would eliminate the need  

for therapy change in the hope that the  one with the best outcome would come up.

This way, the patient would not suffer from  side effects arising from an ineffective  

treatment. Furthermore, the twin could  help to save the associated costs.

The clinician could use the digital twin  to test different treatment protocols in  

advance and select the more efficient  one for one given patient. So that the  

procedure would be tailored  precisely for each patient.

That means doctors could even perform multiple  treatment scenarios on the twin and predict their  

outcomes—before even physically coming  into contact with the patient. In the  

case of liver cancer, a digital twin could  assist in surgical planning. Here’s Chloé:

A surgeon could use a digital twin to navigate  the digital representation of the liver before  

operating on it. So the cancer surgeon would be  able to precisely evaluate our tumor disposition  

related to healthy tissue. And you could  simulate virtually the resection, for example,  

and completely compute the remaining liver  function, which is something vital to assess,  

to decide if it's safe to go for a surgery or  not. Another aspect is to provide the ability  

to simulate in advance how an organ  would respond to a treatment, if you  

change different parameters in the treatment  sets. Giving the physician the possibility to  

predict the effectiveness of the intervention,  to better understand the potential side effects,  

and to limit them and to accelerate the  operation by avoiding the unnecessary treatment.

By avoiding ineffective therapies  and enabling less invasive therapy  

options with digital twins, patients could  potentially experience faster recoveries,  

shorter hospital stays and, in  turn, a better quality of life.

It's a Sandbox to look at cause and effect, like  an experiment when we change some factors like  

therapy regimens or dose in radiotherapy, then  the question is what is the difference in months,  

years and centuries? And to make it easy to  look at these different possibilities and the  

different permutations of cases, the digital twin  is a wonderful take. It's like a sandbox. It's  

like a possibility to starting from different  conditions and looking what comes at the end.

And it doesn’t stop there. Also  when it comes to follow-up care,  

Christian sees potential for a digital twin and  explains its application in managing recurrence:  

The re-irradiation is also a very interesting  object for the digital twin. Because  

with a digital twin I will be able to estimate  the risks of side effects or the possibility  

itself to make a re-irradiation before I try this  at the patient, I need every data I can get. It's  

so important for the patient to get a second  chance, in case of relapse, for longer survival.

Because the life expectancy is increasing,  we have more and more cases in oncology  

and reoccurrence of tumor will be more and more  a challenge. This is clear. And if we have the  

possibility to make the therapy strategies  more transparent and more precise and combine  

this with data, then it's possible to make  more precise predictions for these patients.

Practitioners have treated cancer for centuries,  

having to wait for physical results to manifest  before they knew whether a treatment was effective  

or not. With digital twin technology, medical  science continues to transform exponentially:  

we may have the ability to watch scenarios  play out before the patient has a single  

treatment in the future. Here’s Christian  one last time speaking on the potential:

You can only live one life, it's not possible  to say: Oh, stop, rewind like a video recording,  

it's not possible. But in case of digital twin  you can stop, rewind and start at a certain point.

While we still have quite a way to go  before implementing the digital patient  

twin, a fully individualized  digital avatar of a patient,  

preloaded with their entire medical history and  continually updated with real-time health data,  

it’s incredible to think of the potential the  technology has. The digital twin technology can  

bring us closer to precision medicine and change  cancer care as we know it. If you are interested  

in learning more about this topic, check out our  episode on patient twinning from September 2022. 

From early detection, to diagnosis, to treatment,  to follow-up, cancer care could be reframed,  

the life of patients and their families could be  transformed for the better, the work of Physicians  

and care teams could be dramatically optimized. Thank you for listening!

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