Digital twins in cancer state of-the-art and open research

KamranGholizadehHamlAbadi
Young researchers and elite club,
Qazvin Branch, Islamic Azad University,
Qazvin, Iran
MonirehVahdati
Young researchers and elite club,
Qazvin Branch, Islamic Azad University,
Qazvin, Iran
Ali MohammadSaghiri
Soft Computing Lab,
Computer Engineering Department,
AmirKabir University of Technology,
Tehran, Iran
Agostino Forestiero
Institute for High Performance Computing
and Networking (ICAR),
National Research Council of Italy (CNR),
Via P. Bucci, 8-9C, Rende, CS, Italy
Digital Twins in cancer: State-of-the-art and open research
Authors
AIIOT4DH Workshop @ CHASE 2021: The Sixth IEEE/ACM Conference on Connected Health: Applications, Systems and Engineering Technologies, December 16 - 18, 2021, Washington D.C., USA 01 26

Meeting Schedule
Digital Twinsin cancer:State-of-the-art and open research
02
Research
Methodology
Discussion
TheDT and cancer
literature
Introduction
Related work Conclusion
AIIOT4DH Workshop @ CHASE 2021: The Sixth IEEE/ACM Conference on Connected Health: Applications, Systems and Engineering Technologies, December 16 - 18, 2021, Washington D.C., USA

Introduction
Cancer threats
Second Mortality
Cancer is the second largest
cause of mortality globally
Most common types of
cancer
Prostate, stomach, lung, liver,
colorectal, cervical, breast, and
thyroid cancer
The global cancer
burden is Increasing
Physical, emotional, and
financial strain
Reduce the cancer
burden
Early cancer detection,
appropriate treatment
Critical for cancer
Screening,, Treatment, and
palliative care
04

Introduction
Advanced technologies in cancer ailments
Revolutionize treatments for
various types of cancer disease
Artificial
Intelligence
Blockchain
Internet of
Things (IoT)
These technologies have the potential to revolutionize treatments for various types of cancer disease, even if they may suggest alternative approaches to disease
management that are inefficient in terms of organizing a personalized healthcare solution.
Internet of Things(IoT)
Smart healthcare monitoring Wearable sensors personalized healthcare
Blockchain
Data sharing privacy
Transparency
Smart Contract
ArtificialIntelligence
Healthy food recommendations
Image processing
Health data management
04
05

Introduction
Digital Twins
Real Human Human’s data Human’s models
Real World
A human have a wide range of
organs
Data
Data is received from real
humans with the aid of IoT and
telecommunications structures
like 5G and 6G.
Model
Data is modeled with the help
of artificial intelligence
Human DigitalTwin
With the help of cloud and
edge computing, and
communication network an
individual digital twins could be
produced.
Medical professionals and patients might benefit from personalized DT because they can give timely and essential information, allowing them to make more knowledgeable
and preventative decisions.
We hope to develop DT; not only that it can replicate the diverse organs of individuals who are at risk of cancer, but it can also screen, predict, diagnose, and cure cancer
diseases using machine learning.
DigitalTwin
06

Introduction
Contribution of the paper
A survey on some medicine applications
A review on DT and cancer in both
conceptual and statistical analyses
There is no literature
research on various illnesses
and DT specifically cancer
disorders.
The development obstacles of using DT
in cancer illnesses will be highlighted,
followed by various open research
directions.
07

Related Work
DT in application of Medicine
Digital Twins in health
High potential in different case studies on
health
Fighting different Ailments
Alzheimer, cancer, cardiology, coronavirus
disease 2019, diabetes, viral infection, kidney
disease, and stroke,
Other applications of healthcare
Adult vaccination, DNA paradigm, stress testing,
nutrition, pharmaceuticals, and physical activity.
09

Related Work
DT in cancer
The National Cancer
Institute and the U.S.
Department
This institute brought together a varied
collection of researchers to form new
relationships and explore creative research
projects aimed at expanding the development
of a DT for cancer patients.
Create a million DT of pancreatic cancer patients.
• Drug sensitivity and resistance
• Precision medicine treatment strategies
• Enhanced long-term survival
Building a self-learning DT platform prototype
• Personalized treatment in melanoma patients
• Quickly prototype a 3D multiscale model of melanoma metastases
An Adaptive and dynamic multiscale DT approach
created from the patient’s own data
• Treatment response and resistance being monitored
• Advance the hypothesis that optimal pathways for a certain cancer patient,
and a treatment pathway space.
A virtual cancer
• To build a DT platform that uses biological,
biomedical, and electronic health record data sets.
• Combine mechanistic, machine learning, and
stochastic modeling techniques.
10

Research Methodology
The goal of this study is to assess the present state of DT research in cancer by reviewing the literature and identifying current trends.
ACM Digital Library Google Scholar IEEE Xplore digital
library
John Wiley & Sons MDPI
Elsevier Scopus Springer link SAGE Publications Taylor & Francis

The DT and cancer literature
Conceptual analysis
Medium Business Unlimited
Goals of DT Fight cancer Type of Cancer
Preclinical Research
Individualized cancer care
Cancer diagnosis
Confidentiality of records
Prevention
Cancer diagnosis
Treatment
-
Uterine
Lung
Lung
Breast
Breast
Head and neck cancer
Author
Filippo et al. (2020)
Wickramasinghe et al. (2021)
Zhang et al. (2020)
Gonzalez-Abriletal. (2021)
Bethencourtet al. (2021)
Meraghniet al. (2021)
Tardiniet al. (2021)
Tackle the tremendous molecular
complexity of human bodies
Organize personalized uterine
cancer care.
Provides a method for detecting
potentially vulnerable functions.
Utilizes generative adversarial
networks between humans and DT.
Preventing lymphedema in patients
treated for breast cancer.
Personalized activity by data
gathered from some sensors.
Utilizes deep q-learning to organize
treatment for cancer.
14

The DT and cancer literature
Statistical Analysis
43%
43%
14%
Journal
Conference
Book Chapter
Distribution of papers in recent years
The publication in this area starts in 2019. At
the beginning of this trend, the number of
research stood at one paper. Then, it
experiences a sharp rise to 3 for the following
years, and until September 2021, it remained
the same.
Distribution of papers by type of publication
The majority of the reviewed papers were
focused on both conferences and journals,
with both accounting for 43%. In terms book
chapters, it has the lowest proportion
accounting for only 14% of all seven
publications.
Distribution of papers on online databases
Much of the work being done on DT in cancer
is being extracted from IEEE Xplore. All of the
other papers, except one, were published in
journals. Disseminating research through
conference papers and book chapters is much
more common.
0
1
2
3
4
2019 2020 2021
Number
Year
0 2 4 6
Springer
IEEE
MDPI
Other
Number
Online
database
15

Discussion
Benefits
Conventional cancer treatment has several problems, such as high complexity, unpredictability, and uncertainty. DT can solve these problems.
Personalized healthcare that includes
personalized medicine and treatments.
Personalized healthcare
Multiscale simulation to follow a
hypothesis with high accuracy.
Multiscale simulation
Drug sensitivity and resistance can be
studied with high accuracy.
Drug sensitivity
Detecting the optimal treatment pathway
and optimal treatment monitoring
Optimal treatment
17

Discussion
Future dynamics
Extraordinary capabilities to
manage cancer diseases
Evolution of AI to artificial
superintelligence
The evolution of
IoT to the
nanoscale and
molecular scale
As a future dynamic of research in this area, we may refer to the possible evolution of some parts of DT to bring extraordinary capabilities to manage cancer diseases. For
example, the evolution of AI to artificial superintelligence and perfect cognitive systems may result in the discovery of a new treatment that humans are unable to consider
because of the limitations of the human mind and abilities. As another example, the evolution of IoT to the nanoscale and molecular scale may be used to monitor and manage
every part of the human body
18

Discussion
Development hurdles
Real-time communication
Support to create a connection between the
DT and its related entity.
No standard structuringdata
There is no standard for structuring data and
data flow for organizing DT, which leads to
low interoperability.
Require new professions to model
Entities of a body on the basis of a corporation
with a wide range of experts including clinical
oncologists, pathologists, and radiologists
Lackof data
Lack of data for constructing multiscale
models and dependent information.
Security and Privacy
Preserved solutions are costly and the
huge volume of data, participant, and
technology
Infrastructureof the IoT
Require in DT is very costly and also
high-tech.
As main development hurdles that we can face while
shifting from existing solutions to DT based solutions
19

Discussion
Open Research
Severalopen research directionscan followed
DT could identify high-risk populations,
which allows policymakers to evaluate
different monitoring practices.
Identifyhigh-risk populations
Design a fullyfeaturedDT for cancer care
Novel approachtopersonalizedtreatment
More studiescan be conducted
To design a fully featured DT
for cancer care, all
participants like scientists and
clinicians should work
together.
Evaluate several treatment plans
of the DT of a patient.
all capabilities that are resulted
via DT and conventional
treatment may be required.
Although DT has a great
potential for fighting cancers,
a minority of research was
conducted on DT.
20

Conclusion
DT, application of medicine, and cancer
Digital Twins
Observing data from DT
populations may aid in the
improvement of some
cancer screening,
prediction, prevention,
detection, treatment, and
research investment
strategies.
Medicine
The applications and
benefits of using DT
in some diseases in
particular cancer were
discussed
Cancer
The prospects of using
DT in the design of
treatment plans and
processes related to
various types of
cancer were discussed
Main contribution of the research
To the best of our knowledge, there is no literature research on various illnesses and DT
specifically cancer disorders.
43% 57%
Cancer info in the world
Cancer is a leading cause of death worldwide
22
CHASE 2021:The Sixth IEEE/ACM Conferenceon Connected Health:Applications,Systems and EngineeringTechnologies,December 16- 18, 2021,Washington D.C.,USA

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