The document discusses the challenges faced by the medical imaging sector due to rapid population growth, increased demand for diagnostic procedures, and a shortage of qualified radiologists. It highlights the transformative impact of AI and advanced technologies on healthcare, emphasizing the need for improved workflow integration and patient-centered care. The ultimate goal is to enhance outcomes in disease management, particularly for conditions like breast cancer, through better screening and diagnostic processes.

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Medical Imaging Challenges:
Everyone Deserves Clear
Answers about their Health
Nikos Kourentzis,
November 1st, 2022

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Rapid Population Growth
+83 mm people / year
~9 bn people by 2030
Digital Revolution
Broadband Communication
Big Data
Artificial Intelligence

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Deep transformation in the Medical Imaging
ecosystem…
o Traditional Medical
Imaging Companies
o Digital Business
Consumer Goods
Companies
… is leading to new
entries in the industry
Steady growth of diagnostic procedures.
Increasing budget pressure.
Shortage of skilled, trained radiologists & physicians.
Fast-paced development of advanced analytical solutions.
Blurring sector boundaries between diagnosis and
therapy as well as along the radiology workflow.
o IT Technology
Companies
o New Startups
3

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… and to some
fundamental changes
RSLM – Day 1 /// January 26th, 2021
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DMP improve the health of persons and reduce associated by
identifying and treating chronic conditions more quickly and
more effectively, thus slowing the progression of those
diseases.
AI will not replace radiologists, but Radiologists who use AI
will replace Radiologists who don’t.
Value-based healthcare will continue to rise expectations
from Radiologists & Physicians for superior patient
outcomes.
Patients are increasingly empowered and motivated to take
a more proactive role about decisions affecting their health.
Integrated &
centralized workflow
Optimal Disease
Management
Diagnostic support
through AI
Outcome focus
Patient centricity
Radiologists are shifting their focus to value-creating tasks,
demanding further standardization, automation & workflow
integration.

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10x increase in the annual departmental cross-
sectional images interpreted (1999 to 2010)1
Greater complexity
49% of radiologists reported
signs of burnout3
Radiology departments pushed to their limits
40m annual diagnostic
errors worldwide2
Diagnostic errors
1. McDonald RJ et al. The effects of changes in utilization and technological advancements of cross-sectional imaging on radiologist workload. Acad Radiol. 2015;22(9):1191-1198.
2. Itri JN et al. Fundamentals of Diagnostic Error in Imaging. Radiographics. 2018;38(6):1845-1865.
3. Medscape. Medscape Radiologist Lifestyle, Happiness & Burnout Report 2022. 2022.
HCOs & HCPs face
enormous quality
and efficiency
challenges as the
demand for
diagnostic imaging
increases

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Is it safe to do this exam? What about
the quality of the Diagnosis
They always seem to be short-staffed
and have very little time for me.
I have to go back for another scan
due to inaccurate diagnosis.
Exemplary quotes for illustration
The challenges HCPs face directly
impact our patients

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According to
the WHO
https://www.who.int/news-room/fact-sheets/detail/breast-cancer
there were 2.3 million women
diagnosed with breast cancer and
685.000 deaths in 2020.
7.8 million women diagnosed with
breast cancer in the past 5 years
were alive end of 2020 making it
the world’s most prevalent cancer.
GBPC

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Vision: Improve breast
cancer survival by
increasing awareness of
risk factors and access to
effective screening and
earlier diagnosis

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CRIB – Global process x-modality breast indication
Screening
Selection
Mammography / DBT*
(Imaging center or ObGyn or hospital)
CEM Modality
(Imaging center or hospital or radiology site )
MRI modality
(hospital / Radiology site)
Average risk Cancer Survivors
Patient specifics vs. guidelines
(genetics, history, contraindications)
Higher than average risk
Recurring w/ respect to
local guidelines
General pop. risk assessment
(initially at age 15-30)
Diagnostic work-up
(Unclear results or anomaly found)
Diagnostic
selection
Result: no finding
Screening
Origination
Screening
Procedure /
results
Screening invite
(via public prog. or HCP)
L2
Pre-treatment staging
Disease extent, stage
(immediate) (post)-treatment tracking
(NAC response, re-occurrence)
HCP preference
(ObGyn/Surgeon (?) experience)
Factor weighting varies by region, dependent on
* ObGyn or Surgeon (?) in lead
* Patient / guideline/ indication specifics
* Reimbursability / payor system
* Availability of modality in general and on-site
Reimbursement eval.
(payors, guidelines, patient paid)
Availability eval.
(on-site/ off-site)
L4
L3
Biopsy
(US/ Xray guided / partially automated)
Ultrasound +
ABUS**
MRI / + CA Brand selection
Other HCP referral
(Nipple discharge, occult primary cancer, etc.)
Diagnostic
Origination
CEM / + CA Brand selection
Suspected Confirmed
Patient specifics vs. guidelines
(suspected disease, contraindications)
Reimbursement eval.
(payors, guidelines)
Availability eval.
(on-site/ off-site)
HCP preference
(ObGyn/Surgeon experience)
Diagnostic
procedure /
results
Result: Breast cancer confirmed /
staged / tracked
Result: No breast cancer
Factor weighting varies by region, dependent on
* ObGyn or Surgeon in lead
* Patient / guideline/ indication specifics
* Reimbursability / payor system
* Availability of modality in general and on-site
Process step
or outcome
Modality
Flow /
sequence
L1
L5
L7
L8
Unclear result
Unclear result
DBT /
Mammography
High Risk
Brand selection contrast agent Brand selection contrast agent
Treatment

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Radiology 2030
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Intelligent Systems & AI
• Higher throughput
• Higher Diagnostic Quality
• Less Repeat Exams
New business Models
• Pay per use
• Subscription
• AI reimbursement

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Thank You