Journal presentation: Brink, J. A., & Hricak, H. (2023). Radiology 2040. Radiology, 306(1), 69–72. https://doi.org/10.1148/radiol.222594 This editorial describes a variety of anticipated changes in the science and practice of radiology, some of which will appear almost inevitably and some of which the imaging community will only be able to achieve through vision and intense determination.

1. Radiology 2040
DR ABHINEET DEY
PGT 1, DEPARTMENT OF RADIOLOGY
SILCHAR MEDICAL COLLEGE & HOSPITAL

2. Radiology: Volume 306: Number 1—January 2023
Brink, J. A., & Hricak, H. (2023). Radiology 2040. Radiology, 306(1), 69–72.
https://doi.org/10.1148/radiol.222594

3. Introduction
Historically, radiology has been a specialty of innovation. Radiology has
embraced new technologies and recognized their potential well before
their clinical value has been widely accepted.
Over the past 4 decades alone, we have repeatedly expanded and
reshaped our field to accommodate revolutionary technological
advances.
•Cross-sectional anatomic imaging: CT & MRI
•Functional and molecular imaging
•Interventional radiology
•Radiotheranostics: Combines targeted molecular imaging with
radionuclide therapies

4. The Future of
Radiology
THIS EDITORIAL DESCRIBES A VARIETY OF ANTICIPATED CHANGES
IN THE SCIENCE AND PRACTICE OF RADIOLOGY, SOME OF WHICH
WILL APPEAR ALMOST INEVITABLY AND SOME OF WHICH THE
IMAGING COMMUNITY WILL ONLY BE ABLE TO ACHIEVE THROUGH
VISION AND INTENSE DETERMINATION.

5. Radiology Workflow
Increasingly, computation and data analytics will support imaging and
other diagnostics, as well as connectedness and telehealth
AI-powered autonomous or semiautonomous US using low-cost
transducers driven by smartphone technology will enable patients to
perform simple US data acquisition on their own, with images being
reconstructed automatically.
In the future, other examinations may be performed locally, including
with portable equipment for radiography, CT (motionless), and MRI
(low field strength).

6. Teleradiology
Home reading and teleradiology will continue to rise due to the
growing demand for worker flexibility and the need for continuous
coverage as well as outreach beyond urban centres.
However, radiologists of the future will need to think hard about how to
balance remote and on-site readings for the benefit of patients,
education, and cross-fertilization of knowledge.
It will be important for radiologists to maintain a strong presence within
their health care institutions so that they continue to be recognized as
key partners in patient care and research.

7. Artificial Intelligence (AI)
AI will not replace radiology, but it will profoundly affect our relevance
and our workflow.
The greatest risk to our specialty is that other medical specialties, and
potentially patients themselves, may leverage AI for independent image
interpretation.
Given that referring physicians have clinical information at their
fingertips, they will be able to put imaging findings in a clinically
relevant context to a much greater degree than traditional radiologists.

8. Artificial Intelligence (AI)
AI algorithms will provide comprehensive and autonomous
interpretation.
At present, most AI algorithms are narrowly focused, targeting a specific
imaging feature or function.
Over the next several years, algorithm development will broaden to
include a comprehensive evaluation of all possible features that may be
present in certain imaging examinations.
Algorithm development will become increasingly federated, with the
training of distributed algorithms on local data rather than moving data
beyond secure firewalls.
Radiologists must remain the keepers of such algorithms and oversee
their use unequivocally.

9. Artificial Intelligence (AI)
The “lifelong learning” of AI algorithms, including their ability to adapt
to improved or new technologies (eg, novel MRI pulse sequences, novel
radiotracers) are some of AI’s greatest strengths.
Over time, AI algorithms will enable the integration of radiomic
features and metabolic or functional information with genomic and
other phenotypic information for disease detection and
characterization. These capabilities will likely exceed what is achievable
by humans alone.
As radiologists, we must welcome the assistance that AI will provide to
our practices, recognizing that it will enable us to function at a higher
level, just as did the advent of digital imaging and electronic image
display.

10. Artificial Intelligence (AI)
The drive toward subspecialisation for maximal value creation will
continue. But AI may enable radiologists to achieve highly
subspecialized excellence (as so-called centaur radiologists—a
combination of human plus computer).
While it is tempting to imagine that this scenario may enable AI-
powered generalists to deliver the value typically seen with
subspecialists, subspecialized training will remain extremely important,
as radiologists’ clinical relevance can only be assured by radiologists
being as knowledgeable as our subspecialized referring physicians.

11. Artificial Intelligence (AI)
Imaging examinations will give rise to AI-derived three-dimensional
data sets of imaging findings.
Radiologists will need to ensure the accuracy of salient findings and
ensure the integration of these findings with relevant clinical scenarios
to produce meaningful and impactful diagnoses.

12. Artificial Intelligence (AI)
Imaging interpretations will be converted to lay language instantly and
in a variety of media, including static and motion content with
automatic, cinematically rendered images. Patients and their providers
will have instant and full access to their images and interpretations in
real time, potentially for the application of individual or personal AI
algorithms on features of interest.
Recommended follow-up imaging or other diagnostic testing will be
communicated, confirmed, and, if warranted, arranged automatically
through robust care coordination systems.

13. Artificial Intelligence (AI)
In pathology, For example, the Papanicolaou test no longer requires
human interpretation routinely. Machine-based interpretations,
potentially in distant locations, have become the norm. The only
exceptions are in unusual conditions that prevent automatic reading
and require human intervention.
Certain radiology examinations will undergo a similar evolution.
These changes will further marginalize radiologists and threaten our
relevance unless we integrate ourselves in the care continuum and add
value beyond machine-generated interpretations and
recommendations.

14. Value-based Care
Non–image-based precision diagnostics (i.e. “liquid biopsies”) will
continue to rise, and radiology’s place in the value equation will need to
evolve commensurately.
We must strive to be the primary purveyors of imaging examinations in
every respect, from their most appropriate uses to timely, accurate, and
precise reporting of the information they contain.
Imaging centres will evolve beyond diagnostic centres to treatment
planning and prediction centres. Radiology will be responsible for
phenotyping with imaging markers that are prognostic and predictive of
treatment response on a large scale.

15. Evolution of Imaging
Technologies
Imaging technologies will become increasingly multiscale, multimodal,
and multiomic. They will incorporate relevant metabolic, proteomic,
and genomic information.
“Smart” contrast agents will increase exponentially, leveraging in vivo
biochemistry, immunohistochemistry, reporter genes (genes that
produce receptors that bind imaging probes), and nanoparticles.
Bioengineering will advance rapidly, showing explosive potential to
alter the practice of medicine, with an outsized impact on medical
imaging.

16. Evolution of Imaging
Technologies
Phenotypic data generated by the physical interaction of an external
energy source with biologic tissue will enter multiomic databases that
cross multiple levels of biologic regulation, potentially bypassing the
need for image formation (ie, fingerprinting).
Images will be reconstructed in select cases where human
understanding is best achieved by visual means, such as for surgical or
interventional radiology treatment planning.

17. Environmental concerns
The carbon footprint of medical imaging will be at the forefront of
environmental sustainability efforts.
Thus, technical advances that substantially reduce our energy
consumption will be embraced uniformly. These include imaging
devices and viewing equipment with reduced power requirements.
Renewable sources for consumables in diagnostic and interventional
radiology will become mainstream.

18. Social, and Governance
Concerns
Radiology’s role in ensuring that health care is delivered equitably
across all demographic groups of our society is not assured.
Economic pressures will continue to favor the greatest care
delivery to those who can most afford it.
We must remain vigilant to do our part in bringing the power of
medical imaging to the most underserved populations across the
globe.

19. Radiotherapy
AN EXPANDING ROLE OF RADIOLOGY

20. Precision Imaging and Image-
guided Intervention
Due to advances in imaging, devices, techniques, and robotics, the array
of minimally invasive interventions will continue to grow.
Percutaneous endoscopic imaging will enable interventional
radiologists to perform minimally invasive interventions in domains
previously reserved for other specialties.
When combined with multispectral optical imaging, in vivo virtual
histologic examination may be possible for certain pathologic
conditions, potentially obviating the need for a needle biopsy.

21. Radiotheranostics
Theranostics combines diagnostic imaging with targeted therapy to
noninvasively determine tumor phenotype and evaluate functional and
molecular responses to therapy.
Radiotheranostics will continue to expand exponentially, combining
molecular imaging—currently with PET and SPECT—with radionuclide
therapy, leveraging small drugs, peptides, and antibodies to carry
therapeutic radionuclides (alpha-, beta-, or auger-emitters).
Radiotheranostic growth will expand clinicians’ ability to first “see with
precision” and then “treat with targeting.”

22. Radiotheranostics
While oncologic radiotheranostics already includes numerous
contemporary applications, it has enormous untapped potential for
treating a huge range of cancers.
Whereas patients are typically selected for cancer therapies based on
clinical (and secondarily histopathologic or molecular) parameters,
pairing radiation therapy with a companion diagnostic (eg, technetium
99m, fluorine 18, or gallium 68) allows clinicians to visualize in vivo the
expression of the therapeutic target, confirm the presence of the
therapeutic agent, and visualize tumor burden.

23. Radiotheranostics
In the field of oncology, drug development currently fails about 90% of
the time. Radionuclide therapies, however, provide insights regarding
the biodistribution of both intended targets and radioligands that allow
researchers to quickly halt, adapt, or accelerate their experiments. This
increases the success rates of these therapies over those of
conventional cancer therapies.
Furthermore, they also will have potential for application to other
patient-specific diseases, including inflammatory and autoimmune
conditions.

24. Conclusion
The next 2 decades will bring astonishing changes to health care that
are yet to be imagined.
With the expected growth of AI, radiologists will need to offer added
value beyond image interpretation.
We have been tremendously innovative over time, and we must remain
at the leading edge of innovation in both diagnostic imaging and image-
guided therapy (eg, interventional radiology and radiotheranostics) to
ensure that our technical advances and expertise continue to provide
value in the years ahead.
We must continue to embrace changes that are best for patients, and
decisions made with patients at their centre will always serve us well.

25. Thank you