|
Forecast Period
|
2026-2030
|
|
Market Size (2024)
|
USD 15.35 Billion
|
|
Market Size (2030)
|
USD 30.64 Billion
|
|
CAGR (2025-2030)
|
12.17%
|
|
Fastest Growing Segment
|
Magnetic Resonance Imaging (MRI)
|
|
Largest Market
|
North America
|
Market Overview
Radiomics market was valued at USD 15.35
Billion in 2024 and is expected to reach USD 30.64 Billion by 2030 with a CAGR
of 12.17%. The global radiomics market is witnessing significant growth,
fueled by the increasing adoption of precision medicine and the integration of
advanced analytics in medical imaging. Key market drivers include the rising
prevalence of chronic diseases such as cancer and cardiovascular conditions,
growing demand for non-invasive diagnostic tools, and technological
advancements in imaging and artificial intelligence (AI). According to the
2022 GLOBOCAN, there were nearly 20 million new cancer cases and 9.7 million
cancer deaths worldwide. Lung cancer was the most frequently diagnosed,
accounting for 12.4% of all cases, and was also the leading cause of cancer
death, responsible for 18.7% of cancer-related deaths. The report projects that
by 2050, annual new cancer cases will reach 35 million, a 77% increase from
2022, highlighting the urgent need for enhanced global cancer control measures.
Radiomics plays a pivotal role in extracting quantitative features from
standard medical images, offering deeper insights into disease
characterization, prognosis, and treatment response.
However, the market faces certain
challenges, including the lack of standardized protocols for radiomic data
acquisition and analysis, limited interoperability between imaging platforms,
and concerns regarding data privacy and regulatory compliance. Additionally,
the complexity of radiomics workflows and the need for multidisciplinary
expertise can hinder broader clinical adoption.
Emerging trends shaping the market
include the integration of radiomics into clinical decision support systems,
increasing collaboration between imaging software vendors and AI solution
providers, and the incorporation of radiomic biomarkers in clinical trials for
drug development and personalized treatment strategies. Academic and research
institutions are also contributing to innovation by expanding the applications
of radiomics beyond oncology to neurology, cardiology, and inflammatory
diseases.
The impact of COVID-19 initially
disrupted imaging procedures and clinical workflows; however, the pandemic
ultimately underscored the value of remote diagnostics, big data analytics, and
non-contact screening tools. This shift accelerated interest in radiomics as a
key enabler of virtual health technologies and AI-assisted diagnostics,
positioning it as a cornerstone in the evolution of modern, data-driven
healthcare systems.
Key Market Drivers
Rising
Demand for Personalized and Precision Medicine
The rising demand for personalized and
precision medicine is a significant driver fueling the growth of the global
radiomics market. As cancer and other complex diseases continue to impact
millions worldwide, nearly 10 million cancer-related deaths occurred in 2020
alone, healthcare systems are shifting toward more individualized, data-driven
treatment strategies. Personalized medicine tailors’ medical treatment to
the individual characteristics of each patient, and radiomics plays a critical
role in enabling this transformation by extracting vast amounts of quantitative
data from medical images such as CT, MRI, and PET scans.
These imaging biomarkers provide deep
insights into tumor phenotype, tissue heterogeneity, and disease progression,
which are often undetectable by the human eye. This capability is vital in
oncology, where radiomics helps identify tumor subtypes, predict therapeutic
responses, and monitor treatment outcomes in a non-invasive manner. The advent
of targeted therapies and immunotherapies has made such precise tools
indispensable for effective patient stratification.
Radiomics also complements traditional
diagnostics by offering additional layers of information, while its integration
with genomic and clinical data—termed radiogenomics—enables a more
comprehensive understanding of disease biology. Furthermore, pharmaceutical
companies increasingly use radiomics in clinical trials to optimize patient
selection and improve drug efficacy. As global healthcare moves toward
precision and value-based care, the demand for radiomics as a tool for
personalized medicine is expected to surge significantly.
Advancements
in Medical Imaging Technologies
Advancements in medical imaging
technologies are significantly driving the growth of the global radiomics
market. Over the past decade, diagnostic imaging modalities such as Magnetic
Resonance Imaging (MRI), Computed Tomography (CT), and Positron Emission
Tomography (PET) have undergone rapid technological improvements. These
enhancements have led to higher image resolution, faster scan times, and better
anatomical and functional visualization. As a result, medical imaging now
generates vast amounts of high-quality data that can be mined for advanced
analysis using radiomics.
Radiomics relies heavily on the
availability of detailed and standardized imaging data to extract meaningful
patterns and quantitative features. Modern imaging systems equipped with
advanced detectors, digital signal processors, and automated calibration
systems facilitate the acquisition of consistent and reproducible images. These
high-quality images form the foundation for robust radiomic feature extraction,
enabling the identification of disease characteristics that are not apparent
through traditional visual interpretation.
Moreover, the integration of imaging
technologies with artificial intelligence and machine learning tools further
enhances the capabilities of radiomics. For instance, AI-assisted imaging
platforms can preprocess images, segment regions of interest, and highlight
subtle abnormalities with high precision. This integration allows radiomics to
deliver more accurate predictive models for disease diagnosis, prognosis, and
treatment planning.
These advancements support the growing
demand for non-invasive, data-driven diagnostics. As imaging becomes more
precise and widely accessible across hospitals and research settings, radiomics
is increasingly recognized as a valuable tool for extracting clinically
relevant insights from routine scans, thereby accelerating its adoption in
precision medicine and personalized healthcare.
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Key Market Challenges
Lack
of Standardization
One of the most significant challenges
hindering the growth of the global radiomics market is the lack of
standardization across various stages of the radiomics workflow. Radiomics
involves the extraction of quantitative features from medical images, and for
these features to be clinically meaningful and reproducible, consistent imaging
protocols are essential. However, there is currently a high degree of
variability in how imaging data is acquired, processed, and analyzed across
different healthcare institutions, scanner types, software platforms, and even
operators.
Differences in image acquisition
parameters—such as slice thickness, contrast usage, resolution, and scanning
protocols—can significantly alter the radiomic features extracted, even when
analyzing the same patient or pathology. This inconsistency creates challenges
in comparing data across studies or validating radiomic models at scale. As a
result, findings that appear promising in research setting often fail to
translate into real-world clinical practice, limiting the trust of healthcare
professionals in adopting radiomics-based tools.
The lack of universally accepted
guidelines or standards for image preprocessing, feature selection, and model
validation further exacerbates the issue. This fragmented landscape hinders the
development of regulatory-compliant, scalable radiomics solutions that can be
used confidently in multi-institutional trials or integrated into electronic
health records (EHRs).
Integration
with Clinical Workflows
Another critical challenge facing the
global radiomics market is the limited integration of radiomics tools into
routine clinical workflows. While radiomics holds immense potential for
enhancing diagnostic precision and enabling personalized treatment, its
practical implementation in day-to-day clinical settings remains complex and
fragmented. This disconnects between radiomic research and clinical application
significantly slows adoption across hospitals and healthcare systems.
Radiomics requires a series of technical
steps, including image acquisition, segmentation, feature extraction, and data
interpretation—many of which are not yet fully automated or standardized. These
processes often demand specialized software, advanced computing infrastructure,
and collaboration between radiologists, data scientists, and clinicians. As a
result, integrating radiomics into existing clinical pathways can be
resource-intensive and time-consuming. In many cases, healthcare professionals
find it difficult to incorporate these tools into their already demanding
schedules, especially when radiomic outputs are not seamlessly linked to
electronic health record (EHR) systems or clinical decision-support platforms.
Radiologists and physicians may lack
adequate training or familiarity with interpreting radiomic data, which
typically consists of complex mathematical descriptors rather than conventional
imaging findings. This creates hesitation and scepticism about the clinical
relevance and usability of radiomics, particularly in time-sensitive
environments such as oncology and emergency care.
For radiomics to become a standard
component of precision medicine, it must be seamlessly integrated into existing
diagnostic and treatment workflows. This requires not only user-friendly
software interfaces but also cross-functional collaboration, clinical
validation, and interoperability with hospital information systems. Without
such integration, the scalability and clinical impact of radiomics will remain
limited despite its technological advancements.
Key Market Trends
Integration
of Artificial Intelligence and Machine Learning
The integration of Artificial
Intelligence (AI) and Machine Learning (ML) technologies is revolutionizing the
global radiomics market by significantly enhancing the accuracy, efficiency,
and clinical utility of radiomic analysis. Radiomics involves extracting vast
amounts of quantitative data from medical images, which can be complex and
time-consuming to analyze manually. AI and ML algorithms automate and optimize this
process, enabling faster and more precise identification of patterns and
features that may be imperceptible to the human eye.
AI-powered radiomics platforms utilize
advanced machine learning models to analyze imaging data, segment regions of
interest, and extract relevant features with high consistency. These models can
learn from large datasets, improving their predictive performance over time. By
integrating AI, radiomics shifts from a primarily descriptive approach to a
predictive and prognostic tool, aiding clinicians in making informed decisions
regarding diagnosis, treatment planning, and patient monitoring.
Moreover, AI facilitates the integration
of multimodal data, combining imaging, genomic, clinical, and pathological
information, to deliver a holistic view of a patient’s condition. This fusion
is critical for advancing precision medicine, allowing healthcare providers to
tailor interventions based on comprehensive insights.
The adoption of AI and ML also addresses
several operational challenges by automating routine tasks, reducing
inter-operator variability, and accelerating turnaround times. This makes
radiomics more scalable and accessible in busy clinical environments.
As AI continues to evolve, ongoing
research focuses on enhancing algorithm transparency, interpretability, and
regulatory compliance to build trust among clinicians and patients. Overall,
the synergy between AI, ML, and radiomics is a pivotal trend driving innovation
and adoption in the healthcare industry, unlocking new possibilities for
personalized, data-driven care.
Expansion
Beyond Oncology
The expansion of radiomics applications
beyond oncology represents a significant trend shaping the global radiomics
market. While radiomics initially gained prominence through its ability to
analyse tumours and support cancer diagnosis, prognosis, and treatment
response, its potential is increasingly being recognized in other medical
fields. This broadening scope is driven by the demand for non-invasive,
data-rich diagnostic tools that can improve disease characterization and
patient management across various conditions.
In cardiology, for example, radiomics is
used to assess myocardial tissue characteristics, detect fibrosis, and predict
adverse cardiac events, offering valuable insights beyond traditional imaging
interpretations. Similarly, in neurology, radiomics aids in the evaluation of
brain disorders such as stroke, Alzheimer’s disease, and multiple sclerosis by
quantifying subtle changes in brain structure and function. Pulmonology also
benefits from radiomics through improved characterization of lung diseases, including
chronic obstructive pulmonary disease (COPD) and interstitial lung disease.
The application of radiomics in
inflammatory and autoimmune diseases is another emerging area, where
quantitative imaging can help monitor disease activity and therapeutic response
without invasive biopsies. This diversification expands the market potential
for radiomics technologies, attracting investment from a wider range of
healthcare sectors.
As medical imaging technology continues
to improve and AI integration advances, the ability of radiomics to extract
meaningful features across different organ systems and disease states
strengthens. This expansion beyond oncology not only increases the clinical
relevance of radiomics but also accelerates its adoption, positioning it as a
versatile tool in precision medicine across multiple specialties.
Segmental Insights
Modality Insights
The Magnetic Resonance Imaging (MRI)
segment emerged as the fastest-growing modality in the radiomics market in 2024
due to several compelling factors. MRI technology offers superior soft tissue
contrast and detailed anatomical resolution compared to other imaging
techniques like CT or PET scans. This high level of image clarity allows
radiomics algorithms to extract more precise and diverse quantitative features,
which are critical for accurate disease characterization, especially in complex
conditions such as brain tumors, musculoskeletal disorders, and prostate
cancer.
MRI’s non-invasive nature and lack of
ionizing radiation make it a preferred choice for repeated imaging, which is
essential for longitudinal monitoring and treatment response assessment in
precision medicine. The growing availability of advanced MRI techniques, such
as diffusion-weighted imaging (DWI) and functional MRI (fMRI), further enriches
the dataset available for radiomic analysis, enabling deeper insights into
tissue physiology and pathology.
Technological advancements have also
made MRI more accessible and efficient, with faster scanning protocols and
improved patient comfort, leading to increased adoption in clinical and
research settings. Moreover, the integration of AI-powered radiomics tools with
MRI facilitates automated image processing and feature extraction, enhancing
workflow efficiency and diagnostic accuracy.
These factors combined have driven rapid
growth in the MRI segment within the radiomics market, as healthcare providers
and researchers increasingly recognize MRI’s value in delivering detailed,
actionable data for personalized diagnosis and treatment planning. This trend
is expected to continue as MRI technology and radiomics applications evolve
further.
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Regional Insights
North America emerged as the largest
market in the global radiomics sector in 2024 due to a combination of
favourable factors that have accelerated the adoption and development of
radiomics technologies in the region. One of the primary reasons is the presence
of a highly advanced healthcare infrastructure, supported by significant
investments in cutting-edge medical imaging equipment and digital health
solutions. Leading hospitals and research institutions in North America have
been early adopters of radiomics, recognizing its potential to enhance
diagnostic accuracy and personalize patient care, particularly in oncology.
Additionally, North America benefits
from strong government support and substantial funding for healthcare
innovation, including initiatives that promote artificial intelligence, big
data analytics, and precision medicine. This has fostered a robust ecosystem
for radiomics research and development, enabling rapid clinical validation and
commercialization of radiomics-based applications.
The region also hosts many key players
in the radiomics market, including established medical imaging companies,
technology startups, and pharmaceutical firms actively integrating radiomics
into clinical trials and drug development. Furthermore, the high prevalence of
chronic diseases such as cancer, cardiovascular, and neurological disorders
drives demand for advanced diagnostic tools that radiomics can provide.
Favourable regulatory frameworks and
well-established reimbursement policies in North America encourage the adoption
of novel diagnostic technologies. Combined with growing awareness among
healthcare professionals about the benefits of radiomics, these factors
position North America as the leading market for radiomics in 2024, a trend
expected to sustain as precision medicine continues to evolve.
Recent Developments
- In February 2025, Exactech showcased
groundbreaking research at the Orthopaedic Research Society (ORS) 2025
conference, focusing on the integration of Artificial Intelligence (AI),
radiomics, and advanced polyethylene technology in orthopedic surgery. The
company highlighted how AI-driven radiomics can enhance surgical planning and
outcomes by providing detailed analyses of joint mechanics and wear patterns.
Additionally, Exactech presented advancements in polyethylene materials
designed to improve the longevity and performance of joint replacements. These
innovations aim to address common challenges in orthopedic procedures, such as
implant wear and patient-specific anatomical variations, ultimately leading to
more personalized and effective treatments. Exactech's participation at ORS
2025 underscores its commitment to advancing orthopedic care through the
adoption of cutting-edge technologies.
- An article published in February 2025 by
Breaking Cancer News delves into the transformative role of radiomics in cancer
care. Radiomics involves extracting quantitative data from medical imaging
scans, such as CT, MRI, and PET, to uncover patterns that may not be visible to
the naked eye. This approach enables clinicians to gain deeper insights into
tumor biology, predict treatment responses, and monitor disease progression
more accurately. The integration of AI and machine learning further enhances
the predictive capabilities of radiomics, allowing for more personalized and
effective treatment strategies. The article emphasizes the potential of
radiomics to revolutionize oncology by moving beyond traditional imaging
techniques and providing a more nuanced understanding of cancer at the molecular
level.
- In November 2021, OncoDNA announced its
strategic support for Radiomics' prospective clinical trial, SALMON (meaSure
lung cAncer bioLogy and treatMent respOnse via imaging). This multi-center,
multi-country study aims to validate AI-based radiomics approaches in non-small
cell lung cancer (NSCLC). The trial involves collecting biopsy samples and
imaging data from NSCLC patients to create a non-invasive radiomics atlas of
oncogenic biomarkers based on CT scan features. Additionally, the study seeks
to automate therapy response assessment using AI on follow-up CT scans.
OncoDNA's involvement brings expertise in tumor characterization through both
solid and liquid biopsies, complementing Radiomics' imaging analysis. The
collaboration aims to enhance the understanding and treatment of NSCLC by
integrating advanced imaging techniques with comprehensive biomarker analysis.
Key Market Players
- Radiomics.io (Computational Imaging &
Bioinformatics Lab)
- Radiomics Bio
- Health Innovation Ventures (HIV)
- Sophia Genetics SA
- HealthMyne Inc
- Oncoradiomics
- ptTheragnostic BV
|
By Modality
|
By Image Type
|
By Technology
|
By Application
|
By Region
|
- Magnetic Resonance Imaging (MRI)
- Computed Tomography (CT)
- Positron-Emission-Tomography (PET)
- Others
|
|
- Engineered Features
- Deep Learning
|
- Nuclear Medicine
- Medical Imaging
- Precision Medicine
- Oncology
- Others
|
- North America
- Europe
- Asia Pacific
- South America
- Middle East & Africa
|
Report Scope:
In this report, the Global Radiomics Market has
been segmented into the following categories, in addition to the industry
trends which have also been detailed below:
- Radiomics Market, By Modality:
o Magnetic Resonance Imaging (MRI)
o Computed Tomography (CT)
o Positron-Emission-Tomography (PET)
o Others
- Radiomics Market, By Image Type:
o 2D
o 3D
- Radiomics Market, By Technology:
o Engineered Features
o Deep Learning
- Radiomics Market, By Application:
o Nuclear Medicine
o Medical Imaging
o Precision Medicine
o Oncology
o Others
- Radiomics Market, By Region:
o North America
§ United States
§ Canada
§ Mexico
o Europe
§ France
§ United Kingdom
§ Italy
§ Germany
§ Spain
o Asia-Pacific
§ China
§ India
§ Japan
§ Australia
§ South Korea
o South America
§ Brazil
§ Argentina
§ Colombia
o Middle East & Africa
§ South Africa
§ Saudi Arabia
§ UAE
Competitive Landscape
Company Profiles: Detailed analysis of the major companies presents
in the Global Radiomics Market.
Available Customizations:
Global Radiomics market report with the
given market data, TechSci Research offers customizations according to a
company's specific needs. The following customization options are available for
the report:
Company Information
- Detailed analysis and
profiling of additional market players (up to five).
Global Radiomics
Market is an upcoming report to be released soon. If you wish an early delivery
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