Role of imaging in the era of precision medicine
Abstract
Precision medicine is an emerging approach for treating medical disorders, which takes into account individual variability in genetic and environmental factors. Preventive or therapeutic interventions can then be directed to those who will benefit most from targeted interventions, thereby maximizing benefits and minimizing costs and complications. Precision medicine is gaining increasing recognition by clinicians, healthcare systems, pharmaceutical companies, patients, and the government. Imaging plays a critical role in precision medicine including screening, early diagnosis, guiding treatment, evaluating response to therapy, and assessing likelihood of disease recurrence. The Association of University Radiologists Radiology Research Alliance Precision Imaging Task Force convened to explore the current and future role of imaging in the era of precision medicine and summarized its finding in this article. We review the increasingly important role of imaging in various oncological and non-oncological disorders. We also highlight the challenges for radiology in the era of precision medicine.
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Radiomics has the potential to provide a robust approach to imaging analysis in a noninvasive, rapid, timely, and affordable manner.
“In view of recent advances in targeted treatment and immunotherapy, particularly in the treatment of malignancies, the need for a robust approach to imaging analysis has become clear, and radiomics has the potential to provide this in a noninvasive, rapid, timely, and affordable manner(12).”
From Artificial intelligence, machine learning, computer-aided diagnosis, and radiomics: advances in imaging towards to precision medicine (2019) · cites this paper as [12]
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References 144 · Cited by 87
- Authors
- Giardino, A., Gupta, S., Olson, E., Sepulveda, K., Lenchik, L., Ivanidze, J., Rakow-Penner, R., Patel, M. J., Subramaniam, R. M., & Ganeshan, D.
- Affiliations
- Brigham and Women's Hospital (US)
- Augusta University (US)
- University of California San Diego (US)
- Baylor College of Medicine (US)
- Wake Forest University Health Sciences (US)
- Weill Cornell Medicine (US)
- University of South Florida (US)
- The University of Texas Southwestern Medical Center (US)
- The University of Texas MD Anderson Cancer Center (US)
- Corresponding author
- Gupta, Supriya
- Venue
- Academic Radiology
- Publisher
- Elsevier BV
- Published
- 2017-05
- Volume
- 24
- Issue
- 5
- Pages
- 639-649
- ISSN
- 1076-6332 (ISSN-L)
- OpenAlex
- W2581295769
- Cited by
- 87
- References
- 144
- Citations by year
- 2026: 3 · 2025: 16 · 2024: 13 · 2023: 10 · 2022: 8 · 2021: 8 · 2020: 9 · 2019: 6 · 2018: 10 · 2017: 4
- FWCI
- 0.23
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Academic Radiology (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Medical Imaging Techniques and Applications
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Radiomics and Machine Learning in Medical Imaging
- Keywords
- precision medicine, diagnostic imaging, early diagnosis, cancer screening, treatment response assessment, recurrence, personalized medicine
- MeSH terms
- Humans, Medical Oncology, Radiology, Precision Medicine
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