The DOI matches its Crossref record; 93 of the 93 references it cites were found in a registry or an index.
Bench-to-bedside imaging in brain metastases: a road to precision oncology
Open accessAbstract
Radiology has seen tremendous evolution in the last few decades. At the same time, oncology has made great strides in diagnosing and treating cancer. Distant metastases of neoplasms are being encountered more often in light of longer patient survival due to better therapeutic strategies and diagnostic methods. Brain metastasis (BM) is a dismal manifestation of systemic cancer. In the present scenario, magnetic resonance imaging (MRI), computed tomography (CT) and positron emission tomography (PET) are playing a big role in providing molecular information about cancer. Lately, molecular imaging has emerged as a stirring arena of dynamic imaging techniques that have enabled clinicians and scientists to noninvasively visualize and understand biological processes at the cellular and molecular levels. This knowledge has impacted etiopathogenesis, detection, personalized treatment, drug development, and our understanding of carcinogenesis. This article offers insight into the molecular biology underlying brain metastasis, its pathogenesis, imaging protocols, and algorithms. It also discusses disease-specific molecular imaging features, focusing on common tumors that spread to the brain, such as lung, breast, colorectal cancer, melanoma, and renal cell carcinoma. Additionally, it covers various targeted treatment options, criteria for assessing treatment response, and the role of artificial intelligence in diagnosing, managing, and predicting prognosis for patients with brain metastases.
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“Despite these potential benefits, the deployment of digital tools for both healthcare and research purposes has proven challenging. Few have had success at securing regulatory approval for use, 2 and none have yet had a significant impact on either patient management or candidate therapeutic evaluation.”
From Developing digital health technologies for frontotemporal degeneration (2025) · cites this paper as [2]
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Developing digital health technologies for frontotemporal degeneration
Nevler, N., Niehoff, D., Gleixner, A. M., Dodge, S., Vogel, A. P., Hill, D. L., Ducharme, S., Staffaroni, A. M., Yunusova, Y., Au, R., et al. (2025) · Alzheimer's & Dementia · doi:10.1002/alz.70082 · Cited by 7
Metadata
- Authors
- Shukla, S., Karbhari, A., Rastogi, S., Agarwal, U., Rai, P., & Mahajan, A.
- Affiliations
- Homi Bhabha National Institute (IN)
- University of Liverpool (GB)
- Corresponding author
- Mahajan, A.
- Venue
- Clinical Radiology
- Publisher
- Elsevier BV
- Published
- 2024-07
- Volume
- 79
- Issue
- 7
- Pages
- 485-500
- ISSN
- 0009-9260 (ISSN-L)
- OpenAlex
- W4392881614
- Cited by
- 12
- References
- 93
- Citations by year
- 2026: 4 · 2025: 6 · 2024: 2
- FWCI
- 0.89
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Clinical Radiology (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Medicine › Oncology › Brain Metastases and Treatment
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Medical Imaging Techniques and Applications
- Health Sciences › Medicine › Oncology › Glioma Diagnosis and Treatment
- Keywords
- brain metastases, molecular imaging, precision oncology, lung cancer metastases, breast cancer metastasis, colorectal cancer metastasis, melanoma, renal cell carcinoma, treatment response assessment, AI-assisted diagnosis, imaging protocols
- MeSH terms
- Brain Neoplasms, Humans, Magnetic Resonance Imaging, Tomography, X-Ray Computed, Precision Medicine
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- Shukla, S., Karbhari, A., Rastogi, S., Agarwal, U., Rai, P., & Mahajan, A. (2024). Bench-to-bedside imaging in brain metastases: a road to precision oncology. Clinical Radiology. https://doi.org/10.1016/j.crad.2024.02.015
