ReviewMolecular diagnosis & therapy2019
The Continuing Evolution of Molecular Functional Imaging in Clinical Oncology: The Road to Precision Medicine and Radiogenomics (Part I).
Review in Molecular diagnosis & therapy, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
17 citing papers in PubMed.
- Editorial: Advancing cancer imaging technologies: bridging the gap from research to clinical practice.Frontiers in oncology · 2026Article
- Ultrasound-based radiogenomics: status, applications, and future direction.Ultrasonography (Seoul, Korea) · 2025Article
- Comprehensive Guide to Randomized Controlled Trials in Radiology: Everything You Need to Know.The Indian journal of radiology & imaging · 2025Article
- Injectable hydrogel encapsulating siMMP13 with anti-ROS and anti-apoptotic functions for osteoarthritis treatment.Journal of nanobiotechnology · 2024Article
- Imaging Recommendations for Diagnosis and Management of Primary Parathyroid Pathologies: A Comprehensive Review.Cancers · 2024Review
- Metaheuristic integrated machine learning classification of colon cancer using STFT LASSO and EHO feature extraction from microarray gene expressions.Scientific reports · 2024Article
- Deep-Learning-Based Predictive Imaging Biomarker Model for EGFR Mutation Status in Non-Small Cell Lung Cancer from CT Imaging.Cancers · 2024Article
- Editorial: Editor's challenge: Abhishek Mahajan - how can precision oncology be advanced with validated imaging-based nomograms?Frontiers in oncology · 2024Article
- Molecular and functional imaging in cancer-targeted therapy: current applications and future directions.Signal transduction and targeted therapy · 2023Review
- Deep learning based automated epidermal growth factor receptor and anaplastic lymphoma kinase status prediction of brain metastasis in non-small cell lung cancer.Exploration of targeted anti-tumor therapy · 2023Article
- Standardized uptake value (SUVCancer biology & therapy · 2020Article
- Article
- Nanoparticle Surface Functionalization: How to Improve Biocompatibility and Cellular Internalization.Frontiers in molecular biosciences · 2020Review
- A Novel Approach for Fully Automatic Intra-Tumor Segmentation With 3D U-Net Architecture for Gliomas.Frontiers in computational neuroscience · 2020Article
- A bird's-eye view of deep learning in bioimage analysis.Computational and structural biotechnology journal · 2020Review
- Integrating Small Animal Irradiators withFunctional Imaging for Advanced Preclinical Radiotherapy Research.Cancers · 2019Review
- An Update of AI and Radiomics in Precision Oncology: Insights from Liver Tumors as Case Models.Technology in cancer research & treatmentReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The present era of precision medicine sees 'cancer' as a consequence of molecular derangements occurring at the commencement of the disease process, with morphologic changes happening much later in the process of tumorigenesis. Conventional imaging techniques, such as computed tomography (CT), ultrasound, and magnetic resonance imaging (MRI), play an integral role in the detection of disease at a macroscopic level. However, molecular functional imaging (MFI) techniques entail the visualisation and quantification of biochemical and physiological processes occurring during tumorigenesis, and thus has the potential to play a key role in heralding the transition from the concept of 'one size fits all' to 'precision medicine'. Integration of MFI with other fields of tumour biology such as genomics has spawned a novel concept called 'radiogenomics', which could serve as an indispensable tool in translational cancer research. With recent advances in medical image processing, such as texture analysis, deep learning, and artificial intelligence (AI), the future seems promising; however, their clinical utility remains unproven at present. Despite the emergence of novel imaging biomarkers, a majority of these require validation before clinical translation is possible. In this two-part review, we discuss the systematic collaboration across structural, anatomical, and molecular imaging techniques that constitute MFI. Part I reviews positron emission tomography, radiogenomics, AI, and optical imaging, while part II reviews MRI, CT and ultrasound, their current status, and recent advances in the field of precision oncology.
Indexed as
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30411216What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.