ReviewMolecular diagnosis & therapy2019
The Continuing Evolution of Molecular Functional Imaging in Clinical Oncology: The Road to Precision Medicine and Radiogenomics (Part II).
Review in Molecular diagnosis & therapy, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 5 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
5 citing papers in PubMed.
- Deep-Learning-Based Predictive Imaging Biomarker Model for EGFR Mutation Status in Non-Small Cell Lung Cancer from CT Imaging.Cancers · 2024Article
- Molecular and functional imaging in cancer-targeted therapy: current applications and future directions.Signal transduction and targeted therapy · 2023Review
- Imaging Techniques in Pharmacological Precision Medicine.Handbook of experimental pharmacology · 2023Article
- Radiomic Features Associated with Extent of Resection in Glioma Surgery.Acta neurochirurgica. Supplement · 2022Review
- Overall Survival Prediction in Glioblastoma With Radiomic Features Using Machine Learning.Frontiers in computational neuroscience · 2020Article
Corrections and comments
- Erratum issued
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 morphological changes happening much later in the process of tumourigenesis. Conventional imaging techniques, such as computed tomography (CT), ultrasound (US) and magnetic resonance imaging (MRI) play an integral role in the detection of disease at the macroscopic level. However, molecular functional imaging (MFI) techniques entail the visualisation and quantification of biochemical and physiological processes occurring during tumourigenesis. MFI has the potential to play a key role in heralding the transition from the concept of "one-size-fits-all" treatment 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, the future seems promising; however, their clinical utility remains unproven at present. Despite the emergence of novel imaging biomarkers, the 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
Identifiers
30387041What 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.