ReviewCancers2016
Imaging in Colorectal Cancer: Progress and Challenges for the Clinicians.
Review in Cancers, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 48 papers, 2 of them syntheses that pooled it.
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
48 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Surveillance After Pelvic Exenteration: A Systematic Review of Oncological and Functional Follow-Up.ANZ journal of surgery · 2026Pooled it
- Artificial intelligence in magnetic resonance imaging for predicting lymph node metastasis in rectal cancer patients: a meta-analysis.European radiology · 2025Pooled it
- Metastatic Colorectal Cancer Treatment Response Evaluation by Ultra-Deep Sequencing of Cell-Free DNA and Matched White Blood Cells.Clinical cancer research : an official journal of the American Association for Cancer Research · 2023Trial
- Multimodal radiomics for precision management of colorectal cancer.Discover oncology · 2026Review
- Spectral CT imaging in colorectal cancer: current applications, limitations, and future perspectives.Insights into imaging · 2026Review
- Predicting liver metastasis in colorectal cancer patients using routine biochemical tests enhanced by machine learning.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026Article
- The prognostic role of inflammation-based hematologic markers in stage I-III colorectal cancer: a retrospective analysis.BMC cancer · 2025Article
- Review
- Photoacoustic-Integrated Multimodal Approach for Colorectal Cancer Diagnosis.ACS biomaterials science & engineering · 2025Review
- Fe(III)-Based Nanomicelles for Magnetic Resonance Imaging of Colorectal Cancer with Hepatic Metastasis.Journal of functional biomaterials · 2025Article
- Review
- Advances in the diagnosis of colorectal cancer: the application of molecular biomarkers and imaging techniques: a literature review.Annals of medicine and surgery (2012) · 2025Review
- A new paradigm in postoperative colorectal cancer surveillance: integrating advanced imaging and multi-omics.Frontiers in physiology · 2025Review
- LC-MS/MS analysis reveals plasma protein signatures associated with lymph node metastasis in colorectal cancer.Frontiers in immunology · 2024Article
- Article
- PET/CT in assessment of colorectal liver metastases: a comprehensive review with emphasis onClinical & experimental metastasis · 2023Review
- Applying Deep Transfer Learning to Assess the Impact of Imaging Modalities on Colon Cancer Detection.Diagnostics (Basel, Switzerland) · 2023Article
- Detection of Hepatic Metastasis in Colorectal Cancer: A Comparative Case Report ofJournal of the Belgian Society of Radiology · 2023Article
- Postoperative circulating tumor DNA testing based on tumor naïve strategy after liver metastasis surgery in colorectal cancer patients.Frontiers in oncology · 2023Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The use of imaging in colorectal cancer (CRC) has significantly evolved over the last twenty years, establishing important roles in surveillance, diagnosis, staging, treatment selection and follow up. The range of modalities has broadened with the development of novel tracer and contrast agents, and the fusion of technologies such as positron emission tomography (PET) and computed tomography (CT). Traditionally, the most widely used modality for assessing treatment response in metastasised colon and rectal tumours is CT, combined with use of the RECIST guidelines. However, a growing body of evidence suggests that tumour size does not always adequately correlate with clinical outcomes. Magnetic resonance imaging (MRI) is a more versatile technique and dynamic contrast-enhanced (DCE)-MRI and diffusion-weighted (DW)-MRI may be used to evaluate biological and functional effects of treatment. Integrated fluorodeoxyglucose (FDG)-PET/CT combines metabolic and anatomical imaging to improve sensitivity and specificity of tumour detection, and a number of studies have demonstrated improved diagnostic accuracy of this modality in a variety of tumour types, including CRC. These developments have enabled the progression of treatment strategies in rectal cancer and improved the detection of hepatic metastatic disease, yet are not without their limitations. These include technical, economical and logistical challenges, along with a lack of robust evidence for standardisation and formal guidance. In order to successfully apply these novel imaging techniques and utilise their benefit to provide truly personalised cancer care, advances need to be clinically realised in a routine and robust manner.
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What 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.