MR Imaging Technique Promises More Reliable Cancer Screening and Diagnosis
|
By MedImaging International staff writers Posted on 13 Jun 2016 |

Image: The EU-funded Horizon 2020 GlucoCEST Imaging in Neoplastic Tumours Project (Photo courtesy of GLINT 2016).
A project to develop a novel advanced medical imaging technology is intended to enable earlier detection of cancer, increase survival rates, and allow for a patients’ full recovery.
The new imaging technology is intended to provide more reliable and less invasive cancer diagnosis based on a novel Magnetic Resonance Imaging (MRI) technique that could lead to game-changing diagnostic tools for cancer imaging, and enable personalized cancer treatment.
The European Union (EU)-funded GlucoCEST Imaging of Neoplastic Tumours (GLINT) project began in January 2016, and makes use of a technique called glucose-based Chemical Exchange Saturation Transfer (glucoCEST). The technique can be used to detect the massive native glucose uptake in tumors as they grow. Previously such glucose measurements had to be made using a radio-labeled glucose imaging agent, and Positron Emission Tomography (PET) imaging. The new technique does not require contrast agents and enables closer treatment monitoring.
Scientific Coordinator of GLINT, and inventor of the glucoCEST method Professor Xavier Golay, University College London (London, UK), said, “GLINT offers for the first time a possibility to bring to the clinics a much-touted new imaging technique, allowing to directly image by MRI native, non-labeled glucose the way PET does it using the expensive radio-labeled sugar analogue fluorodeoxyglucose (FDG). This represents among others a huge hope for pediatric patients and for everyone required to undergo continuous surveillance of cancer progression. It also carries the hope to reduce or at least significantly limit the costs of diagnostic cancer imaging.”
Related Links:
University College London
The new imaging technology is intended to provide more reliable and less invasive cancer diagnosis based on a novel Magnetic Resonance Imaging (MRI) technique that could lead to game-changing diagnostic tools for cancer imaging, and enable personalized cancer treatment.
The European Union (EU)-funded GlucoCEST Imaging of Neoplastic Tumours (GLINT) project began in January 2016, and makes use of a technique called glucose-based Chemical Exchange Saturation Transfer (glucoCEST). The technique can be used to detect the massive native glucose uptake in tumors as they grow. Previously such glucose measurements had to be made using a radio-labeled glucose imaging agent, and Positron Emission Tomography (PET) imaging. The new technique does not require contrast agents and enables closer treatment monitoring.
Scientific Coordinator of GLINT, and inventor of the glucoCEST method Professor Xavier Golay, University College London (London, UK), said, “GLINT offers for the first time a possibility to bring to the clinics a much-touted new imaging technique, allowing to directly image by MRI native, non-labeled glucose the way PET does it using the expensive radio-labeled sugar analogue fluorodeoxyglucose (FDG). This represents among others a huge hope for pediatric patients and for everyone required to undergo continuous surveillance of cancer progression. It also carries the hope to reduce or at least significantly limit the costs of diagnostic cancer imaging.”
Related Links:
University College London
Latest MRI News
- AI Reconstruction Tool Speeds Dynamic Breast MRI and Improves Cancer Detection
- International Study Assesses AI for Prostate Cancer MRI Interpretation
- AI Approach Could Shorten Advanced Brain MRI Scans by Up to 90%
- Cardiac MRI Measure Improves Risk Prediction in Tricuspid Regurgitation
- AI System Improves Accuracy of Cardiac MRI Interpretation
- Deep Learning Model Predicts Alzheimer’s Disease Outcomes from Baseline MRI
- Blood-Brain Barrier Imaging Adds Risk Insight to Standard Stroke MRI
- AI Body Composition MRI Analysis Predicts Cardiometabolic Disease Risk
- AI MRI Tool Quantifies Muscle Fat to Assess Cardiometabolic Risk
- Advanced MRI Visualizes CSF Motion Changes After Mild Traumatic Brain Injury
- MRI Tool Enables Long-Term Tracking of Transplanted Cardiac Cells
- MRI-Based AI Tool Supports Differentiation of Parkinsonian Syndromes
- MRI-Derived Biomarker Improves Risk Stratification in Glioblastoma
- Combined Imaging Approach Identifies Cause of Heart Attack without Coronary Blockage
- Advanced MRI System Detects Impaired Cardiac Oxygen Use in Minutes
- AI-Enhanced MRI Improves Image Quality in Arrhythmia Patients
Channels
Radiography
view channel
AI Tool Predicts Five-Year Breast Cancer Risk from Mammograms
Breast cancer risk assessment during routine screening is difficult because many women who develop the disease have no known genetic mutations or family history. Static risk tools provide limited discrimination... Read more
AI Mammography Tools Detect Early Breast Cancer Signs Years Before Diagnosis
Breast cancer screening aims to detect tumors before symptoms develop, but subtle mammographic changes can appear years before diagnosis and may be missed during routine reads. Delayed detection can lead... Read moreUltrasound
view channel
AI Ultrasound Platform Receives CE Mark for Prenatal Screening
Prenatal ultrasound is central to fetal anomaly screening, yet it remains one of the most technically demanding examinations in routine care. Because both image acquisition and interpretation are highly... Read more
Hybrid Imaging Platform Reveals How Sleep Supports Brain Waste Removal
The brain’s glymphatic system clears metabolic waste via cerebrospinal fluid and is thought to support neural health during sleep. Yet clinicians and researchers have struggled to observe its whole‑brain... Read moreNuclear Medicine
view channelNew PET Tracer Detects DVT and Pulmonary Embolism in One Scan
Deep vein thrombosis is the formation of clots in deep leg veins that can migrate to the lungs as pulmonary embolism. Rapid confirmation across both regions often requires multiple tests and can delay treatment.... Read more
Targeted PET Platform Guides Osteosarcoma Resection and Margin Verification
Osteosarcoma, an aggressive primary bone cancer that mainly affects children and adolescents, demands wide excision to prevent local recurrence. Surgeons must achieve negative margins while preserving... Read moreGeneral/Advanced Imaging
view channel
Virtual Staining Technique Creates Histology Images from CT Data
Pulmonary hypertension, a disorder marked by pathological remodeling of the pulmonary vessels, often requires detailed histologic assessment. Yet routine pathology remains anchored in labor‑intensive,... Read more
CT-Derived Biomarker Predicts Outcomes in Gastric Cancer
Gastric cancer, also known as stomach cancer, is the fifth most common malignancy worldwide and often shows heterogeneous outcomes even within the same stage. Prognostic estimates typically rely on tumor-centric... Read more
AI Tool Enhances Response Assessment and Survival Prediction in Pleural Mesothelioma
Pleural mesothelioma, a cancer that grows as a thin, irregular layer along the lung wall, is difficult to measure on imaging. Clinicians rely on diameter-based Response Evaluation Criteria in Solid Tumors... Read moreImaging IT
view channel
Ambient AI Reporting Platform Streamlines Radiology Reporting
Radiology departments face growing imaging volumes and staffing shortages, creating reporting bottlenecks and pressure to maintain turnaround times. Conventional dictation tools document findings after... Read more
Interactive AI Tool Supports Explainable Lung Nodule Assessment
Lung cancer is a leading cause of cancer mortality, and timely characterization of pulmonary nodules on chest computed tomography (CT) is essential for directing care. Interpreting nodule morphology demands... Read more
Breast Imaging Software Enhances Visualization and Tissue Characterization in Challenging Cases
Breast imaging can be particularly challenging in cases involving small breasts or implants, where image reconstruction and tissue characterization may be limited. Clinicians also need reproducible analysis... Read moreIndustry News
view channel
GE HealthCare Showcases AI-Enabled Nuclear Medicine Portfolio at SNMMI 2026
Nuclear medicine is expanding rapidly as health systems adopt theranostics and broaden access to radiopharmaceuticals, increasing demand for scalable operations and consistent diagnostic confidence.... Read more
GE HealthCare Highlights AI-Supported Radiation Therapy Tools at ESTRO 2026
At the European Society for Radiotherapy and Oncology (ESTRO) 2026 Congress in Stockholm, GE HealthCare is highlighting Intelligent Radiation Therapy (iRT), MIM Software innovations, and BK Medical surgical... Read more







 Guided Devices.jpg)