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163 result(s)
Medical professional reviewing patient's MRI images on computer monitor with patient in MRI machine in background.
Postoperative Brain MRI After Tumor Resection: Reducing Artifacts and Improving Diagnostic Accuracy

Postoperative MRI after brain tumor surgery is often affected by artifacts caused by intracranial air, limiting reliable image interpretation. A recent study shows that TGSE-BLADE DWI significantly…

Centralized Management for Clinical Trial Communications and Workflows

Requests for radiological clinical trial evaluations frequently rely on fragmented methods such as emails, phone calls, and spreadsheets. This decentralized approach often leads to communication…

A collaborative session between a radiologist and an investigator analyzing multicentric trial progress and quantitative imaging data on a centralized dashboard.
Integrated Data Management for Multicentric Imaging in Investigator-Initiated Trials (IITs)

Establishing a Framework for Multicentric Data Coordination For many investigators, the transition from a single-site study to a multicentric model introduces significant logistical shifts in data…

Standardized response criteria evaluation in mint Lesion featuring the TGRM module.
From Theory to Practice: Evaluating g-values within mint Lesion

Following the FDA’s recent analysis of the growth rate constant (g) as a prognostic marker1, the challenge for many research organizations is implementation. mint Lesion provides a commercially…

mint Lesion usage during a clinical trial read, featuring the TGRM export tool.
Bridging the Gap Between RECIST and Survival: Why the FDA’s Analysis of the g Value is a Game-Changer

For decades, oncology trials have relied on RECIST 1.1 to evaluate drug efficacy. However, these categorical "snapshot" evaluations do not always correlate perfectly with Overall Survival (OS) or…

PET scans of torso with relevant false positives highlighted by red dotted circles, true positives in green
LMU University Hospital: Artificial Intelligence for TNM Staging in NSCLC – How Reliable Are AI-Based Segmentations?

The recent study “Artificial intelligence for TNM staging in NSCLC – a critical appraisal of segmentation utility in [¹⁸F]FDG PET/CT” provides a critical evaluation of the clinical value of…

Participants at the RECIST and Beyond workshop in Cologne during hands-on training with mint Lesion for structured tumor response assessment.
Successful “RECIST and Beyond” Workshop in Cologne: Advancing Precision in Oncologic Imaging

How can complex tumor findings be assessed accurately, reproducibly, and in line with clinical guidelines?

Screenshot of the mint Lesion interface showing RANO 2.0 configuration, tumor burden calculations, and structured neuro-oncology assessment tools.
Implementing RANO 2.0 for Neuro-Oncology Clinical Trials in mint Lesion

Tumor response assessment in neuro-oncology clinical trials requires careful attention to measurement protocols and confirmation scan requirements. To address evolving research needs and standardize…

Interview with Prof. Timm Denecke about the RACOON-MARDER project and AI-powered early detection of liver cancer using MRI
“Making the Invisible Visible”: How RACOON-MARDER Aims to Improve Early Detection of Liver Cancer Using MRI and AI

Hepatocellular carcinoma (HCC) is a potentially deadly tumor. The decisive factor is the timing of diagnosis: if HCC is detected early, there is a chance for complete removal and, in the best case,…

Image of a patient getting an MRI scan, signifying how RACOON projects in Germany show how imaging, structured reporting, and AI jointly advance clinical research.
RACOON – Imaging, Data & Collaboration for Better Decisions

Modern radiology faces a central question: how can imaging and clinical data be combined in a way that leads to more precise diagnoses, better-informed decisions, and more individualized…