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…
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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…
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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…
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How can complex tumor findings be assessed accurately, reproducibly, and in line with clinical guidelines?
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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…
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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,…
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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…
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Hepatocellular carcinoma (HCC) is often diagnosed too late, limiting treatment options and survival. The RACOON-MARDER project aims to change that. By combining MRI imaging, clinical data, and…
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mint Lesion's Research Suite is an advanced imaging research platform designed to support academic teams in streamlining and scaling their imaging studies across single or multiple centers. Built to…
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How are structured reporting and artificial intelligence transforming radiology practice? Prof. Dr. Thorsten Persigehl from University Hospital Cologne shares how mint Lesion makes prostate…
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