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Structured Reporting Improves TNM Classification Accuracy and Radiologist Satisfaction

In a collaborative, multi-center study, radiology experts developed and validated in mint Lesion a software-assisted structured reporting (SR) framework for non-small cell lung cancer (NSCLC) staging.

Findings revealed that SR significantly improved TNM classification accuracy, reducing common errors in T-, N-, and M-staging compared to traditional free-text reports. Radiologists using SR were more likely to classify cases correctly and rated the tool highly for enhancing report quality, completeness, and interdisciplinary communication. This study suggests that SR may not only improve clinical accuracy but also support data standardization for future lung cancer research.

Read a summary of the study here.

Integrated prostate cancer workflow connecting radiology, urology, and pathology through structured reporting, MRI-guided biopsy, longitudinal follow-up, and AI-supported analysis.
mint Lesion supports an end-to-end prostate cancer workflow by connecting radiology, urology, and pathology within a unified digital environment. The platform enables structured mpMRI reporting, MRI/ultrasound fusion biopsy workflows, FHIR-based interoperability, active surveillance, and AI-supported quantification of metastatic disease.
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Research poster presentation on standardized tumor response assessments using mint Lesion at the NCCN Annual Conference 2026
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NCCN 2026: Memorial Sloan Kettering Cancer Center Presents Research on Structured Tumor Response Assessments with mint Lesion
Big congratulations to Steven Philemond and Alison Chiaramonte of Memorial Sloan Kettering Cancer Center for presenting their research poster “Use of…
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Radiologists participating in a hands-on lung cancer screening workshop using structured reporting software mint Lesion at RÖKO 2026
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Hands-On Workshop Lung Cancer Screening: From Initial Read to Consenus
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