Be Central to the Insight: A Structured, Data-Driven Approach Across the Prostate Pathway

Workflow Integration and FHIR Connectivity

A smooth workflow is defined by how well information flows from one specialist to the next. In many conventional settings, communication bottlenecks can occur because findings are managed in isolation. While urologists often receive static text reports lacking spatial data, pathologists frequently provide results as separate, independent documents. In these siloed environments, correlating histological findings with the original radiological areas or volumes of interest remains a manual process that can lead to fragmented data and a lack of immediate feedback.

mint Lesion provides the digital infrastructure to bridge these gaps, transforming disconnected reports into a unified clinical stream. Radiologists utilize the platform as their central hub, aggregating data to address these barriers and to drive a continuous end-to-end workflow from imaging to diagnosis.

To facilitate this at a technical level, the software supports interoperability with FHIR servers through the exchange of both FHIR Observations and Diagnostic Reports. By adhering to the Implementation Guide developed in collaboration with the Medical Informatics Initiative (MII), mint Lesion promotes high-level data standardization. This connectivity allows the platform to integrate clinical parameters and transfer findings, including PI-RADS scores and volume measurements, directly back to the electronic health record as structured, actionable data.

Closing the Diagnostic Loop: A Unified Clinical View 

mint Lesion supports the integration of radiological, urological, and pathological findings into a unified history, allowing the clinical team to correlate histological results directly with the initial radiological assessments. This coordinated approach provides the multidisciplinary team with a consolidated view of the patient’s diagnostic journey, supporting informed treatment decisions without manual data reconciliation. 

The value of this integrated approach is best seen in its impact on daily clinical collaboration. Dr. Jan Rabe highlights how unifying these disparate data sources enhances the interdisciplinary partnership: 

“I appreciate our collaborative solution because it allows us to map the multi-stage process of prostate diagnostics interdisciplinarily - incorporating laboratory, radiology, urology, and pathology- within a single software platform. The participating departments can access pre-diagnostic data in mint Lesion at any point during the assessment. This facilitates interdisciplinary understanding, streamlines the interpretation of results, and saves us from having to gather data from multiple different sources.” Dr. Jan Rabe, Karlsruhe City Hospital. 

Long-Term Management and Active Surveillance 

As patients enter long-term monitoring, the radiologist’s role transitions from initial detection to longitudinal navigation. mint Lesion enables the tracking of prostate findings over time for MRI-based active surveillance, allowing radiologists to monitor subtle changes and compare historical data with high spatial precision. By providing this evidence-based continuity, you support informed decision-making for patient management and enhance the overall quality of care throughout the surveillance period. 

Managing Advanced Disease with Efficiency 

The end-to-end philosophy extends beyond primary diagnosis into the management of advanced prostate cancer. For patients with metastatic spread to the skeleton, mint Lesion includes integrated AI functionality for tumor load quantification in whole-body diffusion-weighted MRI (WB-DWI), covered by the CE mark of the device itself.

In cases of bone metastasis, manual delineation is a tedious and time-consuming process that often takes an hour or more per scan¹, making it impractical for routine clinical use. Consequently, without AI support, assessment in routine practice is typically qualitative rather than volumetric.

The underlying approach to automated skeletal delineation and WB-DWI quantification has been developed and described in the peer-reviewed literature.¹ This deep learning framework is implemented in mint Lesion, where segmentation results are presented in the reading environment for review, editing and approval by the radiologist before quantitative values such as total diffusion volume are recorded.

In a retrospective single-center study of 360 patients with metastatic castration-resistant prostate cancer, image processing from import of the complete whole-body MRI study to generation of the segmentation masks was performed with a reported median computation time of 90 seconds per examination; where manual refinement by the radiologist was required, this took an additional 4 to 6 minutes per case.² In that study, radiologists reviewed the segmentation alongside additional sequences such as T1-weighted images and relative fat fraction maps before approving the delineation.²

By aligning these distinct clinical phases within a single digital environment, mint Lesion moves the diagnostic process beyond fragmented data toward a unified patient history. This integrated approach supports the clinical team in maintaining consistency from the first image to the final treatment plan, ensuring that every diagnostic contribution remains a visible and accessible part of the patient journey. 

Position your expertise at the center of the clinical team with a connected, data-driven workflow. Request a personalized demo to see how you can remain central to the insight. 

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¹Candito, A., Blackledge, M. D., Holbrey, R. et al. AI-driven software for automated quantification of skeletal metastases and treatment response evaluation using whole-body diffusion-weighted MRI (WB-DWI) in advanced prostate cancer, Phys. Med. Biol. (2025). https://doi.org/10.1088/1361-6560/ae19c5

² D'Erme L, Avesani G, Russo L, et al. Total diffusion volume on whole-body diffusion-weighted imaging is a strong prognostic marker of disease survival in metastatic castration-resistant prostate cancer. Eur Radiol. 2026. https://doi.org/10.1007/s00330-026-12792-1