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deepc Expands Oncology AI Portfolio with CE-Marked Pancreatic CT Solution from SYCAI Medical

From incidental finding to structured follow-up in routine abdominal CT

Munich, Germany & Barcelona, Spain, February 23, 2026 – In abdominal CT reporting, the pancreas is often not the primary focus. A scan ordered for renal colic, trauma, or vascular assessment may still reveal a small cyst, ductal dilation, or subtle parenchymal change. Under increasing reporting volumes and time pressure, consistently identifying and documenting these findings remains demanding.

Pancreatic cancer continues to carry one of the lowest survival rates among major malignancies, largely due to late-stage diagnosis (Siegel et al., CA Cancer J Clin, 2023). Early imaging signs are frequently subtle. Incidental pancreatic findings that appear secondary at the time of reporting can later become clinically significant. Beyond initial detection, ensuring consistent characterization and structured follow-up across examinations adds further complexity.

To address this gap, deepc has partnered with SYCAI Medical, a company dedicated to AI solutions for abdominal cancer screening. SYCAI Medical has developed a CE-marked solution for automated detection and characterization of pancreatic lesions on adult CT scans. The software enables opportunistic screening of CT scans and supports comparison with prior studies, simplifying structured longitudinal assessment within routine workflows.

Integrated directly into existing PACS environments through deepcOS®, the solution operates within standard DICOM workflows and does not require additional imaging protocols or separate viewers. AI-supported findings are presented within the radiologist’s usual reporting interface, preserving clinical control while providing structured assistance. In high-volume CT interpretation, additional tools must support rather than interrupt workflow, and integration discipline is essential to avoid unnecessary alert burden.

Routine abdominal CT represents a significant opportunity for structured pancreatic evaluation at scale. Large numbers of scans performed for unrelated indications already contain clinically relevant information. Supporting consistent review and follow-up within these existing exams allows departments to strengthen pancreatic imaging without introducing parallel screening programs or workflow fragmentation.

With the addition of Sycai Medical Pancreas CT solution, deepc further strengthens its oncology AI coverage across both detection and longitudinal monitoring pathways. The partnership reflects a shared commitment to addressing high-impact diagnostic pressure points with clinically ready, infrastructure-integrated AI solutions.

By combining SYCAI Medical’s focused expertise in pancreatic CT analysis with deepc’s governed platform for scalable AI deployment, the collaboration expands access to structured pancreatic lesion assessment in everyday radiology practice.

About deepc

deepc enables the infrastructure layer that powers safe, vendor-neutral AI in medical imaging. Our platform, deepcOS®, spans the full product lifecycle: discovery, clinical validation, deployment, monitoring, and governance, so hospitals can adopt, scale, and continuously improve the AI tools that matter most to their workflows. Through rigorous, large-scale testing on independent and local data sets, deepc certifies every integrated algorithm for performance, robustness, and regulatory compliance. Clinicians can then easily activate best-in-class solutions across more than 80 indications, confident that patient safety and data privacy are protected by design. deepcOS® installs quickly and interfaces seamlessly with existing PACS/RIS, cloud, or on-prem environments. By abstracting complexity and preserving choice, deepc empowers radiology departments to build and evolve an AI-driven practice, faster, safer, and on their own terms today and into the future.

About SYCAI Medical

Sycai Medical is a Barcelona-based tech startup founded in 2020, dedicated to empowering radiologists through AI and big data. We develop AI-driven algorithms to assist in diagnosing abdominal lesions and predicting their evolution, enabling more precise diagnoses and improving the quality of life for patients with pancreatic lesions.