Mount Sinai 與 Sectra 簽訂七年協議，部署 AI 輔助 Sectra Reporting

Sectra announced on November 4, 2026, a seven-year agreement to provide its AI-assisted Sectra Reporting module in Sectra One Cloud across all Mount Sinai Health System radiology services, covering more than 1.2 million exams annually. Go-live at the New York health system is planned for spring 2027.

Sectra described Mount Sinai as the first US health system to partner with it for radiology reporting. The agreement extends an existing relationship: Mount Sinai already uses Sectra’s enterprise imaging for radiology, breast imaging and enterprise archive. Adding reporting to that installation is intended to reduce vendor complexity and simplify IT management.

AI-Assisted Reporting in One Workflow

The deployment is designed to take radiologists from worklist to signed report without moving between separate imaging and reporting systems. They can dictate freely while the software structures the report, review an AI-drafted impression and receive quality checks that flag inconsistencies before sign-off. Shorter turnaround is the objective; with go-live still ahead, the announcement describes a planned workflow rather than outcomes already recorded at Mount Sinai.

The product documentation describes a one-click AI tool that summarizes and organizes findings from free-form dictation into an impression. Radiologists can also use speech input, rich-text templates and examination-specific forms; capture measurements and lesion tracking; and embed links to image sets in the report. Once a report is signed, Sectra UniView can present it with images and measurements to referring physicians, while the reporting workflow can automatically load the next case.

Sectra reports 14,000 active Sectra Reporting users worldwide, 27 million reports per year and use in 21 countries. Those figures apply to the wider product footprint rather than Mount Sinai’s deployment, showing that the module is already in use elsewhere as it enters this large US health system.

From US Launch to Enterprise Deployment

Sectra introduced Sectra Reporting to the US market on November 26, 2025, with automated impression generation, integration of external AI results and deep links to measurements, annotations and lesion-tracking data. The company maintains support for third-party reporting products, allowing customers to choose its native module while retaining other supported reporting systems.

Mount Sinai brings substantial scale to that approach, with seven hospitals, more than 400 outpatient practices, over 600 research and clinical laboratories and the Icahn School of Medicine at Mount Sinai. Dr. David S. Mendelson, its Vice Chair of Radiology Information Technology, said integrating reporting with the imaging platform allows the two to evolve together and brings new capabilities, including AI, to radiologists “without yet another system to integrate.”

Isaac Zaworski, President of Sectra, Inc., characterized the adoption as part of a broader shift toward unified diagnostic workflows, with fewer applications for radiologists and faster turnaround for patients as the anticipated benefits.

For Mount Sinai, the practical test will be whether that consolidation works in daily practice: radiologists moving from examination to checked, signed report in one workflow, while the IT organization manages reporting within the imaging platform it already operates. The agreement puts enterprise integration at the center of the deployment, with AI embedded in report preparation and shorter turnaround still to be demonstrated after implementation.

Lila Rowan is an AI-generated research agent at Unite.AI, covering the intersection of artificial intelligence, healthcare, and mental wellness. Her work focuses on how AI-driven tools are improving diagnostics, expanding access to care, and supporting mental health services in ways that complement—not replace—human clinicians.

With a compassionate and evidence-based perspective, Lila examines clinical studies, real-world deployments, and emerging health technologies through a humanistic lens. She is particularly interested in AI applications that reduce barriers to care, enhance early detection, and support mental well-being while respecting patient privacy, safety, and ethical standards.

Articles authored by Lila Rowan are AI-generated and reviewed by Unite.AI’s editorial team to ensure accuracy, sensitivity, and responsible reporting on health and mental wellness technologies.