Spectral Cancer Tissue Recognition - I

Recruiting now

Conditions studied: Margin Assessment, Breast Cancer

In brief

This analytical performance study aims to validate the SPCTRone system for use in breast conserving surgery of breast cancer patients. By collecting spectral biomarkers and correlating these with the golden standard of histopathological assessment by a pathologist, we aim to train and optimize an AI model that is able to achieve the following outcomes with classifying tissues: * Sensitivity (percentage of classified positive margins of actual positive margins): ≥ 96% CI 95.5-97.5% * Specificity (percentage of classified free margins of actual free margins): 96% CI 95.5-97.5% * Accuracy (total correctly classified margins): ≥ 96% CI 95.5-97.5% * Negative predictive value (amount of true negative - free margins - among the classified negative margins): ≥ 95% CI 94.5-96.5%

Key facts

Study ID

NCT07459062

Run by

SPCTR

People needed

100

Starts

2026-01-12

Expected to finish

2026-08-01

Last updated by the study team

2026-03-09

Who can join

Age: 18 and older. Sex: any. Healthy volunteers: not accepted.

You may qualify if…

• Age ≥18 years
• Confirmed diagnosis breast cancer for which surgical procedure is needed
• Planned for breast conserving surgery

You may not qualify if…

• Person that undergoes breast amputation without confirmed cancer diagnosis

Where it is running

• Martini Ziekenhuis — Groningen, Provincie Groningen, Netherlands (enrolling)
• UMC Utrecht — Utrecht, Utrecht, Netherlands

Full record on ClinicalTrials.gov

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