PreciseDx's New AI-Powered Digital Test Predicts Early Breast Cancer Recurrence

The new digital test from PreciseDx, which utilizes AI, has been analytically validated to predict the recurrence of early-stage breast cancer with high precision. This test provides greater accuracy than traditional methods, representing a significant advancement in personalized cancer care and contributing to the global standardization of breast cancer treatments.

A new AI-Powered digital breast cancer test, developed by PreciseDx, has shown promising results in predicting the recurrence of early-stage breast cancer within six years, a recent study published in the Clinical Breast Cancer journal reveals. The test, named PreciseBreast, utilizes advanced artificial intelligence (AI) to analyze histology images for better accuracy in prognosis.

PreciseDx's breakthrough involves a meticulous validation process, scrutinizing the precision, repeatability, reproducibility, and resistance to interference of the test's methodology. This has ensured that the PreciseBreast assessment can reliably predict the risk of early-stage breast cancer returning.

Michael J. Donovan, Co-founder and Chief Medical Officer of PreciseDx, emphasizes the significance of this innovation for the global standardization of breast cancer care and commented,

"This accomplishment marks a crucial milestone in our ongoing mission to empower individuals and healthcare professionals with the latest advancements in breast cancer management. With PDxBR, clinicians will have additional precision data to support their treatment recommendations. The importance of these results is the demonstration of reliability for an assessment process that has the potential to improve accessibility and standardization to breast cancer patients around the globe and ultimately elevate the standard of care for patients."

The AI-powered test goes beyond traditional grading approaches by examining invasive breast cancer (IBC) histology images with its Morphology Feature Array—a method that stands to revolutionize how patient care is administered. The assay has been approved for use by the New York State Department of Health, marking a key milestone in its clinical adoption.

According to the study's abstract, the PreciseBreast test employs AI to analyze microanatomic features from stained whole slide images of IBC. It considers a range of factors, including patient age, tumor size, stage, and lymph node status, in its risk assessment algorithm. The validation process confirmed the test's high precision in identifying tumor segments, lymphocytes, and mitotic figures. Furthermore, the risk score's consistency was maintained with minimal variability, demonstrating the test's robustness against common histopathological preparation variations.

The results are a testament to the high degree of precision achieved by the test, which has been analytically validated to perform consistently well across all model features, complementing the clinical validation previously attained.

This development heralds a significant step forward in the field of oncology diagnostics, offering more accurate and actionable insights into disease progression, and could potentially equalize the standard of care for breast cancer patients worldwide.

Abstract of the research

About Author: Mithat Can Turan

I am a software developer and a 4th-year Computer Engineering student at the Turkish-German University. I have worked on numerous software projects, especially those related to healthcare. My primary interests lie in digital health and AI applications within healthcare projects. I closely follow the latest developments in AI and digital health.