AI-Based Decision Support for Professionals

Professionals, Unfold AI, Prostate Cancer Treatment Decision, AI-Based Decision Support

First and Only FDA Cleared AI-Based Prostate Cancer Decision Support Platform

510k FDA Cleared, Unfold AI Prostate Professionals, AI-Based Decision Support

NOV 2022

Cleared by the FDA for AI-Based Decision Support

FDA Awarded breakthrough device designation. Unfold AI Prostate Professionals, AI-Based Decision Support

MAY 2021

Granted Breakthrough Device Designation by the FDA

AUG 2023

Stanford Study Validated Accuracy and Effectiveness of Unfold AI

AUG 2023

SOC2 Compliant

A New Superpower For Doctors

Tumor Characterization, Treatment Guidance, Treatment Selection, Patient consultation. Unfold AI Prostate Professionals, AI-Based Decision Support

Unfold AI combines patient specific data and deep learning algorithms to create a unique personalized cancer estimation map that visualizes the size and extent of cancer in 3D

Are you a doctor looking to incorporate AI-based decision support into your practice?

Download physician Brochure

Clinically Validated Performance Beyond the Standard of Care

Unfold AI Prostate Professionals, AI-Based Decision Support

References: [1] [2] [3] [4] [5]

Unfold AI Research Highlights

Cancer Mapping and Treatment Success Encapsulation Extracapsular Extension Prediction Tumor Volume Encapsulation Confidence Score

Cancer Mapping and Treatment Success

Unfold AI was used to predict the extent of tumors in surgically removed prostate specimens. It predicted tumor margins more accurately than conventional methods.

This approach could improve and standardize treatment margin definition, potentially reducing cancer recurrence rates. Furthermore, an accurate assessment of negative margin probability could facilitate informed decision-making for patients and doctors.

- The average sensitivity of detecting cancer was higher for AI (97%) than for radiologists (37%)
- For index lesions, Unfold AI margins were more often negative (90%) than conventional ROIs (0%, p < 0.001), 10-mm ROI margins (82%, p = 0.24), and hemigland margins (66%, p = 0.004).

Read full paper here

Encapsulation

Extracapsular Extension Prediction

Unfold AI accurately predicted ECE risk, outperforming conventional methodologies. It notably improved ECE prediction over MRI in posterior quadrants, with the potential to inform nerve-spare technique and prevent positive margins.

Clinicians furnished with Unfold AI's ECE risk assessments would have the potential to stage prostate cancer and assess risk more precisely, leading to improved outcomes and quality of life for patients.

- Unfold AI had a significantly higher area under the curve (AUC = 0.81, p < 0.05) than conventional predictors such as MRI (AUC = 0.72) and Partin Tables (0.64).

Read full paper here

Tumor Volume

Unfold AI was shown be highly predictive of true tumor volume measured on prostatectomy specimens, outperforming conventional clinical measures.

More accurate tumor volume assessments may improve risk assessment and treatment strategy selection, particularly when defining margins for focal ablation or radiation dosing.

- 97 patients met study eligibility criteria. Unfold AI cancer estimation maps were strongly correlated to true tumor volume with R² = 0.81
- All conventional metrics were significantly less accurate than Unfold AI including total length of clinically-significant prostate cancer in all cores (R² = 0.69)

Read full abstract here

Encapsulation Confidence Score

Unfold AI's Encapsulation Confidence Score accurately predicted clinically-significant prostate cancer encapsulation probability in an independent population of intermediate-risk prostate cancer patients, demonstrating its utility to assess focal therapy suitability and margin efficacy.

This metric could be used to improve and standardize patient selection and margin definition for prostate cancer focal therapy.