Oncology clinical-trial imaging

VTrial: Regulatory-grade imaging AI for oncology response assessment

Integrated into pharma-sponsored prospective clinical trials for both RECIST response assessment and advanced lesion-level efficacy endpoints, under FDA-reviewed trial protocols.

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VTrial longitudinal assessment interface showing CT-based lesion tracking, target lesion measurement, total tumor burden, timepoint response, lesion mapping, longitudinal trend, and advanced analytics features.
01 Use cases & clinical evidence

One platform. Five clinical applications.

AI-powered RECIST

Standardize and accelerate RECIST 1.1 assessment.

AI-powered end-to-end workflow for lesion detection, measurement, longitudinal tracking, target-lesion preselection, and response assessment across RECIST 1.1, RECIP 1.0, RANO-BM, Lugano, and other established criteria, improving both reproducibility and reader efficiency by more than 50%.

Supporting evidence
ESMO 2026 · Prospective AI-assisted RECIST
To our knowledge, the first reported prospective deployment of AI-assisted RECIST in an oncology clinical trial, providing evidence for the feasibility of integrating imaging AI directly into prospective trial workflows.
Publication forthcoming
02 Regulatory engagement & prospective deployment

From regulatory dialogue to prospective clinical implementation.

VTrial combines direct regulatory scientific engagement with deployment in pharma-sponsored prospective oncology trials.

FDA CDER + CDRH

Critical Path Innovation Meeting

Vysioneer participated in a Critical Path Innovation Meeting with FDA CDER and CDRH focused on the role of AI image analysis in oncology drug development.

“Artificial Intelligence (AI) image analysis software for supporting the evaluation of oncology drug efficacy in clinical trials”
FDA scientific engagement
Prospective clinical deployment

Prospective deployment following FDA guidance

Following FDA guidance, VTrial has been integrated into pharma-sponsored prospective clinical trials for both RECIST response assessment and advanced lesion-level efficacy endpoints, under FDA-reviewed trial protocols.

RECIST + advanced lesion-level efficacy endpoints
03 Governance

Built for clinical-trial use.

Quality, validation, security, and risk-based AI governance are integrated into the platform and study workflow.

Q

Quality system

Controlled design, development, release, change management, and risk management.

ISO 13485 · ISO 14971
V

Trial validation

Study-specific intended use, validation, audit trails, and traceable final assessments.

ICH E6(R3) · 21 CFR Part 11
S

Privacy & security

Controlled access, encryption, data minimization, secure transfers, and incident response.

ISO 27001 · HIPAA · GDPR
EU

EU AI Act alignment

Risk-based AI governance, including performance monitoring, traceability, and lifecycle controls, aligned with the EU AI Act.

EU AI ACT
04 Featured clinical evidence

Selected studies. Broader proof.

ESMO 2026
RECIST
Prospective clinical trial deployment

AI-assisted RECIST 1.1 in a prospective oncology trial

To our knowledge, the first reported prospective deployment of AI-assisted RECIST in an oncology clinical trial, supporting a program that advanced directly from Phase 1 to Phase 3.

Publication forthcoming →
WCLC 2026
IMG + ctDNA
Pfizer CROWN study · Multimodal analysis

Longitudinal AI-derived total tumor burden + ctDNA to predict PFS

AI-derived longitudinal total tumor burden combined with ctDNA to improve prediction of progression-free survival in the Phase 3 CROWN study.

Publication forthcoming →
ESMO 2023 & Neuro-Oncology Advances
TOTAL TUMORBURDEN
Lesion-level analysis · Phase 3 NSCLC

Early volumetric response across all intracranial lesions

Early volumetric response across all intracranial lesions showed stronger prognostic association with systemic PFS than RECIST target-lesion measurements.

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ESMO 2025
RADIOMICS
Pfizer CROWN study · Phase 3

AI-derived radiomics to predict clinical outcomes

Granular CT radiomics features characterized tumor heterogeneity and identified imaging signatures associated with progression-free survival in the Phase 3 CROWN study.

Highlighted by ESMO Daily Reporter
Read the publication →
CPT: Pharmacometrics & Systems Pharmacology
TGI MODELING
Lesion-level modeling

Lesion-level tumor growth inhibition modeling

AI-generated longitudinal lesion measurements enable more robust TGI modeling beyond aggregated RECIST, revealing lesion-level treatment dynamics and stronger prognostic association with PFS.

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Explore all publications and clinical evidence →

Map VTrial to your primary and exploratory endpoints.

Discuss a study-specific workflow for AI-assisted response assessment, lesion-level efficacy data, or novel imaging biomarkers.

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