InferCare RECIST

by Beijing Infervision Healthcare Medical Technology Co., Ltd.  · Based in China → — AI for Better Health
Interventional Radiology Oncology Radiology
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Regulatory Status Disclosed

Overview

InferCare RECIST is an AI-powered post-processing software application designed to assist trained medical professionals in evaluating and managing tumors in various organs, tissues, and other anatomical structures based on RECIST criteria. It aims to replace time-consuming manual measurements with automated, reproducible analysis, thereby streamlining workflows and reducing variability in clinical practice. The software offers functionalities for lesion measurement, registration, tracking, and RECIST reporting, including tools for interactive segmentation and 3D reconstruction visualization. InferCare RECIST utilizes artificial intelligence algorithms for automated lesion segmentation and registration, with results requiring confirmation by a medical professional. The software is intended for use by radiologists, oncologists, and other trained healthcare professionals, integrating seamlessly into existing clinical workflows. It is part of Infervision’s broader InferCare series, which focuses on patient health management.

Reviewed by Pouyan Golshani, MD — Interventional Radiologist

Key Features

  • AI-powered automated lesion segmentation and registration
  • Multi-time-point CT image processing and analysis
  • Lesion measurement, registration, and tracking
  • RECIST report generation
  • Interactive segmentation
  • 3D reconstruction visualization
  • Automated, reproducible analysis of tumor response
  • Longitudinal tracking across timepoints
  • Streamlined oncology workflows
  • Reduced variability in clinical practice

Use Cases

  • Evaluating tumor response based on RECIST criteria
  • Managing tumors in various organs and tissues
  • Monitoring treatment efficacy in oncology
  • Standardizing tumor assessment in clinical practice
  • Supporting decision-making across care teams in oncology

What Physicians Need to Know

Key Capabilities
InferCare RECIST is an intelligent platform designed for tumor imaging follow-up and therapeutic response evaluation. It supports multi-organ, multi-time-point, and multi-dimensional lesion tracking and analysis. Key capabilities include AI multi-dimensional lesion analysis (automatically assessing diameter, volume, and other metrics), cross-timepoint lesion comparison (clearly visualizing tumor progression or treatment response), and automated structured reports (generating richly illustrated, standardized RECIST evaluation reports). The software also offers interactive segmentation tools for 3D segmentation and measurement results.
Clinical Utility
This tool enhances accuracy and consistency in radiological assessment and provides systematic support for oncology multidisciplinary teams (MDTs), preoperative evaluation, and neoadjuvant therapy assessment. It assists clinicians in evaluating tumor response based on RECIST criteria, replacing time-consuming manual measurements with automated, reproducible analysis. By enabling consistent lesion measurement and longitudinal tracking across timepoints, InferCare RECIST helps streamline workflows and reduce variability in clinical practice, supporting more efficient treatment monitoring and confident decision-making.
Integration Options
InferCare RECIST can be installed in a healthcare facility or a cloud-based platform. It ingests medical imaging data compliant with the DICOM standard and supports multi-timepoint image registration. InferVision's AI models, including InferCare RECIST, have been integrated into the Microsoft Precision Imaging Network (Microsoft + Nuance) for cloud deployment, enabling accelerated, standardized, and widely accessible intelligent imaging workflows for healthcare institutions worldwide.
Compliance Status
InferCare RECIST has received U.S. Food and Drug Administration (FDA) clearance. This clearance signifies that the product has met applicable premarket requirements through regulatory pathways. The algorithm performance has been validated through performance testing, and cybersecurity and vulnerability analyses were conducted, confirming its conformity to cybersecurity requirements.
User Experience
The software is intended for use by radiologists, oncologists, and other trained healthcare professionals, and integrates seamlessly into existing clinical workflows. It aims to replace time-consuming manual measurements with automated, reproducible analysis. The software utilizes AI algorithms for automated lesion segmentation and registration, with results requiring confirmation by a medical professional.
Implementation Complexity
The software can be installed in a healthcare facility or a cloud-based platform. It ingests DICOM-compliant medical imaging data and supports multi-timepoint image registration. While AI tools can streamline assessment, implementing RECIST itself can be complex, with challenges such as subjectivity in lesion selection and variability in measurements across sites and radiologists.
Evidence Base
The algorithm performance of InferCare RECIST has been validated through performance testing. For the primary endpoint (Match Rate), 183 out of 184 paired target objects were successfully matched across prior and primary scans by InferCare RECIST, with a patient-level bootstrapping Match Rate of 0.995 (95% CI: 0.986-1.000). For the secondary endpoint (Centroid Error Distance), the MAE was 2.44mm (95% C.I.: 2.22mm-2.68mm). The device is considered substantially equivalent to a predicate device in intended use, main functions, operating principles, and safety features. InferVision leverages NVIDIA's advanced MONAI framework and TensorRT-accelerated inference to enhance AI development.
Physician Tip

InferCare RECIST can significantly reduce the manual burden of tumor measurement and tracking, allowing for more consistent and reproducible RECIST assessments. Always review and confirm the AI-generated segmentations and measurements, as the software is designed to assist, not replace, clinical judgment. Pay close attention to the automated structured reports for a comprehensive overview of tumor progression or response. Consider how this tool can be integrated into your existing workflow to standardize tumor assessment at scale and free up time for patient care.

InferCare RECIST is designed to integrate seamlessly into existing clinical workflows and can be deployed on-premise or via cloud platforms. Its DICOM compliance ensures compatibility with standard medical imaging data. The integration with the Microsoft Precision Imaging Network highlights its capability for broader, cloud-based intelligent imaging workflows.

Details

Category Oncology AI
Pricing Unknown — unknown
DeploymentHealthcare facility or cloud-based platform
Compliance
BAA AvailableUnknown AI-estimated
HIPAA CompliantUnknown AI-estimated
FDA Status Cleared AI-estimated

InferCare RECIST received U.S. Food and Drug Administration (FDA) clearance on March 25, 2026. It is listed on the FDA's AI/ML-Enabled Medical Device List, which identifies devices authorized for marketing in the United States.
Integrations
EHR Not specified
Specialties Interventional Radiology, Oncology, Radiology

What the Web Says

InferCare RECIST is a software solution designed to automate and standardize the RECIST (Response Evaluation Criteria in Solid Tumors) assessment process, primarily for oncology clinical trials and routine practice. It aims to improve efficiency, reduce inter-observer variability, and provide more consistent and accurate tumor response evaluations. Reviews often highlight its potential to streamline workflows and enhance data quality.

Overall: Positive

Strengths

  • Automates RECIST measurements, saving time and improving efficiency.
  • Reduces inter-observer variability in tumor response assessments.
  • Standardizes reporting for consistent data across studies and sites.
  • Potentially improves accuracy of tumor response evaluations.
  • Streamlines workflow for radiologists and oncologists.
  • Enhances data quality for clinical trials and research.

Limitations

  • Initial setup and integration with existing PACS/RIS systems can be complex.
  • Learning curve for new users to fully utilize all features.
  • Cost of implementation and ongoing licensing might be a barrier for smaller institutions.
  • Reliance on image quality; poor quality scans can impact accuracy.
  • Potential for 'black box' perception if algorithms aren't transparent.
  • Limited information available on widespread, long-term physician adoption rates.

Based on reviews from: Healthcare IT News, Radiology Today, Clinical Oncology Journals, Vendor Websites (InferCare), Medical Technology Review Sites, Academic Research Papers

Last updated: 2026-08-19

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Press & Coverage

InferVision
InferVision has received U.S. Food and Drug Administration (FDA) clearance for InferCare RECIST
InferVision announced FDA clearance for InferCare RECIST, an AI-powered solution for standardized tumor assessment in oncology workflows, automating measurements and tracking tumor response.
2026-03
OncoDaily Magazine
FDA Lists More Than 1500 AI-Enabled Medical Devices as Oncology Applications Expand
The FDA's updated list of AI-enabled medical devices includes InferCare RECIST among other AI-powered radiology and radiation therapy systems, highlighting the growing integration of AI in cancer care.
2026-08
InferVision
Leading the Future of Medical Imaging: InferVision Showcases Global-Ready AI Innovations at RSNA 2025
InferVision launched InferCare RECIST at RSNA 2025, an intelligent platform for multi-organ tumor imaging follow-up and therapeutic response evaluation, featuring AI multi-dimensional lesion analysis and automated structured reports.
2025-12
accessdata.fda.gov
InferCare RECIST FDA 510(k) Clearance Letter
The FDA granted 510(k) clearance to InferCare RECIST, a post-processing software application for displaying, processing, analyzing, quantifying, and manipulating multi-time-point CT images for tumor evaluation based on RECIST criteria.
2026-03
Rad AI Slice
AI speeds shoulder ultrasound exams for trainees | Rad AI Slice
InferCare RECIST by Infervision Healthcare received FDA clearance for AI-enabled lesion segmentation for CT monitoring and oncology response assessment.
2026-03
ResearchGate
Artificial Intelligence and Precision Oncology
InferCare RECIST is mentioned in a research paper discussing Artificial Intelligence and Precision Oncology, indicating its relevance in the field of AI-driven cancer treatment and evaluation.
2026-07

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Frequently Asked Questions

InferCare RECIST is an FDA-cleared AI-powered software that standardizes tumor assessment based on RECIST criteria, automating time-consuming manual measurements. It helps streamline workflows, reduce variability in clinical practice, and supports more efficient treatment monitoring and decision-making for radiologists and oncologists.
InferCare RECIST is designed to assist trained medical professionals in evaluating tumor response based on RECIST criteria. While it utilizes AI for automated lesion segmentation and registration, the results require confirmation by a medical professional, ensuring human oversight and compliance with established medical guidelines.
While InferCare RECIST can speed up RECIST measurements and improve inter-reader agreement, AI proposals may require more corrections and can be less consistent than expert-generated measurements, especially in complex cases. Human oversight remains crucial for reviewing every automated measurement, deciding whether to accept, adjust, or replace it, and for cases involving disappearing or non-measurable lesions.
Traditional RECIST 1.1 criteria are widely used but can have limitations, particularly with immunotherapies, leading to the development of iRECIST. Other alternative quantitative volumetric approaches and AI-driven tools are also being explored, with some showing potential to outperform traditional RECIST in specific contexts, but they may lack widespread acceptance or full validation for pivotal trials.
InferCare RECIST is designed for seamless integration into existing clinical workflows. It can be installed in a healthcare facility or a cloud-based platform and ingests medical imaging data compliant with the DICOM standard, supporting multi-timepoint image registration.
InferCare RECIST is intended for use by radiologists, oncologists, and other trained healthcare professionals. While the software automates many aspects of tumor assessment, medical professionals are still required to confirm the AI-generated results.
InferCare RECIST aims to reduce variability in clinical practice by providing automated, reproducible analysis for consistent lesion measurement and longitudinal tracking across timepoints. This helps standardize tumor assessment at scale, which can be a challenge with manual measurements due to inter-reader variability.

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Suggest an Edit → | Last Verified: 2026-08-19 | First Added: 2026-08-19
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