iCAS-LV

by HighRAD  · Based in Israel → — Revolutionizing oncology care by advancing the understanding of disease progression through longitudinal, multi-organ analysis.
Nuclear Medicine Oncology Radiology
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Regulatory Status Disclosed

Overview

The intelligent Computer Assessment Support (iCAS-LV™) is a computer-based Quantitative Changes Analysis of Lesion Volumetric Changes for radiological follow-up of longitudinal liver contrast-enhanced CT (ceCT) volumetric scans. HighRAD’s AI imaging platform is designed to track the entire patient journey, offering profound insights into disease progression through advanced quantitative, multi-organ analysis. It provides quantitative imaging analysis, automated lesion measurement, workflow integration, and standardized reporting, enabling radiologists, oncologists, and pharmaceutical research teams to gain deeper disease insight, make more confident clinical decisions, and improve treatment planning. The technology enhances disease understanding and significantly improves treatment outcomes, boosting radiologist productivity, and enabling quicker, more confident diagnoses.

Reviewed by Pouyan Golshani, MD — Interventional Radiologist

Key Features

  • AI-generated lesion detection for up to 3x faster oncology reporting
  • Accurate volumetric measurement of known and unknown lesions
  • Longitudinal comparison of findings (through all available studies)
  • Automated report generation for streamlined RECIST 1.1 documentation
  • Multi-organ view for complete standardized reporting
  • Seamless connectivity, integrating with all CT, MRI, and PET systems
  • AI-Powered Longitudinal Quantitative Analysis using Simultaneous Deep Learning technology (SimU-Net)
  • Automatic Lesion Detection & Segmentation
  • Data Processing and Integration

Use Cases

  • Tracking oncology patient journey
  • Radiological follow-up of longitudinal liver contrast-enhanced CT (ceCT) volumetric scans
  • Evaluating disease progression and treatment efficacy
  • Streamlining data retrieval and analysis for faster reporting
  • Supporting personalized treatment planning
  • Pharmaceutical tool for evaluating treatment or drug responses and tracking clinical studies

What Physicians Need to Know

Key Capabilities
iCAS-LV is an AI-powered platform for quantitative volumetric changes analysis of liver lesions in longitudinal contrast-enhanced CT (ceCT) scans. It offers automated lesion detection and segmentation, accurate volumetric measurement of both known and unknown lesions, and longitudinal comparison of findings across all available studies. The system also generates automated reports for streamlined RECIST 1.1 documentation and provides a multi-organ view for comprehensive standardized reporting. HighRAD's technology is based on proprietary Simultaneous Deep Learning (SimU-Net) and multi-channel anisotropic 3D U-Net classification for lesion change detection and segmentation.
Clinical Utility
iCAS-LV is designed to track the oncology patient journey, providing insights into disease progression through advanced quantitative, multi-organ analysis. It aims to enhance disease understanding, improve treatment outcomes, and boost radiologist productivity by enabling quicker and more confident diagnoses. The tool can generate AI-powered lesion detection for up to three times faster oncology reporting. It supports personalized treatment planning by leveraging comprehensive quantitative data analysis to track disease progression and optimize treatment plans.
Integration Options
HighRAD's system, including iCAS-LV, offers seamless connectivity and integrates with all CT, MRI, and PET systems. It is adaptable to various clinical protocols.
Compliance Status
HighRAD provides an FDA-cleared oncology AI imaging platform.
User Experience
The system is designed to streamline imaging workflow processes within healthcare facilities, aiming for higher productivity and patient throughput.
Evidence Base
iCAS-LV has an average lesion recall of 0.92±0.14 and segmentation (Dice) of 0.86±0.09. HighRAD's technology is grounded in proprietary Simultaneous Deep Learning (SimU-Net) and multi-channel anisotropic 3D U-Net classification. The company's co-founders have extensive experience in medical imaging and AI, with numerous publications and patents.
Physician Tip

iCAS-LV can significantly expedite oncology reporting and enhance the accuracy of volumetric measurements for liver lesions. Its longitudinal comparison capabilities are valuable for tracking disease progression and treatment efficacy over time. The automated RECIST 1.1 reporting can help standardize documentation and improve efficiency. Consider integrating this tool for a more streamlined workflow and to support personalized treatment planning based on quantitative data.

iCAS-LV is designed for easy integration with existing CT, MRI, and PET systems, and can adapt to various clinical protocols. This suggests a flexible system that can be incorporated into diverse imaging environments without significant compatibility issues.

Details

Category Oncology AI
Pricing Contact for pricing
DeploymentPC-based, self-contained software application that integrates with PACS devices.
Compliance
BAA AvailableUnknown
HIPAA CompliantUnknown
FDA Status Cleared AI-estimated
Integrations
EHR Not specified
Specialties Nuclear Medicine, Oncology, Radiology

What the Web Says

iCAS-LV by HighRAD is an FDA-cleared oncology AI imaging platform specifically designed for the quantitative volumetric changes analysis of liver lesions using contrast-enhanced CT scans. It aims to revolutionize oncology care by providing automated detection, segmentation, and documentation capabilities to streamline data retrieval and analysis for faster and more in-depth reporting. The platform is designed to track the entire patient journey, offering insights into disease progression through advanced quantitative, multi-organ analysis, which can lead to improved treatment outcomes and increased radiologist productivity.

Overall: Positive

Strengths

  • AI-generated lesion detection for up to 3x faster oncology reporting.
  • Accurate volumetric measurement of known and unknown lesions.
  • Longitudinal comparison of findings across all available studies.
  • Automated report generation for streamlined RECIST 1.1 documentation.
  • Multi-organ view for complete standardized reporting.
  • Seamless connectivity and easy integration with all CT, MRI, and PET systems.

Limitations

No significant limitations found in public reviews. Consider checking vendor documentation or requesting a demo for a thorough evaluation.

Based on reviews from: high-rad.com

Last updated: 2026-10-30

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Press & Coverage

high-rad.com
iCAS-LV™ | HighRAD
iCAS-LV is HighRAD's intelligent Computer Assessment Support system for quantitative changes analysis of lesion volumetric changes in longitudinal liver contrast-enhanced CT scans, designed to empower oncology with AI-generated lesion detection, accurate volumetric measurement, and automated reporting for streamlined RECIST 1.1 documentation.
unknown
high-rad.com
HighRAD
HighRAD offers an FDA-cleared oncology AI imaging platform that provides fully automated, quantitative, and comparative analysis for evaluating disease progression and treatment efficacy across multiple organs.
unknown
tracxn.com
Digital image analysis and assessment tool for providers
HighRAD has developed software solutions including iCAS-LV for analyzing liver lesions, iCAS-LG for quantifying pulmonary metastases, and iCAS-BR for brain lesion analysis.
2026-07
thieme-connect.com
Artificial Intelligence for the Practicing Gastroenterologist: Foundations, Contemporary Applications, Real-World Constraints, and Future Directions
iCAS-LV by HighRAD Ltd. is listed as an AI application for assessing liver lesions on CT scans in a narrative review about Artificial Intelligence for gastroenterologists.
2026-03
parikhradiology.com
FDA-Cleared AI/ML Devices in Radiology
iCAS-LV from HighRAD Ltd. received FDA clearance (K232613) on March 1, 2024, to assist trained physicians in visualizing and evaluating physician-identified liver lesions on multi-phase reconstructed CT scans, including analysis of lesion size, shape, position, and change.
2024-03
healthcareaiops.com
FDA AI/ML Clearances
iCAS-LV from Highrad, Ltd. received FDA clearance on March 1, 2024, under product code QIH, as part of the 510(k) clearances for AI/ML-enabled devices.
2024-03
researchgate.net
Regulatory Pathways, Predicate Lineage, and Transparency of Machine Learning-Enabled Medical Devices Cleared by the FDA in 2024
iCAS-LV (K231690) is listed as an FDA-cleared (510(k)) deep learning device for left ventricular function analysis from CT, according to a study assessing ML-enabled medical devices cleared by the FDA in 2024.
2025-12
mdpi.com
Regulatory Pathways, Predicate Lineage, and Transparency of Machine Learning-Enabled Medical Devices Cleared by the FDA in 2024
iCAS-LV (K231690) is identified as an FDA-authorized 510(k) deep learning device for left ventricular function analysis from CT, as detailed in a cross-sectional analysis of ML-enabled medical devices cleared by the FDA in 2024.
2025-12

Videos

Product demos, reviews, and walkthroughs for iCAS-LV.

View all on YouTube

Frequently Asked Questions

iCAS-LV is an AI-powered technology developed by HighRAD for quantitative volumetric changes analysis of liver lesions using longitudinal contrast-enhanced CT (ceCT) volumetric scans. It's designed to assist in the radiological follow-up of liver cancer, offering features like AI-generated lesion detection, accurate volumetric measurement, longitudinal comparison of findings, and automated report generation for RECIST 1.1 documentation.
While the specific integration details for iCAS-LV are not explicitly stated, AI tools in oncology generally integrate with existing EHR systems and PACS platforms. This integration often utilizes standards like DICOM for imaging data and HL7/FHIR for clinical data exchange, allowing seamless access to imaging studies and patient records within multidisciplinary platforms.
General limitations of AI in oncology include concerns about data quality, potential biases in algorithms from training data, and the need for continuous monitoring of AI model performance after deployment. There can also be challenges with integrating AI systems into existing clinical workflows due to technical infrastructure limitations and the 'black box' nature of some AI models, which can make it difficult for physicians to explain decisions to patients.
HighRAD's website states that iCAS-LV is part of their AI imaging platform. While specific compliance details for iCAS-LV are not provided, other AI healthcare solutions emphasize HIPAA compliance, SOC 2 Type II certification, and encryption of patient data at rest and in transit. General data security platforms for 'iCAS' (not specifically iCAS-LV by HighRAD) also highlight compliance with GDPR through encryption, key management, and access control.
The field of AI in oncology is rapidly advancing, with numerous tools being developed for various aspects of cancer care, including diagnosis, treatment planning, and monitoring. While specific direct alternatives to iCAS-LV for liver lesion analysis are not detailed, other AI platforms like IBM Watson for Oncology and Tempus offer decision support and genomic sequencing for personalized cancer treatment. Many AI tools focus on image analysis for cancer detection across different organs.
iCAS-LV boasts an average lesion recall of 0.92±0.14 and a segmentation (Dice) of 0.86±0.09. HighRAD emphasizes that its oncology AI imaging platform is designed to track the entire patient journey and offers profound insights.

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Suggest an Edit → | Report an issue | Last Verified: 2026-04-18 | First Added: 2026-04-18
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