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AmCAD-UT®
AmCAD-UT®
AmCad BioMed
AmCAD-UT® Detection gives physicians a tool to process ultrasound images for sonographic characteristics that assist in making diagnostic decisions. AmCAD-UT® Detection uses statistical pattern recognition and quantification methods to perform analytical processing of images. By processing the image for key characteristics (i.e., echogenic foci, echogenicity, texture, margin, anechoic areas, height/width ratio, nodule shape, and nodule size). AmCAD-UT® Detection provides physicians with quantification and visualization of the sonographic characteristics for informed decision making.
Information source:
Vendor
Last updated:
November 20, 2024
General Information
Technical Specifications
Regulatory
Market
Evidence
General Information
General
Product name
AmCAD-UT®
Company
AmCad BioMed
Subspeciality
Head/Neck
Modality
Ultrasound
Disease targeted
Thyroid cancer, Thyroid nodule
Key-features
Automated nodule recognition, quantification and visualization of sonographic features, risk analysis based on global guidelines
Suggested use
Before: stratifying reading process (non, single, double read), flagging acute findings
During: perception aid (prompting all abnormalities/results/heatmaps), interactive decision support (shows abnormalities/results only on demand), report suggestion
Technical Specifications
Data characteristics
Population
Thyroid ultrasound scanning for thyroid nodule
Input
2D grayscale ultrasound images
Input format
DICOM, BMP, JPEG or TIFF
Output
Visualized and quantified sonographic features, recommendation based on TI-RADS and global guidelines including AACE/ACE/AME, ACR , ATA, EU-TIRADS, BTA, Kwak et al., KSThR and KSR, ) and Seo et al.
Output format
DICOM, pdf
Technology
Integration
Integration in standard reading environment (PACS), Integration via AI marketplace or distribution platform, Stand-alone webbased
Deployment
Locally on dedicated hardware, Cloud-based
Trigger for analysis
Automatically, right after the image acquisition, On demand, triggered by a user through e.g. a button click, image upload, etc.
Processing time
< 3 sec
Regulatory
Certification
CE
Certified, Class IIa
, MDD
FDA
510(k) cleared , Class II
Intended Use Statements
Intended use (according to CE)
Market
Market presence
On market since
2017
Distribution channels
Countries present (clinical, non-research use)
13
Paying clinical customers (institutes)
4 countries
Research/test users (institutes)
12 countries
Pricing
Pricing model
Pay-per-use, Subscription
Based on
Number of installations, Number of analyses
Evidence
Evidence
Peer reviewed papers on performance
Improving the diagnostic strategy for thyroid nodules: a combination of artificial intelligence-based computer-aided diagnosis system and shear wave elastography
(read)
Multi-Reader Multi-Case Study for Performance Evaluation of High-Risk Thyroid Ultrasound with Computer-Aided Detection
(read)
Diagnostic Performance Evaluation of a Computer-Assisted Imaging Analysis System for Ultrasound Risk Stratification of Thyroid Nodules
(read)
Study on the comparison of diagnostic of K-TIRADS, ACR-TIRADS and ATA in CAD and diagnosis of thyroid nodules by computer-assisted ultrasonography
(read)
Non-peer reviewed papers on performance
Other relevant papers