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The RS80A Diagnostic Ultrasound System and transducers are intended for diagnostic ultrasound imaging and fluid analysis of the human body.

The clinical applications include: Fetal/Obstetrics, Abdominal, Gynecology, Pediatric, Small Organ, Neonatal Cephalic, Adult Cephalic, Trans-rectal, Muscular-Skeletal (Conventional, Superficial), Urology, Cardiac Adult, Cardiac Pediatric and Peripheral vessel.

The RS80A is a general purpose, mobile, software controlled, diagnostic ultrasound system. Its function is to acquire ultrasound data and to display the data as B mode, Color Doppler imaging, Power Doppler imaging (including Directional Power Doppler mode; S-Flow), PW Spectral Doppler mode, CW Spectral Doppler mode, Harmonic imaging, Tissue Doppler imaging, Tissue Doppler Wave, 3D imaging mode (real time 4D imaging mode), Elastoscan Mode or as a combination of these modes. The RS80A also gives the operator the ability to measure anatomical structures and offers analysis packages that provide information that is used to make a diagnosis by competent health care professionals. The RS80A has real time acoustic output display with two basic indices, a mechanical index and a thermal index, which are both automatically displayed.

This is a 510(k) premarket notification for the SAMSUNG MEDISON RS80A Diagnostic Ultrasound System. The purpose of this document is to demonstrate "substantial equivalence" to previously cleared predicate devices, meaning that the new device is as safe and effective as the predicate devices and does not raise new questions of safety or effectiveness. As such, the document primarily focuses on comparing the new device's features and performance to those of predicate devices, rather than establishing acceptance criteria and proving the device meets them through a dedicated standalone study with defined ground truth and expert adjudication.

However, based on the provided text, I can infer information related to acceptance criteria through the comparison tables and the declaration of "substantial equivalence."

Inferred Acceptance Criteria and Reported Device Performance

The acceptance criteria for the RS80A Diagnostic Ultrasound System are implicitly met by demonstrating that its technical characteristics, intended uses, and safety compliance are "substantially equivalent" to predicate devices. This means the device's performance is expected to be on par with or better than the established performance of the cleared predicate devices.

Here's an inferred table of key "acceptance criteria" (represented by the features and standards the device claims to meet as being equivalent to predicate devices) and the "reported device performance" (which is the device possessing these features and meeting these standards):

Study Information:

The document describes a bench and non-clinical test approach rather than a specific clinical trial with a test set.

1. Sample size used for the test set and the data provenance: Not explicitly stated as a distinct "test set" for performance evaluation in the described manner. The submission relies on "substantial equivalence" to predicate devices, implying that the performance of the RS80A is within acceptable ranges demonstrated by already cleared devices. The testing mentioned (acoustic output, biocompatibility effectiveness, thermal, electrical, electromagnetic, and mechanical safety) are likely internal engineering and quality assurance tests, not a clinical "test set" with patient data.

2. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable. The document does not describe a clinical study with a "ground truth" established by experts in the context of image interpretation or diagnosis. The "ground truth" for compliance testing is against engineering specifications and international standards.

3. Adjudication method for the test set: Not applicable. No clinical adjudication method is described.

4. If a multi-reader, multi-case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance: Not applicable. This document is for a diagnostic ultrasound system and its transducers, not explicitly an AI-assisted diagnostic device requiring an MRMC study for improved human reader performance. The listed "SW Features" like S-Detect, E-Thyroid, E-Breast, and S-Fusion hint at advanced functionalities that might involve AI-like processing, but the document does not present them as standalone AI clinical decision support systems requiring MRMC studies to show reader improvement. Instead, they are presented as equivalent or improved features compared to predicates.

5. If a standalone (i.e., algorithm only without human-in-the-loop performance) was done: Not applicable for the overall device clearance. The device is a diagnostic ultrasound system, intended for use with a human operator. Even advanced features like S-Detect for lesion analysis are presented as aids within the larger diagnostic system, not as standalone algorithms performing a diagnosis without human interaction.

6. The type of ground truth used (expert consensus, pathology, outcomes data, etc.): For the safety and effectiveness mentioned, the "ground truth" would be the adherence to established international and national standards (e.g., IEC, NEMA, ISO standards) for medical devices. For functional comparisons, the "ground truth" is the established performance and features of the predicate devices. There is no mention of specific clinical ground truth (like pathology or outcomes data) being used for this 510(k) submission, as it relies on substantial equivalence.

7. The sample size for the training set: Not applicable. The document describes a general diagnostic ultrasound system and its transducers, not a machine learning model that would typically have a "training set." While "SW Features" like S-Detect might leverage machine learning, the details of their development (including training sets) are not provided in this 510(k) summary, which focuses on device safety and substantial equivalence rather than algorithm validation.

8. How the ground truth for the training set was established: Not applicable, as no training set is described. If features like S-Detect or E-Thyroid involve machine learning, their internal ground truth establishment would be part of their individual validation, but it's not detailed in this high-level regulatory summary.

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AmCAD-UT® Detection 2.0 is a Windows-based computer-assisted detection (CADe) device intended to assist the medical professionals in analyzing thyroid ultrasound images of user-selected regions of interest (ROI). After the initial review of the ultrasound images by the physicians, the device further provides detailed information with quantification and visualization of sonographic characteristics of thyroid nodules. The device is intended for use on Philips HDI5000 images of discrete thyroid nodules larger than 1cm, for which a biopsy has been recommended. The device performance has been validated on images collected from Philips HDI5000 with a 5-12MHz multi-frequency probe.

AmCAD-UT® Detection 2.0 is a Windows-based computer-assisted detection (CADe) software application device designed to assist medical professionals in analyzing thyroid ultrasound images of user selected regions of interest (ROI). The device uses statistical pattern recognition and quantification methods to perform analytical function of images. For thyroid ultrasound, these pattern recognition and quantification methods are used by a medical professional to analyze DICOM/JPEG/Bitmap compliant thyroid ultrasound images. The software application consists of proprietary software developed by AmCad BioMed Corporation. The software is a Windows-based that may be installed on a standalone PC or review station. AmCAD-UT® Detection 2.0 user interface is designed to follow typical clinical workflow patterns to process, review, and analyze digital images. After the initial review of thyroid ultrasound images by the physician, he/she can use AmCAD-UT® Detection 2.0 to analyze the thyroid images for further interpretation. The physician selects an ROI (Region of Interest) to define the initial boundary of the ROI. Once the ROI is confirmed, the physician may process the image for detection and quantification of sonographic characteristics (i.e., hyperechoic foci, echo-pattern, echo-texture, and anechoic areas) by AmCAD-UT® Detection 2.0. The device provides more detailed information with quantification and visualization of the sonographic characteristics of thyroid nodule that may assist physician in his/her complete interpretation. The software application also automatically generates reports given the user preference inputs (e.g., the nodule size, nodule location and shape, and the presence or absence of the sonographic characteristics) annotated during the image analysis process. A report form has been designed by AmCad to be consistent with the conventional clinical thyroid report form. An output of the report may be viewed and sent to paper printers or saved on the standalone PC or review station as PDF file.

Here's a breakdown of the acceptance criteria and the study details for the AmCAD-UT® Detection 2.0 device, based on the provided 510(k) summary:

1. Table of Acceptance Criteria and Reported Device Performance:

The document doesn't explicitly state quantitative acceptance criteria or provide a table of performance metrics (e.g., sensitivity, specificity) for the AmCAD-UT® Detection 2.0 device. Instead, it broadly states that the clinical reader performance studies demonstrated that physician reading with the assistance of AmCAD-UT® Detection 2.0 enhanced their ability in analyzing sonographic characteristics and led to a significant increase in the effectiveness of clinical judgment.

Here's the summary of reported performance:

2. Sample Size Used for the Test Set and Data Provenance:

• Test Set Sample Size: Not explicitly stated in the document. The document mentions "clinical reader performance studies" but does not provide the number of cases/images used in these studies.
• Data Provenance: The images were collected from a Philips HDI5000 with a 5-12MHz multi-frequency probe. The country of origin for the data is not specified in the provided text, but the manufacturer is based in Taiwan. It is a retrospective study (as implied by collected images used for validation).

3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications:

• Number of Experts: Not explicitly stated. The document mentions "the surgical pathology examination result" as part of the ground truth, which implies expert pathology review.
• Qualifications of Experts: The document explicitly mentions "surgical pathology examination result" as part of the ground truth. This indicates that pathologists, likely with relevant experience, were involved. However, specific qualifications (e.g., years of experience, board certification) are not provided.

4. Adjudication Method for the Test Set:

• The document does not explicitly describe an adjudication method (such as 2+1 or 3+1) for the test set. It mentions "surgical pathology examination result" as part of the ground truth.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, and Effect Size:

• Yes, an MRMC comparative effectiveness study was done. The document states: "The intended use of the AmCAD-UT® Detection 2.0 was validated in a clinical (MRMC) study."
• Effect Size: The document states that the study "demonstrated that the physician reading thyroid nodule sonography images with the assistance of AmCAD-UT® Detection 2.0 can enhance their ability in analyzing the sonographic characteristics and has led to a significant increase in effectiveness of making clinical judgment." However, it does not provide a specific quantitative effect size (e.g., percentage improvement in AUC, sensitivity, or specificity) of how much human readers improve with AI vs. without AI assistance.

6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done:

• Yes, standalone performance testing was done. The document states: "AmCad BioMed Corporation has conducted standalone and clinical reader performance studies to validate and assess the performance of the AmCAD-UT® Detection 2.0 for its intended use. The standalone studies include the detection accuracy testing, reproducibility testing, and algorithm stability testing."

7. The Type of Ground Truth Used:

• The ground truth used for performance studies included:
  • Region of Interest (ROI) definition.
  • Presence of each sonographic characteristic (hyperechoic foci, echo-pattern, echo-texture, and anechoic areas).
  • Surgical pathology examination result.

8. The Sample Size for the Training Set:

• The document does not provide information regarding the sample size used for the training set.

9. How the Ground Truth for the Training Set Was Established:

• The document does not explicitly describe how the ground truth for the training set was established. However, given that the "surgical pathology examination result" and evaluation of sonographic characteristics are used for performance studies, it is reasonable to infer a similar process would be used for training data, likely involving expert review and pathology confirmation.

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