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AmCAD-UT is a Windows-based computer-aided detection (CADe) device intended to assist the medical professionals in analyzing thyroid ultrasound images, acquired from FDA-cleared ultrasound systems. The region of interest (ROI) of a user-selected thyroid nodule is defined by users or suggested by an AI contouring algorithm. 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 ultrasound images of discrete thyroid nodules larger than 1cm, for which a biopsy recommendation is required.

AmCAD-UT is a Windows-based computer-assisted detection (CADe) software application device designed to assist medical professionals in analyzing thyroid ultrasound images with the region of interest (ROI) of a selected nodule defined by users or suggested by an Al algorithm after the user specifies the location of the nodule.

After the initial review of thyroid ultrasound images by the physician, he/she can use AmCAD-UT to analyze thyroid images for further interpretation. Once the ROI is confirmed, the physician may process the image for detection and quantification of sonographic characteristics (i.e., hyperechoic foci, echogenicity, texture, margin, orientation and anechoic areas) by AmCAD-UT. 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 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.

The provided text describes a 510(k) premarket notification for AmCAD-UT, a computer-aided detection (CADe) device for analyzing thyroid ultrasound images.

Here's an analysis of the acceptance criteria and study information:

1. A table of acceptance criteria and the reported device performance

The document does not explicitly state acceptance criteria in a quantitative format (e.g., minimum sensitivity/specificity thresholds). Instead, it states that "the performance data demonstrates that it performs effectively and the device is as safe and effective as the predicate device."

However, it does mention that "the device was effective in determining the contour of thyroid nodules." This refers to the performance of the AI-suggested ROI contouring, which is a new feature compared to the predicate.

Given the information, a table would look something like this, acknowledging the lack of specific quantitative acceptance criteria:

2. Sample size used for the test set and the data provenance

The document does not specify the exact sample size (number of images or nodules) used for the test set in the standalone performance studies.

Regarding data provenance: While not explicitly stated, it's mentioned that the images are "acquired from FDA-cleared ultrasound systems." The manufacturer is AmCad BioMed Corporation, located in Taiwan, R.O.C. It is likely the data originated from (or was collected by) clinical sites associated with the manufacturer or collaborating institutions, possibly in Taiwan or internationally, but this is not explicitly stated. The study type is referred to as "standalone performance studies."

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts

The document states: "The ground truth to be established for performance studies of the device is the ROI labeled by a panel of specialists."

• Number of experts: "a panel of specialists" (the exact number is not specified).
• Qualifications of experts: "specialists" (specific qualifications, e.g., "radiologist with 10 years of experience", 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 ground truth establishment by the "panel of specialists." It simply says the ground truth is the "ROI labeled by a panel of specialists," implying consensus or a collective determination, but without detailing the process.

5. 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

• Was an MRMC study done? No, an MRMC comparative effectiveness study was not done for this particular submission. The "Performance Testing Data to Support SE Determination" table explicitly contrasts the current device's data ("Results from standalone performance testing of the AI suggested ROI's of user-selected nodules") with the predicate device's data, which included "Results from standalone performance testing and clinical performance testing (MRMC study)." This indicates that the MRMC study was performed for the predicate device (K180006), not for the new K203555 submission.
• Effect size of human reader improvement: Since an MRMC study was not performed for this device, no effect size of human readers improving with AI vs. without AI assistance is reported for K203555.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done

Yes, a standalone performance study was done. The document states:

• "AmCad BioMed Corporation has conducted standalone performance studies to validate and assess the performance of the AmCAD-UT for its added function of AI-suggested ROI contouring."
• "The standalone studies evaluated the performance of the contours suggested by the AI algorithm of user-selected nodules..."

7. The type of ground truth used

The document states:

• "The ground truth to be established for performance studies of the device is the ROI labeled by a panel of specialists."
• This indicates the ground truth for the ROI contouring was established by expert consensus/labeling.

It's worth noting that the ground truth for the predicate device (AmCAD-UT® Detection 2.2) included "the ROI, the presence of each sonographic characteristic, and the surgical pathology examination result," suggesting a more comprehensive ground truth for the predicate, potentially including pathology as a definitive outcome. However, for the current device's specific new function (AI-suggested ROI), the ground truth focus is on expert-labeled ROI.

8. The sample size for the training set

The document does not specify the sample size used for the training set.

9. How the ground truth for the training set was established

The document does not explicitly state how the ground truth for the training set was established. It only discusses the ground truth for "performance studies," which typically refers to test/validation sets. However, it's reasonable to infer that the training data would be labeled by similar expert methods, but this is not confirmed in the provided text.

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AmCAD-UT® Detection is a Windows-based computer-aided detection (CADe) device intended to assist the medical professionals in analyzing thyroid ultrasound images, acquired from FDA-cleared ultrasound systems, with 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 of sonographic characteristics of thyroid nodules. The device is intended for use on ultrasound images of discrete thyroid nodules larger than 1cm, for which a biopsy recommendation is required.

AmCAD-UT® Detection 2.2 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).

After the initial review of thyroid ultrasound images by the physician, he/she can use AmCAD-UT Detection to analyze thyroid images for further interpretation. The physician selects an ROI 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, echogenicity, texture, margin, orientation and anechoic areas) by AmCAD-UT Detection. 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 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.

The provided text describes the AmCAD-UT® Detection 2.2 device and its performance study to support its substantial equivalence to a predicate device. Here's a breakdown of the requested information:

Device Acceptance Criteria and Performance

The document doesn't explicitly lay out a table of "acceptance criteria" with specific numerical thresholds for performance metrics. Instead, it describes "performance data" that "demonstrates that the proposed device performs as safely and effectively as the predicate devices." The core acceptance is based on demonstrating substantial equivalence to the predicate device (AmCAD-UT® Detection, Version 2.0) through standalone and clinical performance testing.

However, the "Functional Capability of Image Processing" for the device (AmCAD-UT® Detection 2.2) provides implicit performance goals related to the detection and quantification of certain sonographic characteristics.

Here’s a table presenting the device's functional performance capabilities as described, rather than explicit acceptance criteria with numerical targets:

Study Details

1. Sample size used for the test set and the data provenance:

   • Test set sample size: Not explicitly stated. The document refers to "the test set" for ground truth establishment but does not provide a specific number of cases or images used for the performance studies.
   • Data Provenance:
     • Country of origin: Not explicitly stated in the provided text. The manufacturer is AmCad BioMed Corporation, located in Taipei, Taiwan, R.O.C., suggesting the data could be from Taiwan, but this is not confirmed.
     • Retrospective or Prospective: Not explicitly stated.

2. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:

   • Number of experts: Not explicitly stated. The document mentions "clinical reader performance studies" and "ground truth to be established... include the ROI, the presence of each sonographic characteristic, and the surgical pathology examination result." It does not specify how many experts were involved in establishing the ground truth from the images themselves.
   • Qualifications of experts: Not explicitly stated beyond "medical professionals" or "physicians."

3. Adjudication method (e.g. 2+1, 3+1, none) for the test set:

   • Not explicitly stated. The document mentions "ground truth to be established" but does not detail the adjudication process (e.g., consensus, majority vote with tie-breaker).

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:

   • MRMC study: Yes, a "clinical Multiple-Reader-Multiple-Case (MRMC) study" was done for the AmCAD-UT® Detection 2.2.
   • Effect size: The document states: "The results of the MRMC study demonstrated that the physician reading thyroid nodule sonography images with the assistance of AmCAD-UT® Detection 2.2 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 numerical effect size (e.g., AUC increase, sensitivity/specificity improvement). It only states that the improvement was "significant."

5. If a standalone (i.e., algorithm only without human-in-the-loop performance) was done:

   • Yes, "standalone performance testing" was conducted. It evaluated the device's effectiveness in detecting and quantifying sonographic characteristics on images from various ultrasound systems.

6. The type of ground truth used (expert consensus, pathology, outcomes data, etc.):

   • The ground truth for performance studies included:
     • Region of Interest (ROI)
     • Presence of each sonographic characteristic
     • Surgical pathology examination result (This is a strong objective ground truth for malignancy status where available).

7. The sample size for the training set:

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

8. How the ground truth for the training set was established:

   • The document does not describe how the ground truth for the training set was established. It only mentions "The ground truth to be established for performance studies of the device includes the ROI, the presence of each sonographic characteristic, and the surgical pathology examination result." This statement appears in the context of "Ground Truth Establishment" for the device itself and its performance evaluation, not specifically for a separate training set if machine learning was involved. Given it's a CADe device, it likely involved training, but the details are not provided.

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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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