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PIUR tUS inside System is a computer-aided detection device intended to assist and support medical professionals in the diagnostic workflow of thyroid and thyroid nodules acquired from FDA-cleared ultrasound systems, including image documentation, analysis, and reporting. The device supports the physician with additional information during image review, including quantification and visualization of sonographic characteristics of thyroid nodules.

PIUR tUS inside System may be used on any adult patient aged 22 and older, independent of gender, linguistic and cultural background, or health status, unless any of the contraindications apply.

The PIUR tUS inside System acts as part of the diagnostic chain and must not be used as a sole source for treatment decisions, but as an add-on solution to regular 2D ultrasound imaging.

The PIUR tUS inside System is not intended for body contact (including skin, mucosal membrane, breached or compromised surfaces, blood path indirect, tissues, bones, dentin, or circulation blood).

PIUR tUS inside is a medical device which enhances standard ultrasound devices with a three-dimensional (3D) tomographic imaging method for a 3D analysis of ultrasound volumes. With PIUR tUS inside, examining physicians can make diagnostic decisions based on standard 2D as well as 3D image data integrated in an ultrasound device environment. This 3D data provides information which previously could have only been generated using other 3D imaging technologies like CT or MRI.

The PIUR tUS inside runs on a compatible GE Healthcare ultrasound system. The PIUR tUS inside takes as an input a sequence of 2D ultrasound images that are transmitted through a software interface from the ultrasound to the PIUR tUS inside. In addition, the PIUR Sensor must be clipped onto the ultrasound transducer using individually designed PIUR Brackets. For image acquisition, the user moves the 2D ultrasound transducer perpendicular to the structure to be imaged over the region of interest of the patient's body. An inertial measurement unit (IMU), which is built into the PIUR Sensor, tracks the orientation of the transducer during the scan and sends this information to the ultrasound via Bluetooth.

The PIUR tUS inside combines image information and sensor information to generate tomographic 3D ultrasound volumes on which image analysis can be performed. An important property of this method is the unlimited length of the acquired volume. PIUR tUS inside therefore allows recording and analyzing a complete thyroid lobe.

The PIUR tUS inside and the PIUR tUS Infinity Predicate Device share most hardware and software components and algorithms. On the hardware side, both systems use the same PIUR Sensor to track probe movement during a freehand ultrasound acquisition. The data from the PIUR Sensor is transferred wirelessly through a Bluetooth connection to the software where it is being used to generate ultrasound volumes from the freehand sweep. Both systems also share the same volume compounding software algorithms, semi-automatic lobe and nodule segmentation algorithms, and volume calculation algorithms. The performance for image compounding and volume calculations are therefore the same for both systems.

The main difference between the PIUR tUS inside System and the Predicate Device is the interface for image retrieval. While the Predicate Device uses the Infinity Box to transfer digital ultrasound images from a third-party ultrasound system to the software through a Wi-Fi connection, the PIUR tUS inside has direct access to the image stream through a software interface. It runs directly on the compatible ultrasound scanners: GE Healthcare LOGIQ E10 (K231966) and GE Healthcare LOGIQ E10s/Fortis (K231989). This, however, is not performance relevant as the image data remains the same. It only reduces the number of compatible ultrasound systems as a close collaboration with the ultrasound manufacturer is required.

The PIUR tUS inside System acts as part of the diagnostic chain only and must not be used as a sole source for diagnostic or treatment decisions.

The solution is intended to be used on patients aged 22 and older, independent of gender, linguistic and cultural background, or health status, unless any of the contraindications apply, in a non-sterile environment. The solution is not intended to be used on patients with open wounds or irritated skin or during surgery.

The provided FDA 510(k) clearance letter and summary for PIUR tUS inside (K250484) does not contain the detailed information necessary to fully answer all aspects of your request regarding acceptance criteria and a study that proves the device meets them.

The document primarily focuses on establishing substantial equivalence to a predicate device (PIUR tUS Infinity, K240036) by demonstrating similar intended use, technological characteristics, and principles of operation, rather than providing a detailed clinical performance study with specific acceptance criteria, sample sizes, expert qualifications, or comparative effectiveness.

However, based on the information available in the document, here's what can be extracted and inferred:

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

The document does not explicitly state acceptance criteria in a quantitative manner as one might find in a clinical study report. Instead, the "Performance Data" section indicates that software performance, verification, and validation testing demonstrated that the PIUR tUS inside System met all design requirements and specifications.

It also states that the device was tested for electrical safety, EMC, and a white-noise test was conducted to verify that the wireless equipment does not induce additional white noise or degrade ultrasound image quality. These are performance aspects, but not specific clinical or diagnostic accuracy acceptance metrics.

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

The document mentions "performance validation testing" and "software verification and validation testing," but it does not specify the sample size used for these tests. It also does not provide details on the data provenance (e.g., country of origin, retrospective or prospective nature) for any datasets used in these tests. The only clue is that the device assists in diagnosing thyroid and thyroid nodules acquired from FDA-cleared ultrasound systems.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g., radiologist with 10 years of experience):

The document states under "Ground Truth Establishment" in the Substantial Equivalence Comparison Table:
"The ground truth to be established for performance studies of the device are annotated data sets labeled by medical specialists."

However, it does not specify the number of experts used, their qualifications (e.g., specific specialties, years of experience), or their accreditation.

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

The document does not describe any adjudication method used for establishing the ground truth for the test set.

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:

The document does not mention or describe a multi-reader multi-case (MRMC) comparative effectiveness study. The device is described as a "computer-aided detection device intended to assist and support medical professionals" and an "add-on solution to regular 2D ultrasound imaging," implying a human-in-the-loop scenario. However, no study demonstrating the improvement of human readers with AI assistance is detailed.

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

The document states under "Performance Testing Data to Support SE Determination" in the Substantial Equivalence Comparison Table:
"Results from standalone performance testing of machine learning algorithm suggested ROIs of user-selected nodules."

This indicates that some form of standalone performance testing was conducted specifically for the segmentation ("suggested ROIs") of user-selected nodules. However, the details of this standalone performance (e.g., accuracy metrics, specific results) are not provided in this summary.

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

As mentioned above, the ground truth for performance studies is described as "annotated data sets labeled by medical specialists." This suggests an expert consensus or expert labeling approach, rather than pathology or outcomes data specifically.

8. The sample size for the training set:

The document does not specify the sample size used for the training set of the machine learning algorithms.

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

Similar to the test set, the document states generally: "The ground truth to be established for performance studies of the device are annotated data sets labeled by medical specialists." This implies the training set ground truth would also be established through expert labeling, but no further details are provided.

Summary of what is present vs. what is missing:

The provided 510(k) summary focuses heavily on demonstrating substantial equivalence through shared technological characteristics and general compliance with standards. It explicitly states that the device met "all design requirements and specifications" but lacks specific quantitative performance metrics (e.g., sensitivity, specificity, F1-score) or detailed clinical study results often found in AI/CAD device submissions. The information regarding ground truth establishment, sample sizes for training and testing, expert qualifications, and specific study designs (like MRMC or detailed standalone performance) is either very limited or entirely absent from this summary.

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PIUR tUS Infinity is a computer-aided detection device intended to assist and support medical professionals in the diagnostic workflow of thyroid and thyroid nodules acquired from FDA-cleared ultrasound systems, including image documentation, analysis, and reporting. The device supports the physician with additional information during image review, including quantification and visualization of sonographic characteristics of thyroid nodules.

PIUR tUS Infinity may be used on any adult patient aged 22 and older, independent of gender, linquistic and cultural background, or health status, unless any of the contraindications apply.

The PIUR tUS Infinity acts as part of the diagnostic chain and must not be used as a sole source for treatment decisions, but as an add-on solution to regular 2D ultrasound imaging.

PIUR tUS Infinity device is not intended for body contact (including skin. mucosal membrane, breached or compromised surfaces, blood path indirect, tissues, bones, dentin, or circulation blood),

PIUR tUS Infinity is a computer-aided solution to aid in the diagnostic workflow of thyroid and thyroid nodules, including image documentation, analysis, and reporting. Computer vision and machine learning algorithms are applied to a sequence of ultrasound images of the thyroid that have been acquired by a compatible FDA-cleared ultrasound system. The solution identifies the thyroid lobe and proposes its margins to the user who then can make adjustments to the segmentation and approve the final result. Based on this, a lobe volume is calculated. With additional user input, thyroid nodules can be marked, quantified, and visualized as multiplanar reconstructions or 3D volume renderings. The system provides a user interface for the user to select the five ACR TI-RADS parameters and calculates the ACR TI-RADS level from the user input for each nodule. All proposed results must be verified, adjusted if necessary, and confirmed by the user before they can be added to an automatically generated clinical report.

The Infinity software runs on a stand-alone computer (Infinity Workstation - not part of the medical product) that fulfils the defined minimum requirements. It takes as an input a sequence of ultrasound images that are transmitted from the ultrasound to the Infinity Workstation wirelessly through the Infinity Box. The Infinity Box is a piece of hardware that connects to compatible standard ultrasound systems via digital video output such as HDMI or DVI. It grabs 2D ultrasound images through a video grabber and transfers the images to the Infinity Workstation via Wi-Fi in real-time. In addition, a small Infinity Sensor must be clipped onto the ultrasound transducer using individually designed attachments. An inertial measurement unit (IMU) tracks the orientation of the transducer during the scan and sends this information to the Infinity Workstation via Bluetooth. The Infinity Workstation combines information from the Infinity Box and Sensor to generate tomographic 3D ultrasound volumes on which the abovedescribed image analysis can be performed.

The PIUR tUS Infinity acts as part of the diagnostic chain only and must not be used as a sole source for diagnostic or treatment decisions.

The solution is intended to be used on patients aged 22 and older, independent of gender, linguistic and cultural background, or health status, unless any of the contraindications apply, in a non-sterile environment. The solution is not intended to be used on patients with open wounds or irritated skin or during surgery.

Here's a summary of the acceptance criteria and the study that proves the device meets them, based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance:

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

• ACR TI-RADS Classification Validation: 196 male and female patients.
  • Provenance: US, Europe & Brazil (across multiple ethnicities).
• Individual ACR TI-RADS sub-parameters: A subset of 102 patients (likely from the 196 patient ACR TI-RADS dataset).
• Volume Measurement Validation: The text does not explicitly state the number of cases or patients used for volume measurement validation apart from indicating "against conventional protocol."

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

The text states that the ground truth for performance studies is "annotated data sets labeled by medical specialists" and for the predicate device, "the ROI labeled by a panel of specialists." However, the number and specific qualifications (e.g., "radiologist with 10 years of experience") of these experts are not specified in the provided document for either the subject device or the predicate.

4. Adjudication Method:

The adjudication method (e.g., 2+1, 3+1) for establishing ground truth is not specified in the provided document. The text only mentions "annotated data sets labeled by medical specialists."

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study:

A full MRMC comparative effectiveness study where human readers improve with AI vs without AI assistance is not explicitly described in the provided text. The performance data focuses on:

• Standalone validation of volume measurements against a conventional protocol.
• Standalone validation of ACR TI-RADS classification against conventional 2D ultrasound.

The device is intended to "assist and support medical professionals" and provides "additional information during image review," with "proposed results that must be verified, adjusted if necessary, and confirmed by the user." This implies a human-in-the-loop system, but the study described does not quantify the improvement of human readers specifically with the AI assistance compared to without it.

6. Standalone (Algorithm Only Without Human-in-the-Loop Performance) Study:

Yes, standalone performance was done for several aspects:

• Volume Measurement Validation: The device's volume measurements were validated against a conventional protocol. While a "conventional protocol" likely involves human action, the evaluation of the device's accuracy in producing "volume measurements" and "Lin's Concordance Correlation Coefficient," "Mean Squared Error" implies a standalone assessment of the algorithm's output.
• ACR TI-RADS Classification Validation: The PIUR tUS Infinity's ACR TI-RADS classification was assessed for non-inferiority against conventional 2D ultrasound, which suggests a standalone evaluation of the algorithm's classification output.
• Individual ACR TI-RADS sub-parameters: Performance was assessed for these sub-parameters, again indicating a standalone evaluation of the algorithm's ability to characterize these features.

7. Type of Ground Truth Used:

The ground truth used for performance studies is "annotated data sets labeled by medical specialists." This implies expert consensus or expert-labeled data.

8. Sample Size for the Training Set:

The document does not provide any information regarding the sample size used for the training set for the computer vision and machine learning algorithms.

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

The document does not provide any specific information on how the ground truth for the training set was established. It only generally states that the device uses "computer vision and machine learning algorithms" and that "the ground truth to be established for performance studies of the device are annotated data sets labeled by medical specialists." It does not differentiate between training and test set ground truth establishment methodologies.

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