Search Results

The X-CUBE 90 diagnostic ultrasound system is intended for use by, or by the order of, and under the supervision of, a licensed physician who is qualified for the evaluation of soft tissue and blood flow in the clinical applications of Fetal; Abdominal(renal & GYN/pelvic); Pediatric; Small Organ(breast, testes, thyroid); Neonatal Cephalic; Adult Cephalic; Trans-rectal; Trans-vaginal; Musculo-skeletal(Conventional); Musculo-skeletal(Superficial); Cardiatric); Peripheral Vessel(PV); and Urology(including prostate).

And, in the imaging modes of 2D(B) mode; Harmonic mode(HAR); M mode; Anatomical M mode; Color Flow Doppler(CF) Mode; Power Doppler(PD) Mode; Directional PD mode; Pulsed Wave Doppler(PWD) Mode; Continuous Wave Doppler(CWD) Mode; High PRF Doppler mode; Tissue Doppler Imaging(TDI) Mode; 3D/4D mode. The X-CUBE 90 is intended to be used in a hospital or medical clinic.

X-CUBE 90 product is an ultrasound imaging system for medical diagnosis. This innovative system platform provides optimal patient diagnosis workflow with the wide flat panel display, ergonomic control panel with easy user interface, optimal image quality.

The provided text describes the Alpinion Medical Systems Co., Ltd. X-CUBE 90 ultrasound system and its equivalence to predicate devices, but it does not include information about acceptance criteria or a study proving device performance in the context of AI/ML.

The document is a 510(k) summary for a traditional medical device (ultrasound system), not an AI/ML-powered device. Therefore, it focuses on demonstrating substantial equivalence to previously cleared ultrasound systems based on technical characteristics, indications for use, and compliance with general medical device safety standards.

Here's what can be extracted from the document, with the understanding that the request for AI/ML-specific details cannot be fully met from the provided text:

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

The document does not specify quantitative clinical performance acceptance criteria or report device performance in terms of metrics like sensitivity, specificity, or AUC, which are common for AI/ML devices. Instead, it demonstrates performance by comparing its features and characteristics to legally marketed predicate devices, asserting that it is as safe and effective.

The acceptance criteria are implicitly based on compliance with recognized medical device standards and having equivalent specifications and functionalities to the predicate devices.

Regarding the sections specific to AI/ML devices (points 2-9 in your request), the provided text does not contain this information as it describes a conventional ultrasound system, not an AI/ML powered one.

Therefore, the following cannot be answered from the provided document:

• 2. Sample size used for the test set and the data provenance: Not applicable, as no AI/ML test set is mentioned.
• 3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable.
• 4. Adjudication method (e.g. 2+1, 3+1, none) for the test set: Not applicable.
• 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: Not applicable.
• 6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable.
• 7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.): Not applicable.
• 8. The sample size for the training set: Not applicable, as no AI/ML training set is mentioned.
• 9. How the ground truth for the training set was established: Not applicable.

Summary of Non-Clinical and Clinical Tests (from the document):

• Summary of Non-Clinical Tests: The X-CUBE 90 was evaluated for biocompatibility, acoustic output, and thermal, electrical, electromagnetic, and mechanical safety. It was found to conform to various medical device safety standards (IEC 60601-1, IEC 60601-1-2, IEC 60601-2-37, AAMI/ANSI/ISO10993-1, AAMI/ANSI/ISO14971, AIUM MUS, NEMA UD 2, NEMA UD 3). Quality management system measures were also applied, including risk management, requirements reviews, design reviews, component verification, integration review, performance testing, safety testing, and design validation.
• Summary of Clinical Tests: The submission explicitly states: "The subject of this premarket submission, X-CUBE 90, did not require clinical studies to support substantial equivalence." This is typical for 510(k) submissions of conventional devices demonstrating equivalence to existing ones.

Ask a specific question about this device

The X-CUBE 90 diagnostic ultrasound system is intended for use by, or by the order of, and under the supervision of, a licensed physician who is qualified for the evaluation of soft tissue and blood flow in the clinical applications of Fetal; Abdominal(renal & GYN/pelvic); Pediatric; Small Organ(breast, testes, thyroid); Neonatal Cephalic; Adult Cephalic; Trans-rectal; Trans-vaginal; Musculo-skeletal(Conventional); Musculo-skeletal(Superficial); Cardiac(adult& pediatric); Peripheral Vessel(PV); and Urology(including prostate).

And, in the imaging modes of 2D(B) mode; Harnonic mode(HAR); M mode; Anatomical M mode; Color Flow Doppler(CF) Mode; Power Doppler(PD) Mode; Directional PD mode; Pulsed Wave Doppler(PWD) Mode; Continuous Wave Doppler(CWD) Mode; High PRF Doppler mode; Tissue Doppler Imaging(TDI) Mode; 3D/4D mode. The X-CUBE 90 is intended to be used in a hospital or medical clinic.

X-CUBE 90 product is an ultrasound imaging system for medical diagnosis. This innovative system platform provides optimal patient diagnosis workflow with the wide flat panel display, ergonomic control panel with easy user interface, optimal image quality.

The provided document is an FDA 510(k) premarket notification for the Alpinion Medical Systems Co., Ltd. X-CUBE 90 ultrasound system. This type of submission is for demonstrating substantial equivalence to a legally marketed predicate device, rather than proving efficacy through clinical studies for novel devices.

Therefore, the acceptance criteria and study detailed here are focused on demonstrating that the new device (X-CUBE 90) performs equivalently to previously cleared predicate devices and complies with relevant safety and performance standards. It does not involve a traditional clinical study with patient data in the sense of an Artificial Intelligence (AI) device seeking de novo authorization or PMA.

Based on the provided text, here's an analysis of the acceptance criteria and the study that proves the device meets them:

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

The document does not explicitly present a "table of acceptance criteria" related to specific performance metrics for the ultrasound imaging capabilities beyond what is implied by the comparison to predicate devices and adherence to standards. Instead, substantial equivalence is demonstrated by a comparison of features, technical specifications, and compliance with recognized safety standards. The "performance" is implicitly deemed equivalent if these factors are comparable to or better than the predicate devices.

Here's a breakdown of the comparison presented in the "Determination of Substantial Equivalence: Comparison table with Predicate devices" on page 25:

Acceptance Criteria (Implicit from Substantial Equivalence):

The acceptance criteria for this 510(k) submission are implicitly defined by demonstrating that the X-CUBE 90 is "substantially equivalent" to legally marketed predicate devices (primarily K181277 E-CUBE 12). This means:

• Same intended use: The X-CUBE 90 has the same indications for use as the predicate device.
• Same technological characteristics: The device uses the same fundamental technology (ultrasound, various imaging modes and functions).
• No new questions of safety or effectiveness: Any differences in technological characteristics do not raise new questions of safety or effectiveness. This is primarily addressed through compliance with established safety and performance standards.

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

The document explicitly states: "The subject of this premarket submission, X-CUBE 90, did not require clinical studies to support substantial equivalence."

This means there was no dedicated clinical test set of patient data in the typical sense for demonstrating diagnostic accuracy or efficacy. The "study" for this submission primarily consists of non-clinical performance testing, compliance with international safety and performance standards, and comparisons of technical specifications and features to predicate devices.

Therefore, there is no sample size for an an imaging test set, and no data provenance relevant to patient-derived images.

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

As there was no clinical study involving a test set of patient data to establish ground truth diagnoses, this information is not applicable.

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

Not applicable, as there was no clinical test set for which ground truth adjudication was required.

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

No MRMC study was conducted. This device is an ultrasound system, not an AI-assisted diagnostic tool that would typically be evaluated for reader improvement.

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

Not applicable. This is not an AI algorithm.

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

Not applicable, as no clinical ground truth was established for a test set. The "ground truth" for this type of submission is adherence to recognized performance standards and demonstrated technological equivalence to already cleared devices.

8. The sample size for the training set

Not applicable. This device is an ultrasound imaging system, not an AI/machine learning model whose performance is enhanced through training on a dataset.

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

Not applicable, as there was no training set for an AI/machine learning model.

In summary, this 510(k) submission for the X-CUBE 90 ultrasound system primarily relies on non-clinical testing and comparison to predicate devices, rather than clinical studies with patient data and ground truth establishment, to demonstrate substantial equivalence. The "acceptance criteria" are met by demonstrating that the device's technical specifications, imaging modes, and overall performance fall within the established safety and effectiveness profile of already cleared ultrasound systems, and by proving compliance with relevant international and national medical device standards.

Ask a specific question about this device