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iBreastExam Gen II device is intended to produce a surface pressure map of the breast as an aid in documenting palpable breast lesions identified during a clinical breast exam. iBreastExam Gen II device is intended for use by a qualified healthcare professional trained in its use and is not for home use.

iBreastExam Gen II is a visual mapping system, intended to produce a surface pressure map of the breast as an aid in documenting breast lesions identified during a clinical breast exam. The use of iBreastExam Gen II does not involve the use of any ionizing radiation. The iBreastExam Gen II system consists of a group of hardware and software components. The hardware component(s) consist of: iBreastExam Gen II Scanhead, Computer System, USB Wall Charger and Charging Cables. The software component(s) consist of: iBEConnect Software Program.

The iBreastExam Gen II device is intended to produce a surface pressure map of the breast to aid in documenting palpable breast lesions identified during a clinical breast exam. It is not for diagnosis, but purely a documentation tool. Clinical management decisions should be based on clinical and diagnostic examinations (e.g., ultrasound or mammography).

Here's a breakdown of the acceptance criteria and study details:

1. Table of Acceptance Criteria and Reported Device Performance

The provided text describes performance testing related to accuracy and reproducibility, but it does not explicitly state specific pass/fail acceptance criteria (e.g., "accuracy must be greater than X%") for the device's performance characteristics in a numerical form. Instead, the conclusions for each test conducted state that the device "produced accurate and reproducible results." The closest numerical performance characteristic mentioned is "Detectable lesion size: 5mm and above" for both the subject and predicate devices, which can be inferred as a performance expectation.

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

For the inter-observer, intra-observer, and inter-system bench tests, the sample size used was 20 subjects.

The tests were performed on silicone phantoms constructed by layering slabs of silicon with lesions placed in between. This indicates that the testing was conducted prospectively in a controlled lab environment using simulated tissue, rather than on human patients or retrospective clinical data. Therefore, there is no country of origin for patient data in this context.

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

The ground truth for the test set (silicone phantoms) was established by the physical construction of the phantoms themselves, which included lesions of defined location, size, stiffness, and shape. The "experts" in this context were effectively the creators of the phantoms, who embedded the known characteristics.

The testing methodology involved "recruits" (20 subjects) who were "instructed on how to use iBreastExam Gen II and was allowed to perform several practice exams prior to the study." These recruits were the operators performing the measurements, not experts establishing ground truth or interpreting results, as the device's purpose is documentation of palpable lesions. The document does not specify qualifications for these recruits beyond being trained to use the device.

4. Adjudication Method for the Test Set

There was no adjudication method described in the context of establishing ground truth for the test set, as the ground truth was inherently known from the design of the silicone phantoms (known lesion location, size, stiffness, and shape).

For the inter-observer and intra-observer tests, the reproducibility and accuracy were measured against this known phantom ground truth, and for inter-system, it was comparing measurements from different devices against the same phantom.

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

There was no MRMC comparative effectiveness study mentioned in the provided text. The device, iBreastExam Gen II, is described as a "breast lesion documentation system" that produces a "surface pressure map." Its function is to aid in documenting already palpable lesions and is not intended for diagnosis. The study described focuses on the device's accuracy and reproducibility in measuring known characteristics on phantoms when operated by different individuals or with different devices, not on how it assists human readers in diagnosis or detection. The device itself is not an AI-assisted diagnostic tool.

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

The provided text describes direct interaction between a human operator ("recruit") and the device. The device collects data based on human operation (placing the scanhead on the phantom) and then presents a tactile map via software. The "iBEConnect Software Program" provides positioning guidance and processes data. However, the performance tests described (inter-observer, intra-observer, inter-system) inherently include a human operator in the loop. The device is explicitly stated to be for use by a "qualified healthcare professional trained in its use." Therefore, a standalone (algorithm only without human-in-the-loop) performance study was not explicitly described or, due to the nature of the device, likely conducted as its intended use requires interaction.

7. The Type of Ground Truth Used

The ground truth used for the performance testing was known physical characteristics of silicone phantoms (defined lesion location, size, stiffness, and shape). This is a form of engineered or simulated ground truth, rather than expert consensus, pathology, or outcomes data from human patients.

8. The Sample Size for the Training Set

The document does not describe a "training set" in the context of machine learning or AI. The tests performed are verification and validation of the device's measurement capabilities. If any internal calibration or parameter setting during device development involved data, it is not mentioned. The user training described for the 20 recruits refers to training them on how to use the device, not training the device's internal algorithms.

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

Since no specific "training set" for the device's algorithms or software was described (beyond general software validation), the method for establishing its ground truth is not applicable or detailed in the provided information. The device functions by physical principles (capacitive pressure sensors) and software processing, not through a learning algorithm that requires a separate training dataset with established ground truth.

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The SureTouch Mobile Pressure Mapping System is intended to produce a surface pressure map of the breast as an aid in documenting palpable breast lesions identified during a clinical breast examination. The SureTouch Mobile Pressure Mapping System is intended for use by a qualified healthcare professional trained in its use and is not for home use.

The SureTouch Mobile Pressure Mapping System ("SureTouch") is a computer-based device that produces a pressure map, called a tactile image, of specific areas of the breast as an aid to document lesions detected during a clinical breast exam. SureTouch utilizes a rechargeable, battery-powered hand-held wand (sensor unit) that incorporates a 30 x 40 mm array of pressure sensing elements to collect tactile data as the device is moved across the breast. Data collected using the wand are wirelessly transferred to the tablet display where they are used to generate tactile images and provide information on a lesion's size, shape and hardness. The final report includes a tactile image of each lesion along with its user inputted location. The SureTouch System also includes a calibration and training phantom, a scale to ensure correct force applied during calibration procedures, and a holder for the wand.

Here's an analysis of the provided text to fulfill your request, broken down by the specific points you asked for.

Please Note: The provided text is a 510(k) summary, which focuses on demonstrating substantial equivalence to a predicate device. It usually does not contain a detailed report of clinical study results, particularly for a device like this that is for documentation rather than diagnosis or treatment. Therefore, some of your requested information, especially regarding clinical performance metrics (like sensitivity, specificity, or reader improvement with AI), will not be explicitly available in this document.

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

The document mentions that various tests "met all acceptance criteria" but does not explicitly list the quantitative acceptance criteria for most of the performance tests. It also doesn't provide specific numerical performance results beyond stating that criteria were met.

2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

The document does not provide details on the sample size used for any specific test sets or the provenance of the data (country, retrospective/prospective). This type of information is typically found in more detailed study reports, not a 510(k) summary.

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 does not provide this information. It refers to "intra and inter-observer" testing, which implies multiple observers, but does not specify their number, qualifications, or how ground truth was established for these tests. For a Breast Lesion Documentation System rather than a diagnostic one, "ground truth" might refer to the actual physical properties of simulated lesions or consensus on manual palpation findings, rather than a diagnostic gold standard like pathology.

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

The document does not provide this information.

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 describe an MRMC comparative effectiveness study involving human readers with and without AI assistance to improve diagnostic performance. The device is a "documentation system," not an AI diagnostic aid in the traditional sense discussed in MRMC studies.

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

The document describes "Algorithm output sensitivity" testing, which suggests standalone algorithm performance was evaluated for sensitivity to calibration errors. However, it does not provide details on a standalone diagnostic performance (e.g., sensitivity/specificity of the algorithm alone to detect lesions) because the device's intended use is to document palpable lesions identified by a healthcare professional, not to independently detect them.

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

The document does not explicitly state the type of ground truth used for its performance testing. Given the "phantom testing" and "intra and inter-observer" testing in the context of a "documentation system" for palpable lesions, the ground truth likely involved:

• Physical characteristics of simulated lesions in phantoms: For tests related to accuracy of sensor measurements or calibration pad aging.
• Expert consensus on palpable characteristics: For tests related to intra- and inter-observer reproducibility of documenting palpable lesions.
  It is highly unlikely that pathology or outcomes data would be used as ground truth for a device whose indication is documentation of palpable findings.

8. The sample size for the training set

The document is a 510(k) summary for a medical device that processes sensor data rather than being a deep learning AI model that requires a "training set" in the machine learning sense. The term "training set" is not mentioned, and thus no sample size is provided. The device described appears to be a tactile sensor system, not an AI imaging interpretation system.

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

As there is no mention of a "training set" in the context of machine learning, this information is not applicable and not provided.

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iBreastExam™ device is intended to produce a surface pressure map of the breast as an aid in documenting palpable breast lesions identified during a clinical breast exam. iBreastExam™ device is intended for use by a qualified healthcare professional trained in its use and is not for home use.

The iBreastExam system consists of a group of hardware and software components. The hardware component(s) consist of: iBreastExam Scanhead, Computer System, USB Wall Charger and Charging Cables. The software component(s) consist of: iBEConnect Software Program.

The provided text does not contain detailed information about acceptance criteria and a comprehensive study showing the device meets those criteria. However, I can extract the available information and highlight what is missing based on your request.

Here's a breakdown of the information present and absent:

Information Present in the Document:

• Device Name: iBreastExam
• Intended Use: To produce a surface pressure map of the breast as an aid in documenting palpable breast lesions identified during a clinical breast exam. It is a documentation tool, not for diagnosis.
• Predicate Device: BREASTVIEW® VISUAL MAPPING SYSTEM (K010514)
• Performance Testing Mentioned:
  • Electrical safety tests
  • Electromagnetic compatibility tests
  • Biocompatibility tests
  • Side-by-side performance test between iBreastExam and the predicate device (BreastView).
  • Validation and verification performed on software and hardware subsystems.
• Conclusion: All test results were satisfactory and did not raise any additional safety or effectiveness concerns, leading to a substantial equivalence determination.

Information NOT Present in the Document (and therefore cannot be provided in the tables/sections you requested):

• Specific Acceptance Criteria: The document mentions "Performance tests were conducted per Class II Special Controls Guidance Document: Breast Lesion Documentation System," but it does not list the specific quantitative acceptance criteria for these tests (e.g., a required sensitivity, specificity, accuracy, or a threshold for deviation from the predicate).
• Reported Device Performance against specific criteria: While it states "all test results were satisfactory," it lacks numerical performance data for the iBreastExam against any defined acceptance criteria.
• Detailed Study Information:
  • Sample size for the test set.
  • Data provenance (country of origin, retrospective/prospective).
  • Number and qualifications of experts for ground truth.
  • Adjudication method for the test set.
  • Results of a multi-reader multi-case (MRMC) comparative effectiveness study, including effect size.
  • Standalone algorithm performance (algorithm only without human-in-the-loop).
  • Type of ground truth used (expert consensus, pathology, outcomes data).
  • Sample size for the training set.
  • How ground truth for the training set was established.

Given the limited information, I will present what can be inferred or directly stated, and clearly mark the missing details.

1. Table of Acceptance Criteria and Reported Device Performance

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

• Sample Size for Test Set: Not specified in the document.
• Data Provenance: Not specified in the document. (The document mentions a "side-by-side performance test" but gives no details on the study population or context.)

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

• Not specified in the document. The document refers to the device aiding in documenting "palpable breast lesions identified during a clinical breast exam," implying clinical examination as the basis, but does not detail how ground truth for the testing was established or how many experts were involved.

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

• Not specified in the document.

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 a MRMC study done? The document describes a "side-by-side performance test" with a predicate device, but it does not indicate a multi-reader multi-case (MRMC) comparative effectiveness study with human readers improving with AI assistance. The iBreastExam is described as a "documentation tool" for lesions already palpated.
• Effect size of human readers improving with AI vs without AI assistance: Not applicable/not provided based on the studies described.

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

• The document implies a standalone performance for the device in capturing pressure maps, but it is explicitly stated that the device's output is an "aid in documenting palpable breast lesions identified during a clinical breast exam," and it's not for diagnosis. It's used by a "qualified healthcare professional." No specific standalone performance metrics (e.g., sensitivity/specificity for detecting lesions) are provided, only its ability to collect data and produce a map.

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

• The document implies the ground truth for the "palpable breast lesions" would be based on clinical breast exam findings, as the device is intended to document such lesions. However, the specific method for establishing ground truth for the performance testing is not detailed. It does not mention pathology or outcomes data for the performance study.

8. The sample size for the training set

• Not specified in the document.

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

• Not specified in the document.

In summary, the provided FDA 510(k) letter and summary describe the device's intended use, technological characteristics, and a general statement about performance testing leading to substantial equivalence. However, it lacks the detailed quantitative performance criteria, study design parameters (sample sizes, expert roles, ground truth establishment methods), and specific results that would be required to fully answer your request regarding acceptance criteria and their proven fulfillment. The document focuses on establishing substantial equivalence to a predicate device rather than providing a detailed performance study with explicit acceptance criteria.

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