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The I-neb AAD system with TIM is a nebulizer system designed to aerosolize liquid medication for inhalation by the patient in the home care, nursing home, sub-acute institution, or hospital environment.

The I-neb Insight AAD System is monitoring software that provides feedback to the patient recording treatment events, including treatment times and compliance data which is also available to the clinician. It is an accessory to an accessory for use with the I-neb AAD system.

The I-neb AAD system with TIM is intended for patients 3 years and older who can coordinate breathing.

The I-neb AAD System is an ultrasonic (vibrating mesh) nebulizer system designed to aerosolize liquid medication (except pentamidine) for inhalation by the patient in the home care, nursing home, sub-acute institution, or hospital environment.

The I-neb Insight AAD System is an accessory for use with the I-neb AAD system and controls monitoring software that provides feedback to the patient recording treatment events, including treatment times and compliance data which is also available to the clinician.

The I-neb AAD system with TIM incorporates a modification of the predicate I-neb AAD system with (tidal breathing mode (TBM)), K042991. While the I-neb Insight incorporates updated software to accommodate the added TIM feature, it is a modification of the predicate I-neb Insight AAD System, K052941.

The provided text describes a 510(k) summary for the I-neb AAD Systems with TIM and I-neb Insight AAD System. The primary method for demonstrating substantial equivalence is through comparative bench testing against predicate devices. The document does not describe a study in the context of AI/ML device performance, as it is a medical device from 2011, long before the widespread use of AI in medical imaging. Therefore, many of the questions related to AI device performance are not applicable.

Here's an analysis based on the provided text:

Acceptance Criteria and Reported Device Performance

The acceptance criteria for this device are implicitly tied to demonstrating substantial equivalence to existing predicate devices (K062263 – Omron U-22, K870027 - Salter 8900 nebulzier, K072019 - Activaero - AKITA2 APIXNEB, K042991 - I-neb AAD, K052491 - I-neb Insight). The "acceptance criteria" are not explicitly stated as numerical thresholds but rather as the proposed device exhibiting comparable performance characteristics to the predicates in specific areas.

Study Details:

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

   • The document mentions "3 drugs" were used for particle characterization.
   • The testing was "performed at flow rates of 15 lpm and 30 lpm."
   • The sample sizes for "comparative dosing" are not explicitly stated, but it was done between the I-neb AAD system in TBM vs. TIM mode and compared to Omron U22 and Salter 8900.
   • This was bench testing, not human clinical data. Therefore, the concept of "country of origin for data" or "retrospective/prospective" human data does not apply here.

2. 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)

   • Not applicable. This submission relies on bench testing, not expert-adjudicated ground truth from human data for AI/ML performance.

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

   • Not applicable. This was bench testing, not a human consensus or adjudication study.

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

   • No. This is a 2011 submission for a nebulizer, not an AI/ML diagnostic tool. An MRMC study was not conducted, nor would it be relevant for this device.

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

   • Not applicable. This device is a nebulizer system, not an AI algorithm.

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

   • The "ground truth" for this submission are the performance specifications and characteristics of the predicate devices, against which the proposed device's bench test results (e.g., MMAD, GSD, gravimetric dose) were compared to demonstrate substantial equivalence.

7. The sample size for the training set

   • Not applicable. This device does not involve an AI/ML algorithm requiring a training set.

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

   • Not applicable. This device does not involve an AI/ML algorithm.

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The AKITA JET is a nebulizer system that will be used with patients for whom doctors have prescribed medication (except pentamidine) for nebulization in the home care, nursing home, subacute institution, or hospital environment.

The AKITA JET nebulizer and the AKITA JET nebulizer handset together constitute a multi-use, electronic nebulizer system designed to aerosolize liquid medications. The system includes and features:

• An electrically powered compressor which provides an air flow to the AKITA JET ● nebulizer handset.
• . A nebulizer handset based upon the PARI LC Sprint, K060399
• Single patient, multi-use in the home setting .
• . Multiple patient, multi-use in the hospital and clinical settings
• .
• . Nebulization only during inhalation phase
• Smart Card series for defined patient breathing patterns .

The provided document is a 510(k) summary for the AKITA JET nebulizer system, demonstrating substantial equivalence to predicate devices. It outlines the device description, indications for use, and a high-level overview of performance tests conducted. However, it does not contain detailed information about specific acceptance criteria or the study data that would allow for a comprehensive answer to your request regarding detailed performance metrics, sample sizes, ground truth establishment, or multi-reader studies.

The document focuses on comparing the AKITA JET to predicate devices across several categories to prove substantial equivalence rather than presenting a de novo performance study against pre-defined acceptance criteria.

Therefore, I cannot provide a table of acceptance criteria and reported device performance, nor details on sample sizes for test/training sets, expert qualifications, adjudication methods, MRMC studies, or standalone performance, based solely on the information given in the provided text.

Here's what can be extracted and what is missing:

Acceptance Criteria and Study Information for AKITA JET Nebulizer System

The provided 510(k) summary focuses on demonstrating "substantial equivalence" to predicate devices, rather than establishing de novo acceptance criteria with specific quantitative thresholds that are then met by a new study. The performance tests mentioned are generally for comparison with existing similar devices or to ensure basic safety and effectiveness.

1. Table of Acceptance Criteria and Reported Device Performance

Important Note: The document states, "There are no significant differences that affect the safety or effectiveness of the intended device as compared to the predicate devices." This is the primary "acceptance criterion" in a 510(k) pathway, implying that the device performs equivalently to the listed predicate devices in the noted categories. Specific quantitative thresholds for these categories are not provided.

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

• Sample Size: Not specified in the provided text.
• Data Provenance: Not specified. Standard performance testing for medical devices is typically conducted in a laboratory setting, but the geographical origin or whether it's retrospective/prospective is not mentioned.

3. Number of Experts Used and Qualifications

• Number of Experts: Not applicable. This type of performance testing for a nebulizer typically involves technical measurements and comparisons, not expert clinical evaluation of images or data in the way, for example, a diagnostic AI device would.
• Qualifications: N/A

4. Adjudication Method for the Test Set

• Adjudication Method: Not applicable. The tests described (e.g., cascade impactor, electrical safety) involve objective measurements against standards or predicate devices, not subjective assessments requiring adjudication.

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

• MRMC Study: No, an MRMC study was not done. This type of study is relevant for diagnostic devices where human readers interpret data (e.g., medical images), often with and without AI assistance, to assess diagnostic performance. The AKITA JET is a drug delivery device (nebulizer system), not a diagnostic tool.

6. Standalone (Algorithm Only) Performance Study

• Standalone Study: Yes, in a sense. The described performance tests (e.g., particle characterization, delivery, electrical safety) are conducted on the device itself without human-in-the-loop clinical interpretation. The "algorithm" in this context refers to the device's operational programming (e.g., for breathing patterns, controlled inhalation flow), and its performance would be assessed as part of the overall device functionality. However, it's not a "standalone algorithm" performance in the way a diagnostic AI would be evaluated.

7. Type of Ground Truth Used

• Type of Ground Truth: The "ground truth" for the performance tests would be established by:
  • Objective Measurements: Against established physical and engineering standards (e.g., for particle size distribution, electrical safety, VOC emissions).
  • Predicate Device Performance: The measured performance parameters of the AKITA JET were compared directly to those of the predicate devices (PARI LC Sprint, AKITA 2 APIXNEB, Vortran AutoNeb) to establish substantial equivalence.

8. Sample Size for the Training Set

• Sample Size: Not specified. Nebulizers are hardware devices with embedded software; they don't typically undergo machine learning "training" in the same way an AI diagnostic algorithm would. The development process involves engineering, design, and internal testing, which could be considered an iterative development ("training") process, but a specific "training set sample size" as relevant to AI/ML is not applicable or provided here.

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

• Ground Truth Establishment: Not applicable as defined for AI/ML models. The functionality and performance of the nebulizer system were established through engineering design principles, manufacturing specifications, and testing against those specifications and relevant regulatory standards.

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