(138 days)
The Tyto Insights for Wheeze Detection is an over the-counter artificial intelligence (Al) enabled decision support software system used in the evaluation of lung sounds in adults and pediatrics (2 years and older). It automatically analyzes the acoustic signal of the lung as recorded by the FDA cleared compatible Tyto Stethoscope and identifies recordings where a specific abnormal lung sound suggestive of "Wheeze" is suspected. It is not intended to detect other abnormal or normal lung sounds. A licensed health care professional's advice is required to understand the meaning of the Tyto Insights for Wheeze Detection result. Healthcare providers should consider the device result in conjunction with recording and other relevant patient data.
The Tyto Insights for Wheeze Detection is a web-based (AI) enabled software system designed to aid in the clinical assessment of lungs auscultation sound data by analyzing recorded lung sounds to determine whether a Wheeze is detected within the recorded sound data.
The Tyto Insights for Wheeze Detection Software is intended to process recordings from the FDA-cleared compatible Tyto Stethoscope (Tyto Stethoscope, K181612). The acquisition of the acoustic data (recordings) is carried out by a professional user in a clinical environment or by a lay- user in a non-medical environment, in compliance with the labeling of the Tyto Stethoscope. The system is composed of the following sub-systems:
-
- The Tyto Insights for Wheeze Detection Application Server (APS) communicates with the Tyto Insights for Wheeze Detection Algorithm Server (ALS) and implements an application programming interface (API) for communication with the telehealth server.
-
- The Tyto Insights for Wheeze Detection Algorithm Server (ALS) receives an audio file as input and returns an analysis result of positive or negative regarding whether a wheeze was detected as output.
- The Tyto Insights for Wheeze Detection Web Server (WBS) provides a graphic 3. indication whether a wheeze is detected in the recording. It can be utilized both in patient and clinician side.
All the software subsystems (servers and storage) are hosted in the cloud and communicate through IP network.
Here's a breakdown of the acceptance criteria and study details for the "Tyto Insights for Wheeze Detection" device, based on the provided FDA 510(k) summary:
1. Table of Acceptance Criteria and Reported Device Performance
The document doesn't explicitly state "acceptance criteria" as a pass/fail threshold, but rather focuses on comparing the device's performance to its predicate and demonstrating non-inferiority. The key performance metrics are sensitivity, specificity, and Area Under the Curve (AUC).
| Performance Metric | Acceptance Criterion (Implicit) | Reported Device Performance (Tyto Insights for Wheeze Detection) |
|---|---|---|
| Primary Endpoint | Non-inferiority to the predicate device (TytoCare Lung Sounds Analyzer K221614) based on AUC. Specifically, the lower bound of the 95% two-sided CI for the difference in AUCs (Insights - Analyzer) must be higher than a non-inferiority margin of -0.05. | Insights - Analyzer: 0.0570 (LCI: 0.0289, UCI: 0.0917) |
| Standalone Sensitivity | Not explicitly defined as a pass/fail criterion in the document, but provided as a secondary endpoint. | 0.54 (95% CI: 0.43 - 0.65) |
| Standalone Specificity | Not explicitly defined as a pass/fail criterion in the document, but provided as a secondary endpoint. | 0.98 (95% CI: 0.97 - 0.99) |
| Positive Predictive Value (PPV) | Not explicitly defined as a pass/fail criterion. | 0.72 (95% CI: 0.48 - 0.89) |
| Negative Predictive Value (NPV) | Not explicitly defined as a pass/fail criterion. | 0.97 (95% CI: 0.97 - 0.98) |
| Overall Diagnostic Accuracy | The document states "The overall diagnostic performance show overall good diagnostic accuracy." This is a qualitative statement summarizing the quantitative metrics. | Demonstrated by the above metrics and non-inferiority of AUC. |
Conclusion regarding acceptance criteria: The device met the primary endpoint of non-inferiority to the predicate device based on AUC, as the lower bound of the 95% CI for the difference in AUCs (0.0289) was well above the non-inferiority margin of -0.05.
2. Sample Size Used for the Test Set and Data Provenance
- Sample Size for Test Set: 371 recordings, corresponding to 359 patients. (86 recordings were Wheeze positive and 285 negative).
- Data Provenance: Retrospective validation dataset sourced from real-world use of the FDA cleared compatible Tyto Stethoscope. The country of origin is not explicitly stated, but Tyto Care Ltd. is based in Israel.
3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications
- Number of Experts: Three blinded experienced Pulmonologists.
- Qualifications of Experts: Described as "experienced Pulmonologists." Specific details like years of experience are not provided.
4. Adjudication Method for the Test Set
- Adjudication Method: Binary ground truth was determined by a majority vote of the three blinded Pulmonologists. This implies a "3+1" approach where if at least two out of three experts agreed on the presence or absence of wheeze, that was considered the ground truth.
5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was Done
- There is no indication of a Multi-Reader Multi-Case (MRMC) comparative effectiveness study being performed with human readers with and without AI assistance. The study focused on the stand-alone performance of the AI algorithm and its non-inferiority to a predicate device's algorithm, not on the improvement of human readers with AI assistance.
6. If a Standalone Study (Algorithm Only Without Human-in-the-Loop Performance) was Done
- Yes, a standalone study was done. The performance evaluation section explicitly states: "For the characterization of the stand-alone accuracy, the automated binary result of the software has been compared to ground truth and specificity and sensitivity were calculated." and "The primary end point was area under the Curve (AUC) for the detection of wheezes by the proposed device compared to the TytoCare Lung Sounds Analyzer (K221614)".
7. The Type of Ground Truth Used
- Type of Ground Truth: Expert consensus. Specifically, the binary ground truth was determined by a majority vote of three blinded experienced Pulmonologists.
8. The Sample Size for the Training Set
- The sample size for the training set is not explicitly provided in the document. The text states: "The AI Algorithm was trained with recordings acquired by the real-world use of the compatible Tyto Stethoscope."
9. How the Ground Truth for the Training Set Was Established
- The document states that the AI algorithm was "trained with recordings acquired by the real-world use of the compatible Tyto Stethoscope." However, it does not explicitly detail how the ground truth for this training set was established. It can be inferred that a similar expert labeling process might have been used, but this is not confirmed in the provided text.
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Image /page/0/Picture/0 description: The image shows the logo of the U.S. Food and Drug Administration (FDA). On the left is the Department of Health & Human Services logo. To the right of that is the FDA logo in blue. Underneath the FDA logo is the word "ADMINISTRATION".
December 13, 2023
Tyto Care Ltd. Stella Perry RA&QA Director 14 Beni Gaon Street Natanya, 4250803 Israel
Re: K232237
Trade/Device Name: Tyto Insights for Wheeze Detection Regulation Number: 21 CFR 868.1900 Regulation Name: Diagnostic Pulmonary-Function Interpretation Calculator Regulatory Class: Class II Product Code: PHZ Dated: November 13, 2023 Received: November 14, 2023
Dear Stella Perry:
We have reviewed your section 510(k) premarket notification of intent to market the device referenced above and have determined the device is substantially equivalent (for the indications for use stated in the enclosure) to legally marketed predicate devices marketed in interstate commerce prior to May 28, 1976, the enactment date of the Medical Device Amendments, or to devices that have been reclassified in accordance with the provisions of the Federal Food, Drug, and Cosmetic Act (the Act) that do not require approval of a premarket approval application (PMA). You may, therefore, market the device, subject to the general controls provisions of the Act. Although this letter refers to your product as a device, please be aware that some cleared products may instead be combination products. The 510(k) Premarket Notification Database available at https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm identifies combination product submissions. The general controls provisions of the Act include requirements for annual registration, listing of devices, good manufacturing practice, labeling, and prohibitions against misbranding and adulteration. Please note: CDRH does not evaluate information related to contract liability warranties. We remind you, however, that device labeling must be truthful and not misleading.
If your device is classified (see above) into either class II (Special Controls) or class III (PMA), it may be subject to additional controls. Existing major regulations affecting your device can be found in the Code of Federal Regulations, Title 21, Parts 800 to 898. In addition, FDA may publish further announcements concerning your device in the Federal Register.
Additional information about changes that may require a new premarket notification are provided in the FDA guidance documents entitled "Deciding When to Submit a 510(k) for a Change to an Existing Device"
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(https://www.fda.gov/media/99812/download) and "Deciding When to Submit a 510(k) for a Software Change to an Existing Device" (https://www.fda.gov/media/99785/download).
Your device is also subject to, among other requirements, the Quality System (QS) regulation (21 CFR Part 820), which includes, but is not limited to, 21 CFR 820.30. Design controls; 21 CFR 820.90. Nonconforming product; and 21 CFR 820.100, Corrective and preventive action. Please note that regardless of whether a change requires premarket review. the OS regulation requires device manufacturers to review and approve changes to device design and production (21 CFR 820.30 and 21 CFR 820.70) and document changes and approvals in the device master record (21 CFR 820.181).
Please be advised that FDA's issuance of a substantial equivalence determination does not mean that FDA has made a determination that your device complies with other requirements of the Act or any Federal statutes and regulations administered by other Federal agencies. You must comply with all the Act's requirements, including, but not limited to: registration and listing (21 CFR Part 807); labeling (21 CFR Part 801); medical device reporting of medical device-related adverse events) (21 CFR Part 803) for devices or postmarketing safety reporting (21 CFR Part 4, Subpart B) for combination products (see https://www.fda.gov/combination-products/guidance-regulatory-information/postmarketing-safety-reportingcombination-products); good manufacturing practice requirements as set forth in the quality systems (QS) regulation (21 CFR Part 820) for devices or current good manufacturing practices (21 CFR Part 4, Subpart A) for combination products; and, if applicable, the electronic product radiation control provisions (Sections 531-542 of the Act); 21 CFR Parts 1000-1050.
Also, please note the regulation entitled, "Misbranding by reference to premarket notification" (21 CFR 807.97). For questions regarding the reporting of adverse events under the MDR regulation (21 CFR Part 803), please go to https://www.fda.gov/medical-device-safety/medical-device-reportingmdr-how-report-medical-device-problems.
For comprehensive regulatory information about mediation-emitting products, including information about labeling regulations, please see Device Advice (https://www.fda.gov/medicaldevices/device-advice-comprehensive-regulatory-assistance) and CDRH Learn (https://www.fda.gov/training-and-continuing-education/cdrh-learn). Additionally, you may contact the Division of Industry and Consumer Education (DICE) to ask a question about a specific regulatory topic. See the DICE website (https://www.fda.gov/medical-device-advice-comprehensive-regulatoryassistance/contact-us-division-industry-and-consumer-education-dice) for more information or contact DICE by email (DICE@fda.hhs.gov) or phone (1-800-638-2041 or 301-796-7100).
Sincerely.
Rachana Visaria -S
Rachana Visaria, Ph.D. Assistant Director DHT1C: Division of Sleep Disordered Breathing, Respiratory and Anesthesia Devices OHT1: Office of Ophthalmic, Anesthesia, Respiratory, ENT and Dental Devices
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Office of Product Evaluation and Quality Center for Devices and Radiological Health
Enclosure
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Indications for Use
510(k) Number (if known) K232237
Device Name Tyto Insights for Wheeze Detection
Indications for Use (Describe)
The Tyto Insights for Wheeze Detection is an over the-counter artificial intelligence (Al) enabled decision support software system used in the evaluation of lung sounds in adults and pediatrics (2 years and older). It automatically analyzes the acoustic signal of the lung as recorded by the FDA cleared compatible Tyto Stethoscope and identifies recordings where a specific abnormal lung sound suggestive of "Wheeze" is suspected. It is not intended to detect other abnormal or normal lung sounds. A licensed health care professional's advice is required to understand the meaning of the Tyto Insights for Wheeze Detection result. Healthcare providers should consider the device result in conjunction with recording and other relevant patient data.
| Type of Use (Select one or both, as applicable) | |
|---|---|
| ------------------------------------------------- | -- |
Prescription Use (Part 21 CFR 801 Subpart D)
X Over-The-Counter Use (21 CFR 801 Subpart C)
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Image /page/4/Picture/0 description: The image shows the logo for "tytocare" in blue font. Below the logo, the text "510(k) Summary" is written in a bold, serif font. The logo features a stylized image of a ninja-like character with a round head and two eyes, followed by the company name.
| Submitter Name andAddress: | Tyto Care Ltd.14 Beni Gaon Street Netanya, Israel,4250803 |
|---|---|
| Contact Person: | Stella Raizelman Perry RA & QADirectorEmail: stellar@tytocare.comPhone Number: +972 72-2210750Fax Number: +972 72-2210752 |
| EstablishmentRegistrationNumber: | 3012678246 |
| Date Prepared: | December 13, 2023 |
| Device TradeName(s): | Tyto Insights for Wheeze Detection |
| Device CommonName: | Tyto Insights for Wheeze Detection |
| Classification: | Name: Diagnostic pulmonary-function interpretationcalculatorProduct code: PHZRegulation No: 21 CFR 868.1900Class: IIPanel: Anesthesiology |
Predicate Device(s):
| Device nameTytoCare Lung SoundsAnalyzer | 510(k) No.K221614 | Date of ClearanceJanuary 26, 2023 |
|---|---|---|
| Reference Device(s): | ||
| Device name | 510(k) No. | Date of Clearance |
| eMurmur Heart AI | K220766 | May 31, 2022 |
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Intended use / indication for use statement
The Tyto Insights for Wheeze Detection is an over-the-counter artificial intelligence (AI) enabled decision support software system used in the evaluation of lung sounds in adults and pediatrics (2 years and older). It automatically analyzes the acoustic signal of the lung as recorded by the FDA cleared compatible Tyto Stethoscope and identifies recordings where a specific abnormal lung sound suggestive of "Wheeze" is suspected. It is not intended to detect other abnormal or normal lung sounds. A licensed health care professional's advice is required to understand the meaning of the Tyto Insights for Wheeze Detection result. Healthcare providers should consider the device result in conjunction with recording and other relevant patient data.
Device description
The Tyto Insights for Wheeze Detection is a web-based (AI) enabled software system designed to aid in the clinical assessment of lungs auscultation sound data by analyzing recorded lung sounds to determine whether a Wheeze is detected within the recorded sound data.
The Tyto Insights for Wheeze Detection Software is intended to process recordings from the FDA-cleared compatible Tyto Stethoscope (Tyto Stethoscope, K181612). The acquisition of the acoustic data (recordings) is carried out by a professional user in a clinical environment or by a lay- user in a non-medical environment, in compliance with the labeling of the Tyto Stethoscope. The system is composed of the following sub-systems:
-
- The Tyto Insights for Wheeze Detection Application Server (APS) communicates with the Tyto Insights for Wheeze Detection Algorithm Server (ALS) and implements an application programming interface (API) for communication with the telehealth server.
-
- The Tyto Insights for Wheeze Detection Algorithm Server (ALS) receives an audio file as input and returns an analysis result of positive or negative regarding whether a wheeze was detected as output.
- The Tyto Insights for Wheeze Detection Web Server (WBS) provides a graphic 3. indication whether a wheeze is detected in the recording. It can be utilized both in patient and clinician side.
All the software subsystems (servers and storage) are hosted in the cloud and communicate through IP network.
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Image /page/6/Picture/0 description: The image shows the word "tytocare" in a stylized font. The first letter "t" is connected to a graphic of a face. The letters are all in lowercase and are a blue color. There is a trademark symbol in the upper right corner of the image.
Substantial Equivalence to Predicate Devices
The following table compares the Tyto Insights for Wheeze Detection to the predicate device.
Table 1. Substantial Equivalence Summary
| Device | Predicate device | Reference device | Summary | |
|---|---|---|---|---|
| Device Name | Tyto Insights for WheezeDetection | TytoCare Lungs SoundsAnalyzer | eMurmur Heart AI | NA |
| DeviceManufacturer | Tyto Care Ltd. | Tyto Care Ltd. | CSD Labs GmbH | NA |
| 510(k) Number | K232237 | K221614 | K220766 | NA |
| Device Class | Class II | Class II | Class II | Same as the predicate device. |
| Review Panel | Anesthesiology | Anesthesiology | Cardiology | Same as the predicate device. |
| Product code | PHZ | PHZ | DQD, DQC | Same as the predicate device. |
| Regulation number | 21 CFR 868.1900 | 21 CFR 868.1900 | 21 CFR 870.1875 | Same as the predicate device. |
| Classification Name | Diagnostic pulmonary-function interpretationcalculator,Stethoscope | Diagnostic pulmonary-function interpretationcalculator,Stethoscope | Electronic Stethoscope;Phonocardiograph; | Same as the predicate device. |
| Intended use andindication for use | The “Tyto Insights forWheeze Detection” is an | The TytoCare LungSounds Analyzer is an | The 'eMurmur Heart AI'software is a decision | Same as the predicate device. |
| over-the-counter artificialintelligence (AI) enableddecision support softwaresystem used in theevaluation of lung soundsin adults and pediatrics (2years and older). Itautomatically analyzes theacoustic signal of the lungas recorded by the FDAcleared compatible TytoStethoscope and identifiesrecordings where aspecific abnormal lungsound suggestive of"Wheeze" is suspected. Itis not intended to detectother abnormal or normallung sounds. A licensedhealth care professional'sadvice is required tounderstand the meaningof the Tyto Insights forWheeze Detection result.Healthcare providersshould consider thedevice result inconjunction withrecording and other | over-the-counter decisionsupport software systemused in the evaluation oflung sounds in adults andchildren (2 years andolder). It automaticallyanalyzes the acousticsignal of the lung asrecorded by the FDAcleared compatible TytoStethoscope and identifiesrecordings where aspecific abnormal lungsound suggestive of"Wheeze", is suspected.It is not intended to detectother abnormal or normallung sounds. A licensedhealth care professional'sadvice is required tounderstand the meaningof the TytoCare LungSounds Analyzer result.Healthcare providersshould consider the | support system in theevaluation of recordedpatient heart sounds. Theautomated analysis byeMurmur Heart AIidentifies specific heartsounds that may be present,including S1, S2,physiological heartmurmurs, pathologicalheart murmurs and theabsence of a heart murmur.eMurmur Heart AI isindicated for use in asetting where auscultationwould typically beperformed by a healthcareprovider. It is not intendedas a sole means ofdiagnosis. The heart soundinterpretations offered byeMurmur Heart AI are onlysignificant whenconsidered in conjunctionwith healthcare providerover-read and including allother relevant patient data. | ||
| Device | Predicate deviceconjunction withrecording and otherrelevant patient data. | Reference device | Summary | |
| Type of use | Over-The-Counter Use | Over-The-Counter Use | Prescription use | Same as the predicate device. |
| Intended users | Intended to be used byprofessional users and layusers (18-65 years old). | Intended to be used byprofessional users and layusers (18-65 years old). | Professional users | Same as the predicate device. |
| Intended patientpopulation | Intended for patients of 2years and older | Intended for patients of 2years and older | Intended for patients of allages | Same as the predicate device. |
| Intendedenvironment | Non-clinical (home) andclinical | Non-clinical (home) andclinical | Clinical setting | Same as the predicate device |
| Form | Stand-alone softwaresystem | Stand-alone softwaresystem | Stand-alone softwaresystem | Same |
| Device composition | The following modulescompose the Tyto Insightsfor Wheeze Detection:The Tyto Insights forWheeze DetectionApplication Server(APS)The Tyto Insights forWheeze DetectionAlgorithm Server(ALS)The Tyto Insights forWheeze Detection Web | The following modulescompose the TytoCareLung Sounds Analyzer:The TytoCare LungSounds AnalyzerApplication Server(APS)The TytoCare LungSounds AnalyzerAlgorithm Server(ALS)The TytoCare LungSounds Analyzer Web | 'eMurmur' is a non-medical device softwareplatform which includesthe eMurmur apps andeMurmur web portal.eMurmur Heart AIinteracts with the'eMurmur' softwareplatform. | Same as the predicate deviceBoth the subject device and thereference device include AIenabled algorithm designed forthe analysis of stethoscoperecordings. |
| Device | Predicate device | Reference device | Summary | |
| Server (WBS) provides agraphic indicationwhether a wheeze isdetected in the recordingIt can be utilized both inpatient and clinician side. | Server (WBS) providesa graphic indicationwhether a wheeze isdetected in therecording It can beutilized both in patientand clinician side. | |||
| Input | Lung sounds recorded bycompatible TytoStethoscope | Lung sounds recorded bycompatible TytoStethoscope | Acquires acoustic signalsby means of compatibleelectronic stethoscope | Same |
| Device technologyand operatingprinciple | The recordings arecreated by the compatibleTyto Stethoscope(K181612) and are sentby the third-party point ofcare app to the clinicianapp through the telehealthserver.The telehealth serversends the set of the lungsound recordings to theTyto Insights for WheezeDetection web serverusing its dedicated API.The telehealth serversubsequently sends thelink to results and therelevant UI web view to | The recordings arecreated by the compatibleTyto Stethoscope(K181612) and are sentby the third-party point ofcare app to the clinicianapp through the telehealthserver.The telehealth serversends the set of the lungsound recordings to theTytoCare Lung SoundsAnalyzer web serverusing its dedicated API.The telehealth serversubsequently sends thelink to results and therelevant UI web view to | To analyze heart soundsvia the eMurmur Heart AI,a digital recording of apatient's heart sounds isrequired. Recordings aremade using a supporteddigital stethoscope,connected to a front-endclient like, e.g., theeMurmur app or theeMurmur web portal. Therecorded auscultation dataare transmitted from thefront-end client to theeMurmur backend, whichhosts the eMurmur HeartAI. After analysis by theeMurmur Heart AI, theresults of the analysis on | SimilarThe proposed device, thepredicate and reference deviceacquire lung sounds with devicecleared by the FDA for thatpurpose, analyze the lungsounds and provide indicationon the presence of wheeze.The new algorithm's AI enabledmodality for analysis ofstethoscope recordings doesn'traise different questions ofsafety and effectiveness.Reference device was added tosupport that AI enabledalgorithm designed for the |
| Device | Predicate device | Reference device | Summary | |
| the point of care app andclinician app.The AI enabled algorithmruns automatically andreturns a response foreach audio file with theindication of wheezes tothe telehealth server,which sends a response toboth the clinician side andthe patient side.The length of the signal isdictated by the recordingprocess of the compatibleStethoscope. The subjectdevice processes therecordings in segments ofup to 12 seconds whilesignals shorter than 6seconds will not beprocessed. | the point of care app andclinician app.The rule-based algorithmruns automatically andreturns a response foreach audio file with theindication of wheezes tothe telehealth server,which sends a response toboth the clinician side andthe patient side.The length of the signal isdictated by the recordingprocess of the compatibleStethoscope. The subjectdevice processes therecordings in segments ofup to 12 seconds whilesignals shorter than 6seconds will not beprocessed. | returned to the front-endclient where they aredisplayed to the user.Was not specified. | analysis of stethoscoperecordings, was clearedpreviously by the FDA(K220766) Similar method ofperformance evaluation wasemployed for both devices.Same as the predicate device | |
| Data transfer andstorage | The telehealth serversends the list of therecordings (identified by aunique identifier and timestamp) to the TytoInsights for Wheeze | The telehealth serversends the list of therecordings (identified bya unique identifier andtime stamp) to theTytoCare Lung Sounds | Server analyzes (algorithm)and stores (database)patient-related data andcommunicates with theother components ofeMurmur. The interface to | Same as the predicate device,similar to the reference device. |
| Device | Predicate device | Reference device | Summary | |
| Detection web serverusing its dedicated API.The server executes theTyto Insights for WheezeDetection which runs thealgorithm and providesthe results. Then the TytoInsights for WheezeDetection web serverinitiates the web userinterface.All the softwaresubsystems (server andstorage) are hosted in thecloud and communicatethrough IP network. | Analyzer web serverusing its dedicated API.The server executes theTytoCare Lung SoundsAnalyzer which runs thealgorithm and providesthe results. Then theTytoCare Lung SoundsAnalyzer web serverinitiates the web userinterface.All the softwaresubsystems (server andstorage) are hosted in thecloud and communicatethrough IP network. | the other components is aREST/JSON web API.The backend is not a partof eMurmur Heart AI(medical device); thebackend is part of'eMurmur', a non-medicaldevice. | ||
| Output | • Positive (wheezesuspected),• Negative (Wheeze notsuspected),• The Tyto Insights forWheeze Detection wasnot able to analyze therecording | • Positive (wheezesuspected),• Negative (Wheeze notsuspected),The TytoCare lungssounds analyzer was notable to analyze therecording | Identifies specific heartsounds that may be present,including S1, S2,physiological heartmurmurs, pathologicalheart murmurs and theabsence of a heart murmur. | Same as the predicate deviceSimilarly to the referencedevice, the output is based onthe AI algorithm's analysis. |
| Performance | The primary studyendpoints and hypotheseswere met for the intendedpatient population, thedifference in AUCs was | The primary studyendpoints and hypotheseswere met for the intendedpatient population, thedifference in AUC was in | Sensitivity: 85.0% (72.9%-92.5%)Specificity: 86.7% (74.9%-93.7%) | The study endpoints andhypotheses were met for theintended patient population.The performance of the TytoInsights for Wheeze Detection |
| Device | Predicate device | Reference device | Summary | |
| in favor of Tyto Insightsfor Wheeze Detectioncompared to the predicatedevice and in favor of thenon-inferiority claim.Sensitivity and specificitywere evaluated as thesecondary endpoints.Estimate two-sided 95%CI):Sensitivity: 0.5465[0.4304 - 0.6549]Specificity: 0.9895[0.9684 – 0.9966] | favor of TytoCare LungsSounds Analyzercompared to the clinicalreaders.Sensitivity and specificitywere evaluated as thesecondary endpoints.Estimate two-sided 95%CI):Sensitivity: 0.69 [0.57-0.78]Specificity:0.92 [0.88-0.95] | is non inferior to the predicatedevice.The overall diagnosticperformance show overall gooddiagnostic accuracy. | ||
| User interface forpoint of care andclinician apps | Web view | Web view | The user interface is not apart of eMurmur Heart AI(medical device); the userinterface is part of'eMurmur', a non-medicaldevice. | Same as the predicate device |
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Image /page/8/Picture/0 description: The image shows the logo for TytoCare. The logo features a cartoon ninja character on the left, followed by the text "tytocare" in a stylized font. The ninja character is blue and white, and the text is blue. There is a trademark symbol after the word "tytocare".
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Image /page/12/Picture/0 description: The image shows the logo for TytoCare. The logo features a cartoon ninja character on the left, followed by the text "tytocare" in a stylized font. The ninja character is blue and white, and the text is blue. There is a trademark symbol after the word "tytocare".
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The Tyto Insights for Wheeze Detection like its predicate device the TytoCare Lung Sounds Analyzer (K221614) have the same intended use, in that both are intended to identify recordings where a specific abnormal lung sound suggestive of "Wheeze" is suspected in the same intended patient population (adult and pediatric 2 years and older) by the same user [Health Care Professional (HCP)] when self-administered by patient and/or the HCPs. Both devices are only intended to be interpreted by HCP and HCP advice is required for the patient to understand their result. Both are labeled OTC.
Both the Tyto Insights for Wheeze Detection and its predicate device are stand-alone software systems that deliver the same intended benefit (identify recordings where a specific abnormal lung sound suggestive of "Wheeze" is suspected). For both devices the source of the Lung sounds recordings is the compatible FDA cleared Tyto Stethoscope (K181612).
Similarly, to the predicate device, the Tyto Insights for Wheeze Detection system is composed of three sub-systems: Application Server (APS), Algorithm Server (ALS) and Web Server (WBS). The APS communicates with the ALS and implements an application programming interface API for communication with the telehealth server. The ALS receives an audio file as input and returns an analysis result of positive or negative regarding whether a wheeze was detected as output. The ALS sub-system is composed of an Algorithm and logic wrapper and Interface components. The code of the logic wrapper and Interface component of the ALS component is the same as of the ALS component of the predicate device, the Algorithm's component is different. The Algorithm of the proposed device is Artificial Intelligence enabled while the Algorithm of the predicate device is rule based. The AI Algorithm was trained with recordings acquired by the real-world use of the compatible Tyto Stethoscope. The differences in the software algorithm modality do not raise new questions of safety and effectiveness. A reference device (K220766) was added to provide an example of FDA cleared device that uses as an input recordings recorded by means of compatible digital stethoscope and analyzed by AI enabled algorithm. The different algorithm modality between the proposed device and the predicate device does require that the accuracy of the device be substantiated with valid performance data using acceptable methods. Similar approach of performance evaluation was employed for the reference device as well. The WBS provides a graphic indication whether a wheeze is detected in the recording. It can be utilized both in the patient and clinician side. The minor wording differences in the user interface did not raise
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new questions of safety and effectiveness, the differences as compared to the predicate device did not introduce new critical tasks and didn't impact existing critical tasks.
Standards Conformance
- ANSI AAMI ISO 14971:2019, Medical devices Application of risk management to . medical devices
- . ANSI AAMI IEC 62304:2006/A1:2016, Medical device software - Software life cycle processes
- ISO 15223-1 Fourth edition 2021-07, Medical devices Symbols to be used with ● information to be supplied by the manufacturer - Part 1: General requirements.
- ANSI AAMI IEC 62366-1:2015+AMD1:2020 (Consolidated Text) Medical devices Part 1: Application of usability engineering to medical device.
Performance evaluation:
The Tyto Insights for Wheeze Detection was subject to performance evaluation following methodology similar to the ones used to test the predicate device. A testing plan was developed and performed to verify that the Tyto Insights for Wheeze Detection meets its specifications. The main aspects of the testing plan included:
- . SW verification and validation - The software including both custom developed software and OTS software, have been verified and validated and have been demonstrated to be safe and effective for its intended use. The software documentation level is basic per Content of Premarket Submissions for Device Software Functions, Guidance for Industry and Food and Drug Administration Staff, dated June 14, 2023. All required items related to software as required by FDA guidance for Basic Documentation Level have been included in this submission.
- Cybersecurity- all the applicable information to reflect effective cybersecurity o management and to address the FDA's recommendations described in Cybersecurity in Medical Devices: Refuse to Accept Policy for Cyber Devices and Related Systems Under Section 524B of the FD&C Act, issue date March 2023, Cybersecurity in Medical Devices: Quality System Considerations and Content of Premarket Submissions, issue date September 2023 and in the other FDA's applicable policies have been included in this submission.
- Performance evaluation - retrospective stand-alone performance evaluation of the "Tyto Insights for Wheeze Detection" device in detecting wheeze in the compatible Tyto Stethoscope lung recordings respective to ground truth and the predicate device.
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- Human factors validation the minor user interface modifications did not introduce new . critical tasks and didn't impact existing critical tasks. Therefore, no additional human factors validation was required and the human factors testing for the predicate device was applicable.
The performance of the Tyto Insights for Wheeze Detection device in detecting wheeze in recordings acquired by the compatible Tyto Stethoscope has been evaluated on a retrospective validation dataset of Tyto Stethoscope recordings sourced from real world use of the FDA cleared compatible Tyto Stethoscope. 371 recordings (359 patients) corresponded to the intended patient population of the Tyto Insights for Wheeze Detection Software recorded (86 recordings were Wheeze positive and 285 negative). The sample included recordings with known pre-existing conditions (COPD or Asthma) (7.28%). The demographics of the validation dataset are presented here under in Table 2:
| N=371patientsAge Group (Years) | |||
|---|---|---|---|
| Wheeze Positive | Wheeze Negative | Total | |
| 2-18 | 63 (24.2%) | 197 (75.8%) | 260 (70.08%) |
| >=18 | 23 (20.7%) | 88 (79.5%) | 111 (29.92%) |
| Gender | |||
| Positive | Negative | Total | |
| Male | 53 (27.3%) | 141 (72.7%) | 194 (52.29%) |
| Female | 33(18.6%) | 144 (81.4%) | 177 (47.71%) |
Table 2: Validation data-set demographics
To establish the ground truth, all of the recordings were read by three blinded experienced Pulmonologists at random, the binary ground truth was determined by majority vote of these three Pulmonologists.
For the characterization of the stand-alone accuracy, the automated binary result of the software has been compared to ground truth and specificity and sensitivity were calculated. This standalone accuracy is presented hereunder in Table 3:
| Parameter | Estimate (two-sided 95% CI) |
|---|---|
| Sensitivity (Se) | 0.54 (0.43-0.65) |
| Specificity (Sp) | 0.98 (0.97-0.99) |
| Positive Predictive Value (PPV) | 0.72 (0.48-0.89) |
| Negative Predictive Value (NPV) | 0.97 (0.97-0.98) |
Table 3: The stand-alone accuracy of the Tyto Insights for Wheeze Detection
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To establish standalone accuracy and demonstrate substantial equivalency with the predicate device, the primary end point was area under the Curve (AUC) for the detection of wheezes by the proposed device compared to the TytoCare Lung Sounds Analyzer (K221614) for patients aged 2 years and above. The independent algorithm result was compared to the result of the TytoCare Lung Sounds Analyzer (K221614) for the same recordings to establish the noninferiority of the automated algorithm respective to the predicate device. Success was defined as a lower bound of 95% two-sided CI for the difference in AUCs between the Tyto Insights for Wheeze Detection and the TytoCare Lung Sounds Analyzer (K221614) is higher than noninferiority margin of -0.05 for the recordings. Non-inferiority of Tyto Insights for Wheeze Detection compared to TytoCare Lung Sounds Analyzer (K221614) is demonstrated in Table 4:
| AUC | LCI | UCI | |
|---|---|---|---|
| TytoCare Lung Sounds Analyzer (K221614)[Analyzer] | 0.9085 | 0.8678 | 0.9372 |
| Tyto Insights for Wheeze Detection [Insights] | 0.9654 | 0.9459 | 0.9790 |
| Insights - Analyzer | 0.0570 | 0.0289 | 0.0917 |
Table 4: Primary Endpoint stand-alone assessment: Tyto Insights for Wheeze Detection compared to TytoCare Lung Sounds Analyzer (K221614)
AUC – Area Under the receiver operating characteristic Curve; LCI/UCI – lower/upper bound of two-sided 95% bootstrap (BCa) Confidence Interval
Non-inferiority of Tyto Insights for Wheeze Detection compared to TytoCare Lung Sounds Analyzer (K221614) for 2 years and above was established. Similar effect trend was also shown within the subgroup analysis, as evidence that the device accuracy is consistent with age groups and relevant pre-existing conditions.
Conclusion
The Tyto Insights for Wheeze Detection Software has the same intended use and indication for use as the predicate. The Tyto Insights for Wheeze Detection is only compatible with the FDA cleared TytoCare Stethoscope that provides the input stethoscope recordings. The minor differences in the user interface wording and software algorithm modality do not raise new questions of safety and effectiveness. Non-inferiority of Tyto Insights for Wheeze Detection compared to the predicate device for intended patient population was established. Thus, we conclude that the Tyto Insights for Wheeze Detection is as safe and effective as the predicate device.
§ 868.1900 Diagnostic pulmonary-function interpretation calculator.
(a)
Identification. A diagnostic pulmonary-function interpretation calculator is a device that interprets pulmonary study data to determine clinical significance of pulmonary-function values.(b)
Classification. Class II (performance standards).