Who is the manufacturer of See-Mode Augmented Reporting Tool, Thyroid (SMART-T)?

See-Mode Technologies Pte, Ltd. filed the 510(k) submission for See-Mode Augmented Reporting Tool, Thyroid (SMART-T) (K240697).

What is the FDA product code for See-Mode Augmented Reporting Tool, Thyroid (SMART-T)?

QDQ. It is classified under 21 CFR 892.2090 as a Class 2 device in the Radiology panel.

What is the regulatory pathway for See-Mode Augmented Reporting Tool, Thyroid (SMART-T)?

510(k) clearance (submission type: Traditional).

Does See-Mode Augmented Reporting Tool, Thyroid (SMART-T) use AI or machine learning?

Yes. See-Mode Augmented Reporting Tool, Thyroid (SMART-T) (K240697) is flagged as an AI/ML-enabled medical device in the FDA's AI/ML device list.

Who can help prepare an FDA 510(k) submission like See-Mode Augmented Reporting Tool, Thyroid (SMART-T)?

Innolitics — a medical-device software consultancy — provides regulatory and engineering support for FDA 510(k) submissions. See https://innolitics.com/services/510ks/ or contact https://innolitics.com/contact.

Can an AI/ML device like See-Mode Augmented Reporting Tool, Thyroid (SMART-T) get a guaranteed FDA 510(k) clearance?

Yes. Innolitics offers a guaranteed FDA 510(k) clearance engagement for AI/ML Software as a Medical Device — combining engineering and regulatory execution under one agreement with a guaranteed clearance outcome. Eligibility: the device must be an AI/ML Software as a Medical Device (SaMD), and its performance must meet the criteria Innolitics determines during an initial regulatory strategy engagement to be necessary for FDA clearance. See https://innolitics.com/services/end-to-end-samd/ or contact https://innolitics.com/contact.

See-Mode Augmented Reporting Tool, Thyroid (SMART-T)

K240697 · See-Mode Technologies Pte, Ltd. · QDQ · Sep 9, 2024 · Radiology

Device Facts

Record ID	K240697
Device Name	See-Mode Augmented Reporting Tool, Thyroid (SMART-T)
Applicant	See-Mode Technologies Pte, Ltd.
Product Code	QDQ · Radiology
Decision Date	Sep 9, 2024
Decision	SESE
Submission Type	Traditional
Regulation	21 CFR 892.2090
Device Class	Class 2
Attributes	AI/ML, Software as a Medical Device

Intended Use

Localization and characterization of thyroid ultrasound images.

Device Story

SMART-T is a web-based, stand-alone software for thyroid ultrasound analysis. It ingests DICOM-compliant ultrasound images and uses machine learning to automatically localize thyroid nodules and generate ACR TI-RADS lexicon descriptors (composition, echogenicity, shape, margin, echogenic foci) and TI-RADS category. The software provides a structured report for clinician review, quality control, and finalization. Used in clinical settings by physicians and technicians to assist in nodule identification and characterization. The device output serves as an adjunct to clinical judgment; clinicians may modify findings before report finalization. Benefits include improved diagnostic accuracy, reduced inter-reader variability, and standardized reporting aligned with ACR guidelines.

Clinical Evidence

Clinical validation included a Multi-reader Multi-case (MRMC) study with 18 board-certified radiologists evaluating 600 cases. Primary endpoints included localization accuracy, TI-RADS lexicon descriptor agreement, and TI-RADS level agreement. Results showed significant improvement in aided vs. unaided performance: localization accuracy (95.6% vs 93.6%), and improved agreement across all TI-RADS descriptors and levels (TR-1 to TR-5). Standalone performance was also evaluated against ground truth (consensus of two expert radiologists and an adjudicator).

Technological Characteristics

Web-based, client-server software. Inputs: DICOM ultrasound images. Processing: Machine learning algorithms for nodule localization and ACR TI-RADS classification. Output: Bounding box ROIs, lexicon descriptors, and structured reports. Standards: IEC 62304:2006/AC:2015, ISO 14971:2019. Runs on off-the-shelf hardware.

Indications for Use

Indicated for adult patients (>=22 years old) referred for thyroid ultrasound examination. Assists trained medical professionals in analyzing thyroid ultrasound images by localizing nodules, providing ACR TI-RADS lexicon-based descriptors, and generating structured reports for clinician review and approval. Not for independent medical advice or treatment recommendations.

Regulatory Classification

Identification

A radiological computer-assisted detection and diagnostic software is an image processing device intended to aid in the detection, localization, and characterization of fracture, lesions, or other disease-specific findings on acquired medical images (e.g., radiography, magnetic resonance, computed tomography). The device detects, identifies, and characterizes findings based on features or information extracted from images, and provides information about the presence, location, and characteristics of the findings to the user. The analysis is intended to inform the primary diagnostic and patient management decisions that are made by the clinical user. The device is not intended as a replacement for a complete clinician's review or their clinical judgment that takes into account other relevant information from the image or patient history.

Special Controls

A radiological computer assisted detection and diagnosis software must comply with the following special controls: Design verification and validation must include: 1. i. A detailed description of the image analysis algorithm, including but not limited to a description of the algorithm inputs and outputs, each major component or block, how the algorithm and output affects or relates to clinical practice or patient care, and any algorithm limitations. ii. A detailed description of pre-specified performance testing protocols and dataset(s) used to assess whether the device will provide improved assisted-read detection and diagnostic performance as intended in the indicated user population(s), and to characterize the standalone device performance for labeling. Performance testing includes standalone test(s), side-by-side comparison(s), and/or a reader study, as applicable. iii. Results from standalone performance testing used to characterize the independent performance of the device separate from aided user performance. The performance assessment must be based on appropriate diagnostic accuracy measures (e.g., receiver operator characteristic plot, sensitivity, specificity, positive and negative predictive values, and diagnostic likelihood ratio). Devices with localization output must include localization accuracy testing as a component of standalone testing. The test dataset must be representative of the typical patient population with enrichment made only to ensure that the test dataset contain a sufficient number of cases from important cohorts (e.g., subsets defined by clinically relevant confounders, effect modifiers, concomitant disease, and subsets defined by image acquisition characteristics) such that the performance estimates and confidence intervals of the device for these individual subsets can be characterized for the intended use population and imaging equipment. iv. Results from performance testing that demonstrate that the device provides improved assisted-read detection and/or diagnostic performance as intended in the indicated user population(s) when used in accordance with the instructions for use. The reader population must be comprised of the intended user population in terms of but not limited to clinical training, certification, and years of experience. The performance assessment must be based on appropriate diagnostic accuracy measures (e.g., receiver operator characteristic plot, sensitivity, specificity, positive and negative predictive values, and diagnostic likelihood ratio). Test datasets must meet the requirements described in 1(iii) above. v. Appropriate software documentation, including device hazard analysis, software requirements specification document, software design specification document, traceability analysis, system level test protocol, pass/fail criteria, testing results, and cybersecurity measures. 2. Labeling must include the following: i. A detailed description of the patient population for which the device is indicated for use. ii. A detailed description of the device instructions for use, including the intended reading protocol and how the user should interpret the device output. iii. A detailed description of the intended user, and any user training materials as programs that addresses appropriate reading protocols for the device to ensure that the end user is fully aware of how to interpret and apply the device output. iv. A detailed description of the device inputs and outputs. v. A detailed description of compatible imaging hardware and imaging protocols. vi. Warnings, precautions, and limitations must include situations in which the device may fail or may not operate at its expected performance level (e.g., poor image quality or for certain subpopulations), as applicable. vii. A detailed summary of the performance testing, including: test methods, dataset characteristics, results, and a summary of sub-analyses on case distributions stratified by relevant confounders, such as anatomical characteristics, patient demographics and medical history, user experience, and imaging equipment.

*Classification.* Class II (special controls). The special controls for this device are:(1) Design verification and validation must include: (i) A detailed description of the image analysis algorithm, including a description of the algorithm inputs and outputs, each major component or block, how the algorithm and output affects or relates to clinical practice or patient care, and any algorithm limitations. (ii) A detailed description of pre-specified performance testing protocols and dataset(s) used to assess whether the device will provide improved assisted-read detection and diagnostic performance as intended in the indicated user population(s), and to characterize the standalone device performance for labeling. Performance testing includes standalone test(s), side-by-side comparison(s), and/or a reader study, as applicable. (iii) Results from standalone performance testing used to characterize the independent performance of the device separate from aided user performance. The performance assessment must be based on appropriate diagnostic accuracy measures ( *e.g.,* receiver operator characteristic plot, sensitivity, specificity, positive and negative predictive values, and diagnostic likelihood ratio). Devices with localization output must include localization accuracy testing as a component of standalone testing. The test dataset must be representative of the typical patient population with enrichment made only to ensure that the test dataset contains a sufficient number of cases from important cohorts (*e.g.,* subsets defined by clinically relevant confounders, effect modifiers, concomitant disease, and subsets defined by image acquisition characteristics) such that the performance estimates and confidence intervals of the device for these individual subsets can be characterized for the intended use population and imaging equipment.(iv) Results from performance testing that demonstrate that the device provides improved assisted-read detection and/or diagnostic performance as intended in the indicated user population(s) when used in accordance with the instructions for use. The reader population must be comprised of the intended user population in terms of clinical training, certification, and years of experience. The performance assessment must be based on appropriate diagnostic accuracy measures ( *e.g.,* receiver operator characteristic plot, sensitivity, specificity, positive and negative predictive values, and diagnostic likelihood ratio). Test datasets must meet the requirements described in paragraph (b)(1)(iii) of this section.(v) Appropriate software documentation, including device hazard analysis, software requirements specification document, software design specification document, traceability analysis, system level test protocol, pass/fail criteria, testing results, and cybersecurity measures. (2) Labeling must include the following: (i) A detailed description of the patient population for which the device is indicated for use. (ii) A detailed description of the device instructions for use, including the intended reading protocol and how the user should interpret the device output. (iii) A detailed description of the intended user, and any user training materials or programs that address appropriate reading protocols for the device, to ensure that the end user is fully aware of how to interpret and apply the device output. (iv) A detailed description of the device inputs and outputs. (v) A detailed description of compatible imaging hardware and imaging protocols. (vi) Warnings, precautions, and limitations must include situations in which the device may fail or may not operate at its expected performance level ( *e.g.,* poor image quality or for certain subpopulations), as applicable.(vii) A detailed summary of the performance testing, including test methods, dataset characteristics, results, and a summary of sub-analyses on case distributions stratified by relevant confounders, such as anatomical characteristics, patient demographics and medical history, user experience, and imaging equipment.

Predicate Devices

BU-CAD (K210670)

Reference Devices

Koios DS (K212616)

Related Devices

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K122536 — AMCAD-UT DETECTION MODEL 2.0 · Lin & Associates, LLC · Oct 3, 2013
K242130 — Koios DS · Koios Medical, Inc. · Nov 15, 2024
K212616 — Koios DS · Koios Medical, Inc. · Dec 16, 2021

Submission Summary (Full Text)

{0}------------------------------------------------ Image /page/0/Picture/0 description: The image shows the logo of the U.S. Food and Drug Administration (FDA). The logo consists of two parts: the Department of Health & Human Services logo on the left and the FDA logo on the right. The FDA logo is a blue square with the letters "FDA" in white, followed by the words "U.S. Food & Drug Administration" in blue. See-Mode Technologies Pte. Ltd. % Sadaf Monajemi Co-founder and Director 32 Carpenter Street. #03-01 Singapore, 059911 Singapore September 9, 2024 Re: K240697 Trade/Device Name: See-Mode Augmented Reporting Tool, Thyroid (SMART-T) Regulation Number: 21 CFR 892.2090 Regulation Name: Radiological Computer Assisted Detection And Diagnosis Software Regulatory Class: Class II Product Code: QDQ, QIH Dated: August 2, 2024 Received: August 2, 2024 Dear Sadaf Monajemi: 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. {1}------------------------------------------------ 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" (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 QS 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. All medical devices, including Class I and unclassified devices and combination product device constituent parts are required to be in compliance with the final Unique Device Identification System rule ("UDI Rule"). The UDI Rule requires, among other things, that a device bear a unique device identifier (UDI) on its label and package (21 CFR 801.20(a)) unless an exception or alternative applies (21 CFR 801.20(b)) and that the dates on the device label be formatted in accordance with 21 CFR 801.18. The UDI Rule (21 CFR 830.300(a) and 830.320(b)) also requires that certain information be submitted to the Global Unique Device Identification Database (GUDID) (21 CFR Part 830 Subpart E). For additional information on these requirements, please see the UDI System webpage at https://www.fda.gov/medical-device-advicecomprehensive-regulatory-assistance/unique-device-identification-system-udi-system. 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 medical devices and radiation-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-regulatory {2}------------------------------------------------ assistance/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, Jessica Lamb Jessica Lamb, Ph.D. Assistant Director Imaging Software Team DHT 8B: Division of Radiological Imaging Devices and Electronic Products OHT 8: Office of Radiological Health Office of Product Evaluation and Quality Center for Devices and Radiological Health Enclosure {3}------------------------------------------------ # Indications for Use Submission Number (if known) K240697 Device Name See-Mode Augmented Reporting Tool, Thyroid (SMART-T) ### Indications for Use (Describe) See-Mode Augmented Reporting Tool, Thyroid (SMART-T) is a stand-alone reporting software to assist trained medical professionals in analyzing thyroid ultrasound images of adult (>=22 years old) patients who have been referred for an ultrasound examination. Output of the device includes regions of interest (ROIs) placed on the thyroid ultrasound images assisting healthcare professionals to localize nodules in thyroid studies. The device also outputs ultrasonographic lexicon-based descriptors based on ACR TI-RADS. The software generates a report based on the image analysis results to be reviewed and approved by a qualified clinician after performing quality control. SMART-T may also be used as a structured reporting software for further ultrasound studies. The software includes tools for reading measurements and annotations from the images that can be used for generating a structured report. Patient management decisions should not be made solely on the basis of analysis by See-Mode Augmented Reporting Tool, Thyroid. Type of Use (Select one or both, as applicable) > Prescription Use (Part 21 CFR 801 Subpart D) Over-The-Counter Use (21 CFR 801 Subpart C) ### CONTINUE ON A SEPARATE PAGE IF NEEDED. This section applies only to requirements of the Paperwork Reduction Act of 1995. ### *DO NOT SEND YOUR COMPLETED FORM TO THE PRA STAFF EMAIL ADDRESS BELOW.* The burden time for this collection of information is estimated to average 79 hours per response, including the time to review instructions, search existing data sources, gather and maintain the data needed and complete and review the collection of information. Send comments regarding this burden estimate or any other aspect of this information collection, including suggestions for reducing this burden, to: > Department of Health and Human Services Food and Drug Administration Office of Chief Information Officer Paperwork Reduction Act (PRA) Staff PRAStaff(@fda.hhs.gov "An agency may not conduct or sponsor, and a person is not required to respond to, a collection of information unless it displays a currently valid OMB number." {4}------------------------------------------------ Image /page/4/Picture/1 description: The image shows the logo for See-Mode. The logo consists of a stylized, teal-colored graphic above the text "See-Mode". The graphic appears to be two overlapping wave-like shapes, possibly representing a signal or data visualization. The text "See-Mode" is in a simple, sans-serif font. K240697 This "510(k) Summary" was prepared per section 807.92(c). #### ADMINISTRATIVE INFORMATION 1. | Date of Preparation: | September 5, 2024 | |----------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| | Prepared by: | Sadaf Monajemi, PhD. Co-founder and Director | | Manufacturer: | See-Mode Technologies Pte. Ltd. 32 Carpenter Street #03-01 Singapore 059911 SINGAPORE Email: sadaf@see-mode.com Tel: +61 415 952 782 www.see-mode.com | | Official Contact: | Dr. Sadaf Monajemi, PhD, Co-founder and Director See-Mode Technologies 32 Carpenter Street #03-01 Singapore 059911 SINGAPORE Email: sadaf@see-mode.com www.see-mode.com | #### 2. DEVICE NAME AND CLASSIFICATION Trade/Proprietary Name: See-Mode Augmented Reporting Tool, Thyroid (SMART-T) Regulation Number: 21 CFR 892.2090 Regulation Name: Radiological computer-assisted detection and diagnosis software Classification Name: System, Image Processing, Radiological Review Panel: Radiology Regulatory Class: Class II Product Code: QDQ/QIH #### 3. INTENDED USE Localization and characterization of thyroid ultrasound images. {5}------------------------------------------------ Image /page/5/Picture/1 description: The image shows the logo for See-Mode. The logo consists of a stylized wave-like graphic above the text "See-Mode." Both the graphic and the text are in a teal color. The wave graphic appears to be two overlapping sine waves. #### 4. INDICATIONS FOR USE See-Mode Augmented Reporting Tool, Thyroid (SMART-T) is a stand-alone reporting software to assist trained medical professionals in analyzing thyroid ultrasound images of adult (>=22 years old) patients who have been referred for an ultrasound examination. Output of the device includes regions of interest (ROIs) placed on the thyroid ultrasound images assisting healthcare professionals to localize nodules in thyroid studies. The device also outputs ultrasonographic lexicon-based descriptors based on ACR TI-RADS. The software generates a report based on the image analysis results to be reviewed and approved by a qualified clinician after performing quality control. SMART-T may also be used as a structured reporting software for further ultrasound studies. The software includes tools for reading measurements and annotations from the images that can be used for generating a structured report. Patient management decisions should not be made solely on the basis of analysis by See-Mode Augmented Reporting Tool, Thyroid. #### DEVICE DESCRIPTION 5. See-Mode Augmented Reporting Tool, Thyroid (SMART-T) is a stand-alone, web-based image processing and reporting software for localization, characterization and reporting of thyroid ultrasound images. The software analyzes thyroid ultrasound images and uses machine learning algorithms to extract specific information. The algorithms can identify and localize suspicious soft tissue nodules and also generate lexicon-based descriptors, which are classified according to ACR TI-RADS (composition, echogenicity, shape, margin, and echogenic foci) with a calculated TI-RADS level according to the ACR TI-RADS chart. SMART-T may also be used as a structured reporting software for further ultrasound studies. The software includes tools for reading measurements and annotations from the images that can be used for generating a structured report. The software then generates a report based on the image analysis results to be reviewed and approved by a qualified clinician after performing quality control. Any information within this report can be changed and modified by the clinician if needed during quality control and before finalizing the report. The software runs on a standard "off-the-shelf" computer and can be accessed within the client web browser to perform the reporting of ultrasound images. Input data and images for the software are acquired through DICOM-compliant ultrasound imaging devices. {6}------------------------------------------------ Image /page/6/Picture/1 description: The image shows the logo for See-Mode. The logo consists of a stylized wave-like graphic above the text "See-Mode". The graphic is a teal color and appears to be two overlapping sine waves. The text "See-Mode" is also teal and in a sans-serif font. The data produced by the software is intended to be used by trained medical professionals, including but not limited to physicians and medical technicians. The software is not intended to be used as an independent source of medical advice or to determine or recommend a course of action or treatment for patients. #### 6. SUBSTANTIAL EQUIVALENCE #### 6.1. Predicate Device Manufacturer: TaiHao Medical Inc. Trade Name: BU-CAD 510(k) Identifier: K210670 Regulation Number: 21 CFR 892.2090 Regulation Name: Radiological Computer Assisted Detection/Diagnosis Software For Lesions Suspicious For Cancer Classification Name: Radiological Computer Assisted Detection/Diagnosis Software For Lesions Suspicious For Cancer Classification Panel: Radiology Regulatory Class: Class II Product Code: QDQ, LLZ Date Cleared: December 21, 2021 #### 6.2. Tabular Comparison of Features and Specifications of the Subject Device, Predicate Device, and Reference Device | | Subject Device See-Mode Augmented Reporting Tool, Thyroid (SMART-T) (K240697) | Predicate Device BU-CAD (K210670) | Reference Device Koios DS (K212616) | |------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| | | Administrative information | | | | Regulation | 21 CFR 892.2090 | 21 CFR 892.2090 | 21 CFR 892.2060 | | | Radiological computer-assisted detection and diagnosis software for lesions suspicious for cancer | Radiological computer-assisted detection and diagnosis software for lesions suspicious for cancer | Radiological computer-assisted diagnostic software for lesions suspicious of cancer | | Regulatory Class | Class II | Class II | Class II | | Subject Device | Predicate Device | Reference Device | | | See-Mode Augmented Reporting Tool, Thyroid (SMART-T) (K240697) | BU-CAD (K210670) | Koios DS (K212616) | | | Product Code | QDQ, QIH | QDQ, LLZ | POK, QIH | | 510(k) Number | K240697 | K210670 | K212616 | | Intended Use | | | | | Indications for Use | See-Mode Augmented Reporting Tool, Thyroid (SMART-T) is a stand-alone reporting software to assist trained medical professionals in analyzing thyroid ultrasound images of adult (>=22 years old) patients who have been referred for an ultrasound examination. Output of the device includes regions of interest (ROIs) placed on the thyroid ultrasound images assisting healthcare professionals to localize nodules in thyroid studies. The device also outputs ultrasonographic lexicon-based descriptors based on ACR TI-RADS. The software generates a report based on the image analysis results to be reviewed and approved by a qualified clinician after performing quality control. SMART-T may also be used as a structured reporting software for further ultrasound studies. The | BU-CAD is a software application indicated to assist trained interpreting physicians in analyzing the breast ultrasound images of patients with soft tissue breast lesions suspicious for breast cancer who are being referred for further diagnostic ultrasound examination. Output of the device includes regions of interest (ROIs) and lesion contours placed on breast ultrasound images assisting physicians to identify suspicious soft tissue lesions from up to two orthogonal views of a single lesion, and region-based analysis of lesion malignancy upon the physician's query. The region-based analysis indicates the score of lesion characteristics (SLC), and corresponding BI-RADS categories in user-selected ROIs or ROIs automatically identified by the software. In addition, BU-CAD also automatically classifies lesion shape, orientation, margin, echo pattern, and posterior | Koios DS is an artificial intelligence (AI)/machine learning (ML)-based computer-aided diagnosis (CADx) software device intended for use as an adjunct to diagnostic ultrasound examinations of lesions or nodules suspicious for breast or thyroid cancer. Koios DS allows the user to select or confirm regions of interest (ROIs) within an image representing a single lesion or nodule to be analyzed. The software then automatically characterizes the selected image data to generate an AI/ML-derived cancer risk assessment and selects applicable lexicon-based descriptors designed to improve overall diagnostic accuracy as well as reduce interpreting physician variability. Koios DS may also be used as an image viewer of multi-modality digital images, including ultrasound | | Subject Device See-Mode Augmented Reporting Tool, Thyroid (SMART-T) (K240697) | Predicate Device BU-CAD (K210670) | Reference Device Koios DS (K212616) | | | annotations from the images that can be used for generating a structured report. Patient management decisions should not be made solely on the basis of analysis by See-Mode Augmented Reporting Tool, Thyroid. | BU-CAD may also be used as an image viewer of multi-modality digital images, including ultrasound and mammography. The software includes tools that allow users to adjust, measure and document images, and output into a structured report (SR). Patient management decisions should not be made solely on the basis of analysis by BU-CAD. | allow users to adjust, measure and document images, and output into a structured report. Koios DS software is designed to assist trained interpreting physicians in analyzing the breast ultrasound images of adult (>= 22 years) female patients with soft tissue breast lesions and/or thyroid ultrasounds of all adult (>= 22 years) patients with thyroid nodules suspicious for cancer. When utilized by an interpreting physician who has completed the prescribed training, this device provides information that may be useful in recommending appropriate clinical management. | | | Intended Population | Patients with thyroid nodules who are being referred for ultrasound scan (Prescription only) | Patients with soft tissue breast lesions who are being referred for ultrasound interpreting (Prescription only) | Patients with thyroid nodules suspicious for cancer (Prescription only) | | Image Source | Ultrasound images | Ultrasound images | Ultrasound images | | Rx only? | Yes | Yes | Yes | | | Subject Device | Predicate Device | Reference Device | | | See-Mode Augmented Reporting Tool, Thyroid (SMART-T) (K240697) | BU-CAD (K210670) | Koios DS (K212616) | | Application Description | The subject device is a stand-alone, web-based image processing and reporting software for localization, characterization and reporting of thyroid ultrasound images. The software analyzes thyroid ultrasound images and uses machine learning algorithms to extract specific information. The algorithms can identify and localize suspicious soft tissue nodules and also generate lexicon-based descriptors, which are classified according to ACR TI-RADS (composition, echogenicity, shape, margin, and echogenic foci) with a calculated TI-RADS category according to the ACR TI-RADS chart. The software then generates a report based on the image analysis results to be reviewed and approved by a qualified clinician after performing quality control. Any information within this report can be changed and modified by the clinician if needed during quality control and before finalizing the report. | BU-CAD is a software system designed to assist users in analyzing breast ultrasound images including identification of regions suspicious for breast cancer and assessment of their malignancy. BU-CAD consists of a viewer, a lesion identification module, and a lesion analysis module. The lesion identification module identifies regions of interest (automated ROIs) of a single suspicious soft tissue lesion in up to two orthogonal views of breast ultrasound images for assisting users in detecting soft tissue lesions. Additionally, the lesion identification module generates an ROI and a lesion contour on each breast ultrasound image. The lesion analysis module analyzes given ROIs of a breast lesion on ultrasound images, and generates a score of lesion characteristics (SLC) in terms of malignancy or benignity of a lesion, BI-RADS category, and BI-RADS descriptors. | Koios DS is a computer-aided diagnosis (CADx) software device intended for use as an adjunct to diagnostic ultrasound examinations of lesions or nodules suspicious for breast or thyroid cancer. Koios DS allows the user to select or confirm regions of interest (ROIs) within an image representing a single lesion or nodule to be analyzed. Koios DS software contains functionality for automatically classifying thyroid nodules suspicious for cancer. The system generates an output aligned to either the TI-RADS or ATA classification guidelines. The system automatically generates user-modifiable thyroid nodule descriptors (Composition, Echogenicity, Shape, Margin, Echogenic Foci) and a direct, image-derived cancer risk assessment that is translated into an optional lexicon-specific (TI-RADS or ATA) modifier. | | Anatomical Location | Thyroid | Breast…