Who is the manufacturer of ADAS 3D?

Adas3D Medical S.L. filed the 510(k) submission for ADAS 3D (K240791).

What is the FDA product code for ADAS 3D?

QIH. It is classified under 21 CFR 892.2050 as a Class 2 device in the Radiology panel.

What is the regulatory pathway for ADAS 3D?

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

Does ADAS 3D use AI or machine learning?

Yes. ADAS 3D (K240791) 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 ADAS 3D?

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 ADAS 3D 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.

ADAS 3D

K240791 · Adas3D Medical S.L. · QIH · Sep 9, 2024 · Radiology

Device Facts

Record ID	K240791
Device Name	ADAS 3D
Applicant	Adas3D Medical S.L.
Product Code	QIH · Radiology
Decision Date	Sep 9, 2024
Decision	SESE
Submission Type	Traditional
Regulation	21 CFR 892.2050
Device Class	Class 2
Attributes	AI/ML, Software as a Medical Device

Intended Use

ADAS 3D is indicated for use in clinical settings to support the visualization and analysis of MR and CT images of the heart for use on individual patients with cardiovascular disease. ADAS 3D is indicated for patients with myocardial scar produced by ischemic or non-ischemic heart disease. ADAS 3D processes MR and CT images. The quality and the resolution of the medical images determines the accuracy of the data produced by ADAS 3D. ADAS 3D is indicated to be used only by qualified medical professionals (cardiologists, electrophysiologists, radiologists or trained technicians) for the calculation, guantification and visualization of cardiac images and intended to be used for pre-planning and during electrophysiology procedures. The data produced by ADAS 3D must not be used as an irrefutable basis or a source of medical advice for clinical diagnosis or patient treatment. The data produced by ADAS 3D is intended to be used to support qualified medical professionals for clinical decision making. The clinical significance of using ADAS 3D to identify arrhythmia substrates for the treatment of cardiac arrhythmias (e.g., ventricular tachycardia) or risk stratification has not been established.

Device Story

ADAS 3D is a stand-alone software tool for post-processing cardiovascular MR and CTA DICOM images; used in clinical settings by cardiologists, electrophysiologists, radiologists, or technicians. Input: MR/CTA images. Processing: Machine-learning-based algorithms perform semi-automatic initialization and segmentation of cardiac structures (LV, LA, Aorta, Coronary Arteries). Output: 3D visualizations, quantification of myocardial fibrosis, wall thickness, and anatomical distances; data exported to industry-standard formats for catheter navigation systems. Clinical use: Supports diagnostic decision-making and pre-planning for electrophysiology procedures. Benefit: Provides non-invasive cardiac analysis to assist clinicians in understanding cardiovascular disease.

Clinical Evidence

Bench testing only. Performance of machine learning features evaluated using a multi-site, multi-scanner DICOM dataset (n=100 per feature). Metrics included Dice Coefficient (DC), Mean Surface Distance (MSD), Hausdorff Distance (HD), and Mean Difference in Shifts (MDS). Results showed high performance (e.g., DC 0.82–0.94) consistent with state-of-the-art benchmarks. Four minor sub-pixel discrepancies were noted and deemed clinically acceptable. Subgroup analysis confirmed performance consistency across US and OUS datasets.

Technological Characteristics

Stand-alone software; DICOM-compliant. Machine learning-based segmentation/initialization. Supported OS: Linux RHEL 8, Windows 10, Windows 11. Connectivity: Exports to industry-standard file formats for catheter navigation systems. No hardware components.

Indications for Use

Indicated for patients with myocardial scar from ischemic or non-ischemic heart disease. Used by cardiologists, electrophysiologists, radiologists, or trained technicians for cardiac image visualization, calculation, and quantification to support pre-planning and electrophysiology procedures.

Regulatory Classification

Identification

A medical image management and processing system is a device that provides one or more capabilities relating to the review and digital processing of medical images for the purposes of interpretation by a trained practitioner of disease detection, diagnosis, or patient management. The software components may provide advanced or complex image processing functions for image manipulation, enhancement, or quantification that are intended for use in the interpretation and analysis of medical images. Advanced image manipulation functions may include image segmentation, multimodality image registration, or 3D visualization. Complex quantitative functions may include semi-automated measurements or time-series measurements.

Special Controls

*Classification.* Class II (special controls; voluntary standards—Digital Imaging and Communications in Medicine (DICOM) Std., Joint Photographic Experts Group (JPEG) Std., Society of Motion Picture and Television Engineers (SMPTE) Test Pattern).

Predicate Devices

ADAS 3D (K230803)

Reference Devices

Valles-Colomer, A., et al. Reproducibility analysis of the computerized tomography angiography-derived left atrial wall thickness maps. J Interv Card Electrophysiol 66, 1045–1055 (2023)

Related Devices

K212421 — ADAS 3D · Adas3D Medical S.L. · Sep 3, 2021
K230803 — ADAS 3D · Adas3D Medical S.L. · May 23, 2023
K191125 — ADAS 3D · Galgo Medical S.L · Jan 15, 2020
K210850 — ADAS 3D · Adas3D Medical S.L. · Apr 5, 2021
K242781 — cvi42 Software Application · Circle Cardiovascular Imaging, Inc. · Oct 15, 2024

Submission Summary (Full Text)

{0}------------------------------------------------ September 9, 2024 Image /page/0/Picture/1 description: The image shows the logo for the U.S. Food and Drug Administration (FDA). The logo consists of two parts: on the left, there is an emblem representing the Department of Health & Human Services - USA, and on the right, there is the text "FDA U.S. FOOD & DRUG ADMINISTRATION" in blue. The word "FDA" is in a larger, bolder font, and the words "U.S. FOOD & DRUG" are stacked above the word "ADMINISTRATION". Adas3D Medical S.L Antoni Riu General Manager Rambla Catalunya 53, 4H BARCELONA, 08007 SPAIN Re: K240791 Trade/Device Name: Adas 3D Regulation Number: 21 CFR 892.2050 Regulation Name: Medical Image Management And Processing System Regulatory Class: Class II Product Code: QIH, LLZ Dated: August 9, 2024 Received: August 9, 2024 Dear Antoni Riu: 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 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-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, Samal for Jessica Lamb, Ph.D. Assistant Director Imaging Software Team DHT8B: Division of Radiological Imaging Devices and Electronic Products OHT8: 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) K240791 Device Name ADAS 3D Indications for Use (Describe) ADAS 3D is indicated for use in clinical settings to support the visualization and analysis of MR and CT images of the heart for use on individual patients with cardiovascular disease. ADAS 3D is indicated for patients with myocardial scar produced by ischemic or non-ischemic heart disease. ADAS 3D processes MR and CT images. The quality and the resolution of the medical images determines the accuracy of the data produced by ADAS 3D. ADAS 3D is indicated to be used only by qualified medical professionals (cardiologists, electrophysiologists, radiologists or trained technicians) for the calculation, guantification and visualization of cardiac images and intended to be used for pre-planning and during electrophysiology procedures. The data produced by ADAS 3D must not be used as an irrefutable basis or a source of medical advice for clinical diagnosis or patient treatment. The data produced by ADAS 3D is intended to be used to support qualified medical professionals for clinical decision making. The clinical significance of using ADAS 3D to identify arrhythmia substrates for the treatment of cardiac arrhythmias (e.g., ventricular tachycardia) or risk stratification has not been established. 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/0 description: The image shows the logo for Adas3D Medical. The logo features a stylized red heart with a blue swoosh across it, positioned above the text "Adas3D Medical". The text is in a simple, sans-serif font, with "Adas3D" on the first line and "Medical" on the second line. The heart graphic is slightly offset to the right of the text. ## General Information 1 This 510(k) Summary is being submitted in accordance with the requirements detailed in 21 CFR 807.92. | DATE: | September 9, 2024 | |-------------------------|------------------------------------------------------------------------------------------| | SUBMITTER: | Adas3D Medical S.L. Rambla Catalunya 53, 4-H 08036 Barcelona Barcelona Spain | | CONTACT: | Antoni Riu +34 93 328 3964 antoni.riu@adas3d.com | | DEVICE TRADE NAME: | ADAS 3D | | COMMON NAME: | Radiological Image Processing System | | CLASSIFICATION NAME: | Radiological Image Processing System (21 CFR 892.2050) | | PRODUCT CODE: | Primary product code: QIH Secondary product code: LLZ | | REGULATION DESCRIPTION: | Picture archiving and communications system | | PREDICATE DEVICE: | ADAS 3D (K230803) | {5}------------------------------------------------ Image /page/5/Picture/0 description: The image shows the logo for Adas3D Medical. The logo features a stylized red heart with a blue arc over it, set against a background of small gray squares. Below the heart graphic, the text "Adas3D Medical" is written in a simple, sans-serif font, with "Adas3D" on the top line and "Medical" on the bottom line. ### Device Description ম ADAS 3D is a stand-alone software tool intended to be used for post-processing cardiovascular enhanced Magnetic Resonance (MR) images and Computed Tomography Angiography (CTA) images that are formatted in the Digital Imaging and Communication in Medicine (DICOM) standard. ADAS 3D software aids in the non-invasive calculation, quantification of cardiac imaging data to support a comprehensive diagnostic decision-making process for understanding cardiovascular disease. ADAS 3D exports information to multiple industry standard file formats suitable for documentation and information sharing purposes. The 3D data is exported into industry standard file formats supported by catheter navigation systems. ADAS 3D analyses the enhancement of myocardial fibrosis from DICOM MR images to support: - Visualization of the distribution of the enhancement in a three-dimensional (3D) chamber of the heart. - Quantification of the total volume of the enhancement within the Left Ventricle (LV) and the visualization of the enhancement area in multiple layers through the cardiac structure. - . Calculation, quantification and visualization of corridors of intermediate, signal intensity enhancement in the LV. - Quantification and visualization of the total area and distribution of the enhancement within the left Atrium (LA). Additionally, ADAS 3D imports DICOM CTA images to support: - Quantification of LV wall thickness. - Identification and Visualization of other 3D anatomical structures. - Quantification and visualization of LA wall thickness. - Quantification and visualization of distances from the LA epicardium to other 3D anatomical structures. Additionally, ADAS 3D imports DICOM Magnetic Resonance Angiography (MRA) images to support: - Identification and Visualization of other 3D anatomical structures. Additionally, ADAS 3D uses the following machine-learning-based features: - Standard Initialization of the LV, LA, and Aorta from CTA - Standard Initialization of the Coronary Arteries from CTA - Standard Initialization of the LA from CTA - Standard Initialization of the LV from 2D LGE-MRI and Automatic Slice Alignment ● - Standard Initialization of the LV from 3D LGE-MRI - Standard Initialization of the LA from 3D LGE-MRI {6}------------------------------------------------ Image /page/6/Picture/0 description: The image contains the logo for Adas3D Medical. The logo features a stylized red heart with a blue swoosh across it, positioned above the text "Adas3D Medical." The text is in a simple, sans-serif font, with "Adas3D" on the top line and "Medical" on the bottom line. The background is plain white. It is intended to be used by qualified medical professionals (cardiologists or trained technicians) experienced in examining and evaluating cardiovascular MR and CTA images as part of the comprehensive diagnostic decision-making process. #### ന Indications for Use ADAS 3D is indicated for use in clinical settings to support the visualization and analysis of MR and CT images of the heart for use on individual patients with cardiovascular disease. ADAS 3D is indicated for patients with myocardial scar produced by ischemic heart disease. ADAS 3D processes MR and CT images. The quality and the resolution of the medical images determines the accuracy of the data produced by ADAS 3D. ADAS 3D is indicated to be used only by qualified medical professionals (cardiologists, radiologists or trained technicians) for the calculation, quantification of cardiac images and intended to be used for pre-planning and during electrophysiology procedures. The data produced by ADAS 3D must not be used as an irrefutable basis or a source of medical advice for clinical diagnosis or patient treatment. The data produced by ADAS 3D is intended to be used to support qualified medical professionals for clinical decision making. The clinical significance of using ADAS 3D to identify arrhythmia substrates for the treatment of cardiac arrhythmias (e.g., ventricular tachycardia) or risk stratification has not been established. {7}------------------------------------------------ Image /page/7/Picture/0 description: The image shows the logo for Adas3D Medical. The logo features a stylized red heart with a blue arc passing over it, set against a background of small gray squares. Below the heart graphic, the text "Adas3D Medical" is written in a simple, sans-serif font, with "Adas3D" on the first line and "Medical" on the second. #### 4 Comparison with Predicate Device Adas3D Medical SL is modifying its own device [ADAS 3D; K230803] under this traditional 510(k). The purpose of this submission is to make three (3) modifications to the device. The following two tables compare the Indications for Use, Device Description (including functional and technological characteristics) and the new modifications of the subject device to the predicate device. | Elements of Comparison | Subject Device ADAS 3D (Adas3D Medical S.L.) | Predicate Device ADAS 3D (K230803) | |--------------------------------------------------------------------------------------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| | Regulatory data | | | | Regulatory Class | Class II | Class II | | Classification name | Radiological Image processing system | Radiological Image processing system | | Regulation Number | 21 CFR 892.2050 | 21 CFR 892.2050 | | Product Code | QIH, LLZ | LLZ | | 510(k) Number | K240791 | K230803 | | Use | | | | Indications for Use | ADAS 3D is indicated for use in clinical settings to support the visualization and analysis of MR and CT images of the heart for use on individual patients with cardiovascular disease. ADAS 3D is indicated for patients with myocardial scar produced by ischemic or non- ischemic heart disease. ADAS 3D processes MR and CT images. The quality and the resolution of the medical images determines the accuracy of the data produced by ADAS 3D. ADAS 3D is indicated to be used only by qualified medical professionals (cardiologists, electrophysiologists, radiologists or trained technicians) for the calculation, quantification and visualization of cardiac images and intended to be used for pre-planning and during electrophysiology procedures. The data | Same | | Elements of Comparison | Subject Device | Predicate Device | | | ADAS 3D (Adas3D Medical S.L.) | ADAS 3D (K230803) | | | produced by ADAS 3D must not be used as an irrefutable basis or a source of medical advice for clinical diagnosis or patient treatment. The data produced by ADAS 3D is intended to be used to support qualified medical professionals for clinical decision making. The clinical significance of using ADAS 3D to identify arrhythmia substrates for the treatment of cardiac arrhythmias (e.g., ventricular tachycardia) or risk stratification has not been established. | | | Device Description (Including Functional and Technological Characteristics) | ADAS 3D is a stand-alone software tool designed for post-processing cardiovascular enhanced Magnetic Resonance (MR) images and Computed Tomography Angiography (CTA) images that are formatted in the Digital Imaging and Communication in Medicine (DICOM) standard. ADAS 3D software aids in the non-invasive calculation, quantification and visualization of cardiac imaging data to support a comprehensive diagnostic decision- making process for understanding cardiovascular disease. | ADAS 3D is a stand-alone software tool designed for post-processing cardiovascular enhanced Magnetic Resonance (MR) images and Computed Tomography Angiography (CTA) images that are formatted in the Digital Imaging and Communication in Medicine (DICOM) standard. ADAS 3D software aids in the non- invasive calculation, quantification and visualization of cardiac imaging data to support a comprehensive diagnostic decision-making process for understanding cardiovascular disease. | | | ADAS 3D exports information to multiple industry standard file formats suitable for documentation and information sharing purposes. The 3D data is exported into industry standard file formats supported by catheter navigation systems. ADAS 3D analyses the enhancement of myocardial fibrosis from DICOM MR images to support: | ADAS 3D exports information to multiple industry standard file formats suitable for documentation and information sharing purposes. The 3D data is exported into industry standard file formats supported by catheter navigation systems. ADAS 3D analyses the enhancement of myocardial fibrosis from DICOM MR images to support: | | Elements of Comparison | Subject Device ADAS 3D (Adas3D Medical S.L.) | Predicate Device ADAS 3D (K230803) | | | Visualization of the distribution of the enhancement in a three-dimensional (3D) chamber of the heart. | Visualization of the distribution of the enhancement in a three-dimensional (3D) chamber of the heart. | | | Quantification of the total volume of the enhancement within the Left Ventricle (LV) and the visualization of the enhancement area in multiple layers through the cardiac structure. | Quantification of the total volume of the enhancement within the Left Ventricle (LV) and the visualization of the enhancement area in multiple layers through the cardiac structure. | | | Calculation, quantification and visualization of corridors of intermediate signal intensity enhancement in the LV. | Calculation, quantification and visualization of corridors of intermediate signal intensity enhancement in the LV. | | | Quantification and visualization of the total area and distribution of the enhancement within the left Atrium (LA). | Quantification and visualization of the total area and distribution of the enhancement within the left Atrium (LA). | | | Additionally, ADAS 3D imports DICOM CTA images to support: | Additionally, ADAS 3D imports DICOM CTA images to support: | | | Quantification of LV wall thickness. Identification and Visualization of other 3D anatomical structures. Quantification and visualization of LA wall thickness. Quantification and visualization of distances from the LA epicardium to other 3D anatomical structures. | Quantification of LV wall thickness. Identification and Visualization of other 3D anatomical structures. Quantification and visualization of LA wall thickness. Quantification and visualization of distances from the LA epicardium to other 3D anatomical structures. | | | Additionally, ADAS 3D imports DICOM Magnetic Resonance Angiography (MRA) images to support: | Additionally, ADAS 3D imports DICOM Magnetic Resonance Angiography (MRA) images to support: | | | Identification and Visualization of other 3D anatomical structures. | Identification and Visualization of other 3D anatomical structures. | | | | It is designed to be used by qualified medical professionals (cardiologists, radiologists or | | Elements of Comparison | Subject Device ADAS 3D (Adas3D Medical S.L.) | Predicate Device ADAS 3D (K230803) | | | Additionally, ADAS 3D uses the following machine-learning-based features: Standard Initialization of the LV, LA, and Aorta from CTA Standard Initialization of the Coronary Arteries from CTA Standard Initialization of the LA from CTA Standard Initialization of the LV from 2D LGE-MRI and Automatic Slice Alignment Standard Initialization of the LV from 3D LGE-MRI Standard Initialization of the LA from 3D LGE-MRI It is designed to be used by qualified medical professionals (cardiologists, radiologists or trained technicians) experienced in examining and evaluating cardiovascular MR and CTA images as part of the comprehensive diagnostic decision-making process. | trained technicians) experienced in examining and evaluating cardiovascular MR and CTA images as part of the comprehensive diagnostic decision-making process. | {8}------------------------------------------------ Image /page/8/Picture/0 description: The image shows the logo for Adas3D Medical. The logo features a stylized red heart with a blue swoosh above it, set against a background of small gray dots. Below the graphic is the text "Adas3D Medical" in a simple, sans-serif font. {9}------------------------------------------------ Image /page/9/Picture/0 description: The image shows the logo for Adas3D Medical. The logo features a stylized red heart with a blue arc wrapping around it, positioned above the text "Adas3D Medical." The text is in a simple, sans-serif font. There is a grid of dots in the background behind the heart. {10}------------------------------------------------ Image /page/10/Picture/0 description: The image shows the logo for Adas3D Medical. The logo features a stylized red heart with a blue arc sweeping across it, positioned above the text "Adas3D Medical." The text is stacked, with "Adas3D" on the top line and "Medical" on the bottom line. There are also some small dots in the background. {11}------------------------------------------------ Image /page/11/Picture/0 description: The image shows the logo for Adas3D Medical. The logo features a stylized red heart with a blue swoosh across it, positioned above the text "Adas3D Medical". The text is in a simple, sans-serif font and is stacked in two lines. The background is white. | Feature | Subject Device ADAS 3D (Adas3D Medical S.L.) | Predicate Device ADAS 3D (Adas3D Medical S.L.) (K230803) | Comparison | |--------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| | Supported Operating Systems | Linux RHEL 8, Windows 11 and Windows 10 | Windows 10 | Added support for Linux RHEL 8 and Windows 11 | | Initial Identification of structures | Semi-automatic using Machine Learning technique: Left Chambers from CTA Left Ventricle from 2D DE-MRI Coronaries from CTA Left Ventricle from 3D DE-MRI Left Atrium from 3D DE-MRI Left Atrium Wall Thickness from CTA | Semi-automatic using Machine Learning technique: Left Chambers from CTA Left Ventricle from 2D DE-MRI Coronaries from CTA Manual: Left Ventricle from 3D DE-MRI Left Atrium from 3D DE-MRI Left Atrium Wall Thickness from CTA | Added three new semi-automatic segmentations using Machine Learning technique. Improved the already existing three semi- automatic segmentations. | #### Changes from the predicate device ട് #### Summary of Non-Clinical Testing 6 The subject device has undergone design reviews, risk analyses, and verification and validation testing, to ensure its safety and effectiveness. The subject device has been assessed using well-established methods to validate that is substantial equivalent to the predicate device. ## Machine Learning features 6.1 The machine-learning features were trained and tested using DICOM data from several clinical sites from multiple countries. The DICOM data was acquired using a variety of CT/MRI scanners and scanner protocols from different manufacturers. This DICOM data was anonymized by the hospitals before being sent to us, in compliance with the European General Data Protection Regulation (GDPR). This anonymization process prevented including personal patient information such as gender, age, or ethnicity. This DICOM dataset includes a diverse range of atrial and ventricular conditions. The Left Ventricle (LV) includes ischemic and non-ischemic cardiomyopathies such as left ventricular hypertrophy and dilated cardiomyopathy, as well as other cardiac conditions like premature ventricular contractions. The Left Atrium (LA), includes a diverse range of conditions and presentations, from relatively healthy atrial tissue to various forms of atrial fibrillation (paroxysmal, persistent, long-standing persistent, and recurrent cases), other atrial {12}------------------------------------------------ Image /page/12/Picture/0 description: The image shows the logo for Adas3D Medical. The logo features a stylized red heart with a blue arc across it, positioned above the text "Adas3D Medical". The text is in a simple, sans-serif font, with "Adas3D" on the top line and "Medical" on the bottom line. There is also a grid of dots in the upper left corner of the image. pathologies such as atrial flutter and atrial tachycardia, and structural heart diseases impacting left atrial function. #### 6.1.1 Training For each machine learning feature, the training dataset has been obtained from the initial DICOM dataset, according to the image modality and the target structure. All DICOM images are from European hospitals. The details of the training dataset for each machine learning feature are summarized in the table below. | Machine learning feature | Number of DICOM images | Scanner manufacturers | |-----------------------------------------------------------------------|---------------------------|-------------------------------------------------------------| | Standard Initialization of the Left Chambers and Aorta from CTA | 111 | GE (62%), Toshiba (35%), Philips (3%) | | Standard Initialization of the Coronaries from CTA | 231 | Toshiba (48%), Siemens (37%), GE (14%) and Philips (1%). | | Standard Initialization the LA from CTA | 136 | GE (65%), Toshiba (32%) and Philips (3%) | | Standard Initialization LV from 2D DE-MRI | 126 | Siemens (91%), GE (6%), Phillips (3%) | | Standard Initialization of the LV from 3D DE-MRI | 110 | Siemens (99%), GE (1%) | | Standard Initialization of the LA from 3D DE-MRI | 82 | GE (51%), Philips (49%) | The DICOM dataset has been annotated identifying the target structures. The annotation of the data was generated initially by the hospitals' clinical teams and revised by Adas3D Medical's Clinical Team. The Adas3D Medical's Clinical Team consists of highly experienced individuals with knowledge of cardiac anatomy, interpretation of MRI and CT volumes, and the use of ADAS 3D. #### Performance testing 6.1.2 The performance testing for each machine learning feature was performed using a subset of the initial DICOM dataset, that was selected according to the target structure, the image modality, the country, and the scan manufacturer. Each testing dataset has been selected from hospitals not used in any stage of algorithm development, including training. The details of each testing dataset are summarized in the table below. | Machine learning feature | Number of cases | Data sources | Scanner manufacturers | |-------------------------------------------------|--------------------|--------------|----------------------------------------------| | Standard Initialization of the Left Chambers | 100 | US (62%) and | US: SIEMENS (61%), Toshiba (32%) and GE (7%) | {13}------------------------------------------------ Image /page/13/Picture/0 description: The image shows the logo for Adas3D Medical. The logo features a stylized red heart with a blue arc passing over it, set against a background of small dots. Below the heart graphic, the text "Adas3D Medical" is written in a clear, sans-serif font, with "Adas3D" on the top line and "Medical" on the bottom line. | and Aorta from CTA | | OUS (38%) | OUS: SIEMENS (47%), Toshiba (26%), Canon (13%), GE (11%) and Philips (3%) | |----------------------------------------------------------|-----|---------------------------|----------------------------------------------------------------------------------------------------------------------------------------------| | Standard Initialization of the Coronaries from CTA | 100 | US (64%) and OUS (36%) | US: SIEMENS (64%), Toshiba (26%), GE (8%) and Phillips (2) OUS: SIEMENS (47%), Toshiba (28%), Canon (14%), GE (8%) and Philips (3%) | | Standard Initialization the LA from CTA | 100 | US (65%) and OUS (35%) | US: SIEMENS (58%), Toshiba (34%) and GE (8%) OUS: SIEMENS (53%), Toshiba (30%), Canon (11%), GE (3%) and Philips (3%) | | Automatic Slice Alignment for LV from 2D DE-MRI | 70 | US (52%) and OUS (48%) | US: SIEMENS (72%), Philips (25%) and GE (3%) OUS: Philips (58%), SIEMENS (18%) and GE (24%) | | Standard Initialization of the LV from 2D DE- MRI | 100 | US (52%) and OUS (48%) | US: SIEMENS (71%), Philips (23%) and GE (6%) OUS: Philips (50%), SIEMENS (19%) and GE (31%) | | Standard Initialization of the LV from 3D DE- MRI | 100 | US (69%) and OUS (31%) | US: SIEMENS (62%), Philips (32%) and GE (6%) OUS: SIEMENS (49%), Philips (45%), Toshiba (3%) and GE (3%) | | Standard Initialization of the LA from 3D DE- MRI | 95 | US (60%) and OUS (35%) | US: Philips (50%), SIEMENS (45%) and GE (5%) OUS: SIEMENS (71%), Philips (26%) and GE (3%) | Ground truth annotations were generated using the FDA-cleared ADAS 3D software by two clinical experts independent of the clinical experts who established the ground truth of the training dataset. The performance metrics and the acceptance criteria for each target structure are based on a review of stateof-the-art algorithms. Performance testing follows a non-inferiority approach, with a predefined noninferiority margin. The primary goal of ADAS 3D is to provide a preliminary initialization of the target structure, which would then be subject to further refinement by the user. This non-inferiority approach confirms that the performance aligns with the average performance benchmarks reported in the field. The following metrics have been used to define the acceptance criteria: - MSD: Mean Surface Distance. - HD: Hausdorff Distance. - . MDS: Mean Difference in Shifts computes the slice alignment error between two 2D MRI images. It is computed as the mean of the shifts in x and y dimensions for all slices. {14}------------------------------------------------ Image /page/14/Picture/0 description: The image shows the logo for Adas3D Medical. The logo features a stylized red heart with a blue curved line running across it, positioned above the text "Adas3D Medical". The text is in a simple, sans-serif font, with "Adas3D" on the first line and "Medical" on the second line. - . APD: The Average Perpendicular Distance measures the average distance (in mm) of all corresponding contour points between two contours. A low APD value means that the two contours match closely. - DC: Dice Metric. - Color agreement (CA), Color disagreement by one color (CD1), and Color disagreement by two colors or more (CD2): These three metrics are defined in the paper: Valles-Colomer, A., Rubio Forcada, B., Soto-Iglesias, D. et al. Reproducibility analysis of the computerized tomography angiography-derived left atrial wall thickness maps. J Interv Card Electrophysiol 66, 1045–1055 (2023). https://doi.org/10.1007/s10840-023-01472-5 The table below summarizes the performance results. The metric values used for evaluating the performance are highlighted in bold. | Machine Learning feature | Target structure | Metric | Mean | Lower CI95 | Higher CI95 | Threshold | Meets acceptance criteria | |-----------------------------------------------------------------------------|---------------------|--------|-------|---------------|----------------|-----------|---------------------------------| | Standard Initialization of the Left Chambers and Aorta from CTA | LV | DC | 0.93 | 0.92 | 0.94 | 0.84 | yes | | | LV | MSD | 1.29 | 1.03 | 1.56 | 2.23 | yes | | | LA | DC | 0.94 | 0.94 | 0.95 | 0.84 | yes | | | LA | MSD | 1.06 | 0.95 | 1.17 | 2.23 | yes | | | AO | DC | 0.94 | 0.94 | 0.95 | 0.84 | yes | | | AO | MSD | 0.93 | 0.51 | 1.34 | 2.23 | yes | | | LAA | DC | 0.84 | 0.83 | 0.85 | 0.76 | yes | | | LAA | MSD | 1.01 | 0.91 | 1.1 | 2.23 | yes | | Standard Initialization of the Coronary Arteries from CTA | LCA | DC | 0.82 | 0.80 | 0.84 | 0.78 | yes | | | LCA | HD | 7.71 | 6.05 | 9.37 | 10.86 | yes | | | RCA | DC | 0.82 | 0.80 | 0.83 | 0.78 | yes | | | RCA | HD | 6.61 | 5.24 | 7.97 | 10.86 | yes | | Standard Initialization of the LA from CTA | LA ENDO | MSD | 0.37 | 0.32 | 0.41 | 0.32 | no | | | LA EPI | MSD | 0.56 | 0.51 | 0.61 | 0.76 | yes | | | LA | CA | 56.09 | 53.56 | 58.63 | 43.90 | yes | | | LA | CD1 | 38.32 | 36.37 | 40.28 | 49.00 | yes | | | LA | CD2 | 5.58 | 4.73 | 6.44 | 12.10 | yes | | Automatic Slice Alignment for LV from 2D LGE-MRI | LV | MDS | 2.39 | 2.22 | 2.55 | 6.23 | yes | | Standard Initialization of | LV ENDO | DC | 0.90 | 0.90 | 0.91 | 0.85 | yes | | | LV ENDO | APD | 2.01 | 1.89 | 2.13 | 2.10 | no | | | LV ENDO | HD | 9.72 | 9.04 | 10.40 | 13.25 | yes | {15}------------------------------------------------ Image /page/15/Picture/0 description: The image shows the logo for Adas3D Medical. The logo features a stylized red heart with a blue ribbon wrapping around it. Above the heart are several small dots arranged in a grid pattern. Below the heart is the text "Adas3D Medical" in a simple, sans-serif font. | the LV from 2D LGE-MRI | LV EPI | DC | 0.93 | 0.93 | 0.94 | 0.89 | yes | |------------------------------------------------------------|---------|-----|-------|-------|-------|-------|-----| | | LV EPI | APD | 2.06 | 1.95 | 2.17 | 1.93 | no | | | LV EPI | HD | 9.81 | 9.11 | 10.51 | 13.25 | yes | | Standard Initialization of the LV from 3D LGE-MRI | LV ENDO | DC | 0.88 | 0.87 | 0.88 | 0.79 | yes | | | LV ENDO | HD | 2.40 | 2.15 | 2.64 | 27.32 | yes | | | LV EPI | DC | 0.91 | 0.90 | 0.92 | 0.78 | yes | | | LV EPI | HD | 9.57 | 8.81 | 10.33 | 27.32 | yes | | Standard Initialization of the LA from 3D LGE-MRI | LA | DC | 0.90 | 0.89 | 0.91 | 0.86 | yes | | | LA | MSD | 1.62 | 1.45 | 1.78 | 1.39 | no | | | LA | HD | 12.36 | 11.17 | 13.55 | 16.50 | yes | Four tests did not meet the non-inferiority criteria. In these four cases, the discrepancies are sub-pixel, indicating that our algorithm's performance is acceptable given the minimum pixel spacing of the input images. A subgroup analysis found that the algorithms' performance is consistent across US and OUS groups. #### 6.1.3 Performance testing conclusion The results of the performance testing confirm that the subject device met all acceptance criteria and demonstrate that the performance of the machine learning features is in line with the performance of the predicate device. #### Conclusion 7 The comparison of the subject device with the predicate device show that they have substantially equivalent indications for use, functional and technological characteristics. Adas3D Medical believes the subject device is substantially equivalent to the predicate device and is as safe and effective as the predicate device.

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