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 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

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

AI/ML Overview

Here's a breakdown of the acceptance criteria and study details for the Adas3D Medical S.L. ADAS 3D device, based on the provided text:

Acceptance Criteria and Reported Device Performance

Machine Learning feature	Target structure	Metric	Mean Reported Performance	Threshold	Meets Acceptance Criteria
Standard Initialization of the Left Chambers and Aorta from CTA	LV	DC	0.93	0.84	yes
	LV	MSD	1.29	2.23	yes
	LA	DC	0.94	0.84	yes
	LA	MSD	1.06	2.23	yes
	AO	DC	0.94	0.84	yes
	AO	MSD	0.93	2.23	yes
	LAA	DC	0.84	0.76	yes
	LAA	MSD	1.01	2.23	yes
Standard Initialization of the Coronary Arteries from CTA	LCA	DC	0.82	0.78	yes
	LCA	HD	7.71	10.86	yes
	RCA	DC	0.82	0.78	yes
	RCA	HD	6.61	10.86	yes
Standard Initialization of the LA from CTA	LA ENDO	MSD	0.37	0.32	no
	LA EPI	MSD	0.56	0.76	yes
	LA	CA	56.09	43.90	yes
	LA	CD1	38.32	49.00	yes
	LA	CD2	5.58	12.10	yes
Automatic Slice Alignment for LV from 2D LGE-MRI	LV	MDS	2.39	6.23	yes
Standard Initialization of the LV from 2D LGE-MRI	LV ENDO	DC	0.90	0.85	yes
	LV ENDO	APD	2.01	2.10	no
	LV ENDO	HD	9.72	13.25	yes
	LV EPI	DC	0.93	0.89	yes
	LV EPI	APD	2.06	1.93	no
	LV EPI	HD	9.81	13.25	yes
Standard Initialization of the LV from 3D LGE-MRI	LV ENDO	DC	0.88	0.79	yes
	LV ENDO	HD	2.40	27.32	yes
	LV EPI	DC	0.91	0.78	yes
	LV EPI	HD	9.57	27.32	yes
Standard Initialization of the LA from 3D LGE-MRI	LA	DC	0.90	0.86	yes
	LA	MSD	1.62	1.39	no
	LA	HD	12.36	16.50	yes

Note: The text explicitly states that four tests did not meet the non-inferiority criteria, but these discrepancies were considered sub-pixel and acceptable.

Study Details

Sample size used for the test set and the data provenance:
- Standard Initialization of the Left Chambers and Aorta from CTA: 100 cases (US 62%, OUS 38%)
- Standard Initialization of the Coronaries from CTA: 100 cases (US 64%, OUS 36%)
- Standard Initialization the LA from CTA: 100 cases (US 65%, OUS 35%)
- Automatic Slice Alignment for LV from 2D DE-MRI: 70 cases (US 52%, OUS 48%)
- Standard Initialization of the LV from 2D DE-MRI: 100 cases (US 52%, OUS 48%)
- Standard Initialization of the LV from 3D DE-MRI: 100 cases (US 69%, OUS 31%)
- Standard Initialization of the LA from 3D DE-MRI: 95 cases (US 60%, OUS 35%)
All data in the test set was selected from hospitals not used in any stage of algorithm development (training). The data provenance for the test set includes imaging from both US and OUS (Outside US) countries. The data was anonymized by the hospitals in compliance with GDPR.
Number of experts used to establish the ground truth for the test set and the qualifications of those experts:
The ground truth annotations for the test set were generated by two clinical experts. Their qualifications are not explicitly detailed beyond being "clinical experts independent of the clinical experts who established the ground truth of the training dataset." However, the document states the device is intended for use by "qualified medical professionals (cardiologists, electrophysiologists, radiologists or trained technicians) experienced in examining and evaluating cardiovascular MR and CTA images." It can be inferred that these clinical experts possess similar qualifications.
Adjudication method for the test set:
The adjudication method for reconciling differences between the two clinical experts for the test set ground truth is not explicitly stated. It only mentions that ground truth was generated by two independent experts.
If a multi reader multi case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance:
No, a multi-reader, multi-case (MRMC) comparative effectiveness study evaluating human readers with and without AI assistance was not described in the provided text. The study focused on the standalone performance of the AI features.
If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:
Yes, the performance testing described is a standalone (algorithm only) performance evaluation. The study assessed the accuracy of the machine learning features against expert-generated ground truth, rather than measuring improvements in human reader performance with the device. The goal of the device is stated as "to provide a preliminary initialization of the target structure, which would then be subject to further refinement by the user," indicating a standalone assessment of its initialization capability.
The type of ground truth used:
The ground truth used for the test set was expert consensus / expert annotation. It was generated using the FDA-cleared ADAS 3D software by two independent clinical experts.
The sample size for the training set:
- Standard Initialization of the Left Chambers and Aorta from CTA: 111 DICOM images
- Standard Initialization of the Coronaries from CTA: 231 DICOM images
- Standard Initialization the LA from CTA: 136 DICOM images
- Standard Initialization LV from 2D DE-MRI: 126 DICOM images
- Standard Initialization of the LV from 3D DE-MRI: 110 DICOM images
- Standard Initialization of the LA from 3D DE-MRI: 82 DICOM images
How the ground truth for the training set was established:
The ground truth annotations for the training dataset were "generated initially by the hospitals' clinical teams and revised by Adas3D Medical's Clinical Team." 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."

Summary

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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.

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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

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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

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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 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)

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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-H08036 BarcelonaBarcelonaSpain
CONTACT:	Antoni Riu+34 93 328 3964antoni.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: QIHSecondary product code: LLZ
REGULATION DESCRIPTION:	Picture archiving and communications system
PREDICATE DEVICE:	ADAS 3D (K230803)

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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 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

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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.

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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 ofComparison	Subject DeviceADAS 3D(Adas3D Medical S.L.)	Predicate DeviceADAS 3D(K230803)
Regulatorydata
RegulatoryClass	Class II	Class II
Classificationname	Radiological Image processing system	Radiological Image processing system
RegulationNumber	21 CFR 892.2050	21 CFR 892.2050
Product Code	QIH, LLZ	LLZ
510(k) Number	K240791	K230803
Use
Indications forUse	ADAS 3D is indicated for use in clinical settingsto support the visualization and analysis of MRand CT images of the heart for use onindividual patients with cardiovasculardisease.ADAS 3D is indicated for patients withmyocardial scar produced by ischemic or non-ischemic heart disease. ADAS 3D processes MRand CT images. The quality and the resolutionof the medical images determines theaccuracy of the data produced by ADAS 3D.ADAS 3D is indicated to be used only byqualified medical professionals (cardiologists,electrophysiologists, radiologists or trainedtechnicians) for the calculation, quantificationand visualization of cardiac images andintended to be used for pre-planning andduring 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 anirrefutable basis or a source of medical advicefor clinical diagnosis or patient treatment. Thedata produced by ADAS 3D is intended to beused to support qualified medicalprofessionals for clinical decision making.The clinical significance of using ADAS 3D toidentify arrhythmia substrates for thetreatment of cardiac arrhythmias (e.g.,ventricular tachycardia) or risk stratificationhas not been established.
DeviceDescription(IncludingFunctional andTechnologicalCharacteristics)	ADAS 3D is a stand-alone software tooldesigned for post-processing cardiovascularenhanced Magnetic Resonance (MR) imagesand Computed Tomography Angiography(CTA) images that are formatted in the DigitalImaging and Communication in Medicine(DICOM) standard. ADAS 3D software aids inthe non-invasive calculation, quantificationand visualization of cardiac imaging data tosupport a comprehensive diagnostic decision-making process for understandingcardiovascular disease.	ADAS 3D is a stand-alone software tool designedfor post-processing cardiovascular enhancedMagnetic Resonance (MR) images andComputed Tomography Angiography (CTA)images that are formatted in the Digital Imagingand Communication in Medicine (DICOM)standard. ADAS 3D software aids in the non-invasive calculation, quantification andvisualization of cardiac imaging data to supporta comprehensive diagnostic decision-makingprocess for understanding cardiovasculardisease.
	ADAS 3D exports information to multipleindustry standard file formats suitable fordocumentation and information sharingpurposes. The 3D data is exported intoindustry standard file formats supported bycatheter navigation systems.ADAS 3D analyses the enhancement ofmyocardial fibrosis from DICOM MR images tosupport:	ADAS 3D exports information to multipleindustry standard file formats suitable fordocumentation and information sharingpurposes. The 3D data is exported into industrystandard file formats supported by catheternavigation systems.ADAS 3D analyses the enhancement ofmyocardial fibrosis from DICOM MR images tosupport:
Elements ofComparison	Subject DeviceADAS 3D(Adas3D Medical S.L.)	Predicate DeviceADAS 3D(K230803)
	Visualization of the distribution of theenhancement in a three-dimensional(3D) chamber of the heart.	Visualization of the distribution of theenhancement in a three-dimensional(3D) chamber of the heart.
	Quantification of the total volume ofthe enhancement within the LeftVentricle (LV) and the visualization ofthe enhancement area in multiplelayers through the cardiac structure.	Quantification of the total volume ofthe enhancement within the LeftVentricle (LV) and the visualization ofthe enhancement area in multiplelayers through the cardiac structure.
	Calculation, quantification andvisualization of corridors ofintermediate signal intensityenhancement in the LV.	Calculation, quantification andvisualization of corridors ofintermediate signal intensityenhancement in the LV.
	Quantification and visualization ofthe total area and distribution of theenhancement within the left Atrium(LA).	Quantification and visualization of thetotal area and distribution of theenhancement within the left Atrium(LA).
	Additionally, ADAS 3D imports DICOM CTAimages to support:	Additionally, ADAS 3D imports DICOM CTAimages to support:
	Quantification of LV wall thickness. Identification and Visualization ofother 3D anatomical structures. Quantification and visualization of LAwall thickness. Quantification and visualization ofdistances from the LA epicardium toother 3D anatomical structures.	Quantification of LV wall thickness. Identification and Visualization ofother 3D anatomical structures. Quantification and visualization of LAwall thickness. Quantification and visualization ofdistances from the LA epicardium toother 3D anatomical structures.
	Additionally, ADAS 3D imports DICOMMagnetic Resonance Angiography (MRA)images to support:	Additionally, ADAS 3D imports DICOM MagneticResonance Angiography (MRA) images tosupport:
	Identification and Visualization ofother 3D anatomical structures.	Identification and Visualization ofother 3D anatomical structures.
		It is designed to be used by qualified medicalprofessionals (cardiologists, radiologists or
Elements ofComparison	Subject DeviceADAS 3D(Adas3D Medical S.L.)	Predicate DeviceADAS 3D(K230803)
	Additionally, ADAS 3D uses the followingmachine-learning-based features:Standard Initialization of the LV, LA,and Aorta from CTA Standard Initialization of theCoronary Arteries from CTA Standard Initialization of the LA fromCTA Standard Initialization of the LV from2D LGE-MRI and Automatic SliceAlignment Standard Initialization of the LV from3D LGE-MRI Standard Initialization of the LA from3D LGE-MRI It is designed to be used by qualified medicalprofessionals (cardiologists, radiologists ortrained technicians) experienced in examiningand evaluating cardiovascular MR and CTAimages as part of the comprehensivediagnostic decision-making process.	trained technicians) experienced in examiningand evaluating cardiovascular MR and CTAimages as part of the comprehensive diagnosticdecision-making process.

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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.

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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.

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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.

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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 DeviceADAS 3D(Adas3D Medical S.L.)	Predicate DeviceADAS 3D(Adas3D Medical S.L.)(K230803)	Comparison
SupportedOperatingSystems	Linux RHEL 8, Windows 11 andWindows 10	Windows 10	Added support forLinux RHEL 8 andWindows 11
InitialIdentificationof structures	Semi-automatic using MachineLearning 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 Thicknessfrom CTA	Semi-automatic using MachineLearning 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 fromCTA	Added three newsemi-automaticsegmentations usingMachine Learningtechnique.Improved the alreadyexisting three semi-automaticsegmentations.

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

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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 ofDICOM images	Scanner manufacturers
Standard Initialization ofthe Left Chambers andAorta from CTA	111	GE (62%), Toshiba (35%), Philips (3%)
Standard Initialization ofthe Coronaries from CTA	231	Toshiba (48%), Siemens (37%), GE (14%) and Philips(1%).
Standard Initialization theLA from CTA	136	GE (65%), Toshiba (32%) and Philips (3%)
Standard Initialization LVfrom 2D DE-MRI	126	Siemens (91%), GE (6%), Phillips (3%)
Standard Initialization ofthe LV from 3D DE-MRI	110	Siemens (99%), GE (1%)
Standard Initialization ofthe 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 learningfeature	Numberof cases	Data sources	Scanner manufacturers
Standard Initializationof the Left Chambers	100	US (62%) and	US: SIEMENS (61%), Toshiba (32%) and GE (7%)

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and Aorta from CTA		OUS (38%)	OUS: SIEMENS (47%), Toshiba (26%), Canon (13%), GE(11%) and Philips (3%)
Standard Initializationof the Coronaries fromCTA	100	US (64%) andOUS (36%)	US: SIEMENS (64%), Toshiba (26%), GE (8%) andPhillips (2)OUS: SIEMENS (47%), Toshiba (28%), Canon (14%), GE(8%) and Philips (3%)
Standard Initializationthe LA from CTA	100	US (65%) andOUS (35%)	US: SIEMENS (58%), Toshiba (34%) and GE (8%)OUS: SIEMENS (53%), Toshiba (30%), Canon (11%), GE(3%) and Philips (3%)
Automatic SliceAlignment for LV from2D DE-MRI	70	US (52%) andOUS (48%)	US: SIEMENS (72%), Philips (25%) and GE (3%)OUS: Philips (58%), SIEMENS (18%) and GE (24%)
Standard Initializationof the LV from 2D DE-MRI	100	US (52%) andOUS (48%)	US: SIEMENS (71%), Philips (23%) and GE (6%)OUS: Philips (50%), SIEMENS (19%) and GE (31%)
Standard Initializationof the LV from 3D DE-MRI	100	US (69%) andOUS (31%)	US: SIEMENS (62%), Philips (32%) and GE (6%)OUS: SIEMENS (49%), Philips (45%), Toshiba (3%) andGE (3%)
Standard Initializationof the LA from 3D DE-MRI	95	US (60%) andOUS (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.

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. 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 Learningfeature	Targetstructure	Metric	Mean	LowerCI95	HigherCI95	Threshold	Meetsacceptancecriteria
StandardInitialization ofthe LeftChambers andAorta 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
StandardInitialization ofthe CoronaryArteries fromCTA	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
StandardInitialization ofthe 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 SliceAlignment for LVfrom 2D LGE-MRI	LV	MDS	2.39	2.22	2.55	6.23	yes
StandardInitialization 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

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the LV from 2DLGE-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
StandardInitialization ofthe LV from 3DLGE-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
StandardInitialization ofthe LA from 3DLGE-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.

Regulation Number and Section

§ 892.2050 Medical image management and processing system.

(a)
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.(b)
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).