1091 contrast-enhanced CT images from 38 clinical sites
—
50 patients
—
Ablation Target Segmentation
AI algorithm
Mean DICE = 0.70
Mean DICE = 0.82
1091 contrast-enhanced CT images from 38 clinical sites
—
59 patients
—
Ablation Zone Segmentation
AI algorithm
Mean DICE = 0.70
Mean DICE = 0.88
1091 contrast-enhanced CT images from 38 clinical sites
—
59 patients
—
Liver Vessels Segmentation
AI algorithm
Mean DICE = 0.70
Mean DICE = 0.72
393 contrast-enhanced CT images from 36 clinical sites
—
100 patients
—
Liver Segmentation
AI algorithm
Mean DICE = 0.92
Mean DICE = 0.93
418 MR images from 3 clinical sites
—
25 patients
—
Ablation Target Segmentation
AI algorithm
Mean DICE = 0.70
Mean DICE = 0.76
418 MR images from 3 clinical sites
—
50 patients
—
Pre-ablation CT to Post Ablation CT Image Registration
—
MCD = 6.06 mm
MCD = 4.09 mm
—
—
46 patients
—
Pre-ablation MR to Post-ablation CT Image Registration
—
MCD = 6.06 mm
MCD = 4.72 mm
—
—
25 patients
—
Pre-ablation MR to Pre-ablation CT Image Registration
—
MCD = 7.90 mm
MCD = 5.10 mm
—
—
18 patients
—
Indications for Use
VisAble.IO is a Computed Tomography (CT) and Magnetic Resonance (MR) image processing software package available for use with liver ablation procedures. VisAble.IO is controlled by the user via a user interface. VisAble.IO imports images from CT and MR scanners and facility PACS systems for display and processing during liver ablation procedures. VisAble.IO is used to assist physicians in planning ablation procedures, including identifying ablation targets and virtual ablation needle placement. VisAble.IO is used to assist physicians in confirming ablation zones. The software is not intended for diagnosis. The software is not intended to predict ablation volumes or predict ablation success.
Device Story
VisAble.IO is a stand-alone software application for liver ablation planning and confirmation. It imports CT and MR images from scanners or PACS. Physicians use the software in the OR or interventional radiology control room to segment anatomic structures (liver, vessels, ablation targets), perform virtual needle placement, and segment ablation zones. The software performs image fusion/registration between pre- and post-interventional scans and calculates margins and missed volumes. It provides quantitative analysis to help physicians assess ablation coverage. The device does not perform diagnosis or predict ablation success; it serves as a decision-support tool for the physician, who remains responsible for clinical accuracy and final assessment of segmentations and registrations.
Clinical Evidence
Bench testing only. Validation included algorithmic performance testing for segmentation and registration. Liver segmentation (CT) achieved mean DICE 0.98; Ablation target segmentation (CT) mean DICE 0.82; Ablation zone segmentation (CT) mean DICE 0.88; Liver vessel segmentation (CT) mean DICE 0.72. MR processing: Liver segmentation mean DICE 0.93; Ablation target segmentation mean DICE 0.76. Registration accuracy (MCD) ranged from 4.09 mm to 5.10 mm depending on modality combinations. Testing used datasets from multiple clinical sites (N=38 for CT, N=3 for MR).
Technological Characteristics
Stand-alone software application. Supports CT and MR modalities. Features include manual/automated segmentation, image fusion/registration, and quantitative measurement. Adheres to DICOM standards. Software-only, no energy delivery. Operates on a dedicated computer in hospital environments.
Indications for Use
Indicated for use in liver ablation procedures to assist physicians in planning (identifying targets, virtual needle placement) and confirming ablation zones using CT and MR images. Intended for any patient demographic undergoing ablation treatment.
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).
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Image /page/0/Picture/0 description: The image contains the logo of the U.S. Food and Drug Administration (FDA). On the left is the Department of Health & Human Services logo. To the right of that is the FDA logo, which is a blue square with the letters "FDA" in white. To the right of the blue square is the text "U.S. FOOD & DRUG ADMINISTRATION" in blue.
Techsomed Dalia Dickman Head of Regulatory Affairs Meir Weisgal 2 REHOVOT, 7654055 ISRAEL
April 15, 2024
Re: K240773
Trade/Device Name: VisAble.IO Regulation Number: 21 CFR 892.2050 Regulation Name: Medical Image Management And Processing System Regulatory Class: Class II Product Code: QTZ, QIH, LLZ Dated: March 20, 2024 Received: March 21, 2024
Dear Dalia Dickman:
We have reviewed your section 510(k) premarket notification of intent to market the device referenced above and have determined the device is substantially equivalent (for the indications for use stated in the enclosure) to legally marketed predicate devices marketed in interstate commerce prior to May 28, 1976, the enactment date of the Medical Device Amendments, or to devices that have been reclassified in accordance with the provisions of the Federal Food, Drug, and Cosmetic Act (the Act) that do not require approval of a premarket approval application (PMA). You may, therefore, market the device, subject to the general controls provisions of the Act. Although this letter refers to your product as a device, please be aware that some cleared products may instead be combination products. The 510(k) Premarket Notification Database available at https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm identifies combination product submissions. The general controls provisions of the Act include requirements for annual registration, listing of devices, good manufacturing practice, labeling, and prohibitions against misbranding and adulteration. Please note: CDRH does not evaluate information related to contract liability warranties. We remind you, however, that device labeling must be truthful and not misleading.
If your device is classified (see above) into either class II (Special Controls) or class III (PMA), it may be subject to additional controls. Existing major regulations affecting your device can be found in the Code of Federal Regulations, Title 21, Parts 800 to 898. In addition, FDA may publish further announcements concerning your device in the Federal Register.
Additional information about changes that may require a new premarket notification are provided in the FDA guidance documents entitled "Deciding When to Submit a 510(k) for a Change to an Existing Device" (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).
{1}------------------------------------------------
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.
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-regulatoryassistance/contact-us-division-industry-and-consumer-education-dice) for more information or contact DICE by email (DICE@fda.hhs.gov) or phone (1-800-638-2041 or 301-796-7100).
Sincerely.
Jessica Lamb
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
{2}------------------------------------------------
# Indications for Use
510(k) Number (if known) K240773
Device Name VisAble.IO
#### Indications for Use (Describe)
VisAble.IO is a Computed Tomography (CT) and Magnetic Resonance (MR) image processing software package available for use with liver ablation procedures.
VisAble.IO is controlled by the user via a user interface.
VisAble.IO imports images from CT and MR scanners and facility PACS systems for display and processing during liver ablation procedures.
VisAble.IO is used to assist physicians in planning ablation procedures, including identifying ablation targets and virtual ablation needle placement. VisAble.IO is used to assist physicians in confirming ablation zones.
The software is not intended for diagnosis. The software is not intended to predict ablation volumes or predict ablation success.
| Type of Use (Select one or both, as applicable) |
|-------------------------------------------------|
|-------------------------------------------------|
| <span> <span></span>Prescription Use (Part 21 CFR 801 Subpart D) </span> | <span> <span></span>Over-The-Counter Use (21 CFR 801 Subpart C) </span> |
|-----------------------------------------------------------------------------|----------------------------------------------------------------------------|
|-----------------------------------------------------------------------------|----------------------------------------------------------------------------|
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### K240773
# 510(K) SUMMARY
# TechsoMed's VisAble.IO
### Submitter
TechsoMed Medical Technologies. LTD.
Meir Weisgal 2 Rehovot Israel
Phone: +972545595951
Contact Person: Dalia Dickman, PhD.
Date Prepared: March 19, 2024
Name of Device: VisAble.IO
Common or Usual Name: VisAble.IO
Classification Name: Medical Image Management and Processing System (21 CFR 892.2050)
Regulatory Class: Class II
Product Code: QTZ, QIH, LLZ
### Predicate Devices
| 510(K) Number | K223639 |
|----------------------|------------------------------------------------|
| Trade Name | VisAble.IO |
| Manufacturer | TechsoMed Medical Technologies. LTD. |
| Device Name | VisAble.IO |
| Regulation Number | 892.2050 |
| Regulation Name | Medical Image Management and Processing System |
| Regulatory Class | Class II |
| Primary Product Code | QTZ, QIH, LLZ |
### Device Description
VisAble.IO is a stand-alone software application with tools and features designed to assist users in planning ablation procedures as well as tools for treatment confirmation. The use environment for VisAble.IO is the Operating Room and the hospital healthcare environment such as interventional radiology control room.
VisAble.IO has five distinct workflow steps:
- Data Import
- . Anatomic Structures Segmentation (Liver, Hepatic Vein, Portal Vein, Ablation Target)
- . Instrument Placement (Needle Planning)
- Ablation Zone Segmentation
{4}------------------------------------------------
- . Treatment Confirmation (Registration of Pre- and Post-Interventional Images; Quantitative Analysis)
Of these workflow steps, two (Anatomic Segmentation, and Instrument Placement) make use of the planning image. These workflow steps contain features and tools designed to support the planning of ablation procedures. The other two (Ablation Zone Segmentation, and Treatment Confirmation) make use of the confirmation image volume. These workflow steps contain features and tools designed to support the evaluation of the ablation procedure's technical performance in the confirmation image volume.
Key features of the VisAble.IO Software include:
- . Workflow steps availability
- Manual and automated tools for anatomic structures and ablation zone segmentation
- Overlaying and positioning virtual instruments (ablation needles) and user-selected estimates of the ablation regions onto the medical images
- . Image fusion and registration
- . Compute achieved margins and missed volumes to help the user assess the coverage of the ablation target by the ablation zone
- . Data saving and secondary capture generation
The software components provide functions for performing operations related to image display, manipulation, analysis, and quantification, including features designed to facilitate segmentation of the ablation target and ablation zones.
The software system runs on a dedicated computer and is intended for display and processing, of a Computed Tomography (CT) and Magnetic Resonance (MR), including contrast enhanced images.
The system can be used on patient data for any patient demographic chosen to undergo the ablation treatment.
VisAble.IO uses several algorithms to perform operations to present information to the user in order for them to evaluate the planned and post ablation zones. These include:
- . Segmentation
- . Image Registration
- . Measurement and Quantification
VisAble.IO is intended to be used for ablations with the following ablation instruments:
For needle planning, the software currently supports the following needle models:
- Medtronic: Emprint Antenna 15CM, 20CM, 30CM -
- -NeuWave Medical: PR Probe 15CM, 20CM; PR XT Probe 15CM, 20CM; LK Probe 15CM, 20CM; LK XT Probe 15CM, 20CM
- -H.S. Hospital Service: AMICA Probe 15 CM, 20 CM, 27 CM.
For treatment confirmation (including segmentation and registration), the software is compatible with all ablation devices as these functions are independent from probes/power settings.
### Intended Use / Indications for Use
VisAble.IO is a Computed Tomography (CT) and Magnetic Resonance (MR) image processing software package available for use with liver ablation procedures.
{5}------------------------------------------------
VisAble. IO is controlled by the user via a user interface.
VisAble.IO imports images from CT and MR scanners and facility PACS systems for display and processing during liver ablation procedures.
VisAble.IO is used to assist physicians in planning ablation procedures, including identifying ablation targets and virtual ablation needle placement. VisAble.IO is used to assist physicians in confirming ablation zones.
The software is not intended for diagnosis. The software is not intended to predict ablation volumes or predict ablation success.
### Summary of Technological Characteristics
Both the subject and predicate device are stand-alone software application with tools and features designed to assist users in planning liver ablation procedures as well as tools for treatment confirmation. The use environment for both the subject and predicate device is the Operating Room and the hospital healthcare environment such as interventional radiology control room.
The software components of the subject and predicate device provide functions for performing operations related to image display, manipulation, analysis, and quantification, including features designed to facilitate segmentation of the ablation target and ablation zones.
Both the subject and predicate device have the same five distinct workflow steps:
- Data Import .
- . Anatomic Structures Segmentation
- Instrument Placement (Needle Planning) ●
- . Ablation Zone Segmentation
- . Treatment Confirmation (Registration of Pre- and Post-Interventional Images; Quantitative Analysis)
The following technological differences exist between the subject and the predicate device:
The primary difference between devices is that, while the predicate device supports image processing of CT only, the subject device supports image processing of both Computed Tomography (CT) as well as Magnetic Resonance (MR). These differences do not raise additional concerns of safety or effectiveness as performance data demonstrates that the VisAble.IO is as safe and effective as the predicate device.
A table comparing the key features of the subject and predicate devices is provided below.
#### SUBSTANTIAL EQUIVALENCE COMPARISON TABLE
| | Subject Device<br>VisAble.IO (Ver 1.4) | Predicate Device<br>VisAble.IO (Ver 1.0) |
|------------------------------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| 510(k) number | | K223639 |
| Classification | Class II 892.2050 QTZ, QIH,<br>LLZ | Class II 892.2050 QTZ, QIH,<br>LLZ |
| Intended Use | The intended patient<br>population is patients chosen<br>by interventional radiologists to | The intended patient population<br>is patients chosen by<br>interventional radiologists to |
| | undergo ablation treatment<br>(including patients with soft<br>tissue lesions) | undergo ablation treatment<br>(including patients with soft<br>tissue lesions) |
| Indications for Use | VisAble.IO is a Computed<br>Tomography (CT) and<br>Magnetic Resonance (MR)<br>image processing software<br>package available for use with<br>liver ablation procedures. | VisAble.IO is a Computed<br>Tomography (CT) image<br>processing software package<br>available for use with liver<br>ablation procedures. |
| | VisAble.IO is controlled by the<br>user via a user interface. | VisAble.IO is controlled by the<br>user via a user interface. |
| | VisAble.IO imports images<br>from CT and MR scanners and<br>facility PACS systems for<br>display and processing during<br>liver ablation procedures. | VisAble.IO imports images from<br>CT and MR scanners and facility<br>PACS systems for display and<br>processing during liver ablation<br>procedures. |
| | VisAble.IO is used to assist<br>physicians in planning ablation<br>procedures, including<br>identifying ablation targets and<br>virtual ablation needle<br>placement. VisAble.IO is used<br>to assist physicians in<br>confirming ablation zones. | VisAble.IO is used to assist<br>physicians in planning ablation<br>procedures, including identifying<br>ablation targets and<br>virtual ablation needle<br>placement. VisAble.IO is used to<br>assist physicians in confirming<br>ablation zones. |
| | The software is not intended<br>for diagnosis. The software is<br>not intended to predict ablation<br>volumes or predict ablation<br>success. | The software is not intended for<br>diagnosis. The software is not<br>intended to predict ablation<br>volumes or predict ablation<br>success. |
| User Population | Qualified trained physicians | Qualified trained physicians |
| Where used | The application's use<br>environment is the Operation<br>Room and the hospital<br>healthcare environment such<br>as interventional radiology<br>control room | The application's use<br>environment is the Operation<br>Room and the hospital<br>healthcare environment such as<br>interventional radiology control<br>room |
| Energy Used | None - software only<br>application. The software<br>application does not deliver or<br>depend on energy delivered to<br>or from patients | None - software only application.<br>The software application does<br>not deliver or depend on energy<br>delivered to or from patients |
| Technological<br>Characteristics | VisAble.IO is a stand-alone<br>software application with tools<br>and features designed to assist<br>users in planning liver ablation<br>procedures as well as tools for<br>treatment confirmation. The<br>use environment the device is<br>the Operating Room and the | VisAble.IO is a stand-alone<br>software application with tools<br>and features designed to assist<br>users in planning liver ablation<br>procedures as well as tools for<br>treatment confirmation. The use<br>environment the device is the<br>Operating Room and the hospital |
| | hospital healthcare environment such as interventional radiology control room. VisAble.IO has five distinct workflow steps:<br>Data Import Anatomic Structures Segmentation Instrument Placement (Needle Planning) Ablation Zone Segmentation Treatment Confirmation (Registration of Pre- and Post-Interventional Images; Quantitative Analysis) | healthcare environment such as interventional radiology control room. VisAble.IO has five distinct workflow steps:<br>Data Import Anatomic Structures Segmentation Instrument Placement (Needle Planning) Ablation Zone Segmentation Treatment Confirmation (Registration of Pre- and Post-Interventional Images; Quantitative Analysis) |
| Design: Supported modalities | CT, MR | CT |
| Design: Data Visualization | Window and level, pan, zoom, cross- hairs, slice navigation | Window and level, pan, zoom, cross- hairs, slice navigation |
| Design; Image Segmentation | Tools for segmenting 3D VOIs, including target tissues, ablation zones, vessels and liver. | Tools for segmenting 3D VOIs, including target tissues, ablation zones, vessels and liver. |
| Design: Image registration | Registration of multiple images and imaging modalities into a single view. | Registration of multiple images and imaging modalities into a single view. |
| Design: Ablation zone confirmation | Registration of the planning scan, containing the identified target tissue, with the confirmation scan showing the ablation zone. The delineated target tissue on the planning scan is then projected onto the confirmation scan and overlaid onto the delineated ablation zone segmentation. This helps the user in analysing if the ablation zone covers the target tissue with the desired amount of margin. | Registration of the planning scan, containing the identified target tissue, with the confirmation scan showing the ablation zone. The delineated target tissue on the planning scan is then projected onto the confirmation scan and overlaid onto the delineated ablation zone segmentation. This helps the user in analysing if the ablation zone covers the target tissue with the desired amount of margin. |
{6}------------------------------------------------
{7}------------------------------------------------
{8}------------------------------------------------
# Performance Data
VisAble.IO is validated and verified against its user needs and intended use by the successful execution of planned performance, functional and algorithmic testing included in this submission.
The results of performance, functional and algorithmic testing demonstrate that VisAble.IO meets the user needs and requirements of the device, which are considered to be substantially equivalent to those of the listed predicate device.
Performance testing (Bench) was performed on the following features, to ensure that performance and accuracy was as expected:
- . Segmentation post-processing Testing
- Image Registration Testing
- . Measurement and Quantification Testing
The liver segmentation and liver vessel segmentation algorithms for CT processing are Al alqorithms. The training and model validation dataset characteristics are as follows:
Liver Segmentation Algorithm:
- Patients
- 1091 contrast-enhanced CT images from arterial or venous phases in axial orientation
- · Age distribution: 50.70 ± 24.14
- · Sex distribution: 34.58% female, 65.42% male
- Location of clinical sites: Germany, France, Turkey, Japan, Israel, Netherlands, Canada, USA, UK
- · Imaging procedure: Contrast-enhanced CT images taken for diagnostic reading
- · Number of clinical sites: 38
Liver Vessel Segmentation Algorithm:
- Patients .
- · N=393 contrast-enhanced CT images from the portal-venous or late venous phases in axial orientation
- · Age distribution: 51.40 ± 22.81
- · Sex distribution: 37.43% female, 62.57% male
- · Location of clinical sites: Central Europe, North America, East Asia
- · Imaging procedure: Contrast-enhanced CT images taken for diagnostic reading in liver diagnosis
- · Number of clinical sites: 36
The liver segmentation for MR processing is an AI algorithm. The training and model validation dataset characteristics are as follows:
- . Patients
- 418 MR images from arterial and venous phase •
- Age distribution: 64.30 ± 13.99
- . Sex distribution: 26.86% female, 73.14% male
- Location of clinical sites: Central Europe
- Imaging procedure: MR images taken for diagnostic reading
- Number of clinical sites: 3
{9}------------------------------------------------
The following table provides a summary of the validation results:
| Algorithm | N | Gender | Mean Age | N per Region | MR /CT Brand | Performance Goal | Performance |
|-------------------------------------------------------------|-----|--------------------------------|----------|-------------------|------------------------------------------------------------------------------------------------------------------|------------------|------------------|
| CT Processing | | | | | | | |
| Liver Segmentation | 50 | M: 52%<br>F: 48% | 60.6 | US: 32<br>OUS: 18 | GE Medical Systems,<br>Siemens | Mean DICE =0.92 | Mean DICE =0.98 |
| Ablation Target Segmentation | 59 | M: 54%<br>F: 46% | 60.0 | US: 30<br>OUS: 29 | GE Medical Systems,<br>Siemens, Philips | Mean DICE = 0.70 | Mean DICE = 0.82 |
| Ablation Zone Segmentation | 59 | M:64% F:<br>36% | 66.0 | US: 30<br>OUS: 29 | GE Medical Systems,<br>Siemens | Mean DICE = 0.70 | Mean DICE = 0.88 |
| Liver Vessels Segmentation | 100 | M: 52%<br>F: 48% | 58.5 | US: 72<br>OUS: 28 | GE Medical Systems,<br>Siemens | Mean DICE = 0.70 | Mean DICE = 0.72 |
| MR Processing | | | | | | | |
| Liver Segmentation | 25 | M: 76%<br>F: 24% | 70.4 | US: 25 | GE Medical Systems, Philips,<br>Siemens | Mean DICE = 0.92 | Mean DICE = 0.93 |
| Ablation Target Segmentation | 50 | M: 70%<br>F: 30% | 69 | US: 46<br>OUS: 4 | GE Medical Systems, Philips,<br>Siemens | Mean DICE = 0.70 | Mean DICE = 0.76 |
| Image Registration | | | | | | | |
| Pre-ablation CT to Post Ablation CT<br>Image Registration | 46 | M: 59%<br>F: 41% | 63.3 | US: 13<br>OUS: 33 | GE Medical Systems,<br>Siemens,<br>Philips | MCD*= 6.06 mm | MCD*=4.09 mm |
| Pre-ablation MR to Post-ablation CT<br>Image Registration | 25 | M: 56%<br>F: 28%<br>Other: 16% | 68.4 | US: 25 | MR: GE Medical Systems, Philips, Siemens<br>CT: GE Medical Systems, Philips, Siemens, Toshiba | MCD* = 6.06 mm | MCD* = 4.72 mm |
| Pre-ablation MR to<br>Pre-ablation CT<br>Image Registration | 18 | M: 83%<br>F: 17% | 71.5 | US: 14<br>OUS: 4 | MR: GE Medical<br>Systems, Philips,<br>Siemens,<br>Toshiba<br><br>CT: GE Medical<br>Systems, Philips,<br>Toshiba | MCD* = 7.90 mm | MCD* = 5.10 mm |
{10}------------------------------------------------
*MCD = Mean Corresponding Distance
VisAble.IO provides functions including linear distance measurements and volumetric measurements. The resolution of the medical image data directly affects the ability of the user to make definitive measurements, especially when the sizes of structures to identify, segment or measure are near the resolution of the image data. The software's functions are dependent on the user actions as well as on the available information in the provided medical image data.
Segmentation tools provided within VisAble.IO include manual and semiautomated segmentation, and system post-processing of segmentations to remove 2D-holes and/or disconnected 3D regions present. The use of the segmentation tools to achieve a satisfactory delineation of ablation target or ablation zone is a user operation and the clinical accuracy of segmentation is the responsibility of the user and not a VisAble.IO function.
Registration tools provided within VisAble.IO include automated local rigid registration within a region of interest around user-segmentations of ablation targets and ablation zones. Final accuracy of registration is dependent on user assessment and manual modification of the registration prior to acceptance, and not a VisAble.IO function.
Measurements of the achieved margins and missed volumes, calculated by comparing the segmentations, are presented by the system following user acceptance of segmentations and registration as clinically accurate. Accuracy of linear distance measures calculated by VisAble.IO are dependent on the image resolution.
Test planning was performed in accordance with standard testing procedures and guidelines as listed in internal development processes.
Verification and validation testing were carried out as per planned arrangements in the Project Test Plan and Phase Test Plan(s) to ensure that design outputs meet design inputs and that this edition of VisAble.IO meets the product acceptance criteria. These are in accordance with the company's Design Control process in compliance with 21 CFR Part 820.30, which included testing that fulfills the requirements of FDA "Guidance on Software Contained in Medical Devices" and adherence to the DICOM standard.
Potential risks were analyzed and satisfactorily mitigated in the device design.
# Conclusions
The VisAble.IO (V1.4) is as safe and effective as the cleared VisAble.IO (K223693). The VisAble.IO has the same intended uses and similar indications, technological characteristics, and principles of operation as its predicate device. The minor differences in indications do not alter the intended use of the device and do not affect its safety and effectiveness when used as labeled. In addition, the minor technological differences between the VisAble.IO and its predicate device raise no new issues of safety or effectiveness. Performance data demonstrate that the VisAble.IO (V 1.4) is as safe and effective as the cleared VisAble.IO (K223693). Thus, the VisAble.IO is substantially equivalent to the predicate device.
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Part 2 — Embeddings: the galaxy map 3 min
1. Search: exact and fuzzy
Type a phrase like "coronary artery calcification" into the search box. You get two kinds of results. Exact results match the literal phrase — prefix searches work ("coronary artery calcificati") but suffix searches do not. Fuzzy results match on the meaning and intent of your phrase rather than the exact words, and are sorted by relevance score. Hover over the Exact or Fuzzy badge on any row to see exactly why it matched.
Use the checkboxes above the results to narrow: SaMD keeps only software-only devices, AI / ML keeps only devices with AI.
Exact vs. fuzzy search: what's the difference?
Exact matches on the literal phrase (prefix search works, suffix does not). Fuzzy matches on the meaning and intent of the phrase rather than the exact words. Hover over the badge on any row to see why it matched.
You search "coronary artery calcification" and want only software devices with AI. What two filters do you apply?
Narrow by SaMD (software-only devices), then narrow by AI/ML (devices with AI).
2. The results table
Scroll right in the results table. The intended use is extracted for you — no need to open the PDF. The device story gives a high-level snapshot of what the device does and how it's used. The AI Performance sub-table shows each output name, acceptance criteria, observed values, and development/test dataset descriptions — the same format Innolitics uses for regulatory strategy outputs, and the fastest high-level fingerprint of an AI device. It is AI-generated but has been very reliable in practice.
Where do you find a device's intended use without opening the PDF?
Scroll right in the search results table. The intended use column is extracted for you; no need to dig into the 510(k) summary PDF.
What does the AI Performance sub-table show, and why is it useful?
Output name, acceptance criteria, observed values, development dataset description, and test dataset description. It's the same format we use for regulatory strategy output and Fast 510(k) input, and the fastest high-level fingerprint of an AI device. AI-generated but reliable in practice.
3. Judging fuzzy relevance
Fuzzy results trail off in relevance as you scroll. Use three signals to decide how far down to go: the fuzzy badge explanations, the intended use column, and whether your target output (e.g., Cobb angle) still appears in the AI Performance sub-table. Once it stops appearing, you're past the relevant zone. A top hit with a low score (~0.4) and a stretched explanation is a hint the closest predicates are far away — the project may be headed for De Novo. Note the fuzzy search is a pattern match: it doesn't handle negation ("not") well, and hardware devices can appear — filter by SaMD/AI ML to cut them.
How do you judge how far down fuzzy search results to go?
Use the relevancy signals: the fuzzy badge explanations, the intended use column, and whether the target output (e.g., Cobb angle) still appears in the AI Performance sub-table. Once it stops appearing, results are trailing off in relevancy.
4. Device detail page: chat and citations
Click a device name to open its detail page: device facts on the left, a chat window on the right. Ask something like "Describe the training data". The answer carries little citation bubbles — click one to jump to the highlighted passage in the source PDF, so you can verify every AI answer against the document. There's also a Download PDF button for sharing.
How do you verify an AI chat answer on the device detail page?
Click the citation bubbles to jump to the relevant highlight in the source document.
Reading rule for every project: how many summaries do you read in full?
At least the three most relevant 510(k) or De Novo summaries, in full. After that, use targeted chat questions to confirm your memory quickly. The tool supports this professional habit — it doesn't replace it.
5. Side-by-side comparison
Select multiple rows in the results table (aim for under ~10), then open the PDF Viewer tab. Ask one question — it goes to all selected devices in parallel, each with citations. This is the fastest way to compare and contrast devices: training data, PCCP scope, how they handled adding new scanners, and so on.
What does the side-by-side PDF viewer mode do?
Select multiple devices, open the PDF viewer tab, and ask one question (e.g., "Describe the training data"). It queries all selected devices simultaneously with citations, so you can compare and contrast quickly.
6. Collections
With rows selected, go to the Collections tab and create a labeled collection (e.g., "Cobb Angle Project"). Reload that selection any time — before a client call, pull up the collection and ask questions across all of its devices at once.
How do you save a set of selected devices for later use?
Select the rows, go to the Collections tab, and create a labeled collection (e.g., "Cobb Angle Project"). You can reload the selection anytime and carry it into the PDF viewer and other tabs that support selections.
7. Product codes and the regulations tree
Click a product code in the results to jump to it in the regulations tree — identification text, sibling product codes, and devices you can open in a PDF viewer on the right. Click a regulation number to see its identification, special controls, and related product codes. You can also search by product code or regulation number at the top of the tree. Always read the special controls if any exist for your device — it broadens your search and sharpens pre-kickoff research.
What can you do from the regulations tree view?
Browse product codes and regulation numbers, read the identification text and special controls, browse sibling product codes, open device PDFs on the right, and search by product code or regulation number at the top of the tree.
8. Chart view
Click Show Chart and segment by regulation number (or product code) to see which regulations dominate your result set. Clicking a regulation takes you into the regulations tree. Great for spotting that most matches are, say, hardware laparoscopic devices — a cue to go back and filter.
How do you see which regulations dominate a search result set?
Click "Show Chart" and segment by Regulation Number. Clicking a regulation takes you to the regulations tree.
9. The predicate graph
Open the Predicates tab for a family-tree view of predicate relationships. Click a node to trace its parents and children; selections from search carry over pre-selected. Commonly predicated devices are worth reading — a lot of people predicated them for a reason. The visual lineage is also handy on client calls, e.g. to show how a predicate family evolved and justify why your predicate still holds.
In the predicate graph, why are commonly predicated devices worth reading?
A lot of people predicated them for a reason. Clicking a node traces parents and children, and selections from search carry over pre-selected.
10. Embeddings: the galaxy map
The Embeddings tab plots every matching document in a 2-D "galaxy map" where semantically similar devices cluster together. Hover or click clusters to explore, and let AI label the clusters for you. Embeddings beat product codes for grouping: two devices can carry different product codes (LLZ vs. QIH) yet do the same thing — the embedding captures the meaning of the intended use and device story. This is also exactly how retrieval-augmented generation (RAG) works under the hood, and it makes a great visual on client calls.
Try it yourself
Head to the search page and work through a few of these AI/ML fuzzy searches to build intuition: perivascular fat on CT · aortic valve calcification opportunistic screening on noncontrast CT · breast cancer prediction on digital pathology slides · autism detection · gestational age prediction · a hearing aid that can also detect a pulse · foundation model based analysis of ECG · large language models · penetration test. Watch how the relevance scores, intended use, and AI Performance tables tell you when results stop being meaningful.