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MyAblation Guide is a software application for image processing, 2D/3D visualization, and comparison of medical images imported from multiple imaging modalities.

The software is controlled by the end user interface on a workstation with DICOM connectivity or as an integrated version on a Siemens CT scanner workstation.

The application is used to assist in the preparation and performance of ablative procedures, including of ablation targets, virtual ablation probe placement and contouring of ablated areas, as well as supporting the User in their assessment of the treatment. The application can only be used by trained Users.

The software is not intended for diagnosis and is not intended to predict ablation volumes or predict ablation success.

myAblation Guide is a software medical device that is used in the context of percutaneous ablative procedures with straight instruments. It is used by clinical professionals in a hospital premise; it can be either deployed on compatible CT scanners or a computer workstation.

The application is operated by medical professionals such as Interventional Radiologists and medical technologists with current license and/or certification as required by regional authority. myAblation Guide allows operating functions in an arbitrary sequence. In addition, it includes a structured sequence of steps for ease of utility.

The application supports anatomical datasets from CT, MR, CBCT, as well as PET/CT.

The application includes means and functionalities to support in:

· Multimodality viewing and contouring of anatomical, and multi-parametric images such as CT, CBCT, PET/CT, MRI

· Multiplanar reconstruction (MPR) thin/thick, minimum intensity projection (MIP), volume rendering technique (VRT)

· Freehand and semi-automatic contouring of regions-of-interest on any orientation including oblique

• Manual and semi-automatic registration using rigid and deformable registration
• · Expansion of created contour structures to visualize a safety margin

· Functionality to support the user in creating virtual ablation needle paths and associated virtual ablation zones derived from manufacturer data

• · Export of virtual needle paths in the Dicom SSO format
• · Supports the user in comparing, contouring, and ablation needle planning based on datasets acquired with different imaging modalities
• Supports multimodality image fusion
• · Supports user's procedure flow via a task stepper

Thermal ablation cannot be triggered from myAblation Guide.

The provided text details the 510(k) submission for the myAblation Guide (VB80A) device. It includes information on non-clinical testing performed to demonstrate the device meets established design criteria.

Here's an organized breakdown of the acceptance criteria and study proving the device meets them, based on the provided text:

Acceptance Criteria and Reported Device Performance

Note on Acceptance Criteria: The document implies the Moltz et al. study's Dice coefficient of 0.82 on liver metastases as a benchmark, stating "the algorithm effectively demonstrated the segmentation of both hyperdense and hypodense lesions... With a Dice coefficient (Dice similarity index) of 0.82". For the internal study, the reported Dice scores and sensitivities appear to be the performance metrics being presented to demonstrate functionality rather than explicitly stated "acceptance criteria" that must be met. However, for the purpose of this exercise, we can infer that these reported values demonstrate the device's acceptable performance.

Study Details

1. Sample Size Used for the Test Set and Data Provenance:

   • Lesion Segmentation (Moltz et al. study): 5 different datasets comprising 10 liver metastases. Data provenance is not specified (e.g., country of origin, retrospective/prospective).
   • Lesion Segmentation (Internal Study): 50 patients. Data provenance is not specified (e.g., country of origin, retrospective/prospective), but it is referred to as an "internal study," suggesting it was conducted by the manufacturer or an affiliated entity.
   • Ablation Zone Segmentation: 33 patients with 41 available ablation zones. Data provenance is not specified.

2. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications of Those Experts:

   • The document does not specify the number of experts or their qualifications for establishing ground truth for the test sets in either the Moltz et al. study or the internal studies.

3. Adjudication Method for the Test Set:

   • The document does not provide details on any adjudication method (e.g., 2+1, 3+1, none) used for the test sets. It only mentions the comparison of algorithm performance against a reference.

4. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study:

   • No MRMC comparative effectiveness study was done. The document explicitly states: "No clinical studies were carried out for the subject device, and therefore, no such clinical data is provided within this submission." The study focuses on "algorithm's performance" and "semi-automatic liver ablation zone segmentation."

5. Standalone (Algorithm Only Without Human-in-the-Loop) Performance:

   • Yes, the performance data presented (Dice scores, Sensitivity) are indicative of standalone (algorithm only) performance for the semi-automatic segmentation algorithms. The phrasing "To assess the algorithm's performance" and "The internal analysis of the lesion segmentation" supports this. The device is a "software application for image processing," and the described tests evaluate the segmentation algorithms within this software.

6. Type of Ground Truth Used:

   • The document does not explicitly state the type of ground truth used (e.g., expert consensus, pathology, outcomes data). However, for segmentation tasks, ground truth is typically established by expert manual annotation or referencing pathology for pathological confirmation. Given the context of "assessed" cases and "segmentation," it is highly probable that the ground truth was established by expert review/annotation of the medical images.

7. Sample Size for the Training Set:

   • The document does not specify the sample size for the training set. The provided information relates only to the test sets used for evaluating the semi-automatic segmentation algorithms.

8. How the Ground Truth for the Training Set Was Established:

   • The document does not provide information on how the ground truth for the training set was established, as the size and specifics of the training set are not mentioned.

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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.

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
• . 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.

Here's a summary of the acceptance criteria and study details for the Techsomed VisAble.IO device, based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

*MCD = Mean Corresponding Distance

Note on Segmentation and Registration Accuracy: The document explicitly states:

• "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."
• "Final accuracy of registration is dependent on user assessment and manual modification of the registration prior to acceptance, and not a VisAble.IO function."
  This suggests that while the algorithms perform well against the statistical metrics, the final clinical accuracy is attributed to the user.

2. Sample Sizes Used for the Test Set and Data Provenance

3. Number of Experts Used to Establish Ground Truth for the Test Set and Their Qualifications

The document does not explicitly state the "number of experts used to establish the ground truth for the test set" or their specific "qualifications." It generally refers to "performance data demonstrate that the VisAble.IO (V 1.4) is as safe and effective as the cleared VisAble.IO (K223693)," but does not detail the specific ground truth generation process for the reported performance metrics.

4. Adjudication Method for the Test Set

The document does not specify an adjudication method (e.g., 2+1, 3+1, none) for the test set.

5. If a Multi Reader Multi Case (MRMC) Comparative Effectiveness Study Was Done, and Effect Size

No MRMC comparative effectiveness study is mentioned in the provided text, nor is there any discussion of human reader improvement with or without AI assistance.

6. If a Standalone (Algorithm Only Without Human-in-the-Loop Performance) Was Done

Yes, the performance data presented in the table (DICE scores, MCD) are for the algorithms themselves, indicating a standalone performance evaluation. The document highlights that "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," and then presents the algorithmic validation results. However, it also clarifies that the final clinical accuracy of segmentations and registrations is dependent on user actions.

7. The Type of Ground Truth Used

The ground truth for the algorithmic performance (e.g., DICE scores for segmentation, MCD for registration) is implicitly expert-derived segmentation and registration. While the document doesn't explicitly detail the process, DICE scores and Mean Corresponding Distances are calculated by comparing algorithmic outputs to a pre-established "true" segmentation or correspondence, which in medical imaging is typically generated by human experts (e.g., radiologists, experienced technicians).

8. The Sample Size for the Training Set

• CT Processing - Liver Segmentation Algorithm: N = 1091 contrast-enhanced CT images
• CT Processing - Liver Vessel Segmentation Algorithm: N = 393 contrast-enhanced CT images
• MR Processing - Liver Segmentation AI algorithm: N = 418 MR images

9. How the Ground Truth for the Training Set Was Established

The document provides details on the characteristics of the training datasets but does not explicitly state how the ground truth for these training sets was established. It describes the data as "contrast-enhanced CT images taken for diagnostic reading" or "MR images taken for diagnostic reading," suggesting that these were real-world clinical images, but the manual annotation or expert review process for creating the ground truth for training is not described.

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Artemis along with the Needle Guide Attachment is used for image-guided interventional and diagnostic procedures of the prostate gland. It provides 2D and 3D visualization of Ultrasound (US) images and the ability to fuse and register these images with those from other imaging modalities such as Ultrasound, Magnetic Resonance, Computed Tomography, etc. It also provides the ability to display a simulated image of a tracked insertion tool such as a biopsy needle, guidewire or probe on a computer monitor screen that shows images of the target organ and the projected future path of the interventional instrument taking into account patient movement. The software also provides a virtual grid on the live ultrasound for performing systematic sampling of the target organ. Other software features include patient data management, multi-planar reconstruction, segmentation, image measurements, 2D/3D image registration, reporting, and pathology management.

Artemis is intended for treatment planning and guidance for clinical, interventional and/or diagnostic procedures. The device is intended to be used in interventional and diagnostic procedures in a clinical setting. Example procedures include, but are not limited to image fusion for diagnostic clinical examinations and procedures, soft tissue ablations and placement of fiducial markers. Artemis is also intended to be used for patients in active surveillance to keep track of previous procedures information and outcomes.

Artemis Cryo Treatment Planning module is an add on to the existing Artemis software that allows physicians to prepare for cryo treatment planning based on positive pathology cores obtained during Artemis guided biopsies and registration results with other imaging modalities such as MRI, CT. The module allows accurate placement of cryo probes on targets, 3D tracking, real-time feedback on extend of cryo ice formation. The technology provided by Artemis generates ice models based on the specifications provided by the cryo device manufacturers and displays the models on the live ultrasound to provide guidance to the users during the procedure.

The module also allows outlining or segmenting other organs that surround the prostate. Organs include bladder and urethra.

Artemis is designed to display the 2-D live video received from commercially available ultrasound machines and use this 2-D video to reconstruct a 3-D ultrasound image. The system has been designed to work with the clinicians' existing ultrasound machine, probe, commercially available biopsy needle guide, needle gun combination, and cryoablation systems. Additional software features include patient data management, multi-planar reconstruction, segmentation, image measurement, reporting and 3-D image registration.

Artemis is comprised of a mechanical assembly that holds the ultrasound probe and tracks probe position. The mechanical tracker is connected to a PC-based workstation containing a video digitizing card and running the image processing software. Control of the ultrasound probe and ultrasound system is done manually by the physician, just as it would be in the absence of Artemis. However, by tracking the position and orientation of the ultrasound probe while capturing the video image, the workstation is able to reconstruct and display a 3-D image and 3-D rendered surface model of the prostate.

The reconstructed 3-D image can be further processed to perform various measurements including volume estimation, which can be examined for abnormalities by a physician. Patient information, notes, and images may be stored for future retrieval, and locations for biopsies may be selected by the physician. The system also allows previously acquired 3-D models to be recalled, aligned, or registered to the current 3-D model of the prostate, which is especially useful for patients under active surveillance.

The physician may attach a commercially available biopsy needle guide compatible to the ultrasound probe and use the probe and needle to perform tissue biopsy and or cryoablation. Whenever the ultrasound machine is turned on by the physician, the live 2-D ultrasound image is displayed on the screen of Artemis during the procedure. As the ultrasound probe with attached needle guide is maneuvered by the physician, the position and orientation of the probe with respect to the organ is tracked. Artemis is able to add, display and edit loaded plans for the procedure as well as provide the probe position and needle trajectory relative to the 3-D image and 3-D rendered surface model of the prostate.

In addition to standard transrectal needle guidance procedures, Artemis also supports transperineal needle guidance by mounting a Needle Guide Attachment (NGA). A commercially available needle guide compatible with the NGA is used. This NGA will be used for both biopsy and cryo needles. The NGA provides additional data to track the needle direction angle. When using transperineal mode, the procedure planning, segmentation, registration and navigation are performed in the same way as the standard transrectal procedure. The only difference lies in how the needle guide needs to be moved to target the different planned locations. For the transrectal procedure, the needle guide is always attached to the probe. Therefore moving the probe moves the needle guide. In transperineal needle guidance procedures the needle is not attached to the probe. Therefore the NGA needs to be moved to move the needle guide. Artemis highlights the closed target to the current needle guide position.

Artemis offers the physician additional 3-D information for assessing prostate abnormalities, planning and implementing biopsy procedures. The additional image processing features are generated with minimal changes to previous Ultrasound probe based procedures, and the physician always has access to the live 2-D ultrasound image during prostate assessment or biopsy procedure. The device also provides automated reports with information and pictures from the procedure.

The provided text describes the acceptance criteria and the study proving the device meets these criteria for the Artemis medical imaging system.

Here's a breakdown of the requested information based on the text:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly present a table of predetermined acceptance criteria with corresponding performance results. Instead, it broadly states that "Nonclinical and performance testing results are provided in the 510(k) and demonstrate that the predetermined acceptance criteria are met." It mentions that "Measurement validation using, phantoms, clinical CT, and MRI images were used to show that Artemis performs as well as or better than the predicate devices and furthermore shows that Artemis was safe and effective."

Below is a table summarizing the types of tests and the overall conclusion regarding acceptance, as the specific numerical criteria and results are not detailed in this public summary.

2. Sample Size Used for the Test Set and Data Provenance

• Sample Size for Test Set: The document does not specify the exact sample size (number of phantoms or clinical images) used for the measurement validation or other performance tests. It states "Measurement validation using, phantoms, clinical CT, and MRI images were used."
• Data Provenance: The provenance (e.g., country of origin, retrospective or prospective) of the clinical CT and MRI images used for measurement validation is not specified in the provided text. The testing appears to be non-clinical and performed at the manufacturer's facility ("at the manufacturer's facility and has passed all in-house testing criteria").

3. Number of Experts and Qualifications for Ground Truth

The document does not specify the number of experts used to establish ground truth or their qualifications. The testing described is "nonclinical and performance testing" and "measurement validation," suggesting a focus on technical accuracy rather than human interpretation studies.

4. Adjudication Method for the Test Set

The document does not mention any adjudication method for establishing ground truth, such as 2+1 or 3+1.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

There is no mention of an MRMC comparative effectiveness study being performed, nor any effect size regarding how human readers might improve with AI vs. without AI assistance. The study described focuses on the device's technical performance and comparison to predicate devices, not on human-in-the-loop performance.

6. Standalone (Algorithm Only) Performance

The testing primarily focuses on the device's technical performance, including "measurement validation." This strongly implies that a standalone (algorithm only) performance evaluation was conducted to ensure the device's core functionalities, such as image reconstruction, segmentation, registration, and ice model generation, meet design specifications independently. The statement "Artemis has been assessed and tested at the manufacturer's facility and has passed all in-house testing criteria including validating design, function and specifications" supports this. Specific performance metrics (e.g., accuracy, precision) for these standalone functions are not provided, only a general statement of meeting acceptance criteria.

7. Type of Ground Truth Used

The type of ground truth used for performance validation included:

• Phantoms: For measurement validation.
• Clinical CT images: For measurement validation.
• Clinical MRI images: For measurement validation.

The basis for the "ground truth" on these phantoms and clinical images (e.g., known measurements for phantoms, expertly annotated features on clinical images) is implied but not explicitly detailed.

8. Sample Size for the Training Set

The document does not provide information regarding the sample size used for any potential training set. The descriptions of "nonclinical and performance testing" and "measurement validation" focus on evaluation (test set) rather than model training. It's possible that a training set was used for specific software features involving image processing or reconstruction, but this is not mentioned.

9. How the Ground Truth for the Training Set Was Established

As no information about a training set is provided, there is also no information on how its ground truth might have been established.

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Ablation-fit is a medical imaging application available for use with liver ablation procedures.

Ablation-fit is used to assist physicians in planning, permitting the graphical display of anatomy involved in the procedure, ablation targets and ablation needle placement.

Ablation-fit is used to assist physicians in confirming ablation zones during follow-up.

The software is not intended for diagnosis. The software is not intended to predict ablation volumes or predict ablation success.

Ablation-fit is a stand-alone medical imaging software that integrates Reconstruction, Segmentation, Registration and Visualization algorithms into a user interface to support physicians during liver ablation treatments planning and follow-up.

Ablation-fit allows to perform the entire workflow from DICOM (Digital Imaging and COmmunications in Medicine) images to 3D reconstruction of volume of interests, ablation probe placement and treatment outcome verification.

Specifically, Ablation-fit main functionalities include:

• Image loading from different supports (including PACS),
• DICOM images handling and visualization in axial, sagittal, coronal views,
• image segmentation,
• tools for manual edit of segmentations.
• 3D visualization,
• virtualization of ablation probe placement,
• pre- and post-treatment images registration.

The software permits segmentation and 3D reconstruction of volumes of interest. The software contours all of this anatomic information not only in axial, sagittal, and coronal planes for 2D visualization, but also three-dimensionally. Every computed segmentation can be manually modified in the 2D axial visualization and consequently the three-dimensional mapping of the scan changes accordingly.

Ablation-fit let the user simulate the virtual needle insertion and shows the desired ellipsoid of ablation.

Once the ablation procedure has been performed, pre- and post-treatment scans are registered. Consequently, the software can verify whether the ablation zones entirely surrounds the lesion and the safety margin.

Here's a breakdown of the acceptance criteria and the study details for the Ablation-fit device, based on the provided FDA 510(k) summary:

Acceptance Criteria and Device Performance

The document doesn't present a direct table of specific acceptance criteria with corresponding performance metrics in a single, clear format. However, it states that "software testing using retrospective image data of ablation procedures" was conducted to evaluate "the accuracy of Ablation-fit in assessing the outcome of lesion percutaneous thermal ablations and the accuracy of the automatically performed segmentations." It also mentions "Bench tests that compare the output of all segmentation and registration processes with ground truth annotated by qualified experts show that the algorithms performed as expected."

Based on these statements, we can infer the following general acceptance criteria and reported performance:

Study Details

Here's the breakdown of the study information:

2. Sample Size Used for the Test Set and Data Provenance

• Sample Size for Test Set: The exact number of cases or images in the "retrospective image data of ablation procedures" used for software testing is not specified in this document.
• Data Provenance: The data used for testing was "retrospective image data of ablation procedures." The country of origin for the data is not specified.

3. Number of Experts Used to Establish the Ground Truth for the Test Set and Their Qualifications

• Number of Experts: "Qualified experts" were used to annotate ground truth for segmentation and registration processes. In addition, "three radiologists" performed testing for semi-automatic functionalities to account for user interaction variability.
• Qualifications of Experts: The specific qualifications (e.g., years of experience, subspecialty) of the "qualified experts" and the "three radiologists" are not specified beyond their profession.

4. Adjudication Method for the Test Set

• The document implies that ground truth was "annotated by qualified experts." For the "semi-automatic functionalities," testing involved "three radiologists" to account for user variability. There is no explicit mention of an adjudication method (e.g., 2+1, 3+1 consensus) for establishing the ground truth, particularly expert consensus for discrepancies. It's possible annotation by a single "qualified expert" was considered ground truth, or an unstated consensus method was used.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done

• No, an MRMC comparative effectiveness study was not explicitly mentioned or described. The testing involved "three radiologists" testing "semi-automatic functionalities to account for variability resulting from user interaction," but this appears to be part of validating the device's interaction and robustness, not a comparative effectiveness study of human readers with vs. without AI assistance.
• Effect Size of Human Readers Improvement with AI vs. without AI assistance: This information is not provided as an MRMC study was not described.

6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done

• Yes, a standalone performance assessment was conducted for some aspects. The document states: "Bench tests that compare the output of all segmentation and registration processes with ground truth annotated by qualified experts show that the algorithms performed as expected." This implies an evaluation of the algorithm's performance in these tasks independent of a human user's interaction in the final output generation.
• Additionally, "the accuracy of the automatically performed segmentations" was evaluated, which is a standalone assessment.

7. The Type of Ground Truth Used

• The primary type of ground truth used was expert consensus / expert annotation. Specifically, "ground truth annotated by qualified experts" was used for segmentation and registration processes.

8. The Sample Size for the Training Set

• The document does not specify the sample size used for the training set.

9. How the Ground Truth for the Training Set Was Established

• The document does not explicitly state how the ground truth for the training set was established. It only discusses the ground truth for the "test set" or "bench tests."

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VisAble.IO is a Computed Tomography (CT) 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 scanners and facility PACS systems for display and processing during liver ablation procedures.

VisAble.IO is used to assist physicians in planning liver 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.

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
• 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 Seqmentation, 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), 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 the user in order for them to evaluate the planned and post ablation zones. These include:

• Seamentation
• 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 ー Probe 15CM, 20CM; LK XT Probe 15CM, 20CM

For treatment confirmation (including seqmentation and registration), the software is compatible with all ablation devices as these functions are independent from probes/power settings.

The provided text describes the VisAble.IO device and its performance testing for FDA 510(k) clearance. Here's a breakdown of the requested information based on the document:

1. A table of acceptance criteria and the reported device performance

The document uses "Primary Performance Goal" as the acceptance criterion and "Primary Endpoint" as the reported device performance.

Note: The document states that segmentation tools provide manual and semi-automated segmentation, and post-processing. The clinical accuracy of segmentation is referred to as "a user operation and the clinical accuracy of segmentation is the responsibility of the user and not a VisAble.IO function." Similarly, for registration, it states "Final accuracy of registration is dependent on user assessment and manual modification of the registration prior to acceptance, and not a VisAble.IO function." This suggests that the reported performance metrics (DICE scores and MCD) likely reflect the algorithm's capability to provide good initial segmentations and registrations for user refinement.

2. Sample sizes used for the test set and the data provenance (e.g., country of origin of the data, retrospective or prospective)

The sample sizes for the test sets are provided in the table. The provenance for the training/validation datasets are described generally as:

• Liver Segmentation Algorithm Test Set Size: N=50
  • Provenance for training/validation (not explicitly test set data): 1091 contrast-enhanced CT images from arterial or venous phases.
  • Location of clinical sites: Germany, France, Turkey, Japan, Israel, Netherlands, Canada, USA, UK (38 clinical sites)
• Ablation Target Segmentation Test Set Size: N=59
• Ablation Zone Segmentation Test Set Size: N=59
• Liver Vessels Segmentation Test Set Size: N=100
  • Provenance for training/validation (not explicitly test set data): N=393 contrast-enhanced CT images from the portal-venous or late venous phases.
  • Location of clinical sites: Central Europe, North America, East Asia (36 clinical sites)
• PrePost Ablation Image Registration Test Set Size: N=46

The document doesn't explicitly state whether the test set data was retrospective or prospective. Given that it's performance data for a 510(k) submission, it is typically retrospective data collected for validation.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)

The document does not specify the number of experts used to establish the ground truth for the test set or their qualifications.

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set

The document does not specify the adjudication method used for the test set, nor does it explicitly mention a process of expert adjudication for the ground truth.

5. 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

The document does not mention a multi-reader multi-case (MRMC) comparative effectiveness study or any effect size related to human reader improvement with AI assistance. The study focuses on the standalone algorithmic performance.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done

Yes, the performance data presented (DICE scores and MCD) are for the standalone algorithmic performance. The text explicitly states that the "clinical accuracy of segmentation is the responsibility of the user and not a VisAble.IO function" and "final accuracy of registration is dependent on user assessment and manual modification... and not a VisAble.IO function," suggesting the provided metrics are for the initial algorithmic output prior to user intervention.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.)

The document does not explicitly state the type of ground truth used (e.g., expert consensus, pathology, etc.) for the segmentation and registration algorithms. It implies that the "Primary Performance Goal" was set for these algorithms, suggesting a pre-defined or expert-derived ground truth was used for comparison, but the methodology for establishing it is not detailed.

8. The sample size for the training set

The document provides the sample sizes for the training and model validation datasets as:

• Liver Segmentation Algorithm: 1091 contrast-enhanced CT images.
• Liver Vessel Segmentation Algorithm: N=393 contrast-enhanced CT images.
• The sample sizes for training of Ablation Target Segmentation, Ablation Zone Segmentation, and PrePost Ablation Image Registration algorithms are not explicitly stated in the provided text.

9. How the ground truth for the training set was established

The document does not explicitly describe how the ground truth for the training set was established. It only mentions the characteristics of the images used for training (e.g., contrast-enhanced CT, arterial/venous phases, age/sex distribution, location of clinical sites, imaging procedure).

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MIM software is used by trained medical professionals as a tool to aid in evaluation and information management of digital medical images. The medical image modalities include, but are not limited to, CT, MRI, CR, DX, MG, US, SPECT, PET and XA as supported by ACR/NEMA DICOM 3.0. MIM assists in the following indications:

· Receive, transmit, store, retrieve, display, print, and process medical images and DICOM objects.

· Create, display and print reports from medical images.

· Registration, fusion display, and review of medical images for diagnosis, treatment evaluation, and treatment planning.

· Evaluation of cardiac left ventricular function, including left ventricular end-diastolic volume, end-systolic volume, and ejection fraction.

· Localization and definition of objects such as tumors and normal tissues in medical images.

· Creation, transformation, and modification of contours for applications including, but not limited to, quantitative analysis, aiding adaptive therapy, transferring contours to radiation therapy treatment planning systems, and archiving contours for patient follow-up and management.

· Quantitative and statistical analysis of PE7/SPECT brain scans by comparing to other registered PET/SPECT brain scans.

· Planning and evaluation of permanent implant brachytherapy procedures (not including radioactive microspheres).

· Calculating absorbed radiation dose as a result of administering a radionuclide.

· Assist with the planning and evaluation procedures by providing visualization and analysis, including energy zone visualization through the placement of virtual ablation devices validated for inclusion in MIM-Ablation. The software is not intended to predict specific ablation zone volumes or predict ablation success.

When using device clinically, within the United States, the user should only use FDA approved radionly, If using with unapproved ones, this device should only be used for research purposes.

Lossy compressed mammographic images and digitized film screen images must not be reviewed for primary image interpretations. Images that are printed to film must be printed using a FDA-approved printer for the diagnosis of digital mammography images. Mammographic images must be viewed on a display system that has been cleared by the FDA for the diagnosis of digital mammography images. The software is not to be used for mammography CAD.

MIM - Ablation is a standalone software application that allows for the planning and evaluation of ablation procedures. This is achieved by utilizing the following functionality:

• . Manual and automatic tools for normal structure, target region, and ablation zone segmentation
• lmage re-slicing and reorientation orthogonally to a user-defined angle to give a . "probe's-eye view" image for planning
• Manual and constraint-driven placement of virtual ablation devices on medical . imaging in order to visualize the ablation energy zones.
• . The calculation of the percentage of designated structures that are covered by each energy zone during planning, as well as a calculation of the final ablation zone coverage after the ablation has been performed
• Multimodality image registration, including rigid and deformable fusion, for the . comparison of images taken at different times during the ablation planning and treatment administration
  MIM - Ablation is run on a dedicated workstation in the hospital healthcare environment and can be used with an 3D DICOM image. The software can be used on image data for any patient demographic that is undergoing ablation treatment with devices validated for inclusion in MIM - Ablation.

The acceptance criteria and study proving MIM-Ablation meets these criteria are detailed below, based on the provided FDA 510(k) summary.

MIM-Ablation Acceptance Criteria and Performance Study

The MIM-Ablation software, as described in the 510(k) summary, demonstrates its efficacy and safety through specific performance testing. The core functionality validated is the accurate representation and calculation of "energy zones" (simulated ablation zones) based on manufacturer specifications of validated ablation devices within the software.

1. Table of Acceptance Criteria and Reported Device Performance

• Percent difference ranged from -3.75% to 1.53%, falling within the manufacturer tolerance. |
  | Image Resolution Independence | Volume of imported 3D energy zone objects in MIM is independent of image resolution (0.5mm, 1.0mm, 1.5mm). | Percent Difference in Volume:
• At 0.5 mm: -1.65% to 0.29%
• At 1.0 mm: -0.87% to -0.6%
• At 1.5 mm: -0.70% to 0.00%.
  This demonstrates consistency across various resolutions. |
  | Contour Resolution Independence | Dimensions of imported 3D energy zone objects in MIM match manufacturer specifications, independent of contour resolution. | Percent Difference in Dimensions:
• At 0.25 mm: -1.43% to -0.43%
• At 0.5 mm: -1.16% to 0.00%
• At 1.0 mm: -2.15% to -0.38%.
  This indicates independence from contour resolution. |
  | Image Modality Independence | Dimensions of 3D energy zone objects in MIM match manufacturer specifications across four image modalities. | Percent Difference in Dimensions:
• Ranged from 0.64% to 0.89%.
  This highlights the minimal effect of image modality on contour dimensions. |
  | Percent Coverage Calculation | Accuracy of "Percent Coverage" statistic (volume of structure covered by energy zone) with one or multiple ablation probes. | Percent Difference in Calculation:
• With one ablation probe: 0.00% to 1.57%
• With two ablation probes: 0.00% to 0.19%.
  This validates the accuracy of the coverage calculation feature. |
  | HIFU Energy Zone Dimensions | Dimensions of the unique HIFU energy zone (3cm and 4cm transducer treatment heights, overlap) match manufacturer specifications. | Percent Error in Measurements (MIM vs. SonoBlate):
• Ranged from 0.00% to 6.00%.
  These measurements fell within the manufacturer tolerance, verifying consistency in HIFU dimensions. |
  | Constraint-Driven Planning | Constraint-driven planning functionality places energy zones that adhere to user-set constraints, and indicates when planning is not possible. | Verified Functionality:
• The work verified that energy zones adhere to constraints and that an "unattainable plan" is indicated when a scenario is not possible, ensuring appropriate targeting and preventing impossible planning. |

2. Sample Size Used for the Test Set and Data Provenance

The provided document does not specify the exact sample size for the test set in terms of an overall number of cases or images. Instead, the testing appears to be highly controlled and synthetic or semi-synthetic, focusing on the accuracy of internal calculations and representations based on input parameters (manufacturer specifications, different resolutions, different contour resolutions, multiple modalities, and various probe configurations).

• Data Provenance: The data provenance is primarily "internal" verification data, based on manufacturer specifications (user guides, marketing material) of the Varian V-Probes and SonaBlate HIFU system. This suggests a controlled environment, likely using simulated or canonical data derived from these specifications. The document does not explicitly state the country of origin of the data or whether it was retrospective or prospective clinical data. Given the "verification and validation testing" language and the precise percentage differences, it points towards rigorous technical and performance testing rather than a clinical study on patient data.

3. Number of Experts and Qualifications for Ground Truth

The document does not describe the establishment of ground truth through expert consensus for the performance testing. The ground truth for the device's calculations and representations of ablation zones is explicitly stated as the manufacturer specifications of the validated ablation devices (Varian V-Probes and SonaBlate HIFU system). This is a technical ground truth rather than a clinical one from human experts evaluating medical images.

4. Adjudication Method for the Test Set

No adjudication method is mentioned, as the ground truth is derived from manufacturer specifications rather than subjective expert interpretations requiring adjudication.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

No MRMC comparative effectiveness study was done. The study described focuses on the device's technical performance in accurately representing and calculating energy zones, not on its impact on human reader performance or the improvement of human readers with AI assistance.

6. Standalone Performance (Algorithm Only)

The testing described is primarily focused on the standalone performance of the algorithm in generating and calculating energy zones based on defined inputs (manufacturer specifications, different image/contour resolutions, etc.). It verifies the internal consistency and accuracy of the software's representations independent of a human operator, beyond the initial input parameters.

7. Type of Ground Truth Used

The ground truth used for this study is manufacturer specifications (from user guides and marketing material) of the validated ablation devices. This serves as the engineering/technical ground truth against which the software's generated energy zone dimensions and volumes are compared.

8. Sample Size for the Training Set

The document does not describe a "training set" in the context of a machine learning model that learns from data. MIM-Ablation's functionality, as described, appears to be based on predefined models and algorithms derived from the physical specifications of ablation devices, rather than a data-driven machine learning approach requiring a training set. The descriptions point to a rule-based or model-based system.

9. How Ground Truth for the Training Set Was Established

As no training set (for machine learning) is implied, there is no mention of how ground truth for a training set was established. The "ground truth" for the device's functionality is the engineering specifications of the ablation devices, which were used to "generate models and import into MIM-Ablation."

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