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Ikshana is a software device to display medical images. It includes functions for image review, image manipulation, measurements, and 3D visualization.

Medical images may only be interpreted using an FDA-cleared display monitor that meets technical specifications that are reviewed and accepted by the FDA.

Ikshana is intended to be used as an adjunct to the interpretation of images performed using diagnostic imaging systems and is not intended for primary diagnosis. Display monitors used for reading medical images for diagnostic purposes must be FDA-approved radiology monitors.

Ikshana software is indicated for use by qualified healthcare professionals, including, but not restricted to, radiologists, non-radiology specialists, physicians, and technologists.

When accessing the Ikshana software from a wireless stereoscopic head-mounted display (HMD) or mobile device, the images viewed are for informational purposes only and are not intended for diagnostic use.

Ikshana is a stand-alone modular software platform to be used by clinicians for the visualization of medical images in 3D to allow for surgical planning activities. The device takes 2D medical images and creates accurate 3D representations that clinicians can then view on a stereoscopic display. This modular package is used to

• · Load patient CT/MR DICOM data
• . View DICOM data using a traditional computer monitor or in Augmented Reality (AR) using a head-mounted display, HMD (Microsoft HoloLens 2).

The provided document describes the acceptance criteria and the study conducted for the Ikshana device, particularly focusing on its measurement and segmentation capabilities.

1. Table of Acceptance Criteria and Reported Device Performance:

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

• Measurement Study: A combination of orthopedic and maxillofacial models was used. The specific number of cases for the test set is not explicitly stated, but the study evaluated "multiple users."
• Segmentation Study: 60 trials were conducted using a combination of cardiovascular, orthopedic, and maxillofacial models. The specific number of cases is not explicitly stated beyond "60 trials."
• Data Provenance: Not specified in the provided text (e.g., country of origin or whether it was retrospective/prospective).

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

• Segmentation Study: The results were "validated by subject matter experts." The specific number and qualifications of these experts are not mentioned.
• Measurement Study: The ground truth for the measurement study seems to be derived from a comparison with the reference device, Medical Mimics, which implies its measurements are considered a reference standard, rather than expert consensus on individual cases.

4. Adjudication Method for the Test Set:

• The document does not explicitly describe an adjudication method like 2+1 or 3+1. For the segmentation study, it states results were "validated by subject matter experts," which suggests some form of expert review, but the specific process is not detailed. For the measurement study, the comparison is directly with the reference device's measurements.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done:

• No, a multi-reader multi-case (MRMC) comparative effectiveness study was not explicitly described for assessing the improvement of human readers with AI assistance. The studies focused on the performance of the device itself (measurement and segmentation accuracy/equivalence).

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

• Yes, the performance studies described (Measurement Study and Segmentation Study) appear to be standalone evaluations of the Ikshana software's capabilities. The measurement study compared Ikshana's measurements to another device, and the segmentation study compared Ikshana's segmentation models to a reference device, with expert validation. This assesses the algorithm's performance directly.

7. The Type of Ground Truth Used:

• Measurement Study: The ground truth for the measurement study appears to be established through measurements obtained using the referenced predicate device, Mimics Medical. The study aimed to show "equivalence" with the predicate, implying the predicate's measurements serve as the reference.
• Segmentation Study: The ground truth for the segmentation study was established by comparing Ikshana's segmentation models with those from the previously cleared reference device, Mimics Medical (K183105), and these results were "validated by subject matter experts." This indicates a hybrid approach, using a cleared device as a primary reference and expert review for validation.

8. The Sample Size for the Training Set:

• The document does not provide information about the sample size used for the training set. The focus is on the performance evaluation of the final device.

9. 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 details about the training process are not included.

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Fine Osteotomy™ is a system intended for open- and closed-wedge osteotomies, treatment of bone and joint deformities, fixation of fractures and malalignment caused by injury or disease, such as osteoarthritis, of the distal femur and proximal tibia.

Fine Osteotomy™ disposable instrumentation is intended to assist in pre-operative planning and/or the marking of bone and/or guiding of surgical instruments in non-acute, non-joint replacing osteotomies around the knee.

Fine OsteotomyTM is a patient-specific device.

Fine Osteotomy™ is a system for planning and performing osteotomies of the distal femur and proximal tibia and for stabilizing the bone with bone screws and a patientspecific bone plate that fits the patient's anatomy. Fine Osteotomy™ consists of patientspecific surgical planning and instrument guides designed from images of the patient's bones, a patient-specific bone plate designed from the patient's images, compression and/or locking bone screws, and class 1 reusable manual instruments. The bone plate is a patient-specific, single-use implant; the surgical planning and instrument guides are patient-specific, single-use. Fine Osteotomy™ is offered in three configurations: 1) as a system of patient specific implants and single use instruments for performing osteotomies and implanting hardware to stabilize the resection, 2) as patient specific single use instruments alone for performing osteotomies, and 3) as a patient specific bone plate and screws for stabilizing a bone resection or fracture.

When used as a system, Fine Osteotomy™ enables the surgeon to perform an osteotomy and stabilize the bone around the knee that matches the pre-surgical plan using the patient-specific cutting guides and bone plate. When the planning guides and resection instruments are used alone, Fine Osteotomy™ enables the surgeon to perform an osteotomy around the knee that matches the pre-surgical plan using the patientspecific cutting guides designed from the patient's CT images. When the bone plate and screws are used alone, Fine Osteotomy™ enables the surgeon to stabilize fractured or resected bone per the pre-surgical plan using the patient's CT images in design of the Bodycad plate and use of the bone models intra operatively to guide placement of the implants and alignment of bone. Fine Osteotomy is provided clean, non-sterile.

The purpose of this Special 510(k) Device Modification is to notify the FDA of changes and additions to the single use instruments and added software option for segmentation of images and creation of STL files of the bone models.

Materials: Wrought Titanium-6Aluminum-4Vanadium ELI Alloy (Ti6Al4V ELI: ASTM F136-13) for the bone plates and screws, additively manufactured Nylon-12 for patient specific, single use resection guides and models.

The provided text does not contain detailed information about specific acceptance criteria, a study that proves the device meets those criteria, or the performance of the device in relation to such criteria. The document is a 510(k) summary for a medical device (Fine Osteotomy™) being submitted to the FDA, asserting substantial equivalence to a previously cleared predicate device.

Here's what can be extracted and what information is missing based on your request:

Missing Information:

• A table of acceptance criteria and reported device performance.
• Sample size used for the test set and data provenance.
• Number of experts and their qualifications used to establish ground truth for the test set.
• Adjudication method for the test set.
• Whether a multi-reader multi-case (MRMC) comparative effectiveness study was done, and if so, the effect size of human reader improvement with AI assistance.
• Whether a standalone (algorithm only) performance study was done.
• Type of ground truth used (expert consensus, pathology, outcomes data, etc.).
• Sample size for the training set.
• How the ground truth for the training set was established.

Information provided in the document related to performance/validation:

The document mentions "Verification and validation (V&V) activities" but details are limited.

G. PERFORMANCE DATA

Verification and validation (V&V) activities included the following:

• Engineering analyses of updated and new single-use instruments demonstrating "no new risks and no new worst case." (This is a safety assessment, not a performance metric against acceptance criteria).
• Surgeon user evaluations demonstrating the new and updated instruments "to work as intended." (This is a qualitative statement, lacking specific metrics or criteria).
• Validation of the new software option for segmentation of patient image files and creation of STL files and virtual models "with similar resolution as previously 510(k) cleared Bodycad segmentation software." (This hints at a comparative resolution study, but no specific acceptance criteria or quantitative performance data are provided).

In summary, the provided FDA 510(k) summary focuses on establishing substantial equivalence for device modifications rather than detailing a comprehensive clinical or performance study with defined acceptance criteria and quantitative results, which would typically be included in a more extensive study report.

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SurgiCase Viewer is intended to be used as a software interface to assist in visualization of treatment options.

SurgiCase Viewer provides functionality to allow visualization of 3D data and to perform measurements on these 3D data, which should allow a clinician to evaluate and communicate about treatment options.

SurgiCase Viewer is intended for use by people active in the medical sector. When used to review and validate treatment options, SurgiCase Viewer is intended to be used in conjunction with other diagnostic tools and expert clinical judgment.

The SurgiCase Viewer can be used by a medical device/service manufacturer/provider or hospital department to visualize 3D data during the manufacturing process of the product/service to the end-user who is ordering the device/service. This allows the end-user to evaluate and provide feedback on proposals or intermediate steps in the manufacturing of the device or service.

The SurgiCase Viewer is to be integrated with an online Medical Device Data System which is used to process the medical device or service and which is responsible for case management, user management, authorization, authentication, etc.

The data visualized in the SurgiCase Viewer is controlled by the medical device manufacturer using the SurgiCase Viewer in its process. The Device manufacturer will create the 3D data to be visualized to the end-user and export it to one of the dedicated formats supported by the SurgiCase Viewer. Each of these formats describe the 3D data in STL format with additional meta-data on the 3D models. The SurgiCase Viewer does not alter the 3D data it imports and its functioning is independent of the specific medical indication/situation or product/service it is used for. It's the responsibility of the Medical device company using the SurgiCase Viewer to comply with the applicable medical device regulations.

The provided text describes the 510(k) submission for the "SurgiCase Viewer" device (K213684). However, it does not contain the specific details required to fully address all parts of your request related to acceptance criteria, test set specifics, expert ground truth establishment, MRMC studies, or training set details. This document primarily focuses on demonstrating substantial equivalence to a predicate device.

The study presented here is a non-clinical performance evaluation comparing the new SurgiCase Viewer with its predicate (K170419) and a secondary reference device (K183105).

Here's a breakdown of what can be extracted and what is missing, based on your questions:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly present a table of acceptance criteria with numerical performance metrics. Instead, it states that the device was validated to determine substantial equivalence based on:

• Intended Use: "Both the subject device as well as the predicate device have the same intended use; They are both intended to be used as a software interface to assist in visualization and communication of treatment options."
• Device Functionality: The new device was compared to the predicate in terms of features like 3D view navigation, visualization options, measuring, and annotations. For new functionalities (medical image visualization, VR visualization), it states "The abovementioned technological differences do not impact the safety and effectiveness of the subject device for the proposed intended use as is demonstrated by the verification and validation plan."
• Medical Images Functionality (compared to Mimics Medical K183105): "Both functionality produce the same results in: Contrast adjustments, Interactive image reslicing, 3D contour overlay on images."
• Measurement functionality: "Measurement functionality on images was compared with already existing functionality on the 3D models and shown to provide correct results both on images and 3D."

2. Sample size used for the test set and the data provenance:

• Sample Size: Not explicitly stated. The document refers to "verification and validation" and "performance testing" but does not provide details on the number of cases or images used in these tests.
• Data Provenance: Not explicitly stated (e.g., country of origin). It refers to "medical images functionality" and "3D models" but doesn't specify if these were from retrospective patient data, simulated data, etc. The study is described as "non-clinical testing."

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:

• Experts: Not explicitly stated. The validation involved "end-users," but their specific number, roles, or qualifications are not provided.
• Ground Truth Establishment: Not explicitly detailed. The comparison against the predicate and reference device functionalities implies that their established performance served as a form of "ground truth" for the new device's functions.

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

• Not explicitly stated. There is no mention of a formal reader adjudication process.

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:

• No MRMC study described. This submission focuses on the device's substantial equivalence in functionality and safety, not on human reader performance improvement with AI assistance. The device's stated indication is "to assist in visualization of treatment options," implying a tool for clinicians, but not an AI-driven diagnostic aid that would typically undergo MRMC studies.

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

• The context suggests a standalone functional assessment of the software's capabilities (e.g., whether it correctly performs contrast adjustments, measurement calculations, etc.) in comparison to the predicate and reference device. It's not an AI algorithm with a distinct "performance" metric like sensitivity/specificity, but rather a functional software application.

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

• For the functional comparison: The "ground truth" seems to be the established, correct functioning of the predicate and reference devices for equivalent features, and the defined requirements for new features. For instance, if the Mimics Medical device correctly performs "contrast adjustments," the SurgiCase Viewer needs to produce the "same results." For measurements, it needs to provide "correct results." This isn't a traditional clinical ground truth like pathology for a diagnostic AI.

8. The sample size for the training set:

• Not applicable / Not mentioned. This device description does not indicate the use of machine learning or AI models that require a "training set" in the conventional sense. It's described as a software interface for visualization and measurements.

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

• Not applicable. (See point 8).

In summary, the provided document demonstrates that the SurgiCase Viewer is substantially equivalent to existing cleared devices based on a functional and software validation process. It assures that new functionalities do not negatively impact safety or effectiveness and that shared functionalities perform comparably. However, it does not detail the type of rigorous clinical performance study (e.g., with patient data, expert readers, and quantitative statistical metrics) that would be common for AI/ML-driven diagnostic devices.

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