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The KKT device is to be used in the aid of management of chronic pain due to non-congenital defects. The device can be used as part of a series of steps in the patient. The procedure involves the use of diagnostic imaging that quantifies the misalignment of vertebrae. The treatment is then administered using the KKT device to deliver impulses at a precise vector. Spinalytics is a software application which facilitates treatment using the KKT device.

Spinalytics provides an interface to manage the patient information stored in a central database. Spinalytics facilitates measuring angles and distances of relevant sketal structures in a patient, by providing the practitioner with an interface to mark the position of these structures directly on digitized X-Rays. Spinalytics then calculates standard treatment protocol parameters which can be sent directly to the KKT device. Spinalytics is an optional accessory to the KKT device and does not change the intended use of the device.

Spinalytics Application is an optional software accessory to the KKT device which facilitates the calculation of the treatment parameters, which were previously calculated manually. Qualified personnel may generate, review, verify, approve, print and export the treatment plan prior to patient treatment. Spinalytics Application also communicates directly with the KKT Device to seamlessly enter the treatment parameters into the device. The clinicians may still enter their own parameters in the Spinalytics Application which meet their own treatment and clinical protocols, if they choose.

The Spinalytics Application software is installed on a computer near the KKT Device. It can be installed on any commercial grade PC that meets the minimum hardware and operating system requirements. The computer and the KKT Device communicate over a USB cable.

Here's a breakdown of the requested information based on the provided text, focusing on the acceptance criteria and the study that proves the device meets those criteria:

1. Table of Acceptance Criteria and Reported Device Performance

The provided text does not explicitly define a table of specific numerical acceptance criteria (e.g., minimum accuracy percentages, sensitivity, specificity) for the Spinalytics software's performance in measuring angles and distances. Instead, the acceptance is broadly stated in terms of meeting software specifications and passing validation.

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

• Sample Size for Test Set: The document does not specify a numerical sample size for the test set used in the software verification and validation. It broadly mentions "specific patient/X-ray" data without quantifying the number of patients or X-rays.
• Data Provenance: Not explicitly stated. The nature of the device (measuring angles/distances on X-rays) suggests the data would be X-ray images, but their origin (country, retrospective/prospective collection) is not mentioned.

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

The document does not explicitly state the number of experts used or their qualifications for establishing ground truth for the test set. It mentions that the software facilitates measurements that were "previously calculated manually" or information "inputted by the physician," but it doesn't describe an expert-led ground truth establishment process for the validation.

4. Adjudication Method for the Test Set

The document does not describe any formal adjudication method (e.g., 2+1, 3+1) used for the test set. The focus is on software verification and validation against design specifications and calculations.

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

No, a Multi-Reader Multi-Case (MRMC) comparative effectiveness study comparing human readers with and without AI assistance was not reported or performed. The document states: "There was no human clinical testing required to support the medical device as the indications for use is equivalent to the predicate device."

6. Standalone (Algorithm Only Without Human-in-the-Loop Performance) Study

The evaluation described is essentially a standalone (algorithm only) performance study, focusing on the software's ability to accurately calculate parameters based on user input. The software "facilitates measuring angles and distances" by "providing the practitioner with an interface to mark the position of these structures directly on digitized X-Rays." This means the algorithm's performance is on the calculation after a human marks the points. The validation was conducted to "verify data calculations" and ensure "correct information for a specific patient/X-ray" based on these calculations.

7. Type of Ground Truth Used

The ground truth for the device's performance appears to be expert-defined manual calculations/measurements and established software design specifications. The software is validated to generate "correct information" and "verify data calculations," implying comparison to what would be considered correct through manual analysis or pre-defined rules. The text mentions that the software automates calculations that were "previously calculated manually."

8. Sample Size for the Training Set

The document does not provide any information about a training set or its sample size. This is typical for a rule-based or calculation-based software accessory that does not employ machine learning models requiring a specific training phase.

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

Since no training set is mentioned (as the software appears to be calculation-based rather than machine learning), this question is not applicable.

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Using 3D data and models obtained with sterEOS workstation, spineEOS software is indicated for assisting healthcare professionals in viewing, measuring images as well as in preoperative planning of spine surgeries. The device includes tools for measuring spine anatomical components for placement of surgical implants. Clinical judgment and experience are required to properly use the software online.

spineEOS 1.0 allows surgeons to perform preoperative surgical planning of spine surgeries in case of Adolescent Idiopathic Scoliosis (AIS) or deformative spine. The software provides surgical tools for the correction of the curvature, for the placement of cages and for the achievement of osteotomies. The images displayed are x-rays from EOS System (K152788) and 3D model of the spine from sterEOS Workstation (K141137). spineEOS also displays preoperative parameters compared with reference values and updated values of parameters after planning. spineEOS is accessible on any computer via ONEFIT Management System (Class I device - Product code LMD - 510(k) Exempt) that provides a secure interface and storage through authentication mechanisms.

The FDA 510(k) summary for spineEOS provides some information regarding its performance data, but it does not contain a detailed study with acceptance criteria, specific reported device performance metrics, sample sizes, or information about experts and ground truth as requested.

The document primarily focuses on establishing substantial equivalence to a predicate device (Surgimap 2.0) by comparing intended use, indications, and technological characteristics.

Here's an analysis of what is available and what is missing from the provided text, structured according to your request:

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

• Missing from the document. The document states: "Software verification and validation testing were conducted and documentation was provided as recommended by FDA's Guidance for Industry and FDA Staff, 'Guidance for the Content of Premarket Submissions for Software Contained in Medical Devices'." However, specific acceptance criteria or detailed results of these tests (e.g., accuracy of measurements, success rate of planning tools) are not provided in this 510(k) summary.

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

• Missing from the document. The summary mentions "Software verification and validation testing," but does not specify the sample size of any test set or the provenance of the data used for such testing.

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)

• Missing from the document. There is no mention of experts, ground truth establishment, or their qualifications for any validation testing.

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

• Missing from the document. No information about adjudication methods for a test set is provided.

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

• Missing from the document. The document makes no mention of a multi-reader multi-case (MRMC) comparative effectiveness study. The focus is on demonstrating equivalence to the predicate device's existing functionality rather than quantifying human performance improvements.

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

• Implied, but not detailed. The "Software verification and validation testing" would typically involve standalone performance testing of the algorithms and software functionalities. However, the specifics of these tests and their results are not detailed. The spineEOS is described as "assisting healthcare professionals," implying it's a human-in-the-loop device, but standalone testing of its components would be part of standard V&V. Again, no specific results are provided.

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

• Missing from the document. As no specific performance study is detailed, the type of ground truth used is not mentioned.

8. The sample size for the training set

• N/A (or not explicitly stated as a "training set"). The spineEOS is a software for viewing, measuring, and planning based on existing 3D data and models (from sterEOS workstation). It's not described as a machine learning device that requires a distinct "training set" in the sense of a deep learning model. Its validation would focus on the accuracy of its measurements and the functionality of its planning tools against known standards or expert opinion, not on learning from a dataset.

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

• N/A. Since a classical machine learning "training set" is not explicitly mentioned or implied for this type of device, the method for establishing its ground truth is not applicable in that context.

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The ONEFIT Hip Planner software is indicated for assisting healthcare professionals in preoperative planning of hip replacement surgery. The software allows for overlaying of 3D/2D implant models on radiological images and 3D reconstruction of bone, and includes tools for performing measurements on the image and 3D model of bones and for selecting and positioning the implant model. Clinical judgments and experience are required to properly use the software.

The ONEFIT Hip Planner software allows surgeons to perform pre-operative surgical planning for hip replacement. The program features an extensive regularly updated library of digital 3D models of implants form leading implant manufacturers. It allows the overlay of the 3D/2D implant models on the radiological images and on the 3D reconstruction and permits the selection of appropriate size and position of implant. ONEFIT Hip Planner is accessible on any computer via ONEFIT Management System that provides secure interface through authentication mechanisms, web accessible authentication servers and access for authorized users through secure protocols to web server.

The provided document is a 510(k) summary for the ONEFIT Hip Planner, which is a pre-operative planning software for hip replacement surgery. It establishes substantial equivalence to a predicate device, TraumaCAD Release 2.0 (K073714). The performance data section in this document is very brief and does not contain the detailed information requested in your prompt.

Specifically, the document states:

• "Software verification and validation testing were conducted and documentation was provided as recommended by FDA's Guidance for Industry and FDA Staff, 'Guidance for the Content of Premarket Submissions for Software Contained in Medical Devices.'"

This statement indicates that testing was performed, but it does not provide any specific details regarding:

1. A table of acceptance criteria and the reported device performance.
2. Sample size used for the test set and data provenance.
3. Number of experts used to establish ground truth and their qualifications.
4. Adjudication method.
5. Whether an MRMC comparative effectiveness study was done, or any effect size for human readers with and without AI assistance.
6. Whether a standalone performance study was done.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.).
8. The sample size for the training set.
9. How the ground truth for the training set was established.

Therefore, based solely on the provided text, it is not possible to answer your questions in detail. The document confirms that some performance data demonstrations were done to support the claim of substantial equivalence to the predicate device, but the specifics of these studies are not part of this 510(k) summary. Further information would typically be found in the full 510(k) submission, which is not included here.

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