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The NSite Scoliosis Assessment App is intended as an adjunct tool for qualified healthcare professionals to provide deformity measurements and guide management recommendations based on a calculated Asymmetry Index for patients with or at risk for idiopathic scoliosis, which will yield an output of clinically significant scoliosis, which is defined as a Cobb Angle greater than 20 degrees.

NSite Medical leverages 3D scanning on a mobile device for scoliosis screening and monitoring. NSite's proprietary algorithm calculates the risk of having clinically significant scoliosis that may require treatment by a specialist.

The NSite Scoliosis Assessment App generates a 3D scan of the individual using a mobile device camera. Using the 3D scan, the application analyzes the asymmetry of the individual's back surface and calculates an Asymmetry Index (AI). The Asymmetry Index is a quantitative measure of the back asymmetry. The Asymmetry Index is then used to calculate a high/low risk stratification that a patient will have clinically significant scoliosis (defined as Cobb angle > 20 degrees) using a logistic regression model. This risk stratification, when considered in combination with the stated NSite Scoliosis Assessment App performance, is intended to provide health care providers with information that can be used for management recommendations. The model was developed using a database of patient Asymmetry Indexes with known Cobb angles.

The provided text describes the NSite Scoliosis Assessment App, an adjunct tool for qualified healthcare professionals to assess scoliosis risk, and its clinical study to demonstrate substantial equivalence to a predicate device.

Here's an analysis of the acceptance criteria and study proving device performance, based only on the provided text, as some details are not explicitly stated:

1. Table of Acceptance Criteria and Reported Device Performance

The document states: "All predefined acceptance criteria for the performance testing were met." However, the specific acceptance criteria (e.g., sensitivity, specificity thresholds) and the numerical results for the device's performance (e.g., actual sensitivity and specificity achieved) are not detailed in the provided text. The output is described as a "low or high risk of clinically significant scoliosis, which is defined as a Cobb Angle greater than 20 degrees."

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

• Test Set Sample Size: The document does not explicitly state the numerical sample size of the test set used in the clinical study. It mentions the study was performed using "adolescent patients spanning the age range where Adolescent Idiopathic Scoliosis (AIS) commonly presents and remains treatable" and "adolescents of gender and race at ratios where AIS is commonly observed."
• Data Provenance: The text does not specify the country of origin of the data. The study is described as a "clinical study," suggesting it was prospective, but this is not explicitly stated as retrospective or prospective.

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

The document does not specify the number of experts used to establish the ground truth for the test set or their qualifications. It mentions "radiograph" as the basis for the Cobb angle, implying radiologists were involved, but details are absent.

4. Adjudication Method for the Test Set

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

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

The document does not mention that a Multi-Reader Multi-Case (MRMC) comparative effectiveness study was done. Therefore, no effect size of human readers improving with AI vs. without AI assistance is provided. The app is intended as an "adjunct tool," implying human-in-the-loop, but a comparative effectiveness study is not detailed.

6. Standalone (Algorithm Only) Performance

The document does not explicitly state if a standalone (algorithm-only) performance study was conducted with specific metrics for that mode of operation. The primary intention is as an "adjunct tool" for healthcare professionals. The study "validated the accuracy of the predicated probability of major Cobb angle," which implies an algorithm output, but whether this was evaluated without human interaction or review is not clarified.

7. Type of Ground Truth Used

The ground truth used was:

• Cobb Angle obtained via radiograph: This is the primary stated ground truth for validating the accuracy of the device's "predicated probability of major Cobb angle." This typically implies expert consensus (e.g., radiologists) on these radiographic measurements.

8. Sample Size for the Training Set

The document does not state the specific sample size used for the training set. It mentions: "The model was developed using a database of patient Asymmetry Indexes with known Cobb angles."

9. How Ground Truth for the Training Set Was Established

The document states: "The model was developed using a database of patient Asymmetry Indexes with known Cobb angles." It implies that the Cobb angles for the training data were also established through similar means as the test set ground truth (i.e., likely from radiographs). However, the precise method for establishing the ground truth for the training set (e.g., number of readers, adjudication) is not detailed.

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The NSI Implant System is intended to be implanted in the upper or lower jaw arches to provide support for fixed or removable dental prostheses in a single tooth, partially edentulous prostheses, or full arch prostheses.

The NSI Implant System is intended to be implanted in the upper or lower jaw arches to provide support for fixed or removable dental prostheses in a single tooth, partially edentulous prostheses, or full arch prostheses.

The provided document is a 510(k) summary for a dental implant system (NSI Hexed and Non-Hexed Implant System). It explicitly states that "Clinical studies were not conducted, or deemed necessary, for the purpose of this 510(k) submission." Therefore, there is no information available in this document regarding acceptance criteria or a study proving device performance against such criteria.

The submission focuses on demonstrating substantial equivalence to legally marketed predicate devices based on technological characteristics and intended use, rather than on new clinical performance data.

Consequently, I cannot provide the requested information, which includes:

1. A table of acceptance criteria and the reported device performance
2. Sample size used for the test set and the data provenance
3. Number of experts used to establish the ground truth for the test set and their qualifications
4. Adjudication method for the test set
5. If a multi-reader multi-case (MRMC) comparative effectiveness study was done
6. If a standalone performance study was done
7. The type of ground truth used
8. The sample size for the training set
9. How the ground truth for the training set was established

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