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iCTmotor (WL-1) is intended for use in dental surgery and implantology. The main control unit is designed to operate a specific dental micro motor that drives dental handpieces to cut hard and soft tissues in the mouth and screw dental implants. iCTmotor (WL-1) is compatible with a handpiece equipped with connection according to ISO 3964.

iCTmotor (WL-1) is a software based driving engine that controls the speed of a specific dental micromotor. This device is optimized for dental implant procedures and user programmable parameters operate and control a dental handpiece for dental implant surgery. iCTmotor (WL-1) consists of a main controller unit, a charger, a foot controller, micro motor, cable, a water holder, tube holder, and micro motor holder. The main control unit operates the speed and torque of a dental micromotor that drives dental handpiece to cut tissues in the mouth and to screw dental implants. The main control unit is operated via a wireless foot pedal. The holders are used for placement of a water bag, a micro motor and a handpiece. The power cord delivers electric power to the main control unit.

The provided text is a 510(k) summary for the iCTmotor (WL-1), a dental device. It does not describe an AI/ML-based medical device or a study involving human readers or AI assistance. Therefore, it's not possible to provide acceptance criteria or a study description related to AI/ML device performance from this document.

The document focuses on demonstrating substantial equivalence to a predicate device (MASTERsurg / EXPERTsurg) through non-clinical performance testing. It highlights the device's intended use in dental surgery and implantology, specifically controlling a dental micromotor for cutting tissues and screwing dental implants.

The non-clinical tests performed are related to the physical and electrical characteristics of the device, as well as software validation for its control functions.

Key points from the document relevant to non-clinical performance testing (not AI/ML):

• Acceptance Criteria & Performance: The document states that "Performance testing was conducted according to ISO 14457:2012 to show that the device meets its design requirements and performs as intended." The specifications for the following parameters were met:

  • Rotating speed of micromotor
  • Torque of micromotor
  • Stop of micromotor
  • Rotating direction of micromotor
  • Irrigation amount

  The exact numerical acceptance criteria and the reported numerical performance for these parameters are not explicitly detailed in a table format within this summary, but the general claim is that they were "met." For example, under "Electrical Specification Motor (Speed)," the iCTmotor (WL-1) has a speed of "400- 40,000rpm," and the predicate has "300 - 40,000 rpm." While these are performance specs, the document doesn't present them as formal "acceptance criteria" vs. "reported performance" in a dedicated test. Instead, it asserts compliance with ISO 14457:2012.

• Sample Size and Data Provenance: Not applicable for an AI/ML context. For the non-clinical tests, the sample size would refer to the number of units tested, which is not specified but is typically a small engineering sample or a representative batch. The data provenance is from the manufacturer's internal testing.

• Experts and Ground Truth: Not applicable in the context of AI/ML interpretation. The "ground truth" for these performance tests is the engineering specification for each parameter (e.g., a specific RPM range, torque value).

• Adjudication Method: Not applicable. Performance testing of physical devices is typically a direct measurement against a specification.

• MRMC Comparative Effectiveness Study: Not applicable. This study focuses on a hardware device, not an AI/ML algorithm.

• Standalone Performance: The "performance testing" described (rotating speed, torque, etc.) represents the standalone performance of the device's control system and motor.

• Type of Ground Truth: The ground truth for this device's performance testing is based on engineering specifications and established international standards (ISO 14457:2012) for dental handpieces/micromotors.

• Training Set Sample Size: Not applicable. This is a hardware device with software control, not an AI/ML model that requires training data. The software was subjected to verification and validation as per FDA guidance for software in medical devices, but this is distinct from AI/ML model training.

• Ground Truth for Training Set: Not applicable, as there is no AI/ML training set in this context. Software "ground truth" for verification and validation typically means that the software functions as designed according to its requirements specification.

In summary, this document is a 510(k) premarket notification for a traditional medical device (iCTmotor (WL-1)) and does not contain information about AI/ML acceptance criteria or a study proving an AI/ML device meets such criteria.

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The iCT device with sliding gantry is intended to produce cross-sectional images of the body by computer reconstruction of x-ray transmission data from either the same axial plane taken at different angles or spiral planes* taken at different angles.

(*spiral plane: the axial planes resulted from the continuous rotation of detectors and x-ray tube, and the simultaneous translation of the sliding gantry).

iCT is a whole body x-ray computed tomography (CT) scanner. It combines a standard CT gantry with a ceiling mounted suspension and drive mechanism to move the gantry horizontally during image acquisition. The standard CT gantry features a continuously rotating tub-detector system and functions according to the fan beam principle. The ceiling mounted suspension and drive mechanism allows iCT to be moved along rails for storage or to share the iCT between multiple rooms. The ceiling mounted system also provides precise horizontal movement that is integrated with the CT scan control. During image acquisition, the iCT drive mechanism translates the CT gantry while the patient table remains stationary. Moving the gantry allows the patient to remain stationary instead of translating the patient relative to the gantry as is required with fixed gantry systems. iCT may be used with commercially available patient tables, including surgical tables, that meet the appropriate size and x-ray transmission characteristic requirements.

iCT leverages the previously cleared SOMATOM Definition, Model AS/AS+ (K081022) gantry, power supply and operator console components, including the syngo software platform and compatible syngo applications. iCT produces CT images in DICOM format. The syngo platform is able to run optional postprocessing applications.

Here's a breakdown of the acceptance criteria and study information for the iCT device, based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

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

• Sample Size: The document explicitly states that "sample clinical images are unnecessary to support substantial equivalence in this case and instead testing relied on laboratory studies." This implies that clinical images were NOT used as a test set. The testing was done using "high precision phantoms." The specific number of phantoms or scans performed is not provided.
• Data Provenance: Not applicable, as clinical data was not used for the test set.

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

• Not applicable as the testing was conducted using "high precision phantoms" and laboratory studies, not clinical data and expert interpretation.

4. Adjudication Method for the Test Set

• Not applicable, as the testing was conducted using "high precision phantoms" and laboratory studies, not human evaluation of clinical data.

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 done. The document states that "sample clinical images are unnecessary to support substantial equivalence in this case and instead testing relied on laboratory studies." This indicates the evaluation was technical and mechanical, not clinical or involving human readers.

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

• Yes, the primary evaluation was a standalone technical/mechanical evaluation of the iCT system's performance metrics (image quality, z-axis accuracy, gantry stability) against the specifications of the predicate device using phantoms. This is effectively a "standalone" assessment of the device's physical and image acquisition capabilities without human interpretation of clinical images.

7. The Type of Ground Truth Used

• The ground truth was established by the specifications and performance characteristics of the predicate device, specifically the SOMATOM Definition, Model AS/AS+ with the sliding gantry package. The iCT's performance was measured against these established technical benchmarks using "high precision phantoms."

8. The Sample Size for the Training Set

• Not applicable. The iCT is leveraging a previously cleared CT gantry, power supply and operator console components (SOMATOM Definition, Model AS/AS+), including its syngo software platform and compatible syngo applications. The iCT itself is primarily a modification concerning the physical mounting and movement of this existing CT technology (ceiling rails vs. floor rails). Therefore, it doesn't appear to involve its own separate "training set" in the context of an AI/algorithm. The core imaging algorithms are assumed to be from the predicate device.

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

• Not applicable, as a separate training set for the iCT's distinct features (ceiling mounted gantry movement) is not described, and the core imaging software/algorithms are inherited from the cleared predicate device. The information provided focuses on the physical and technical performance of the modified gantry system.

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The ICTA software is intended as a review tool to mark previously acquired sections of the adult (greater than or equal to 18 years) EEG recordings (surface or intracranial) that may correspond to electrographic seizures, in order to assist qualified clinical practitioners, who will exercise professional judgment in using the information, in the assessment of EEG traces.

• Surface recordings must be obtained with full montage according to the standard 10/20 . system.
• Intracranial recordings must be obtained with depth electrodes (strips and/or grids). .
  This device does not provide any diagnostic conclusion about the patient's condition to the user.

ICTA is a software only product. It runs on a personal computer and requires no specialized hardware. It identifies electroencephalographic activity that might correspond to seizures (referred as "events"). These events are then reviewed, accepted, modified and/or deleted by the qualified medical practitioner. The software does not make any final decisions that result in any automatic diagnosis or treatment. The EEG input is read from a file on the personal computer (or available across the network).
ICTA employs Bayesian formulation to provide a detection variable based on the probabilities that a given section of EEG contains a seizure-like activity. The a priori probabilities that a certain set of features represent seizure or non-seizure data were computed from the training data set. These probabilities are used by the detection method for all seizure detections.
The software has two components: ICTA-S for analysis of surface EEG recordings and ICTA-D for analysis of intracranial recordings. Whether a particular module is active is determined by the user. The user also determines parameters that are needed for the algorithm to perform its intended task. None of the components is responsible for data acquisition, review or any other function different from analysis.

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

1. Table of Acceptance Criteria and Reported Device Performance

The acceptance criteria for ICTA were established through a comparison with a predicate device (NeuroWorks Seizure Detector, K090019) and the "gold standard" of expert neurophysiologists. The key performance metrics are Positive Percent Agreement (PPA) and False Detection Rate (FDR).

Note: The document states "Equivalent" for both metrics when comparing to the predicate, even though the FDRs are numerically different. This suggests the FDA considers these values acceptable within the context of seizure detection assistance tools.

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

• ICTA-S (Surface EEG):
  • Number of Seizures: 615
  • Total Number of Patients: 102
  • Total Number of Hours: 395
  • Data Provenance: Retrospective, patients with medically refractory seizures admitted to an Epilepsy Monitoring Unit. The specific country of origin is not explicitly stated, but Natus Medical Incorporated DBA Excel-Tech Ltd. is based in Oakville, Ontario, Canada.
• ICTA-D (Intracranial EEG):
  • Number of Seizures: 429
  • Total Number of Patients: 93 (57 Male, 36 Female)
  • Total Number of Hours: 619 hours
  • Data Provenance: Retrospective, adult patients seen for routine clinical evaluation at Epilepsy Monitoring Units of Toronto Western General Hospital (Canada) and NewYork-Presbyterian Hospital (USA).

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

• Number of Experts: Three independent, blinded EEG experts were used for both ICTA-S and ICTA-D studies.
• Qualifications: All experts were board-certified Neurophysiologists (or neurologists/epileptologists). The document does not specify their years of experience.

4. Adjudication Method for the Test Set

• Adjudication Method: A "majority rule (at least 2 out of 3)" was applied. This means that for a seizure to be considered a "true" electrographic seizure (ground truth), at least two of the three independent experts had to agree on its presence.

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

• The document does not describe a multi-reader multi-case (MRMC) comparative effectiveness study where human readers' performance with and without AI assistance was evaluated. The study focuses on evaluating the standalone performance of the ICTA algorithm against a human-established ground truth and comparing it to a predicate device's reported performance.

6. Standalone Performance Study

• Yes, a standalone (algorithm only without human-in-the-loop performance) study was done. The entire clinical testing section describes the evaluation of the ICTA-S and ICTA-D algorithms' performance (PPA and FDR) independently against the ground truth established by the expert panel. The results presented in the tables (e.g., PPA 75% / FDR 2.0 FP/h for ICTA-S) are for the algorithm in standalone mode.

7. Type of Ground Truth Used

• Type of Ground Truth: Expert consensus. Specifically, electrographic seizures identified by a panel of three board-certified Neurophysiologists, with a majority rule for final determination.

8. Sample Size for the Training Set

• The document states that Bayesian formulation was used, and "The a priori probabilities that a certain set of features represent seizure or non-seizure data were computed from the training data set."
• However, the specific sample size for the training set is not provided in the summary.

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

• The document states that probabilities were computed from the "training data set." It does not explicitly detail the method for establishing ground truth for this training set. However, given the nature of the device and the methods described for the test set, it is highly probable that the ground truth for the training set was also established through expert review and annotation of EEG recordings, likely by qualified medical practitioners. The summary implies that this training data was used to establish the "a priori probabilities" for the Bayesian model.

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