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Alignment System Cranial is intended to plan and to achieve a trajectory with surgical instruments during cranial stereotactic procedures.

The indications for use are biopsy of intracranial lesions, placement of stereoelectroencephalography (SEEG) electrodes and placement of anchor bolts for laser interstitial thermal therapy (LITT).

The subject device Alignment System Cranial is an image guided surgery system intended to support the surgeon to plan and to achieve a trajectory with surgical instruments during cranial stereotactic procedures using optical tracking technology.

For this purpose, the Alignment System Cranial consists of a combination of hardware and software. The Alignment Software Cranial with LITT 2.1 is installed on an Image Guided Surgery (IGS) platform (Curve, Curve Navigation 17700, Kick 2 Navigation Station or Buzz Navigation) consisting of a computer unit, a touch display and an infrared tracking camera. During surgery, the software tracks the position of instruments in relation to the patient anatomy and identifies this position on pre- or intraoperative images. The position of the surgical instruments is continuously updated on these images by optical tracking. This position information is used by the software to align either passive or active positioning devices to a planned trajectory for subsequent surgical steps.

The Alignment System Cranial has different configurations of hardware devices depending on which positioning device is used and which indication is performed. The Alignment Software Cranial with LITT 2.1 supports the active positioning devices Surgical Base System 1.4 and Cirq Arm System 2.0 (+ Cirq Robotic Alignment Module + Cirq Robotic Disposable Kinematic Unit) as well as the passive positioning device VarioGuide. Both types of positioning devices consist of articulated arms with different joints where additional devices and surgical instruments can be attached to for further manual or robotic alignment to a defined trajectory.

In addition, the subject device offers a set of indication specific instruments to support biopsy, sEEG and LITT procedures. This instrumentation consists of instrument holders, tracking arrays, guide tubes, reduction tube, bone anchors, drill bits and depth stops. None of the instruments is delivered sterile. All patient contacting materials consist of different alloys of stainless steel.

The Alignment Software Cranial with LITT has the following accessories:

• Automatic Registration providing an automatic registration for subsequent use.
• Automatic Registration iMRI providing an automatic image registration for intraoperatively . acquired MR images.

The provided text is a 510(k) summary for the "Alignment System Cranial," which includes "Alignment Software Cranial with LITT." It details the device's indications for use, description, and comparison to predicate devices, along with performance data to demonstrate substantial equivalence.

Here's an analysis of the acceptance criteria and the study that proves the device meets them, based on the provided text:

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

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

• Sample Size for Test Set:
  • Number of registrations: 6
  • Total number of samples: 37 (This likely refers to individual measurements taken over the 6 registrations)
• Data Provenance: The document does not explicitly state the country of origin or whether the data was retrospective or prospective. However, the study was conducted as "System accuracy testing" to evaluate the device in "a realistic clinical setup and representative worst case scenarios," suggesting it was a controlled, prospective study performed by the manufacturer.

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

The document does not provide information on the number of experts or their qualifications used to establish ground truth for this system accuracy testing. This type of testing typically relies on metrology standards and physical measurements rather than clinical expert consensus for ground truth.

4. Adjudication method for the test set

The document does not specify an adjudication method. For system accuracy testing based on physical measurements, an adjudication process involving human experts is generally not applicable in the same way it would be for image-reading or diagnostic AI.

5. If a multi-reader multi-case (MRMC) comparative effectiveness study was done, and its effect size

No, a multi-reader multi-case (MRMC) comparative effectiveness study was not done. The performance data presented is for the system accuracy of the device concerning its ability to align instruments, not for a diagnostic AI algorithm that human readers would interact with. The document explicitly states: "No clinical testing was needed for the Subject Device since optical tracking technology in the scope of image guided surgery for the included indications for use is well established in the market."

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

The performance study was for the system's accuracy (hardware + software components), which is a key aspect of its standalone functionality in terms of guiding instruments. While it's not an "algorithm only" study in the sense of a pure AI diagnostic tool, it measures the precision of the device's output without direct human interpretation in the loop of the measurement itself. The "Automatic Registration" features (including one for iMRI) are mentioned as accessories, implying an algorithmic component, but specific performance criteria for these AI/ML-based features are not detailed beyond the general system accuracy. The document mentions that "There have been no changes to the AI/ML algorithm" for surface matching for patient registration, implying its prior validation.

7. The type of ground truth used

The ground truth for the system accuracy testing ("positional and angular navigation accuracy") would have been established through precise physical measurements using calibrated instruments and metrological standards (e.g., a coordinate measuring machine or similar setup to establish a true target position against which the device's reported position is compared). It is not based on expert consensus, pathology, or outcomes data, as this is a measurement of mechanical and software precision.

8. The sample size for the training set

The document does not provide information on the sample size for the training set for any embedded AI/ML components (e.g., the AI/ML based model for landmark delivery in surface matching). The focus of this 510(k) summary is on the system accuracy for the LITT indication, and asserts "no changes to the AI/ML algorithm" for patient registration.

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

The document does not provide information on how the ground truth for any training set was established for embedded AI/ML components. It only mentions that an existing AI/ML algorithm for surface matching landmarks has not changed.

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The AlignRT Plus system is indicated for:

• · Tracking respiratory motion throughout the simulation process to facilitate subsequent 4DCT reconstruction and coaching the patient in breathing techniques required for Deep-Inspiration Breath Hold (DIBH).
• · Verification of patient identity for their radiation treatment session.
• · Positioning and monitoring of patients during radiation delivery, relative to the setup isocenter and/or the prescribed treatment isocenter.
• · Withholding the beam automatically during radiation delivery, as well as gating the patient's respiratory motion.
• · Performing quality assurance on MV, kV imagers, room lasers, and the treatment couch.
• · Visualizing the Cherenkov signal associated with the radiation beam on entry and exit from the patient.
• · Passing and receiving information to/from other systems associated with the radiotherapy treatment.

The AlignRT Plus system (K212583) is a combination of the devices AlignRT InBore, AlignRT Offline, DoseRT, GateCT, GateRT and SimRT.

AlignRT Plus is a video-based three-dimensional (3D) surface imaging system used to monitor the patient's position in 3D before and during radiotherapy treatment. During each treatment session the patient's position is compared to the reference surface and offsets are displayed to the user. The system can be used to track pation during tumour localization in the CT scanner in order to facilitate subsequent 4D CT reconstruction. The system can be used to track the breath hold level consistency throughout the simulation process. The system can also be used to track patient motion during treatment delivery for radiation therapy procedures and hold the beam when the patient is not in position. Use of optional accessories allows the user to:

• monitor the patient's position inside bore-based linacs; and/or —
• to view the Cherenkov light emitted by the radiation beam as it enters and exits the patient's skin; and/or
• verify the patient's identity.

The system is non-invasive, does not require the use of body markers and produces no irradiation during the imaging process. The system mainly consists of advanced software. 3D cameras (≤6 cameras) and calibration tools. Each camera pod monitoring the pation will, however, project a pattern on the patient to acquire a 3D image of the patient.

This 510(k) notification is to obtain clearance for the following changes to the cleared device:

• 1. Introduction of new software, version 7.3. This is an updated version of the existing cleared software, to support the:
  • a. New Cherenkov imaging feature, called DoseRT.
  • b. Updated respiratory gating feature, called Respiratory Module.
• 2. Introduction of new hardware:
  • a. DoseRT camera to enable Cherenkov imaging.
• 3. Update to indications for use to include the new Cherenkov imaging feature and clarify existing indications.

The provided document describes the AlignRT Plus 7.3 system, a surface-guided radiation therapy system. However, it does not contain detailed acceptance criteria and a study dedicated to proving the device meets those criteria in the format requested.

The document focuses on demonstrating substantial equivalence to a predicate device (AlignRT Plus K212583) and a reference device (BeamSite K212606) for new features, primarily Cherenkov imaging and an updated respiratory module. It mentions "Verification tests were performed to ensure that the module works as intended and pass/fail criteria were used to verify requirements. Validation testing was performed using summative evaluation techniques per IEC 62366-1:2015. Verification and validation testing passed in all test cases." but does not provide details of these tests, specific acceptance criteria, or the results.

Therefore, many of the requested fields cannot be filled from the provided text.

Here's a summary of the information that can be extracted or inferred, and what is missing:

1. Table of Acceptance Criteria and Reported Device Performance:

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

• Sample Size: Not specified for any of the performance claims. The document states "no clinical investigations were performed."
• Data Provenance: Not specified. It's likely internal testing data given the lack of clinical studies. Retrospective or prospective nature is not mentioned, nor is country of origin.

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

• Not specified. The document does not describe the use of experts to establish ground truth for testing.

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

• Not specified.

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 comparative effectiveness study was done. The device is a patient positioning and monitoring system, not an AI-assisted diagnostic tool for human readers.

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

• The document implies that the device's technical performance characteristics (e.g., positioning accuracy, respiratory tracking) were evaluated as a standalone system against predefined specifications, as it mentions "Verification tests were performed to ensure that the module works as intended and pass/fail criteria were used to verify requirements." However, no specific details like algorithms, metrics, or detailed results are provided.

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

• For the positioning accuracy, the ground truth appears to be based on measurements using a "calibration phantom."
• For respiratory tracking, the ground truth for "relative respiratory position" is implied to be a measured value for comparison.
• For Cherenkov visualization, the ground truth is the actual presence and characteristics of the radiation beam.
• No expert consensus, pathology, or outcomes data is explicitly mentioned as ground truth for these technical performance tests.

8. The sample size for the training set:

• Not applicable/Not specified. The document describes a medical device system, not an AI model requiring a distinct training set in the typical sense of machine learning. The "advanced software" may incorporate algorithms, but details about training data, if any, are not present.

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

• Not applicable/Not specified (refer to point 8).

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The Align Studio is intended for use as a medical front-end device providing tools for management of orthodontic models, systematic inspection, detailed analysis, treatment simulation and virtual appliance design options based on 3Dmodels of the patient's dentition before the start of an orthodontic treatment.

The use of the Align Studio requres the user to have the necessary training and domain knowledge in the practice of orthodontics, as well as to have received a dedicated training in the use of the software.

Align Studio is a PC-based software that sets up virtual orthodontics via digital impressions. It automatically segments the crown and the gum in a simple manner and provides basic model analysis to assist digital orthodontic procedures.

The provided document, an FDA 510(k) summary for "Align Studio," does not contain detailed information about specific acceptance criteria, a comprehensive study proving the device meets those criteria, or the methodology (e.g., sample size, expert qualifications, ground truth establishment) typically associated with such studies for AI/ML-based medical devices.

Instead, this document focuses on demonstrating substantial equivalence to predicate devices (Ortho System and CEREC Ortho Software) rather than presenting a detailed performance study against predefined acceptance criteria for an AI-powered system. The Non-Clinical Test Summary section briefly mentions "software validation" and "performance testing" but without quantifiable metrics or specific methodologies. It states that "Align Studio meets all performance test criteria and that all functions work without errors" and "test results support the conclusion that actual device performance satisfies the design intent and is equivalent to its predicate device."

Therefore, I cannot populate the table or answer most of the questions as the required information is not present in the provided text.

Here's what can be extracted based on the limited information provided:

1. A table of acceptance criteria and the reported device performance
The document does not provide a table of acceptance criteria with quantifiable performance metrics specific to an AI/ML system's output. It broadly states the device "meets all performance test criteria" and "functions work without errors." The focus is on functional equivalence to predicate devices rather than specific quantitative performance targets for an AI component.

2. Sample size used for the test set and the data provenance
Not specified. The document does not detail the test set used for performance evaluation, nor its size or origin (country, retrospective/prospective).

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts
Not specified. The document doesn't describe the establishment of a ground truth for a test set, which would typically involve expert review for AI/ML performance evaluation.

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set
Not specified, as a detailed ground truth establishment process is not described.

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 comparative effectiveness study is mentioned. The submission focuses on substantial equivalence based on device features and intended use, not on human reader performance with AI assistance.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
The "Non-Clinical Test Summary" section mentions "Performance Testing" which could imply standalone testing, but no specific metrics for an algorithm-only performance (e.g., segmentation accuracy, measurement precision without human interaction) are provided. The device is described as "PC-based software" for "virtual orthodontics" that "automatically segments the crown and the gum," implying an algorithm performing actions. However, the document does not detail the standalone performance metrics for this automated segmentation or other AI features.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)
Not specified. Given the lack of detailed performance study information, the type of ground truth used is not described.

8. The sample size for the training set
Not specified. The document does not provide details on the training set used for any AI/ML components within the "Align Studio" software.

9. How the ground truth for the training set was established
Not specified. Without information on a training set, the method of establishing its ground truth is also not provided.

Summary of available information regarding software validation and performance:

• Software Validation: "Align Studio contains Basic Documentation Level software was designed and developed according to a software development process and was verified and validated."
• Performance Testing: "Through the performance test, it was confirmed that Align Studio meets all performance test criteria and that all functions work without errors. Test results support the conclusion that actual device performance satisfies the design intent and is equivalent to its predicate device."
• Clinical Studies: "No clinical studies were considered necessary and performed."

This filing relies on demonstrating substantial equivalence to already cleared predicate devices based on shared technological characteristics and intended use, rather than presenting a novel performance study for an AI/ML component with specific acceptance criteria and detailed clinical validation results.

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The Align Cervical Interbody Fusion is indicated for intervertebral body fusion of the spine in skeletally mature patients who have had at least six months of non-operative treatment. The device systems are designed for use with allogenic bone graft comprised of cancellous and/or corticocancellous bone graft and/or autograft to facilitate fusion. One device is used per intervertebral body space. The Align Cervical Interbody Fusion System is intended for use at either one level or two contiguous levels in the cervical spine, from C2 to T1, for the treatment of degenerative disc disease (DDD) with up to Grade I spondylolisthesis. DDD is defined as back pain of discogenic origin with degeneration of the disc confirmed by history and radiographic studies. The Align Cervical Interbody Fusion is intended to be used with supplemental spinal fixation system cleared for use in the cervical spine.

The Align Cervical Interbody Fusion System consists of intervertebral body fusion devices that are implanted in the intervertebral body space via an anterior approach to improve stability of the spine while supporting fusion. Components are offered in different shapes and sizes to meet the requirements of the individual patient anatomy. Align cervical cages will be manufactured from titanium alloy per ASTM F3001 and will be offered with an optional hydroxyapatite (HA) coating. Implants will be provided sterile by gamma irradiation.

The provided text is a 510(k) summary for the "Align Cervical Interbody Fusion System," a medical device, and not an AI/ML device. Therefore, the document does not contain the information requested in your prompt regarding acceptance criteria and studies proving the device meets those criteria for an AI/ML device.

The document discusses:

• Device Type: Intervertebral body fusion device
• Regulatory Classification: Class II
• Intended Use: Intervertebral body fusion of the cervical spine for degenerative disc disease.
• Materials: Titanium alloy with optional hydroxyapatite (HA) coating.
• Performance Testing: Confirmatory fatigue testing (dynamic compression shear, and dynamic torsion per ASTM F2077) – this is mechanical testing for an implant, not AI/ML performance.
• Substantial Equivalence: Comparison to predicate devices based on indications for use, materials, and geometry.

There is no mention of:

• Acceptance criteria for an AI/ML algorithm.
• Performance metrics like sensitivity, specificity, AUC, etc.
• Sample sizes for test or training sets related to AI/ML data.
• Experts establishing ground truth for AI/ML.
• Adjudication methods.
• Multi-reader multi-case (MRMC) comparative effectiveness studies for AI assistance.
• Standalone algorithm performance.
• Provenance of data (country, retrospective/prospective).
• Ground truth methods (pathology, outcomes data).

Therefore, I cannot populate the requested table or answer the questions related to AI/ML device acceptance criteria and study details based on the provided text.

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• Retention of aligners e.g. by fabrication of aligner attachments
• Bonding of lingual retainers
• Occlusal build-ups

Not Found

The provided text is an FDA 510(k) clearance letter for the AlignerFlow LC device. It indicates that the device has been found substantially equivalent to predicate devices for its stated indications for use (retention of aligners, bonding of lingual retainers, and occlusal build-ups).

However, the provided document does not contain any information about acceptance criteria, device performance studies, sample sizes, ground truth establishment methods, expert qualifications, adjudication methods, or MRMC studies. The letter is a regulatory clearance document, not a clinical study report or a technical performance evaluation.

Therefore, I cannot provide the requested table and study details based on the input text.

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The Align Radial Head System and accessories are designed specifically for:

• Replacement of the radial head for degenerative or post-traumatic disabilities presenting pain, crepitation, and decreased motion at the radio-humeral and/or proximal radio-ulnar joint with:
  • o Joint destruction and/or subluxation.
  • o Resistance to conservative treatment.
• Primary replacement after fracture of the radial head.
• Symptomatic sequelae after radial head resection.
• Revision following failed radial head arthroplasty.

The system is intended for press fit use.

The subject Align Radial Head System and the predicate Align Radial Head System (K172688) are a radial head prosthesis and instrumentation platform that is designed to orient the radial head perpendicular to the axis of forearm rotation. It consists of cobalt chrome modular heads in different sizes with cobalt chrome locking screws, titanium alloy stems, necks, and specialized instrumentation.

The provided text is a 510(k) summary for the ALIGN Radial Head System, which is a medical device for radial head replacement. This document primarily focuses on demonstrating substantial equivalence to a predicate device rather than presenting a detailed study proving the device meets specific acceptance criteria in the context of AI/ML performance.

Therefore, many of the requested sections related to AI/ML study components (such as sample sizes for test and training sets, expert qualifications, ground truth establishment, MRMC studies, or standalone performance) are not applicable to this type of regulatory submission and are not present in the provided text.

The "acceptance criteria" discussed in this document refer to the criteria for demonstrating substantial equivalence to a predicate device, primarily through mechanical testing to ensure safety and effectiveness.

Here’s the information based on the provided text, with "N/A" for sections not covered by this type of submission:

1. Table of Acceptance Criteria and Reported Device Performance

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

N/A. This document describes mechanical testing of a physical medical device, not a study involving a "test set" of data or patient provenance in the context of an AI/ML device. The testing would involve physical samples of the device components. The document does not specify the number of samples used for static and fatigue compression 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)

N/A. Not applicable to mechanical testing of a physical implant.

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

N/A. Not applicable to mechanical testing of a physical implant.

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

N/A. Not applicable as this is not an AI/ML device.

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

N/A. Not applicable as this is not an AI/ML device.

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

For the mechanical testing, the "ground truth" would be established engineering standards and specifications for material strength, fatigue life, and structural integrity under simulated physiological loads, which are used to determine if the device performs equivalently to the predicate. This document does not elaborate on specific standards or the methodology of establishing "ground truth" beyond stating "mechanical testing" was performed.

8. The sample size for the training set

N/A. Not applicable as this is not an AI/ML device.

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

N/A. Not applicable as this is not an AI/ML device.

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Alignment System Cranial is intended to support the surgeon to plan and to achieve a trajectory with surgical instruments during cranial stereotactic procedures.

The indications for use are biopsy of intracranial lesions and placement of stereoelectroencephalography (SEGG) electrodes.

The subject device Alignment System Cranial is an image guided surgery system intended to support the surgeon to plan and to achieve a trajectory with surgical instruments during cranial stereotactic procedures using optical tracking technology.

For this purpose, the Alignment System Cranial consists of a combination of hardware and software. The Alignment Software Cranial with its sw components is installed on an Image Guided Surgery (IGS) platform (Curve, Curve Navigation 17700, Kick 2 Navigation Station or Buzz Navigation) consisting of a computer unit, a touch display and an infrared tracking camera. During surgery, the subject device tracks the position of instruments in relation to the patient anatomy and identifies this position on pre- or intraoperative images. The position of the surgical instruments is continuously updated on these images by optical tracking. This position information is used by the Alignment Software Cranial to align either passive or active positioning devices to a planned trajectory for subsequent surgical steps.

The Alignment System Cranial has different configurations of hardware devices depending on which positioning device is used and which indication is performed. The Alignment Software Cranial 2.0 supports the active positioning devices Surgical Base System 1.4 and Cirq Arm System 2.0 (+ Cirq Robotic Alignment Module + Cirq Robotic Disposable Kinematic Unit) as well as the passive positioning device Varioquide. Both types of positioning devices consist of articulated arms with different joints where additional devices and surgical instruments can be attached to for further robotic or manual alignment respectively to a defined trajectory.

In addition, the subject device offers a set of indication specific instruments to support biopsy and sEEG procedures. This instrumentation consists of instrument holders, tracking arrays, guide tubes, reduction tube, bone anchors, drill bits and depth stops. None of the instruments is delivered sterile. All patient contacting materials consist of different alloys of stainless steel.

With this submission, an already existing feature is now performed introducing a new algorithm using artificial intelligence and machine (AI/ML). This ML based functionality is used as an aid in the registration step (in surface matching) by allowing a pre-registration based on guide points which are delivered by this algorithm. This pre-registration step is not mandatory. The AI/ML algorithm is a Convolutional Network (CNN) developed using a Supervised Learning approach. The algorithm was developed using a controlled internal process that defines activities from the inspection of input data to the training and verification of the training process begins with the model observing, learning, and optimizing its parameters based on the training pool data. The model's prediction and performance are then evaluated against the test pool. The test pool data is set aside at the beginning of the project. This is a static algorithm (locked).

The Alignment Software Cranial has the following accessories:

• . Automatic Registration providing an automatic registration for subsequent use.
• . Automatic Registration iMRI providing an automatic image registration for intraoperatively acquired MR images.

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

1. Table of Acceptance Criteria and Reported Device Performance

2. Sample Sizes Used for Test Set and Data Provenance

The document does not explicitly state the numerical sample size for the test set used for the AI/ML algorithm's performance evaluation or for the general system accuracy testing. However, it indicates:

• AI/ML Test Set: "The test pool data is set aside at the beginning of the project. This is a static algorithm (locked)." No further details on provenance or numerical size are provided.
• System Accuracy Testing: "evaluated considering a realistic clinical setup and representative worst case scenarios." No specific number of cases or data provenance (e.g., country of origin, retrospective/prospective) is mentioned.

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

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

4. Adjudication Method for the Test Set

The document does not specify an adjudication method for the test set.

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

No mention of an MRMC comparative effectiveness study or human reader improvement with AI assistance is provided. The AI/ML component is described as an "aid in the registration step" by providing "pre-registration based on guide points."

6. Standalone (Algorithm Only) Performance Study

Yes, a standalone performance evaluation of the AI/ML algorithm was done. It focused on comparing its landmark detection capabilities to the conventional method: "For the landmark detection feature in the pre-registration step now implemented using AI/ML, performance testing comparing conventional to machine learning based landmark detection was performed showing equivalent performance as in the third predicate device."

7. Type of Ground Truth Used

The document does not explicitly state the type of ground truth (e.g., expert consensus, pathology, outcomes data) used for the AI/ML algorithm's test set or the system accuracy measurements. For the AI/ML, it implies that the ground truth for landmark detection was established against which the algorithm's performance was compared to the predicate's conventional method.

8. Sample Size for the Training Set

The document states: "The algorithm was developed using a controlled internal process that defines activities from the inspection of input data to the training and verification of the training process begins with the model observing, learning, and optimizing its parameters based on the training pool data." However, it does not provide the numerical sample size for the training set.

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

The document states that the AI/ML algorithm is a "Convolutional Network (CNN) developed using a Supervised Learning approach." This implies that the training data was labeled with the correct ground truth for the landmarks. However, it does not explicitly describe how this ground truth was established (e.g., by experts, manually annotated, etc.).

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Align anterior cages are indicated for intervertebral body fusion of the spine in skeletally mature patients who have had at least six months of non-operative treatment. The device systems are designed for use with allogenic bone graft comprised of cancellous and/or corticocancellous bone graft and/or autograft to facilitate fusion. One device is used per intervertebral body space. Align anterior cages are intended for use at ether one level or two contiguous levels in the lumbar spine, from L2 to S1, for the treatment of degenerative disc disease (DDD) with up to Grade I spondylolisthesis. DDD is defined as back pain of discogenic origin with degeneration of the disc confirmed by history and radios. Align 2-screw anterior cages may be used as a stand alone device only when two (2) vertebral body bone screws are used. Align 4-screw anterior cages may be used as a stand alone device only when at least two (2) vertebral body bone screws are inserted in the two medial fixation holes with one superior screw trajectory. If the physician chooses to use Align anterior cages with fewer than two (2) screws in the two medial fixation holes with one inferior and one superior screw trajectory, then an additional spinal fixation system cleared for use in the lumbosacral spine must be used.

Align anterolateral cages are indicated for intervertebral body fusion of the spine in skeletally mature patients who have had at least six months of non-operative treatment. The device systems are designed for use with allogenic bone graft comprised of cancellous and/or corticocancellous bone graft and/or autograft to facilitate fusion. One device is used per intervertebral body space. Align anterolateral cages are intended for use at either one level or two contiguous levels in the lumbar spine, from L2 to S1, for the treatment of degenerative disc disease (DDD) with up to Grade I spondylolisthesis. DDD is defined as back pain of discogenic origin with degeneration of the disc confirmed by history and radiographic studies. Align anterolateral cages are intended to be used with supplemental spinal fixation system cleared for use in the lumbosacral spine.

Align lateral cages are indicated for intervertebral body fusion of the spine in skeletally mature patients who have had at least six months of non-operative treatment. The device systems are designed for use with allogenic bone graft comprised of cancellous and/or corticocancellous bone graft and/or autograft to facilitate fusion. One device is used per intervertebral body space. Align lateral cages are intended for use at either one level in the lumbar spine, from L2 to S1, for the treatment of degenerative disc disease (DDD) with up to Grade I spondylolisthesis. DDD is defined as back pain of discogenic origin with degeneration of the disc confirmed by history and radiographic studies. Align lateral cages are intended to be used with supplemental spinal fixation system cleared for use in the lumbosacral spine.

Align implants are intervertebral body fusion devices intended for lumbar interbody fusion using an anterior lumbar interbody fusion surgical approach (ALIF), anterolateral (i.e., oblique) lumbar interbody fusion surgical approach (OLIF), or a lateral lumbar interbody fusion surgical approach (LLIF). The devices are intended to improve stability of the spine while supporting fusion. The Align constructs are intended for use at one or two contiguous levels in the lumbar spine (L2-S1). Components are offered in different shapes and sizes to meet the requirements of the individual patient's anatomy and are provided sterile. Align devices are available in six configurations: modular constructs, standard constructs, fully round ALIF (FRA) constructs, and open constructs for ALIF approach, anterolateral (i.e., oblique) constructs for OLIF approach, and lateral constructs for LLIF approach. Align cages are secured on the vertebral bodies using bone screws. A cover plate assembly prevents the screws from backing out after insertion. The cages and cover plates are made of titanium alloy (Ti-6Al-4V ELI) per ASTM F3001 Standard Specification for Additive Manufacturing Titanium-6 Alulminum-4 Vanadium ELI (Extra Low Interstitial) with Powder Bed Fusion. The bone screws and cover plate screws are made from titanium alloy (Ti-6Al-4V ELI) per ASTM F136 Standard Specification for Wrought Titanium-6Aluminum-4Vanadium ELI (Extra Low Interstitial) Alloy for Surgical Implant Applications. All constructs are zero profile, reducing potential for vessel interference with the anterior column. With the exception of the modular constructs, all cages and bone screws are also available with a hydroxyapatite coating.

The provided text is related to a 510(k) premarket notification for a medical device called "Align" by Acuity Surgical Devices, LLC. It describes the device, its indications for use, and a comparison to a predicate device. However, it explicitly states that no clinical data was provided to demonstrate substantial equivalence. This means there is no study described that proves the device meets specific acceptance criteria based on clinical performance.

Therefore, I cannot provide the requested information regarding acceptance criteria and a study proving the device meets those criteria, as such a study is not part of this 510(k submission. The submission relies on non-clinical testing and substantial equivalence to a predicate device and reference devices to demonstrate safety and effectiveness.

Here’s what I can extract based on the document:

1. A table of acceptance criteria and the reported device performance:
Not applicable as no clinical acceptance criteria or performance study results are provided. The submission focuses on demonstrating substantial equivalence through non-clinical testing.

2. Sample size used for the test set and the data provenance:
Not applicable as no clinical study with a test set is described. Non-clinical testing was performed.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:
Not applicable as no clinical study requiring expert ground truth establishment is described.

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set:
Not applicable as no clinical study with adjudication is described.

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:
Not applicable. The device is an intervertebral body fusion device, not an AI-assisted diagnostic tool.

6. If a standalone (i.e. algorithm only without human-in-the loop performance) was done:
Not applicable. The device is a surgical implant, not an algorithm.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.):
Not applicable as no clinical study requiring a ground truth is described.

8. The sample size for the training set:
Not applicable as no clinical study or AI model with a training set is described.

9. How the ground truth for the training set was established:
Not applicable as no clinical study or AI model with a training set and ground truth establishment is described.

Summary of Non-Clinical Testing (as provided in the document):

The device's substantial equivalence is supported by non-clinical testing, which includes:

• Performance testing per ASTM F2077 for Static Axial Compression, Dynamic Axial Compression, Static Compression Shear, and Dynamic Compression Shear.
• Performance testing per ASTM F2267 for Subsidence and Expulsion testing.
  • Note: These tests performed on the predicate device (K201671) are deemed applicable to the modified devices because there is no difference in size, dimension, raw material, or manufacturing method/equipment, except for a nanometer-thin layer of hydroxyapatite applied to the surface.
• Performance testing of HA®® Surface integrity was conducted per the Promimic protocol, which was accepted by FDA for the clearance of reference devices K201614, K170392, and K101225.
• Performance testing of the break-off cover plate screw per the protocol accepted by FDA for the clearance of the reference device K130958.

The document concludes that these non-clinical tests indicate that "Align" is substantially equivalent to the predicate and reference devices.

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The Align Lumbar Interbody Fusion System is indicated for intervertebral body fusion of the spine in skeletally mature patients who have had at least six months of non-operative treatment. The device systems are with allogenic bone graft comprised of cancellous and/or corticocancellous bone graft to facilitate fusion.

The Align Lumbar Interbody Fusion System is intended for use at either one level or two contiguous levels in the lumbar spine, from L2 to S1, for the treatment of degenerative disc disease (DDD) with up to Grade I spondylolisthesis. DDD is defined as back pain of discogenic origin with degeneration of the disc confirmed by history and radios.

The Align Lumbar Interbody Fusion System is intended to be used with supplemental spinal fixation system cleared for use in the lumbosacral spine.

The Align Lumbar Interbody Fusion System consists of several models of intervertebral body fusion devices. The Align ALIF unitary cages and Align fully round ALIF (FRA) cages are intended for anterior approaches. The Align AOLIF cages are intended for anterolateral approaches. The Align Lateral cages are intended for lateral approaches. The Align TLIF cages and Align Oblique TLIF cages are intended for transforaminal approaches. The Align PLIF cages are intended for posterior approaches.

Align Lumbar Interbody Fusion System devices are made from titanium alloy (Ti-6A1-4V ELI) per ASTM F3001 Standard Specification for Additive Manufacturing Titanium-6 Aluminum-4 Vanadium ELI (Extra Low Interstitial) with Powder Bed Fusion. Align Lumbar Interbody Fusion System devices are also made from polyetheretherketone (Zeniva ZA-500 PEEK®) per ASTM F2026 Standard Specification for Polyetheretherketone (PEEK) Polymers for Surgical Implant Applications. The PEEK devices contain radiopaque markers constructed from Tantalum per ASTM F560 Standard Specification for Unalloyed Tantalum for Surgical Implant Applications to assist with intraoperative placement. The radiopaque markers are positioned so the implant can be visualized from an Anterior-Posterior (AP) and Lateral x-ray view.

Reusable instruments to support implantation of the subject device are provided with non-sterile implants in sterilization trays. Implants are also available sterile packaged.

This document is a 510(k) premarket notification for a medical device, the "Align Lumbar Interbody Fusion System." Within this specific type of regulatory submission to the FDA, detailed information regarding acceptance criteria and the study that proves the device meets those criteria, especially in the context of AI/ML performance, is generally not present.

The 510(k) pathway focuses on demonstrating "substantial equivalence" to a legally marketed predicate device, primarily through non-clinical testing (bench testing, biocompatibility) and comparisons of technological characteristics. Clinical data is often not required for 510(k) submissions unless the device has new indications for use, different technological characteristics that raise new safety or effectiveness questions, or if the predicate device itself required clinical data.

Based on the provided document, I can primarily address the information regarding non-clinical testing acceptance criteria and studies. The questions related to AI/ML specific performance, such as MRMC studies, expert ground truth adjudication, and training/test set details, are not applicable to this specific submission as there is no mention of AI/ML components in the "Align Lumbar Interbody Fusion System."

Here's an analysis of what is available in the document regarding acceptance criteria and studies:

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

The document broadly states that the device met acceptance criteria, especially for bench testing. However, it does not provide a specific table detailing numerical acceptance criteria and corresponding reported performance values. This level of detail is typically found in the full submission, not in the publicly available 510(k) summary.

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

• Test Set (for physical device testing): Not explicitly stated in terms of a "sample size" like one would for a clinical study. For bench testing, typically a certain number of samples per configuration are tested (e.g., 6 or 12 per test type). This detail is not provided in a summary.
• Data Provenance: The studies are laboratory-based bench tests and biocompatibility tests, not clinical data from patients. Therefore, terms like "country of origin" or "retrospective/prospective" are not applicable in this context.

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):

• Not Applicable: This submission relies on engineering and material science standards (ASTM, ISO), not expert clinical reviews for "ground truth". The "ground truth" for these tests is generally defined by the parameters and methodologies outlined in the referenced standards.

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

• Not Applicable: Adjudication methods like 2+1 or 3+1 are used in clinical studies, particularly for imaging interpretation, to resolve discrepancies between readers. This is not relevant for bench testing.

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: The document states, "No clinical data was provided to demonstrate substantial equivalence." This implies no human reader studies of any kind were performed for this submission, negating the possibility of an MRMC study related to AI assistance.

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

• Not Applicable: This device is an implantable medical device (intervertebral body fusion system), not a software algorithm or AI-powered system. No standalone algorithm performance was assessed.

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

• Bench Testing Standards & Specifications: For the non-clinical tests, the "ground truth" is adherence to the specified engineering standards (e.g., ASTM F2077, ASTM F2267) and biocompatibility standards (ISO 10993 series), and comparison to the performance of the predicate device. The goal is to show that the device performs mechanically as intended and is biocompatible, similar to existing devices.

8. The sample size for the training set:

• Not Applicable: As this is a physical medical device and not an AI/ML system, there is no "training set."

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

• Not Applicable: No training set exists for this device.

In summary: The provided document describes a 510(k) submission for a physical implantable device. The "acceptance criteria" and "proof" primarily stem from meeting established international and national standards for biocompatibility and mechanical performance, and demonstrating equivalence to predicate devices through laboratory bench testing. The questions related to AI/ML performance, clinical studies, and expert ground truth are not applicable to the information contained within this specific 510(k) summary.

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The AlignRT Plus system is indicated for use to position and monitor patients relative to the prescribed treatment isocentre, and to withhold the beam automatically during radiation delivery.

For cranial treatments, a manual head adjuster is included which can be used in concert with AlignRT Plus to provide fine corrections for pitch, roll and yaw rotations.

AlignRT Plus is also used to track the patient's respiratory pattern for respiratory synchronized image acquisition, and radiation therapy treatment.

Patient contour data can be extracted and exported from the data acquired for the purpose of treatment planning.

AlignRT Plus can be calibrated directly to the treatment beam isocentre and in turn assists in performing quality assurance on MV, kV imagers, room lasers and the treatment couch.

AlignRT Plus is indicated for use during simulation, setup and stereotactic radiosurgery and precision radiotherapy for lesions, tumors and conditions anywhere in the body where radiation is indicated.

The AlignRT Plus system (K203387) is a combination of the devices AlignRT, GateCT and GateRT.

AlignRT Plus is a video-based three-dimensional (3D) surface imaging system, which is used to image the skin surface of a patient in 3D before and during radiotherapy treatment. The system consists of advanced software, a computer workstation, and one, two or three 3D camera units (each camera unit comprising a stereo pair of sensors to allow 3D surface reconstruction). The system is non-invasive, does not require the use of body markers and produces no ionizing irradiation during the imaging process.

AlignRT Plus is also able to perform both respiratory synchronised CT imaging and treatment delivery. In both instances, the system acquires a gated 3D surface model of the patient. User selected points are then tracked in real time in order to provide gating and position monitoring signals.

Real-time imaging and surface matchinq of the patient is possible during both setup and the treatment delivery to determine any patient movement. During treatment delivery, AlignRT Plus is also able to withhold the beam automatically, should the patient move outside user-defined tolerances.

Patient contour data may be extracted from surface data acquired by the system and exported for the purpose of treatment planning by radiotherapy professionals.

AlignRT Plus may be calibrated directly to the treatment beam isocentre using an optional custom designed calibration phantom and image processing software. It can analyse MV and kV digital imaging data acquired by other cleared devices. This in turn assists the user in performing quality assurance on MV, kV imagers, room lasers and the treatment couch.

The AlignRT Plus system includes the optional Head Adjuster for cranial treatments to allow for the manual, fine correction of pitch, roll and yaw in the patient's head position.

Precise isocenter calibration and the optional Head Adjuster provide improved frameless Stereotactic Radiosurgery (SRS). This is provided with the brand name "AlignRT SRS module".

The AlignRT Plus system is also provided under the brand OSMS (Optical Surface Monitoring System). This product is identical to AlignRT.

This 510(k) is requested for a modifications to FDA 510(k) cleared product "AlignRT Plus" (K203387).

This 510(k) is to obtain clearance for the following changes to the cleared device:

• Introduction of new software, SimRT 7.2. This is an updated version of the cleared software, GateCT, with a new user interface similar to the cleared AlignRT 6.2/6.3/6.4 software;
• 2. Introduction of new camera pods (hardware). These function in the same way as the currently cleared hardware but are aesthetically different and have upgraded capabilities to support future product development;
• 3. Improve the product's accuracy claim for Source-Surface Distancing (SSD) from <2.0mm to <0.2mm.

The provided text is a 510(k) Premarket Notification for the AlignRT Plus system. It details modifications to an already cleared device. The key information regarding acceptance criteria and device performance is found under the "System Performance and Accuracy" section within the "Summary of the Technological Characteristics" table.

Here's a breakdown of the requested information 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:

The document mentions that the changes were tested with "test method and acceptance criteria as the predicate device," but it does not explicitly state the sample size used for the test set or the data provenance (e.g., country of origin, retrospective/prospective study). The study appears to be a technical verification and validation of changes to functionality and hardware.

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

The document does not mention the use of experts to establish ground truth for the test set. The performance metrics appear to be based on physical measurements using calibration phantoms and internal system testing.

4. Adjudication Method for the Test Set:

The document does not describe an adjudication method for the test set, as the testing appears to be highly technical and objective (measurements against known standards/phantoms) rather than subjective expert review.

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

The document does not indicate that a multi-reader multi-case (MRMC) comparative effectiveness study was done. The device is an objective measurement system for patient positioning and monitoring, not an image interpretation or diagnostic aid that would typically involve human readers. Therefore, an effect size of human readers improving with AI assistance is not applicable in this context.

6. Standalone (Algorithm Only) Performance:

The provided information focuses on the integrated system's performance, as the system consists of hardware (cameras) and software working together to deliver the stated functionalities. The performance metrics (positioning accuracy, surface displacement, SSD accuracy) inherently describe the algorithm's capability within the system context. However, it's not explicitly presented as a separate "algorithm-only" study with distinct metrics from the integrated device.

7. Type of Ground Truth Used:

The ground truth for the performance evaluations (positioning accuracy, surface displacements) appears to be based on physical measurements using a custom-designed calibration phantom. For respiratory tracking, it's based on the system's ability to track "user selected points" and real-time 3D surface models. For the improved SSD accuracy, it's also likely a technical measurement against a known standard.

8. Sample Size for the Training Set:

The document does not specify a training set sample size. The nature of the device (surface imaging and tracking) suggests it may rely on established physics and geometric principles rather than a large, data-driven machine learning model that requires explicit training sets in the same manner as a diagnostic imaging AI. The "software" updates mentioned (SimRT 7.2) are described as an updated version with a new user interface, not necessarily a re-trained AI model from a new dataset.

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

As no explicit training set or AI model requiring such a set is detailed, the document does not provide information on how ground truth for a training set was established.

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