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The Velocity Alpha™ Drill System is indicated for trepanating, incision, cutting, removal, shaping, sawing of soft and hard tissue, bone, and bone replacement materials.
Applications: Cutting, removing, shaping and sawing hard and soft tissue, bone, and bone replacement materials.
Areas of use: Neurosurgery and spinal surgery.

The Velocity Alpha™ Highspeed Surgical Drill System is an electric AC powered surgical motor drill system for rapid cutting, sawing, drilling and manipulation of soft tissue and bone.
The Subject Device has several components, such as an electric motor hand piece connected to and driven by an AC-powered control unit, a foot control unit (wired or wireless (Bluetooth)) and several adapters and nosepiece attachments, e.g. straight & angled nosepiece attachments, craniotome attachments, speed reducer attachments and sawing attachments.
The device has an optional irrigation pump that can supply irrigation through sterile tubing. Speed is variable from 1.000 RPM up to 80.000 RPM in order to adjust the speed to the surgeon's requirements. The direction of rotation can be pre-selected to the left and to the right.

The provided text describes the "Velocity Alpha Highspeed Surgical Drill System" and presents a summary of its substantial equivalence to a predicate device, including performance data. However, it does not contain a typical study design with acceptance criteria and results in the format implied by your request for "device performance" in relation to specific clinical outcomes or diagnostic accuracy.

The document primarily focuses on demonstrating substantial equivalence to a predicate device for regulatory clearance (510(k)). The "Performance data testing" section refers to engineering and functional tests rather than clinical studies or those involving expert review of diagnostic output.

Here's an analysis of the provided information based on your requested headings:

1. Table of Acceptance Criteria and Reported Device Performance

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

This document does not specify a "test set" in the context of clinical data, diagnostic images, or patient-specific results. The performance data presented are for the device itself (e.g., motor speed, temperature, electrical safety). Therefore, there is no information on sample size or data provenance in that regard.

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

Not applicable. The "ground truth" for the engineering performance tests (motor speed, temperature, etc.) would be established by technical specifications and validated measurement equipment, not by clinical experts.

4. Adjudication Method for the Test Set

Not applicable. There is no mention of adjudication, as the tests performed are technical and do not involve subjective interpretation.

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 does not describe any studies comparing human reader performance with or without AI assistance.

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

Not applicable. This device is a surgical drill system, not an AI algorithm or diagnostic tool. The performance tests are for the physical device's operation.

7. The Type of Ground Truth Used

The ground truth for the performance data testing was based on technical specifications and established international standards (e.g., IEC 60601-1, IEC 60601-1-2) which define acceptable limits for motor speed, torque, temperature, noise, electrical safety, and electromagnetic compatibility.

8. The Sample Size for the Training Set

Not applicable. This device is a mechanical/electrical surgical system and does not utilize a "training set" in the AI/machine learning sense.

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

Not applicable for the same reason as above.

Summary of the Study that Proves the Device Meets the Acceptance Criteria:

The document describes a series of engineering and functional performance tests conducted on the Velocity Alpha Highspeed Surgical Drill System. These tests evaluated various technical aspects of the device, including:

• Motor speed and torque analysis: To confirm the motor performs within its specified range.
• Temperature analysis: To ensure the motor temperature remains within safe and specified limits during activity.
• Lifetime testing: To verify the system's durability and functionality over its expected operational lifespan.
• Noise level analysis: To confirm the noise generated by the device does not exceed specified limits.
• Electrical Safety testing: Conducted to ensure compliance with IEC 60601-1:2005, a standard for medical electrical equipment safety.
• Electromagnetic Compatibility (EMC) testing: Conducted to ensure compliance with IEC 60601-1-2:2014, a standard for EMC of medical electrical equipment.
• Wireless Foot Control testing: Included software verification/validation (IEC 62304:2006), EMC (IEC 60601-1-2:2007), and Electrical Safety (IEC 60601-1-1:2005) tests.
• Software Validation: Met requirements according to IEC 62304:2006.
• Biocompatibility testing: Performed on patient-contacting components (attachments/nosepieces) to meet ISO 10993 and EN ISO 10993-1 requirements.

Conclusion of the study: All tests "Passed," indicating that the device met its specified technical and safety acceptance criteria, demonstrating its substantial equivalence to the predicate device (Aesculap ELAN 4 Electro Motor System) based on technological characteristics, functionality, and intended use, without negative effects on safety or effectiveness. The document explicitly states "No clinical data is required for this device classification submission."

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Velocity is a software package that provides the physicians a means for comparison of medical data including imaging data that is DICOM compliant. It allows the display, annotation, volume rendering, registration, and fusion of medical images as an aid during use by diagnostic radiology, radiation therapy planning and other medical specialties. Velocity is not intended for mammography.

Velocity is a software application providing relevant tools for Radiotherapy professionals to use while creating treatment plans. The Velocity device is a Picture Archiving and Communication System (medical imaging software). Velocity provides medical image processing designed to facilitate the oncology or other clinical specialty work flow by allowing the comparison of medical imaging data from different modalities, points in time, and / or scanning protocols. The product provides users with the means to display, co-register and analyze medical images from multiple modalities including PET, SPECT, CT, RT Dose and MR; draw Regions of Interest (ROI), calculate and report relative differences in pixel intensities, Standardized Uptake Value (SUV) or other values within those regions; and import / export results to/from commercially available radiation treatment planning systems and PACS devices. Co-registration includes deformable registration technology that can be applied to DICOM data including diagnostic and planning image volumes, structures, dose, and automatic anatomical atlas-based segmentation tools. Velocity is used as a stand-alone application on recommended Off-The-Shelf (OTS) computers supplied by the company or by the end-user.

The provided document is a 510(k) Premarket Notification for the "Velocity" software. It focuses on demonstrating substantial equivalence to a predicate device ("Velocity AI – K081076") and does not contain detailed information about specific acceptance criteria, test set sizes, expert qualifications, or comparative effectiveness studies typically associated with proving a device meets strict performance benchmarks via a clinical study with AI components.

However, based on the information provided, we can infer some aspects and highlight what is explicitly stated:

Key Takeaways from the Document:

• Device Type: Velocity is a "Picture Archiving and Communication System (Medical Imaging Software)" designed for display, annotation, volume rendering, registration, and fusion of medical images for diagnostic radiology, radiation therapy planning, and other medical specialties.
• Predicate Device Approach: The submission relies on demonstrating "substantial equivalence" to a legally marketed predicate device (Velocity AI – K081076) and a secondary predicate for a specific feature (MIM Y90 Dosimetry - K172218).
• No Clinical Tests: The document explicitly states: "No clinical tests have been included in this pre-market submission." This immediately tells us that the detailed performance studies often associated with AI/ML model validation (e.g., MRMC studies, standalone performance with robust ground truth) were not part of this submission for the core functionality.
• Software Verification & Validation (V&V): The primary performance data cited is "Software Verification and Validation Testing," indicating a focus on functional correctness, reliability, and safety of the software rather than a direct clinical performance evaluation. The software was considered a "major" level of concern.
• Ground Truth: Given no clinical tests, there's no mention of how ground truth for a test set was established using expert consensus, pathology, or outcomes data for clinical performance metrics. The ground truth for V&V would be tied to software requirements and specifications.
• AI/ML Context: While "AI" is in the predicate device name ("Velocity AI"), the listed functionalities of "Velocity" (display, annotation, volume rendering, registration, fusion) are standard PACS and image processing features. The "deformable registration technology" and "automatic anatomical atlas-based segmentation tools" could be considered AI/ML elements, but the document does not detail specific performance studies of these elements with clinical ground truth.

Based on the available text, here's an attempt to answer your questions. Please note that many answers will state that the information is "Not provided" or "Not applicable" due to the nature of this 510(k) submission, which did not include clinical performance studies.

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

The document does not provide a specific table of acceptance criteria with corresponding reported device performance metrics in the way a clinical study typically would (e.g., sensitivity, specificity, F1-score for an AI component). The performance data cited is:

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

• Sample Size for Test Set: Not specified. As "No clinical tests have been included," there isn't a "test set" in the context of clinical performance evaluation using patient data for AI validation. The V&V would use internal test cases.
• Data Provenance: Not specified.

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. Since no clinical tests were performed for the submission, there is no mention of external experts establishing ground truth for a clinical test set.

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

• Not applicable. No clinical tests were performed.

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 explicitly states: "No clinical tests have been included in this pre-market submission." Therefore, an MRMC comparative effectiveness study was not performed or submitted.

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

• Not specified in a clinical performance context. While the software operates "as a stand-alone application," this refers to its deployment rather than a standalone algorithmic performance study against clinical ground truth. The V&V process would have involved testing the algorithm's functional performance against specified requirements.

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

• For Software Verification and Validation: The ground truth would be defined by the software requirements and specifications (e.g., expected output for given input, correctness of calculations, proper display of images). This is a technical ground truth, not a clinical one derived from patient outcomes or expert consensus on a diagnosis.
• For Clinical Performance: Not applicable, as no clinical tests were performed.

8. The sample size for the training set

• Not specified. The document does not describe the development or training of any AI/ML components beyond mentioning "deformable registration technology" and "automatic anatomical atlas-based segmentation tools." No information is provided regarding the training data or its size.

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

• Not specified. As there is no information on a specific training set or the development process for embedded AI/ML features, how any training ground truth was established is not detailed.

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VelocityAIS (VelocityAI) is a stand-alone software product that provides the physician a means for comparison of medical imaging data from multiple DICOM conformant imaging modality sources. It allows the display, annotating, volume rendering, registration and fusing of medical images as an aid during use by diagnostic radiology, oncology, radiation therapy planning and other medical specialties. VelocityAIS (VelocityAI) is not intended for mammography diagnosis.

Version 2.0 of VelocityAIS, also marketed as VelocityAI with this version, is a stand-alone software product that provides medical image processing designed to facilitate the oncology or other clinical specialty work flow by allowing the comparison of medical imaging data from different modalities, points in time, and/or scanning protocols. The product provides users with the means to display, co-register and fuse medical images from multiple modalities including PET, SPECT, CT, and MR, draw Regions of Interest (ROI), calculate, and report relative differences in pixel intensities, Standardized Uptake Value (SUV) or other values within those regions, and import and export results to and from commercially available radiation treatment planning systems and PACS devices. Version 2.0 of the product contains the additional features of: Automated deformable registration. Anatomical atlas based segmentation tools. Operating systems compatibility with MicroSoft Windows XP Home and Professional (Service Pack 2), MicroSoft Vista Home and Professional, Linux (CentOS) and MacOSX (Leopard). VelocityAIS (VelocityAI) is used as a stand-alone application on recommended Off-The-Shelf (OTS) computers supplied by the company or by the end-user.

The provided document is a 510(k) Pre-Market Notification Summary for the VelocityAIS (also "VelocityAI") software, version 2.0. This document primarily focuses on establishing substantial equivalence to predicate devices for regulatory clearance, rather than detailing a specific clinical study with granular performance metrics and acceptance criteria for a novel device function.

Here's a breakdown of the requested information based on the provided text, and explicit statements about what is not available in this document:

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

Explanation: The document states that the software "meets its functional specifications and performance requirements" but does not provide a table of quantifiable acceptance criteria (e.g., sensitivity, specificity, accuracy, precision, processing speed) or specific numerical performance results. The core of this 510(k) is about demonstrating substantial equivalence to existing predicate devices, implying that its performance is equivalent or better without introducing new safety/effectiveness concerns.

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

• Sample Size for Test Set: Not mentioned in the provided text.
• Data Provenance: Not mentioned in the provided text. The document describes the software's capabilities with "medical imaging data from multiple DICOM conformant imaging modality sources" but does not specify the origin or nature of the data used for verification/validation.
• Retrospective/Prospective: Not mentioned in the provided text.

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 mentioned in the provided text. The document focuses on software functionality and comparison to predicate devices, not on the details of a clinical reader study or the establishment of ground truth by experts.

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

• Not mentioned in the provided text.

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 mentioned in the provided text. This 510(k) summary does not describe an MRMC comparative effectiveness study or the impact of AI assistance on human readers. The device is described as "medical image processing designed to facilitate the oncology or other clinical specialty work flow" and providing "a means for comparison of medical imaging data," but it doesn't quantify improvements in human reader performance.

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

• The document describes the device as a "stand-alone software product" that provides image processing capabilities, implying its functionality without direct human intervention in its core processing. However, it's an "aid during use by diagnostic radiology, oncology, radiation therapy planning and other medical specialties," meaning human experts interpret the output.
• Performance of the algorithm only (e.g., specific metrics for deformable registration or segmentation accuracy): Not explicitly detailed in the provided text. The claim is general: "verified and validated that the VelocityAIS (VelocityAI) software meets its functional specifications and performance requirements."

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

• Not mentioned in the provided text.

8. The sample size for the training set

• Not mentioned in the provided text. The document does not describe the training of any AI/ML models, though it mentions "Automated deformable registration" and "Anatomical atlas based segmentation tools" which could imply the use of such models.

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

• Not mentioned in the provided text.

In summary, the provided 510(k) document is a regulatory submission focused on substantial equivalence. It confirms that the manufacturer verified and validated the software's functional specifications and performance requirements. However, it does not contain the detailed clinical study information (e.g., specific acceptance criteria, sample sizes, ground truth establishment, expert qualifications, or comparative effectiveness study results) that is typically found in a clinical validation report for a device with advanced diagnostic capabilities. This type of information is often provided in more detailed validation reports or during later clinical trials, which are not part of this initial 510(k) summary for a "Picture Archiving and Communication System (Medical Imaging Software)" with image processing features.

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VelocityAIS is a stand-alone software product that provides the physician a means for comparison of medical imaging data from multiple DICOM conformant imaging modality sources. It allows the display, annotating, volume rendering, registration and fusing of medical images as an aid during use by diagnostic radiology, oncology, radiation therapy planning and other medical specialties. VelocityAIS is not intended for mammography diagnosis.

VelocityAIS is a stand-alone software product that provides medical image processing designed to facilitate the oncology or other clinical specialty work flow by allowing the comparison of medical imaging data from different modalities, points in time, and/or scanning protocols. The product provides users with the means to display, co-register and fuse medical images from multiple modalities including PET, SPECT, CT, and MR, draw Regions of Interest (ROI), calculate, and report relative differences in pixel intensities, Standardized Uptake Value (SUV) or other values within those regions, and import and export results to and from commercially available radiation treatment planning systems and PACS devices. VelocityAIS is used as a stand-alone application on recommended Off-The-Shelf (OTS) computers supplied by the company or by the end-user.

Here's a breakdown of the acceptance criteria and the study information for K070248 (Velocity AIS), based on the provided text:

Important Note: The provided document is a 510(k) summary for a pre-market notification, not a detailed study report. As such, it primarily focuses on establishing substantial equivalence to predicate devices and demonstrating that the software meets its functional specifications. It does not contain extensive details about clinical performance studies with specific statistical acceptance criteria for diagnostic accuracy, reader studies, or detailed ground truth methodologies that would be typical for a device making a diagnostic claim based on AI.

Acceptance Criteria and Reported Device Performance

The document does not explicitly present specific numerical "acceptance criteria" for diagnostic performance (e.g., sensitivity, specificity, AUC) or a comparative table of "reported device performance" against such criteria.

Instead, the core of the acceptance criteria for this 510(k) is based on:

• Functional Specifications and Performance Requirements: The device must meet its own defined functional specifications and performance requirements.
• Substantial Equivalence: The device must be demonstrated as "substantially equivalent" to legally marketed predicate devices, meaning it is similar in characteristics, materials, features, technological features, intended use, and indications for use, and does not pose any new issues of safety and effectiveness.

The reported device "performance" is implicitly stated as:

Study Details (Based on available information)

Given the nature of the 510(k) summary, specific details about "studies" in the context of diagnostic accuracy or deep learning models are limited. The provided text describes primarily the verification and validation (V&V) of the software's functional specifications and its comparison to predicate devices, rather than a clinical performance study as one might expect for a new diagnostic AI.

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

  • Sample Size: Not specified for any "test set" in the context of diagnostic performance. The document only mentions "medical imaging data from multiple DICOM conformant imaging modality sources."
  • Data Provenance: Not specified. No mention of country of origin or whether the data was retrospective or prospective.

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

  • Not specified. There is no mention of experts or ground truth establishment for a diagnostic test set. The validation seems to be primarily functional.

• 4. Adjudication method for the test set:

  • Not specified. This is not applicable given the lack of detail on a diagnostic test set and ground truth establishment.

• 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, an MRMC comparative effectiveness study is not mentioned or described. The device is characterized as aiding "during use by diagnostic radiology, oncology, radiation therapy planning and other medical specialties," but no study on human reader improvement with or without AI assistance is detailed.

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

  • The document states, "VelocityAIS is a stand-alone software product." This implies independent functionality. However, it's not a "standalone performance study" in the sense of an algorithm making a diagnostic claim without human oversight. Its stated use is "as an aid" for physicians, suggesting a human-in-the-loop model for clinical decision-making. No metrics for standalone diagnostic accuracy are provided.

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

  • Not specified in the context of clinical or diagnostic performance. The ground truth refers to whether the software meets its internal "functional specifications and performance requirements," rather than a clinical truth.

• 8. The sample size for the training set:

  • Not applicable/not specified. This device predates the widespread use of deep learning in medical imaging diagnostics for which a "training set" of patient data would be a primary concern. Its function involves image display, co-registration, fusion, ROI drawing, and calculation, which are rule-based software functionalities, not statistical learning from a large training dataset.

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

  • Not applicable/not specified, for the same reasons as #8. Ground truth for training would not be relevant for this type of software as described.

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The Velocity Advantage would be used by a physician in conjunction with standard vitrectomy equipment to cut and remove vitreous and other intraocular tissue.

Not Found

The provided text is a 510(k) clearance letter from the FDA for the "Velocity Advantage" device. It does not contain any information about acceptance criteria, device performance studies, sample sizes, expert qualifications, or ground truth methodologies.

The letter primarily confirms that the device is substantially equivalent to a predicate device and can therefore be marketed. It lists the device name, a brief indication for use, and regulatory information.

Therefore, I cannot extract the requested information from this document.

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