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The Planmed Clarity 2D and S mammography units acquire digital 2D mammographic images. The Planmed Clarity 2D and S systems are intended to be used for screening and diagnosis of breast cancer. The Planmed Clarity 2D and S systems may also be used for additional diagnostic workup of the breast. Additionally, the Planmed Clarity 2D and S systems can be used to provide digital x-ray images of breast biopsy specimens.

The Planmed Clarity 2D and Clarity S are Full Field Digital Mammography (FFDM) systems for generating mammographic x-ray images that can be used for screening and diagnosis of breast cancer. Planmed Clarity 2D and Clarity S utilize an amorphous silicon based digital image receptor to capture images. The receptor directly converts the incoming X-ray photons to digital image data.

The workflow with Clarity 2D is controlled by the side displays/touch panels and the workflow of Clarity S is controlled from the acquisition workstation and Clarity Manager acquisition and communications software. The patient information is entered manually or received from the hospital, radiology, or mammography information systems (HIS, RIS, or MIS, respectively), as a format of modality worklist. Subsequently, the images are acquired, processed, and displayed for preview. After initial evaluation by the user, the images are either printed or transferred for soft-copy review.

Acceptance Criteria and Study for Planmed Clarity 2D and S

This response synthesizes the information provided about the Planmed Clarity 2D and S mammography systems, focusing on the acceptance criteria and the studies conducted to demonstrate compliance.

1. Table of Acceptance Criteria and Reported Device Performance

The provided document primarily details performance testing rather than explicitly stated acceptance criteria with numerical targets. However, based on the descriptions, we can infer the acceptance criteria. The device's performance is deemed acceptable if it meets these inferred criteria and demonstrates clinical image quality comparable to the predicate device.

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

• Test Set Sample Size: 6 patients particpated in routine breast cancer screening. The clinical evaluation used images from these 6 patients, with some cases also including diagnostic mammograms (spot and/or magnification images).
• Data Provenance: The data was obtained from two sites: one in Belgium and one in Bulgaria. The study appears to be prospective in nature, as images were "taken at one site in Belgium and one site in Bulgaria where altogether 6 patients participated to routine breast cancer screening."

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

• Number of Experts: Three
• Qualifications: "MQSA qualified experienced US interpreting physicians independently."

4. Adjudication Method for the Test Set

The document states, "The images were then reviewed by three MQSA qualified experienced US interpreting physicians independently." This indicates that there was no formal adjudication method (e.g., 2+1 or 3+1 consensus) described. Each expert provided an independent assessment, and the aggregate finding (all images rated good or excellent) was reported.

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

No, a formal MRMC comparative effectiveness study comparing human readers with AI assistance versus without AI assistance was not described in the provided text. The study primarily focused on the standalone performance of the image processing algorithm and its impact on image quality for human interpretation. The clinical image evaluation assessed if the image quality produced by the new software was acceptable for human readers, not whether AI assistance improved human performance.

6. Standalone Performance Study

Yes, a standalone performance evaluation of the new image processing algorithm (CORE) was implicitly performed. While not in the context of a "standalone algorithm" in isolation from the hardware, the "Clinical image evaluation" aimed to determine if the images processed with the new Planmed CORE software algorithm were of "sufficiently acceptable quality for mammographic usage when reviewed by MQSA qualified experienced interpreting physicians." This assesses the algorithm's output quality as a standalone component contributing to the overall system's diagnostic utility. The physical laboratory testing also evaluates the image chain, including the processing, in a standalone manner from actual diagnostic human interpretation.

7. Type of Ground Truth Used

For the clinical image evaluation, the "ground truth" used for assessing image quality was expert consensus on image quality acceptability. The experts rated images as "good" or "excellent," and the overall judgment ("acceptable for all cases and image types") served as the ground truth criterion. The selection of cases with BI-RADS score 1 or 2 suggests that the intent was to evaluate images from non-cancerous breasts (or breasts with benign findings) to assess general image clarity, rather than a diagnostic accuracy study where pathology or outcomes data would be directly compared.

8. Sample Size for the Training Set

The document does not provide information regarding the sample size for a training set for the CORE image processing algorithm. The algorithm is described as "developed by Planmed in-house," but details on its development data (training, validation, testing) are not included in this summary.

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

As no information is provided about a training set, the method for establishing its ground truth is not described in the document.

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Planmed Verity is intended to be used for X-ray computed cone beam tomography imaging of anatomies within upper and lower extremities, head and neck.

The Planmed Verity is a cone beam computed tomography x-ray system for generating 3D imaging scans of extremity, head and neck anatomies. The Planmed Verity utilizes an amorphous silicon based digital image receptor to capture digital images. The toroidal shaped gantry includes a rotating x-ray source combined with a flat panel image receptor. The scan rotation angle is less than a full circle and during the scan 300 to 400 projection images are being acquired. The receptor directly converts the incoming X-ray photons to digital image data. Projection image data is used to generate a 3D image volume of the anatomy through a reconstruction software algorithm.

The provided text is a 510(k) summary for the Planmed Verity CBCT system. It focuses on demonstrating substantial equivalence to a predicate device, primarily through performance data related to new software features.

Based on the provided document, here's an analysis of the acceptance criteria and the study proving the device meets them:

1. Table of Acceptance Criteria and Reported Device Performance

The document doesn't explicitly present a formal table of quantitative acceptance criteria with corresponding performance metrics like sensitivity, specificity, or AUC, as might be found for an AI diagnostic algorithm. Instead, the acceptance is demonstrated qualitatively and through the clinical evaluation of specific new software features.

The key reported performance is:

• Overall image quality was acceptable for all cases and image types.
• The clinical image quality of the eFoV feature outside the primary field of view is of lower image quality and offers visualization aid, not diagnostic value. (This is a self-acknowledged limitation rather than a "performance metric" per se but is crucial for labeling).
• The new software features have acceptable image quality.

2. Sample Size and Data Provenance

• Test Set Sample Size: The document states "a number of sample scans and diagnostic images." The exact number is not specified.
• Data Provenance: Not explicitly stated, but given the manufacturer (Planmed Oy, Finland) and the context of a 510(k) submission, it's highly likely the data originated from a clinical setting, potentially in Finland or Europe. There is no information on whether it was retrospective or prospective.

3. Number of Experts and Qualifications

• Number of Experts: Two
• Qualifications: "Two experienced radiologists"

4. Adjudication Method for the Test Set

• The radiologists "studied independently" the images and "scored different essential image quality related items."
• "The results have been summarized in a clinical study report."
• There is no explicit mention of an adjudication method (e.g., 2+1, 3+1 consensus). The phrasing "studied independently" suggests individual scoring, followed by a summary, but not necessarily a formal consensus process for discrepancies.

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

• No, an MRMC comparative effectiveness study was not done in the sense of evaluating human readers' improvement with AI vs. without AI assistance.
• The clinical evaluation focused on the image quality produced by the new software features themselves, as assessed by radiologists, not on how these features assisted radiologists in a diagnostic task. The AI here is integrated into the reconstruction and image enhancement, not necessarily a separate diagnostic aid.

6. Standalone (Algorithm Only) Performance

• Implicitly, yes, to the extent that the radiologists were evaluating the image output of the algorithms directly. The "new software features eFoV, improved CALM motion blur reduction, MAR improved metal artefact removal and stitching algorithm performance have been clinically evaluated." This involved the output of the algorithms being presented to experts for assessment of "image quality related items." This is not a quantitative standalone diagnostic performance (e.g., classifying disease), but rather an assessment of the quality of the images produced by the algorithms.

7. Type of Ground Truth Used

• Expert Consensus/Opinion on Image Quality: The "ground truth" here is the qualitative assessment of image quality by two experienced radiologists. This is not pathology, outcomes data, or consensus on disease presence/absence, but rather expert subjective evaluation of the technical and diagnostic quality of the images generated by the new algorithms.

8. Sample Size for the Training Set

• Not specified. The document focuses on the evaluation of the software features, not on the training of any underlying machine learning models. It's possible that these "new software features" (eFoV, CALM, MAR, stitching) are based on traditional image processing algorithms rather than deep learning, in which case a "training set" in the common AI sense might not apply, or was part of internal development.

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

• Since the training set size is not specified, and the nature of the "new software features" is not detailed (e.g., if they are AI/ML based), the method for establishing ground truth for a training set is not provided in this document.

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The Planmed Clarity 2D and Planmed Clarity S mammography units acquire digital 2D mammographic images. The Planmed Clarity 2D/S systems are intended to be used for screening and diagnosis of breast cancer. The Clarity 2D/S systems may also be used for additional diagnostic workup of the breast.

The Planmed Clarity 2D and Clarity S are Full Field Digital Mammography (FFDM) systems for generating mammographic x-ray images that can be used for screening and diagnosis of breast cancer. Planmed Clarity 2D and Clarity S utilize an amorphous silicon based digital image receptor to capture images. The receptor directly converts the incoming X-ray photons to digital image data.

The workflow with Clarity 2D is controlled by the side displays/touch panels and the workflow of Clarity S is controlled from the acquisition workstation and Clarity Manager acquisition and communications software. The patient information is entered manually or received from the hospital, radiology, or mammography information systems (HIS, RIS, or MIS. respectively), as a format of modality worklist. Subsequently, the images are acquired. processed, and displayed for preview. After initial evaluation by the user, the images are either printed or transferred for soft-copy review.

Here's a breakdown of the acceptance criteria and study information for the Planmed Clarity 2D and Clarity S device, based on the provided text:

Acceptance Criteria and Device Performance

Study Information

2. Sample Size and Data Provenance for Test Set:

• Sample Size: 6 patients
• Data Provenance: One site in Bulgaria. The cases selected also included diagnostic mammograms (spot and/or magnification images) in addition to routine screening images (BI-RADS score 1 or 2).
• Retrospective/Prospective: The text does not explicitly state if the study was retrospective or prospective. Given that "6 patients participated to routine breast cancer screening" and images were then selected for evaluation, it suggests a prospective acquisition for the purpose of the study.

3. Number of Experts and Qualifications for Ground Truth (Test Set):

• Number of Experts: Two
• Qualifications: MQSA qualified experienced US radiologists.

4. Adjudication Method for Test Set:

• Method: The two MQSA qualified experienced US radiologists reviewed the images independently. There is no mention of a formal adjudication process (like 2+1 or 3+1) if their independent ratings differed. The statement "All images were rated good or excellent" suggests they either agreed or the individual assessments were sufficient.

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

• Was it done?: No, a formal MRMC comparative effectiveness study comparing human readers with AI assistance versus without AI assistance was not performed as described in the provided text. The study focused on physician perception of image quality from the new device rather than reader performance with AI.

6. Standalone (Algorithm Only) Performance Study:

• Was it done?: No, a standalone algorithm-only performance study was not described. The evaluation focused on the overall system's image quality as reviewed by human experts.

7. Type of Ground Truth Used (Test Set):

• Type: The ground truth for the clinical image evaluation was based on expert consensus/review by two MQSA qualified experienced US radiologists, who rated the images as "good or excellent" for mammographic usage. The images themselves were selected based on BI-RADS scores 1 or 2 (indicating negative or benign findings), and some diagnostic mammograms.

8. Sample Size for Training Set:

• The provided text does not mention a training set or any machine learning/AI components requiring a training set. The descriptions relate to the hardware and software of a digital mammography system and its image quality validation.

9. How Ground Truth for Training Set was Established:

• Not applicable, as no training set for a machine learning model is mentioned.

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Planmed Verity is intended to be used for X-ray computed cone beam tomography imaging of anatomies within upper and lower extremities, head and neck.

The Planmed Verity is a cone beam computed tomography x-ray system for generating 3D imaging scans of extremity, head and neck anatomies. The Planmed Verity utilizes an amorphous silicon based digital image receptor to capture digital images. The receptor directly converts the incoming X-ray photons to digital image data.

The workflow with Planmed Verity is controlled from the integrated acquisition workstation and Planmed Verity Manager image acquisition and communications software. The patient information is entered manually or received from the hospital. radiology, or x-ray modality information systems (HIS, RIS, or MIS, respectively), as a format of modality worklist. Subsequently, the images are acquired, processed, and displayed for preview. After initial evaluation by the operator, the images are either printed or transferred for soft-copy review.

The provided text describes the Planmed Verity, a Cone Beam Computed Tomography (CBCT) system, and its comparison to a predicate device for FDA 510(k) clearance. The focus of the changes in the subject device is the inclusion of new image enhancement software (ULD and CALM) and a slightly updated flat panel detector.

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

1. Table of Acceptance Criteria and Reported Device Performance

The document doesn't explicitly state quantitative acceptance criteria in a clear, tabulated format. Instead, it relies on demonstrating equivalence to the predicate device and showing improvements in specific aspects. The primary acceptance criterion seems to be "substantial equivalence" to the predicate device in terms of safety and effectiveness for the stated indications for use, with additional improvements.

2. Sample Sizes and Data Provenance

• Test Set (Clinical Image Evaluation):

  • Sample Size: The document mentions "representative sample scans and diagnostic images" for the clinical image evaluation. It does not provide a specific numerical sample size.
  • Data Provenance: The text does not explicitly state the country of origin or whether the clinical data was retrospective or prospective for the main clinical image evaluation. However, the ULD protocol verification was performed "at a clinic in Helsinki, Finland." The clinical image evaluation was performed with a system not in final form (using 'D' detector instead of 'DX'), suggesting it might have been an early prospective study or an evaluation based on existing data.

• Phantom Study (CALM):

  • Sample Size: Not specified (likely a single phantom with various simulated motion scenarios).
  • Data Provenance: Not specified, likely an in-house laboratory study.

3. Number of Experts and Qualifications for Ground Truth (Test Set)

• Clinical Image Evaluation: "an experienced radiologist" - One expert. Qualifications: "experienced radiologist." No further detail regarding years of experience or subspecialty is provided.
• ULD Protocol Verification: "The radiologists evaluated the clinical image quality..." - Multiple experts (plural "radiologists"). Qualifications: "radiologists." No further details on their experience or subspecialty.

4. Adjudication Method for the Test Set

• The document does not describe an adjudication method like 2+1 or 3+1. For the clinical image evaluation, it states "an experienced radiologist scored representative sample scans." For the ULD protocol, "The radiologists evaluated the clinical image quality." This suggests individual evaluation without a formal multi-reader adjudication process described in the text.

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

• No explicit MRMC comparative effectiveness study is mentioned comparing human readers with AI vs. without AI assistance.
  • The CALM feature study compares imaging quality with CALM vs. without CALM, implying an algorithm performance comparison, not necessarily a human reader performance study with and without that algorithm. It improves image quality, which could indirectly improve human reader performance, but this is not directly assessed in an MRMC setting.
  • The ULD protocol evaluation focused on whether the image quality was "clinically suitable," not on a direct comparison of human diagnostic accuracy with and without ULD-processed images.

6. Standalone (Algorithm Only) Performance Study

• Yes, standalone performance (algorithm only) was implicitly evaluated for the new software features:
  • CALM: The statement "The effectiveness of the CALM feature was additionally verified with imaging a scull phantom with suitable test inserts. Simulated small and large amplitude motion blur as well as step-like distortion was added to the projection images and the effectiveness of the CALM feature to correct the motion blur was verified. Results show that the CALM algorithm clearly reduces motion blur." This is a standalone assessment of the algorithm's ability to correct motion blur using a phantom.
  • ULD: While radiologists evaluated the clinical suitability, the ULD feature itself is an image processing algorithm designed to maintain image quality at lower doses. Its effectiveness in lowering dose while producing acceptable images is a standalone characteristic.

7. Type of Ground Truth Used

• Expert Consensus/Opinion: For the clinical image evaluation, the "experienced radiologist" provided the 'ground truth' by scoring image quality. Similarly, "the radiologists" for the ULD protocol provided their clinical suitability judgment. This relies on expert opinion.
• Phantom Data: For the CALM feature evaluation, the 'ground truth' was derived from the known simulated motion blur introduced into the phantom images. This is a controlled experimental ground truth.
• Non-clinical Physics Data: For the detector comparison, the ground truth was based on objective physical metrics (MTF, DQE, noise performance) provided by the manufacturer (Varex).

8. Sample Size for the Training Set

• The document does not provide information on the sample size used for training the algorithms (ULD noise filtration, CALM motion blur reduction). This is a common omission in 510(k) summaries, which often focus on verification and validation of the final product.

9. How Ground Truth for the Training Set Was Established

• The document does not provide information on how ground truth was established for the training data used for the ULD and CALM algorithms.

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The Planmed Clarity 2D mammography unit acquires digital 2D mammographic images. The Planned Clarity 2D system is intended to be used for screening and diagnosis of breast cancer. The Planmed Clarity system may also be used for additional diagnostic workup of the breast.

The Planmed Clarity is a Full Field Digital Mammography (FFDM) system for generating mammographic images that can be used for screening and diagnosis of breast cancer. The Planmed Clarity utilizes an amorphous silicon based digital image receptor to capture digital images. The receptor directly converts the incoming X-ray photons to digital image data. The workflow with Planmed Clarity is controlled from the acquisition workstation and Planmed Clarity Manager image acquisition and communications software. The patient information is entered manually or received from the hospital. radiology, or mammography information systems (HIS, RIS, or MIS, respectively), as a format of modality worklist. Subsequently, the images are acquired, processed, and displayed for preview. After initial evaluation by the user, the images are either printed or transferred for soft-copy review.

The provided text describes the 510(k) submission for the Planmed Clarity Full Field Digital Mammography (FFDM) system. However, it does not contain information about acceptance criteria or a study proving the device meets those acceptance criteria for an AI/algorithm-based diagnostic device.

The document outlines the testing and performance data for the mammography imaging system itself, focusing on its physical and technical capabilities compared to a predicate device. This includes:

• Biocompatibility testing
• Electrical safety and electromagnetic compatibility (EMC)
• Software Verification and Validation Testing (for the system's software, not an AI algorithm)
• Physical laboratory testing (sensitometric response, spatial resolution, noise analysis, dynamic range, repeated exposures, AEC performance, phantom tests, patient radiation dose, breast compression system)
• Clinical image evaluation by an MQSA certified radiologist to assess overall image quality.

Therefore, I cannot fulfill your request for:

1. A table of acceptance criteria and reported device performance specifically for an AI/algorithm.
2. Sample size used for the test set and data provenance for an AI/algorithm study.
3. Number of experts and their qualifications for AI ground truth establishment.
4. Adjudication method for AI test set.
5. MRMC comparative effectiveness study results for AI assistance.
6. Standalone performance for an AI algorithm.
7. Type of ground truth for AI.
8. Sample size for AI training set.
9. Ground truth establishment method for AI training set.

The document confirms the Planmed Clarity is a mammography imaging system, not an AI diagnostic device. The "Software Verification and Validation Testing" refers to the operational software of the mammography unit, not a separate AI diagnostic algorithm subject to specific diagnostic performance acceptance criteria. The clinical image evaluation mentioned is for the image quality of the output of the imaging system and not for the diagnostic performance of an AI model using those images.

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Planmed Verity is intended to be used for X-ray computed tomography imaging of anatomies within upper and lower extremities and maxillofacial area.

The device is to be operated and used by legally qualified health care professionals.

Planmed Verity utilizes the CBCT (Cone Beam Computed Tomography) technology with a flat panel detector to provide high resolution volumetric images. During image acquisition the detector and X-ray tube perform a single rotation around the target of imaging, during which an amount of snapshot X-ray images are acquired. The X-ray radiation is pulsed so that it is active only when data is collected for the projection images. Before reconstruction, calibration corrections are applied to the image data. The reconstruction is then performed using a dedicated reconstruction engine and algorithm.

The system is designed as a compact, stand-alone unit from which the whole imaging procedure from patient information management to image acquisition, processing and archiving can be performed.

The unit provides a motorized gantry with adjustable height and tilt for the best possible extremity and maxillofacial area positioning. The construction also enables a weight-bearing option, in which the patient stands inside the gantry during image acquisition. Weight-bearing imaging of the extremity shows the anatomy under natural load.

The provided document is a 510(k) summary for the Planmed Verity, a Computed Tomography X-ray System. It describes the device, its intended use, and comparisons to a predicate device, but it does not contain a table of acceptance criteria and reported device performance as requested. Therefore, I cannot generate the table or directly answer some of the specific questions about acceptance criteria in numerical detail.

However, I can extract information related to the studies performed and general conclusions:

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

The document does not provide a table of acceptance criteria with specific thresholds or reported numerical device performance against those criteria. It states: "All results were equivalent or slightly better in Planmed Verity than in the predicate device." and "the imaging performance of Planmed Verity was found both substantially equivalent to the predicate device and sufficient for clinical use." Without specific metrics defined in the document, a table cannot be constructed.

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

• Test Set Description: "A clinical study was completed to evaluate the image quality of Planmed Verity's maxillofacial area. The images for this clinical study were selected from patients imaged as part of normal clinical routine in a university hospital in Finland."
• Sample Size: The sample size for this clinical study is not specified in the provided text.
• Data Provenance:
  • Country of Origin: Finland (university hospital).
  • Retrospective/Prospective: The phrasing "selected from patients imaged as part of normal clinical routine" suggests a retrospective collection of images.

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

This information is not provided in the document.

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

This information is not provided in the document.

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

The document describes a clinical study to evaluate "image quality" and compares the new device to a predicate device, focusing on "imaging performance." It does not mention an AI component or evaluate human reader performance with or without AI assistance. Therefore, an MRMC study comparing human readers with AI assistance was not done based on the provided text.

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

The device is a CT X-ray system, not an AI algorithm. The performance evaluation would be for the imaging system itself, not a standalone algorithm. The clinical study assessed the "image quality" of the system.

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

The document states the clinical study was to evaluate "image quality." It does not explicitly define the "ground truth" method used for this evaluation beyond stating that the "results show that the imaging position... gives a clinically sufficient image quality." This usually implies expert assessment/consensus of the images for diagnostic quality, but the specifics are not detailed.

8. The sample size for the training set

This information is not applicable as the document describes a CT imaging device evaluation, not a machine learning model's training set.

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

This information is not applicable for the same reason as point 8.

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Planmed Verity is intended to be used for X-ray computed tomography imaging of anatomies within upper and lower extremities.

The use of Planmed Verity X-ray unit is allowed only under supervision of a health care professional.

Planmed Verity utilizes the CBCT (Cone Beam Computed Tomography) technology with a flat panel detector to provide high resolution volumetric images. During image acquisition the detector and X-ray tube perform a single rotation around the target of imaging, during which an amount of snapshot X-ray images are acquired. The X-ray radiation is pulsed so that it is active only when data is collected for the projection images. Before reconstruction, calibration corrections are applied to the image data. The reconstruction is then performed using a dedicated reconstruction engine and algorithm.

The system is designed as a compact, stand-alone unit from which the whole imaging procedure from patient information management to image acquisition, processing and archiving can be performed.

The unit provides a motorized gantry with adjustable height and tilt for the best possible extremity positioning. The construction also enables a weight-bearing option, in which the patient stands inside the gantry during image acquisition. Weight-bearing imaging of the extremity shows the anatomy under natural load.

The provided text does not contain acceptance criteria or a study that proves the device meets specific acceptance criteria.

The document is a 510(k) summary for the Planmed Verity device, seeking clearance based on substantial equivalence to a predicate device (Xoran xCATTM). It describes the device's intended use, technology, and comparison to the predicate device.

Here's a breakdown of why the requested information cannot be extracted from the given text:

• No specific acceptance criteria are listed. The document states that "non-clinical studies were completed to compare the imaging performance... The non-clinical comparison included common image quality measures such as high contrast resolution, image noise and Hounsfield Unit (HU) accuracy." However, it does not provide specific thresholds or targets for these measures.
• The "study" is a comparison to a predicate device, not a study demonstrating achievement of specific performance criteria against predefined benchmarks. The conclusion states that the device was found "both substantially equivalent to the predicate device and sufficient for clinical use," implying the predicate device's performance serves as the de facto "acceptance criteria."

Therefore, I cannot provide the requested table or detailed study information. The current document primarily focuses on establishing substantial equivalence rather than detailing an independent study against predefined acceptance criteria for the Planmed Verity.

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Planmed Nuance DigiGuide is an optional system for Stereotactic Biopsy. It consists of a needle guidance unit attached to Planned Nuance or Planmed Nuance Excel digital mammography X-ray units and DigiGuide software module for Nuance Manager 3 acquisition software.

The system is used for needle sampling of women's breast tissues for examination. The use of Planmed Nuance DigiGuide is allowed only under supervision of a health care professional.

Planmed Nuance DigiGuide is a digital biopsy imaging system. This system is compatible with Planmed Nuance and Planmed Nuance Excel FFDM X-ray units. .

The Planmed Nuance DigiGuide system consists of the FFDM X-ray unit (Planmed Nuance or Planmed Nuance Excel) that is equipped with the needle guidance unit and the acquisition workstation (AWS), including a personal computer with the Nuance Manager 3 software, which is used for acquiring mammographic images, determining the lesion coordinates, and taking the biopsy.

This document describes the Planmed Nuance DigiGuide, a stereotactic biopsy system for Full Field Digital Mammography (FFDM). The submission is a 510(k) premarket notification (K121963) to the FDA.

1. Table of Acceptance Criteria and Reported Device Performance

The FDA submission for the Planmed Nuance DigiGuide does not explicitly define quantitative acceptance criteria for its performance. Instead, it relies on a comparison to a predicate device and qualitative assessments.

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

• Sample Size: 20 stereotactic biopsies.
• Data Provenance: Conducted at a mammography screening facility. The information does not explicitly state the country of origin, but the manufacturer is based in Finland. It is a prospective clinical test.

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

The document does not specify the number of experts or their qualifications used to establish ground truth for the 20 stereotactic biopsies. It mentions "a mammography screening facility, which already had long experience in using the previous Planmed DigiGuide system," implying experienced healthcare professionals were involved in the clinical evaluation.

4. Adjudication Method for the Test Set

The document does not explicitly state the adjudication method (e.g., 2+1, 3+1, none) used for the clinical test set. It describes the "end result" of the comparison study, suggesting a consensus or evaluation process by the clinical site's staff.

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 versus without AI assistance?

No MRMC comparative effectiveness study was mentioned. This device is a hardware system for biopsy guidance, not an AI-assisted diagnostic tool for human readers. The clinical test was a comparison of the new hardware system to its predicate, focusing on image quality, accuracy, and reliability during the biopsy procedure.

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

This is not applicable as the Planmed Nuance DigiGuide is a hardware system for biopsy guidance, requiring human operation. It is not an algorithm with standalone performance.

7. The Type of Ground Truth Used

For the clinical study, the "ground truth" was likely defined by the success and accuracy of the biopsy procedure itself, including successful tissue acquisition and the clinical assessment of the system's performance (image quality, accuracy, reliability) by experienced users at the mammography screening facility. It is implied to be expert clinical assessment rather than pathology or outcomes data specifically. The statement "The new Planmed Nuance DigiGuide system was accurate and reliable in clinical use" suggests a clinical consensus on performance.

8. The Sample Size for the Training Set

No training set is mentioned as this device is a hardware system, not a machine learning algorithm requiring a separate training set.

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

Not applicable, as there is no training set for this device.

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The Planmed Sophie Nuance Classic is a mammography x-ray system, which is intended to be used to produce radiographs of the human breast. The device can be equipped with accessories to fulfil different diagnostic needs. Spot mammography is only used in combination with stereotactic needle biopsy guidance.

The Planmed Sophie Nuance Classic is a conventional mammography x-ray system utilizing films and cassettes. This product is a modification of the previous devices Planmed Sophie and Planmed Sophie Classic, where the changes made are concentrated on the lower shelf construction (with easier assembly and better serviceability), a new Flex AEC system, more modern overall design and enhanced user friendliness. The modification also serves as a base to an easy upgradeability to full field digital imaging use in the future.

This document is a 510(k) summary for a mammographic x-ray system, the Planmed Sophie Nuance Classic. It establishes substantial equivalence to previously marketed predicate devices rather than providing information about specific acceptance criteria and a study proving a device meets them.

Therefore, the requested information elements related to acceptance criteria, device performance, study details (sample sizes, data provenance, expert qualifications, adjudication, MRMC, standalone performance), and ground truth establishment are not available in the provided text.

The document primarily focuses on:

• Device Identification: Trade name, common name, classification, regulation number.
• Manufacturer Information: Name, address, contact persons.
• Intended Use: To produce radiographs of the human breast, with accessories for different diagnostic needs.
• Product Description: A conventional mammography x-ray system utilizing films and cassettes, described as a modification of previous Sophie models with improvements in shelf construction, AEC system, design, and user-friendliness, and future upgradeability to digital.
• Substantial Equivalence: A list of predicate devices (Planmed Sophie models) to which the new device is considered substantially equivalent in design, composition, and function, concluding it is "as safe and effective as the predicate devices."
• FDA Correspondence: Official letter from the FDA confirming the substantial equivalence determination and outlining regulatory requirements.

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The Planmed Sophie and Planmed Sophie Classic are Mammographic X-ray Systems, which are intended to be used to produce radiographs of the human breast. The devices can be equipped with accessories to fulfil different diagnostic needs, as spot mammography and stereotactic breast needle biopsy.

Planmed Sophie and Sophie Classic (with Digispot and Cytoguide)

This document is a 510(k) premarket notification acceptance letter for the PlanMed Sophie and Sophie Classic Mammographic X-ray Systems. It does not contain the information requested about acceptance criteria and a study proving a device meets these criteria. This type of information would typically be found in a detailed submission document or a clinical study report, not in the FDA's acceptance letter which only states that the device is substantially equivalent to a legally marketed predicate device.

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