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510(k) Data Aggregation
(909 days)
MEDICSIGHT PLC
Medicsight ColonCAD™ API is a non-invasive computer aided detection (CAD) image analysis software tool designed to assist radiologists in the detection of colorectal polyps during their review of digital images derived from CT colonography (CTC). This CAD software post-processes the CTC image data obtained from multi-detector computed tomography (MDCT) scanners.
The device is intended to be used on patients referred for a CT Colonography examination, as an overlay tool to prompt the radiologist to colonic findings that have been identified by the device. The CAD can assist radiologists after they have made an initial review of all the CTC image data, supporting their evaluation ("second read").
Medicsight ColonCAD API is a medical imaging software tool designed to assist radiologists in the detection of polyps in CT scans of the product is packaged as an Application Programming Interface (API) which allows it to be integrated into existing medical imaging solutions.
The ColonCAD API assists the radiologist in detecting colorectal polyps using mathematical image processing techniques. The CAD assists the radiologist by highlighting potential polyps in 2D and 3D image views. The results are displayed in the form of "CAD marks" on or near the potential polyps. The radiologist must assess every CT scan image to search for polyps and review the CAD marked images to determine if the indicated findings are polyps.
Patient management decisions should not be made solely on the results of ColonCAD analysis.
The information provided details the Medicsight ColonCAD API device, its intended use, and a summary of studies conducted. However, the document does not explicitly state specific acceptance criteria (e.g., a required sensitivity or specificity value) or the reported device performance in a numerical table. It only mentions that the device's accuracy was "significantly higher" with CAD assistance.
Therefore, I cannot populate a table of acceptance criteria and reported device performance with specific numerical values based on this document.
Here's an analysis of the provided information concerning the study:
1. Table of Acceptance Criteria and Reported Device Performance
| Acceptance Criteria | Reported Device Performance |
|---|---|
| Not explicitly stated in the provided document. | Radiologists' accuracy for detecting colorectal polyps of any size was significantly higher with CAD than in the unassisted read, as measured by the segment-level area under the ROC curve (AUC). |
2. Sample Size Used for the Test Set and Data Provenance
- Sample Size for Test Set: Not explicitly stated in the provided document.
- Data Provenance: Not explicitly stated in the provided document (e.g., country of origin, retrospective or prospective).
3. Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications
- Number of Experts: Not explicitly stated in the provided document.
- Qualifications of Experts: Not explicitly stated in the provided document.
4. Adjudication Method for the Test Set
- Adjudication Method: Not explicitly stated in the provided document.
5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study
- Was an MRMC study done? Yes. The document states: "The results of the MRMC study demonstrated that radiologists' accuracy for detecting colorectal polyps of any size was significantly higher with CAD than in the unassisted read, as measured by the segment-level area under the ROC curve (AUC)."
- Effect Size: The document states that accuracy was "significantly higher" with CAD, and mentions "segment-level area under the ROC curve (AUC)" as the metric. However, it does not provide a numerical effect size (e.g., the specific AUC values for assisted vs. unassisted read, or the magnitude of improvement).
6. Standalone Performance Study
- Was a standalone study done? The document focuses on the C-CAD (Computer Aided Detection) device assisting radiologists, implying a human-in-the-loop scenario. While it mentions "internal clinical evaluations" as part of non-clinical studies, it does not detail a standalone algorithm-only performance study with specific metrics. The primary clinical study discussed is an MRMC study evaluating human-in-the-loop performance.
7. Type of Ground Truth Used
- Type of Ground Truth: Not explicitly stated in the provided document for the clinical study. It refers to "detecting colorectal polyps," implying a definitive diagnosis, but the method for establishing this truth is not detailed (e.g., pathology, expert consensus).
8. Sample Size for the Training Set
- Sample Size for Training Set: Not explicitly stated in the provided document. The document mentions the ColonCAD API uses the "same underlying image processing technology" and "same algorithm" as the predicate ColonCAR 1.2 device (K042674), suggesting the training might have occurred prior to this specific API version's development or relies on pre-trained models.
9. How the Ground Truth for the Training Set Was Established
- How Ground Truth Was Established (Training Set): Not explicitly stated in the provided document. As with the test set, the method for establishing the ground truth for training data (if new training was performed) is not detailed.
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(20 days)
MEDICSIGHT
Colon CAR 1.2 is a PC-based, stand-alone, non-invasive, image analysis software application for the display and visualization of 2D and 3D medical image data of the colon derived from CT scans, for the purpose of assisting radiologists and other clinicians in the evaluation of polyps, cancers and other lesions. The software provides functionality for the user to extract the region of interest (ROI) either manually using a drawing tool, or "semi-automatically" through the user selecting single or double seed points followed by interactive fine-tuning the boundaries of the ROI. It also allows for the simultaneous display of supine and prone images.
Colon CAR 1.2 contains additional imaging tools which allow enhancement of specified features, and which the clinician can view simultaneously with the non-enhanced view.
Colon CAR™ (Computer Assisted Reader) 1.2 is a software tool designed to assist radiologists and other clinicians in the evaluation of polyps and other lesions in the colon. The software allows the user to select regions of interest either manually or by selecting a single or double seed point, followed by semi-automatic detection of the ROI boundary. It provides 2D and 3D visualisation of polyps and measurement of polyp characteristics such as size and volume. The further feature of Colon CAR™ 1.2 as compared to the cleared device is a Polyp Enhanced Viewing Filter (PEV), the results of which are presented in a Joint Reader filter view (enhanced and non-enhanced data viewed simultaneously). The PEV filter identifies intra-colonic filling defects protruding into the colonic lumen, thereby highlighting potential polyp candidates for further interrogation by the reporting radiologist. This filter is fully adjustable and, in deciding the desired characteristics of the objects to be highlighted, the radiologist may specify the degree of object sphericity (or roundness), the height of the protruding object in relation to its base (object 'flatness') as well as select an approximate object diameter range.
The provided text does not contain specific acceptance criteria or an explicit study describing the device's performance against such criteria. The document is a 510(k) summary for the Medicsight Colon CAR 1.2, focusing on its substantial equivalence to a predicate device rather than presenting detailed performance statistics or an independent study to prove acceptance criteria.
However, based on the information provided, we can infer some aspects and highlight what is missing:
1. Table of Acceptance Criteria and Reported Device Performance:
| Acceptance Criteria (Inferred) | Reported Device Performance |
|---|---|
| Substantial Equivalence to Predicate Device (MedicColon 1.0, K033102) | "The functional features and the intended use of Colon CAR 1.2 are substantially equivalent to the predicate device. The modifications to the original device did not introduce any new potential safety risks." |
| Safety: No new potential safety risks | "A comprehensive hazard analysis was carried out on Colon CAR 1.2, which concluded that any residual risks were as low as reasonably practicable and judged as acceptable when weighed against the intended benefits of use of the system." |
| Effectiveness: Equivalent to legally marketed device | "Colon CAR 1.2 is equivalent in performance to the existing legally marketed device." |
2. Sample Size for Test Set and Data Provenance:
- Sample Size: Not explicitly stated. The document mentions "Test data are provided to validate the performance of the system," but does not specify the size of this test set.
- Data Provenance: Not explicitly stated. The document mentions "Medicsight PLC." is located in "London W1J 5AT UK," but there is no information about the origin of the test data (e.g., country of origin, retrospective or prospective).
3. Number of Experts and Qualifications for Ground Truth:
- Not explicitly stated. The document refers to "radiologists and other clinicians" as intended users, but there is no information about experts used to establish ground truth for any test sets.
4. Adjudication Method for Test Set:
- Not explicitly stated. No details are provided regarding how ground truth was established or if any adjudication process was used.
5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study:
- Not explicitly stated. The document does not describe an MRMC study comparing human readers with and without AI assistance, nor does it provide an effect size. The device is described as "a software tool designed to assist radiologists," implying human-in-the-loop, but no comparative effectiveness study is presented.
6. Standalone Performance Study:
- Not explicitly stated. While the device is "PC-based, stand-alone, non-invasive, image analysis software," the document does not present a standalone performance study of the algorithm without human-in-the-loop. The "Polyp Enhanced Viewing Filter (PEV)" is described as highlighting "potential polyp candidates for further interrogation by the reporting radiologist," indicating an assisted workflow rather than a standalone diagnostic output.
7. Type of Ground Truth Used:
- Not explicitly stated. Given the context of colon polyp detection, common ground truths include expert consensus (e.g., colonoscopy findings, pathology reports), but the document does not specify.
8. Sample Size for Training Set:
- Not explicitly stated. There is no information provided about a training set or its size.
9. How Ground Truth for Training Set was Established:
- Not explicitly stated. Since no training set is mentioned, there is no information on how its ground truth might have been established.
Summary of Missing Information:
The provided 510(k) summary primarily focuses on demonstrating substantial equivalence to a predicate device, which often relies on functional comparisons and hazard analysis rather than detailed performance studies with explicit acceptance criteria and corresponding results. The document lacks the specific details requested regarding test set size, data provenance, expert qualifications, ground truth establishment methods, and detailed performance metrics that would be found in a comprehensive clinical or technical study report.
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(16 days)
MEDICSIGHT
Lung CAR I.1 is a PC-based, stand-alone, non-invasive, image analysis software application for the display and visualization of 2D and 3D medical image data of the lung derived from CT scans, for the purpose of assisting radiologists and other clinicians in the evaluation of lung lesions (e.g. nodules). The software provides functionality for the user to extract the region of interest (ROI) either manually using a drawing tool, or "semi-automatically" through the user selecting either a single or double seed point followed by interactive fine-tuning the boundaries of the ROI. Lung CAR 1.1 provides quantative information for measurement of lesion volume and other measured characteristics over time allowing the user to review and track any changes in the physician-indicated nodules or lesions.
Lung CAR 1.1 contains additional imaging tools which allow enhancement of specified features, and which the clinician can view simultaneously with the nonenhanced view.
Lung CAR™ (Computer Assisted Reader) 1.1 is a software tool designed to assist radiologists and other clinicians in the evaluation of nodules and other lesions in the lug. The software allows the user to select Regions of Interest either manually or by selecting a single or double seed point, followed by semi-automatic detection of the ROI boundary. It provides 2D and 3D visualisation of nodules and other lesions, and measurement of nodule characteristics such as size and volume. The further features of Lung CAR™ 1.1 as compared to the cleared device are a series of filters, the results of which are presented in a Joint Reader filter view (enhanced and non-enhanced data viewed simultaneously). These filters are an edge enhancement filter, noise removal filters and a sphericity filter. The sphericity filter enhances structures of images with spherical elements within certain Hounsfield Unit (HU) ranges that are defined by the user. This enhancement can aid the user when looking at a highlighted area (sphere) as a potential spherical nodule.
Given the provided documentation, I can extract information related to the device description, intended use, and comparison to predicate devices, but there is no information about acceptance criteria or a specific study that proves the device meets acceptance criteria. The text focuses on establishing substantial equivalence to existing predicate devices for regulatory approval, rather than detailing a performance study with acceptance criteria.
The document is a 510(k) summary of safety and effectiveness for Medicsight Lung CAR™ Release 1.1. It states that "Test data are provided to validate the performance of the system and its substantial equivalence to the predicate devices." However, these "test data" are not described in this summary.
Therefore, I cannot fulfill all parts of your request. I will report on what is available and indicate where information is missing.
Here's a breakdown of the available information and what is missing:
1. A table of acceptance criteria and the reported device performance:
- Missing. The document does not provide a table of acceptance criteria or reported device performance metrics against specific criteria. It asserts substantial equivalence based on functional features and intended use.
2. Sample size used for the test set and the data provenance:
- Missing. The document mentions "Test data are provided to validate the performance," but does not specify the sample size of the test set, the country of origin of the data, or whether it was retrospective or prospective.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:
- Missing. This information is not present in the provided text.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set:
- Missing. This information is not present.
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:
- Missing. The document does not describe an MRMC study or any quantitative improvement in human reader performance with the device.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:
- The device is described as "designed to assist radiologists and other clinicians," indicating it's a human-in-the-loop system, not a standalone algorithm for diagnosis. No standalone performance study details are provided.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc):
- Missing. The document does not specify how ground truth was established for any test data.
8. The sample size for the training set:
- Missing. No information on a training set is provided.
9. How the ground truth for the training set was established:
- Missing. No information on a training set or its ground truth establishment is provided.
Summary of available information:
- Device Name: Lung CAR™ Release 1.1
- Manufacturer: Medicsight PLC.
- Intended Use: PC-based, stand-alone, non-invasive, image analysis software for display and visualization of 2D and 3D medical image data of the lung from CT scans, to assist clinicians in evaluating lung lesions (e.g., nodules). It allows manual or semi-automatic Region of Interest (ROI) extraction and provides quantitative information for measurement of lesion volume and other characteristics for tracking changes over time. It also contains additional imaging tools for enhancement.
- Predicate Devices:
- Conclusion of document: "Lung CAR 1.1 does not raise any new potential safety risks and is equivalent in performance to existing legally marketed devices. Lung CAR 1.1 is therefore substantially equivalent with respect to safety and effectiveness to the predicate devices."
The document functions as a regulatory submission (510(k) summary) aiming to establish substantial equivalence for market clearance, rather than a detailed scientific study report. Therefore, detailed performance metrics, study designs, sample sizes, and ground truth methodologies are not typically included in this type of summary.
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(64 days)
MEDICSIGHT
MedicLung I is a PC-based, stand-alone, non-invasive, image analysis software application for the display and visualization of 2D and 3D medical image data of the lung derived from CT scans, for the purpose of assisting radiologists and other clinicians in the evaluation of lung lesions (e.g. nodules). The software provides functionality for the user to extract the region of interest (ROI) either manually using a drawing tool, or "semiautomatically" through the user selecting either a single or double seed point followed by interactive fine-tuning the boundaries of the ROI. MedicLunq I provides quantative information for measurement of lesion volume and other measured characteristics over time allowing the user to review and track any changes in the physician-indicated nodules or lesions.
MedicLung™ 1 is a software tool designed to assist radiologists and other clinicians in the evaluation of nodules and other lesions in the lug. The software allows the user to select Regions of Interest either manually or by selecting a single or double seed point, followed by semi-automatic detection of the ROI boundary. It provides 2D and 3D visualisation of nodules and other lesions, and measurement of nodule characteristics such as size and volume.
Here's an analysis of the acceptance criteria and study information for the MedicLung™ Release 1 device, based on the provided text:
1. Table of Acceptance Criteria and Reported Device Performance
The provided text does not explicitly state specific quantitative acceptance criteria or detailed performance metrics for MedicLung™ Release 1. It primarily focuses on demonstrating substantial equivalence to predicate devices through functional similarity and safety assessments.
However, based on the description, the implicit "acceptance criteria" are tied to demonstrating the device's ability to assist in the evaluation of lung lesions, measure nodule characteristics, and track changes over time, consistent with the performance of its predicate devices.
| Acceptance Criterion (Implicit) | Reported Device Performance (Implicit) |
|---|---|
| Assist Radiologists in Lung Lesion Evaluation: The device should effectively aid clinicians in identifying and evaluating nodules and other lesions in the lung. | "MedicLung™ 1 is a software tool designed to assist radiologists and other clinicians in the evaluation of nodules and other lesions in the lung." It "assists users in assessing CT images for the identification and evaluation of nodules and other lesions in the colon." The "Intended Use" also states it is "for the purpose of assisting radiologists and other clinicians in the evaluation of lung lesions (e.g. nodules)." |
| Provide 2D and 3D Visualization: The device should offer both 2D and 3D views of nodules and lesions. | "It provides 2D and 3D visualisation of nodules and other lesions." |
| Enable Nodule Measurement: The device should allow for the measurement of nodule characteristics. | "measurement of nodule characteristics such as size and volume." "MedicLung I provides quantative information for measurement of lesion volume and other measured characteristics over time." |
| Facilitate Region of Interest (ROI) Selection: The device should offer manual and semi-automatic ROI selection. | "The software allows the user to select Regions of Interest either manually or by selecting a single or double seed point, followed by sem_autonatic detection of the ROI boundary." The "Intended Use" reiterates this: "The software provides functionality for the user to extract the region of interest (ROI) either manually using a drawing tool, or "semi-automatically" through the user selecting either a single or double seed point followed by interactive fine-tuning the boundaries of the ROL." |
| Track Changes Over Time: The device should allow for reviewing and tracking changes in physician-indicated lesions. | "allowing the user to review and track any changes in the physician-indicated nodules or lesions." |
| Safety: The device should not introduce new safety risks and residual risks should be acceptable. | "A comprehensive hazard analysis was carried out on MedicLung 1, which concluded that any residual risks were as low as reasonably practicable and judged as acceptable when weighed against the intended benefits of use of the system." "MedicLung 1 docs not raisc any new potcntial safety risks." |
| Equivalence to Predicate Devices: The functional features and intended use should be substantially equivalent to predicate devices. | "As in the predicate devices, GE Advanced LungAnalysis-1 and Siemens LunCarcC'1, Mediclung 1 assists users in assessing CT images for the identification and evaluation of nodules and other lesions in the colon." "The functional features and the intended use of MedicLung 1 are substantially equivalent to the predicate devices." |
2. Sample Size Used for the Test Set and Data Provenance
The document states: "'I'cst data are provided to validate the performance of the system and its substantial equivalence to the predicate devices."
However, it does not specify the sample size used for the test set or the data provenance (e.g., country of origin of the data, retrospective or prospective).
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 used to establish ground truth or their qualifications.
4. Adjudication Method for the Test Set
The document does not mention any adjudication method used for the test set.
5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done
The document does not indicate that a Multi-Reader Multi-Case (MRMC) comparative effectiveness study was done, nor does it provide an effect size for human readers improving with or without AI assistance.
6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done
The device is described as a "software tool designed to assist radiologists and other clinicians." The functionality includes user selection of ROIs and "interactive fine-tuning." This strongly suggests a human-in-the-loop system. The document does not provide information about a standalone (algorithm-only) performance study. Its intended use implies it's an assistive tool, not a fully autonomous diagnostic system.
7. The Type of Ground Truth Used
The document does not explicitly state the type of ground truth used (e.g., expert consensus, pathology, outcomes data). Given the nature of a 510(k) submission for an assistive evaluation tool, it's highly probable that some form of expert consensus or clinically validated findings would have been used as a reference, but this is not confirmed in the provided text.
8. The Sample Size for the Training Set
The document does not specify the sample size for the training set.
9. How the Ground Truth for the Training Set Was Established
The document does not describe how the ground truth for the training set was established.
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(61 days)
MEDICSIGHT
MedicHeart 1 is a PC-based, stand-alone, non-invasive, image analysis software application intended to assist radiologists and other clinicians in the identification and quantification of coronary calcified plaques in the coronary arteries from CT image data. This quantification allows for evaluation of the progression or regression of calcified plaques in coronary arteries over time.
MedicHeart™ is a software tool designed to assist radiologists and other clinicians in the identification and quantification of coronary artery calcification. The software allows the user to manually select Regions of Interest by a single click or a drawing tool followed by semi-automatic detection. It provides calculation of calcium score using the traditional Agatston method, as well as measurement of the volume and mass of calcified plaques.
Here's an analysis of the provided text, outlining the acceptance criteria and the study details for the MedicHeart™ Release 1 device:
1. Table of Acceptance Criteria and Reported Device Performance
The provided text does not explicitly state specific numerical acceptance criteria for the MedicHeart™ Release 1 device's performance. Instead, it relies on demonstrating substantial equivalence to predicate devices. The performance is reported in terms of achieving this equivalence.
| Acceptance Criteria Category | Specific Criteria (from predicate equivalence) | Reported Device Performance |
|---|---|---|
| Functional Equivalence | Device evaluates CT images for identification and quantification of coronary artery calcified plaques, similar to GE SmartScore, Viatronix V3D, and Voxar Calcium Scoring. | "The functional features and the intended use of MedicHeart 1 are substantially equivalent to the predicate devices." |
| Safety | Residual risks are as low as reasonably practicable and acceptable when weighed against benefits. | "A comprehensive hazard analysis was carried out... concluded that any residual risks were as low as reasonably practicable and judged as acceptable..." |
| Overall Performance | Equivalent in performance to existing legally marketed devices (predicates). | "MedicHeart 1 does not raise any new potential safety risks and is equivalent in performance to existing legally marketed devices." |
2. Sample Size Used for the Test Set and Data Provenance
The document states, "Test data are provided to validate the performance of the system and its substantial equivalence to the predicate devices." However, it does not specify the sample size of the test set used.
Regarding data provenance:
- Country of Origin: Not explicitly stated.
- Retrospective or Prospective: Not explicitly stated.
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 used to establish the ground truth for the test set, nor does it detail their qualifications.
4. Adjudication Method for the Test Set
The document does not describe any adjudication method (e.g., 2+1, 3+1, none) used for the test set.
5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study
A multi-reader multi-case (MRMC) comparative effectiveness study was not mentioned or described in the provided text. Therefore, no effect size for human readers' improvement with AI assistance can be determined from this document. The focus is on the device's standalone performance compared to predicates.
6. Standalone Performance Study
Yes, a standalone study was done. The device is described as a "PC-based, stand-alone, non-invasive, image analysis software application." The reported performance focuses on its ability to identify and quantify coronary calcified plaques and its substantial equivalence to predicate devices, without explicitly involving human-in-the-loop performance measurement.
7. Type of Ground Truth Used
The document does not explicitly state the type of ground truth used (e.g., expert consensus, pathology, outcomes data). The phrase "identification and quantification of coronary artery calcification" suggests a ground truth related to anatomical presence and extent of calcification, likely established through expert review of imaging data that the device processes.
8. Sample Size for the Training Set
The document does not specify the sample size for the training set. In fact, it doesn't mention a "training set" at all, which is common for regulatory submissions where the focus is on validation against an independent test set.
9. How Ground Truth for the Training Set Was Established
Since the document does not mention a training set, it does not describe how its ground truth was established.
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(37 days)
MEDICSIGHT
MedicColon I is a PC-based, stand-alone, non-invasive, image analysis software application for the display and visualization of 2D and 3D medical image data of the colon derived from CT scans, for the purpose of assisting radiologists and other clinicians in the evaluation of polyps, cancers and other lesions. The software provides functionality for the user to extract the region of interest (ROI) either manually using a drawing tool, or "semi-automatically" through the user selecting a seed point followed by interactive fine-tuning the boundaries of the ROI. It also allows for the simultaneous display of supine and prone images
MedicColon™ 1 is a software tool designed to assist radiologists and other clinicians in the evaluation of polyps, cancers and other lesions in the colon. The software allows the user to select Regions of Interest either manually or by selecting a single or double seed point, followed by semi-automatic detection of the ROI boundary. It provides 2D and 3D visualisation of polyps and other lesions, and measurement of polyp characteristics such as size and volume.
The provided document does not contain acceptance criteria or a study proving the device meets them. This 510(k) Summary of Safety and Effectiveness document instead focuses on establishing substantial equivalence to predicate devices for the MedicColon™ Release 1 software.
Here's what the document does provide:
- Device Description: MedicColon™ 1 is a software tool to assist radiologists in evaluating polyps, cancers, and other lesions in the colon from CT scans. It offers 2D and 3D visualization, semi-automatic ROI selection, and measurement of polyp characteristics.
- Intended Use: PC-based, stand-alone, non-invasive image analysis software for display and visualization of 2D and 3D CT colon data to assist clinicians in evaluating polyps, cancers, and other lesions.
- Predicate Devices: VOXAR VC, MODEL 1.0 (K012072) and SIEMENS SYNGO COLONOGRAPHY SOFTWARE PRODUCT (K030982).
- Conclusion of Substantial Equivalence: MedicColon 1 is considered substantially equivalent to the predicate devices with respect to safety and effectiveness, and does not raise new safety risks. Test data were provided to validate performance and substantial equivalence.
Therefore, it is impossible to answer the requested questions about acceptance criteria and study details based on the provided text. The document states that "Test data are provided to validate the performance of the system and its substantial equivalence to the predicate devices," but does not describe the nature of this test data, the studies conducted, or any specific performance metrics or acceptance criteria.
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