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The ImageChecker-CT is indicated for use as a general imaging workstation, and is intended to be used to acquire, store, transmit and display images from medical scanning devices.

Specific indications for use for the ImageChecker-CT Workstation are the display of a composite view of 2D cross-sections, and 3D volumes of chest CT images, including findings or regions of interest ("ROI") identified by the radiologist or Computer Assisted Detection ("CAD") findings.

The general indications for use of the ImageChecker-CT Workstation are as a general imaging workstation to assist radiologists in reviewing digital computed Tomography (CT) images of the chest.

Specific indications for use for the ImageChecker-CT Workstation are the display of a composite view of 2D cross-sections, and 3D volumes of chest CT images, including findings or regions of interest ("ROI") identified by the radiologist or Computer Assisted Detection ("CAD") findings.

The ImageChecker-CT System is a combination of dedicated computer software and hardware. The System uses an off-the-shelf personal computer with Windows and Linux-based CPUs, a hard drive, and a single monitor.

The provided document, K023003 for the ImageChecker-CT Workstation, does not contain information about acceptance criteria or a study proving the device meets specific performance criteria.

Instead, the document primarily focuses on establishing substantial equivalence to predicate devices. This means that instead of presenting a stand-alone performance study with acceptance criteria, the manufacturer is arguing that their device is as safe and effective as other legally marketed devices with similar intended use and technological characteristics.

Therefore, many of the requested details cannot be extracted from this specific 510(k) summary. I can only provide information directly mentioned or inferable from the document regarding the type of evaluation conducted.

Here's a breakdown of the requested information based on the provided text:

1. Table of acceptance criteria and the reported device performance

The document does not specify performance acceptance criteria or report device performance metrics in the way a clinical performance study would for a new device. The "Studies" section states, "The ImageChecker-CT Workstation will undergo design verification tests for conformance with specifications." This implies internal testing against design specifications, not necessarily clinical performance metrics.

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

Not applicable. The document describes a comparison to predicate devices for substantial equivalence, not a performance study with a distinct test set.

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

Not applicable. The document does not describe a performance study involving ground truth establishment by experts.

4. Adjudication method for the test set

Not applicable. No test set or expert adjudication is described for a performance study.

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 makes no mention of an MRMC study or any assessment of human reader improvement with AI assistance. The device is described as a "general imaging workstation" that can display CAD findings, but its effectiveness with CAD is not studied here.

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

No. The document describes a workstation for displaying images and CAD findings, but it does not report on the standalone performance of any algorithm. The 510(k) focuses on the workstation itself, not the performance of a specific CAD algorithm.

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

Not applicable. No performance study with ground truth is described.

8. The sample size for the training set

Not applicable. The document does not describe the development or training of an algorithm.

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

Not applicable. The document does not describe the development or training of an algorithm.

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Lung CARE CT is a self-contained image analysis software package for evaluating CT volume data sets. Combining enhanced commercially available digital image processing tools with optimized workflow and reporting tools, the software is designed to support the physician in confirming the presence of absence of physician-identified lung lesions (eg. nodules) in addition to evaluation, documentation and follow-up of any such lesions using standard or low-dose spiral CT scanning. This evaluation tool allows for volumetric analysis of pulmonary nodule or lesion size over time, helping the Physician to assess the changes in their growth. It is also designed to help the physician classify conspicuous regions of tissue unambiguously, with respect to their size, dimensions, shape and position.

This premarket notification covers Siemens LungCARE CT software package. It is based on Siemens syngo software platform. Lung CARE CT is a self-contained image analysis software package for cvaluating CT volume data sets. Combining enhanced commercially available digital image processing tools (MIP, MPR, SSD, VRT), evaluation tools (volumetric estimation using consistent standardized measurement protocol, comparator tool for nodule matching by synchronization of two datasets, classification of nodules using configurable descriptors) and reporting tools (targeted presets, saved lesion) with optimized workflow palette, the software package is designed to support the physician in confirming the presence of physician identified lung lesions (eg. nodulcs) in addition to evaluation, documentation and follow-up of any such lesions using standard or low-dose spiral CT scanning. This visualization tool allows for volumetric analysis of pulmonary nodule or lesion size over time, helping the Physician to assess the changes in their growth. It is also designed to help the physician classify conspicuous regions of tissue unambiguously, with respect to their size, dimensions, shape and and position.

This document describes the LungCARE CT software package, a 3D CT reconstruction software designed to assist physicians in evaluating lung lesions. The submission includes a summary of pre-clinical and clinical information, and a declaration of substantial equivalence to previously cleared devices.

Here's an analysis of the provided information concerning acceptance criteria and the supporting studies:

1. Table of Acceptance Criteria and Reported Device Performance

The submission does not explicitly state specific quantitative acceptance criteria for performance metrics (e.g., minimum accuracy, sensitivity, or reproducibility thresholds). Instead, the studies focus on demonstrating the capabilities and reproducibility of the device's volumetric measurements under various conditions.

• Volumetric estimation using standardized measurement protocol.
• Nodule matching by synchronization of two datasets (comparator tool).
• Classification of nodules using configurable descriptors.
• Targeted presets and saved lesion reporting tools.
• Visualization for volumetric analysis of pulmonary nodule or lesion size over time to assess growth.
• Classification of conspicuous tissue regions by size, dimensions, shape, and position. (Implied, as these are features of the device, not an evaluated performance metric in the studies described). |

2. Sample Sizes and Data Provenance

A. Lung Phantom Bench Testing Study (Kohl et al.):

• Sample Size: Not explicitly stated, but it's a bench testing study using a lung phantom, implying manufactured phantoms rather than patient data.
• Data Provenance: Not applicable as it's a phantom study.

B. Clinical Evaluation (Wormanns et al.):

• Sample Size (Test Set): 10 patients with pulmonary metastatic disease. A total of 150 pulmonary nodules were manually marked and evaluated across these patients.
• Data Provenance: Not explicitly stated (e.g., country of origin), but it is a clinical evaluation, therefore retrospective patient data since the study was conducted to evaluate the software.

3. Number of Experts and their Qualifications for Ground Truth

• A. Lung Phantom Bench Testing Study (Kohl et al.): Not applicable, as this was a phantom study and did not involve human interpretation or ground truth establishment in the traditional sense for medical imaging. The "ground truth" would be the known physical dimensions or changes in the phantom.
• B. Clinical Evaluation (Wormanns et al.): Not explicitly stated how many experts were involved in manually marking the 150 pulmonary nodules. The qualifications of these individuals are also not specified (e.g., "radiologist with 10 years of experience").

4. Adjudication Method

• The information provided does not specify an adjudication method for either study (e.g., 2+1, 3+1, none).
• For the clinical study, it states that "150 pulmonary nodules were manually marked and then evaluated," which implies a single expert or a non-adjudicated process unless specified otherwise.

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

• No MRMC comparative effectiveness study is described where human readers' performance with and without AI assistance is compared. The clinical study focused on the reproducibility of the software's volumetric measurements, not on the human reader's improvement with the software.

6. Standalone (Algorithm Only) Performance

• Yes, a standalone study was performed. The "Wormanns et al." clinical evaluation assessed the reproducibility of volumetric measurements using LungCARE CT where "The proposed segmentation results, provided by the software package, were not modified by the user." This indicates the study evaluated the algorithm's performance in segmenting and measuring nodules without human intervention to adjust its output.

7. Type of Ground Truth Used

• A. Lung Phantom Bench Testing Study (Kohl et al.): The ground truth would be based on the known physical properties and dimensions of the phantom and the controlled changes applied to it.
• B. Clinical Evaluation (Wormanns et al.): The ground truth for the 150 pulmonary nodules was established by manual marking. This implies expert human identification and marking of the nodules, which then serves as a reference for the software's measurements. This is a form of expert consensus or expert-derived ground truth, though the number and qualifications of experts are not specified, nor is an explicit consensus process mentioned.

8. Sample Size for the Training Set

• The document does not provide any information about the training set used for the LungCARE CT software. The studies described are evaluation studies of an already developed product.

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

• Since there is no information about the training set, there is also no information on how its ground truth was established.

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