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AutoSPECT® produces images, which depict the three-dimensional distribution of radiopharmaceutical tracers in a patient. This software is intended to provide enhancements to gamma camera emission image processing by automating previously manual image processing functions, providing manual and automated motion correction, providing enhanced reconstruction algorithms that include resolution recovery, scatter correction, noise compensation, and attenuation correction via application of a transmission dataset.

AutoSPECT® is a software application that produces images, which depict the three-dimensional distribution of radiopharmaceutical tracers in a patient via automatic or manual processing. One or more cardiac SPECT, gated SPECT, or MCD cardiac data sets may be processed automatically using AutoSPECT®. Additionally, one or more non-cardiac SPECT, or MCD data sets may be processed manually. AutoSPECT® contains basic data-processing algorithms that have been cleared previously; in addition to enhanced data reconstruction algorithms that include scatter correction, resolution recovery, map-based attenuation correction, and OSEM (Astonish SPECT) reconstruction.

The AutoSPECT software option may be used on images from a gamma camera system that are DICOM 3.0 compatible. The following data sets may be used:

Cardiac, brain, or other (bone, liver, etc.) SPECT datasets .
Gated SPECT datasets .
Vantage SPECT datasets
SPECT-CT datasets ●
Total Body SPECT datasets .
MCD and MCD-AC datasets .

AutoSPECT® provides the user three options for automatically processing cardiac datasets: AutoAll, ' > Auto Recon, and Auto Reorient. Each option is described in greater detail in the Software Description section, Section 4.

AutoSPECT® also allows the user to process non-cardiac SPECT and MCD datasets. In this case, the operator manually positions the reconstruction limit lines to reconstruct transverse data sets. If necessary, the data set can be reoriented manually by positioning the azimuth, elevation, and twist lines to the desired locations.

In addition, the capability of processing groups of SPECT data sets in a batch mode fashion is provided. Once the operator has selected the datasets and determined the processing method, AutoSPECT® processes the first dataset, followed by all remaining datasets without further interaction from the user.

AutoSPECT® application runs on Microsoft Windows XP Professional environment. The minimum hardware requirements are listed:

. Intel x86/Pentium class processor > 1 GHz ;
Graphics capability must meet or exceed 1280x1024 pixels with 32 bit pixel depth; .
30 GB of disk space (minimum); .
512 MB of DRAM (minimum); .
. 10/100 BaseTX Ethernet interface;
Port capable of supporting a dongle; .
. CD drive- capable of reading and writing;
. 56 Kbps modem (minimum)

Here's a breakdown of the acceptance criteria and study details for the AutoSPECT® device, based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

The submission claims to expand marketing relative to half-count imaging using Astonish-AC. The acceptance criteria revolve around achieving equivalent or improved diagnostic accuracy, image quality, and interpretive certainty compared to a baseline method (full-time back projection).

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

• Sample Size: 297 patient images.
• Data Provenance: The data was acquired using Philips' imaging systems and AutoSPECT® (with Astonish & Astonish AC). It was a "multi-center evaluation" and used "previously scanned images," indicating it was retrospective and likely from various centers where Philips' equipment was used. The country of origin is not explicitly stated, but Philips Medical Systems (Cleveland), Inc. is the submitting entity.

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

The document does not explicitly state the number of experts or their specific qualifications (e.g., "radiologist with 10 years of experience") used to establish ground truth. It vaguely refers to "multi-center evaluations" and conclusions about "diagnostic accuracy" and "interpretive certainty," implying expert interpretation was involved, but details are missing.

4. Adjudication Method for the Test Set

The document does not specify an adjudication method (e.g., 2+1, 3+1, none) for the test set.

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

• Was an MRMC study done? The text describes "multi-center evaluations" that compared different processing techniques and their impact on "diagnostic accuracy" and "interpretive certainty." This strongly suggests a comparative effectiveness study, likely involving multiple readers to assess the different image sets. However, it does not explicitly label it an "MRMC study."
• Effect Size of human readers' improvement with AI vs. without AI assistance: The study compared different reconstruction techniques (Astonish, Astonish-AC, and full-time back projection) on images, not directly the improvement of human readers with AI assistance versus without AI assistance. The tools (Astonish, Astonish-AC) are enhancements to the imaging process, which then impact the diagnostic accuracy and interpretive certainty. The benefit is reported for the technique, not explicitly as a reader-AI collaboration enhancement.

6. Standalone (Algorithm Only Without Human-in-the-Loop Performance) Study

The study evaluates the output of the AutoSPECT® software's reconstruction algorithms (Astonish and Astonish-AC) in terms of diagnostic accuracy, image quality, and interpretive certainty. Since these are measures that require human interpretation to determine against clinical outcomes or established diagnoses, the study is not a standalone (algorithm only) performance assessment. It assesses the impact of the algorithm's output on human interpretation.

7. Type of Ground Truth Used

The ground truth used is implied to be expert consensus or established clinical diagnoses/outcomes to determine "diagnostic accuracy," "sensitivity," "specificity," and "normalcy." The document does not specify how this ground truth was definitively established (e.g., based on pathology confirmation for all cases, or long-term follow-up for outcomes).

8. Sample Size for the Training Set

The document does not provide any information about the sample size used for the training set. The study detailed is an evaluation of existing reconstruction techniques and their expanded claims.

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

Since no information is provided about a training set, the method for establishing its ground truth is not mentioned.

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The AutoSPECT Plus with InStill Motion Correction option to the ADAC Gamma Camera Systems produces images which depict anatomical density of the patient. This system is intended to provide enhancements of gamma camera emission images by automating previously manual image processing functions and providing manual and automated motion correction.

The AutoSPECT Plus with InStill Motion Correction software option enables automatic processing of one or more cardiac SPECT, gated SPECT, Vantage SPECT, MCD, or MCD-AC cardiac data sets. In addition. AutoSPECT Plus with InStill Motion Correction enables the manual processing of one or more SPECT. gated SPECT, Vantage SPECT, MCD, or MCD-AC data sets. The basic data processing algorithms utilized by AutoSPECT Plus with InStill Motion Correction are ones which have been utilized in previously cleared ADAC products.

For automatically processing cardiac data sets, AutoSPECT Plus with InStill Motion Correction provides three options. The first of these options, "Auto All", automatically determines the reconstruction limits, reconstructs and reorients the cardiac data sets and creates the short axis, horizontal long axis and vertical long axis data sets. The second option, "Auto Recon", automatically determines the reconstruction limits and reconstructs the cardiac data sets. The third option. "Auto Reorient", automatically reorients the cardiac transverse data sets. If necessary, AutoSPECT Plus with InStill Motion Correction reconstructs the data sets prior to re-orientation.

AutoSPECT Plus with InStill Motion Correction software also allows the user to process noncardiac SPECT, Vantage, MCD, or MCD-AC data sets. In this case, the operator manually positions the reconstruction limit lines to reconstruct transverse data sets. If necessary, the data set can be reoriented by manually positioning the Azimuth and elevation lines to the desired location.

The AutoSPECT Plus with InStill Motion Correction software will also process groups of SPECT data sets in a batch mode fashion. Once the operator has selected the data sets and determined the processing method (i.e. Auto All, Auto Recon, Reorient, or Reconstruct), AutoSPECT Plus with InStill Motion Correction processes the first data set followed by all remaining data sets without further interaction from the operator.

The provided text does not contain detailed acceptance criteria or a comprehensive study report with the specific information requested in the prompt. The document is primarily a 510(k) summary for the "AutoSPECT Plus with InStill Motion Correction" device, focusing on its substantial equivalence to predicate devices and its intended use.

Here's what can be extracted and what information is missing:

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

• No specific acceptance criteria are explicitly stated in the document (e.g., a specific accuracy, sensitivity, or specificity threshold).
• No quantitative device performance metrics (e.g., reported accuracy, sensitivity, specificity) are provided. The "Testing" section only vaguely states: "Images were processed using the AutoSPECT Plus with and without InStill Motion Correction."

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

• Sample size for test set: Not mentioned.
• Data provenance (e.g., country of origin, retrospective or prospective): Not mentioned.

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

• Not mentioned.

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

• Not mentioned.

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 implies a comparison ("with and without InStill Motion Correction"), but it does not describe an MRMC comparative effectiveness study involving human readers. It focuses on the processing of images by the device itself, not human interpretation aided by the device. Therefore, no effect size for human reader improvement is provided.

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

• Based on the description, the device performs "automatic processing" and "automated motion correction." The "Testing" section suggests evaluating the output of this automated processing. This implies a standalone algorithm only evaluation, but no performance metrics are given.

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

• Not mentioned. Given the nature of a SPECT image processing and motion correction device, "ground truth" would likely involve expert visual assessment of image quality, artifact reduction, or quantitative metrics derived from the images, but this is not specified.

8. The sample size for the training set

• Not mentioned.

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

• Training set details and ground truth establishment methodology are not mentioned.

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