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It is used by radiation oncology department to segment CT images, to generate needed information for treatment planning, treatment evaluation and treatment adaption.

The proposed device, AccuContour 4.0 Family, is a standalone software with the following variants: AccuContour and AccuContour-Lite. The functions of AccuContour-Lite is a subset of AccuContour.

AccuContour:
It is used by oncology department to register multi-modality images and segment (non-contrast) CT images, to generate needed information for treatment planning, treatment evaluation and treatment adaptation.

The product has two image processing functions:

1. Deep learning contouring: it can automatically contour organs-at-risk, in head and neck, thorax, abdomen and pelvis (for both male and female) areas,
2. Automatic registration: rigid and deformable registration, and
3. Manual contouring.

It also has the following general functions:

• Receive, add/edit/delete, transmit, input/export, medical images and DICOM data;
• Patient management;
• Review tool of processed images;
• Extension tool;
• Plan evaluation and plan comparison;
• Dose analysis.

AccuContour-Lite:
It is used by oncology department to segment (non-contrast) CT images, to generate needed information for treatment planning, treatment evaluation and treatment adaptation.

The product has one image processing function:
Deep learning contouring: it can automatically contour organs-at-risk, in head and neck, thorax, abdomen and pelvis (for both male and female) areas,

It also has the following general functions:

• Receive, add/edit/delete, transmit, input/export, medical images and DICOM data;
• Patient management;
• Review tool of processed images.

Here's an analysis of the acceptance criteria and study details for the AccuContour 4.0, extracted and organized from the provided FDA 510(k) clearance letter.

1. Table of Acceptance Criteria and Reported Device Performance

The acceptance criteria are derived from the "Pass Criteria" columns in Tables 1, 2, 3, and 4, which specify minimum DSC and maximum HD95 values. The reported device performance is represented by the "Lower Bound 95% CI" for both DSC and HD95, and the "Average Rating" for clinical applicability.

Table A: Performance for Synthetic CT (sCT) Contouring Function (Derived from MR Images)

*Note: For Stomach, the reported DSC (0.782) is below the pass criteria (0.8). However, the document states, "The results indicate that the auto-segmentation performance of the AccuContour system for sCT images derived from both CBCT and MR modalities meets the requirements for geometric accuracy." This suggests there might be an overall or combined assessment, or other factors led to acceptance despite this single instance. The average clinical rating is 4.1, which is above the threshold of 3.

Table B: Performance for Synthetic CT (sCT) Contouring Function (Derived from CBCT Images)

Table C: Performance for 4DCT Registration Function (Rigid Registration)

*Note: For Stomach (0.791) and Spleen (0.786), the reported DSC is below the pass criteria (0.8). However, the document states, "According to the results, the accuracy of 4DCT image registration images meets the requirements and all structure models demonstrating that only minor edits would be required in order to make the structure models acceptable for clinical use." The average clinical rating for both is 4.5, above the threshold of 3.

Table D: Performance for 4DCT Registration Function (Deformable Registration)

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

• Synthetic CT (sCT) Contouring Function:

  • Sample Size: 247 synthetic CT images (116 generated from MR, 131 generated from CBCT).
  • Data Provenance:
    • Demographic Distribution: 57% male, 43% female. Age distribution: 13% (21-40), 44.1% (41-60), 36.8% (61-80), 6.1% (81-100). Race: 78% White, 12% Black or African American, 10% Others.
    • Imaging Equipment: MR images from GE (21.6%), Philips (56.9%), Siemens (21.6%). CBCT images from Varian (58.8%), Elekta (41.2%).
    • Retrospective/Prospective: Not explicitly stated, but the description of demographic and equipment distribution from a "sample" indicates retrospective data collection from existing patient records.
    • Country of Origin: The racial distribution explicitly mentions "U.S. clinical radiotherapy practice," suggesting the data is primarily from the United States.

• 4DCT Registration Function:

  • Sample Size: 30 4DCT image sets.
  • Data Provenance:
    • Imaging Equipment: Siemens (90.0%), Philips (10.0%) scanners.
    • Demographic Distribution: 17 males (56.7%), 13 females (43.3%). Age: 33-82 years, with majority in 51-65 (40.0%) and 66-80 (43.3%) year brackets.
    • Image Characteristics: Uniform 3mm slice thickness (100%).
    • Sourcing Location: Most images (90.0%) from Drexel Town Square Health Center/Community Memorial Hospital, remainder from Froedtert Hospital.
    • Retrospective/Prospective: Not explicitly stated, but implies retrospective data from patient archives of the mentioned hospitals.
    • Country of Origin: Based on the hospital names (Drexel Town Square Health Center, Community Memorial Hospital, Froedtert Hospital), the data is from the United States.

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

• Number of Experts: Not explicitly stated. The text mentions "clinical experts evaluate the clinical applicability" and "RTStruct contoured by the professional physician as the gold standard." This implies at least one, and likely multiple, qualified medical professionals.
• Qualifications of Experts: The experts are described as "clinical experts" and "professional physician(s)." Their specific qualifications (e.g., "radiologist with 10 years of experience") are not provided. They are implied to be clinically qualified radiotherapy personnel.

4. Adjudication Method for the Test Set

• Adjudication Method: Not explicitly stated. The ground truth for segmentation is stated to be "RTStruct contoured by the professional physician". For clinical applicability, "clinical experts evaluate the clinical applicability" and assign a 1-5 scale score. This suggests a single expert (or group consensus without specific adjudication rules like 2+1) established the ground truth segmentation, and separate clinical experts evaluated the results. There is no mention of a formal adjudication process for disagreements in ground truth labeling if multiple experts were involved in its creation.

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

• Was an MRMC study done? No.
• Effect Size of Human Improvement (if applicable): Not applicable, as no MRMC study comparing human readers with and without AI assistance was reported. The testing focused solely on the algorithm's performance against expert-generated ground truth and expert evaluation of the algorithm's output.

6. Standalone Performance

• Was a standalone performance study done? Yes. The entire report details the "Performance Test Report on Synthetic CT (sCT) Contouring Function" and "Performance Test Report on 4DCT Registration Function," measuring the algorithm's performance (DSC, HD95) against gold standard contours and qualitative evaluation by clinical experts. This reflects the algorithm's performance independent of human interaction during the contouring process.

7. Type of Ground Truth Used

• Ground Truth: For the synthetic CT contouring and 4DCT registration functions, the ground truth was "RTStruct contoured by the professional physician" (i.e., expert consensus or expert-generated contours).

8. Sample Size for the Training Set

• Training Set Sample Size: Not provided in the document.

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

• Training Set Ground Truth Establishment: Not provided in the document. The document only details the ground truth used for the validation/test set.

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Affirm 400 is a surgical microscope accessory used in fluorescent visualization of suspected grade III and IV gliomas during neurosurgery, comprising an excitation filter for blue spectral range between 390 nm and 420 nm and an observation filter for visible light with spectral range between 510 nm and 700 nm.

Affirm 400 is an accessory to the Class I Digital Surgical Microscope (DSM). Affirm 400 is a hardware and software which allows intraoperative viewing of suspected grade III and IV gliomas under fluorescence with the 5-ALA optical imaging agent. Affirm 400 is composed of optical filters: the "Excitation" filter and the "Emission" filter. The Excitation filter is designed to filter light between 390-420 nanometers. The Emission filter is designed to filter light between 510 – 700 nanometers. The use of a suitable detection system allows for visualization of surgical interventions. The emitted light is then captured by the optics of the digital microscope, passed through filters to remove unwanted wavelengths of light, and finally detected by the image sensors. This detected signal is then projected on a monitor enabling the surgeon to view the magnified image. The Affirm 400 includes installation of a software license that facilitates use of the accessory. After the software license is installed, the user has the option to switch from the normal white light mode of the surgical microscope to the Affirm 400 mode.

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