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1. The Makoto Intravascular Imaging SystemTM is intended for the near-infrared examination of coronary arteries in patients undergoing invasive coronary angiography.
   a. The System is intended for the detection of lipid-core-containing plaques of interest.
   b. The System is intended for the assessment of coronary artery lipid core burden.
   c. The System is intended for the identification of patients and plaques at increased risk of major adverse cardiac events.
2. The System is intended for ultrasound examination of coronary and peripheral intravascular pathology.
   a. Intravascular ultrasound imaging is indicated in patients who are candidates for transluminal coronary and peripheral interventional procedures. The System is not indicated for use in the cerebral vessels.

The Makoto Intravascular Imaging System™ is an intravascular imaging device with the ability to simultaneously assess vessel composition and structure using near-infrared spectroscopy (NIRS) and intravascular ultrasound (IVUS). This dual-modality instrument performs near-infrared spectroscopic analysis of the vessel to detect lipid corecontaining plaques of interest (LCP) displayed in a map called a Chemogram, and simultaneously generates high resolution IVUS images that display structural details of the vessel and plaque in transverse and longitudinal views.

This FDA 510(k) summary describes the acceptance criteria and study results for the Makoto Intravascular Imaging System's new Automatic Border Contouring (ABC) and Guide Catheter Detection (GCD) software features.

Here's a breakdown of the requested information:

1. Table of Acceptance Criteria and Reported Device Performance

2. Sample Size and Data Provenance for the Test Set

• Sample Size:
  • Patients: 18 unique patients
  • Scans: 29 total scans
  • Frames: 981 frames
• Data Provenance: Retrospective, collected from both Japanese hospitals (12 scans, 5 patients, 381 frames from 3 sites) and US hospitals (17 scans, 13 patients, 609 frames from 3 sites). The test dataset ensured no patient overlap with the calibration dataset.

3. Number of Experts and Qualifications for Ground Truth

• Number of Experts: 6 expert IVUS readers.
• Qualifications: Described as "expert IVUS readers." No specific years of experience or board certifications are mentioned in the provided text.

4. Adjudication Method for the Test Set

The document doesn't explicitly state an adjudication method (like 2+1 or 3+1 for discordance resolution among experts). It indicates that the reference standard was "established using six expert IVUS readers who served as ground truth annotators," and that "The annotation process was standardized through the use of IVUS Tracing Guidelines and a proprietary in-house developed tracing software to ensure consistency and reproducibility." This suggests a consensus-based approach guided by protocols, but the explicit steps for resolving disagreements are not detailed.

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

• No, a MRMC comparative effectiveness study involving human readers with and without AI assistance was not detailed in this section. The acceptance criteria for ABC were established based on an inter- and intra-reader variability study using manual contouring by expert readers, which served as a benchmark for the algorithm's performance, but not a direct comparison of human performance improvement with AI.

6. Standalone (Algorithm Only) Performance

• Yes, the provided study presents the standalone performance of the ABC and GCD algorithms. The results in the tables directly evaluate the algorithms' accuracy against the established ground truth.

7. Type of Ground Truth Used

• Expert Consensus / Expert Annotation: The ground truth for the test set was established by "six expert IVUS readers" who followed "IVUS Tracing Guidelines" and used proprietary software to annotate specific features (guide catheter and stent regions, guidewire marking, lumen and EEM contours, calcium arcs, stent struts).

8. Sample Size for the Training Set

The document refers to a "calibration dataset" (which can be inferred to be the training/development set) but does not explicitly state the sample size for this set. It only mentions that the test dataset had "no patient overlap from the calibration dataset."

9. How Ground Truth for the Training Set Was Established

The document does not explicitly detail how the ground truth for the "calibration dataset" (training set) was established. It notes: "The test dataset was annotated by 6 readers, two of whom were not involved in the calibration dataset. While four annotators were shared between calibration and test datasets, the impact of this overlap was mitigated through randomized site allocation and diverse annotation styles to ensure the model did not learn specific annotator tendencies." This implies a similar expert annotation process was used for the calibration dataset as for the test set, but specific details are not provided.

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