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The ACIST HDi System is intended to be used for ultrasound examination of coronary and peripheral intravascular pathology. Intravascular ultrasound imaging is indicated in patients who are candidates for transluminal interventional procedures.

The ACIST Kodama Intravascular Ultrasound Catheter is intended for use with the ACIST HDi System.

The primary function of HDi System is to collect reflected ultrasonic (sound) waves from the Kodama catheter and render an intravascular image on the console touchscreen. The catheter emits sound energy from a transducer at the tip; sound waves reflected from the inner vascular tissues are received from the transducer and sent to the console where a high resolution, cross-sectional image is displayed on the touchscreen in real-time.

The main devices are the Console, Patient Interface Module (PIM), Linear Translation System (LTS) (optional), and Kodama Catheter.

The console houses hardware and software required to generate the energy used to excite the transducer in the Kodama catheter; it is the center of control and system architecture for how signals are acquired, processed, images constructed and presented, and overall power management and control of the PIM and LTS. The system digitally records case images, provides a review of recorded cases, and provides for the archival of recorded cases onto removable media.

The handheld PIM provides the electromechanical interface between the catheter and the console. It also provides the mechanical interface to secure the catheter, as well as the mechanical energy to rotate the catheter's imaging assembly. The LTS device provides automated, controlled linear translation of the catheter by providing mechanical coupling to the PIM and to the catheter's telescoping anchor as the PIM is pulled back along the longitudinal axis. The coupling between the LTS and PIM and LTS to catheter is strictly mechanical. The LTS device allows the user to perform automatic pullbacks and can be controlled via touchscreen buttons on the console or the buttons on the LTS. Manual pullbacks may be performed with or without the LTS, making the use of the LTS optional to the user.

The Kodama Catheter emits sound energy from its transducer at the distal tip, which is guided into the coronary and peripheral vasculature. The catheter can be operated at two different frequencies, 40MHz and/or 60MHz, depending on user preference. The catheter design includes an imaging assembly (with transducer, drive cable, coaxial cable, and rotor), sheath assembly (which includes the femoral marker and hydrophilic coating), telescope assembly, and catheter hub assembly. The electrical energy from the catheter is transmitted, via the transmission line embedded in the drive cable, back to the HDi console for signal processing and image reconstruction.

The provided text describes the ACIST Kodama Intravascular Ultrasound Catheter and ACIST HDi System, and cites a 510(k) submission for substantial equivalence to predicate devices. However, the document does not contain specific acceptance criteria or a dedicated study proving the device meets quantitative acceptance criteria for performance metrics like sensitivity, specificity, accuracy, or reader improvement.

Instead, the submission focuses on demonstrating substantial equivalence through:

• Bench Testing: Evaluating physical and electrical performance characteristics.
• Animal Study: Confirming imaging capabilities and usability in a peripheral vessel model.
• Comparison to Predicate Devices: Highlighting similar indications for use, fundamental scientific technology, safety, and performance.

Therefore, many of the requested details cannot be extracted directly from this document.

Here's an attempt to answer the questions based on the available information:

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

No explicit quantitative acceptance criteria (e.g., specific accuracy thresholds, sensitivity/specificity targets) or corresponding reported performance values are provided in the document for the new device as compared to a predefined standard. The performance is assessed against specifications and compared to predicate devices qualitatively.

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

• Bench Testing Test Set Sample Size: Not specified.
• Animal Study Test Set Sample Size: "a porcine model" - the exact number of animals is not specified.
• Data Provenance:
  • Bench testing data provenance is implied to be from ACIST Medical Systems' internal testing.
  • Animal study data provenance is "conducted by ACIST Medical Systems in a laboratory environment."

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

• Bench Testing: Ground truth is established by engineering specifications and direct measurements against those specifications. No external experts are mentioned for ground truth.
• Animal Study: "The physician also provided evaluation on the usability of Kodama catheter." - This suggests at least one physician. Specific qualifications (e.g., years of experience, specialty) are not mentioned. The ground truth here appears to be the visual assessment of imaging capabilities and clinical usability by the physician.

4. Adjudication method for the test set

• No specific adjudication method (like 2+1 or 3+1 consensus) is described for either the bench testing or the animal study. The animal study mentions a "physician also provided evaluation," implying a single observer or their primary findings rather than a multi-reader consensus process for ground truth.

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 multi-reader multi-case (MRMC) comparative effectiveness study is mentioned, nor is there any mention of AI assistance in the context of this device. The device is an intravascular ultrasound system, not an AI-powered diagnostic tool in the sense of assisting human readers in interpretation.

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

• This is not applicable as the device is an imaging system (hardware and software) that produces images for human interpretation, not an algorithm providing a standalone diagnostic output.

7. The type of ground truth used

• Bench Testing: Engineering specifications and direct physical/electrical measurements.
• Animal Study: Visual assessment of imaging by a physician and their subjective evaluation of usability.

8. The sample size for the training set

• No training set is mentioned as this is not an AI/machine learning device that requires a distinct training and test set for algorithm development in the traditional sense. The device is a medical imaging system.

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

• Not applicable, as no training set is mentioned.

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The ACIST HDi System is intended to be used for the intravascular ultrasound imaging assessment of coronary artery disease. Intravascular ultrasound imaging is indicated in patients who are candidates for transluminal coronary interventional procedures.
The ACIST Kodama Intravascular Ultrasound Catheter is a medical device for use by or on the order of a physician and is intended for ultrasound examination of coronary intravascular pathology only. Intravascular ultrasound imaging is indicated in patients who are candidates for transluminal coronary interventional procedures.

The primary function of HDi System is to collect reflected ultrasonic (sound) waves from the Kodama catheter and render an intravascular image on the console touchscreen. The catheter emits sound energy from a transducer at the tip; sound waves reflected from the inner vascular tissues are received from the transducer and sent to the console where a high resolution, cross-sectional image is displayed on the touchscreen in real-time.
The main devices are the Console, Patient Interface Module (PIM), Linear Translation System (LTS) (optional), and Kodama Catheter.
The console houses hardware and software required to generate the energy used to excite the transducer in the Kodama catheter; it is the center of control and system architecture for how signals are acquired, processed, images constructed and presented, and overall power management and control of the PIM and LTS. The system digitally records case images, provides a review of recorded cases, and provides for the archival of recorded cases onto removable media
The handheld PIM provides the electromechanical interface between the catheter and the console. It also provides the mechanical interface to secure the catheter, as well as the mechanical energy to rotate the catheter's imaging assembly. The LTS device provides automated, controlled linear translation of the catheter by providing mechanical coupling to the PIM and to the catheter's telescoping anchor as the PIM is pulled back along the longitudinal axis. The coupling between the LTS and PIM and LTS to catheter is strictly mechanical. The LTS device allows the user to perform automatic pullbacks and can be controlled via touchscreen buttons on the console or the buttons on the LTS. Manual pullbacks may be performed with or without the LTS, making the use of the LTS optional to the user.
The Kodama Catheter emits sound energy from its transducer at the distal tip, which is guided into the coronary arteries of the heart. The catheter can be operated at two different frequencies, 40MHz and/or 60MHz, depending on user preference. The catheter design includes an imaging assembly (with transducer, drive cable, coaxial cable, and rotor), sheath assembly (which includes the femoral marker and hydrophilic coating), telescope assembly, and catheter hub assembly. The electrical energy from the catheter is transmitted, via the transmission line embedded in the drive cable, back to the HDi console for signal processing and image reconstruction.

This document is a 510(k) summary for the ACIST Kodama Intravascular Ultrasound Catheter and ACIST HDi System. It describes the device, its intended use, and how it compares to predicate devices to establish substantial equivalence.

Based on the provided text, the device is an intravascular ultrasound imaging system. The document does not describe an AI/Algorithm-based device, but rather a traditional medical imaging device. Therefore, many of the requested details such as sample size for test sets, expert involvement, adjudication methods, MRMC studies, or training set information are not applicable or available in this specific document.

The "acceptance criteria" and "study that proves the device meets the acceptance criteria" in the context of this document refer to demonstrating substantial equivalence to predicate devices, primarily through non-clinical performance and safety testing, rather than an AI model's performance on a specific task.

Here's an attempt to answer the questions based only on the provided text, acknowledging that most questions relate to AI/algorithm performance which is not the subject of this submission:

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

Since this is not an AI/algorithm device submission, the acceptance criteria are not in terms of traditional performance metrics like sensitivity, specificity, or AUC against a ground truth for an AI task. Instead, the acceptance criteria are implicitly demonstrating that the device is as safe and effective as its predicate devices. The "reported device performance" in this context refers to the outcomes of non-clinical tests that support substantial equivalence.

2. Sample sized used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

Not applicable, as this is a traditional medical device submission based on non-clinical engineering and safety testing. There is no "test set" in the context of an algorithm's performance on patient data. The tests performed are bench, operating environment, packaging, software, electrical safety, EMC, and biocompatibility testing. The data provenance is not specified beyond being generated through these tests.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)

Not applicable. The ground truth for engineering and safety tests is based on established scientific principles, standards, and regulatory requirements, not expert consensus on medical images. A "Medical Advisory Board" supported labeling changes, but their role was not to establish ground truth for an algorithm's performance.

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

Not applicable. There is no test set requiring adjudication in the context of an AI algorithm's performance.

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

Not applicable. This device is not an AI-assisted diagnostic tool; it is an intravascular ultrasound imaging system.

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

Not applicable. This is not an AI algorithm.

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

For the non-clinical tests conducted, the "ground truth" refers to compliance with engineering specifications, recognized standards (e.g., IEC 60601-1 and IEC 60601-1-2), and established safety and performance benchmarks for intravascular ultrasound systems. The goal was to prove substantial equivalence to predicate devices, implying that the device performs as expected and safely.

8. The sample size for the training set

Not applicable. This is not an AI algorithm requiring a training set.

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

Not applicable. This is not an AI algorithm.

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