Search Results

ShuntCheck is an aid to the detection of flow in implanted cerebrospinal fluid (CSF) shunts. ShuntCheck cannot alone diagnose CSF shunt function or malfunction. The clinical diagnosis of CSF shunt function or malfunction, incorporating the flow information from ShuntCheck, should be made only by a qualified neurosurgeon.

ShuntCheck is a non-invasive device which detects flow in a CSF shunt via transcutaneous thermal convection. The device consists of a single use disposable thermosensor array patch which is connected to a handheld "biodisplay" unit. The shunt is cooled transcutaneously by placing ice over the shunt cephalic to the thermosensor. The thermosensor array patch, which is placed on the skin over the shunt "downstream" of the ice, reads the change in skin temperature over the shunt as cooled fluid flows downstream and also at a nearby control location. Data is captured in the biodisplay unit. If the device detects a characteristic downstream transcutaneous temperature dip, the biodisplay reports "flow confirmed". If no temperature dip is detected, the unit reports "flow not confirmed"

The provided text does not contain specific acceptance criteria or a detailed study description with performance metrics to fully answer all aspects of the request. The document is primarily a 510(k) summary and an FDA clearance letter for the ShuntCheck device, which is an aid to detect flow in CSF shunts. It mentions functional and safety testing, and animal studies, but does not provide quantitative acceptance criteria or detailed results of a clinical study that would demonstrate performance.

However, based on the available information, here's what can be extracted and inferred:

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

The document does not explicitly state quantitative acceptance criteria for device performance (e.g., sensitivity, specificity, accuracy thresholds) or provide reported device performance metrics in a clinical context. It mentions:

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

• Test Set Sample Size: Not explicitly stated for any clinical or animal studies. The text mentions "three animal studies" and "a representative sample of the device" for safety testing. This suggests multiple animals were used, but the exact number is not provided.
• Data Provenance:
  • Type: Primarily animal studies and bench testing. There is no mention of human clinical trial data for performance evaluation in this summary.
  • Country of origin: Not specified.
  • Retrospective or Prospective: Animal studies and bench testing are generally prospective in nature.

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 primary performance evaluation described was in animal studies and bench testing; there's no indication of human expert involvement for ground truth establishment in a test set. The intended use states that "The clinical diagnosis of CSF shunt function or malfunction, incorporating the flow information from ShuntCheck, should be made only by a qualified neurosurgeon," implying neurosurgeons are the experts who would ultimately interpret the device's output in a clinical setting, but not for establishing ground truth in a validation study described here.

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

Not applicable. As no human expert-adjudicated test set is described, there is no mention of an adjudication method.

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 performed. The ShuntCheck is a non-invasive thermal convection device, not an AI-assisted diagnostic tool. Therefore, an MRMC study comparing human readers with and without AI assistance is not relevant to this device. The device provides "flow confirmed" or "flow not confirmed" output.

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

This is not a software-only "algorithm." It is a physical device (thermosensor array patch connected to a handheld "biodisplay" unit) that detects temperature changes to infer flow. The device itself provides a "flow confirmed" or "flow not confirmed" output, which can be considered its "standalone" output. The studies mentioned (bench testing, animal studies) assessed this device's ability to accurately provide this output. However, it's explicitly stated that "ShuntCheck cannot alone diagnose CSF shunt function or malfunction," and its output must be interpreted by a neurosurgeon.

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

The document implies that the ground truth for the animal studies was based on known flow rates (ml/hr) or the functional state of the shunt (e.g., presence or absence of flow) as established by experimental conditions in the animal models. For bench testing, the ground truth was related to known electrical resistances and expected temperature outputs.

8. The sample size for the training set

The device is not AI/machine learning based and therefore does not have a "training set" in the conventional sense of data used to train an algorithm. The development cycle would involve engineering design, prototyping, and testing, but not and algorithmic training set.

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

Not applicable, as there is no training set for an AI algorithm.

Ask a specific question about this device