Search Results

The DigniCap® Scalp Cooling System is indicated to reduce the likelihood of chemotherapy-induced alopecia in cancer patients with solid tumors.

The DigniCap® Scalp Cooling System consists of a computer controlled system that includes a refrigerated tank containing the liquid coolant that is maintained at -7 ± 2°C. The coolant circulates from the cooling unit to and through the channels of the cap and back to the cooling unit. The scalp temperature is monitored by three separate sensors. Deviations from the treatment temperature are automatically adjusted by the system (scalp temperature can be controlled with an accuracy of ± 2.0°C). The DigniCap® Scalp Cooling System components include the following:
Digni C3 – Is a refrigerator unit with an integral control system operated via a touch screen and is capable of controlling two separate DigniCap® Cooling caps independently of each other. Scalp cooling is performed in conjunction with a silicone inner cap (DigniCap®), an outer neoprene cap (DigniTherm), and the liquid coolant (DigniCool).
DigniCap® – A soft, tight-fitting silicone cap which has two separate cooling circuits, one for the front and one for the back of the head. Each cooling circuit is equipped with a temperature sensor, and the cap is also equipped with a third sensor for safety control. The cap is available in different sizes.
DigniCool - The liquid coolant monopropylene glycol.
DigniTherm - The outer neoprene cap that insulates and keeps the inner cap in place. This neoprene cover cap, called the DigniTherm, comes in different sizes and is colored coded to match the corresponding DigniCap® Cooling cap.
DigniStick- A component used to save data from a treatment or for troubleshooting. It can also be used to update software.
DigniCard - A key card which has to be inserted in order to start a treatment.

The provided document is a 510(k) summary for the DigniCap Scalp Cooling System. It focuses on the substantial equivalence to a predicate device and an expanded indication for use.

Based on the document, here's a breakdown of the requested information:

1. Table of Acceptance Criteria and Reported Device Performance

The FDA 510(k) summary for K170871 does not explicitly define acceptance criteria in terms of specific performance metrics (e.g., success rate thresholds) that the device must meet for this specific submission. Instead, it relies on demonstrating substantial equivalence to a previously cleared device (DEN150010) and provides a literature review of clinical studies from outside the U.S. to support the expanded indication for use.

The clinical studies vary in their definitions of success and methods of assessment. Here's a summary of the reported success rates and the conditions under which they were achieved, derived from "Table 1 Clinical Data with the DigniCap® Scalp Cooling System Outside of U.S.":

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

• Test Set (Clinical Data): The document refers to a literature review of 18 clinical evaluations outside of the U.S.
  • The total number of unique patients across all studies where a sample size is specified appears to be over 1000. For instance, Hernández et al. had 204 patients, Fehr et al. had 55, Drinkut et al. had 34, Campennì et al. had 109, Schaffrin-Nabe et al. (2015) had 226, Andrews et al. had 122, Friedrich and Carstensen had 83, Udrea et al. had 108, Meunier et al. had 133, Ekwall et al. had 43, Abramov et al. had 20, Kato et al. had 359, Byahov et al. had 77, Ridderheim et al. had 74, Henriksen et al. had 26, and Lundgren et al. had 9.
  • Data Provenance: The studies were conducted in various countries outside the U.S., including: Mexico, Germany, Switzerland, Australia, Romania, France, Sweden, Russia, and Japan.
  • Retrospective or Prospective: The studies are a mix of retrospective, single-arm prospective non-randomized studies, and one randomized prospective study (Ekwall et al., 2013). The document explicitly mentions "These studies did not have long term follow up, and were single armed non-randomized prospective studies" in a general statement (Page 6), though "Table 1" clarifies the nature of each study more specifically.

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

The document does not provide details on the number of experts or their specific qualifications (e.g., number of years of experience) used to establish ground truth. Assessments of hair loss were performed by:

• Physicians/Treating Physiicans: Campennì et al., Henriksen et al.
• Nursing staff: Drinkut et al.
• Patients/Patient self-assessment: Drinkut et al., Campennì et al., Meunier et al., Ekwall et al., Henriksen et al.
• Independent observers/Investigators: Lundgren et al., Ekwall et al.
• Photos/Photo documentation: Hernández et al., Drinkut et al., Friedrich and Carstensen, Ekwall et al., Kato et al., Ridderheim et al.

4. Adjudication method for the test set

The document does not describe specific adjudication methods (e.g., 2+1, 3+1) for the assessment of hair loss. The methods vary by study and typically involve a single assessment by the listed parties (physicians, nurses, patients, or independent observers), or photograph review.

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, an MRMC comparative effectiveness study was not done. This document pertains to a medical device (scalp cooling system), not an AI algorithm for diagnosis or interpretation. Therefore, the concept of "human readers improve with AI vs without AI assistance" is not applicable in this context.

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

• Not applicable. The DigniCap Scalp Cooling System is a physical medical device. It is not an algorithm, and the concept of "standalone performance" for an algorithm without human involvement does not apply. The device's performance is measured by its efficacy in reducing hair loss in human patients undergoing chemotherapy.

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

The "ground truth" for assessing the device's effectiveness was primarily based on:

• Clinical assessment of hair loss: This was done using various scales (Dean scale, WHO scale, US NCI CTCAE scale) and patient self-assessments.
• Photo documentation: Used in several studies for objective assessment of hair loss.
• Patient outcomes data: Success was often defined by a percentage of hair loss (e.g., <50% hair loss, <25% hair loss, no visible hair loss, not needing a wig).
• Hair-mass-index (HMI) using a trichometer: Schaffrin-Nabe et al. (2016).

8. The sample size for the training set

This 510(k) relies on previous testing and a literature review for an expanded indication. It does not describe a "training set" in the context of an AI/machine learning model. The clinical data reviewed are for validating the device's efficacy, not for training an algorithm.

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

Not applicable, as there is no mention of a training set for an AI/machine learning model. The efficacy data are drawn from existing clinical studies.

Ask a specific question about this device