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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.

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The DigniCap™ Scalp Cooling System is indicated to reduce the likelihood of chemotherapy induced alopecia in women with breast cancer.

The Dignitana DigmiCap™ Scalp Cooling System consists of a computer controlled system that includes a refrigerated tank containing the cooling agent that is maintained at -8 ± 1 ℃. The liquid 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 thermometers. Deviations from the pre-set temperature are automatically adjusted by the system (scalp temperature can be controlled with an accuracy of ±2.0℃).

The DigniCap™ Scalp Cooling System components include the following:

Digni C3 system - Is a refrigerator unit with an integral control system operated via a touch screen monitor and is capable of controlling two separate cooling caps independently of each other. Scalp cooling is performed in conjunction with a silicon inner cap (DigniCap™), an outer neoprene cap (DigniTherm™), and the liquid coolant (DigniCool™).

DigniCap™ - A soft, tight-fitting silicon cap which has two separate cooling circuits, one for the front of the head and one for the back of the head plus a third sensor for overall safety control.

DigniCool™ - The liquid coolant monopropylene glycol (MPG5).

DigniTherm™ - The outer neoprene cap that insulates and keeps the inner cap in place. To improve cooling and ensure proper fitting, this cap is covers the DigniCap™ and includes a chin strap which is used to hold the cap in place. This neoprene cover cap, called the DigniTherm™, comes in different sizes and is colored coded to match the corresponding correct silicone Cooling Cap. In addition to acting as a means of maintaining cooling cap placement, this outer cap also provides insulation which improves cooling efficiency

DIGNISTICK™ – A component used to save data from a treatment or for troubleshooting when inserted in the slot. It can also be used to update software.

DIGNICARD™ – A key card which has to be inserted in order to start a treatment.

Acceptance Criteria and Device Performance for DigniCap™ Scalp Cooling System

1. Table of Acceptance Criteria and Reported Device Performance

2. Sample Size and Data Provenance

• Pivotal Study (effectiveness and safety):
  • Test Set Sample Size: 101 evaluable patients in the treatment group, 16 patients in the control group.
  • Data Provenance: Prospective, multi-center (6 sites), concurrent controlled clinical study conducted in the U.S. (based on the FDA De Novo submission context).
• Feasibility Study (safety and feasibility):
  * Test Set Sample Size: 19 evaluable patients.
  * Data Provenance: Prospective, 2-site clinical study conducted in the U.S.

3. Number of Experts and Qualifications for Ground Truth

• Pivotal Study:
  • For the primary effectiveness endpoint (Dean score ≤ 2), the assessment was based on patient self-assessment of standardized photographs. This does not involve independent expert grading in the primary outcome.
  • For an independent secondary assessment, "An independent panel review of the photographs was conducted and 73 patients (72%) were rated as treatment successes." The qualifications of these panel members are not specified in the provided text.
• Feasibility Study:
  • Hair loss was assessed by an independent panel consisting of: a hair dresser, a patient advocate, and a dermatologist specializing in hair. The number of experts within this panel is three. Specific years of experience are not provided for the individual experts.

4. Adjudication Method for the Test Set

• Pivotal Study: The primary endpoint was patient self-assessment against standardized photographs. This implies individual assessment rather than a consensus or adjudication method among multiple graders for the primary endpoint. For the independent panel review (secondary), the adjudication method is not described beyond "review of photographs."
• Feasibility Study: Hair loss assessment was done by an "independent panel" by "review of photographs blinded to patient and sequence." The specific adjudication method (e.g., majority vote, discussion to consensus) is not specified.

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

• A MRMC comparative effectiveness study, in the typical sense of evaluating human reader performance with and without AI assistance, was not performed.
• The pivotal study was a controlled clinical trial comparing the device (with human users) to a control group without the device. The "effect size of how much human readers improve with AI vs without AI assistance" is not applicable as this is a device for patients, not an AI diagnostic tool for readers. The study did, however, demonstrate a significant improvement in hair retention for patients using the device compared to those who did not.

6. Standalone (Algorithm Only) Performance

• A standalone (algorithm only) performance study was not performed or is not applicable in this context. The DigniCap™ Scalp Cooling System is a physical device used by patients, not an AI algorithm intended for automated analysis. The "software" component mentioned in the device description primarily controls cooling mechanisms, not performs diagnostic analysis.

7. Type of Ground Truth Used

• Pivotal Study (Primary Endpoint): Patient self-assessment based on the Dean Scale using standardized photographs.
• Pivotal Study (Secondary Independent Assessment): Independent panel review of photographs based on the Dean Scale.
• Feasibility Study: Independent panel review of photographs based on the Dean Scale, and also patient assessment following the Dean Scale.

8. Sample Size for the Training Set

• The provided text describes clinical studies (feasibility and pivotal) that serve as testing for the device's efficacy and safety. It does not describe a "training set" in the context of machine learning. The DigniCap™ is a mechanical device with software controls, not a machine learning model that requires a training set of data to learn from.

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

• As explained above, there is no mention of a "training set" in the machine learning sense in the provided document. The clinical studies represent testing of the device's performance, not training of an algorithm.

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