Search Results
Found 1 results
510(k) Data Aggregation
(56 days)
The DigniCap Delta® Scalp Cooling System is indicated to reduce the likelihood of chemotherapy-induced alopecia in cancer patients with solid tumors.
The DigniCap Delta Scalp Cooling System ("DigniCap Delta")is a device that is intended to function as a cooling system to reduce the likelihood of chemotherapy-induced alopecia in cancer patients with solid tumors. The proposed therapy of the new device is comparable to the therapy of the predicate device, DigniCap Scalp Cooling System (K170871).
DigniCap Delta cools fluid to a prescribed set temperature and circulates that cooled fluid through a cooling wrap and then back to the device. This mode of operation is equivalent to other scalp cooling devices. User operation of the DigniCap Delta system is carried out on the illuminated graphics display with the integrated touch control, located on the front of the unit. The navigation and selection buttons on the display are used to interface with the device.
The provided text is a 510(k) Premarket Notification for the DigniCap Delta Scalp Cooling System. This document focuses on demonstrating substantial equivalence to a predicate device (DigniCap Scalp Cooling System, K170871) rather than establishing new acceptance criteria and proving device performance against them through a clinical study.
Therefore, the requested information (acceptance criteria, study details, sample sizes, expert qualifications, adjudication, MRMC, standalone performance, ground truth, training set information) for a new, independent study demonstrating fundamental device performance against specific acceptance criteria is largely not present in this document.
Instead, the document details non-clinical bench testing to demonstrate that the modifications in the DigniCap Delta (subject device) do not raise new questions of safety or effectiveness compared to the already cleared predicate device.
However, I can extract the information that is present and indicate where the requested information is not applicable or not provided.
Description of Acceptance Criteria and Study to Prove Device Meets Acceptance Criteria
1. Table of acceptance criteria and the reported device performance:
Since this 510(k) relies on substantial equivalence and non-clinical bench testing for minor modifications, there isn't a table of "acceptance criteria" for a new clinical efficacy study in the traditional sense. The "acceptance criteria" are implied by the performance requirements tested during non-clinical bench testing to ensure the device performs as intended and is safe. The "reported device performance" is a summary statement that the device met these requirements.
| Acceptance Criteria (Implied from Non-Clinical Testing) | Reported Device Performance |
|---|---|
| Biocompatibility of Cooling Cap Materials (ISO 10993-1 compliant) | Met: Cap materials are biocompatible in accordance with ISO 10993-1. |
| Accessory Performance | Met: Device met all performance requirements and is considered safe and effective for its intended use. |
| Stable Fluid Temperature Verification | Met: The bench testing has demonstrated that the DigniCap Delta can maintain and adjust cooling fluid temperature as needed to meet the predetermined treatment specifications. (Coolant Temperature Range: -7 to 1.5°C) |
| Notifications and Alarms System Functionality | Met: Tested and confirmed to function as intended. |
| Electrical Safety (IEC 60601-1:2005(R)2012 and IEC 62133-2:2017 compliant) | Met: Electrical Safety Testing was conducted to the current standard. |
| Electromagnetic Compatibility (IEC 60601-1-2:2014 compliant) | Met: Electromagnetic Compatibility Testing was conducted to the current standard. |
| Software Verification and Validation | Met: Software verification and validation testing performed. |
| Overall Safety and Effectiveness (no new questions of safety/effectiveness compared to predicate) | Met: The collective results of the performance testing demonstrate that DigniCap Delta meets the established specifications necessary for consistent performance during its intended use and does not raise different questions of safety or effectiveness when compared to the predicate device. |
2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective):
- Sample Size for Test Set: Not applicable. No clinical test set (patient-based) was used as this submission relies on non-clinical bench testing and substantial equivalence to a predicate device.
- Data Provenance: Not applicable. The data is from non-clinical bench testing, not patient data.
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. There was no clinical test set requiring expert-established ground truth for a diagnostic or treatment outcome. Non-clinical testing results are verified against established engineering and regulatory standards by qualified personnel within the testing process.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set:
- Not applicable. No clinical test set was used requiring adjudication.
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 a scalp cooling system, not an AI diagnostic tool involving human readers.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:
- Not applicable. This device is a physical cooling system, not an algorithm. Its operation is "standalone" in that it performs its cooling function independently, but this is not the typical interpretation of "standalone" performance for an AI/algorithm-based device.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.):
- For the non-clinical testing, the "ground truth" refers to established engineering specifications, published standards (e.g., ISO 10993-1, IEC 60601 series), and the intended functional performance of the device (e.g., maintaining specific temperatures, correct alarm function).
8. The sample size for the training set:
- Not applicable. This device does not involve a "training set" in the context of machine learning or AI.
9. How the ground truth for the training set was established:
- Not applicable. No training set was used.
Ask a specific question about this device
Page 1 of 1