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510(k) Data Aggregation
(217 days)
MedicCO2LON (MedicCO2LON)
The MedicCO2LON device is intended to be used for colonic distension with CO2 gas for CT Colonography and conventional Colonoscopy procedures.
MedicCO2LON is designed to function with specific colonic insufflation administration sets that allow passage of gas from the device to the colorectal cavity. MedicCO2LON should only be used with administration sets specifically designed for this purpose.
The device should only be used by personnel trained in the practice of undertaking CT Colonography and conventional Colonoscopy examinations and the use of an automatic insufflation device.
The device should only be used for CT Colonography or conventional Colonoscopy procedures and should not be used for any other patient examination procedure.
MedicCO2LON is an automated insufflation device designed for administering and requlating colonic distension by insufflation with carbon dioxide qas, in preparation for and during CT Colonography (CTC or Virtual Colonoscopy) and conventional Colonoscopy.
Construction:
The MedicCO2LON colonic insufflator is constructed using a plastic (PC/ABS) external shell covering a metal internal frame, internal components are low voltage (3.3V, 12V and 24V DC) powered from an internal mains connected power supply.
None of the parts of the MedicCO2LON contact the patient directly and the user only has transient contact with the unit, with it being table or trolley mounted.
Use period:
The units are for short term use (normally no more than 30 min) and provides. to the patient, CO2 via an external pressure regulator to the device to insufflate the patient using a standard administration set at up to 30mmHg
The provided document is a 510(k) summary for a medical device called MedicCO2LON, a colonic insufflator. This document focuses on demonstrating substantial equivalence to a predicate device, the BRACCO PROTOCOX2L TOUCH Colon Insufflator (K132192), rather than providing detailed acceptance criteria and a comprehensive study report for a novel AI/software-based medical device.
Therefore, many of the requested details regarding acceptance criteria for AI models, sample size for test/training sets, expert qualifications, ground truth establishment, MRMC studies, and standalone performance are not present in this type of submission. This document primarily focuses on the physical and functional comparison of a new device with an existing predicate, and engineering testing, not clinical performance studies with AI components.
However, I can extract the acceptance criteria as presented for this specific device's performance validation based on its physical/functional characteristics, and the reported performance.
Here's an attempt to answer the questions based only on the provided text, while acknowledging the limitations for an AI/software-centric request:
Acceptance Criteria and Device Performance for MedicCO2LON (Physical/Functional Device)
The provided document describes the functional performance and safety characteristics of the MedicCO2LON device, comparing it to a predicate device. The "acceptance criteria" can be inferred from the performance targets and comparisons made. The study described is primarily bench testing and engineering validation to demonstrate equivalence, not a clinical trial involving human readers or AI.
1. A table of acceptance criteria and the reported device performance
| Function/Parameter | Acceptance Criteria (Implied/Predicate Performance) | Reported MedicCO2LON Performance | Test Report Document Identification |
|---|---|---|---|
| Displayed Data (Input Pressure) | Current output pressure (Predicate) | Current Input Pressure | MCODOC121-102 Appendix Image |
| Displayed Data (Gas Flow Rate) | Not defined (Predicate) | Gas Flow Rate | MCODOC121-102 Appendix Image |
| Displayed Data (Delivered Gas Volume) | Delivered Gas Volume (Predicate) | Delivered Gas Volume | MCODOC121-102 Appendix Image |
| Displayed Data (Gas Supply Level) | Gas Supply level (Predicate) | Gas Supply level | MCODOC121-102 Appendix Image |
| Control Data (Start/Stop/Resume Flow) | Start / Stop flow (Predicate) | Start / Stop / Resume flow | MCODOC121-102 Appendix Image |
| Control Data (Reset Delivered Volume) | Reset Delivered Volume (Predicate) | Reset Delivered Volume | MCODOC121-102 Appendix Image |
| Control Data (Set Target Pressure) | Set Target Pressure (Predicate) | Set Target Pressure | MCODOC121-102 Appendix Image |
| Control Data (Set Maximum Flow) | Not defined (Predicate) | Set Maximum Flow | MCODOC121-102 Appendix Image |
| Maximum total gas volume | No maximum limit (Predicate) | 12.0 L | MCODOC166-101 Page 7 section 3.3 |
| Gas Volume Profile | Flow stops at 3L to 10L (Predicate) | Stops at 4,6,8,10,12L | MCODOC121-102 Volume Accuracy test |
| Default target flow rate | 3.0LPM (Predicate) | 3.0LPM | Power up default on screen |
| Gas Flow Start Profile | Various steps for 0-1.0L delivered volume (Predicate) | 0.5LPM per 0.5L Volume. | MCODOC121-102 Flow rate Accuracy test |
| Target Pressure | 0 to 35mmHg (Predicate) | 0 to 30mmHg | MCODOC121-102 Pressure Accuracy test |
| Volume Accuracy | Unknown (Predicate) | +/- 20% at current reading. | MCODOC121-102 Volume Accuracy test |
| Flow Adjustment | 1.0LPM (Predicate) | 0.5LPM | MCODOC121-102 Flow rate Accuracy test |
| Flow Accuracy | +20% @ 3LPM (Predicate) | +/- 10% at 3LPM | MCODOC121-102 Flow rate Accuracy test |
| Pressure Accuracy | +/- 10% (Predicate) | +/- 1mmHg of current reading | MCODOC121-102 Pressure Accuracy test |
| Safety overpressure relief | Independent Redundant Mechanical Relief (Predicate) | Independent redundant mechanical relief | MCODOC166-101 Page 6 section 3.2 |
| Safety pressure relief (mechanical) | 1.5psi (78mmHg) nominal (Predicate) | 1.5psi (78mmHg) | MCODOC166-101 Page 6 section 3.2 |
| Safety pressure relief accuracy (mechanical) | Unknown (Predicate) | +/- 20mmHg of trip pressure | MCODOC166-101 Page 6 section 3.2 |
| Safety pressure relief accuracy (electronic) | 50mmHg for 5 seconds (Predicate) | 50mmHg for 5 seconds | MCODOC166-101 Page 6 section 3.2 |
2. Sample size used for the test set and the data provenance
The document does not specify a "sample size" in terms of patient cases or imaging data. The testing described is engineering and performance testing of the device's physical functions (e.g., flow rate, pressure accuracy, volume delivery). These are physical measurements, not statistical analyses of clinical data from patients. Therefore, data provenance (country, retrospective/prospective) is not applicable in the context of this type of device submission.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts
This is not applicable. The "ground truth" for this device's performance is typically established by calibrated measurement equipment and engineering standards, not by human expert assessment of clinical images.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set
Not applicable, as the "test set" refers to engineering measurements, not clinical case reviews.
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 colonic insufflator, a physical medical device for gas delivery, not an AI software supporting human readers.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
Not applicable. This is a physical device, not an algorithm.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)
The "ground truth" for the device's performance metrics (e.g., pressure, flow, volume) would be derived from:
- Calibrated measurement equipment: e.g., precise pressure gauges, flow meters, volume displacement methods.
- Engineering specifications and standards: Adherence to established safety and performance norms for medical devices.
- Comparison to predicate device's established performance.
8. The sample size for the training set
Not applicable. This is not a machine learning device.
9. How the ground truth for the training set was established
Not applicable. This is not a machine learning device.
In summary, the provided FDA 510(k) summary is for a Class II medical device (colonic insufflator) that is a physical apparatus, not an AI/software device. Consequently, the performance validation outlined focuses on engineering specifications, safety features, and functional equivalence to a predicate device, rather than the types of data-driven performance studies typically associated with AI/ML-based medical devices (e.g., diagnostic imaging aids).
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