K Number
K042232
Manufacturer
Date Cleared
2004-10-05

(49 days)

Product Code
Regulation Number
892.2040
Panel
RA
Reference & Predicate Devices
AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
Intended Use

The intended uses of the NP-2600 Series Imagers is high resolution hard copy imaging of digital image source material and through the conversion of electronic signals from a wide variety of direct/indirect medical imaging modality outputs. The hardcopy output includes however is not limited to, digital radiography, nuclear medicine, ultrasound, CT, MRI, CR and Radiation Therapy planning; however, does not include digital mammography hardcopy. Images are suitable for medical image diagnosis use and referral. The system is intended for use by medical radiologists, imaging modality specialists, and communications to referring physicians.

Device Description

The NP-2600 Series Imagers are dry, thermal, color-only (NP-2600), grayscale only (NP-26xx) and grayscale/color(NP-2660) printer/imagers. The devices produce continuous tone, diagnostic quality BM images on transmissive film and reflective incident-light-viewed media. The color images produced via dye-diffusion technology are photographic quality implementing a "CRT to Image" matching process for medical applications.

AI/ML Overview

The provided text describes the Codonics NP-2600 Series Medical Dry Imagers, a device for high-resolution hardcopy imaging of digital medical images. However, it does not contain specific acceptance criteria or details of a study designed to prove the device meets such criteria in terms of analytical or clinical performance metrics.

The document states that "Laboratory tests have documented effective application and expected results consistent with predicate devices currently in commercial distribution and additional verification and validation testing is planned prior to release." This suggests that some testing was performed, but the specifics of acceptance criteria and a detailed study report are not present.

Here's a breakdown of the information that can be extracted and what is missing:


1. Table of Acceptance Criteria and Reported Device Performance

Acceptance Criteria (Inferred from description of performance characteristics)Reported Device Performance (from text)
Maintain data integrity with interpolation and scalingInterpolation and scaling of images without Lossy data compression is employed
Optimize color and CRT image hardcopy display resultsValidated digital linear and visual linear routines and verified industry/modality specific Look Up Tables (LUTs) are applied
Pixel size for resolution81u (microns) for the NP-2600 Series Imagers
Pixel resolution (dpi)12.4 pixels/mm or 314 dpi
Grayscale resolution (discernible levels)A palate of 256 levels of discernable grey
Color palate (levels of each color)256 levels each of yellow, magenta, and cyan
Total color palate16.7 million colors
Image quality suitable for medical useSMPTE resolution and contrast pattern and uniform density response function confirms quality suitable for the intended medical imaging use.
Electrical safety complianceUL 2601-1, CAN/CSA-C22.2 No 601.1-M90, IEC EN-60601-1
Electromagnetic standards complianceEN-60601-1-2 (2001)
Performance consistent with predicate devices"Laboratory tests have documented effective application and expected results consistent with predicate devices currently in commercial distribution"

Missing: Specific quantitative acceptance criteria (e.g., minimum spatial frequency response, specific density response tolerances, exact uniformity metrics). The current performance descriptions are generally qualitative or provide a single value without a defined acceptable range.


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

The document mentions "printer resolution pattern testing" and "clinical studies" were performed. However, it does not specify:

  • The sample size used for the test set (e.g., number of images, number of printouts).
  • The data provenance (e.g., country of origin of the data, retrospective or prospective).

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

The document mentions "clinical studies" and that images are "suitable for medical image diagnosis use." However, it does not specify:

  • The number of experts used to establish ground truth for any test set.
  • The qualifications of those experts (e.g., radiologist with 10 years of experience).

4. Adjudication method for the test set

The document does not mention any adjudication method for establishing ground truth or evaluating performance in a test set.


5. If a multi-reader multi-case (MRMC) comparative effectiveness study was done

The document does not mention a multi-reader multi-case (MRMC) comparative effectiveness study. Therefore, there is no information on the effect size of how much human readers improve with AI vs. without AI assistance (as this is an imaging device, not an AI assistance tool in this context).


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

The device is a hardcopy imager. Its "standalone" performance is described by its physical and performance characteristics (pixel size, resolution, color palate, etc.) and its ability to produce diagnostic quality images. The text states:

  • "The NP-2600 Series Imagers are dry, thermal, color-only (NP-2600), grayscale only (NP-26xx) and grayscale/color(NP-2660) printer/imagers."
  • "The devices produce continuous tone, diagnostic quality BM images on transmissive film and reflective incident-light-viewed media."
  • "The SMPTE resolution and contrast pattern and uniform density response function confirms quality suitable for the intended medical imaging use."

This confirms that its standalone performance in producing images was assessed against relevant industry standards (SMPTE pattern testing). However, specific metrics from these tests beyond general confirmation of suitability are not detailed as specific acceptance criteria or study results.


7. The type of ground truth used

The document implicitly refers to "diagnostic quality" images and "quality suitable for the intended medical imaging use." This suggests that the ground truth for image quality is based on industry standards and expectations for medical image diagnosis, likely involving visual assessment against reference patterns (like the SMPTE resolution and contrast pattern). However, it does not explicitly state the type of ground truth used (e.g., expert consensus, pathology, outcomes data) for a formal study dataset.


8. The sample size for the training set

The device is a printer/imager, not a machine learning algorithm that requires a training set in the typical sense. It relies on "industry standard format conversion software and image rendering algorithms" and "validating digital linear and visual linear routines and verified industry/modality specific Look Up Tables (LUTs)". Therefore, the concept of a "training set" for an algorithm isn't directly applicable in this context.


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

As above, the concept of a training set for an algorithm is not applicable. The "ground truth" for the device's image rendering capabilities would be based on established colorimetry standards, grayscale standards, and visual perception requirements for diagnostic medical imaging.

§ 892.2040 Medical image hardcopy device.

(a)
Identification. A medical image hardcopy device is a device that produces a visible printed record of a medical image and associated identification information. Examples include multiformat cameras and laser printers.(b)
Classification. Class II (special controls; voluntary standards—Digital Imaging and Communications in Medicine (DICOM) Std., Joint Photographic Experts Group (JPEG) Std., Society of Motion Picture and Television Engineers (SMPTE) Test Pattern). The device is exempt from the premarket notification procedures in subpart E of part 807 of this chapter subject to the limitations in § 892.9.