Last updated: February 18, 2010

Quality Control of NHANES II Xrays

Digitization and Quality Control

The NHANES II radiographs were digitized by the University of California at San Francisco and the Radix Corporation. All radiographs have been digitized on either a Lumisys 100 or 150 laser spot scanner, with a spot size of 175 microns. The cervical and lumbar spine images have a resolution of 1463x1755x12 bits (5 MBytes) and 2048x2487x12bits (10 MBytes), respectively. After each image has passed a three-tiered quality control procedure, the data is stored on erasable optical disk and is ready for inclusion in the archives optical jukebox.

Quality control (QC) of the NHANES II x-ray images consists of three independent stages. The QC done at each stage is as follows:

• Stage 1: This stage is done by a trained computer operator and laser scanner technician. The following operations are performed:
  • re-calibrate laser scanner with each scan
  • clean optics every 2-3 months
  • use step-wedge films to check scanner calibration every 2-3 months
  • clean pinch rollers regularly
  • visibly check each image for general contrast, image alignment, and for removal of identification tags
• Stage 2: This stage is done by a non-medical person trained to filter out images that do not meet the following criteria:
  • inspect each image to ensure that identification tags are not visible
  • check for sufficient contrast
  • check for correct image orientation
• Stage 3: This stage is being done at NLM by a trained physician under contract to NCHS. The physician answers the following questions concerning each image:
  • is the digitized image acceptable?
  • is the digitized image worse, same, or better than radiograph?
  • would a reader be able to detect and score the extent of osteophytes, subluxation, sclerosis, or disk space narrowing?

If an image is rejected at stage 1, the radiograph is re-digitized. Rejection at stage two or three eliminates the image from the archive, although such images might prove useful for future work in automating quality control. A separate database to archive these rejected images might be developed.