title: Digital image documentation for quality assessment.
abstract: OBJECTIVE
  To demonstrate the feasibility of the use of digital images to document routine cases and to perform diagnostic quality assessment.
  
  
  METHODS
  Pathologists documented cases by acquiring up to 12 digital images per case. The images were sampled at 25:1, 50:1, 100:1, 200:1, or 400:1 magnifications, according to adequacy in aiding diagnosis. After each acquisition, the referral pathologist marked a region of interest within each acquired image in order to evaluate intrinsic redundancy. The extrinsic redundancy was determined by counting the unnecessary images. Cases were randomly selected and reviewed by one pathologist. The quality of each image, the possibility of accomplishing a diagnosis based on images, and the degree of agreement was evaluated.
  
  
  RESULTS
  During routine practice, 1469 cases were documented using 3902 images. Most of the images were acquired at higher power magnifications. From all acquired cases, 143 cases and their 373 related images were randomly selected for review. In 88.1% (126/143) of reviewed cases, it was possible to accomplish the diagnosis based on images. In 30.2% (38/126) of these cases, the reviewer considered that the diagnosis could be accomplished with fewer images. The referral pathologist and the reviewer found intrinsic redundancy in 57.8% and 54.5% of images, respectively.
  
  
  CONCLUSIONS
  Our results showed that digital image documentation to perform diagnostic quality assessment is a feasible solution. However, owing to the impact on routine practice, guidelines for acquisition and documentation of cases may be needed.
authors.affiliation: Institute of Molecular Pathology and Immunology of the University of Porto, Porto, Portugal. dcruz@ipatimup.pt
authors.forename: D
authors.initials: D
authors.lastname: Cruz
authors.forename: C
authors.initials: C
authors.lastname: Valentí
authors.forename: A
authors.initials: A
authors.lastname: Dias
authors.forename: M
authors.initials: M
authors.lastname: Seixas
authors.forename: F
authors.initials: F
authors.lastname: Schmitt
mesh_terms: D003933:Diagnosis; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008853:Microscopy / Q000592:standards; D010336:Pathology / Q000592:standards*; D011786:Quality Control; D012984:Software