Recommendations for image prefetch or film digitization strategy based on an analysis of an historic radiology image database

J Digit Imaging. 1998 May;11(2):94-9. doi: 10.1007/BF03168731.


Picture archiving and communications systems (PACS) utilize short- and long-term storage to provide both rapid retrieval and large storage capacity. Owing to the practical limitations imposed on the size of the much faster short-term storage, it is important to use an effective algorithm in the retrieval of comparison images from long to short-term storage. A strategy must be used to maximize the likelihood that the relevant historic images have been previously retrieved into short-term memory. Data were collected with a database consisting of 754 consecutive examinations and 7,723 associated historic studies. The most frequent number of previous examinations was zero (11% of patients). In 45% of cases, no previous matching examinations had been performed. Two basic strategies of image retrieval were evaluated. The first algorithm retrieved the last n studies in chronological order. The second strategy tested was retrieval based on a defined interval of time. This strategy was found to be less efficient. By using the former strategy, a 91% success rate (defined as successful retrieval of the previous matching exam) was achieved with retrieval of only 30% of the prior exams. The second approach required retrieval of 70% of the prior exams to achieve a 90% success rate for the previous matching exam. However, the data from this latter strategy suggest that examinations are often ordered in clusters. Thus, there was found to be a 72% likelihood that a previous matching exam, if present, would available on a PACS after only 1 week of operation, and an 80% chance after only 1 month of operation. The data therefore suggest that digitization of film in a new PACS environment might not be necessary owing to the relatively short period of time required to populate the database with historical studies.

MeSH terms

  • Algorithms
  • Databases, Factual
  • Evaluation Studies as Topic
  • Humans
  • Information Storage and Retrieval*
  • Methods
  • Radiology Information Systems*