Advertisement

Pediatric Radiology

, 26:887 | Cite as

Standard method of diagnosis versus use of a computer database in the evaluation of skeletal dysplasias

  • R. K. Harned
  • L. E. Patrick
  • B. B. Gay
  • G. O. Atkinson
  • P. K. Niemer
  • J. B. Wyly
  • W. S. Clark
Article
  • 25 Downloads

Abstract

Objective

The objective of this study was to compare reference textbooks and the computer database, OSSUM, for accuracy and ease of use in the diagnosis of skeletal dysplasias.

Materials and methods

Twenty cases of clinically and radiologically established skeletal dysplasias were evaluated as unknowns by four pediatric radiologists. Readers 1 and 2 evaluated group A (10 cases) using reference texts and group B (10 cases) using OSSUM. Readers 3 and 4 evaluated group A using OSSUM and group B using reference texts. The radiologists independently listed their roentgenographic findings, the top three diagnoses, confidence level, difficulty level, and time spent on each case.

Results

The correct diagnosis was made in 68 % of both the reference text cases and the OSSUM cases. Difficulty level was significantly higher (3.5 vs 2.9,P=0.0013) and confidence significantly lower (3.3 vs. 2.3,P=0.0001) when using OSSUM. Average time spent on cases was 25 min with references and 30 min with OSSUM (P>0.05). However, there was a decrease in both the time (38 min vs 23 min,P=0.05) and the difficulty (3.9 vs 3.1,P=0.001) between the first five and the last five cases. The composite of four readers correctly identified 90 % of the skeletal dysplasias when the results of both methods were combined.

Conclusions

In the ability to reach a correct diagnosis, no difference was detected between the OSSUM and reference texts methods. The increased time necessary, greater difficulty and decreased confidence levels with OSSUM are expected to improve with increasing program familiarity. Use of both textbooks and the database was complementary.

Keywords

Osteogenesis Imperfecta Difficulty Level Skeletal Dysplasia Reference Text Multiple Epiphyseal Dysplasia 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. 1.
    Andersen PE Jr, Hauge M (1989) Congenital generalised bone dysplasias: a clinical, radiological, and epidemiological survey. J Med Genet 27: 37–44CrossRefGoogle Scholar
  2. 2.
    DiLiberti JH (1988) Use of computers in dysmorphology. J Med Genet 25:445–453CrossRefPubMedGoogle Scholar
  3. 3.
    Strømme P (1991) The diagnosis of syndromes by use of a dysmorphology data-base. Acta Paediatr Scand 80:106–109CrossRefPubMedGoogle Scholar
  4. 4.
    Winter RM, Baraitser M (1984) Malformation, syndromes: a diagnostic approach. Arch Dis Child 59:294–295CrossRefPubMedGoogle Scholar
  5. 5.
    Patton MA (1987) A computerized approach to dysmorphology. MD Cornput 4: 33–39Google Scholar
  6. 6.
    Taybi H, Lachman RS (1990) Radiology of syndromes, metabolic disorders, and skeletal dysplasias, 3rd edn. Year Book Medical Publishers, Littleton, Mass.Google Scholar
  7. 7.
    Kozlowski K, Beighton P (1984) Gamut index of skeletal dysplasias: an aid to radiodiagnosis. Springer, Berlin Heidelberg New YorkGoogle Scholar
  8. 8.
    Spranger JW, Langer LO Jr, Wiedeman HR (1974) Bone dysplasias: an atlas of constitutional disorders of skeletal development. Saunders, PhiladelphiaGoogle Scholar
  9. 9.
    Spranger JW et al (1992) International classification of osteochondrodysplasias. Eur J Pediatr 151: 407–415CrossRefPubMedGoogle Scholar

Copyright information

© Springer-Verlag 1996

Authors and Affiliations

  • R. K. Harned
    • 1
  • L. E. Patrick
    • 1
  • B. B. Gay
    • 1
  • G. O. Atkinson
    • 1
  • P. K. Niemer
    • 1
  • J. B. Wyly
    • 1
  • W. S. Clark
    • 2
  1. 1.Department of RadiologyEgleston Children’s Hospital of Emory UniversityAtlantaUSA
  2. 2.Department of BiostatisticsThe Rollins School of Public Health of Emory UniversityAtlantaUSA

Personalised recommendations