Hiring in life sciences? Share your open positions with our professional community. Read more Close

Advertisement

Automated fractal analysis of trabecular bone in multiple myeloma: a macro-based radiographic study.

Created on 20 Jul 2026

Authors

Ozlem Busra Dogan, Hatice Boyacioglu Erden

Published in

BMC oral health. Jul 20, 2026. Epub Jul 20, 2026.

Abstract

This study aimed to investigate the applicability of fractal analysis for evaluating trabecular bone microarchitecture in multiple myeloma patients while implementing an automated macro-based workflow to provide reproducible and standardized post-processing analysis with reduced operator-dependent variability.
The study included 41 patients with multiple myeloma and 41 age- and sex-matched healthy controls. Fractal dimension measurements were initially performed manually using the conventional ImageJ/FracLac box-counting method. Subsequently, a macro-based automated workflow was evaluated for reproducibility and standardization of the analysis process.
No statistically significant differences were observed between the multiple myeloma and control groups for ROI1 (1.5329 ± 0.043 vs. 1.5368 ± 0.040, p = 0.674), ROI2 (1.5320 ± 0.042 vs. 1.5322 ± 0.041, p = 0.979), or ROI3 (1.5361 ± 0.049 vs. 1.5371 ± 0.048, p = 0.928). Intra-observer reliability was excellent (ICC = 0.91, 95% CI: 0.857-0.949), and agreement between manual and automated fractal dimension measurements was perfect.
Fractal dimension analysis did not show statistically significant differences between multiple myeloma patients and controls in this cohort, suggesting limited discriminative value of the method for structural assessment of multiple myeloma under the present conditions. However, the macro-focused workflow was compatible with manual measurements and may provide a standardized and repeatable framework that could help reduce operator-induced variability in image processing and analysis, thereby supporting methodological consistency in future imaging research.

PMID:
42472795
Bibliographic data and abstract were imported from PubMed on 20 Jul 2026.

Read full publication at:
Please sign in to see all details.

Advertisement

Stats

  • Community rating n/a 0 votes
  • Reviewers' rating n/a 0 votes
  • Your rating

1-terrible, 9-excellent. How would you rate this publication? Sign in in to submit your rating.

  • Recommendations n/a n/a positive of 0 vote(s)
  • Views 15
  • Comments 0

Recommended by

  • No recommendations yet.

Post a comment

You need to be signed in to post comments. You can sign in here.

Comments

There are no comments yet.

Advertisement