Clinical evaluation of Duchenne muscular dystrophy severity using ultrasound small-window entropy imaging

Dong Yan, Qiang Li, Chia Wei Lin, Jeng Yi Shieh, Wen Chin Weng*, Po Hsiang Tsui*

*Corresponding author for this work

Research output: Contribution to journalJournal Article peer-review

12 Scopus citations

Abstract

Information entropy of ultrasound imaging recently receives much attention in the diagnosis of Duchenne muscular dystrophy (DMD). DMD is the most common muscular disorder; patients lose their ambulation in the later stages of the disease. Ultrasound imaging enables routine examinations and the follow-up of patients with DMD. Conventionally, the probability distribution of the received backscattered echo signals can be described using statistical models for ultrasound parametric imaging to characterize muscle tissue. Small-window entropy imaging is an efficient nonmodel-based approach to analyzing the backscattered statistical properties. This study explored the feasibility of using ultrasound small-window entropy imaging in evaluating the severity of DMD. A total of 85 participants were recruited. For each patient, ultrasound scans of the gastrocnemius were performed to acquire raw image data for B-mode and small-window entropy imaging, which were compared with clinical diagnoses of DMD by using the receiver operating characteristic curve. The results indicated that entropy imaging can visualize changes in the information uncertainty of ultrasound backscattered signals. The median with interquartile range (IQR) of the entropy value was 4.99 (IQR: 4.98-5.00) for the control group, 5.04 (IQR: 5.01-5.05) for stage 1 patients, 5.07 (IQR: 5.06-5.07) for stage 2 patients, and 5.07 (IQR: 5.06-5.07) for stage 3 patients. The diagnostic accuracies were 89.41%, 87.06%, and 72.94% for ≥stage 1, ≥stage 2, and ≥stage 3, respectively. Comparisons with previous studies revealed that the small-window entropy imaging technique exhibits higher diagnostic performance than conventional methods. Its further development is recommended for potential use in clinical evaluations and the follow-up of patients with DMD.

Original languageEnglish
Article number715
JournalEntropy
Volume22
Issue number7
DOIs
StatePublished - 07 2020

Bibliographical note

Publisher Copyright:
© 2020 by the authors.

Keywords

  • Backscattered signals
  • Duchenne muscular dystrophy
  • Entropy
  • Ultrasound

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