Using Texture Analysis of Neck Computed Tomography Images to Differentiate Primary Hyperparathyroidism From Normal Controls

Copyright © 2023 Wolters Kluwer Health, Inc. All rights reserved..

OBJECTIVE: To investigate the utility of texture analysis in detecting osseous changes associated with hyperparathyroidism on neck CT examinations compared with control patients and to explore the best regions in the head and neck to evaluate changes in the trabecular architecture secondary to hyperparathyroidism.

METHODS: Patients with hyperparathyroidism who underwent a 4D CT of the neck with contrast were included in this study. Age-matched control patients with no history of hyperparathyroidism who underwent a contrast-enhanced neck CT were also included. Mandibular condyles, bilateral mandibular bodies, the body of the C4 vertebra, the manubrium of the sternum, and bilateral clavicular heads were selected for analysis, and oval-shaped regions of interest were manually placed. These segmented areas were imported into an in-house developed texture analysis program, and 41 texture analysis features were extracted. A mixed linear regression model was used to compare differences in the texture analysis features contoured at each of the osseous structures between patients with hyperparathyroidism and age-matched control patients.

RESULTS: A total of 30 patients with hyperparathyroidism and 30 age-matched control patients were included in this study. Statistically significant differences in texture features between patients with hyperparathyroidism and control patients in all 8 investigated osseous regions. The sternum showed the greatest number of texture features with statistically significant differences between these groups.

CONCLUSIONS: Some CT texture features demonstrated statistically significant differences between patients with hyperparathyroidism and control patients. The results suggest that texture features may discriminate changes in the osseous architecture of the head and neck in patients with hyperparathyroidism.

Medienart:

E-Artikel

Erscheinungsjahr:

2024

Erschienen:

2024

Enthalten in:

Zur Gesamtaufnahme - volume:48

Enthalten in:

Journal of computer assisted tomography - 48(2024), 1 vom: 02. Jan., Seite 137-142

Sprache:

Englisch

Beteiligte Personen:

Kawashima, Yusuke [VerfasserIn]
Fujita, Akifumi [VerfasserIn]
Buch, Karen [VerfasserIn]
Qureshi, M Mustafa [VerfasserIn]
Li, Baojun [VerfasserIn]
Takumi, Koji [VerfasserIn]
Rai, Aayushi [VerfasserIn]
Chapman, Margaret N [VerfasserIn]
Sakai, Osamu [VerfasserIn]

Links:

Volltext

Themen:

Journal Article

Anmerkungen:

Date Completed 15.01.2024

Date Revised 15.01.2024

published: Print-Electronic

Citation Status MEDLINE

doi:

10.1097/RCT.0000000000001517

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

NLM360313914