Characterization of limb lymphedema using the statistical analysis of ultrasound backscattering.

Lymphedema Nakagami distribution information entropy ultrasound imaging

Journal

Quantitative imaging in medicine and surgery
ISSN: 2223-4292
Titre abrégé: Quant Imaging Med Surg
Pays: China
ID NLM: 101577942

Informations de publication

Date de publication:
Jan 2020
Historique:
entrez: 21 1 2020
pubmed: 21 1 2020
medline: 21 1 2020
Statut: ppublish

Résumé

Lymphedema is a disease in which tissue swelling is caused by interstitial fluid retention in subcutaneous tissue. It is caused by a compromised lymphatic system. Lymphoscintigraphy is the current and primary modality used to assess lymphatic system dysfunction. Ultrasound elastography is a complementary tool used for evaluating the tissue stiffness of the lymphedematous limb. Tissue stiffness implies the existence of changes in tissue microstructures. However, ultrasound features related to tissue microstructures are neglected in clinical assessments of lymphedematous limbs. In this study, we aimed to evaluate the lymphedematous diagnostic values of ultrasound Nakagami and entropy imaging, which are, respectively, model- and nonmodel-based backscattered statistical analysis methods for scatterer characterization. A total of 60 patients were recruited, and lymphoscintigraphy was used to score the patient's clinical severity of each of their limb lymphedema (0: normal; 1: partial lymphatic obstruction; and 2: total lymphatic obstruction). We performed ultrasound examinations to acquire ultrasound backscattered signals for B-mode, Nakagami, and entropy imaging. The envelope amplitude, Nakagami, and entropy values, as a function of the patients' lymphatic obstruction grades, were expressed in terms of their median and interquartile range (IQR). The values were then used in both an independent For each increase in a patient's score from 0 to 2, the envelope amplitude values were 405.44 (IQR: 238.72-488.17), 411.52 (IQR: 298.53-644.25), and 476.37 (IQR: 348.86-648.16), respectively. The Nakagami parameters were 0.16 (IQR: 0.14-0.22), 0.26 (IQR: 0.23-0.34), and 0.24 (IQR: 0.16-0.36), respectively, and the entropy values were 4.55 (IQR: 4.41-4.66), 4.86 (IQR: 4.78-4.99), and 4.87 (IQR: 4.81-4.97), respectively. The P values between the normal control and lymphedema groups obtained from B-mode and Nakagami analysis were larger than 0.05; whereas that of entropy imaging was smaller than 0.05. The areas under the ROC curve for B-mode, Nakagami, and entropy imaging were 0.64 (sensitivity: 70%; specificity: 47.5%), 0.75 (sensitivity: 70%; specificity: 75%), and 0.94 (sensitivity: 95%; specificity: 87.5%), respectively. The current findings demonstrated the diagnostic values of ultrasound Nakagami and entropy imaging techniques. In particular, the use of non-model-based entropy imaging enables for improved performance when characterizing limb lymphedema.

Sections du résumé

BACKGROUND BACKGROUND
Lymphedema is a disease in which tissue swelling is caused by interstitial fluid retention in subcutaneous tissue. It is caused by a compromised lymphatic system. Lymphoscintigraphy is the current and primary modality used to assess lymphatic system dysfunction. Ultrasound elastography is a complementary tool used for evaluating the tissue stiffness of the lymphedematous limb. Tissue stiffness implies the existence of changes in tissue microstructures. However, ultrasound features related to tissue microstructures are neglected in clinical assessments of lymphedematous limbs. In this study, we aimed to evaluate the lymphedematous diagnostic values of ultrasound Nakagami and entropy imaging, which are, respectively, model- and nonmodel-based backscattered statistical analysis methods for scatterer characterization.
METHODS METHODS
A total of 60 patients were recruited, and lymphoscintigraphy was used to score the patient's clinical severity of each of their limb lymphedema (0: normal; 1: partial lymphatic obstruction; and 2: total lymphatic obstruction). We performed ultrasound examinations to acquire ultrasound backscattered signals for B-mode, Nakagami, and entropy imaging. The envelope amplitude, Nakagami, and entropy values, as a function of the patients' lymphatic obstruction grades, were expressed in terms of their median and interquartile range (IQR). The values were then used in both an independent
RESULTS RESULTS
For each increase in a patient's score from 0 to 2, the envelope amplitude values were 405.44 (IQR: 238.72-488.17), 411.52 (IQR: 298.53-644.25), and 476.37 (IQR: 348.86-648.16), respectively. The Nakagami parameters were 0.16 (IQR: 0.14-0.22), 0.26 (IQR: 0.23-0.34), and 0.24 (IQR: 0.16-0.36), respectively, and the entropy values were 4.55 (IQR: 4.41-4.66), 4.86 (IQR: 4.78-4.99), and 4.87 (IQR: 4.81-4.97), respectively. The P values between the normal control and lymphedema groups obtained from B-mode and Nakagami analysis were larger than 0.05; whereas that of entropy imaging was smaller than 0.05. The areas under the ROC curve for B-mode, Nakagami, and entropy imaging were 0.64 (sensitivity: 70%; specificity: 47.5%), 0.75 (sensitivity: 70%; specificity: 75%), and 0.94 (sensitivity: 95%; specificity: 87.5%), respectively.
CONCLUSIONS CONCLUSIONS
The current findings demonstrated the diagnostic values of ultrasound Nakagami and entropy imaging techniques. In particular, the use of non-model-based entropy imaging enables for improved performance when characterizing limb lymphedema.

Identifiants

pubmed: 31956528
doi: 10.21037/qims.2019.10.12
pii: qims-10-01-48
pmc: PMC6960425
doi:

Types de publication

Journal Article

Langues

eng

Pagination

48-56

Informations de copyright

2020 Quantitative Imaging in Medicine and Surgery. All rights reserved.

Déclaration de conflit d'intérêts

Conflicts of Interest: The authors have no conflicts of interest to declare.

Références

Radiology. 2018 Dec;289(3):759-765
pubmed: 30106341
Acta Physiol Scand. 1966 Mar;66(3):337-45
pubmed: 5331269
J Pathol. 1981 Mar;133(3):243-72
pubmed: 7463213
PLoS One. 2017 Aug 1;12(8):e0181789
pubmed: 28763461
J Reconstr Microsurg. 2016 Jan;32(1):56-65
pubmed: 25893630
Int J Mol Sci. 2017 Jan 17;18(1):
pubmed: 28106728
J Breast Health. 2017 Apr 01;13(2):83-87
pubmed: 31244534
Sci Rep. 2017 Jan 20;7:41004
pubmed: 28106118
J Pathol. 1981 Mar;133(3):229-42
pubmed: 7463212
Ann Surg. 2018 Sep;268(3):513-525
pubmed: 30004927
Lymphat Res Biol. 2018 Feb;16(1):36-42
pubmed: 28759307
J Plast Reconstr Aesthet Surg. 2015 Nov;68(11):1592-9
pubmed: 26239375
J Med Ultrason (2001). 2014 Jul;41(3):359-64
pubmed: 27277911
Breast J. 2012 Jul-Aug;18(4):357-61
pubmed: 22759095
Lymphat Res Biol. 2018 Apr;16(2):174-181
pubmed: 28956970
Ultrasound Med Biol. 2018 Jul;44(7):1327-1340
pubmed: 29622501
J Vasc Surg Venous Lymphat Disord. 2017 Mar;5(2):261-273
pubmed: 28214496
Ultrasound Med Biol. 2014 May;40(5):917-30
pubmed: 24462151
J Acoust Soc Am. 2007 Jun;121(6):3542-57
pubmed: 17552706
Microvasc Res. 2014 Nov;96:55-63
pubmed: 24956510

Auteurs

Ya-Lun Lee (YL)

Department of Medical Imaging and Intervention, Chang Gung Memorial Hospital at Linkou, Taoyuan, Taiwan.
Department of Biomedical Engineering and Environmental Sciences, National Tsing Hua University, Hsinchu, Taiwan.

Yen-Ling Huang (YL)

Department of Medical Imaging and Intervention, Chang Gung Memorial Hospital at Linkou, Taoyuan, Taiwan.

Sung-Yu Chu (SY)

Department of Medical Imaging and Intervention, Chang Gung Memorial Hospital at Linkou, Taoyuan, Taiwan.

Wen-Hui Chan (WH)

Department of Medical Imaging and Intervention, Chang Gung Memorial Hospital at Linkou, Taoyuan, Taiwan.

Ming-Huei Cheng (MH)

Division of Reconstructive Microsurgery, Department of Plastic and Reconstructive Surgery, Chang Gung Memorial Hospital, Chang Gung University, College of Medicine, Taoyuan, Taiwan.

Ying-Hsiu Lin (YH)

Department of Medical Imaging and Radiological Sciences, College of Medicine, Chang Gung University, Taoyuan, Taiwan.

Tu-Yung Chang (TY)

Department of Public Health, College of Public Health, China Medical University, Taichung, Taiwan.

Chih-Kuang Yeh (CK)

Department of Biomedical Engineering and Environmental Sciences, National Tsing Hua University, Hsinchu, Taiwan.

Po-Hsiang Tsui (PH)

Department of Medical Imaging and Intervention, Chang Gung Memorial Hospital at Linkou, Taoyuan, Taiwan.
Department of Medical Imaging and Radiological Sciences, College of Medicine, Chang Gung University, Taoyuan, Taiwan.
Institute for Radiological Research, Chang Gung University and Chang Gung Memorial Hospital at Linkou, Taoyuan, Taiwan.

Classifications MeSH