A combination of ultrasound and contrast-enhanced ultrasound improves diagnostic accuracy for the differentiation of cervical tuberculous lymphadenitis from primary lymphoma.

Contrast-enhanced ultrasound LASSO. cervical tuberculous lymphadenitis lymph nodes lymphoma

Journal

Clinical hemorheology and microcirculation
ISSN: 1875-8622
Titre abrégé: Clin Hemorheol Microcirc
Pays: Netherlands
ID NLM: 9709206

Informations de publication

Date de publication:
18 Aug 2023
Historique:
pubmed: 21 8 2023
medline: 21 8 2023
entrez: 21 8 2023
Statut: aheadofprint

Résumé

To present a method combining ultrasound (US) and contrast-enhanced ultrasound (CEUS) features for differential diagnosis of cervical tuberculous lymphadenitis (CTL) and primary lymphoma. A total of 155 patients with CTL (n = 49) and lymphoma (n = 106) who underwent US and CEUS were retrospectively included. The features extracted from US and CEUS and the significant clinical data were created three models using the least absolute shrinkage and selection operator and logistic regression analysis. The diagnostic performance of the models was assessed using the area under the curve (AUC). The combined model outperformed US model and CEUS model in distinguish CTL from lymphoma achieved favorable performances in training set and validation set with AUCs of 0.958 and 0.946 as well as high accuracies (91.7% and 87.2%), sensitivities (95.9% and 84.4%) and specificities (82.4% and 93.3%). Delong's test showed that among the three models, combined model was significantly different from the other two models in training set (p = 0.011 and 0.029, respectively) and validation set (p = 0.018 and 0.001, respectively). A combination of US and CEUS achieved good diagnostic performance in differentiating lymphoma and CTL, which might aid in clinical decision-making.

Identifiants

pubmed: 37599529
pii: CH231876
doi: 10.3233/CH-231876
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Auteurs

Naxiang Liu (N)

Department of Ultrasound, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, China.

Yijie Chen (Y)

Department of Ultrasound, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, China.

Yaoqin Wang (Y)

Department of Ultrasound, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, China.

Weiqin Huang (W)

Department of Ultrasound, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, China.

Lili Zhan (L)

Department of Ultrasound, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, China.

Zhongshi Du (Z)

Department of Ultrasound, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, China.

Zhaoming Zhong (Z)

Department of Ultrasound, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, China.

Zhougui Wu (Z)

Department of Ultrasound, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, China.

Youhong Shen (Y)

Department of Ultrasound, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, China.

Xiaohong Deng (X)

Department of Ultrasound, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, China.

Shixiong Ni (S)

Department of Ultrasound, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, China.

Lina Tang (L)

Department of Ultrasound, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, China.

Classifications MeSH