Your browser doesn't support javascript.
loading
Show: 20 | 50 | 100
Results 1 - 1 de 1
Filter
Add more filters










Database
Language
Publication year range
1.
Eur J Radiol ; 138: 109664, 2021 May.
Article in English | MEDLINE | ID: mdl-33798933

ABSTRACT

INTRODUCTION: Distant metastases are found in the many of patients with lung cancer at time of diagnosis. Several diagnostic tools are available to distinguish between metastatic spread and benign lesions in the adrenal gland. However, all require additional diagnostic steps after the initial CT. The purpose of this study was to evaluate if texture analysis of CT-abnormal adrenal glands on the initial CT correctly differentiates between malignant and benign lesions in patients with confirmed lung cancer. MATERIALS AND METHODS: In this retrospective study 160 patients with endoscopic ultrasound-guided biopsy from the left adrenal gland and a contrast-enhanced CT in portal venous phase were assessed with texture analysis. A region of interest encircling the entire adrenal gland was used and from this dataset the slice with the largest cross section of the lesion was analyzed individually. RESULTS: Several texture parameters showed statistically significantly difference between metastatic and benign lesions but with considerable between-groups overlaps in confidence intervals. Sensitivity and specificity were assessed using ROC-curves, and in univariate binary logistic regression the area under the curve ranged from 36 % (Kurtosis 0.5) to 69 % (Entropy 2.5) compared to 73 % in the best fitting model using multivariate binary logistic regression. CONCLUSION: In lung cancer patients with abnormal adrenal gland at imaging, adrenal gland texture analyses appear not to have any role in discriminating benign from malignant lesions.


Subject(s)
Adrenal Gland Neoplasms , Lung Neoplasms , Adrenal Gland Neoplasms/diagnostic imaging , Diagnosis, Differential , Humans , Lung Neoplasms/diagnostic imaging , Retrospective Studies , Sensitivity and Specificity , Tomography, X-Ray Computed
SELECTION OF CITATIONS
SEARCH DETAIL
...