Skip to main content
Key Specialties
Cardiology Diabetology Endocrinology Gastroenterology Geriatrics and Gerontology Gynecology and Obstetrics Hematology Infectious Disease Internal Medicine Nephrology Neurology Oncology Pediatrics Respiratory Medicine Rheumatology Surgery
Congress Coverage
2024 ACC Congress 2023 ESMO Congress 2023 EASD Congress 2023 ERS Congress 2023 ESC Congress
Clinical Collections
Advances in Alzheimer’s

Keynote webinar | Spotlight on medication adherence

LIVE: Thursday 27th June 2024, 18:00-19:30 (CEST)
Join our expert panel to discover why you need to understand the drivers of non-adherence in your patients, and how you can optimize medication adherence in your clinics to drastically improve patient outcomes.
ADVANCED SEARCH
Log in
Top
Cancer Imaging
Published in: Cancer Imaging 1/2024

Open Access 01-12-2024 | Thymoma | Research article

Histogram analysis based on unenhanced CT for identifying thymoma and lymphoma among prevascular mediastinal incidentalomas

Authors: Ming Liu, Yang Zhang, Li-Heng Liu

Published in: Cancer Imaging | Issue 1/2024

Login to get access

Abstract

Objective

To determine whether histogram analysis based on unenhanced CT can play a role in the differential diagnosis of thymoma and lymphoma from thymic hyperplasia and cyst (mean CT attenuation > 10 HU).

Materials and methods

This retrospective study included consecutive asymptomatic participants who have prevascular mediastinal lesions incidentally detected by unenhanced CT between December 2013 and August 2020, and with definitive diagnosis by pathology or additional radiologic work-ups. A total of thirteen histogram parameters on enhanced CT were calculated for each lesion, then were compared between tumor (thymoma + lymphoma) and non-tumor (hyperplasia + cyst). Receiver operating characteristic analysis was conducted to investigate the performance of histogram parameter for identifying tumor.

Results

The study population included 192 patients (106 men and 86 women) with a mean age of 50.5 years at the time of CT examination. Of them, 94 patients have tumor (87 thymomas and 7 lymphoma) and 98 have non-tumor (48 thymic hyperplasia and 50 cysts). Nine of the thirteen histogram parameters revealed significant difference between the two groups, including median, minimum, range, 10th percentile, 90th percentile, kurtosis, skewness, uniformity and entropy. No significant difference was observed in the mean CT attenuation between groups. Higher median was found to be independent predictors for distinguishing tumor from non-tumor, and can achieve an area under the curve (AUC) of 0.785 (95% confidence interval [95% IC], 0.720–0.841).

Conclusions

Histogram analysis based on unenhanced CT may be able to provide some help in the differential diagnosis of incidental lesions in prevascular mediastinal.

Grand support

This study was sponsored by Natural Science Foundation of Shanghai (No. 21ZR1459700).
Literature
1.
Yoon SH, Choi SH, Kang CH, Goo JM. Incidental anterior mediastinal nodular lesions on chest CT in asymptomatic subjects. J Thorac Oncol. 2018;13:359–66.CrossRefPubMed
2.
Roden AC, Szolkowska M. Common and rare carcinomas of the thymus. Virchows Arch. 2021;478:111–28.CrossRefPubMed
3.
Scarpetta-Gonzalez DF, Morales EI, Sua LF, Velasquez M, Sangiovanni S, Fernandez-Trujillo L. Primary thymus tumors: retrospective case analysis at a reference center in Latin America, 2011–2019. BMC Cancer. 2021;21:279.CrossRefPubMedPubMedCentral
4.
Carter BW, Marom EM, Detterbeck FC. Approaching the patient with an anterior mediastinal mass: a guide for clinicians. J Thorac Oncol. 2014;9:102–9.CrossRef
5.
Ackman JB, Chintanapakdee W, Mendoza DP, Price MC, Lanuti M, Shepard JO. Longitudinal CT and MRI characteristics of Unilocular Thymic cysts. Radiology. 2021;301:443–54.CrossRefPubMed
6.
Henschke CI, Lee IJ, Wu N, et al. CT screening for Lung cancer: prevalence and incidence of mediastinal masses. Radiology. 2006;239:586–90.CrossRefPubMed
7.
Kent MS, Wang T, Gangadharan SP, Whyte RI. What is the prevalence of a nontherapeutic thymectomy? Ann Thorac Surg. 2014;97:276–82. discussion 282.CrossRefPubMed
8.
Ackman JB, Verzosa S, Kovach AE, et al. High rate of unnecessary thymectomy and its cause. Can computed tomography distinguish thymoma, Lymphoma, thymic hyperplasia, and thymic cysts? Eur J Radiol. 2015;84:524–33.CrossRefPubMed
9.
Morikawa K, Igarashi T, Shiraishi M, et al. Quantitative Histogram analysis of T2-Weighted and diffusion-weighted magnetic resonance images for prediction of malignant thymic epithelial tumors. J Comput Assist Tomogr. 2021;45:795–801.CrossRefPubMed
10.
Kim K, Jeong JH, Kim SJ. Diagnostic test accuracy of 18F-FDG PET or PET/CT for characterization of histologic type of thymic epithelial Tumor: a Meta-analysis. Clin Nucl Med. 2022;47:36–42.CrossRefPubMed
11.
Wieclawek W. Information granules in image histogram analysis. Comput Med Imaging Graph. 2018;65:129–41.CrossRefPubMed
12.
Rajamohan N, Goyal A, Kandasamy D, et al. CT texture analysis in evaluation of thymic tumors and thymic hyperplasia: correlation with the international thymic malignancy interest group (ITMIG) stage and WHO grade. Br J Radiol. 2021;94:20210583.CrossRefPubMedPubMedCentral
13.
Nagayama Y, Inoue T, Oda S, et al. Unenhanced dual-layer spectral-detector CT for characterizing indeterminate adrenal lesions. Radiology. 2021;301:369–78.CrossRefPubMed
Metadata
Title
Histogram analysis based on unenhanced CT for identifying thymoma and lymphoma among prevascular mediastinal incidentalomas
Authors
Ming Liu
Yang Zhang
Li-Heng Liu
Publication date
01-12-2024
Publisher
BioMed Central
Published in
Cancer Imaging / Issue 1/2024
Electronic ISSN: 1470-7330
DOI
https://doi.org/10.1186/s40644-023-00617-z

Other articles of this Issue 1/2024

Cancer Imaging 1/2024 Go to the issue

Research article

A clinical-radiomics nomogram based on dual-layer spectral detector CT to predict cancer stage in pancreatic ductal adenocarcinoma

Research

Relationship of FDG PET/CT imaging features with tumor immune microenvironment and prognosis in colorectal cancer: a retrospective study

Research article

Automated segmentation of lesions and organs at risk on [68Ga]Ga-PSMA-11 PET/CT images using self-supervised learning with Swin UNETR

Research article

Comparison of different classification systems for pulmonary nodules: a multicenter retrospective study in China

Research article

Development and validation of a clinic-radiological model to predict tumor spread through air spaces in stage I lung adenocarcinoma

Research article

HCA-DAN: hierarchical class-aware domain adaptive network for gastric tumor segmentation in 3D CT images
Webinar | 19-02-2024 | 17:30 (CET)

Keynote webinar | Spotlight on antibody–drug conjugates in cancer

Watch now

Antibody–drug conjugates (ADCs) are novel agents that have shown promise across multiple tumor types. Explore the current landscape of ADCs in breast and lung cancer with our experts, and gain insights into the mechanism of action, key clinical trials data, existing challenges, and future directions.

Dr. Véronique Diéras
Prof. Fabrice Barlesi
Developed by: Springer Medicine
Image Credits