Relationship Between Computed Tomography Imaging Features and Clinical Characteristics, Masaoka-Koga Stages, and World Health Organization Histological Classifications of Thymoma

Abstract

Objectives: Computed tomography (CT) is an important technique for evaluating the condition and prognosis of patients with thymomas, and it provides guidance regarding treatment strategies. However, the correlation between CT imaging features, described using standard report terms, and clinical characteristics, Masaoka-Koga stages, and World Health Organization (WHO) classifications of patients with thymomas has not been described in detail nor has risk factor analysis been conducted. Methods: Overall, 159 patients with thymomas who underwent preoperative contrast-enhanced CT between September 2011 and December 2018 were retrospectively reviewed. We assessed the clinical information, CT imaging features, and pathological findings for each patient. A total of 89 patients were specially used to evaluate postoperative recurrence or metastasis between September 2011 and December 2015 to obtain an appropriate observation period. The relationship between CT imaging features and clinical characteristics, Masaoka-Koga stage, and WHO histological classification were analyzed, and related risk factors based on CT imaging features were identified. Results: CT imaging features did not significantly differ based on sex or age. Some imaging features demonstrated significant differences between the groups with and without related clinical characteristics. Contour (odds ratio [OR] = 3.711, P = 0.005), abutment ≥50% (OR = 4.277, P = 0.02), and adjacent lung abnormalities (OR = 3.916 P = 0.031) were independent risk factors for relapse or metastasis. Among all imaging features, there were significant differences between stage I/II and III/IV lesions in tumor size, calcification, infiltration of surrounding fat, vascular invasion, pleural nodules, elevated hemidiaphragm, and pulmonary nodules. Tumor size (odds ratio = 1.261, P = 0.014), vascular invasion (OR = 2.526, P = 0.023), pleural nodules (OR = 2.22, P = 0.048), and pulmonary nodules (OR = 3.106, P = 0.006) were identified as independent risk factors. Tumor size, contour, internal density, infiltration of surrounding fat, and pleural effusion significantly differed between low- and high-risk thymomas. Tumor size (OR = 1.183, P = 0.048), contour (OR = 2.288, P = 0.003), internal density (OR = 2.192, P = 0.024), and infiltration of surrounding fat (OR = 2.811 P = 0.005) were independent risk factors. Conclusions: Some CT imaging features demonstrated significant correlations with clinical characteristics, Masaoka-Koga clinical stages, and WHO histological classifications in patients with thymomas. Familiarity with CT features identified as independent risk factors for these related clinical characteristics can facilitate preoperative evaluation and treatment management for the patients with thymoma.

Keywords: Masaoka–Koga stage; WHO histological classification; computed tomography; myasthenia gravis; thymoma.

Copyright © 2019 Han, Gao, Chen, Du, Duan, Yu, Guo, Zhang and Ma.

Figures

Figure 1

Tumor size and pleural effusion are associated with patient's symptoms. (A) Axial contrast-enhanced chest CT image obtained at the level of the aortic arch showed a small thymoma with a smooth contour (Masaoka–Koga stage I and WHO classification A), which was first found at the time of physical examination in a 49-year-old woman. (B) A 53-year-old man with chief complains of cough, chest pain symptoms. Axial contrast-enhanced chest CT image obtained at the level of below the aortic arch showed a larger thymoma with lobulated contour and infiltration of surrounding fat (arrows), accompanied with left pleural effusion (Masaoka–Koga stage III and WHO classification B2).

Figure 2

Masaoka–Koga stage II thymomas. (A) Axial contrast-enhanced chest CT image showed a thymoma with a clear contour (Masaoka–Koga stage IIa and WHO classification B1), which was first found at the time of physical examination in a 55-year-old woman. (B) A 50-year-old woman mainly complains of general fatigue and subsequently was confirmed myasthenia gravis. Axial contrast-enhanced chest CT image obtained at the level of the left pulmonary trunk showed a thymoma with a slight lobulated contour (Masaoka–Koga stage IIb and WHO classification AB).

Figure 3

A multi-lobulated heterogeneous thymoma with vascular invasion. Axial contrast-enhanced chest CT image obtained at the level of the aortic arch demonstrated a thymoma in a 54-year-old man complained of bosom frowsty and chest pain (Masaoka–Koga stage III and WHO classification B1). The lesion directly invaded the left brachiocephalic vein (A, white arrow). The tumor showed the heterogeneous attenuation distributions and multi-lobulated contour (A,B, arrow head), the aortic arch was pushed backward.

Figure 4

A heterogeneous thymoma accompanied with pleural nodule. (A) Axial contrast-enhanced chest CT image obtained at the level of the pulmonary trunk demonstrated a multi-lobulated thymoma with internal multiple calcification lesions (white arrow) in a 69-year-old man with myasthenia gravis (Masaoka–Koga stage IVa and WHO classification B3). (B) Showed the adjacent thickened pleura (red arrow head) and pleural nodule (white arrow head).

Figure 5

A thymoma with infiltration of surrounding fat and lymph node enlargement. Axial contrast-enhanced chest CT image obtained at the level of the pulmonary trunk demonstrated a thymoma in a 49-year-old man (Masaoka–Koga stage IVb and WHO classification B3). (A,B) Showed the thickened pleura (red arrow head), infiltration of surrounding fat (white arrows), and bulging margin (white arrow head). The lymph node enlargement appeared at the superior level of the lesion (A, red arrow) and at the level of left hilum (B, red arrow).

Figure 6

The schematic diagram of CT imaging features as risk factors for clinical characteristics, Masaoka–Koga stage, and WHO histological classification. The X-axis displayed the CT imaging features and Y-axis indicated the clinical characteristics, Masaoka–Koga stage, and WHO histological classification. The ratio of occurrence frequency of one imaging feature was quantitatively calculated in one subgroup and size of ratio value was represented by color bar (With and without relapse or metastasis were based on a total of 89 patients). The circle and oval circle showed the imaging features as risk factors for the related clinical characteristics, Masaoka–Koga stage, and WHO histological classification. The single star (*) indicated the significant difference (P < 0.05) and the double stars (**) indicated the significant difference (P < 0.01) by the binary logistic regression analysis.