Thymus imaging in myasthenia gravis: The relevance in clinical practice

Challenges in Diagnosing and Treating Myasthenia Gravis in Infants and Children with Presentation of Cases

Myasthenia gravis (MG) is a rare condition that impairs function at the neuromuscular junction of skeletal muscles, seen less commonly in children. Causes include autoimmune MG, congenital myasthenic syndromes, and transient neonatal myasthenia gravis. Symptoms of weakness, hypotonia, and fatigability can be reasonably explained by more common causes, thus children with MG disorders commonly experience delays in treatment with severe consequences. This leads to the progression of disease and serious complications including myasthenic crises and exacerbations. We describe 5 cases of MG, which illustrate clinical and genetic challenges in establishing diagnosis and subsequent consequences of delayed diagnosis.

Thymic Lesions in Myasthenia Gravis: A Clinicopathological Study from India

Background and Objectives: Thymic pathology is common in Myasthenia Gravis(MG) and plays a crucial role in its pathogenesis and clinical outcome. This study aims to discuss the clinicohistopathological spectrum of thymic lesions in MG. Methods: In this retrospective study, MG patients who underwent thymectomy from 2011 to 2020 were included. Clinical, radiological, serological, and histopathological details are described. Results: Of 83 patients(F = 45; M = 38), 7(8%) had ocular myasthenia, and the remaining 76(92%) had the generalized form. At onset, the median age was 36 years(M = 44; F = 31). AChR antibody was positive in 71/79 patients. RNST showed decrement response in 68/78 patients. The histopathological study demonstrated thymoma in 44(53%), thymic hyperplasias [32(38%)], involuted thymus [5(6%)], thymic cyst (1) and thymic lipoma (1). WHO grading of thymoma: B2- 48%, AB-18%, B-18%, B3-14%, A-2.3% . In these, capsular infiltration was noted in 11/44, 9 had focal and 2 had diffuse infiltration. Active germinal centers were present in 20/32 patients with thymic hyperplasia and 4/44 with thymoma. Thymomas were predominant in males and thymic hyperplasia in females. The age of onset and antibody positivity rate was higher in thymoma patients. Conclusion: In our cohort, there is a female preponderance. Thymoma was the commonest pathology followed by hyperplasia. We observed earlier onset of myasthenia in females. AChR antibody positivity rate was more frequent in thymomas. This study indicates that clinico-radiological evaluation adequately supported by serology and histopathology can effectively recognize the type of thymic pathology that can guide these patients’ treatment planning, management, prognosis and follow-up.

Acute Angle of Multilobulated Contours Improves the Risk Classification of Thymomas

Background: Computed tomography plays an important role in the identification and characterization of thymomas. It has been mainly used during preoperative evaluation for clinical staging. However, the reliable prediction of histological risk types of thymomas based on CT imaging features requires further study. In this study, we developed and validated a nomogram based on CT imaging and included new indices for individualized preoperative prediction of the risk classification of thymomas.

Methods: We conducted a retrospective, multicenter study that included 229 patients from two Chinese medical centers. All the patients underwent cross-sectional CT imaging within 2 weeks before surgery. The results of pathological assessments were retrieved from existing reports of the excised lesions. The tumor perimeter that contacted the lung (TPCL) was evaluated and a new quantitative indicator, the acute angle (AA) formed by adjacent lobulations, was measured. Two predictive models of risk classification were created using the least absolute shrinkage and selection operator (LASSO) method in a training cohort for features selection. The model with a smaller Akaike information criterion was then used to create an individualized imaging nomogram, which we evaluated regarding its prediction ability and clinical utility.

Results: A new CT imaging-based model incorporating AA was developed and validated, which had improved predictive performance during risk classification of thymomas when compared with a model using traditional imaging predictors. The new imaging nomogram with AA demonstrated its clinical utility by decision curve analysis.

Conclusions: Acute angle can improve the performance of a CT-based predictive model during the preoperative risk classification of thymomas and should be considered a new imaging marker for the evaluation and treatment of patients with thymomas. On the contrary, TPCL is not useful as a predictor for the risk classification of thymomas in this study.

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

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.

Correlation Between Thymus Radiology and Myasthenia Gravis in Clinical Practice

Background: The ability to distinguish between a normal thymus, thymic hyperplasia, and thymoma should aid in clinical management and decision making for patients with myasthenia gravis (MG). We sought to determine the accuracy of routine radiological examinations in predicting thymic pathology.

Methods: We retrospectively analyzed the records of patients with MG who had undergone thymectomy from the Second Affiliated Hospital of Zhengzhou University. Each patient received at least one initial radiological diagnosis and one histological diagnosis, and the patients were classified into the all-patient, CT, contrast CT, and MRI groups. The sensitivity, accuracy and specificity of each group were calculated for different histological types.

Results: This study included 114 patients. All sensitivity, specificity and accuracy values except for sensitivity to hyperplasia in each group for different histological types were satisfactory. MRI had higher sensitivity (68.4, 95% CI: 43.5–87.4%) to histological hyperplasia than did CT (14.3, 95% CI: 0.4–57.9%) and contrast CT (26.7, 95% CI: 7.8–55.1%). Contrast CT had higher specificity (97.9, 95% CI: 88.9–99.95%) for histological hyperplasia than did MRI (88.5, 95% CI: 69.9–97.6%).

Discussion: For patients with MG, CT, contrast CT, and MRI examinations can effectively identify thymoma. Additionally, compared with CT or contrast CT, MRI may have a stronger ability to distinguish thymoma and detect hyperplasia.