Thymic amyloidoma mimicking sclerosing thymoma in a triple vessel disease patient: An incidental finding

Dhingra, Harshi; Singh, Amarjit; Baliyan, Asif; Bansal, Vinisha

doi:10.4103/ijpm.ijpm_432_19

Cited by 2 publications

(3 citation statements)

References 11 publications

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“…So far, computed tomography (CT) examination is still the most widely used method during the diagnosis of thymoma. In clinical practice, CT examination can be adopted to predict the histological classification of thymoma [ 9 , 10 ].…”

Section: Introductionmentioning

confidence: 99%

[Retracted] Histological Classification and Invasion Prediction of Thymoma by Machine Learning‐Based Computed Tomography Imaging

Wang

Zhang

et al. 2022

Contrast Media & Molecular Imaging

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Purpose. The values of machine learning-based computed tomography (CT) imaging in histological classification and invasion prediction of thymoma were investigated. Methods. 181 patients diagnosed with thymoma by surgery or biopsy in Shantou Central Hospital between February 2017 and March 2022 were selected. According to the concept of simplified histological classification and the latest histological classification by the WHO, thymoma was divided into two groups, including low-risk (types A, AB, B1, and metaplastic type) and high-risk groups (types B2 and B3). CT images were reconstructed by filtering back projection (FBP) algorithm. CT image features were collected for statistical analysis. Results. The main symptoms of patients diagnosed with thymoma included respiratory tract infection, chest distress and shortness of breath, and chest pain. 35.91% of them suffered from complicated myasthenia gravis. Tumor size and position in low-risk and high-risk groups showed no statistical significance ( P > 0.05 ). Tumor morphology and boundary between the two groups suggested statistical difference ( P < 0.05 ). Whether tumor invaded adjacent tissues was apparently correlated with simplified histological classification ( P < 0.01 ). The sensitivity and specificity of CT images for the invasion of mediastinal pleura or pericardium were around 90% and negative predictive values both reached above 95%. Those of the CT images for lung invasion were over 80%. The negative and positive predictive values were 93.54% and 63.82%, respectively. Those of the CT images for blood vessel invasion were 67.32% and 97.93%. The negative and positive predictive values were 98.21% and 83%, respectively. Conclusion. The machine learning-based CT image had significant values in the prediction of different histological classification and even invasion level.

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Section: Introductionmentioning

confidence: 99%

[Retracted] Histological Classification and Invasion Prediction of Thymoma by Machine Learning‐Based Computed Tomography Imaging

Wang

Zhang

et al. 2022

Contrast Media & Molecular Imaging

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“…[1,8] The tumors that existed for a long time and involved stimulating fibrogenic proliferation and spontaneous regression caused by tumor degenerative change possibly involves the formation of ST. Moran et al suggested that extensive fibrosis may reflect a change that could be considered as an unusual, extensive fibrosing variant of type A thymoma. [2,10] Furthermore, Ito et al suggested that thymoma with hemorrhage and necrosis could transform into a sclerotic lesion as the necrosis component was absorbed over time to cause fibrosis. [11] As illustrated in the present case, the patient underwent >30 times the sessions of preoperative chemotherapy and radiotherapy performed usually, which may cause partial necrosis or hemorrhage, and secondary extensive sclerotic lesions with hyalinization and calcification.…”

Section: Discussionmentioning

confidence: 99%

“…Histologically, type AB thymoma is mainly composed of diffuse lymphoid cells and clustered spindle cells (CK-positive), whereas the sclerosing type is mainly composed of abundant collagen fibers and a very small number of lymphocytes [1,8] . The tumors that existed for a long time and involved stimulating fibrogenic proliferation and spontaneous regression caused by tumor degenerative change possibly involves the formation of ST. Moran et al suggested that extensive fibrosis may reflect a change that could be considered as an unusual, extensive fibrosing variant of type A thymoma [2,10] . Furthermore, Ito et al suggested that thymoma with hemorrhage and necrosis could transform into a sclerotic lesion as the necrosis component was absorbed over time to cause fibrosis [11] .…”

Section: Discussionmentioning

confidence: 99%

An unusual huge thymoma composed of sclerosing thymoma and type AB thymoma

Jiang

Zhang

Guo³

et al. 2021

Medicine

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Rationale:Sclerosing thymoma (ST) is quite a rare disease, as denoted in previous literature. Less than 20 cases of ST have been reported to date. However, the combined thymoma, composed of both type AB thymoma and ST, has never been described before.Patient concerns:The subject, a 49-year-old woman, came in with the chief complaint of cough for 10 days.Diagnoses:Both the contrast-enhanced computed tomography scan and the ultrasonography showed a huge mass located in the right thoracic cavity with inhomogeneous contrast accompanied by the invasion of the pericardium and pleura. Subsequently, computed tomography-guided core-needle biopsy revealed type B2 thymoma, and type AB thymoma could not be excluded. Based on postsurgical histopathology and immunohistochemical finding, this tumor was given the final diagnosis of ST and type AB thymoma.Interventions:After 6 months of adjuvant chemotherapy and local radiotherapy, total thymectomy was performed.Outcomes:The patient has been duly followed up for 1 year without any tumor recurrence.Lessons:ST is a very rare mediastinal neoplasm. Moreover, ST in combination with AB thymoma and affecting a large area, is unprecedented. Whether radiotherapy and chemotherapy have a certain effect on ST requires further investigation. In addition, due to the unclear recurrence rate of ST, long-term follow-up evaluation seems necessary.

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Thymic amyloidoma mimicking sclerosing thymoma in a triple vessel disease patient: An incidental finding

Cited by 2 publications

References 11 publications

[Retracted] Histological Classification and Invasion Prediction of Thymoma by Machine Learning‐Based Computed Tomography Imaging

[Retracted] Histological Classification and Invasion Prediction of Thymoma by Machine Learning‐Based Computed Tomography Imaging

An unusual huge thymoma composed of sclerosing thymoma and type AB thymoma

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