Minimally invasive thoracoscopic resection of a micronodular thymoma with lymphoid stroma via a subxiphoid single-incision approach: A case report.

RATIONALE: This study aims to present a novel surgical approach for the resection of anterior mediastinal tumors, specifically focusing on micronodular thymoma with lymphoid stroma (MNT), a rare and distinct variant of thymoma. The single subxiphoid incision technique, although reported in limited cases, offers a minimally invasive option with potential benefits. We report the case of a 76-year-old male who underwent this innovative procedure and was diagnosed with MNT, providing insight into the management and outcomes of this rare pathology. PATIENT CONCERNS: The patient presented for the excision of an anterior mediastinal tumor, with the surgery facilitated by sternal hooks to improve visualization. The rarity of MNT and its unclear prognosis underscore the need for enhanced diagnostic accuracy and tailored treatment strategies. DIAGNOSES: Initially diagnosed preoperatively with a thymic cyst, the patient's final diagnosis was revised to MNT following surgery, highlighting the diagnostic challenges associated with this rare tumor. INTERVENTIONS: The tumor was successfully removed using minimally invasive thoracoscopic surgery through a subxiphoid single-incision, demonstrating the feasibility and potential advantages of this approach. OUTCOMES: The patient had a favorable postoperative course, with a swift recovery and no complications, and remained in good health without signs of relapse at the 9-month follow-up. LESSONS: This case underscores the importance of recognizing the unique pathological features of MNT and the need for a cautious diagnostic approach to differentiate it from other cystic lesions. Additionally, the successful use of single-port thoracoscopy under the xiphoid process for the removal of thymic tumors suggests its potential as an effective surgical method for these challenging cases.

Differentiating low-risk thymomas from high-risk thymomas: preoperative radiomics nomogram based on contrast enhanced CT to minimize unnecessary invasive thoracotomy.

BACKGROUND: This study was designed to develop a combined radiomics nomogram to preoperatively predict the risk categorization of thymomas based on contrast-enhanced computed tomography (CE-CT) images. MATERIALS: The clinical and CT data of 178 patients with thymoma (100 patients with low-risk thymomas and 78 patients with high-risk thymomas) collected in our hospital from March 2018 to July 2023 were retrospectively analyzed. The patients were randomly divided into a training set (n = 125) and a validation set (n = 53) in a 7:3 ratio. Qualitative radiological features were recorded, including (a) tumor diameter, (b) location, (c) shape, (d) capsule integrity, (e) calcification, (f) necrosis, (g) fatty infiltration, (h) lymphadenopathy, and (i) enhanced CT value. Radiomics features were extracted from each CE-CT volume of interest (VOI), and the least absolute shrinkage and selection operator (LASSO) algorithm was performed to select the optimal discriminative ones. A combined radiomics nomogram was further established based on the clinical factors and radiomics scores. The differentiating efficacy was determined using receiver operating characteristic (ROC) analysis. RESULTS: Only one clinical factor (incomplete capsule) and seven radiomics features were found to be independent predictors and were used to establish the radiomics nomogram. In differentiating low-risk thymomas (types A, AB, and B1) from high-risk ones (types B2 and B3), the nomogram demonstrated better diagnostic efficacy than any single model, with the respective area under the curve (AUC), accuracy, sensitivity, and specificity of 0.974, 0.921, 0.962 and 0.900 in the training cohort, 0.960, 0.892, 0923 and 0.897 in the validation cohort, respectively. The calibration curve showed good agreement between the prediction probability and actual clinical findings. CONCLUSIONS: The nomogram incorporating clinical factors and radiomics features provides additional value in differentiating the risk categorization of thymomas, which could potentially be useful in clinical practice for planning personalized treatment strategies.

Predicting the risk category of thymoma with machine learning-based computed tomography radiomics signatures and their between-imaging phase differences.

The aim of this study was to develop a medical imaging and comprehensive stacked learning-based method for predicting high- and low-risk thymoma. A total of 126 patients with thymomas and 5 patients with thymic carcinoma treated at our institution, including 65 low-risk patients and 66 high-risk patients, were retrospectively recruited. Among them, 78 patients composed the training cohort, while the remaining 53 patients formed the validation cohort. We extracted 1702 features each from the patients' arterial-, venous-, and plain-phase images. Pairwise subtraction of these features yielded 1702 arterial-venous, arterial-plain, and venous-plain difference features each. The Mann‒Whitney U test and least absolute shrinkage and selection operator (LASSO) and SelectKBest methods were employed to select the best features from the training set. Six models were built with a stacked learning algorithm. By applying stacked ensemble learning, three machine learning algorithms (XGBoost, multilayer perceptron (MLP), and random forest) were combined by XGBoost to produce the the six basic imaging models. Then, the XGBoost algorithm was applied to the six basic imaging models to construct a combined radiomic model. Finally, the radiomic model was combined with clinical information to create a nomogram that could easily be used in clinical practice to predict the thymoma risk category. The areas under the curve (AUCs) of the combined radiomic model in the training and validation cohorts were 0.999 (95% CI 0.988-1.000) and 0.967 (95% CI 0.916-1.000), respectively, while those of the nomogram were 0.999 (95% CI 0.996-1.000) and 0.983 (95% CI 0.990-1.000). This study describes the application of CT-based radiomics in thymoma patients and proposes a nomogram for predicting the risk category for this disease, which could be advantageous for clinical decision-making for affected patients.

[Intraspinal Metastasis of Thymic Carcinoma:Report of One Case].

Intraspinal metastasis from malignant carcinomas in other body parts is rarely reported.Intraspinal metastases are often epidural,with primary tumors mostly from the lung and prostate.The extramedullary subdural metastasis of thymic carcinoma is particularly rare and prone to misdiagnosis due to overlapping imaging features with primary intraspinal tumors.This article reports one case of intraspinal metastasis of thymic carcinoma,with the main diagnostic clues including a history of thymic carcinoma,fast growth rate,and irregular shape.

Ectopic pleural thymoma with T-cell lymphocytosis and bone metastasis: a case report.

BACKGROUND: The diagnostic complexities that arise in radiographic distinction between ectopic pleural thymoma and other thoracic neoplasms are substantial, with instances of co-occurring T-cell lymphocytosis and osseous metastasis being exceedingly rare. CASE PRESENTATION: A 51-year-old woman was admitted to our hospital with dyspnea and chest pain. Upon imaging examination, she was found to have diffuse and nodular pleural thickening on the left side, collapse of the left lung and a compression in the second thoracic vertebrae. All lesions showed significant 18F-FDG uptake on 18F-FDG PET/CT examination. Furthermore, she exhibited T-cell lymphocytosis in her peripheral blood, lymph nodes, and bone marrow. After ruling out malignant pleural mesothelioma (MPM), lung cancer with pleural metastasis, and T-cell lymphoma, the definitive diagnosis asserted was ectopic pleural thymoma with T-cell lymphocytosis and bone metastasis. CONCLUSION: Physicians need to expand their knowledge of the imaging features of ectopic pleural thymoma. Cases with T-cell lymphocytosis may exhibit increased aggressiveness and prone to bone metastasis.

Ectopic cervical thymoma: a rare entity in the anterior neck.

Thymoma is a rare malignancy with usual location in the antero-superior mediastinum. Ectopic cervical thymoma (ECT) is an extremely rare tumor that originates from ectopic tissue, and is caused by the aberrant migration of the embryonic thymus. Our patient was a 56-year-old man who had a nodular lesion in the neck for several years. Computed tomography and Enhanced magnetic resonance imaging were performed. He underwent surgery, and a histological examination resulted in a diagnosis of type AB thymoma.

Intrathyroidal thymic carcinoma.

A young woman in her early 30s presented with a right thyroid mass and progressive hoarseness due to a right vocal cord palsy. The preoperative fine-needle aspiration cytology was classified as Bethesda V and she underwent a total thyroidectomy and neck dissection. Intraoperatively, the thyroid mass was adherent to the oesophagus, trachea and encasing the right recurrent laryngeal nerve which was sacrificed. Final histopathology diagnosed a rare subtype of thyroid cancer known as intrathyroidal thymic carcinoma (ITC). She was then sent for adjuvant radiotherapy after a multidisciplinary tumour board discussion. This case report highlights the difficulty in preoperative diagnosis of ITC and the importance of immunohistochemical staining in clinching the diagnosis. In view of its rarity, there have been no published consensus on the treatment of ITC, hence we would like to share some learning points through a comprehensive literature review.

Tumor habitat and peritumoral region evolution-based imaging features to assess risk categorization of thymomas.

AIM: To develop an aggregate model that integrated clinical data, habitat characteristics, and intratumoral and peritumoral features to assess the risk categorization of thymomas. MATERIALS AND METHODS: We retrospectively analyzed 140 thymoma patients (70 low-risk and 70 high-risk), including pathological data. The patients were randomly divided into training cohort (n = 114) and test cohort (n = 26). The k-means clustering was utilized to partition the primary tumor into habitats based on intratumoral radiomic features, 6 distinct habitats were identified. By expanding the region of interest (ROI) mask, 2 peritumoral regions were obtained. Finally, 7 clinical characteristics, 3 habitat values, 20 radiomic features were utilized to develop an aggregated model, to predict the risk of thymoma. Shapley additive explanations (SHAP) interpretation was used for features importance ranking. The accuracy and area under curve (AUC) were used to analyze the performance of the models. RESULTS: The aggregated model, which utilized the XGBoost classifier, demonstrated the best performance with an AUC of 0.811 and an accuracy of 0.769. In comparison, the radiomic model produced an AUC of 0.654 and an accuracy of 0.692. Additionally, the Intratumoral + peritumoral model exhibited an AUC of 0.728 and an accuracy of 0.769. CONCLUSION: Our study establishes a novel tool to predict the risk of thymoma with a good performance. If prospectively validated, the model may refine thymoma patient selection for risk-adaptative therapy and improve prognosis.

Late coronary artery injury following chemoradiotherapy for thymic carcinoma: a case report.

INTRODUCTION: Surgery remains the primary treatment modality for thymic carcinoma, with adjuvant radiotherapy being recommended to effectively mitigate local recurrence and metastasis rates subsequent to incomplete or complete resection. Chemoradiotherapy has the potential to induce coronary artery occlusion, thereby potentially impacting patients' long-term survival rates. The existing literature currently lacks comprehensive research on the lesion characteristics of coronary artery injury resulting from chemoradiotherapy. CASE PRESENTATION: The male patient, aged 55, was admitted to the hospital due to recurrent chest tightness and pain persisting for one week. Notably, the patient had previously undergone curative resection surgery for thymic carcinoma seven years ago. After the surgical procedure, the patient underwent a course of adjuvant chemotherapy comprising docetaxel and platinum. 11 months later, imaging examination diagnosed tumor recurrence, and concurrent chemoradiotherapy was administered at a total dose of 62 Gy/31F for planning gross target volume (PGTV) and 54 Gy/31F for planning target volume (PTV) with 2 cycles of paclitaxel and cisplatin. Re-admission of the patient occurred after a 7-year interval subsequent to the completion of concurrent chemoradiotherapy, leading to a subsequent diagnosis of acute non-ST segment elevation myocardial infarction. Following administration of antiplatelet, anticoagulant, and anti-myocardial ischemia therapy, coronary angiography revealed the presence of a bifurcation lesion at the distal end of the left main trunk. Intravascular ultrasound (IVUS) examination demonstrated significant negative remodeling of both the main trunk and its branches at the bifurcation site, characterized by minimal atherosclerotic plaque components. CONCLUSIONS: Chemoradiotherapy may induce damage to endothelial cells, resulting in an inflammatory response. Negative remodeling of blood vessels is likely to occur, primarily characterized by vasoconstriction but with less atherosclerotic plaque burden. Routine stent implantation in negatively remodeled areas may lead to vascular rupture, necessitating intravascular imaging examination.

Deep learning for risk stratification of thymoma pathological subtypes based on preoperative CT images.

OBJECTIVES: This study aims to develop an innovative, deep model for thymoma risk stratification using preoperative CT images. Current algorithms predominantly focus on radiomic features or 2D deep features and require manual tumor segmentation by radiologists, limiting their practical applicability. METHODS: The deep model was trained and tested on a dataset comprising CT images from 147 patients (82 female; mean age, 54 years ± 10) who underwent surgical resection and received subsequent pathological confirmation. The eligible participants were divided into a training cohort (117 patients) and a testing cohort (30 patients) based on the CT scan time. The model consists of two stages: 3D tumor segmentation and risk stratification. The radiomic model and deep model (2D) were constructed for comparative analysis. Model performance was evaluated through dice coefficient, area under the curve (AUC), and accuracy. RESULTS: In both the training and testing cohorts, the deep model demonstrated better performance in differentiating thymoma risk, boasting AUCs of 0.998 and 0.893 respectively. This was compared to the radiomic model (AUCs of 0.773 and 0.769) and deep model (2D) (AUCs of 0.981 and 0.760). Notably, the deep model was capable of simultaneously identifying lesions, segmenting the region of interest (ROI), and differentiating the risk of thymoma on arterial phase CT images. Its diagnostic prowess outperformed that of the baseline model. CONCLUSIONS: The deep model has the potential to serve as an innovative decision-making tool, assisting on clinical prognosis evaluation and the discernment of suitable treatments for different thymoma pathological subtypes. KEY POINTS: • This study incorporated both tumor segmentation and risk stratification. • The deep model, using clinical and 3D deep features, effectively predicted thymoma risk. • The deep model improved AUCs by 16.1pt and 17.5pt compared to radiomic model and deep model (2D) respectively.

[Thymoma with Partial Anomalous Pulmonary Venous Drainage from the Left Upper Lobe:Report of a Case].

A 73-year-old woman presented with left anterior chest pain and back pain. Computed tomography (CT) scan showed an anterior mediastinal tumor. It also showed partial anomalous pulmonary venous drainage (left superior pulmonary vein draining into the left brachiocephalic vein), and the tumor was located near the left brachiocephalic vein. The operation was performed through a median sternotomy to resect the thymus and tumor with partial resection of the left upper lobe due to the tumor's adhesion to the left upper lobe. One of the vascular anomalies encountered in adult thoracic surgery is partial anomalous pulmonary venous drainage. It is important to recognize the presence of such an anomaly on imaging and to anticipate the surgical procedure with a preoperative surgical technique.

The role of calcification in predicting invasion of thymoma to adjacent organs.

PURPOSE: Thoracoscopic procedures such as video-assisted thoracoscopic surgery (VATS) and robot-assisted thoracoscopic surgery (RATS) have gained popularity for the treatment of thymoma. Accurate preoperative assessments of tumor invasion are crucial to identifying the appropriate surgical approach. Although imaging techniques have been used to predict invasion, a quantifiable method is still needed in clinical practice. METHODS: The ubjects of this retrospective study were 226 patients with thymoma who underwent surgery at our hospital. Clinicopathological data, tumor staging, and recurrence rates were analyzed. Calcification identified through computed tomography (CT) defined the "calcified group" as having a long diameter of ≥ 5 mm. Statistical analyses were performed to assess relationships and survival outcomes. RESULTS: The calcified group had higher Masaoka and World Health Organization classification than the noncalcified group, with significantly higher organ invasion rates. The calcified group also had remarkably higher recurrence rates. CONCLUSION: Thymoma calcification appears to correlate with increased invasiveness and recurrence rates, suggesting its potential as a predictor of tumor stage and prognosis. Despite its retrospective nature and inherent limitations, this study highlights the potential clinical significance of calcification in the surgical planning and prognostication of patients with thymoma.

Making an accurate diagnosis of anterior mediastinal lesions: a proposal for a new diagnostic algorithm from the BTOG Thymic Malignancies Special Interest Group.

Due to the rising demand in cross-sectional thoracic imaging, anterior mediastinal lesions are being identified with increasing frequency. Following iterative and multidisciplinary discussions, the BTOG Thymic Malignancies Special Interest Group have developed an algorithm to standardise the diagnostic approach for these relatively uncommon but important conditions which span from benign (thymic remnant, thymic hyperplasia and thymic cysts) to suspected localised thymomas to suspected more aggressive malignancy (thymic carcinoma, lymphoma and germ cell tumours). For each condition, we provide a brief description, an overview of the key radiological findings and a description of the proposed algorithm including the rationale behind the recommendations. We also highlight the role of magnetic resonance (MR) imaging for the characterisation of anterior mediastinal masses in specific indications when the necessary local resources and expertise exist. In addition, we hope this provides the rationale for service development in MR of the anterior mediastinum where current resource and expertise requires development. Through this standardised pathway, we hope to drive improvements in patient care by rationalising surveillance schedules, avoiding unnecessary resections of benign entities with their associated morbidity and optimising the diagnostic work-up prior to the appropriate treatment of anterior mediastinal malignancies.

The Role of [18F]FDG PET/CT in the Characterization of Thymic Epithelial Tumors at Initial Stage.

Purpose: The aim of this study was to evaluate the potential role of [18F]FDG positron emission tomography/computed tomography (PET/CT) in the characterization of thymic epithelial tumors (TETs). Materials and Methods: A total of 73 patients who underwent preoperative [18F]FDG PET/CT were included in this study. Visual total score (VTS), maximum standard uptake values (SUVmax), metabolic tumor volume (MTV), total lesion glycolysis (TLG), and heterogeneity index (HI) parameters were analyzed to investigate the prediction of histopathologic grade and advanced stage. Results: The cohort included 26 patients with low-grade thymoma (LGT), 36 patients with high-grade thymoma (HGT), and 11 patients with thymic carcinoma (TC). Ninety-one percent of TC had VTS >2, whereas 31% of LGT and 75% of HGT had VTS >2. SUVmax, MTV, and TLG were statistically significantly higher in the TC group than in both thymoma and HGT. Using the cutoff value of 7.25 for SUVmax, TC was differentiated from thymomas with 91% sensitivity and 74% specificity. TC had significantly lower HI values than thymomas. HI parameters showed good diagnostic ability to differentiate TC from thymoma and TC from HGT. SUVmax, MTV, and TLG were significantly higher in advanced-stage disease than in early-stage disease. Conclusions: Visual and quantitative parameters can reliably predict both advanced disease and the grade of primary tumor in TETs. Therefore, as a promising metabolic imaging method, [18F]FDG PET/CT makes important contributions to preoperative evaluation in routine clinical practice.

Resection and a rare type of reconstruction of the superior vena cava with the left brachiocephalic vein.

Resection and reconstruction of the superior vena cava (SVC) are required in a selected group of patients with anterior mediastinal tumors and lung neoplasms. We present the case of a 63-year-old woman who underwent invasive type B2 thymoma resection and a rare type of reconstruction of the superior vena cava using a patch of the left brachiocephalic vein (LBV). The various types of reconstruction of the superior vena cava are discussed.

Practical methods to differentiate thymic malignancies by positron-emission tomography and tumor markers.

PURPOSE: An accurate diagnosis of thymic malignancies is important, but challenging due to the broad range of differential diagnoses. This study aims to evaluate the efficacy of PET/CT and tumor markers for diagnosing thymic malignancies. METHODS: Patients admitted to our department between January 2012 and December 2021 with primary anterior mediastinal tumors were retrospectively evaluated. We evaluated the relationship between the maximum standardized uptake value (SUVmax), tumor markers, and pathological diagnosis in four groups: thymic carcinoma, thymoma, lymphoma, and others. RESULTS: In total, 139 patients were included in this study. The SUVmax was significantly higher in lymphoma, thymic carcinoma, and thymoma, in that order. The cytokeratin 19 fragment (CYFRA 21-1) was significantly higher in thymic carcinoma than in the other groups. An ROC curve analysis indicated that the optimal cut-off values of SUVmax for thymic carcinoma plus lymphoma and CYFRA 21-1 for thymic carcinoma were 7.97 (AUC = 0.934) and 2.95 (AUC = 0.768), respectively. Using a combination of cut-off values (SUVmax = 8, CYFRA 21-1 = 3), the accuracy rate for diagnosing thymic carcinoma was 91.4%. CONCLUSIONS: The SUVmax and CYFRA 21-1 levels are significant indicators for the diagnosis of thymic carcinoma. Combining these indicators resulted in a more accurate diagnosis of thymic malignancies, which could facilitate the decision-making process for determining the optimal treatment strategies.

Advanced thymic carcinoma with a hepatic metastasis treated with chemotherapy and staged resection.

Thymic carcinoma is rare, with resulting treatment of patients with extrathoracic metastasis being on a case-by-case basis. We describe the management of a woman in her 70s with an incidentally discovered cystic hepatic lesion with confirmation of a solitary extrathoracic metastasis from a synchronous primary thymic carcinoma. Following chemotherapy and staged resection of the metastasis and the primary tumour, the patient remained free of disease on radiological surveillance 6 months postoperatively.