Introduction Pericardial cysts (PCs) are infrequent, non-malignant, and congenital abnormalities. The identification and treatment of PCs remain a significant challenge, with limited research on surgical management. Methods We performed a retrospective study of patients with PCs who underwent surgical intervention at the First Affiliated Hospital of Xinjiang Medical University from February 2002 to December 2022. Results A total of 55 patients underwent surgery due to PCs during the study period. Thirty-one were females and 24 were males. The average age of the patients was 44.7 ± 12.9 (six to 63 years old). PCs were located in the right hemithorax in 50 (90.9%) patients and left hemithorax in five (9.1%) patients. Approach methods were video-assisted thoracoscopic surgery (VATS) in 43 (78.2%) cases; thoracotomy in 11 (20%) cases, and median sternotomy in one (1.8%) cases. The average postoperative hospitalization period was 5.6 days (two to 14 days). Three patients developed postoperative complications (two pleural effusion, one pneumonia), whereas no mortality was observed in any patient due to the operation. Forty-one patients (74.5%) were followed up for three months to eight years postoperatively, during which no recurrent cysts were detected. Conclusion In this single-center retrospective study, we demonstrated that pericardial cyst cure is an appropriate operation according to cyst characteristics. VATS has been shown to be highly effective and safe in patients with PCs, offering the advantage of reducing postoperative morbidity efficiently.

This study aims to evaluate the feasibility and effectiveness of deep transfer learning (DTL) and clinical-radiomics in differentiating thymoma from thymic cysts.
Clinical and imaging data of 196 patients pathologically diagnosed with thymoma and thymic cysts were retrospectively collected from center 1. (training cohort: n = 137; internal validation cohort: n = 59). An independent external validation cohort comprised 68 thymoma and thymic cyst patients from center 2. Region of interest (ROI) delineation was performed on contrast-enhanced chest computed tomography (CT) images, and eight DTL models including Densenet 169, Mobilenet V2, Resnet 101, Resnet 18, Resnet 34, Resnet 50, Vgg 13, Vgg 16 were constructed. Radiomics features were extracted from the ROI on the CT images of thymoma and thymic cyst patients, and feature selection was performed using intra-observer correlation coefficient (ICC), Spearman correlation analysis, and least absolute shrinkage and selection operator (LASSO) algorithm. Univariate analysis and multivariable logistic regression (LR) were used to select clinical-radiological features. Six machine learning classifiers, including LR, support vector machine (SVM), k-nearest neighbors (KNN), Light Gradient Boosting Machine (LightGBM), Adaptive Boosting (AdaBoost), and Multilayer Perceptron (MLP), were used to construct Radiomics and Clinico-radiologic models. The selected features from the Radiomics and Clinico-radiologic models were fused to build a Combined model. Receiver operating characteristic curve (ROC), calibration curve, and decision curve analysis (DCA) were used to evaluate the discrimination, calibration, and clinical utility of the models, respectively. The Delong test was used to compare the AUC between different models. K-means clustering was used to subdivide the lesions of thymomas or thymic cysts into subregions, and traditional radiomics methods were used to extract features and compare the ability of Radiomics and DTL models to reflect intratumoral heterogeneity using correlation analysis.
The Densenet 169 based on DTL performed the best, with AUC of 0.933 (95% CI: 0.875-0.991) in the internal validation cohort and 0.962 (95% CI: 0.923-1.000) in the external validation cohort. The AdaBoost classifier achieved AUC of 0.965 (95% CI: 0.923-1.000) and 0.959 (95% CI: 0.919-1.000) in the internal and external validation cohorts, respectively, for the Radiomics model. The LightGBM classifier achieved AUC of 0.805 (95% CI: 0.690-0.920) and 0.839 (95% CI: 0.736-0.943) in the Clinico-radiologic model. The AUC of the Combined model in the internal and external validation cohorts was 0.933 (95% CI: 0.866-1.000) and 0.945 (95% CI: 0.897-0.994), respectively. The results of the Delong test showed that the Radiomics model, DTL model, and Combined model outperformed the Clinico-radiologic model in both internal and external validation cohorts (p-values were 0.002, 0.004, and 0.033 in the internal validation cohort, while in the external validation cohort, the p-values were 0.014, 0.006, and 0.015, respectively). But there was no statistical difference in performance among the three models (all p-values <0.05). Correlation analysis showed that radiomics performed better than DTL in quantifying intratumoral heterogeneity differences between thymoma and thymic cysts.
The developed DTL model and the Combined model based on radiomics and clinical-radiologic features achieved excellent diagnostic performance in differentiating thymic cysts from thymoma. They can serve as potential tools to assist clinical decision-making, particularly when endoscopic biopsy carries a high risk.

Benign cysts of the thoracic cavity represent a group of rare lesions, the spectrum of which is expanding. Most of these are congenital in nature, secondary to abnormal development during embryogenesis while a smaller subset represents acquired lesions. We retrospectively reviewed the clinicopathologic features of 136 patients with thoracic cysts that were treated in our institution over a span of 20 years. The patients were 85 female and 51 male patients with an average age of 51 years. Eighty-four of the patients were asymptomatic (62%), the remainder mainly presented with chest pain, shortness of breath, or cough. Surgical resection was performed in 123 patients while 12 patients were treated with aspiration only and 1 underwent core biopsy. The cyst size ranged from 0.5 to 14.8 cm (mean, 4.4 cm); histologically, the lesions included 50 thymic cysts (28 multilocular; 22 unilocular), 37 bronchogenic cysts, 23 pleuropericardial cysts, 12 unclassified cysts, 6 Müllerian cysts, 5 enteric cysts, and 3 parathyroid cysts. Clinical follow-up revealed that 97 patients were alive and well 4 months to 37 years after initial diagnosis; 25 patients were lost to follow-up and 14 patients died of unrelated causes. The current study is one of the largest studies on the subject with emphasis on clinicopathologic characteristics. This series has a higher incidence of thymic cysts compared with prior publications and covers a wider spectrum of different histologic types than previously reported.

OBJECTIVE: To compare the efficacy and safety of robotic-assisted thoracoscopic surgery (RATS) with video-assisted thoracoscopic surgery (VATS) in the treatment of mediastinal cysts.
METHODS: Retrospective analysis on clinical data of 70 cases of minimally invasive surgery for mediastinal cysts completed in the Department of Thoracic Surgery, Gansu Provincial People\'s Hospital from April 2014 to December 2022. There were 34 cases in the RATS group with a cyst diameter of (3.70 ± 1.16) cm and 36 cases in the VATS group with a cyst diameter of (4.07 ± 1.20) cm. All cysts were evaluated preoperatively using magnetic resonance imaging (MRI) or chest computed tomography (CT) localization. Surgery-related indices were compared among the two groups.
RESULTS: All patients in two groups successfully completed resection of mediastinal cysts without perioperative deaths. Compared with the VATS group, the RATS group possessed shorter operative time [(75.32 ± 17.80) min vs. (102.22 ± 19.80) min, P < 0.001], lesser intraoperative bleeding [10 (5.00, 26.00) ml vs. 17.50 (5.00, 50.50) ml, P = 0.009], shorter postoperative chest drainage time [2 (1.00, 6.00) ml vs. 3 (2.00, 6.50) ml, P = 0.006] and shorter postoperative hospital stay [3 (2.00, 6.50) d vs. 4 (3.00, 7.50) d, P = 0.001]. There was no statistically significant discrepancy in intermediate openings and complications in both groups (P > 0.05).
CONCLUSIONS: Compared with VATS, RATS is safety and effectivity in the treatment of mediastinal cysts and thus has advantages in operative time, intraoperative bleeding, postoperative chest drainage time and postoperative hospital stay.

Purpose: To evaluate the feasibility and usefulness of T1 and T2 mapping in characterization of mediastinal masses. Methods: From August 2019 through December 2021, 47 patients underwent 3.0-T chest MRI with T1 and post-contrast T1 mapping using modified look-locker inversion recovery sequences and T2 mapping using a T2-prepared single-shot shot steady-state free precession technique. Mean native T1, native T2, and post-contrast T1 values were measured by drawing the region of interest in the mediastinal masses, and enhancement index (EI) was calculated using these values. Results: All mapping images were acquired successfully, without significant artifact. There were 25 thymic epithelial tumors (TETs), 3 schwannomas, 6 lymphomas, and 9 thymic cysts, and 4 other cystic tumors. TET, schwannoma, and lymphoma were grouped together as \"solid tumor,\" to be compared with thymic cysts and other tumors (\"cystic tumors\"). The mean post-contrast T1 mapping (P < .001), native T2 mapping (P < .001), and EI (P < .001) values showed significant difference between these two groups. Among TETs, high risk TETs (thymoma types B2, B3, and thymic carcinoma) showed significantly higher native T2 mapping values (P = .002) than low risk TETs (thymoma types A, B1, and AB). For all measured variables, interrater reliability was good to excellent (intraclass coefficient [ICC]: .869∼.990) and intrarater reliability was excellent (ICC: .911∼.995). Conclusion: The use of T1 and T2 mapping in MRI of mediastinal masses is feasible and may provide additional information in the evaluation of mediastinal masses.

UNASSIGNED: This study aimed to investigate the diagnostic value of machine-learning (ML) models with multiple classifiers based on non-enhanced CT Radiomics features for differentiating anterior mediastinal cysts (AMCs) from thymomas, and high-risk from low risk thymomas.
UNASSIGNED: In total, 201 patients with AMCs and thymomas from three centers were included and divided into two groups: AMCs vs. thymomas, and high-risk vs low-risk thymomas. A radiomics model (RM) was built with 73 radiomics features that were extracted from the three-dimensional images of each patient. A combined model (CM) was built with clinical features and subjective CT finding features combined with radiomics features. For the RM and CM in each group, five selection methods were adopted to select suitable features for the classifier, and seven ML classifiers were employed to build discriminative models. Receiver operating characteristic (ROC) curves were used to evaluate the diagnostic performance of each combination.
UNASSIGNED: Several classifiers combined with suitable selection methods demonstrated good diagnostic performance with areas under the curves (AUCs) of 0.876 and 0.922 for the RM and CM in group 1 and 0.747 and 0.783 for the RM and CM in group 2, respectively. The combination of support vector machine (SVM) as the feature-selection method and Gradient Boosting Decision Tree (GBDT) as the classification algorithm represented the best comprehensive discriminative ability in both group. Comparatively, assessments by radiologists achieved a middle AUCs of 0.656 and 0.626 in the two groups, which were lower than the AUCs of the RM and CM. Most CMs exhibited higher AUC value compared to RMs in both groups, among them only a few CMs demonstrated better performance with significant difference in group 1.
UNASSIGNED: Our ML models demonstrated good performance for differentiation of AMCs from thymomas and low-risk from high-risk thymomas. ML based on non-enhanced CT radiomics may serve as a novel preoperative tool.

UNASSIGNED: Mediastinal cysts are uncommon, and their diagnosis remains a clinical challenge, especially for patients with a solid mass on computed tomography (CT). Endoscopic ultrasound (EUS) is considered a valuable method to differentiate mediastinal cysts and EUS-fine needle aspiration (FNA) is a strategy for obtaining specimens from the cysts for cytological diagnosis. This study aims to evaluate the safety and utility of EUS-FNA for diagnosis of mediastinal cysts.
UNASSIGNED: This was a retrospective analysis of patients who underwent EUS-FNA with 19-gauge needle at Tianjin Medical University Cancer Institute and Hospital and were further diagnosed with mediastinal cysts confirmed by cytological and surgical pathological results between January 2016 and December 2020. Safety was estimated by the incidence of reported adverse events (AEs). Patients were followed for 48 hours and 1 week after the EUS-FNA procedure to evaluate AEs.
UNASSIGNED: A total of 20 patients were diagnosed with mediastinal cysts using EUS-FNA, yet only 5 were diagnosed by CT. There were 15 patients diagnosed with bronchogenic cyst, 4 with enteric cyst, and 1 with pericardial cyst. The EUS appearance of cyst content varied, ranging from anechoic (4 cases) to hypoechoic (16 cases). AEs occurred in 2/20 (10%) patients after the EUS-FNA indicating an acceptable low rate of AEs. For all anechoic cysts that underwent complete FNA drainage, 3 patients had good prognosis, whereas 1 experienced recurrence. For 16 patients with hypoechoic cysts, adequate tissue was obtained for cytological examination. No patient developed an infection-related complication.
UNASSIGNED: For the diagnosis of mediastinal cysts, EUS-FNA was more accurate than CT. The EUS-FNA of mediastinal cysts is safe with an acceptable low rate of AEs when antibiotic prophylaxis is used postoperatively. Cysts containing free-flowing fluid can be achieved with complete needle drainage by a single pass with a 19-gauge needle.

BACKGROUND: mediastinal cysts are rare lesions developed from mediastinal structures. They may be acquired like thoracic duct cysts or lymphangiomas or congenital like the bronchogenic cysts, enteric cysts or celomic cysts. These cysts are rare and may cause diagnostic challenges.
OBJECTIVE: To assess the major characteristics of these cysts based on a single institution experience.
METHODS: the authors performed a descriptive, retrospective study from January 2009 to March 2020 in a single institution. Cystic lesions taking birth from the mediastinum for which gross features, microscopic features were available were included.
RESULTS: this study contained 52 mediastinal cysts that were completely resected and no patient presented complications after the surgical resection. The bronchogenic cysts were the most frequent and represented 57.69% of all lesions. Thymic cysts and pericardial cysts represented respectively 40.38% and 1.92% of the cases. The positive diagnosis was based on the microscopic exam. The final diagnosis was concordant with the radiologic findings in 15 cases reaching a rate of 28%.
CONCLUSIONS: the diagnosis of mediastinal cysts is based on the microscopic analysis of the cystic wall. Pericardial cysts may be suspected based on their characteristic location in the cardiophrenic angle, thymic cyst may be evoked based on their location in the thymic region and bronchogenic cysts are mainly located in the middle mediastinum. Inspite of these most frequent locations, the cysts may be located in any part of the mediastinum and may be difficult to diagnose when the key diagnostic features are absent.

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UNASSIGNED: The transient occlusion of the terminal thoracic duct is a rare disease responsible for renitent supraclavicular cysts. The aim of this study was to describe the clinical characteristics, evolution, and treatment.A retrospective multicenter study and literature review was carried out. The literature search (PubMed) was conducted including data up to 31 December 2020 and PRISMA guidelines were respected.This study identified 6 observational cases between September 2010 and December 2020. The search results indicated a total of 24 articles of which 19 were excluded due to the lack of recurrent swelling or the unavailability of full texts (n = 5). Fourteen patients (8 from literature) mostly reported a noninflammatory, painless renitent mass in the supraclavicular fossa which appeared rapidly over a few hours and disappeared spontaneously over an average of 8 days (range: from about 2 hours to 10 days). Anamnesis indicated a high-fat intake during the preceding days in all cases and 7 from literature found in the Medline databases. Recurrences were noted in 10 patients. Thoracic duct imaging was performed in all cases to detect abnormalities or extrinsic compression as well as to eliminate differential diagnoses.A painless, fluctuating, noninflammatory, and recurrent swelling of the left supraclavicular fossa in patients evoking an intermittent obstruction of the terminal portion of the thoracic duct was identified. A low-fat diet was found as safe and effective treatment.