Thymic Imaging Pitfalls and Strategies for Optimized Diagnosis.

Thymic imaging is challenging because the imaging appearance of a variety of benign and malignant thymic conditions are similar. CT is the most commonly used modality for mediastinal imaging, while MRI and fluorine 18 fluorodeoxyglucose (FDG) PET/CT are helpful when they are tailored to the correct indication. Each of these imaging modalities has limitations and technical pitfalls that may lead to an incorrect diagnosis and mismanagement. CT may not be sufficient for the characterization of cystic thymic processes and differentiation between thymic hyperplasia and thymic tumors. MRI can be used to overcome these limitations but is subject to other potential pitfalls such as an equivocal decrease in signal intensity at chemical shift imaging, size limitations, unusual signal intensity for cysts, subtraction artifacts, pseudonodularity on T2-weighted MR images, early imaging misinterpretation, flow and spatial resolution issues hampering assessment of local invasion, and the overlap of apparent diffusion coefficients between malignant and benign thymic entities. FDG PET/CT is not routinely indicated due to some overlap in FDG uptake between thymomas and benign thymic processes. However, it is useful for staging and follow-up of aggressive tumors (eg, thymic carcinoma), particularly for detection of occult metastatic disease. Pitfalls in imaging after treatment of thymic malignancies relate to technical challenges such as postthymectomy sternotomy streak metal artifacts, differentiation of postsurgical thymic bed changes from tumor recurrence, or human error with typical "blind spots" for identification of metastatic disease. Understanding these pitfalls enables appropriate selection of imaging modalities, improves diagnostic accuracy, and guides patient treatment. ©RSNA, 2024 Test Your Knowledge questions for this article are available in the supplemental material.

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.

Imaging and Histopathological Features Of Primary Thymic Neuroendocrine Tumor.

OBJECTIVES: To investigate CT, MRI, and PET/CT features with histopathological findings of primary thymic neuroendocrine tumor. MATERIALS AND METHODS: All 9 cases with pathologically proven primary thymic neuroendocrine tumors were reviewed retrospectively. Among them, 7 underwent enhanced CT, 1 with MRI (enhanced) and another with PET/CT scan. Multiple characters were examined, including tumor location, contour, CT attenuation, enhancement pattern, involvement of surrounding structure and lymphadenopathy. RESULTS: Among 9 patients studied, 7 (77%) masses were located in the anterior superior mediastinum, 1 in the anterior superior-middle mediastinum, and 1 in the anterior and middle mediastinum. The maximum diameter (longitudinal) ranged from 4.2 to 23 cm (mean ± standard deviation, 9.5 cm ± 2.8). Four masses had irregular, 3 had lobulated, and 2 had smooth contours, while 8 masses had clear margins and 1 had an ill-defined margin. Six masses showed heterogeneous attenuation with necrotic/cystic component (n=5), calcification (n=2) and hemorrhage(n=1), and 3 showed homogeneous attenuation on the non-enhanced image. After contrast administration, 8 masses showed heterogeneous attenuation, and 1 showed homogeneous attenuation with tumor vessels visible in 4 masses. Among all, 8 masses showed strong enhancement, and 1 showed moderate enhancement in comparison to muscles in the anterior thoracic wall on enhanced images. Involvement of adjacent mediastinal structures was observed in 5 cases. Immunohistochemical analysis showed that the tumor cells were positive for CgA, Syn, CK, CD56 and EMA. CONCLUSION: Primary NETs are large masses located anterior superior mediastinum, irregular in contour, showing heterogeneous attenuation with necrotic/cystic component and strong heterogeneous enhancement with tumor vessels, compressing local mediastinal structures. In addition, immunohistochemical examination is required in such a diagnosis.

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.

A diagnostic model based on 18F-FDG PET/CT parameters in improving the differential diagnosis of invasive thymic epithelial tumors and anterior mediastinal lymphomas.

BACKGROUND: Accurately distinguishing between invasive thymic epithelial tumors (TETs) and anterior mediastinal lymphoma before surgery is crucial for subsequent treatment choices. But currently, the diagnosis of invasive TET is sometimes difficult to distinguish from anterior mediastinal lymphoma. OBJECTIVE: To assess the application of fluorine-18-fluorodeoxyglucose (18F-FDG) positron emission tomography/computer tomography (PET/CT) in the differential diagnosis of TETs and anterior mediastinal lymphomas. METHODS: 18F-FDG PET/CT images of 133 invasive TETs and anterior mediastinal lymphomas patients were retrospectively analyzed. In particular, the tumor's longest diameter and maximum standardized uptake value (SUVmax) were evaluated. The SUVmax and longest diameter values of the two groups were analyzed by using the receiver operating characteristic (ROC) curve to determine the optimal threshold and diagnostic efficiency. RESULTS: Age, myasthenia gravis, SUVmax and tumor longest diameter differed significantly between invasive TETs and anterior mediastinal lymphomas patients. The tumor location, calcification, relationship with adjacent vessels and distant metastasis differed significantly between the groups. The ROC analysis showed an AUC for SUVmax and tumor longest diameter of 0.841 and 0.737. Respectively, the cutoff values with the best diagnostic performance were 9.65 (sensitivity: 77.78%, specificity: 81.97%) and 6.65 (sensitivity: 80.56%, specificity: 62.30%) for SUVmax and tumor longest diameter. The diagnostic model of SUVmax, calcification, relationship with surrounding blood vessels, lymph node metastasis and lung metastasis in the highest AUC of 0.935 (sensitivity: 90.16%, specificity: 88.89%). In addition, we incorporated splenic involvement and metastatic sub-diaphragmatic lymph node into Model 2 as a new predictive model 3 for differential diagnosis and found a significant improvement in the diagnostic performance of Model 3. CONCLUSION: The diagnostic model composed of 18F-FDG PET parameters is improving the differential diagnosis of invasive TETs and anterior mediastinal lymphomas.

Histogram analysis based on unenhanced CT for identifying thymoma and lymphoma among prevascular mediastinal incidentalomas.

OBJECTIVE: To determine whether histogram analysis based on unenhanced CT can play a role in the differential diagnosis of thymoma and lymphoma from thymic hyperplasia and cyst (mean CT attenuation > 10 HU). MATERIALS AND METHODS: This retrospective study included consecutive asymptomatic participants who have prevascular mediastinal lesions incidentally detected by unenhanced CT between December 2013 and August 2020, and with definitive diagnosis by pathology or additional radiologic work-ups. A total of thirteen histogram parameters on enhanced CT were calculated for each lesion, then were compared between tumor (thymoma + lymphoma) and non-tumor (hyperplasia + cyst). Receiver operating characteristic analysis was conducted to investigate the performance of histogram parameter for identifying tumor. RESULTS: The study population included 192 patients (106 men and 86 women) with a mean age of 50.5 years at the time of CT examination. Of them, 94 patients have tumor (87 thymomas and 7 lymphoma) and 98 have non-tumor (48 thymic hyperplasia and 50 cysts). Nine of the thirteen histogram parameters revealed significant difference between the two groups, including median, minimum, range, 10th percentile, 90th percentile, kurtosis, skewness, uniformity and entropy. No significant difference was observed in the mean CT attenuation between groups. Higher median was found to be independent predictors for distinguishing tumor from non-tumor, and can achieve an area under the curve (AUC) of 0.785 (95% confidence interval [95% IC], 0.720-0.841). CONCLUSIONS: Histogram analysis based on unenhanced CT may be able to provide some help in the differential diagnosis of incidental lesions in prevascular mediastinal. GRAND SUPPORT: This study was sponsored by Natural Science Foundation of Shanghai (No. 21ZR1459700).

CT-guided pretreatment biopsy diagnosis in patients with thymic epithelial tumours: diagnostic accuracy and risk of seeding.

AIM: To investigate the diagnostic performance of computed tomography (CT)-guided percutaneous transthoracic needle biopsy (PTNB) for thymic epithelial tumours (TETs) and the complication rate after PTNB including seeding after PTNB. MATERIALS AND METHODS: This retrospective study identified PTNBs for anterior mediastinal lesions between May 2007 and September 2021. The diagnostic performance for TETs and complications were investigated. The concordance of the histological grades of TETs between PTNB and surgery was evaluated. The factors associated with pleural seeding after PTNB were determined using Cox regression analysis. RESULTS: Of 387 PTNBs, 235 PTNBs from 225 patients diagnosed as TETs (124 thymomas and 101 thymic carcinomas) and 150 PTNBs from 133 patients diagnosed as other than TETs were included. The sensitivity, specificity, and accuracy for TETs were 89.4% (210/235), 100% (210/210), and 93.5% (360/385), respectively, with an immediate complication rate of 4.4% (17/385). The concordance rate of the histological grades between PTNB and surgery was 73.3% (77/105) after excluding uncategorised types of thymomas. During follow-up after PTNB (median duration, 38.8 months; range, 0.3-164.6 months), no tract seeding was observed. Pleural seeding was observed in 26 patients. Thymic carcinoma (hazard ratio [HR], 5.94; 95% confidence interval [CI], 2.07-17.08; p=0.001) and incomplete resection (HR, 3.29; 95% CI, 1.20-9.02; p=0.02) were associated with pleural seeding, while the biopsy approach type (transpleural versus parasternal) was not associated (p=0.12). CONCLUSIONS: Pretreatment biopsy for TETs was accurate and safe and may be considered for diagnosing TETs, particularly when the diagnosis is challenging and histological diagnosis is mandatory.

Contrast-enhanced CT-based radiomics differentiate anterior mediastinum lymphoma from thymoma without myasthenia gravis and calcification.

AIM: To explore the value of a radiomics model based on enhanced computed tomography (CT) in differentiating anterior mediastinal lymphoma (AML) and thymoma without myasthenia gravis (MG) and calcification. MATERIALS AND METHODS: The present study analysed patients who were diagnosed histologically with AML and thymoma in three independent institutions. All pre-treatment patients underwent enhanced CT. In the training group of patients from institutions 1 (the First Affiliated Hospital of Kunming Medical University) and 3 (the Yunnan Cancer Hospital), two radiologists independently analysed the enhanced CT images and performed manual segmentation of each tumour. Radiomics features were screened using interobserver interclass coefficient (ICC) analysis, feature correlation analysis, and L1 regularisation. The discriminative efficacy of the logistic regression model was evaluated using receiver operating characteristic (ROC) analysis. Validation group of patients from institution 2 (the Second Affiliated Hospital of Zhejiang University School of Medicine) was used to validate the proposed models. RESULTS: A total of 114 patients were enrolled in this study and 1,743 radiomics features were extracted from the enhanced CT images. After feature screening, the remaining 37 robust radiomics features were used to construct the model. In the training group, the AUC of the model was 0.987 (95% confidence interval [CI]: 0.976-0.999), the sensitivity, specificity, and accuracy were 0.912, 0.946, and 0.924, respectively. In the validation group, the AUC of the model was 0.798 (95% CI: 0.683-0.913), the sensitivity, specificity, and accuracy were 0.760, 0.700, and 0.743, respectively. CONCLUSION: The radiomics model created provided effective information to assist in the selection of clinical strategies, thus reducing unnecessary procedures in patients with AML and guiding direct surgery in patients with thymoma to avoid biopsy.

Review of clinical and diagnostic imaging of the thymus: from age-related changes to thymic tumors and everything in between.

The thymus, a primary lymphoid organ of the immune system, undergoes several changes due to a variety of reasons, ranging from aging to pathological conditions. These changes can make distinguishing between benign and neoplastic changes in the thymus challenging, thereby complicating the histopathological diagnoses of thymic tumors. Moreover, most patients with thymic tumors are asymptomatic at the time of diagnosis. Therefore, imaging plays an extremely important role in the evaluation of thymic lesions. In this review, we introduced the imaging characteristics of the thymus, ranging from benign findings, such as normal maturation and benign lesions, to neoplasms.

Lobulated tumor contour as a predictor of preoperative tumor invasion of the lung or pericardium in thymoma patients.

PURPOSE: Preoperative investigations to detect invasion to neighboring organs are important for deciding on the most appropriate surgical approach for thymoma. We evaluated preoperative computed tomography (CT) findings in thymoma patients to identify the CT features associated with tumor invasion. METHODS: Clinicopathologic information on 193 patients who underwent surgical resection for thymoma at Chiba University Hospital between 2002 and 2016 was collected retrospectively. The surgical pathology identified invasion of thymoma in 35 patients: in the lung (n = 18), pericardium (n = 11), or both (n = 6). Contact lengths between the tumor contour and lung (CLTL) or pericardium (CLTP) were measured at the maximum section of the tumor on axial CT. Univariate and multivariate analyses were performed to analyze the relationship between pathological invasion of the lung or pericardium and the clinicopathologic features. RESULTS: The mean CLTL and CLTP were significantly longer in patients with invasion of the neighboring organs than in those without invasion. A lobulated tumor contour was identified in 95.6% of the patients with invasion of the neighboring organs. A multivariate analysis revealed that a lobulated tumor contour was significantly associated with both lung and pericardial invasion. CONCLUSIONS: A lobulated tumor contour was significantly associated with lung and/or pericardial invasion in thymoma patients.

Multifocal primary intrapulmonary thymoma successfully resected via robotic-assisted thoracoscopic surgery.

Primary intrapulmonary thymoma (PIT) represents a rare subset of ectopic thymoma that arises solely from inside the pulmonary parenchyma. Multifocal PIT, where multiple isolated PIT origins coexist in the lungs, has only been confirmed in one previous case report, in which the patient died before surgical resection. These tumours are difficult to diagnose as imaging findings are non-specific, and non-invasive biopsy often yields inaccurate results. We present the case of a man in his 70s who was referred to thoracic surgery for resection of a presumptive endobronchial pulmonary carcinoid tumour. Only after surgical resection did we identify that the patient had multifocal PIT. In this report, we describe our diagnostic and management process for this patient and review the current literature on PIT.

Quantitative CT parameters combined with preoperative systemic inflammatory markers for differentiating risk subgroups of thymic epithelial tumors.

BACKGROUND: Thymic epithelial tumors (TETs) are the most common primary neoplasms of the anterior mediastinum. Different risk subgroups of TETs have different prognosis and therapeutic strategies, therefore, preoperative identification of different risk subgroups is of high clinical significance. This study aims to explore the diagnostic efficiency of quantitative computed tomography (CT) parameters combined with preoperative systemic inflammatory markers in differentiating low-risk thymic epithelial tumors (LTETs) from high-risk thymic epithelial tumors (HTETs). METHODS: 74 Asian patients with TETs confirmed by biopsy or postoperative pathology between January 2013 and October 2022 were collected retrospectively and divided into two risk subgroups: LTET group (type A, AB and B1 thymomas) and HTET group (type B2, B3 thymomas and thymic carcinoma). Statistical analysis were performed between the two groups in terms of quantitative CT parameters and preoperative systemic inflammatory markers. Multivariate logistic regression analysis was used to determine the independent predictors of risk subgroups of TETs. The area under curve (AUC) and optimal cut-off values were calculated by receiver operating characteristic (ROC) curves. RESULTS: 47 TETs were in LTET group, while 27 TETs were in HTET group. In addition to tumor size and CT value of the tumor on plain scan, there were statistical significance comparing in CT value of the tumor on arterial phase (CTv-AP) and venous phase (CTv-VP), and maximum enhanced CT value (CEmax) of the tumor between the two groups (for all, P < 0.05). For systemic inflammatory markers, HTET group was significantly higher than LTET group (for all, P < 0.05), including platelet-to-lymphocyte ratio (PLR), neutrophil-to-lymphocyte ratio (NLR) and systemic immune-inflammation index (SII). Multivariate logistic regression analysis showed that NLR (odds ratio [OR] = 2.511, 95% confidence interval [CI]: 1.322-4.772, P = 0.005), CTv-AP (OR = 0.939, 95%CI: 0.888-0.994, P = 0.031) and CTv-VP (OR = 0.923, 95%CI: 0.871-0.979, P = 0.008) were the independent predictors of risk subgroups of TETs. The AUC value of 0.887 for the combined model was significantly higher than NLR (0.698), CTv-AP (0.800) or CTv-VP (0.811) alone. The optimal cut-off values for NLR, CTv-AP and CTv-VP were 2.523, 63.44 Hounsfeld Unit (HU) and 88.29HU, respectively. CONCLUSIONS: Quantitative CT parameters and preoperative systemic inflammatory markers can differentiate LTETs from HTETs, and the combined model has the potential to improve diagnostic efficiency and to help the patient management.

Deep learning-based radiomic nomogram to predict risk categorization of thymic epithelial tumors: A multicenter study.

PURPOSE: The study was aimed to develop and evaluate a deep learning-based radiomics to predict the histological risk categorization of thymic epithelial tumors (TETs), which can be highly informative for patient treatment planning and prognostic assessment. METHOD: A total of 681 patients with TETs from three independent hospitals were included and separated into derivation cohort and external test cohort. Handcrafted and deep learning features were extracted from preoperative contrast-enhanced CT images and selected to build three radiomics signatures (radiomics signature [Rad_Sig], deep learning signature [DL_Sig] and deep learning radiomics signature [DLR_Sig]) to predict risk categorization of TETs. A deep learning-based radiomic nomogram (DLRN) was then depicted to visualize the classification evaluation. The performance of predictive models was compared using the receiver operating characteristic and decision curve analysis (DCA). RESULTS: Among three radiomics signatures, DLR_Sig demonstrated optimum performance with an AUC of 0.883 for the derivation cohort and 0.749 for the external test cohort. Combining DLR_Sig with age and gender, DLRN was depict and exhibited optimum performance among all radiomics models with an AUC of 0.965, accuracy of 0.911, sensitivity of 0.921 and specificity of 0.902 in the derivation cohort, and an AUC of 0.786, accuracy of 0.774, sensitivity of 0.778 and specificity of 0.771 in the external test cohort. The DCA showed that DLRN had greater clinical benefit than other radiomics signatures. CONCLUSIONS: Our study developed and validated a DLRN to accurately predict the risk categorization of TETs, which has potential to facilitate individualized treatment and improve patient prognosis evaluation.