Quantitative Thoracic Magnetic Resonance Criteria for the Differentiation of Cysts from Solid Masses in the Anterior Mediastinum

MRI-Based Stepwise Approach to Anterior Mediastinal Cystic Lesions for Diagnosis and Further Management

As the majority of incidentally detected lesions in the anterior mediastinum is small nodules with soft tissue appearance, the differential diagnosis has typically included thymic neoplasm and prevascular lymph node, with benign cyst. Overestimation or misinterpretation of these lesions can lead to unnecessary surgery for ultimately benign conditions. nonsurgical anterior mediastinal lesions. The pitfalls of MRI evaluation for anterior mediastinal cystic lesions are as follows: first, we acknowledge the limitation of T2-weighted images for evaluating benign cystic lesions. Due to variable contents within benign cystic lesions, such as hemorrhage, T2 signal intensity may be variable. Second, owing to extensive necrosis and cystic changes, the T2 shine-through effect may be seen on diffusion-weighted images (DWI), and small solid portions might be missed on enhanced images. Therefore, both enhancement and DWI with apparent diffusion coefficient values should be considered. An algorithm will be suggested for the diagnostic evaluation of anterior mediastinal cystic lesions, and finally, a management strategy based on MRI features will be suggested.

Surgical indications for mediastinal cysts-a narrative review

Background and Objective

Whether and when surgical intervention is indicated for mediastinal cysts is a matter of some debate. While most mediastinal cysts are found incidentally, the anatomic location, clinical presentation, and symptoms, as well as the potential for malignancy, are important considerations that inform decisions related to whether to intervene surgically. The objective of this review is to summarize the current literature regarding the criteria for surgical excision of mediastinal cysts and provide a framework for the clinician and surgeon to arrive at a decision regarding the appropriateness of surgical intervention of mediastinal cysts.

Methods

A review of the published literature in the last 45 years (1977-2022) was conducted through PubMed, MeSh and Google Scholar. We included retrospective reviews, meta-analyses, and case studies published in the English language. A single author identified eligible studies, and those identified were reviewed by the team until consensus was met. Pediatric literature was excluded from this review.

Key Content and Findings

The current literature predominantly contains case studies, small retrospective studies, and meta-analyses describing mediastinal cysts. In the anterior mediastinum, multiloculated thymic cysts should be resected to rule out thymic malignancy. Intralesional fat, smooth borders, and a more midline location are features suggestive of a benign process, while asymmetric cystic wall thickening has been associated with malignancy. Both esophageal and bronchogenic cysts should be excised, taking into account the risk of complications (up to a 45% risk) of infection, rupture, or compression, as well as the rare risk of associated malignancy. Simple thymic and small pericardial cysts can be observed and followed with serial radiographic tools and should be resected if they increase in size, compress surrounding structures, or lead the patient to develop symptoms.

Conclusions

Since mediastinal cysts are rare and often asymptomatic, there are no formal guidelines outlining when surgical intervention should be undertaken. Based on our review of the literature, surgical intervention should be pursued if the patient's symptoms correlate with radiographic findings of a mediastinal cyst, there is compression of the surrounding structures, and concern of malignancy is present.

Mediastinal thymic cysts: a narrative review

Background and Objective

Mediastinal thymic cysts are a relatively rare pathology. With the expansion of eligible individuals screened with cross-sectional imaging for lung cancer, it is likely that there will be an increase in the number of individuals presenting with these cysts. Understanding this rare pathology will become more important when this incidental pathology is encountered.

Methods

Search of PubMed was undertaken using keywords "mediastinal", "mediastinum", "thymic", "thymus", "cyst". Relevant literature was reviewed and selected for this comprehensive narrative review, including case reports, case series, and retrospective reviews.

Key Content and Findings

Thymic cysts in the mediastinum can be classified into two broad categories, congenital and inflammatory. Accurate diagnosis by imaging is challenging and the majority of patients are asymptomatic. Literature suggests that the majority of cysts are benign, however an unknown percentage may harbor neoplastic processes and over time can cause significant compressive symptoms. Definitive treatment and diagnosis is surgical, with overall excellent outcomes. The decision to pursue surgical treatment versus surveillance requires a shared decision making approach with patients.

Conclusions

Given the scarcity of available high quality evidence regarding the management of mediastinal thymic cysts, this review provides practitioners a broad knowledge base to guide patients to make informed decisions.

Machine-learning classifiers based on non-enhanced computed tomography radiomics to differentiate anterior mediastinal cysts from thymomas and low-risk from high-risk thymomas: A multi-center study

Background

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.

Methods

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.

Results

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.

Conclusion

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.

Added Value of Magnetic Resonance Over Computed Tomography in Distinguishing Nonneoplastic Complex Thymic Cysts From Malignant Cystic Thymic Neoplasms

PURPOSE

The aim of the study was to evaluate cystic thymic masses by using computed tomography (CT) and magnetic resonance (MR) scoring systems to differentiate nonneoplastic thymic cysts from cystic thymic neoplasms.

METHODS

This retrospective multisite study included adult patients who underwent CT and MR imaging of the chest between 2007 and 2020 with any of the following impressions on cross-sectional imaging studies: "thymic mass with cystic component," "unilocular or multilocular cystic thymic lesion," "complex thymic cyst," "thymic cyst with hemorrhage." Two blinded radiologists reviewed and recorded specific imaging features as well as overall impressions on both CT and MR using a Likert scale scoring system. Data were analyzed, and diagnostic accuracy of CT and MR was compared using areas under the receiver operating characteristic curves (AUC).

RESULTS

Fifty-six patients were included, of which 45 (80%) had benign masses. Total of 21 patients (38%) had indeterminate scores on CT of which 3 (14%) were malignant, while only 6 (11%) had indeterminate scores on MR and 1 was malignant. Magnetic resonance scoring system (AUC, 0.95) performed better than CT scoring system (AUC, 0.86) in distinguishing benign versus malignant lesions (P = 0.06). Lack of enhancement within the mass was completely predictive of benign etiology (P < 0.001). Wall thickness of an enhancing cyst was predictive of malignancy, with AUC 0.93.

CONCLUSIONS

Magnetic resonance yielded higher specificity allowing a larger number of lesions to be confidently assigned a benign diagnosis. This could help in averting unnecessary follow-up, biopsies, or surgery. The authors recommend follow-up imaging with MR for prevascular masses, even those appearing "solid" on CT.

Clinical usefulness of PET/MRI in differentiating anterior mediastinal masses

OBJECTIVES

To investigate the clinical usefulness of 18F-fluorodeoxyglucose (FDG) PET/MRI in differentiating anterior mediastinal lesions, including small ones.

MATERIAL AND METHODS

Among 96 patients who underwent 18F-FDG PET/MRI screening for anterior mediastinal lesions, we retrospectively reviewed images of 42 patients with histologically or clinically diagnosed thymic carcinomas, thymomas or anterior mediastinal cysts. MRI findings and maximum standardized uptake value (SUVmax) were compared among the three categories. In addition, small lesions measuring <3.0 cm which did not show very high signal intensity (isointense to water) on T2 weighted images (T2WI) were sub-analyzed.

RESULTS

Significant differences in SUVmax were observed among anterior mediastinal cysts (P < 0.001, vs. thymomas and thymic carcinomas), thymomas (P = 0.032, vs. thymic carcinomas) and thymic carcinomas. Regarding the MRI findings, anterior mediastinal cysts showed higher T2WI signal intensity (P = 0.004 vs. thymomas and P = 0.042 vs. thymic carcinomas) and thymic carcinomas tended to show ill-defined contours (P = 0.024 vs. anterior mediastinal cysts and P = 0.036 vs. thymomas). SUVmax was also significantly higher in small thymic tumors than small anterior mediastinal cysts without very high T2WI signal intensity (P = 0.003).

CONCLUSION

18F-FDG PET/MRI is clinically useful in differentiating anterior mediastinal lesions, including those smaller than 3 cm.

Role of quantitative energy spectrum CT parameters in differentiating thymic epithelial tumours and thymic cysts

AIM

To explore the utility of multiple energy spectrum computed tomography (CT) parameters in distinguishing thymic epithelial tumours (TETs) from thymic cysts among lesions <5 cm in diameter.

MATERIALS AND METHODS

Data pertaining to 56 patients with TETs and thymic cysts <5 cm in diameter were assessed retrospectively. All patients underwent surgical resection and the diagnosis was confirmed histopathologically. Thirty-five patients with TETs (average age, 51.97 years) and 21 patients with thymic cysts (average age, 50.54 years) were included. The region of interest for the lesion on the energy spectrum CT was delineated on the post-processing workstation, and multiple parameters of the energy spectrum CT were obtained. The diagnostic efficacies of the parameters were analysed using receiver operating characteristic (ROC) curves.

RESULTS

To distinguish small TETs from thymic cysts, a single-energy CT value of 60 keV showed good differential diagnostic performance in the arterial phase (cut-off value = 68.42 HU; area under the curve [AUC] = 0.978), a single-energy CT value of 70 keV showed good differential diagnostic performance in the venous phase (cut-off value = 59.77 HU; AUC = 0.956). In the arterial and venous phases, effective atomic numbers of 8.065 and 8.175, respectively, were used as cut-off values to distinguish small TETs from thymic cysts (AUC = 0.972 and AUC = 0.961, respectively). Iodine concentrations of 10.99 and 11.05 were used as cut-off values to distinguish small TETs from thymic cysts (AUC = 0.956 and AUC = 0.924, respectively).

CONCLUSION

According to the present study, energy spectrum CT parameters may have clinical value in the differential diagnosis of TETs and thymic cysts.

Longitudinal CT and MRI Characteristics of Unilocular Thymic Cysts

Background Isoattenuating and hyperattenuating thymic cysts at CT are often misinterpreted as lymphadenopathy or thymic epithelial neoplasms. Purpose To evaluate the longitudinal change in thymic cyst appearance at CT and MRI. Materials and Methods All chest MRI studies showing thymic cysts between July 2008 and December 2019, identified from a retrospective search of a quality assurance database, were included in this study if initial CT depicted a thymic lesion, the patient was referred for follow-up MRI for characterization, and the baseline (ie, index) MRI indicated a cystic lesion. Follow-up CT scans and/or MRI scans were identified through July 2020. Thymic cyst characteristics, such as size, location, and morphologic features, as well as CT and MRI characteristics, were recorded. Change in size, attenuation, and T1-weighted MRI signal was assessed longitudinally. Descriptive statistics of longitudinal change were tabulated. Results A total of 244 chest MRI studies in 140 patients with 142 unique cysts and 392 CT examinations (636 total examinations and 645 thymic cysts-nine examinations with two cysts each) were evaluated. The median follow-up duration was 2.2 years. Thirty-three patients with 34 unique cysts (34 of 142 cysts [24%]) underwent imaging follow-up for more than 5 years. Thymic cysts followed up for more than 5 years were most commonly saccular (189 of 274 cysts [69% axially]) and retrosternal (14 of 34 cysts [41%]). Craniocaudal dimension was larger than transverse and anteroposterior dimensions in 223 of 274 cysts (81%). Mean thymic cyst attenuation was 25 HU (range, 15-100 HU). Five of 31 cysts (16%) exhibited wall calcification. The median cyst wall thickness was 2.0 mm (range, 0.9-3.0 mm). Most thymic cysts changed in volume (31 of 34 cysts [91%]), CT attenuation (15 of 35 cysts [43%]), and T1-weighted MRI signal (12 of 18 cysts [67%]) over time. None developed mural irregularity, nodularity, or septations. Conclusion Unilocular thymic cysts, defined at index MRI, never developed irregular wall thickening, mural nodularity, or septations that would raise concern for malignant transformation. However, these cysts showed mural calcification and change in size, CT attenuation, and MRI signal over more than 5 years of follow-up. © RSNA, 2021 Online supplemental material is available for this article.

Pneumonia, pleurisy, mediastinitis, and mediastinal cyst infection secondary to endobronchial ultrasound-guided transbronchial needle aspiration: A case report

INTRODUCTION

Endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA) is less commonly used in nonmalignant diseases. In particular, its application in mediastinal cystic lesions has been reported less frequently. EBUS-TBNA is a reassuringly safe procedure with an overall complication rate less than 2%, and serious adverse event rate of 0.14% to 0.16%. The most common complications are infections (mediastinal cyst infection most seen).

PATIENT CONCERNS

A 28-year-old male presented to the hospital with mediastinal cyst that was incidentally discovered by computed tomography. There was no past history of the patient reviewed.

DIAGNOSIS

The cyst was identified as a round, anechoic structure by EBUS and serous fluid was aspirated. The carcino-embryonic antigen, mycobacterium tuberculosis DNA and cultures in the fluid were negative. Cytology analysis showed lots of lymphocytes and no malignant cells. The diagnosis of lymphangioma was confirmed based on the computed tomography and EBUS presentation, the nature of the aspirated fluid and the large number of mature lymphocytes within the cystic fluid.

INTERVENTIONS

Twenty-six hours after EBUS-TBNA, the patient complained of a fever with the highest temperature of 39°C, accompanied by a right-side chest pain, no other symptoms of were reported. The following examinations confirmed the diagnosis of pneumonia, pleurisy, mediastinitis and mediastinal cyst infection, while cultures from cyst and right pleural effusion were both negative. The patient was treated with Teicoplanin+Imipenem/cilastatin, and ultrasound guided transcutaneous catheterization drainage of mediastinal cyst and pleural effusion were performed.

OUTCOMES

Seven days after the treatments, the patient's symptoms resolved, the complete blood count, C-reactive protein, erythrocyte sedimentation rate were lowered. The size of the cyst was slightly reduced on 17 June compared to that before EBUS-TBNA. Although the surgical resection of the cyst was recommended, the patient declined. After extracted the two drainage tubes, the patient was discharged on June 22. The patient was followed up by telephone 6 months after discharge and he remained asymptomatic.

CONCLUSIONS

EBUS-TBNA is a useful diagnostic and therapeutic tool for the management of mediastinal cysts. However, considering the possibility of serious complications, the clinical procedure should be carried out scrupulously with appropriate patient selection and strict aseptic principles.

Can computed tomography-based radiomics potentially discriminate between anterior mediastinal cysts and type B1 and B2 thymomas?

Background

Anterior mediastinal cysts (AMC) are often misdiagnosed as thymomas and undergo surgical resection, which caused unnecessary treatment and medical resource waste. The purpose of this study is to explore potential possibility of computed tomography (CT)-based radiomics for the diagnosis of AMC and type B1 and B2 thymomas.

Methods

A group of 188 patients with pathologically confirmed AMC (106 cases misdiagnosed as thymomas in CT) and thymomas (82 cases) and underwent routine chest CT from January 2010 to December 2018 were retrospectively analyzed. The lesions were manually delineated using ITK-SNAP software, and radiomics features were performed using the artificial intelligence kit (AK) software. A total of 180 tumour texture features were extracted from enhanced CT and unenhanced CT, respectively. The general test, correlation analysis, and LASSO were used to features selection and then the radiomics signature (radscore) was obtained. The combined model including radscore and independent clinical factors was developed. The model performances were evaluated on discrimination, calibration curve.

Results

Two radscore models were constructed from the unenhanced and enhanced phases based on the selected four and three features, respectively. The AUC, sensitivity, and specificity of the enhanced radscore model were 0.928, 89.3%, and 83.8% in the training dataset and 0.899, 84.6%, and 87.5% in the test dataset (higher than the unenhanced radscore model). The combined model of enhanced CT including radiomics features and independent clinical factors yielded an AUC, sensitivity and specificity of 0.941, 82.1%, and 94.6% in the training dataset and 0.938, 92.3%, and 87.5% in the test dataset (higher than the unenhanced combined model and enhanced radscore model).

Conclusions

The study suggested the possibility that the combined model in enhanced CT provided a potential tool to facilitate the differential diagnosis of AMC and type B1 and B2 thymomas.

Pictorial Review of Mediastinal Masses with an Emphasis on Magnetic Resonance Imaging

Magnetic resonance imaging (MRI) has become a crucial tool for evaluating mediastinal masses considering that several lesions that appear indeterminate on computed tomography and radiography can be differentiated on MRI. Using a three-compartment model to localize the mass and employing a basic knowledge of MRI, radiologists can easily diagnose mediastinal masses. Here, we review the use of MRI in evaluating mediastinal masses and present the images of various mediastinal masses categorized using the International Thymic Malignancy Interest Group's three-compartment classification system. These masses include thymic hyperplasia, thymic cyst, pericardial cyst, thymoma, mediastinal hemangioma, lymphoma, mature teratoma, bronchogenic cyst, esophageal duplication cyst, mediastinal thyroid carcinoma originating from ectopic thyroid tissue, mediastinal liposarcoma, mediastinal pancreatic pseudocyst, neurogenic tumor, meningocele, and plasmacytoma.