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.
METHODS: 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.

The thymus is the primary lymphoid organ responsible for the maturation and proliferation of T lymphocytes. During the first years of our lives, the activation and inactivation of T lymphocytes occur within the thymus, facilitating the correct maturation of central immunity. Alterations in the positive and negative selection of T lymphocytes have been studied as the possible origins of autoimmune diseases, with Myasthenia Gravis (MG) being the most representative example. Structural alterations in the thymus appear to be involved in the initial autoimmune response observed in MG, leading to the consideration of thymectomy as part of the treatment for the disease. However, the role of thymectomy in MG has been a subject of controversy for many years. Several publications raised doubts about the lack of evidence justifying thymectomy\'s role in MG until 2016 when a randomized study comparing thymectomy via sternotomy plus prednisone versus prednisone alone was published in the New England Journal of Medicine (NEJM). The results clearly favored the group of patients who underwent surgery, showing improvements in symptoms, reduced corticosteroid requirements, and fewer recurrences over 3 years of follow-up. In recent years, the emergence of less invasive surgical techniques has made video-assisted or robotic-assisted thoracoscopic (VATS/RATS) thymectomy more common, replacing the traditional sternotomy approach. Despite the increasing use of VATS, it has not been validated as a technique with lower morbidity compared to sternotomy in the treatment of MG. The results of the 2016 trial highlighted the benefits of thymectomy, but all the patients underwent surgery via sternotomy. Our hypothesis is that VATS thymectomy is a technique with lower morbidity, reduced postoperative pain, and shorter postoperative hospital stays than sternotomy. Additionally, VATS offers better clinical improvement in patients with MG. The primary objective of this study is to validate the VATS technique as the preferred approach for thymectomy. Furthermore, we aim to analyze the impact of VATS thymectomy on symptoms and corticosteroid dosage in patients with MG, identifying factors that may predict a better response to surgery.

OBJECTIVE: Using contrast-enhanced computed tomography (CECT) and deep learning technology to develop a deep learning radiomics nomogram (DLRN) to preoperative predict risk status of patients with thymic epithelial tumors (TETs).
METHODS: Between October 2008 and May 2020, 257 consecutive patients with surgically and pathologically confirmed TETs were enrolled from three medical centers. We extracted deep learning features from all lesions using a transformer-based convolutional neural network and created a deep learning signature (DLS) using selector operator regression and least absolute shrinkage. The predictive capability of a DLRN incorporating clinical characteristics, subjective CT findings and DLS was evaluated by the area under the curve (AUC) of a receiver operating characteristic curve.
RESULTS: To construct a DLS, 25 deep learning features with non-zero coefficients were selected from 116 low-risk TETs (subtypes A, AB, and B1) and 141 high-risk TETs (subtypes B2, B3, and C). The combination of subjective CT features such as infiltration and DLS demonstrated the best performance in differentiating TETs risk status. The AUCs in the training, internal validation, external validation 1 and 2 cohorts were 0.959 (95% confidence interval [CI]: 0.924-0.993), 0.868 (95% CI: 0.765-0.970), 0.846 (95% CI: 0.750-0.942), and 0.846 (95% CI: 0.735-0.957), respectively. The DeLong test and decision in curve analysis revealed that the DLRN was the most predictive and clinically useful model.
CONCLUSIONS: The DLRN comprised of CECT-derived DLS and subjective CT findings showed a high performance in predicting risk status of patients with TETs.
CONCLUSIONS: Accurate risk status assessment of thymic epithelial tumors (TETs) may aid in determining whether preoperative neoadjuvant treatment is necessary. A deep learning radiomics nomogram incorporating enhancement CT-based deep learning features, clinical characteristics, and subjective CT findings has the potential to predict the histologic subtypes of TETs, which can facilitate decision-making and personalized therapy in clinical practice.
CONCLUSIONS: • A non-invasive diagnostic method that can predict the pathological risk status may be useful for pretreatment stratification and prognostic evaluation in TET patients. • DLRN demonstrated superior performance in differentiating the risk status of TETs when compared to the deep learning signature, radiomics signature, or clinical model. • The DeLong test and decision in curve analysis revealed that the DLRN was the most predictive and clinically useful in differentiating the risk status of TETs.

Tumor-to-tumor metastasis is defined as when metastasis from a primary tumor (donor) grows in a different primary neoplasm (recipient). Due to the structure of the thymus and the low incidence rate, thymic epithelial neoplasm has been rarely described in the literature as a recipient for metastases.In this report,a patient with advanced prostatic cancer and under control after chemo/hormone therapy was directed to our thoracic surgery unit for an anterior mediastinal mass detected during the staging workup for prostate disease. A limited uptake at fluorodeoxyglucose-positron emission tomography (FDG-PET) in the mediastinal lesion, while the surrounding tissue showed diffusely negative hypermetabolism, suggested a second primary thymic epithelial tumor with a possible carcinomatous differentiation. A thymectomy through a median sternotomy was carried out. Histopathological analysis after thymectomy revealed a type A thymoma with multiple elements of prostate adenocarcinoma within it. The foci of prostate adenocarcinoma were co-located in the context of the thymoma, revealing what is defined as a tumor-to-tumor metastasis.To our knowledge, this is the first report describing a thymoma as the recipient of metastases coming from a primary extrathoracic tumor without the involvement of other thoracic organs.

暂无摘要。

Thymic epithelial neoplasms are the most common tumors of thymic origin but are overall rare in the general population. Their morphologic diversity, ranging from low grade to overtly malignant lesions, along with various histologic growth patterns make them a diagnostically challenging group of tumors. Very occasionally, thymomas and thymic carcinomas may develop in combination with other benign or malignant lesions of thymic origin, further complicating the diagnostic process. The focus of this review lies on the spectrum of thymic epithelial tumors that present with other thymic lesions in the same tumor mass, such as multilocular thymic cysts, neuroendocrine neoplasms, lymphomas, and germ cell tumors among others. Awareness of the existence of such unusual tumors may not only aid in their diagnosis but may also have implications for prognostic and therapeutic purposes.

Radiomics is an upcoming field in nuclear oncology, both promising and technically challenging. To summarize the already undertaken work on supradiaphragmatic neoplasia and assess its quality, we performed a literature search in the PubMed database up to 18 February 2022. Inclusion criteria were: studies based on human data; at least one specified tumor type; supradiaphragmatic malignancy; performing radiomics on PET imaging. Exclusion criteria were: studies only based on phantom or animal data; technical articles without a clinically oriented question; fewer than 30 patients in the training cohort. A review database containing PMID, year of publication, cancer type, and quality criteria (number of patients, retrospective or prospective nature, independent validation cohort) was constructed. A total of 220 studies met the inclusion criteria. Among them, 119 (54.1%) studies included more than 100 patients, 21 studies (9.5%) were based on prospectively acquired data, and 91 (41.4%) used an independent validation set. Most studies focused on prognostic and treatment response objectives. Because the textural parameters and methods employed are very different from one article to another, it is complicated to aggregate and compare articles. New contributions and radiomics guidelines tend to help improving quality of the reported studies over the years.

Thymic epithelial tumors are presently staged using a consistent TNM classification developed by the International Association for the Study of Lung Cancer (IASLC) and approved by the Union for International Cancer Control and the American Joint Committee on Cancer. The stage classification is incorporated in the eight edition of the TNM classification of thoracic malignancies. The IASLC Staging and Prognostic Factors Committee (SPFC)-Thymic Domain (TD) is in charge for the next (ninth) edition expected in 2024. The present article represents the midterm report of the SPFC-TD: in particular, it describes the unresolved issues identified by the group in the current stage classification which are worth being addressed and discussed for the ninth edition of the TNM classification on the basis of the available data collected in the central thymic database which will be managed and analyzed by Cancer Research And Biostatistics. These issues are grouped into issues of general importance and those specifically related to T, N, and M categories. Each issue is described in reference to the most recent reports on the subject, and the priority assigned by the IASLC SPFC-TD for the discussion of the ninth edition is provided.

Sebaceous differentiation is an unexpected and unusual phenomenon in the normal thymic gland. Among thymic tumors, sebaceous glands are a relatively common component of mediastinal teratomas but are exceedingly rare in other neoplasms of thymic origin. This review explores the spectrum of non-teratomatous thymic tumors in which sebaceous differentiation has been identified, discusses the potential histogenesis and evaluates the effects of this occurrence on diagnosis, treatment and prognosis.

OBJECTIVE: This study aimed to provide an extensive overview of clinical and pathological findings along with various therapeutic options analyzing in addiction, retrospectively, the surgical outcomes of a single center cohort.
BACKGROUND: Thymic neoplasms are rare thoracic tumors which commonly are located in the anterior mediastinum and are associated with a wide spectrum of clinical presentations. They may run an indolent course or could present a very aggressive biologic progression with infiltration of mediastinal structures and presence of distant metastases. The pathogenesis of these tumors is so far not completely clear. Several treatment modalities in a multidisciplinary setting have to be considered in order to provide the best treatment for patients affected by thymic tumors.
METHODS: We conducted a retrospective cohort analysis of all patients who underwent surgery due to thymic tumor in a university hospital located in Switzerland (Bern University Hospital) and then we performed a narrative review of the English literature using PubMed, Embase, Cochrane Database of Systematic Reviews and Scopus.
CONCLUSIONS: Minimally invasive techniques play an important role in the treatment of thymic tumors. A careful patients selection in a multidisciplinary setting is mandatory in order to offer the best treatment for patients affected by thymic tumors.