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Predicting subtypes of thymic epithelial tumors using CT: new perspective based on a comprehensive analysis of 216 patients.

ABSTRACT: It is highly necessary to identify low versus high risk thymic epithelial tumors (TETs) before operation to guide optimal treatment strategies. Current CT diagnostic parameters could not effectively achieve this goal. We evaluated three parameters of CT scan in a cohort of 216 TETs patients. Parameters of contrast enhancement, risk of aggressiveness, and nodule with fibrous septum were evaluated in low (A, AB) versus high risk (B1, B2, B3 and thymic carcinoma) TETs. Grade of contrast enhancement showed predictive value in classifying low and high risk TETs well. A maximal contrast-enhanced range of 25.5?HU could produce 78.8% sensitivity and 68.5% specificity in determining low risk subtypes. Additionally, risk of aggressiveness parameter was demonstrated to be associated with TETs subtype (r = 0.801, P < 0.001) and may add confidence in determining low versus high risk subtypes. Furthermore, multiple nodule with fibrous septum could suggest subtype AB. Findings from this study support role of studied parameters of CT manifestations in predicting the low and high risk stages of TETs. These findings provide empirical evidence for incorporating these parameters in clinical practice for identifying TETs stage before operation, if validated in additional studies.

SUBMITTER: Hu YC

PROVIDER: S-EPMC4225535 | biostudies-literature | 2014 Nov

REPOSITORIES: biostudies-literature

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Predicting subtypes of thymic epithelial tumors using CT: new perspective based on a comprehensive analysis of 216 patients.

Hu Yu-Chuan YC Wu Lang L Yan Lin-Feng LF Wang Wen W Wang Shu-Mei SM Chen Bao-Ying BY Li Gang-Feng GF Zhang Bei B Cui Guang-Bin GB

Scientific reports 20141110

It is highly necessary to identify low versus high risk thymic epithelial tumors (TETs) before operation to guide optimal treatment strategies. Current CT diagnostic parameters could not effectively achieve this goal. We evaluated three parameters of CT scan in a cohort of 216 TETs patients. Parameters of contrast enhancement, risk of aggressiveness, and nodule with fibrous septum were evaluated in low (A, AB) versus high risk (B1, B2, B3 and thymic carcinoma) TETs. Grade of contrast enhancement ...[more]

PMID: 25382196

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Project description:To determine the prognostic CT features in patients with untreated thymic epithelial tumors (TETs). Clinical data and CT imaging features of 194 patients with pathologically confirmed TETs were retrospectively reviewed. The subjects included 113 male and 81 female patients between 15 and 78 years of age, with a mean age of 53.8 years. Clinical outcomes were categorized according to whether relapse, metastasis or death occurred within 3 years after the first diagnosis. Associations between clinical outcomes and CT imaging features were determined using univariate and multivariate logistic regression analyses, while the survival status was analyzed by Cox regression. In this study, we analyzed 110 thymic carcinomas, 52 high-risk thymomas and 32 low-risk thymomas. Percentages of poor outcome and patient death in thymic carcinomas were much higher than those in patients with high-risk and low-risk thymomas. In the thymic carcinomas groups, 46 patients (41.8%) experienced tumor progression, local relapse or metastasis and were categorized as having poor outcomes; vessel invasion and pericardial mass were confirmed to be independent predictors by logistic regression analysis (p < 0.01). In the high-risk thymoma group, 11 patients (21.2%) were categorized as having poor outcomes, and the CT feature pericardial mass was confirmed to be an independent predictor (p < 0.01). In survival analysis, Cox regression showed that CT features of lung invasion, great vessel invasion, lung metastasis and distant organ metastasis were independent predictors for worse survival in the thymic carcinoma group (p < 0.01), while lung invasion and pericardial mass were independent predictors for worse survival in high-risk thymoma group. No CT features were related to poor outcome and worse survival in the low-risk thymoma group. Patients with thymic carcinoma had poorer prognosis and worse survival than those with high-risk or low-risk thymoma. CT can serve as an important tool for predicting the prognosis and survival of patients with TETs. In this cohort, CT features of vessel invasion and pericardial mass were related to poorer outcomes in those with thymic carcinoma and pericardial mass in those with high-risk thymoma. Features including lung invasion, great vessel invasion, lung metastasis and distant organ metastasis indicate worse survival in thymic carcinoma, whereas lung invasion and pericardial mass indicate worse survival in high-risk thymoma.

Project description:BackgroundThymic malignancies represent a heterogeneous group of rare thoracic cancers, which are classified according to the World Health Organization histopathologic classification, that distinguishes thymomas from thymic carcinomas. Data regarding the biology of those tumors are limited in the literature, and the vast majority have been obtained using surgical specimens from early-stage disease. Meanwhile, treatment of advanced, refractory thymic tumors currently relies on chemotherapy, with limited efficacy. Comprehensive genomic profiling (CGP) of advanced, refractory tumors would open some opportunities for innovative treatments.Patients and methodsA total of 90 and 174 consecutive patients with thymoma or thymic carcinoma, respectively, for whom formalin-fixed, paraffin-embedded specimens from recurrent, refractory tumor were sequenced, were included. Sequencing was performed using hybridization-captured, adaptor ligation-based libraries to a mean coverage depth of >500× for up to 315 cancer-related genes plus 37 introns from 28 genes frequently rearranged in cancer.ResultsThymomas featured a low frequency of genomic alterations (average of 1.8/tumor), and low levels of TMB. The genomic alterations identified in more than 10% of cases were in the CDKN2A/B and TP53 genes. Amplification in the NTRK1 gene was found in an unresectable, stage III, type B3 thymoma. Thymic carcinomas featured a significantly higher frequency of alterations at 4.0/tumor (P < .0001). Clinically relevant genomic alterations were observed in the CDKN2A, KIT, and PTEN/PI3K/MTOR pathways. Elevated TMB in thymic carcinomas was uncommon with only 6% of cases featuring ≥10 mutations/Mb.ConclusionsOur cohort is the largest available so far, reporting on CGP of thymic epithelial tumors in the setting of advanced disease. The identification of clinically relevant genomic alterations in the KIT, PI3K, CDKN2A/B, or NTRK genes provides a strong rationale for potential precision medicine approaches using targeted agents. A subset of thymic carcinomas show high tumor mutation burden, what may be a predictor of efficacy of immune checkpoint inhibitors.

Project description:BackgroundThymic epithelial tumors (TETs) are the most common primary tumors in the anterior mediastinum, which have considerable histologic heterogeneity. This study aimed to develop and validate a nomogram based on computed tomography (CT) and texture analysis (TA) for preoperatively predicting the pathological classifications for TET patients.MethodsTotally TET 172 patients confirmed by postoperative pathology between January 2011 to April 2019 were retrospectively analyzed and randomly divided into training (n = 120) and validation (n = 52) cohorts. Preoperative clinical factors, CT signs and texture features of each patient were analyzed, and prediction models were developed using the least absolute shrinkage and selection operator (LASSO) regression. The performance of the models was evaluated and compared by the area under receiver-operator characteristic (ROC) curve (AUC) and the DeLong test. The clinical application value of the models was determined via the decision curve analysis (DCA). Then, a nomogram was developed based on the model with the best predictive efficiency and clinical utility and validated using the calibration plots.ResultsTotally 87 patients with low-risk TET (LTET) (types A, AB, B1) and 85 patients with high-risk TET (HTET) (types B2, B3, C) were enrolled in this study. We separately constructed 4 prediction models for differentiating LTET from HTET using clinical, CT, texture features, and their combination. These 4 prediction models achieved AUCs of 0.66, 0.79, 0.82, 0.88 in the training cohort and 0.64, 0.82, 0.86, 0.94 in the validation cohort, respectively. The DeLong test and DCA showed that the Combined model, consisting of 2 CT signs and 2 texture parameters, held the highest predictive efficiency and clinical utility (p < 0.05). A prediction nomogram was subsequently developed using the 4 independently risk factors from the Combined model. The calibration curves indicated a good consistency between the actual observations and nomogram predictions for differentiating TET classifications.ConclusionA prediction nomogram incorporating both the CT and texture parameters was constructed and validated in our study, which can be conveniently used for the preoperative individualized prediction of the simplified histologic subtypes in TET patients.

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Predicting subtypes of thymic epithelial tumors using CT: new perspective based on a comprehensive analysis of 216 patients.

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Predicting subtypes of thymic epithelial tumors using CT: new perspective based on a comprehensive analysis of 216 patients.

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