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.

Use quantitative parameters in spectral computed tomography for the differential diagnosis of metastatic mediastinal lymph nodes in lung cancer patients.

BACKGROUND: Accurate diagnosis of mediastinal lymph node (LN) metastases is very important for the treatment and prognosis in lung cancer patients. Spectral computed tomography (CT), as a non-invasive approach, has good prospects for detecting mediastinal nodal metastasis. However, the diagnostic criteria of differentiating metastatic and nonmetastatic LNs have not been determined. METHODS: Clinical and imaging data of 64 lung cancer patients (mean age 61.3±10.3 years, 41 men) from April to December 2019 were retrospectively analyzed. The unenhanced scan and contrast enhanced arterial phase (AP) and venous phase (VP) spectral CT scans were performed. The 70 keV monochromatic image and iodine-based image in all phases were analyzed to measure the parameters of LNs. LNs were divided into the metastatic and non-metastatic groups based on confirmative pathological results, and their differences were statistically analyzed. The receiver operating characteristics curve (ROC) was used to evaluate the efficacy of the differential diagnosis. RESULTS: Seventy-four metastatic LNs and 152 non-metastatic LNs were obtained. Compared with non-metastatic LNs, metastatic LNs often had a larger size (P<0.001). In the unenhanced scans, the density of metastatic LNs was lower than that of non-metastatic LNs (P<0.001); however, there was no difference in CT value in AP and VP between metastatic and non-metastatic LNs (P=0.07, P=0.08, respectively). A statistically significant difference was found in iodine concentration (IC), normalized iodine concentration (NIC) and slope of the spectral curve (λHU) in unenhanced scan, IC and λHU in AP, as well as IC, NIC and λHU in VP between metastatic and non-metastatic LNs. There was no difference in NIC in AP between them. CONCLUSIONS: Combined with morphology, spectral CT quantitative parameters demonstrate certain diagnostic efficiency for differential diagnosis between metastatic and non-metastatic LNs in lung cancer patients.