In order to provide an effective way to prevent or substantially delay the recurrence of invasive meningioma, and improve the curative effect of surgical treatment, we collected and analyzed the clinical manifestations, pathological features, preoperative imaging characteristics as well the data obtained during the surgical treatment of invasive meningioma. From February 2014 to February 2016, 59 patients with invasive meningioma were enrolled in this study. Invasive meningioma was confirmed in all patients by operation. Information about clinical manifestations, pathological features, preoperative imaging and surgical treatment were collected and analyzed. After surgery, pathological specimens were collected, and cases were confirmed as invasive meningioma by pathological examination. The course of disease ranged from 15 days to 7 years (average, 13.2 months). We used World Health Organization (WHO) criteria for classification of meningioma in the nervous system tumors as our reference. Symptoms were as follows: Intracranial hypertension (29 cases), cranial nerve dysfunction (10 cases), epilepsy (11 cases) and other symptoms (9 cases). We had 56 cases of WHO grade I; 6 cases of WHO grade II and 7 cases of WHO grade III. Surgical removal was: Simpson grade I (56 cases), Simpson grade II (2 cases), Simpson grade III and above (56 cases). We used before surgery imaging data to formulate our surgical plan. In general, during surgeries we did not proceed to complete resection, because in the majority of cases, some key structures were invaded and meningioma was very deep and any attempt for total resection could easily lead to significant damage to these structures.

Background: Pulmonary nodular mucinous adenocarcinoma (PNMA) tends to be easily misdiagnosed as tuberculoma in practice. In this study, we aimed to discriminate PNMA from tuberculoma with dynamic computed tomography (CT).Methods: In this study, 38 consecutive pathologically confirmed cases of PNMA and 23 cases of tuberculoma from January 2015 to December 2019 were retrospectively collected. The mean CT attenuations of each lesion were examined. The values on the plain scan, the venous scan, and the enhanced values (CT attenuation of lesion of venous scan minus that of the plain scan) were tested with an independent t-test pair-wisely. Receiver operating characteristic (ROC) curve analyses were performed to test the differential diagnosis values. The presence of satellite lesions was determined with the chi-square test. Results:The mean CT attenuation of tuberculoma shown on the plain scan was significantly higher than that of PNMA (35.15±16.00 vs. 24.00±12.67 HU; P<0.01). The enhanced value of tuberculoma on venous scan was significantly lower than that of PNMA (13.44±13.40 vs. 22.52±14.00 HU; P=0.02). The optimum CT attenuation of the plain scan and the enhanced value for differential diagnosis were 28.80 and 14.25 HU [area under the curve (AUC) =0.72, 95% confidence interval (CI): 0.58-0.86; and AUC =0.70, 95% CI: 0.59-0.84], with sensitivity (78.3% vs. 71.1%) and specificity (63.8% vs. 69.6%) respectively. The satellite lesions were more often observed in the tuberculoma group (P<0.01). Conclusions:The CT attenuation of the plain scan, the enhanced value after enhancement, and the presence of satellite lesions might be useful in differentiating PNMA from tuberculoma.

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Background: Central lung cancer with obstructive atelectasis is very common in clinical practice.Determination of the tumor borderline is important. Conventional computed tomography (CT) alone may not be sufficiently accurate to distinguish central lung cancer from obstructive atelectasis. Spectral CT can improve the soft-tissue resolution greatly. In this study, we evaluated the application value of double-layer spectral detector CT in differentiating central lung cancer from atelectasis.Methods: A total of 51 patients (37 males) with pathologically confirmed central lung cancer accompanied by atelectasis were enrolled. The rates of differentiation between tumors and atelectasis were retrospectively analyzed using conventional CT and three types of spectral images (40 keV virtual monoenergetic imaging, iodine density map, and their fusion image) of unenhanced scans as well as arterial and venous phases.Cochran's Q test and Friedman test were used to compare the differentiation rates and the maximal diameters of the tumors in each image.Results: Among the 51 cases, conventional CT, 40 keV monoenergetic, iodine density, and their fusion images of the venous phase were successful in differentiating tumors from atelectasis in 17 (33.33%), 35 (68.63%), 39 (76.47%), and 38 (74.51%) cases, respectively. The differentiation rates of the 40 keV monoenergetic, iodine density, and fusion images were significantly higher than those of conventional images (χ 2 =−0.35, −0.43, and −0.41, respectively, all P<0.001). There were no significant differences in the differentiation rates among the 40 keV monoenergetic, iodine density, and fusion images (χ 2 =−0.06, −0.08, 0.02, respectively, all P=1.00). The maximal tumor diameters in the four images did not significantly differ (χ 2 =3.61, P=0.31). Conventional and spectral images of unenhanced and arterial phases could not/barely identify the tumor borderlines.Conclusions: Venous-phase spectral images of double-layer spectral detector CT can differentiate most central lung cancers from atelectasis, and the maximal diameter measurement of the tumor is reliable. Double-layer spectral detector CT can accurately identify the borderlines of most central lung cancers through spectral images during routine CT examinations without requiring other imaging modalities.Therefore, this method has considerable clinical value for applications in tumor staging, efficacy evaluation, and radiotherapy.