Pituicytoma: Four cases with unusual imaging features and a literature review.

OBJECTIVE: Pituicytomas (PTs) are rare and benign neoplasms. The variable imaging and clinical features of PTs, which overlap with other sellar pathologies, can make preoperative diagnosis challenging. In the interest of a more comprehensive understanding of the diagnostic aspects of PTs, it is necessary to report and synthesize the variable imaging and clinical features of PTs. METHODS: We retrospectively included and analysed four pathologically proven PTs with unusual imaging and/or clinical features. Additionally, we reviewed the literature on PT between 2007 and 2019 in the PubMed database to provide context for the individual patient data described herein. RESULTS: Our series included three female and one male adult patient (mean age: 44.75, age range: 20-56 y). Based on clinical symptoms, we noticed that case 1 had Cushing's syndrome, case 2 had increased prolactin, case 3 had extremity enlargement but with a normal level of human growth factor, and case 4 presented with tinnitus and dizziness. On radiograph, inconsistent with the main imaging findings of PTs in the literature, there was one case in the pituitary anterior lobe, three cases with hypointensity on T2-weighted images, two patients with reduced homogeneous contrast enhancement, and one case demonstrating invasion potential. In addition, one of our patients underwent PET-CT examination, and the lesion had a slight increase in glucose uptake and no significant decrease in ammonia uptake. Postoperative follow-up monitoring revealed no tumour recurrence. CONCLUSION: Our cases highlight the unusual imaging manifestations of PTs. Recognizing these imaging features plays an important role in the preoperative diagnosis, treatment, and postsurgery monitoring of PTs.

Diffusion kurtosis imaging in evaluating gliomas: different region of interest selection methods on time efficiency, measurement repeatability, and diagnostic ability.

OBJECTIVES: Comparing the diagnostic efficacy of diffusion kurtosis imaging (DKI) derived from different region of interest (ROI) methods in tumor parenchyma for grading and predicting IDH-1 mutation and 1p19q co-deletion status of glioma patients and correlating with their survival data. METHODS: Sixty-six patients (29 females; median age, 45 years) with pathologically proved gliomas (low-grade gliomas, 36; high-grade gliomas, 30) were prospectively included, and their clinical data were collected. All patients underwent DKI examination. DKI maps of each metric were derived. Three groups of ROIs (ten spots, ROI-10s; three biggest tumor slices, ROI-3s; and whole-tumor parenchyma, ROI-whole) were manually drawn by two independent radiologists. The interobserver consistency, time spent, diagnostic efficacy, and survival analysis of DKI metrics based on these three ROI methods were analyzed. RESULTS: The intraexaminer reliability for all parameters among these three ROI methods was good, and the time spent on ROI-10s was significantly less than that of the other two methods (p < 0.001). DKI based on ROI-10s demonstrated a slightly better diagnostic value than the other two ROI methods for grading and predicting the IDH-1 mutation status of glioma, whereas DKI metrics derived from ROI-10s performed much better than those of the ROI-3s and ROI-whole in identifying 1p19q co-deletion. In survival analysis, the model based on ROI-10s that included patient age and mean diffusivity showed the highest prediction value (C-index, 0.81). CONCLUSIONS: Among the three ROI methods, the ROI-10s method had the least time spent and the best diagnostic value for a comprehensive evaluation of glioma. It is an effective way to process DKI data and has important application value in the clinical evaluation of glioma. KEY POINTS: • The intraexaminer reliability for all DKI parameters among different ROI methods was good, and the time spent on ROI-10 spots was significantly less than the other two ROI methods. • DKI metrics derived from ROI-10 spots performed the best in ROI selection methods (ROI-10s, ten-spot ROIs; ROI-3s, three biggest tumor slices ROI; and ROI-whole, whole-tumor parenchyma ROI) for a comprehensive evaluation of glioma. • The ROI-10 spots method is an effective way to process DKI data and has important application value in the clinical evaluation of glioma.