MR Imaging Characteristics and ADC Histogram Metrics for Differentiating Molecular Subgroups of Pediatric Low-Grade Gliomas.

BACKGROUND AND PURPOSE: BRAF and type 1 neurofibromatosis status are distinctive features in pediatric low-grade gliomas with prognostic and therapeutic implications. We hypothesized that DWI metrics obtained through volumetric ADC histogram analyses of pediatric low-grade gliomas at baseline would enable early detection of BRAF and type 1 neurofibromatosis status. MATERIALS AND METHODS: We retrospectively evaluated 40 pediatric patients with histologically proved pilocytic astrocytoma (n = 33), ganglioglioma (n = 4), pleomorphic xanthoastrocytoma (n = 2), and diffuse astrocytoma grade 2 (n = 1). Apart from 1 patient with type 1 neurofibromatosis who had a biopsy, 11 patients with type 1 neurofibromatosis underwent conventional MR imaging to diagnose a low-grade tumor without a biopsy. BRAF molecular analysis was performed for patients without type 1 neurofibromatosis. Eleven patients presented with BRAF V600E-mutant, 20 had BRAF-KIAA rearrangement, and 8 had BRAF wild-type tumors. Imaging studies were reviewed for location, margins, hemorrhage or calcifications, cystic components, and contrast enhancement. Histogram analysis of tumoral diffusivity was performed. RESULTS: Diffusion histogram metrics (mean, median, and 10th and 90th percentiles) but not kurtosis or skewness were different among pediatric low-grade glioma subgroups (P < .05). Diffusivity was lowest in BRAF V600E-mutant tumors (the 10th percentile reached an area under the curve of 0.9 on receiver operating characteristic analysis). There were significant differences between evaluated pediatric low-grade glioma margins and cystic components (P = .03 and P = .001, respectively). Well-defined margins were characteristic of BRAF-KIAA or wild-type BRAF rather than BRAF V600E-mutant or type 1 neurofibromatosis tumors. None of the type 1 neurofibromatosis tumors showed a cystic component. CONCLUSIONS: Imaging features of pediatric low-grade gliomas, including quantitative diffusion metrics, may assist in predicting BRAF and type 1 neurofibromatosis status, suggesting a radiologic-genetic correlation, and might enable early genetic signature characterization.

A deep-learning method for the denoising of ultra-low dose chest CT in coronary artery calcium score evaluation.

AIM: To evaluate a novel deep-learning denoising method for ultra-low dose CT (ULDCT) in the assessment of coronary artery calcium score (CACS). MATERIALS AND METHODS: Sixty adult patients who underwent two unenhanced chest CT examinations, a normal dose CT (NDCT) and an ULDCT, were enrolled prospectively between September 2017 to December 201. A special training set was created to learn the characteristics of the real noise affecting the ULDCT implementing a fully convolutional neural network with batch normalisation. Subsequently, the 60 ULDCTs of the evaluation set were denoised. Two blinded radiologists assessed the NDCT, ULDCT, and denoised-ULDCT (DULDCT), assigning a CACS and categorised each scan as having a score above or below 100 and presence of calcifications (score 0 versus >0). Statistical analysis was used to evaluate the agreement between the readers and differences in CACSs between each imaging method. RESULTS: After excluding one patient, the cohort included 59 patients (median age 67 years, 58% men). The ULDCT median effective radiation dose (ERD) was 0.172 mSv, which was 2.8% of the NDCT median ERD. Denoising improved the signal-to-noise ratio by 27.7% (p<0.001). Interobserver agreement was almost perfect between readers (intraclass correlation coefficient >0.993). CACSs were lower for ULDCT and DULDCT as compared to the NDCT (p ≤ 0.001). In differentiating between the presence and absence of coronary artery calcifications, DULDCT showed greater accuracy (98-100%) and positive likelihood ratio (14.29->99) compared to ULDCT (92% and 2.78, respectively). CONCLUSION: DULCT significantly reduced the image noise and better identified patients with no coronary artery calcifications than native ULDCT.

Neuroimaging Findings in Children with Constitutional Mismatch Repair Deficiency Syndrome.

BACKGROUND AND PURPOSE: Constitutional mismatch repair deficiency is a hereditary childhood cancer predisposition syndrome characterized by brain tumors and colorectal and hematologic malignancies. Our objective was to describe the neuroimaging findings in patients with constitutional mismatch repair deficiency. MATERIALS AND METHODS: This retrospective study included 14 children with genetically confirmed constitutional mismatch repair deficiency who were referred to 2 tertiary pediatric oncology centers. RESULTS: Fourteen patients from 11 different families had diagnosed constitutional mismatch repair deficiency. The mean age at presentation was 9.3 years (range, 5-14 years). The most common clinical presentation was brain malignancy, diagnosed in 13 of the 14 patients. The most common brain tumors were glioblastoma (n = 7 patients), anaplastic astrocytoma (n = 3 patients), and diffuse astrocytoma (n = 3 patients). Nonspecific subcortical white matter T2 hyperintensities were noted in 10 patients (71%). Subcortical hyperintensities transformed into overt brain tumors on follow-up imaging in 3 patients. Additional non-neoplastic brain MR imaging findings included developmental venous anomalies in 12 patients (85%) and nontherapy-induced cavernous hemangiomas in 3 patients (21%). CONCLUSIONS: On brain MR imaging, these patients have both highly characteristic intra-axial tumors (typically multifocal high-grade gliomas) and nonspecific findings, some of which might represent early stages of neoplastic transformation. The incidence of developmental venous anomalies is high in these patients for unclear reasons. Awareness of these imaging findings, especially in combination, is important to raise the suspicion of constitutional mismatch repair deficiency in routine diagnostic imaging evaluation or surveillance imaging studies of asymptomatic carriers because early identification of the phenotypic "gestalt" might improve outcomes.

CT imaging features of symptomatic and asymptomatic floating aortic thrombus.

AIM: To present the computed tomography (CT) imaging features of floating aortic thrombus with emphasis on clinical and radiographic predictors for systemic shower emboli. MATERIALS AND METHODS: A retrospective computerised search for patients with protruding thoracic aortic thrombus on CT was conducted. Clinical and demographic characteristics were retrieved from medical files. Patients were divided into two groups: symptomatic and asymptomatic, based on the presence or absence of documented systemic emboli at the time of diagnosis or during follow-up. CT imaging features were analysed: location and extent of systemic emboli, presence or absence of thrombus insertion calcification, percentage of thrombus circumference that is attached to the aortic wall and thrombus volume. Clinical and demographic variables and CT imaging features were analysed as potentially associated with symptomatic emboli. RESULTS: The symptomatic group included 6/15 (40%) patients and the asymptomatic group included 9/15 (60%) patients. Patients in the symptomatic group were significantly younger (symptomatic: 53.3±11.7 years, asymptomatic: 76.9±8.4 years, p=0.003). All the symptomatic patients were women (100%), while 2/9 (22.2%) of the asymptomatic patients were women, (p=0.007). A non-calcified insertion site was more frequent in the symptomatic group (symptomatic 4/6 [66.7%] versus asymptomatic group 1/9 [11.1%], p=0.011). The percentage of thrombus circumference attached to the aortic wall was significantly smaller in symptomatic patients (symptomatic: 31.8±8.4%, asymptomatic: 43.7±5%, p=0.003). CONCLUSION: The imaging features of symptomatic floating thrombus include a narrow base of attachment and lack of insertion calcification. Free-floating thrombus should be actively sought and diagnosed or excluded when performing CT andiography for emboli.