CT in the Differentiation of Gliomas from Brain Metastases: The Radiomics Analysis of the Peritumoral Zone

Due to their similar imaging features, high-grade gliomas (HGGs) and solitary brain metastases (BMs) can be easily misclassified. The peritumoral zone (PZ) of HGGs develops neoplastic cell infiltration, while in BMs the PZ contains pure vasogenic edema. As the two PZs cannot be differentiated macroscopically, this study investigated whether computed tomography (CT)-based texture analysis (TA) of the PZ can reflect the histological difference between the two entities. Thirty-six patients with solitary brain tumors (HGGs, n = 17; BMs, n = 19) that underwent CT examinations were retrospectively included in this pilot study. TA of the PZ was analyzed using dedicated software (MaZda version 5). Univariate, multivariate, and receiver operating characteristics analyses were used to identify the best-suited parameters for distinguishing between the two groups. Seven texture parameters were able to differentiate between HGGs and BMs with variable sensitivity (56.67–96.67%) and specificity (69.23–100%) rates. Their combined ability successfully identified HGGs with 77.9–99.2% sensitivity and 75.3–100% specificity. In conclusion, the CT-based TA can be a useful tool for differentiating between primary and secondary malignancies. The TA features indicate a more heterogenous content of the HGGs’ PZ, possibly due to the local infiltration of neoplastic cells.

Quantitative CT imaging features for COVID-19 evaluation: The ability to differentiate COVID-19 from non- COVID-19 (highly suspected) pneumonia patients during the epidemic period

Objectives COVID-19 and Non-Covid-19 (NC) Pneumonia encountered high CT imaging overlaps during pandemic. The study aims to evaluate the effectiveness of image-based quantitative CT features in discriminating COVID-19 from NC Pneumonia. Materials and methods 145 patients with highly suspected COVID-19 were retrospectively enrolled from four centers in Sichuan Province during January 23 to March 23, 2020. 88 cases were confirmed as COVID-19, and 57 patients were NC. The dataset was randomly divided by 3:2 into training and testing sets. The quantitative CT radiomics features were extracted and screened sequentially by correlation analysis, Mann-Whitney U test, the least absolute shrinkage and selection operator (LASSO) logistic regression (LR) and backward stepwise LR with minimum AIC methods. The selected features were used to construct the LR model for differentiating COVID-19 from NC. Meanwhile, the differentiation performance of traditional quantitative CT features such as lesion volume ratio, ground glass opacity (GGO) or consolidation volume ratio were also considered and compared with Radiomics-based method. The receiver operating characteristic curve (ROC) analysis were conducted to evaluate the predicting performance. Results Compared with traditional CT quantitative features, radiomics features performed best with the highest Area Under Curve (AUC), sensitivity, specificity and accuracy in the training (0.994, 0.942, 1.0 and 0.965) and testing sets (0.977, 0.944, 0.870, 0.915) (Delong test, P < 0.001). Among CT volume-ratio based models using lesion or GGO component ratio, the model combining CT lesion score and component ratio performed better than others, with the AUC, sensitivity, specificity and accuracy of 0.84, 0.692, 0.853, 0.756 in the training set and 0.779, 0.667, 0.826, 0.729 in the testing set. The significant difference of the most selected wavelet transformed radiomics features between COVID-19 and NC might well reflect the CT signs. Conclusions The differentiation between COVID-19 and NC could be well improved by using radiomics features, compared with traditional CT quantitative values.

Relationship Between Clustered Ring Nonmass Enhancement of Breast MRI and Prognostic Molecular Biomarkers in Breast Cancer

BackgroundClustered ring enhancement (CRE) of breast MRI is a lexicon of nonmass enhancement (NME) representing tendency of breast cancer and molecular biomarkers are predictors of response to therapy. The purpose of this study was to retrospectively determine the relationship between CRE NME and prognostic molecular biomarkers in breast cancer.MethodsRetrospective analysis of 58 breast lesions in 56 female patients between July 2013 and December 2018 was performed in our institution. Cases with MRI reporting NME in the text were collected via searching the report database. The patterns of enhancement including CRE on breast MRI were reviewed by a radiologist blinded to pathology report. The pathological results and expression of molecular biomarkers were collected. Univariate analysis was applied to evaluate the association between MRI NME imaging features, pathological and IHC stain findings.Results58 Breast lesions were pathologically proven breast carcinoma, and 31 lesions with CRE and 27 lesions without CRE on breast MRI. The expression of estrogen receptor (ER) (P=0.017) and progesterone receptor (PR) (P=0.017) was significantly lower in lesions with CRE compared with those without CRE. The expression of Ki-67 (≥ 25%) was significantly higher in lesions with CRE(P=0.046). The lesions with CRE have a lower expression ratio of ER (50.71 ± 45.39% vs. 74.26 ± 33.59%, p= 0.028).ConclusionOur results indicated that lesions with CRE may possess different features from those without CRE in molecular expression. They tend to bear a more aggressive biological behavior.

Impaired Topographic Organization in Patients With Idiopathic Blepharospasm

Background: Idiopathic blepharospasm (BSP) is a common adult-onset focal dystonia. Neuroimaging technology can be used to visualize functional and microstructural changes of the whole brain.Method: We used resting-state functional MRI (rs-fMRI) and graph theoretical analysis to explore the functional connectome in patients with BSP. Altogether 20 patients with BSP and 20 age- and gender-matched healthy controls (HCs) were included in the study. Measures of network topology were calculated, such as small-world parameters (clustering coefficient [Cp], the shortest path length [Lp]), network efficiency parameters (global efficiency [Eglob], local efficiency [Eloc]), and the nodal parameter (nodal efficiency [Enod]). In addition, the least absolute shrinkage and selection operator (LASSO) regression was adopted to determine the most critical imaging features, and the classification model using critical imaging features was constructed.Results: Compared with HCs, the BSP group showed significantly decreased Eloc. Imaging features of nodal centrality (Enod) were entered into the LASSO method, and the classification model was constructed with nine imaging nodes. The area under the curve (AUC) was 0.995 (95% CI: 0.973–1.000), and the sensitivity and specificity were 95% and 100%, respectively. Specifically, four imaging nodes within the sensorimotor network (SMN), cerebellum, and default mode network (DMN) held the prominent information. Compared with HCs, the BSP group showed significantly increased Enod in the postcentral region within the SMN, decreased Enod in the precentral region within the SMN, increased Enod in the medial cerebellum, and increased Enod in the precuneus within the DMN.Conclusion: The network model in BSP showed reduced local connectivity. Baseline connectomic measures derived from rs-fMRI data may be capable of identifying patients with BSP, and regions from the SMN, cerebellum, and DMN may provide key insights into the underlying pathophysiology of BSP.

Rhino Orbital Cerebral Mucormycosis in settings of Covid-19 infection: A Case Series of Thirteen Patients

Background Rhino-Orbital-Cerebral Mucormycosis (ROCM) is an important infectious disease encountered in huge number in this recent post-covid 19 era. An alteration in defence immune system during covid-19 illness, in the presence of uncontrolled hyperglycaemia has led to the new epidemic of ROCM especially in developing nations like India. Method This case series of thirteen patients illustrates the various clinical presentation, laboratorical parameters, imaging features and outcome of patients of ROCM admitted in a tertiary care hospital in Northern India. Result In our case series, a total of 13 newly diagnosed cases of Rhino-Orbital-Cerebral Mucormycosis were studied. History of covid-19 illness was observed in 7 cases (53.8%), use of steroid during Covid-19 illness was seen in 5 cases (38.5%), oxygen therapy was given in 4 cases (30.8%). Co-morbid state in the form of diabetes mellitus was present in 12 cases (92.3%) with mean duration 16.69 months with an important finding of 6 cases (46.2%) having new-onset diabetes; hypertension in present in 3 cases (23.1%). Magnetic resonance imaging of paranasal sinuses showed involvement of multiple sinuses in all the 13 cases(100%), including maxillary and ethmoidal sinuses, with frontal in 12 cases (92.3%), sphenoidal in 11 cases (84.6%), symmetric in 9 cases (69.2%), mastoiditis in 4 cases (30.8%), maxillary space involvement in 4 cases (30.8%), palatal involvement in 1 case (7.7%). Multi-speciality approach treatment was given in the liposomal amphotericin B therapy in all the patients along with thorough endo-nasal debridement done in all cases, transcutaneous retrobulbar amphotericin B in 6 cases (46.2%) with exenteration done in 7 patients (53.9%). At 3 months of follow-up, there was substantial clinical improvement in all the cases. Conclusion There should be definite emphasis on high suspicion of mucor clinically for early diagnosis and aggressive management at initial state of diagnosis for better outcome. The need for sustained proper glycemic control during covid 19 era along with judicious use of steroid and public awareness for early symptoms and manifestations of mucor can curb the magnitude of such potentially opportunistic epidemic to a substantial rate. The longer the infection remains undetected, the greater the devastation ROCM can impose, of which blindness is an important hazard.