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Objective: To examine the association of tag single nucleotide polymorphisms (tagSNPs) (rs1130409, rs1760944, rs2307486 and rs3136817) in APEX1 with the risk of severe radiation-induced pneumonitis (RP) after radiotherapy among Han Chinese patients with lung cancer. Methods: A total of 168 patients with lung cancer who were receiving radiotherapy were prospectively recruited. RP was evaluated according to the Radiation Therapy Oncology Group. A case-control study was performed. The case group included patients with RP grade of ≥3, while the control group comprised patients with RP grades <3. Four tagSNPs of APEX1 were genotyped in 126 patients with complete follow-up by multi-SNaP-shot® (Genesky Biotechnologies Inc., Shanghai, China) genotyping assays. Results were assessed by a logistic regression model for RP risk and Mantal-Cox log-rank test for the cumulative RP probability by the genotypes. Results: rs1130409 was associated with severe RP. GT genotype of rs1130409 was significantly higher in patients with RP than in those of the control group [68.8% vs 41.8%; p = 0.025; resulting odds ratio (OR), 5.98], Patients with lung cancer bearing the G allele had a 5.83-fold higher risk of RP than those with the wild TT genotype [OR = 5.83; 95% confidence interval (CI), 1.27-26.90; p = 0.024], and this was further confirmed by the binary regression adjusted by some confounding factors, including Karnofsky performance scale, concurrent chemotherapy-radiotherapy and lung volume receiving >30Gy (OR = 6.96; 95% CI, 1.36-35.77; p = 0.02). rs1130409 was also associated with the time to occurrence of severe RP (p = 0.04). Three-dimensional model APEX1 protein showed that rs!130409 is located in the random coil structure corresponding to the DNA repair function region. Advances in knowledge: rs1130409 of APEX1 can be a predictor of RP grades ≥3 among patients with lung cancer. [ABSTRACT FROM AUTHOR]

Objective: Optic neuritis (ON) is defined as an inflammation of the optic nerve and provides a useful model for studying the effects of inflammatory demyelination of white matter. The aim of this study was to assess the diffusion changes in both the optic nerve and optic radiation in patients with acute and chronic ON using diffusion tensor (DT) MRI. Methods: 33 patients with idiopathic demyelinating optic neuritis (IDON) and 33 gender- and age-matched healthy controls were examined with DT-MRI and with T1 and T2 weighted MRI. Results: Compared with controls, both first-episode and recurrent patients with IDON in the acute stage showed significantly increased radial diffusivity (λ˔) and decreased mean fractional anisotropy (FA) in the affected nerves. Reduced FA, increased λ˔, mean diffusivity (MD) and axial diffusivity (λ‖) were determined in patients with subacute IDON. We found no significant difference in the directional diffusivity of optic radiation in patients whose disease had lasted less than 1 year compared with healthy controls. However, significant changes in the FA and lH of the optic radiation were detected in patients with disease duration of more than 1 year. Conclusion: These results show the great potential and capacity of DT-MRI measures as useful biomarkers and indicators for the evaluation ofmyelin injury in the visual pathway. [ABSTRACT FROM AUTHOR]

Ectopic pituitary adenomas (EPAs) are rare lesions. The purpose of this study was to describe the CT and MRI features of sphenoid sinus EPAs. Eight patients with histology-proven EPAs in the sphenoid sinus, all of whom underwent CT and MRI, were reviewed retrospectively. The following imaging features were analysed: (i) size, (ii) margin, (iii) CT attenuation characteristics and (iv) MRI signal intensity. In addition, the involvement of adjacent structures and the time-intensity curve (TIC) of dynamic contrast-enhanced (DCE) MRI were analysed. All EPAs had well-defined margins and showed no relationship to the intrasellar pituitary gland. The mean size was 28 mm (range, 20-46 mm). On non-enhanced CT, the lesions appeared isodense to grey matter in 7 (88%) patients and hypodense in 1 (12%) patient. Only two patients underwent post-contrast CT, and they showed moderate enhancement. On T1 weighted images, EPAs appeared isointense in 6 (75%) patients and hypointense in 2 (25%). On T2 weighted images, the lesions appeared hyperintense in 2 (25%) patients and isointense in 6 (75%). EPAs showed mild to moderate heterogeneous contrast enhancement and exhibited a cribriform-like appearance. Two patients underwent DCE MRI; the TIC showed a rapidly enhancing and slow washout pattern. The following features were also seen: an empty sella, bone changes and involvement of the cavernous sinus (5 patients; 62.5%). In conclusion, a high index of suspicion for EPA and a familiarity with the imaging findings may help to diagnose this rare entity accurately. [ABSTRACT FROM AUTHOR]

Objective: To investigate the diagnostic performance of quantitative and semi-quantitative parameters derived from dynamic contrast-enhanced MRI (DCE-MRI) in differentiating sinonasal inverted papilloma (SIP) from SIP with coexisting malignant transformation into squamous cell carcinoma (MT-SIP)., Methods: This retrospective study included 122 patients with 88 SIP and 34 MT-SIP. Quantitative and semi-quantitative parameters derived from DCE-MRI were compared between SIP and MT-SIP. The multivariate logistic regression analysis was performed to identify independent indicators and construct regression model for distinguishing MT-SIP and SIP. Diagnostic performance of independent indicators and regression model were evaluated using receiver operating coefficient (ROC) analysis and compared using DeLong test., Results: There were significant differences in maximum slope of increase, contrast-enhancement ratio, bolus arrival time, volume of extravascular extracellular space (V e ), and rate constant (K ep ) between SIP and MT-SIP ( p < 0.05). There were no significant differences in initial area under the gadolinium curve ( p = 0.174) and volume transfer constant ( p = 0.105) between two groups. Multivariate analysis results showed that V e and K ep were identified as the independent indicators for differentiating MT-SIP from SIP ( p < 0.001). Areas under the ROC curves (AUCs) for predicting MT-SIP were 0.779 for V e and 0.766 for K ep . The AUC of the combination of V e and K ep was 0.831, yielding 83% specificity and 76.5% sensitivity., Conclusion: DCE-MRI can quantitatively differentiate between MT-SIP and SIP. The combination of V e and K ep yielded an optimal performance for discriminating SIP from its malignant mimics., Advances in Knowledge: DCE-MRI with quantitative and semi-quantitative parameters can provide valuable evidences for quantitatively identifying MT-SIP.

Objectives: To develop an MRI-based radiomics model to predict postlaminar optic nerve invasion (PLONI) in retinoblastoma (RB) and compare its predictive performance with subjective radiologists' assessment., Methods: We retrospectively enrolled 124 patients with pathologically proven RB (90 in training set and 34 in validation set) who had MRI scans before surgery. A radiomics model for predicting PLONI was developed by extracting quantitative imaging features from axial T2W images and contrast-enhanced T1W images in the training set. The Kruskal-Wallis test, least absolute shrinkage and selection operator regression, and recursive feature elimination were used for feature selection, where upon a radiomics model was built with a logistic regression (LR) classifier. The area under the curve (AUC) of the receiver operating characteristic (ROC) curve and the accuracy were assessed to evaluate the predictive performance in the training and validation set. The performance of the radiomics model was compared to radiologists' assessment by DeLong test., Results: The AUC of the radiomics model for the prediction of PLONI was 0.928 in the training set and 0.841 in the validation set. Radiomics model produced better sensitivity than radiologists' assessment (81.1% vs  43.2% in training set, 82.4vs 52.9% in validation set). In all 124 patients, the AUC of the radiomics model was 0.897, while that of radiologists' assessment was 0.674 ( p < 0.001, DeLong test)., Conclusion: MRI-based radiomics model to predict PLONI in RB patients was shown to be superior to visual assessment with improved sensitivity and AUC, and may serve as a potential tool to guide personalized treatment.