Hyperoxia-Induced ΔR1: MRI Biomarker of Histological Infarction in Acute Cerebral Stroke.

OBJECTIVE: To evaluate whether hyperoxia-induced ΔR1 (hyperO2ΔR1) can accurately identify histological infarction in an acute cerebral stroke model. MATERIALS AND METHODS: In 18 rats, MRI parameters, including hyperO2ΔR1, apparent diffusion coefficient (ADC), cerebral blood flow and volume, and 18F-fluorodeoxyglucose uptake on PET were measured 2.5, 4.5, and 6.5 hours after a 60-minutes occlusion of the right middle cerebral artery. Histological examination of the brain was performed immediately following the imaging studies. MRI and PET images were co-registered with digitized histological images. The ipsilateral hemisphere was divided into histological infarct (histological cell death), non-infarct ischemic (no cell death but ADC decrease), and non-ischemic (no cell death or ADC decrease) areas for comparisons of imaging parameters. The levels of hyperO2ΔR1 and ADC were measured voxel-wise from the infarct core to the non-ischemic region. The correlation between areas of hyperO2ΔR1-derived infarction and histological cell death was evaluated. RESULTS: HyperO2ΔR1 increased only in the infarct area (p ≤ 0.046) compared to the other areas. ADC decreased stepwise from non-ischemic to infarct areas (p = 0.002 at all time points). The other parameters did not show consistent differences among the three areas across the three time points. HyperO2ΔR1 sharply declined from the core to the border of the infarct areas, whereas there was no change within the non-infarct areas. A hyperO2ΔR1 value of 0.04 s-1 was considered the criterion to identify histological infarction. ADC increased gradually from the infarct core to the periphery, without a pronounced difference at the border between the infarct and non-infarct areas. Areas of hyperO2ΔR1 higher than 0.04 s-1 on MRI were strongly positively correlated with histological cell death (r = 0.862; p < 0.001). CONCLUSION: HyperO2ΔR1 may be used as an accurate and early (2.5 hours after onset) indicator of histological infarction in acute stroke.

Radiomics-based prediction model for outcomes of PD-1/PD-L1 immunotherapy in metastatic urothelial carcinoma.

OBJECTIVES: To evaluate the usefulness of a radiomics-based prediction model for predicting response and survival outcomes of patients with metastatic urothelial carcinoma treated with immunotherapy targeting programmed cell death 1 (PD-1) and its ligand (PD-L1). METHODS: Sixty-two patients who underwent immunotherapy were divided into training (n = 41) and validation sets (n = 21). A total of 224 measurable lesions were identified on contrast-enhanced CT. A radiomics signature was constructed with features selected using a least absolute shrinkage and selection operator algorithm in the training set. A radiomics-based model was built based on a radiomics signature consisting of five reliable RFs and the presence of visceral organ involvement using multivariate logistic regression. According to a cutoff determined on the training set, patients in the validation set were assigned to either high- or low-risk groups. Kaplan-Meier analysis was performed to compare progression-free and overall survival between high- and low-risk groups. RESULTS: For predicting objective response and disease control, the areas under the receiver operating characteristic curves of the radiomics-based model were 0.87 (95% CI, 0.65-0.97) and 0.88 (95% CI, 0.67-0.98) for the validation set, providing larger net benefit determined by decision curve analysis than without radiomics-based model. The high-risk group in the validation set showed shorter progression-free and overall survival than the low-risk group (log-rank p = 0.044 and p = 0.035). CONCLUSIONS: The radiomics-based model may predict the response and survival outcome in patients treated with PD-1/PD-L1 immunotherapy for metastatic urothelial carcinoma. This approach may provide important and decision tool for planning immunotherapy. KEY POINTS: • A radiomics-based model was built based on radiomics features and the presence of visceral organ involvement for prediction of outcomes in metastatic urothelial carcinoma treated with immunotherapy. • This prediction model demonstrated good prediction of treatment response and higher net benefit than no model in the independent validation set. • This radiomics-based model demonstrated significant associations with progression-free and overall survival between low-risk and high-risk groups.

Reliability of CT radiomic features reflecting tumour heterogeneity according to image quality and image processing parameters.

The reliability of radiomics features (RFs) is crucial for quantifying tumour heterogeneity. We assessed the influence of imaging, segmentation, and processing conditions (quantization range, bin number, signal-to-noise ratio [SNR], and unintended outliers) on RF measurement. Low SNR and unintended outliers increased the standard deviation and mean values of histograms to calculate the first-order RFs. Variations in imaging processing conditions significantly altered the shape of the probability distribution (centre of distribution, extent of dispersion, and segmentation of probability clusters) in second-order RF matrices (i.e. grey-level co-occurrence and grey-level run length), thereby eventually causing fluctuations in RF estimation. Inconsistent imaging and processing conditions decreased the number of reliably measured RFs in terms of individual RF values (intraclass correlation coefficient ≥0.75) and inter-lesion RF ratios (coefficient of variation <15%). No RF could be reliably estimated under inconsistent SNR and inclusion of outlier conditions. By contrast, with high SNR and no outliers, all first-order RFs, 11 (42%) grey-level co-occurrence RFs and five (42%) grey-level run length RFs showed acceptable reliability. Our study suggests that optimization of SNR, exclusion of outliers, and application of relevant quantization range and bin number should be performed to ensure the robustness of radiomics studies assessing tumor heterogeneity.

Spatiotemporal heterogeneity of tumor vasculature during tumor growth and antiangiogenic treatment: MRI assessment using permeability and blood volume parameters.

Tumor heterogeneity is an important concept when assessing intratumoral variety in vascular phenotypes and responses to antiangiogenic treatment. This study explored spatiotemporal heterogeneity of vascular alterations in C6 glioma mice during tumor growth and antiangiogenic treatment on serial MR examinations (days 0, 4, and 7 from initiation of vehicle or multireceptor tyrosine kinase inhibitor administration). Transvascular permeability (TP) was quantified on dynamic-contrast-enhanced MRI (DCE-MRI) using extravascular extracellular agent (Gd-DOTA); blood volume (BV) was estimated using intravascular T2 agent (SPION). With regard to region-dependent variability in vascular phenotypes, the control group demonstrated higher TP in the tumor center than in the periphery, and greater BV in the tumor periphery than in the center. This distribution pattern became more apparent with tumor growth. Antiangiogenic treatment effect was regionally heterogeneous: in the tumor center, treatment significantly suppressed the increase in TP and decrease in BV (ie, typical temporal change in the control group); in the tumor periphery, treatment-induced vascular alterations were insignificant and BV remained high. On histopathological examination, the control group showed greater CD31, VEGFR2, Ki67, and NG2 expression in the tumor periphery than in the center. After treatment, CD31 and Ki67 expression was significantly suppressed only in the tumor center, whereas VEGFR2 and α-caspase 3 expression was decreased and NG2 expression was increased in the entire tumor. These results demonstrate that MRI can reliably depict spatial heterogeneity in tumor vascular phenotypes and antiangiogenic treatment effects. Preserved angiogenic activity (high BV on MRI and high CD31) and proliferation (high Ki67) in the tumor periphery after treatment may provide insights into the mechanism of tumor resistance to antiangiogenic treatment.