ASPECTS-based net water uptake predicts poor reperfusion and poor clinical outcomes in patients with ischemic stroke.

OBJECTIVE: To investigate the value of automated Alberta Stroke Program Early CT Score (ASPECTS)-based net water uptake (NWU) to predict tissue-level reperfusion status and 90-day functional outcomes in acute ischemic stroke (AIS) patients after reperfusion therapy. METHODS: One hundred and twelve patients with AIS who received reperfusion therapy were enrolled. ASPECTS-NWU was calculated from admission CT (NWUadmission) and follow-up CT (NWUFCT), and the difference (ΔNWU) was calculated. Tissue-level reperfusion status was evaluated via follow-up arterial spin labeling imaging. The relationship between ASPECTS-NWU and tissue-level reperfusion was evaluated. Predictors of 90-day unfavorable outcomes (modified Rankin Scale score > 2) were assessed by multivariate logistic regression analysis and receiver operating characteristic (ROC) curves. RESULTS: Poor reperfusion was observed in 40 patients (35.7%) after therapy. Those patients had significantly elevated NWUFCT (median, 14.15% vs. 8.08%, p = 0.018) and higher ΔNWU (median, 4.12% vs. -2.03%, p < 0.001), compared to patients with good reperfusion. High ΔNWU was a significant marker of poor reperfusion despite successful recanalization. National Institutes of Health Stroke Scale score at admission (odds ratio [OR], 1.11; 95% confidence interval [CI] 1.03-1.20, p = 0.007) and ΔNWU (OR, 1.07; 95% CI 1.02-1.13, p = 0.008) were independently associated with unfavorable outcomes. An outcome prediction model including both parameters yields an area under the curve of 0.762 (sensitivity 70.3%, specificity, 84.2%). CONCLUSIONS: Elevated NWUFCT and higher ΔNWU were associated with poor tissue-level reperfusion after therapy. Higher ΔNWU was an independent predictor of poor reperfusion and unfavorable neurological outcomes despite successful recanalization. KEY POINTS: • ASPECTS-NWU may provide pathophysiological information about tissue-level reperfusion status and offer prognostic benefits for patients with AIS after reperfusion therapy. • Elevated NWUFCT and higher ΔNWU were correlated with poor tissue-level reperfusion after therapy. • A higher ΔNWU is an independent predictor of poor reperfusion and 90-day unfavorable outcomes despite successful recanalization.

Effect of Hashimoto's thyroiditis on the dual-energy CT quantitative parameters and performance in diagnosing metastatic cervical lymph nodes in patients with papillary thyroid cancer.

BACKGROUND: To evaluate the effect of Hashimoto's thyroiditis (HT) on dual-energy computed tomography (DECT) quantitative parameters of cervical lymph nodes (LNs) in patients with papillary thyroid cancer (PTC), and its effect on the diagnostic performance and threshold of DECT in preoperatively identifying metastatic cervical LNs. METHODS: A total of 479 LNs from 233 PTC patients were classified into four groups: HT+/LN+, HT+/LN-, HT-/LN + and HT-/LN - group. DECT quantitative parameters including iodine concentration (IC), normalized IC (NIC), effective atomic number (Zeff), and slope of the spectral Hounsfield unit curve (λHU) in the arterial phase (AP) and venous phase were compared. Receiver operating characteristic curve analyses were performed to evaluate DECT parameters' diagnostic performance in differentiating metastatic from nonmetastatic LNs in the HT - and HT + groups. RESULTS: The HT+/LN + group exhibited lower values of DECT parameters than the HT-/LN + group (all p < 0.05). Conversely, the HT+/LN - group exhibited higher values of DECT parameters than the HT-/LN - group (all p < 0.05). In the HT + group, if an AP-IC of 1.850 mg/mL was used as the threshold value, then the optimal diagnostic performance (area under the curve, 0.757; sensitivity, 69.4%; specificity, 71.0%) could be obtained. The optimal threshold value of AP-IC in the HT - group was 2.050 mg/mL. In contrast, in the HT - group, AP-NIC demonstrated the highest area under the curve of 0.988, when an optimal threshold of 0.243 was used. The optimal threshold value of AP-NIC was 0.188 in the HT + group. CONCLUSIONS: HT affected DECT quantitative parameters of LNs and subsequent the diagnostic thresholds. When using DECT to diagnose metastatic LNs in patients with PTC, whether HT is coexistent should be clarified considering the different diagnostic thresholds.

The incremental value of CCTA-derived myocardial radiomics signature for ischemia diagnosis with reference to CT myocardial perfusion imaging.

OBJECTIVES: To explore the incremental value of myocardial radiomics signature derived from static coronary computed tomography angiography (CCTA) for identifying myocardial ischemia based on stress dynamic CT myocardial perfusion imaging (CT-MPI). METHODS: Patients who underwent CT-MPI and CCTA were retrospectively enrolled from two independent institutions, one used as training and the other as testing. Based on CT-MPI, coronary artery supplying area with relative myocardial blood flow (rMBF) value <0.8 was considered ischemia. Conventional imaging features of target plaques which caused the most severe narrowing of the vessel included area stenosis, lesion length (LL), total plaque burden, calcification burden, non-calcification burden, high-risk plaque (HRP) score, and CT fractional flow reserve (CT-FFR). Myocardial radiomics features were extracted at three vascular supply areas from CCTA images. The optimized radiomics signature was added to the conventional CCTA features to build the combined model (radiomics + conventional). RESULTS: There were 168 vessels from 56 patients enrolled in the training set, and the testing set consisted of 135 vessels from 45 patients. From either cohort, HRP score, LL, stenosis ≥50% and CT-FFR ≤0.80 were associated with ischemia. The optimal myocardial radiomics signature consisted of nine features. The detection of ischemia using the combined model was significantly improved compared with conventional model in both training and testing set (AUC 0.789 vs 0.608, p < 0.001; 0.726 vs 0.637, p = 0.045). CONCLUSIONS: Myocardial radiomics signature extracted from static CCTA combining with conventional features could provide incremental value to diagnose specific ischemia. ADVANCES IN KNOWLEDGE: Myocardial radiomics signature extracted from CCTA may capture myocardial characteristics and provide incremental value to detect specific ischemia when combined with conventional features.

Predicting Response to Systemic Chemotherapy for Advanced Gastric Cancer Using Pre-Treatment Dual-Energy CT Radiomics: A Pilot Study.

OBJECTIVE: To build and assess a pre-treatment dual-energy CT-based clinical-radiomics nomogram for the individualized prediction of clinical response to systemic chemotherapy in advanced gastric cancer (AGC). METHODS: A total of 69 pathologically confirmed AGC patients who underwent dual-energy CT before systemic chemotherapy were enrolled from two centers in this retrospective study. Treatment response was determined with follow-up CT according to the RECIST standard. Quantitative radiomics metrics of the primary lesion were extracted from three sets of monochromatic images (40, 70, and 100 keV) at venous phase. Univariate analysis and least absolute shrinkage and selection operator (LASSO) were used to select the most relevant radiomics features. Multivariable logistic regression was performed to establish a clinical model, three monochromatic radiomics models, and a combined multi-energy model. ROC analysis and DeLong test were used to evaluate and compare the predictive performance among models. A clinical-radiomics nomogram was developed; moreover, its discrimination, calibration, and clinical usefulness were assessed. RESULT: Among the included patients, 24 responded to the systemic chemotherapy. Clinical stage and the iodine concentration (IC) of the tumor were significant clinical predictors of chemotherapy response (all p < 0.05). The multi-energy radiomics model showed a higher predictive capability (AUC = 0.914) than two monochromatic radiomics models and the clinical model (AUC: 40 keV = 0.747, 70 keV = 0.793, clinical = 0.775); however, the predictive accuracy of the 100-keV model (AUC: 0.881) was not statistically different (p = 0.221). The clinical-radiomics nomogram integrating the multi-energy radiomics signature with IC value and clinical stage showed good calibration and discrimination with an AUC of 0.934. Decision curve analysis proved the clinical usefulness of the nomogram and multi-energy radiomics model. CONCLUSION: The pre-treatment DECT-based clinical-radiomics nomogram showed good performance in predicting clinical response to systemic chemotherapy in AGC, which may contribute to clinical decision-making and improving patient survival.