Radiomics Analysis of Pericoronary Adipose Tissue From Baseline Coronary Computed Tomography Angiography Enables Prediction of Coronary Plaque Progression.

PURPOSE: The relationship between plaque progression and pericoronary adipose tissue (PCAT) radiomics has not been comprehensively evaluated. We aim to predict plaque progression with PCAT radiomics features and evaluate their incremental value over quantitative plaque characteristics. PATIENTS AND METHODS: Between January 2009 and December 2020, 500 patients with suspected or known coronary artery disease who underwent serial coronary computed tomography angiography (CCTA) ≥2 years apart were retrospectively analyzed and randomly stratified into a training and testing data set with a ratio of 7:3. Plaque progression was defined with annual change in plaque burden exceeding the median value in the entire cohort. Quantitative plaque characteristics and PCAT radiomics features were extracted from baseline CCTA. Then we built 3 models including quantitative plaque characteristics (model 1), PCAT radiomics features (model 2), and the combined model (model 3) to compare the prediction performance evaluated by area under the curve. RESULTS: The quantitative plaque characteristics of the training set showed the values of noncalcified plaque volume (NCPV), fibrous plaque volume, lesion length, and PCAT attenuation were larger in the plaque progression group than in the nonprogression group ( P < 0.05 for all). In multivariable logistic analysis, NCPV and PCAT attenuation were independent predictors of coronary plaque progression. PCAT radiomics exhibited significantly superior prediction over quantitative plaque characteristics both in the training (area under the curve: 0.814 vs 0.615, P < 0.001) and testing (0.736 vs 0.594, P = 0.007) data sets. CONCLUSIONS: NCPV and PCAT attenuation were independent predictors of coronary plaque progression. PCAT radiomics derived from baseline CCTA achieved significantly better prediction than quantitative plaque characteristics.

The Relationship Between Cardiac CT-based Left Atrial Structure and Epicardial Adipose Tissue and Postablation Atrial Fibrillation Recurrence Within 2 Years.

PURPOSE: The aim of this study was to explore the association of cardiac CT-based left atrium (LA) structural and functional parameters and left atrial epicardial adipose tissue (LA-EAT) parameters with postablation atrial fibrillation (AF) recurrence within 2 years. MATERIALS AND METHODS: Contrast-enhanced cardiac CT images of 286 consecutive AF patients (median age: 65 y; 97 females) who underwent initial ablation between June 2018 and June 2020 were retrospectively analyzed. Structural and functional parameters of LA, including maximum and minimum volume and ejection fraction of LA and left atrial appendage (LAA), and LA-EAT volume, were measured. The body surface area indexed maximum and minimum volume of LA (LAVImax, LAVImin) and LAA (LAAVImax, LAAVImin), and LA-EAT volume index (LA-EATVI) were calculated. Independent predictors of AF recurrence were determined using Cox regression analysis. The clinical predictors were added to the imaging predictors to build a combined model (clinical+imaging). The predictive performance of the clinical, imaging, and combined models was assessed using the area under the receiver operating characteristics curve (AUC). RESULTS: A total of 108 (37.8%) patients recurred AF within 2 years after ablation at a median follow-up of 24 months (IQR=11, 32). LA and LAA size and LA-EAT volume were significantly increased in patients with AF recurrence (P<0.05). After the multivariable regression analysis, LA-EATVI, LAAVImax, female sex, AF duration, and stroke history were independent predictors for AF recurrence. The combined model exhibited superior predictive performance compare to the clinical model (AUC=0.712 vs. 0.641, P=0.023) and the imaging model (AUC=0.712 vs. 0.663, P=0.018). CONCLUSION: Cardiac CT-based LA-EATVI and LAAVImax are independent predictors for postablation AF recurrence within 2 years and may provide a complementary value for AF recurrence risk assessment.

Neurological prognosis in surgically treated acute aortic dissection with brain computed tomography perfusion.

OBJECTIVES: The aim of this study was to explore the prognostic value of brain computed tomography perfusion (CTP) for postoperative new stroke in acute type A aortic dissection (ATAAD) patients. METHODS: Patients with ATAAD and suspected cerebral malperfusion who underwent brain CTP and surgical repair were retrospectively analysed. Brain perfusion was quantified mainly with the averaged cerebral blood flow. Significant clinical and imaging findings were identified through univariable and multivariable regression analysis. Furthermore, the added prognostic benefit of perfusion parameters was confirmed with the receiver operating characteristic curves in the entire cohort and subgroup analysis. RESULTS: The incidence of postoperative new stroke was 30.8% (44/143). The independent adjusted predictors of postoperative new stroke included an impaired averaged cerebral blood flow (ml/100 ml/min) (odds ratio: 0.889; P < 0.001), severe stenosis (odds ratio: 5.218; P = 0.011) or occlusion (odds ratio: 14.697; P = 0.048) of the true lumen in common carotid artery (CCA), hypotension on admission (odds ratio: 9.644; P = 0.016) and a longer surgery time (odds ratio: 1.593; P = 0.021). The area under the receiver operating characteristic curves significantly improved after adding perfusion parameters to clinical and computed tomography angiography characteristics (P = 0.048). This benefit was more pronounced in patients with severe stenosis or occlusion in CCA true lumen (P = 0.004). CONCLUSIONS: Brain CTP could be a useful prognostic tool for surgically treated ATAAD patients and especially beneficial in patients with severe stenosis or occlusion of the CCA true lumen.

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.

Prognostic value of coronary CT angiography and CT myocardial perfusion imaging among patients with and without Diabetes.

OBJECTIVES: Whether stress CT myocardial perfusion imaging (CT-MPI) improves risk assessment in patients with diabetes mellitus (DM) remains unexplored. We aimed to evaluate the prognostic value of coronary CT angiography (CCTA) and stress CT-MPI in suspected coronary artery disease (CAD) patients with and without DM. METHODS: A total of 334 patients with suspected CAD who underwent CCTA and stress CT-MPI from May 2020 to July 2021 were retrospectively analyzed. The endpoint was major adverse cardiovascular events (MACEs). Multivariable Cox regression analysis was used to evaluate the risk factors for MACEs, including clinical risk factors, CCTA characteristics and CT-MPI characteristics. RESULTS: After a median follow-up of 21 months,15 patients of the DM group and 16 patients of the non-DM group experienced MACEs. Multivariate Cox stepwise regression analysis showed that abnormal perfusion myocardial segments ratio was associated with MACEs after adjusting for clinical risk factors and CCTA characteristics in all patients (HR:1.023, p < 0.001), DM group (HR:1.024, p = 0.008) and non-DM group (HR:1.028, p = 0.003). By adding CT-MPI characteristics to CCTA characteristics and clinical risk factors, the global chi-square for predicting MACEs increased from 62.24 to 78.84 in all patients (p < 0.001), from 19.18 to 27.30 in DM group (p = 0.004) and from 39.51 to 48.65 in non-DM group (p = 0.003); the increment of C-index in all patients, DM group and non-DM group were 0.018, 0.054 and 0.019, respectively. CONCLUSION: In all patients and those with and without DM, CT-MPI has incremental prognostic value over clinical risk factors alone or combined with CCTA characteristics in predicting MACEs.

Predicting coronary plaque progression with conventional plaque parameters and radiomics features derived from coronary CT angiography.

OBJECTIVES: To determine the value of combining conventional plaque parameters and radiomics features derived from coronary computed tomography angiography (CCTA) for predicting coronary plaque progression. MATERIALS AND METHODS: Clinical data and CCTA images of 400 patients who underwent at least two CCTA examinations between January 2009 and August 2020 were analyzed retrospectively. Diameter stenosis, total plaque volume and burden, calcified plaque volume and burden, noncalcified plaque volume and burden (NCPB), pericoronary fat attenuation index (FAI), and other conventional plaque parameters were recorded. The patients were assigned to a training cohort (n = 280) and a validation cohort (n = 120) in a 7:3 ratio using a stratified random splitting method. The area under the receiver operating characteristics curve (AUC) was used to evaluate the predictive abilities of conventional parameters (model 1), radiomics features (model 2), and their combination (model 3). RESULTS: FAI and NCPB were identified as independent risk factors for coronary plaque progression in the training cohort. Both model 2 (training cohort AUC: 0.814, p < 0.001; validation cohort AUC: 0.729, p = 0.288) and model 3 (training cohort AUC: 0.824, p < 0.001; validation cohort AUC: 0.758, p = 0.042) had better diagnostic performances in predicting plaque progression than model 1 (training cohort AUC: 0.646; validation cohort AUC: 0.654). Moreover, model 3 was slightly higher than model 2, although not statistically significant. CONCLUSIONS: The combination of conventional coronary plaque parameters and CCTA-derived radiomics features had a better ability to predict plaque progression than conventional parameters alone. CLINICAL RELEVANCE STATEMENT: The conventional coronary plaque characteristics such as noncalcified plaque burden, pericoronary fat attenuation index, and radiomics features derived from CCTA can identify plaques prone to progression, which is helpful for further clinical decision-making of coronary artery disease. KEY POINTS: • FAI and NCPB were identified as independent risk factors for predicting plaque progression. • Coronary plaque radiomics features were more advantageous than conventional parameters in predicting plaque progression. • The combination of conventional coronary plaque parameters and radiomics features could significantly improve the predictive ability of plaque progression over conventional parameters alone.

Risk prediction of preoperative acute ischemic stroke in acute type A aortic dissection.

OBJECTIVES: To predict preoperative acute ischemic stroke (AIS) in acute type A aortic dissection (ATAAD). METHODS: In this multi-center retrospective study, 508 consecutive patients diagnosed as ATAAD between April 2020 and March 2021 were considered for inclusion. The patients were divided into a development cohort and two validation cohorts based on time periods and centers. Clinical data and imaging findings obtained were analyzed. Univariable and multivariable logistic regression analyses were performed to identify predictors associated with preoperative AIS. The performance of resulting nomogram was evaluated in discrimination and calibration on all cohorts. RESULTS: A total of 224 patients were in the development cohort, 94 in the temporal validation cohort, and 118 in the geographical validation cohort. Six predictors were identified: age, syncope, D-dimer, moderate to severe aortic valve insufficiency, diameter ratio of true lumen in ascending aorta < 0.33, and common carotid artery dissection. The nomogram established showed good discrimination (area under the receiver operating characteristic curve [AUC], 0.803; 95% CI: 0.742, 0.864) and calibration (Hosmer-Lemeshow test p = 0.300) in the development cohort. External validation showed good discrimination and calibration abilities in both temporal (AUC, 0.778; 95% CI: 0.671, 0.885; Hosmer-Lemeshow test p = 0.161) and geographical cohort (AUC, 0.806; 95% CI: 0.717, 0.895; Hosmer-Lemeshow test p = 0.100). CONCLUSIONS: A nomogram, based on simple imaging and clinical variables collected on admission, showed good discrimination and calibration abilities in predicting preoperative AIS for ATAAD patients. KEY POINTS: • A nomogram based on simple imaging and clinical findings may predict preoperative acute ischemic stroke in patients with acute type A aortic dissection in emergencies. • The nomogram showed good discrimination and calibration abilities in validation cohorts.

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.

Patient-specific post-trigger delay in coronary CT angiography: A prospective study comparing with fixed delay.

OBJECTIVES: To validate the peak enhancement timing of a patient-specific post-trigger delay (PTD) in Coronary CT angiography (CCTA) and compare its image quality against a fixed PTD. METHODS: In this prospective study, 204 consecutive participants were randomly divided into two groups to perform CCTA in bolus tracking with either a fixed 5-second PTD (Group A) or a patient-specific PTD (Group B). Test bolus was also performed in Group B to determine the reference peak enhancement timing. One reader evaluated objective image quality, while two readers rated subjective image quality. The predicted PTD was validated through correlation and agreement analysis with the reference measurement. Objective image quality was compared between groups via two-sample t-test and linear regression, while the subjective ratings were compared with chi-square analysis. RESULTS: The two groups each had 102 participants with comparable characteristics (52.9 ± 11.3 versus 52.1 ± 11.3 years of age, and 53 versus 52 males). The scan timing from patient-specific PTD demonstrated strong correlation (R = 0.77) and consistency (ICC = 0.618) with the reference peak timing. Both readers rated better subjective image quality for the Group B (p < 0.001). The mean vessel enhancement was significantly higher in Group B in all coronary vessels (all p < 0.05). After adjusting for the participant variation, the patient-specific PTD strategy was associated with an average of 33.5 HU higher enhancement compared to the fixed PTD. CONCLUSIONS: Patient-specific delay could achieve reliable scan timing, optimize vessel opacification and obtain better image quality in CCTA.

Prognostic analysis and risk stratification of lung adenocarcinoma undergoing EGFR-TKI therapy with time-serial CT-based radiomics signature.

OBJECTIVES: To evaluate the value of time-serial CT radiomics features in predicting progression-free survival (PFS) for lung adenocarcinoma (LUAD) patients after epidermal growth factor receptor-tyrosine kinase inhibitors (EGFR-TKIs) therapy. MATERIALS AND METHODS: LUAD patients treated with EGFR-TKIs were retrospectively included from three independent institutes and divided into training and validation cohorts. Intratumoral and peritumoral features were extracted from time-serial non-contrast chest CT (including pre-therapy and first follow-up images); moreover, the percentage variation per unit time (day) was introduced to adjust for the different follow-up periods of each patient. Test-retest was performed to exclude irreproducible features, while the Boruta algorithm was used to select critical radiomics features. Radiomics signatures were constructed with random forest survival models in the training cohort and compared against baseline clinical characteristics through Cox regression and nonparametric testing of concordance indices (C-indices). RESULTS: The training cohort included 131 patients (74 women, 56.5%) from one institute and the validation cohort encompassed 41 patients (24 women, 58.5%) from two other institutes. The optimal signature contained 10 features and 7 were unit time feature variations. The comprehensive radiomics model outperformed the pre-therapy clinical characteristics in predicting PFS (training: 0.78, 95% CI: [0.72, 0.84] versus 0.55, 95% CI: [0.49, 0.62], p < 0.001; validation: 0.72, 95% CI: [0.60, 0.84] versus 0.54, 95% CI: [0.42, 0.66], p < 0.001). CONCLUSION: Radiomics signature derived from time-serial CT images demonstrated optimal prognostic performance of disease progression. This dynamic imaging biomarker holds the promise of monitoring treatment response and achieving personalized management. KEY POINTS: • The intrinsic tumor heterogeneity can be highly dynamic under the therapeutic effect of EGFR-TKI treatment, and the inevitable development of drug resistance may disrupt the duration of clinical benefit. Decision-making remained challenging in practice to detect the emergence of acquired resistance during the early response phase. • Time-serial CT-based radiomics signature integrating intra- and peritumoral features offered the potential to predict progression-free survival for LUAD patients treated with EGFR-TKIs. • The dynamic imaging signature allowed for prognostic risk stratification.

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.

Improved interobserver agreement on nodule type and Lung-RADS classification of subsolid nodules using computer-aided solid component measurement.

PURPOSE: The Lung CT Screening Reporting and Data System (Lung-RADS) classification of subsolid nodules (SSNs) can be challenging due to limited interobserver agreement in determining the type and size of the nodule. Our study aimed to assess the effect of a computer-aided method on the interobserver agreement of Lung-RADS classification for SSNs. MATERIALS AND METHODS: This study consisted of 156 SSNs in 121 patients who underwent initial CT screening for lung cancer. Three independent readers determined the nodule type and measured the size of the entire nodule as well as the solid component, first without and then assisted by a semi-automated computer-aided tool. They assigned to each nodule the corresponding Lung-RADS 1.1 category. Agreement in size measurements was assessed by intraclass correlation coefficient (ICC) and Bland-Altman indexes, while agreement in nodule type and Lung-RADS was determined using Fleiss kappa statistics. The relationship between final diagnosis of the nodules and Lung-RADS classifications was also evaluated. RESULTS: Among the 156 nodules, manual size measurement reached an ICC of 0.994, and 48 nodules contained solid component measured by all the three readers both manually and semi-automatically. ICCs for the solid component measurement were 0.952, 0.997 and 0.996 for manual diameter, semi- automated diameter and volume measurement, respectively. Bias and 95% limits of agreement for average diameter of solid component were smaller with semi-automated measurements than with manual measurements. Kappa values of semi-automated assessment for nodule type (0.974) and Lung-RADS classification (0.958 for diameter and 0.952 for volume) were higher than with the manual measurements (0.783 for nodule type and 0.652 for Lung-RADS classification). Compared to manual work, the semi-automated assessment identified more 4B nodules among the 26 pathologically confirmed invasive adenocarcinomas (IACs). CONCLUSION: Semi-automated assessment could improve the interobserver agreement of nodule type and Lung-RADS classification for SSNs, and be inclined to classify SSNs corresponding to pathologically confirmed IACs into higher risk categories.

Effects of slice thickness on CT radiomics features and models for staging liver fibrosis caused by chronic liver disease.

OBJECTIVES: To investigate the effects of slice thickness on CT radiomics features and models for staging liver fibrosis. METHODS: A total of 108 pathologically confirmed liver fibrosis patients from a single center were retrospectively collected and divided into different groups. Both thick (5- or 7-mm) and thin slices (1.3- or 2-mm) were analyzed. A fivefold cross-validation with 100 repeats was conducted. The minimum redundancy-maximum relevance algorithm was used to reduce the radiomics features, and the top 10 ranking features were included for further analysis for each loop. The random forest was used for model establishment. The models with median AUC were selected for the assessment of the discriminative performance for both datasets. Mutual features selected by the models with AUC > 0.8 were searched and considered as the most predictive ones. RESULTS: A total of 162 and 643 radiomics features with excellent reliability were selected from thick- and thin-slice datasets, respectively. The overall discriminative performance of the 500 AUCs from the thin-slice dataset was better than the thick slice. The median AUC values of the thick-sliced datasets were significantly lower than those of the thin-sliced datasets (0.78 and 0.90 for differentiating F1 vs. F2-4, 0.72 and 0.85 for differentiating F1-2 vs. F3-4, both P = 0.03). For differentiating F1-3 vs. F4, no significant difference was found (0.85 vs 0.94, P = 0.15). Six mutual predictive features across all the datasets were found. CONCLUSIONS: The radiomics features extracted from thin-slice images and their corresponding models were better and more stable for staging liver fibrosis.

Influence of Different Segmentations on the Diagnostic Performance of Pericoronary Adipose Tissue.

Objective: To investigate the influence of different segmentations on the diagnostic performance of pericoronary adipose tissue (PCAT) CT attenuation and radiomics features for the prediction of ischemic coronary artery stenosis. Methods: From June 2016 to December 2018, 108 patients with 135 vessels were retrospectively analyzed in the present study. Vessel-based PCAT was segmented along the 40 mm-long proximal segments of three major epicardial coronary arteries, while lesion-based PCAT was defined around coronary lesions. CT attenuation and radiomics features derived from two segmentations were calculated and extracted. The diagnostic performance of PCAT CT attenuation or radiomics models in predicting ischemic coronary stenosis were also compared between vessel-based and lesion-based segmentations. Results: The mean PCAT CT attenuation was -75.7 ± 9.1 HU and -76.1 ± 8.1 HU (p = 0.395) for lesion-based and vessel-based segmentations, respectively. A strong correlation was found between vessel-based and lesion-based PCAT CT attenuation for all cohort and subgroup analyses (all p < 0.01). A good agreement for all cohort and subgroup analyses was also detected between two segmentations. The diagnostic performance was comparable between vessel-based and lesion based PCAT CT attenuation in predicting ischemic stenosis. The radiomics features of PCAT based on vessel or lesion segmentation can both adequately identify the ischemic stenosis. However, no significant difference was detected between the two segmentations. Conclusions: The quantitative evaluation of PCAT can be reliably measured both from vessel-based and lesion-based segmentation. Furthermore, the radiomics analysis of PCAT may potentially help predict hemodynamically significant coronary artery stenosis.

Prognosis with non-contrast CT and CT Perfusion imaging in thrombolysis-treated acute ischemic stroke.

BACKGROUND AND PURPOSE: The Alberta Stroke Program Early CT Score (ASPECTS) and hyperdense vessel sign (HDVS) on baseline non-contrast CT (NCCT) may benefit prognosis of acute ischemic stroke (AIS). We aimed to investigate the agreement of ASPECTS between automated and manual interpretations, and further understand the roles of NCCT and CT Perfusion (CTP) in prognosis. MATERIALS AND METHODS: From January 2019 to May 2020, thrombolysis-treated AIS patients undergoing NCCT and Perfusion imaging before treatment were retrospectively reviewed. A radiologist, a senior neuroradiologist and a neurologist blindly interpreted ASPECTS from NCCT images and a prototypical software produced automated results. Another independent radiologist determined presence of HDVS and CTP-ASPECTS. Three-month modified Rankin scale (mRS) ≤ 2 indicated good functional outcome. NCCT ASPECTS were compared against CTP-ASPECTS using squared weighted kappa. Univariable, multivariable and receiver operating characteristics (ROC) analysis were conducted to evaluate the prognostic value of clinical risk factors, NCCT and CTP findings. RESULTS: Seventy-five patients were included in this study, of whom 35 (46.7%) presented favorable outcome. Fair to substantial agreement with CTP-ASPECTS was witnessed for automated and manual interpretations (0.685, automated; 0.778, radiologist; 0.830, neuroradiologist; 0.313, neurologist). ASPECTS, HDVS, infarct core volume and mismatch ratio were univariably related to functional outcome, and infarct core volume remained as an independent prognostic factor in the multivariable analysis. The multivariable model achieved an area under ROC (AUC) of 0.768 (95% CI, 0.666-0.870). CONCLUSIONS: Automated ASPECTS achieves substantial agreement with reference CTP-ASPECTS, and comprehensive CT assessment may benefit AIS prognosis after intravenous thrombolysis.

Optimize scan timing in abdominal multiphase CT: Bolus tracking with an individualized post-trigger delay.

PURPOSE: To conduct a head-to-head comparison in terms of image quality and diagnostic confidence between an individualized post-trigger delay and a conventional fixed post-trigger delay in bolus tracking abdominal multiphase CT. METHODS AND MATERIALS: Abdominal multiphase CT was performed in 104 patients with either of the two bolus tracking strategies: an individualized post-trigger delay (group A) and fixed post-trigger delay of 11 s (group B). All CT scan parameters and contrast media protocol parameters were consistent between the two groups. Quantitative parameters (organs and blood vessels enhancement, image noise, signal-to-noise ratios [SNRs] and contrast-to-noise ratios [CNRs]) and qualitative visual parameters (overall image quality and diagnostic confidence) were compared. Quantitative and qualitative image quality for the two groups were compared using the Mann-Whitney U and independent sample t test. Degrees of agreement between two radiologists were evaluated using the Kappa analysis. RESULTS: In the arterial phase (AP), images of group A provided higher attenuation (P ≤ 0.001). Although SNRs of liver, pancreas and aorta were similar in AP between the two groups, CNRs of liver, pancreas and portal vein in group A were significantly higher than those in group B (all P values ≤ 0.002). The overall subjective image quality and diagnostic confidence between the two groups were similar (P = 0.809; P = 0.768). CONCLUSION: Compared to a fixed post-trigger delay using bolus tracking, application of an individualized post-trigger delay can optimize the objective image quality in arterial phase without compromising diagnostic quality in abdominal multiphase CT.

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.

Understanding the Effects of Both CD14-Mediated Innate Immunity and Device/Tissue Mechanical Mismatch in the Neuroinflammatory Response to Intracortical Microelectrodes.

Intracortical microelectrodes record neuronal activity of individual neurons within the brain, which can be used to bridge communication between the biological system and computer hardware for both research and rehabilitation purposes. However, long-term consistent neural recordings are difficult to achieve, in large part due to the neuroinflammatory tissue response to the microelectrodes. Prior studies have identified many factors that may contribute to the neuroinflammatory response to intracortical microelectrodes. Unfortunately, each proposed mechanism for the prolonged neuroinflammatory response has been investigated independently, while it is clear that mechanisms can overlap and be difficult to isolate. Therefore, we aimed to determine whether the dual targeting of the innate immune response by inhibiting innate immunity pathways associated with cluster of differentiation 14 (CD14), and the mechanical mismatch could improve the neuroinflammatory response to intracortical microelectrodes. A thiol-ene probe that softens on contact with the physiological environment was used to reduce mechanical mismatch. The thiol-ene probe was both softer and larger in size than the uncoated silicon control probe. Cd14-/- mice were used to completely inhibit contribution of CD14 to the neuroinflammatory response. Contrary to the initial hypothesis, dual targeting worsened the neuroinflammatory response to intracortical probes. Therefore, probe material and CD14 deficiency were independently assessed for their effect on inflammation and neuronal density by implanting each microelectrode type in both wild-type control and Cd14-/- mice. Histology results show that 2 weeks after implantation, targeting CD14 results in higher neuronal density and decreased glial scar around the probe, whereas the thiol-ene probe results in more microglia/macrophage activation and greater blood-brain barrier (BBB) disruption around the probe. Chronic histology demonstrate no differences in the inflammatory response at 16 weeks. Over acute time points, results also suggest immunomodulatory approaches such as targeting CD14 can be utilized to decrease inflammation to intracortical microelectrodes. The results obtained in the current study highlight the importance of not only probe material, but probe size, in regard to neuroinflammation.

The Role of Toll-Like Receptor 2 and 4 Innate Immunity Pathways in Intracortical Microelectrode-Induced Neuroinflammation.

We have recently demonstrated that partial inhibition of the cluster of differentiation 14 (CD14) innate immunity co-receptor pathway improves the long-term performance of intracortical microelectrodes better than complete inhibition. We hypothesized that partial activation of the CD14 pathway was critical to a neuroprotective response to the injury associated with initial and sustained device implantation. Therefore, here we investigated the role of two innate immunity receptors that closely interact with CD14 in inflammatory activation. We implanted silicon planar non-recording neural probes into knockout mice lacking Toll-like receptor 2 (Tlr2-/-), knockout mice lacking Toll-like receptor 4 (Tlr4-/-), and wildtype (WT) control mice, and evaluated endpoint histology at 2 and 16 weeks after implantation. Tlr4-/- mice exhibited significantly lower BBB permeability at acute and chronic time points, but also demonstrated significantly lower neuronal survival at the chronic time point. Inhibition of the Toll-like receptor 2 (TLR2) pathway had no significant effect compared to control animals. Additionally, when investigating the maturation of the neuroinflammatory response from 2 to 16 weeks, transgenic knockout mice exhibited similar histological trends to WT controls, except that knockout mice did not exhibit changes in microglia and macrophage activation over time. Together, our results indicate that complete genetic removal of Toll-like receptor 4 (TLR4) was detrimental to the integration of intracortical neural probes, while inhibition of TLR2 had no impact within the tests performed in this study. Therefore, approaches focusing on incomplete or acute inhibition of TLR4 may still improve intracortical microelectrode integration and long term recording performance.

Targeting CD14 on blood derived cells improves intracortical microelectrode performance.

Intracortical microelectrodes afford researchers an effective tool to precisely monitor neural spiking activity. Additionally, intracortical microelectrodes have the ability to return function to individuals with paralysis as part of a brain computer interface. Unfortunately, the neural signals recorded by these electrodes degrade over time. Many strategies which target the biological and/or materials mediating failure modes of this decline of function are currently under investigation. The goal of this study is to identify a precise cellular target for future intervention to sustain chronic intracortical microelectrode performance. Previous work from our lab has indicated that the Cluster of Differentiation 14/Toll-like receptor pathway (CD14/TLR) is a viable target to improve chronic laminar, silicon intracortical microelectrode recordings. Here, we use a mouse bone marrow chimera model to selectively knockout CD14, an innate immune receptor, from either brain resident microglia or blood-derived macrophages, in order to understand the most effective targets for future therapeutic options. Using single-unit recordings we demonstrate that inhibiting CD14 from the blood-derived macrophages improves recording quality over the 16 week long study. We conclude that targeting CD14 in blood-derived cells should be part of the strategy to improve the performance of intracortical microelectrodes, and that the daunting task of delivering therapeutics across the blood-brain barrier may not be needed to increase intracortical microelectrode performance.