A multi-cohort study of the hippocampal radiomics model and its associated biological changes in Alzheimer's Disease.

There have been no previous reports of hippocampal radiomics features associated with biological functions in Alzheimer's Disease (AD). This study aims to develop and validate a hippocampal radiomics model from structural magnetic resonance imaging (MRI) data for identifying patients with AD, and to explore the mechanism underlying the developed radiomics model using peripheral blood gene expression. In this retrospective multi-study, a radiomics model was developed based on the radiomics discovery group (n = 420) and validated in other cohorts. The biological functions underlying the model were identified in the radiogenomic analysis group using paired MRI and peripheral blood transcriptome analyses (n = 266). Mediation analysis and external validation were applied to further validate the key module and hub genes. A 12 radiomics features-based prediction model was constructed and this model showed highly robust predictive power for identifying AD patients in the validation and other three cohorts. Using radiogenomics mapping, myeloid leukocyte and neutrophil activation were enriched, and six hub genes were identified from the key module, which showed the highest correlation with the radiomics model. The correlation between hub genes and cognitive ability was confirmed using the external validation set of the AddneuroMed dataset. Mediation analysis revealed that the hippocampal radiomics model mediated the association between blood gene expression and cognitive ability. The hippocampal radiomics model can accurately identify patients with AD, while the predictive radiomics model may be driven by neutrophil-related biological pathways.

The interaction of global small vessel disease burden and Alzheimer's disease pathologies do not change the independent association of amyloid-beta with hippocampal volume: A longitudinal study on mild cognitive impairment subjects.

The purpose of this study was to investigate whether the co-existence of global small vessel disease (SVD) burdens and Alzheimer's disease (AD) pathologies change hippocampal volume (HV) and cognitive function of mild cognitive impairment (MCI) subjects. We obtained MRI images, cerebrospinal fluid biomarkers (Aß1-42 and p-tau), and neuropsychological tests of 310 MCI subjects from ADNI. The global SVD score was assessed. We used linear regression and linear mixing effect to analyze the effects of global SVD burdens, AD pathologies, and their interactions (SVD*AD) on baseline and longitudinal HV and cognition respectively. We used simple mediation effect to analyze the influencing pathways. After adjusting for global SVD and SVD*AD, Aß remained independently correlated with baseline and longitudinal HV (std ß = 0.294, p = .007; std ß = 0.292, p < .001), indicating that global SVD did not affect the correlation between Aß and HV. Global SVD score was correlated with longitudinal but not baseline HV (std ß = 0.470, p = .050), suggesting that global SVD may be more representative of long-term permanent impairment. Global SVD, AD pathologies, and SVD*AD were independently correlated with baseline and longitudinal cognitions, in which the association of Aß (B = 0.005, 95% CI: 0.005; 0.024) and p-tau (B = -0.002, 95% CI: -0.004; -0.000) with cognition were mediated by HV, suggesting that HV is more likely to explain the progression caused by AD pathology than SVD. The co-existence of global SVD and AD pathologies did not affect the individual association of Aß on HV; HV played a more important role in the influence of AD pathology on cognition than in SVD.

Optimal time point for neutrophil-to-lymphocyte ratio to predict stroke-associated pneumonia.

PURPOSE: This study aimed at the population receiving thrombolytic therapy and to explore the optimal time point for neutrophil-to-lymphocyte ratio (NLR) in predicting stroke-associated pneumonia (SAP). METHODS: We assessed patients undergoing intravenous thrombolysis (IVT) for acute ischemic stroke. Blood parameters were sampled before thrombolysis (within 30 min after admission) and within 24-36 h after thrombolysis, respectively. The primary outcome measure was the occurrence of SAP. Multivariate logistic regression analysis was performed to analyze the association between admission blood parameters and the event of SAP. We also used receiver operating characteristic (ROC) curve analysis to assess the discriminative ability of blood parameters measured at different times in predicting SAP. RESULTS: Among the 388 patients, SAP occurred in 60 (15%) patients. Multivariate logistic regression analysis showed that NLR was significantly associated with SAP (NLR before IVT: aOR = 1.288; 95%CI = 1.123-1.476; p < 0.001; NLR after IVT: (aOR = 1.127, 95%CI = 1.017-1.249; p = 0.023). The ROC curve showed that the predictive ability of NLR after IVT was better than NLR before IVT, not only in predicting the occurrence of SAP but also in predicting short-term and long-term functional outcomes, hemorrhagic transformation, and 1-year mortality. CONCLUSION: Increased NLR measured within 24-36 h after IVT has a significant predictive effect on the occurrence of SAP and can be used to predict short-term and long-term poor functional outcomes, hemorrhagic transformation, and 1-year mortality.

A2DS2 Score Combined With Clinical and Neuroimaging Factors Better Predicts Stroke-Associated Pneumonia in Hyperacute Cerebral Infarction.

OBJECTIVE: To investigate the predictors of stroke-associated pneumonia (SAP) and poor functional outcome in patients with hyperacute cerebral infarction (HCI) by combining clinical factors, laboratory tests and neuroimaging features. METHODS: We included 205 patients with HCI from November 2018 to December 2019. The diagnostic criterion for SAP was occurrence within 7 days of the onset of stroke. Poor outcome was defined as a functional outcome based on a 3-months MRS score >3. The relationship of demographic, laboratory and neuroimaging variables with SAP and poor outcome was investigated using univariate and multivariate analyses. RESULTS: Fifty seven (27.8%) patients were diagnosed with SAP and 40 (19.5%) developed poor outcomes. A2DS2 score (OR = 1.284; 95% CI: 1.048-1.574; P = 0.016), previous stroke (OR = 2.630; 95% CI: 1.122-6.163; P = 0.026), consciousness (OR = 2.945; 95% CI: 1.514-5.729; P < 0.001), brain atrophy (OR = 1.427; 95% CI: 1.040-1.959; P = 0.028), and core infarct volume (OR = 1.715; 95% CI: 1.163-2.528; P = 0.006) were independently associated with the occurrence of SAP. Therefore, we combined these variables into a new SAP prediction model with the C-statistic of 0.84 (95% CI: 0.78-0.90). Fasting plasma glucose (OR = 1.404; 95% CI: 1.202-1.640; P < 0.001), NIHSS score (OR = 1.088; 95% CI: 1.010-1.172; P = 0.026), previous stroke (OR = 4.333; 95% CI: 1.645-11.418; P = 0.003), SAP (OR = 3.420; 95% CI: 1.332-8.787; P = 0.011), basal ganglia-dilated perivascular spaces (BG-dPVS) (OR = 2.124; 95% CI: 1.313-3.436; P = 0.002), and core infarct volume (OR = 1.680; 95% CI: 1.166-2.420; P = 0.005) were independently associated with poor outcome. The C-statistic of the outcome model was 0.87 (95% CI: 0.81-0.94). Furthermore, the SAP model significantly improved discrimination and net benefit more than the A2DS2 scale, with a C-statistic of 0.76 (95% CI: 0.69-0.83). CONCLUSIONS: After the addition of neuroimaging features, the models exhibit good differentiation and calibration for the prediction of the occurrence of SAP and the development of poor outcomes in HCI patients. The SAP model could better predict the SAP, representing a helpful and valid tool to obtain a net benefit compared with the A2DS2 scale.

Prediction of occult lymph node metastasis using SUV, volumetric parameters and intratumoral heterogeneity of the primary tumor in T1-2N0M0 lung cancer patients staged by PET/CT.

OBJECTIVE: The aim of this study was to identify whether PET/CT-related metabolic parameters of the primary tumor could predict occult lymph node metastasis (OLM) in patients with T1-2N0M0 NSCLC staged by 18F-FDG PET/CT. METHODS: 215 patients with clinical T1-2N0M0 (cT1-2N0M0) NSCLC who underwent both preoperative FDG PET/CT and surgical resection with the systematic lymph node dissection were included in the retrospective study. Heterogeneity factor (HF) was obtained by finding the derivative of the volume-threshold function from 40 to 80% of the maximum standardized uptake value (SUVmax). Univariate and multivariate stepwise logistic regression analyses were used to identify these PET parameters and clinicopathological variables associated with OLM. RESULTS: Statistically significant differences were detected in sex, tumor site, SUVmax, mean SUV (SUVmean), metabolic tumor volume (MTV), total lesion glycolysis and HF between patients with adenocarcinoma (ADC) and squamous cell carcinoma (SQCC). OLM was detected in 36 (16.7%) of 215 patients (ADC, 27/152 = 17.8% vs. SQCC, 9/63 = 14.3%). In multivariate analysis, MTV (OR = 1.671, P = 0.044) in ADC and HF (OR = 8.799, P = 0.023) in SQCC were potent associated factors for the prediction of OLM. The optimal cutoff values of 5.12 cm3 for MTV in ADC, and 0.198 for HF in SQCC were determined using receiver operating characteristic curve analysis. CONCLUSIONS: In conclusion, MTV was an independent predictor of OLM in cT1-2N0M0 ADC patients, while HF might be the most powerful predictor for OLM in SQCC. These findings would be helpful in selecting patients who might be considered as candidates for sublobar resection or new stereotactic ablative radiotherapy.

Determination of Risk Factors and Establishment of a Prediction Model for Immediate Technical Failure during Endovascular Treatment of Femoropopliteal Occlusive Disease.

BACKGROUND: For long femoropopliteal occlusive lesions, the immediate technical failure (ITF) of endovascular treatment (EVT) is relatively high. Therefore, this study aims to reveal risk factors and establish a prediction model of ITF of EVT in femoropopliteal occlusive disease (FPOD) patients based on preoperative clinical date that may be helpful to the clinical procedures. METHODS: A retrospective analysis of 1,563 FPOD patients who underwent above-the-knee EVT was undertaken. Univariate analysis with chi-squared test was used to screen risk factors from preoperative clinical data. Multivariable analysis with logistic regression was used to generate a model for predicting the ITF rate of EVT, which was evaluated through the receiver operating characteristic curve and another independent cohort of 242 FPOD patients. RESULTS: Risk factors for ITF during EVT in FPOD included age (>80 years, X1), the absence of diabetes mellitus (X2), low-density lipoprotein (>160 mg/dL, X3), lesion calcification (X4), lesion length (>20 cm, X5), ostial occlusion of superficial femoral artery (SFA) (X6), and SFA lesion involving the popliteal artery (X7). A logistic regression model was established based on the equation: -6.504 + 1.236X1 + 0.945X2 + 1.406X3 + 1.136X4 + 1.059X5 + 2.307X6 + 2.194X7. Scores were given to risk factors as follows: X1 (yes = 12, no = 0), X2 (yes = 9, no = 0), X3 (yes = 14, no = 0), X4 (yes = 11, no = 0), X5 (yes = 11, no = 0), X6 (yes = 23, no = 0), and X7 (yes = 22, no = 0). We determined that the optimal comprehensive score for predicting EVT failure was 39, with a sensitivity of 0.847 and a specificity of 0.8. Among these 242 peripheral arterial disease patients, 12 of 14 patients who had failed EVT had a comprehensive score of >39. CONCLUSIONS: We identified a number of risk factors of ITF during the above-the-knee EVT and established a prediction model that may be used for guidance in clinical practice.