Analyzing the value of delayed 18 F-FDG PET/CT images in diagnosing small colorectal cancer liver metastases in patients with hypothyroidism based on diagnostic accuracy and image standardized uptake value.

PURPOSE: The objective of this study was to investigate the value of delayed 18F fluorodeoxyglucose PET/computed tomography (18F-FDG PET/CT) images in patients with small colorectal cancer liver metastases (CRLMs) with hypothyroidism. METHOD: We performed a retrospective analysis of 66 small-CRLM patients with hypothyroidism and 66 small-CRLM patients with euthyroidism, all of whom underwent dual-time-point 18 F-FDG PET/CT imaging. First, the diagnostic accuracy of PET/CT early imaging and PET/CT delayed imaging on lesions was analyzed. Next, the correlation of metabolic parameters between PET/CT early imaging and PET/CT delayed imaging was analyzed according to the grouping of all lesions. Finally, PET/CT parameters were analyzed for correlation with thyroid hormones. RESULTS: The diagnostic accuracy of delayed imaging in small-CRLM patients with hypothyroidism is not as good as that in small-CRLM patients with euthyroidism; PET/CT metabolic parameters are also unfavorable for the diagnosis of small-CRLM. For small-CRLM patients with hypothyroidism, the greater the thyroid-stimulating hormone level, the greater the uptake of 18 F-FDG in normal liver tissue, and the smaller the ratio of tumor lesion uptake to normal liver tissue uptake. CONCLUSION: PET/CT-delayed imaging has better performance than early imaging in small-CRLM patients with euthyroidism. However, the more severe the hypothyroidism, the worse the diagnostic delayed imaging performance. The scan time can be extended appropriately to optimize the imaging efficacy.

Analysis of independent risk factors for aneurysm rupture based on carotid tortuosity index and morphological parameters of single intracranial aneurysms in anterior circulation.

PURPOSE: Our study focused on the risk factors associated with anterior circulation intracranial aneurysm (IA) rupture by examining the carotid artery (CA) tortuosity index (TI) and anterior circulation IA morphological parameters. METHOD: This study conducted a retrospective analysis of clinical and imaging data from 163 patients with anterior circulation IA diagnosed by head and neck computed tomography angiography (CTA). The patients were categorized into two groups: the ruptured group (57 cases) and the unruptured group (106 cases). CA was categorized based on its location into three segments: the extracranial segment of the internal carotid artery (EICA) TI, the angle of the internal carotid artery (ICA) and the common carotid artery (CCA) TI. Measure the morphological parameters of all IA: IA length neck (L), IA height (H), aneurysm diameter width (D), the ratio of L to the mean diameter of the IA-bearing artery (SR), the ratio of H to D (AR), the angle of flow inflow (FA) and IA angle (AA). The study conducted five types of analysis to determine the risk factors for anterior circulation IA rupture. The first was an univariate analysis of the risk factors. The second was an analysis of the correlation between CA TI and IA morphological parameters. The third used multivariate logistic stepwise regression analysis to analyse independent risk factors for IA rupture. The fourth was to plot ROC curves to build a predictive model for IA rupture and calculate diagnostic thresholds. Finally, a data set from another hospital (78 cases) was used as a validation set to validate the multivariate model. RESULT: Univariate analysis revealed that there were statistically significant differences (P < 0.05) in gender, EICA TI, location of IA and IA morphological parameters (FA, H, AR, L, SR), which acted as risk factors for anterior circulation IA rupture. The results of Spearman correlation analysis indicate that CCA TI is significantly correlated with SR, H and L (P < 0.05), while EICA TI is significantly correlated with FA and L (P < 0.05). The results of multivariate logistic analysis showed that FA (OR = 1.072, 95%CI = 1.04-1.10, P < 0.001), SR (OR = 4.949, 95%CI = 1.96-12.53, P = 0.001), EICA TI (OR = 1.037, 95%CI = 1.01-1.07, P = 0.003) were independent risk factors for IA rupture. The ROC curve plotting results suggest that the area under the curve (AUC) of FA is 0.860 with a diagnostic threshold of 110.1°; the AUC of SR is 0.786 with a diagnostic threshold of 1.67; the AUC of EICA TI is 0.723 with a diagnostic threshold of 28.845; the AUC of the three combined is 0.903 with a threshold of 0.480. The combined factor diagnostic model is validated according to the validation set, and the results show that the AUC (0.866) of the validation set is not much different from the AUC (0.903) of the multivariate model, and the multivariate model has a better diagnostic effect. CONCLUSION: In clinical practice, it is important to consider the evaluation of aneurysm rupture in combination with imaging, as FA, SR and ECIA TI are independent risk factors for IA rupture in the anterior circulation. Unlike the IA morphological parameters, EICA TI is an often overlooked extracranial parameter, but is equally important in its power to predict IA rupture. When the EICA TI exceeds 28.845, the IA has the possibility of rupture. Finally, multivariate diagnostic model are of interest when considering rupture of the anterior circulation IA.

Performance of Radiomics Models Based on Coronary Computed Tomography Angiography in Predicting The Risk of Major Adverse Cardiovascular Events Within 3 Years: A Comparison Between the Pericoronary Adipose Tissue Model and the Epicardial Adipose Tissue Model.

RATIONALE AND OBJECTIVES: To compare the prediction performance of the epicardial adipose tissue (EAT) and pericoronary adipose tissue (PCAT) radiomics models based on coronary computed tomography angiography for major adverse cardiovascular events (MACE) within 3 years. MATERIALS AND METHODS: Our study included 288 patients (144 with MACE and 144 without MACE within 3 years) by matching age, gender, body mass index, and medication intake. Patients were randomly assigned either to the training (n = 201) or validation cohort (n = 87). A total of 184 radiomics features were extracted from EAT and PCAT images. Spearman's rank correlation coefficient and the gradient boosting decision tree algorithm were performed for feature selection. Five models were established based on PCAT or EAT radiomics features and clinical factors, including PCAT, EAT, clinical, PCAT-clinical, and EAT-clinical model (MPCAT, MEAT, Mclinical, MPCAT-clinical, and MEAT-clinical). Receiver operating characteristic curves, calibration curves, and the decision curve analysis were plotted to evaluate the model performance. RESULTS: The MPCAT achieved an area under the curve (AUC) of 0.703 in the validation cohort, which was better than MEAT with AUC of 0.538. The MPCAT-clinical showed better performance (AUC = 0.781) in predicting MACE than the Mclinical (AUC = 0.748) or MEAT-clinical (AUC = 0.745). CONCLUSION: Our results showed that the PCAT was better than the EAT in both single modality and combined models, and the MPCAT-clinical had the most significant clinical value in predicting the occurrence of MACE within 3 years.

Risk Factors of Impaired Perfusion in Patients With Symptomatic Internal Carotid Artery Steno-Occlusive Disease.

Objective: To quantitatively evaluate the impaired perfusion status of patients with symptomatic internal carotid artery (ICA) steno-occlusive disease and to explore the risk factors of impaired perfusion with computed tomography perfusion (CTP). Methods: The clinical and imaging data of 187 patients with ICA steno-occlusive disease were retrospectively analyzed. The ICA stenosis rate was divided into Grades I-IV (70-79%; 80-89%; 90-99%; 100%), and the circle of Willis was classified as four types (types I-IV). According to the literature, the value of cerebral blood flow/cerebral blood volume (CBF/CBV) of 7.55/min was used as cut-off to predict symptomatic patients. All patients were categorized into two groups: those with impaired perfusion [n = 99 (52.9%)] and those without impaired perfusion [n = 88 (47.1%)]. Symmetrical bilateral internal watershed areas were selected as the regions of interest (ROIs). Statistical analysis was made on the status of impaired perfusion and the risk factors of impaired perfusion. Results: Univariate analysis revealed that systolic blood pressure (SBP), diastolic blood pressure (DBP), mean arterial pressure (MAP), types of the circle of Willis, and clinical features at admission differed between the two groups (patients with or without impaired perfusion) (p < 0.05). Multiple logistic stepwise regression analysis showed that MAP [odds ratio (OR) = 0.946, 95% confidential interval (CI) = 0.917-0.974, p < 0.001] and type IV (type I vs. IV: OR = 4.987, 95% CI = 1.955-12.723, p = 0.001) at admission were independently associated with impaired perfusion in the internal watershed areas. Conclusion: MAP and the type of circle of Willis at admission are independent risk factors associated with the impaired perfusion in patients with ICA steno-occlusive disease.

Diffusion- and Susceptibility Weighted Imaging Mismatch Correlates With Collateral Circulation and Prognosis After Middle Cerebral Artery M1-Segment Occlusion.

Objective: To explore the relation between diffusion-weighted and susceptibility weighted imaging (DWI-SWI) mismatch and collateral circulation or prognosis in patients with occluded M1 segments of middle cerebral artery (MCA). Methods: We enrolled 59 patients with MCA M1-segment occlusion for a retrospective review of baseline clinical and imaging data. As markers of circulatory collaterals, prominent laterality of posterior (PLPCA) and anterior (PLACA) cerebral arteries on magnetic resonance angiography (MRA) studies and a hyperintense vessel sign (HVS) on T2 fluid-attenuated inversion recovery (FLAIR) images were collectively scored. The extent of acute cerebral infarction was then quantified on DWI, using the Alberta Stroke Program Early CT Score (DWI-ASPECTS). Hypointensity vessel sign prominence (PVS) was also evaluated by SWI and similarly scored (SWI-ASPECT) to calculate DWI-SWI mismatch [(DWI-ASPECTS) - (SWI-ASPECTS)], ranging from -10 to 10 points. Results: DWI-SWI mismatch showed significant associations with PLPCA, PLACA, HVS prominence, and collective collateral scores (all, p < 0.05). National Institutes of Health Stroke Scale (NIHSS), DWI-SWI mismatch, and DWI-ASPECTS also differed significantly according to patient prognosis (good vs. poor) after MCA M1-segment occlusion (p < 0.05). In binary logistic regression analyses, NIHSS and DWI-SWI mismatch emerged as independent prognostic factors (p < 0.05). Conclusions: Collateral circulation may be an important aspect of DWI-SWI mismatch, which in this study correlated with prognostic outcomes of MCA M1-segment occlusion.

Risk Factors of Anterior Circulation Intracranial Aneurysm Rupture: Extracranial Carotid Artery Tortuosity and Aneurysm Morphologic Parameters.

Background: This study was conducted to explore the risk factors of anterior circulation intracranial aneurysm rupture based on extracranial carotid artery (ECA) tortuosity. Methods: This retrospective study, conducted from January 1, 2017, to March 1, 2021, collected and reviewed the clinical and imaging data of 308 patients with anterior circulation intracranial aneurysm [133 (43.2%) patients in the ruptured aneurysm group; 175 (56.8%) patients in the unruptured aneurysm group]. Computed tomography angiography (CTA) of the head and neck was used to determine the ECA tortuosity (normal, simple tortuosity, kink, coil) and the morphologic parameters of the aneurysms. The relationship of aneurysm rupture to ECA tortuosity and the morphologic parameters were analyzed. Results: After univariate analysis, kink, angle of flow inflow (FA), aspect ratio (AR), aneurysm length (L), the distance from the tortuosity to the aneurysm (distance), and size ratio (SR) were significantly correlated with anterior circulation intracranial aneurysm rupture (p < 0.05). Spearman correlation analysis showed that ECA tortuosity was correlated with FA and SR (p < 0.05). Multiple logistic analyses showed that FA [odds ratio (OR), 1.013; 95% CI, 1.002-1.025], SR (OR, 1.521; 95% CI, 1.054-2.195), and kink (OR, 1.823; 95% CI, 1.074-3.096) were independently associated with aneurysm rupture. Conclusion: Study results suggest that FA, SR, and ECA kink were independent risk factors associated with anterior circulation intracranial aneurysm rupture.

New Insights in Addressing Cerebral Small Vessel Disease: Association With the Deep Medullary Veins.

OBJECTIVE: To assess the suitability of deep medullary vein visibility in susceptibility weighted imaging-magnetic resonance imaging studies as a method for the diagnosis and evaluation of cerebral small vessel disease progression. METHODS: A total of 92 patients with CSVD were enrolled and baseline clinical and imaging data were reviewed retrospectively. Neuroimaging biomarkers of CSVD including high-grade white matter hyperintensity (HWMH), cerebral microbleed (CMB), enlarged perivascular space (PVS), and lacunar infarct (LI) were identified and CSVD burden was calculated. Cases were grouped accordingly as mild, moderate, or severe. The DMV was divided into six segments according to the regional anatomy. The total DMV score (0-18) was calculated as the sum of the six individual segmental scores, which ranged from 0 to 3, for a semi-quantitative assessment of the DMV based on segmental continuity and visibility. RESULTS: The DMV score was independently associated with the presence of HWMH, PVS, and LI (P < 0.05), but not with presence and absence of CMB (P > 0.05). Correlation between the DMV score and the CSVD burden was significant (P < 0.05) [OR 95% C.I., 1.227 (1.096-1.388)]. CONCLUSION: The DMV score was associated with the presence and severity of CSVD.

Asymmetric Deep Medullary Veins in Patients With Occlusion of a Large Cerebral Artery: Association With Cortical Veins, Leptomeningeal Collaterals, and Prognosis.

Objective: To explore the relationships of asymmetric deep medullary veins (ADMV) to asymmetric cortical veins (ACV), leptomeningeal collaterals and prognosis in patients with occlusion of a large cerebral artery. Methods: Clinical and imaging data of 56 patients with occlusion of a large cerebral artery were collected and reviewed. We assessed the time delayed between stroke onset and MR imaging (within 24 h of stroke onset), extension of cerebral infarction using the Alberta stroke program early CT score based on diffusion-weighted imaging (ASPECTs). ADMV and ACV were assessed using susceptibility-weighted imaging. The presence of ADMV (ACV) was defined as deep medullary veins (cortical veins) of the affected hemisphere that were greater in number and diameter than in the contralateral hemisphere. To evaluate leptomeningeal collaterals, the hyperintense vessel sign (HVS) was detected using T2 weighted fluid attenuated inversion recovery images. At 90 days, a modified Rankin scale score (mRS) was assessed to evaluate the clinical outcome. Results: Of 56 patients, 27 presented with ADMV. Those patients who presented with and without ADMV differed significantly in HVS and ACV (P < 0.05) but not in time delayed between stroke onset and MR imaging, age, gender, stroke risk factors, baseline NIHSS score, or modified Rankin scale score at 3 months (P > 0.05). Logistic regression analysis found that the presence of ADMV was independently related to HVS and ACV (ACV: OR 95% C.I., 1.287-4.368; HVS: OR 95% C.I., 1.132-4.887). Conclusions: The presence of ADMV on SWI was associated with prominent ACV and good leptomeningeal collateral flow but was not related to prognosis in patients with occlusion of a large cerebral artery.