Probiotic nucleotides increase IL-10 expression in airway macrophages to mitigate airway allergy.

BACKGROUND: Dysfunctional immune regulation plays a crucial role in the pathogenesis of airway allergies. Macrophages are one of the components of the immune regulation cells. The aim of this study is to elucidate the role of lysine demethylase 5 A (KDM5A) in maintaining macrophages' immune regulatory ability. METHODS: DNA was extracted from Lactobacillus rhamnosus GG to be designated as LgDNA. LgDNA was administered to the mice through nasal instillations. M2 macrophages (M2 cells) were isolated from the airway tissues using flow cytometry. RESULTS: We found that airway M2 cells of mice with airway Th2 polarization had reduced amounts of IL-10 and KDM5A. Mice with Kdm5a deficiency in M2 cells showed the airway Th2 polarization. The expression of Kdm5a in airway M2 cells was enhanced by nasal instillations containing LgDNA. KDM5A mediated the effects of LgDNA on inducing the Il10 expression in airway M2 cells. Administration of LgDNA mitigated experimental airway allergy. CONCLUSIONS: M2 macrophages in the airway tissues of mice with airway allergy show low levels of KDM5A. By upregulating KDM5A expression, LgDNA can increase Il10 expression and reconcile airway Th2 polarization.

Photon-counting Detector CT for Liver Fat Quantification: Validation across Protocols in Metabolic Dysfunction-associated Steatotic Liver Disease.

Background Traditional energy-integrating detector CT has limited utility in accurately quantifying liver fat due to protocol-induced CT value shifts, but this limitation can be addressed by using photon-counting detector (PCD) CT, which allows for a standardized CT value. Purpose To develop and validate a universal CT to MRI fat conversion formula to enhance fat quantification accuracy across various PCD CT protocols relative to MRI proton density fat fraction (PDFF). Materials and Methods In this prospective study, the feasibility of fat quantification was evaluated in phantoms with various nominal fat fractions. Five hundred asymptomatic participants and 157 participants with suspected metabolic dysfunction-associated steatotic liver disease (MASLD) were enrolled between September 2023 and March 2024. Participants were randomly assigned to six groups with different CT protocols regarding tube voltage (90, 120, or 140 kVp) and radiation dose (standard or low). Of the participants in the 120-kVp standard-dose asymptomatic group, 51% (53 of 104) were designated as the training cohort, with the rest of the asymptomatic group serving as the validation cohort. A CT to MRI fat quantification formula was derived from the training cohort to estimate the CT-derived fat fraction (CTFF). CTFF agreement with PDFF and its error were evaluated in the asymptomatic validation cohort and subcohorts stratified by tube voltage, radiation dose, and body mass index, and in the MASLD cohort. The factors influencing CTFF error were further evaluated. Results In the phantoms, CTFF showed excellent agreement with nominal fat fraction (intraclass correlation coefficient, 0.98; mean bias, 0.2%). A total of 412 asymptomatic participants and 122 participants with MASLD were included. A CT to MRI fat conversion formula was derived as follows: MRI PDFF (%) = -0.58 · CT (HU) + 43.1. Across all comparisons, CTFF demonstrated excellent agreement with PDFF (mean bias values < 1%). CTFF error was not influenced by tube voltage, radiation dose, body mass index, or PDFF. Agreement between CTFF and PDFF was also found in the MASLD cohort (mean bias, -0.2%). Conclusion Standardized CT value from PCD CT showed a robust and remarkable agreement with MRI PDFF across various protocols and may serve as a precise alternative for liver fat quantification. © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Wildman-Tobriner in this issue.

Quantification accuracy in photon-counting detector CT for coronary artery calcium score: a pilot study.

To validate the accuracy of coronary artery calcium score (CACS) using photon-counting detector (PCD) CT under various scanning settings and explore the optimized scanning settings considering both the accuracy and the radiation dose. A CACS phantom containing six hollow cylindrical hydroxyapatite calcifications of two sizes with three densities and 12 patients underwent CACS scans. For PCD-CT, two scanning modes (sequence and flash [high-pitch spiral mode]) and five tube voltages (90kV, 120kV, 140kV, Sn100kV, and Sn140kV) at different image quality (IQ) levels were set for phantom, and patients were scanned with 120kV at IQ19 using flash mode. All acquisitions from PCD-CT were reconstructed at 70keV. Acquisitions in sequence mode at 120kV on an energy-integrating detector CT (EID-CT) was used as the reference. Agatston, mass, and volume scores were calculated. The CACS from PCD-CT exhibited excellent agreements with the reference (all intraclass correlation coefficient [ICC] > 0.99). The root mean square error (RMSE) between the Agatston score acquired from PCD-CT and the reference (5.4-11.5) was small. A radiation dose reduction (16-75%) from PCD-CT compared with the reference was obtained in all protocols using flash mode, albeit with IQ20 only at sequence mode (22-44%). For the patients, ICC ( all ICC > 0.98) and Bland-Altman analysis of CACS all showed high agreements between PCD-CT and the reference, without reclassifying CACS categories(P = 0.317). PCD-CT yields repeatable and accurate CACS across diverse scanning protocols according to our pilot study. Sn100kV, 90kV, and 120kV using flash mode at IQ20 are recommended for clinical applications considering both accuracy and radiation dose.

Low-dose Ultra-high-resolution Photon-Counting Detector CT for Visceral Artery CT Angiography: A Preliminary Study.

RATIONALE AND OBJECTIVES: To validate the image quality of low-dose ultra-high-resolution (UHR) scanning mode of photon-counting detector CT (PCD-CT) for visceral artery computed tomography angiography (CTA). MATERIAL AND METHODS: We prospectively enrolled 57 patients each in the full dose (FD) and low-dose (LD) protocols, respectively, to undergo abdominal CT scans using the UHR mode on a PCD-CT system (NAEOTOM Alpha), between April 2023 and September 2023. Both the FD data and LD data were then reconstructed into two series of images: (a) 0.2 mm slice thickness, reconstruction kernel Bv48, quantum iterative reconstruction (QIR) 4; (b)1 mm slice thickness, Bv40, QIR 3. The signal-to-noise ratios (SNRs) and contrast-to-noise ratios (CNRs) of seven arteries were objectively measured. The image noise, vessel sharpness, overall quality, and visibility of nine arteries were subjectively assessed by three radiologists. RESULTS: The SNRs and CNRs of 0.2 mm reconstruction set was inferior to that of 1 mm reconstruction set (p < 0.001 for all the arteries and noise), however, the image quality of 0.2 mm reconstruction set was higher than that of 1 mm reconstruction set in qualitative evaluation especially for tiny arteries in Volume-rendered (VR) image (p < 0.001). The SNRs and CNRs were not significantly higher for FD group than LD group on the same slice thickness except for SNRs of common hepatic artery, splenic artery and bilateral renal arteries in 0.2 mm reconstruction set. In the comparison on image quality between normal weight and overweight patients within the same reconstruction set, the results showed that low-dose scan did not significantly impact the image quality in overweight patients. The ratings of visibility of nine visceral arteries were not significantly different among FD and LD at the same thickness reconstruction set except for superior mesenteric artery (p = 0.002 and 0.007 for 0.2 mm and 1 mm reconstruction set in axial image; p = 0.002 and 0.007 for 0.2 mm and 1 mm reconstruction set in coronal image, respectively) and left gastric artery (p = 0.002 and p < 0.001 for 0.2 mm and 1 mm reconstruction set in VR image, respectively). CONCLUSION: The low-dose UHR scanning mode of PCD-CT has proven to be adequate for the clinical evaluation of visceral arteries. Utilizing a reconstruction with a slice thickness of 0.2 mm could enhance arterial depiction, particularly for small vessels.

Prediction of tumor regression grade in far-advanced gastric cancer after preoperative immuno-chemotherapy using dual-energy CT-derived extracellular volume fraction.

OBJECTIVES: This study examines the effectiveness of dual-energy CT (DECT) delayed-phase extracellular volume (ECV) fraction in predicting tumor regression grade (TRG) in far-advanced gastric cancer (FAGC) patients receiving preoperative immuno-chemotherapy. MATERIALS AND METHODS: A retrospective analysis was performed on far-advanced gastric adenocarcinoma patients treated with preoperative immuno-chemotherapy at our institution from August 2019 to March 2023. Patients were categorized based on their TRG into pathological complete response (pCR) and non-pCR groups. ECV was determined using the delayed-phase iodine maps. In addition, tumor iodine densities and standardized iodine ratios were meticulously analyzed using the triple-phase enhanced iodine maps. Univariate analysis with five-fold cross-validation and Spearman correlation determined DECT parameters and clinical indicators association with pCR. The predictive accuracy of these parameters for pCR was evaluated using a weighted logistic regression model with five-fold cross-validation. RESULTS: Of the 88 patients enrolled (mean age 60.8 ± 11.1 years, 63 males), 21 (23.9%) achieved pCR. Univariate analysis indicated ECV's significant role in differentiating between pCR and non-pCR groups (average p value = 0.021). In the logistic regression model, ECV independently predicted pCR with an average odds ratio of 0.911 (95% confidence interval, 0.798-0.994). The model, incorporating ECV, tumor area, and IDAV (the relative change rate of iodine density from venous phase to arterial phase), showed an average area under curves (AUCs) of 0.780 (0.770-0.791) and 0.766 (0.731-0.800) for the training and validation sets, respectively, in predicting pCR. CONCLUSION: DECT-derived ECV fraction is a valuable predictor of TRG in FAGC patients undergoing preoperative immuno-chemotherapy. CLINICAL RELEVANCE STATEMENT: This study demonstrates that DECT-derived extracellular volume fraction is a reliable predictor for pathological complete response in far-advanced gastric cancer patients receiving preoperative immuno-chemotherapy, offering a noninvasive tool for identifying potential treatment beneficiaries.

Performance of calcium quantifications on low-dose photon-counting detector CT with high-pitch: A phantom study.

Purpose: To evaluate the performance of calcium quantification on photon-counting detector CT (PCD-CT) with high-pitch at low radiation doses compared to third-generation dual-source energy-integrating detector CT (EID-CT). Materials and methods: The phantom with three calcium inserts (50, 100, and 300 mg of calcium per milliliter), with and without the elliptical outer layer, was evaluated using high-pitch (3.2) and standard pitch (0.8) on PCD-CT, and standard pitch on EID-CT. Scans were performed with different tube voltages (PCD-CT: 120 and 140 kilo-voltage peak [kVp]; EID-CT: 70/Sn150 and 100/Sn150 kVp) and four radiation doses (1, 3, 5, and, 10 milli-Gray [mGy]). Utilizing the true calcium concentrations (CCtrue) of the phantom as the gold standard references, regression equations for each kVp setting were formulated to convert CT attenuations (CaCT) into measured calcium concentrations (CCm). The correlation analysis between CaCT and CCtrue was performed. The percentage absolute bias (PAB) was calculated from the differences between CCm and CCtrue and used to analyze the effects of scanning parameters on calcium quantification accuracy. Results: A strong correlation was found between CaCT and CCtrue on PCD-CT (r > 0.99) and EID-CT (r > 0.98). For high- and standard-pitch scans on PCD-CT, the accuracy of calcium quantification is comparable (p = 0.615): the median (interquartile range [IQR]) of PAB was 5.59% (2.79%-8.31%) and 4.87 % (2.62%-8.01%), respectively. The PAB median (IQR) was 7.43% (3.77%-11.75%) for EID-CT. The calcium quantification accuracy of PCD-CT is superior to EID-CT at the large phantom (5.46% [2.68%-9.55%] versus 9.01% [6.22%-12.74%]), and at the radiation dose of 1 mGy (4.43% [2.08%-8.59%] versus 13.89% [8.93%-23.09%]) and 3 mGy (4.61% [2.75%-6.51%] versus 9.97% [5.17%-14.41%]), all p < 0.001. Conclusions: Calcium quantification using low-dose PCD-CT with high-pitch scanning is feasible and accurate, and superior to EID-CT.

High-Detectivity All-Polymer Photodiode Empowers Smart Vitality Surveillance and Computational Imaging Rivaling Silicon Diodes.

Near-infrared (NIR) organic photodetectors (OPDs), particularly all-polymer-based ones, hold substantial commercial promise in the healthcare and imaging sectors. However, the process of optimizing their active layer composition to achieve highly competitive figures of merit lacks a clear direction and methodology. In this work, celebrity polymer acceptor PY-IT into a more NIR absorbing host system PBDB-T:PZF-V, to significantly enhance the photodetection competence, is introduced. The refined all-polymer ternary broadband photodetector demonstrates superior performance metrics, including experimentally measured noise current as low as 6 fA Hz-1/2, specific detectivity reaching 8 × 1012 Jones, linear dynamic range (LDR) of 145 dB, and swift response speed surpassing 200 kHz, striking a fair balance between sensitivity and response speed. Comprehensive morphological and photophysical characterizations elucidate the mechanisms behind the observed performance enhancements in this study, which include reduced trap density, enhanced charge transport, diminished charge recombination, and balanced electron/hole mobilities. Moreover, the practical deployment potential of the proof-of-concept device in self-powered mode is demonstrated through their application in a machine learning-based cuffless blood pressure (BP) estimation system and in high-resolution computational imaging across complex environments, where they are found to quantitatively rival commercial silicon diodes.

Silver coated PS microsphere array SERS microfluidic chip for pesticide detection.

Carbendazim and acetamidine are pesticides that widely used to control pests and diseases in oilseed rape. In this paper, a rapid, accurate and reliable method was proposed for the detection of carbendazim and acetamidine with SERS microfluidic chip technology. Ag-ps(Polystyrene microspheres) microsphere SERS substrate was prepared by spin coating and magnetron sputtering deposition of Ag. The enhancement factor of prepared SERS substrate was 2.4 × 1010. The SERS detection working curves were well fitted and the linear parameters R2 were 0.987 and 0.994, respectively. The limit of detection was 0.01 mg/mL. The use of SERS microfluidic chip to detect carbendazim and acetamidine is expected to provide a way for the detection of pesticide residues in crops, which has broad application prospects in the field of food safety.

Stability and accuracy of fat quantification on photon-counting detector CT with various scan settings: A phantom study.

OBJECTIVE: Fat deposition is an important marker of many metabolic diseases. As a noninvasive and convenient examination method, CT has been widely used for fat quantification. With the clinical application of photon-counting detector (PCD)-CT, we aimed to investigate the accuracy, stability, and dose level of PCD-CT using various scan settings for fat quantification. MATERIALS AND METHODS: Eleven agar-based lipid-containing phantoms (vials with different fat fractions [FFs]; range: 0 %-100 %) were scanned using PCD-CT. Three scanning types (sequence scan, regular spiral scan with a pitch of 0.8, and high-pitch spiral scan with a pitch of 3.2), four tube voltages (90, 120, 140, and 100 kV with a tin filter), and three image quality (IQ) levels (IQ levels of 20, 40, and 80) were alternated, and each scan setting was used twice. For each scan, a 70-keV image was generated using the same reconstruction parameters. A regular spiral scan at 120 kV with IQ80 was used to transfer the CT numbers of all scans to the FF. Intraclass correlation coefficient (ICC) and Bland-Altman analysis were implemented for accuracy and agreement evaluation, and group differences were compared using analysis of variance. RESULTS: Excellent agreement and accuracy of FF derived by PCD-CT with all scan settings was demonstrated by high ICCs (>0.9; range: 0.929-0.998, p < 0.017) and low bias (<5% range: -2.9 %-5%). The root mean square error (RMSE) between the PCD-CT-acquired FF and the reference standard ranged from 1.0 % to 5.0 %, among which the high-pitch scan at 120 kV with IQ20 accounted for the lowest RMSE (1.0 %). The spiral scan at 120 kV with IQ20 and IQ80 yielded the lowest bias (mean value: 1.19 % and 1.23 %, respectively). CONCLUSION: Fat quantification using PCD-CT reconstructed at 70 keV was accurate and stable under various scan settings. PCD-CT has great potential for fat quantification using ultralow radiation doses.

Resting-state functional connectivity of goal-directed and habitual-learning systems: The efficacy of cognitive-behavioral therapy for obsessive-compulsive disorder.

BACKGROUND: There is an imbalance between goal-directed and habitual-learning system in patients with obsessive-compulsive disorder (OCD). At present, the relationship between cognitive behavior therapy (CBT) as a first-line therapy and goal-directed and habitual-learning disorder is still unclear. We attempted to discuss the effect of CBT treatment in patients with OCD, using abnormalities in goal-directed and habitual-learning-related brain regions at baseline as predictive factors. METHODS: A total of 71 subjects, including 35 OCD patients and 36 healthy controls, were recruited. The OCD patients underwent 8 weeks of CBT. These patients were divided into two groups based on treatment response (Nresponders = 18, Nnonresponders = 17). Further subgroup analysis was conducted based on disease duration (Nshort = 17, Nlong = 18) and age of onset (Nearly = 14, Nlate = 21). We collected resting-state ROI-ROI functional connectivity data and apply repeated-measures linear mixed-effects models to investigate the differences of different subgroups. RESULTS: CBT led to symptom improvement in OCD patients, with varying degrees of effectiveness across subgroups. The orbitofrontal cortex (OFC) and insula, key regions for goal-directed behavior and habitual-learning, respectively, showed significant impacts on CBT efficacy in subgroups with different disease durations and ages of onset. CONCLUSION: The findings suggest that the goal-directed system may influence the efficacy of CBT through goal selection, maintenance, and emotion regulation. Furthermore, we found that disease duration and age of onset may affect treatment outcomes by modulating functional connectivity between goal-directed and habitual-learning brain regions.

Pre-PCI CT-FFR Predicts Target Vessel Failure After Stent Implantation.

OBJECTIVES: To investigate the predictive value of coronary computed tomography angiography-derived fractional flow reserve (CT-FFR) before percutaneous coronary intervention (PCI) to predict target vessel failure (TVF) after stent implantation. METHODS: This retrospective study included 429 patients (429 vessels) who underwent PCI and stent implantation after CCTA within 3 months. All patients underwent coronary stent implantation between January 2012 and December 2019. A dedicated workstation (Syngo Via, Siemens) was used to analyze and measure the CT-FFR value. The cut-off values of pre-PCI CT-FFR for predicting TVF were defined as 0.80 and the value using the log-rank maximization method, respectively. The primary outcome was TVF, defined as a composite of cardiac death, target vessel myocardial infarction, and clinically driven target vessel revascularization (TVR), which was a secondary outcome. RESULTS: During a median 64.0 months follow-up, the cumulative incidence of TVF was 7.9% (34/429). The cutoff value of pre-PCI CT-FFR based on the log-rank maximization method was 0.74, which was the independent predictor for TVF [hazard ratio (HR): 2.61 (95% CI: 1.13, 6.02); P =0.024] and TVR [HR: 3.63 (95%CI: 1.25, 10.51); P =0.018]. Compared with the clinical risk factor model, pre-PCI CT-FFR significantly improved the reclassification ability for TVF [net reclassification improvement (NRI), 0.424, P <0.001; integrative discrimination index (IDI), 0.011, P =0.022]. Adding stent information to the prediction model resulted in an improvement in reclassification for the TVF (C statistics: 0.711, P =0.001; NRI: 0.494, P <0.001; IDI: 0.020, P =0.028). CONCLUSIONS: Pre-PCI CT-FFR ≤0.74 was an independent predictor for TVF or TVR, and integration of clinical, pre-PCI CT-FFR, and stent information models can provide a better risk stratification model in patients with stent implantation.

Using Dual-source Photon-counting Detector CT to Simultaneously Quantify Fat and Iron Content: A Phantom Study.

RATIONALE AND OBJECTIVES: To evaluate the feasibility of using photon-counting detector computed tomography (PCD CT) to simultaneously quantify fat and iron content MATERIALS AND METHODS: Phantoms with pure fat, pure iron and fat-iron deposition were scanned by two tube voltages (120 and 140 kV) and two image quality (IQ) settings (80 and 145). Using an iron-specific three-material decomposition algorithm, virtual noniron (VNI) and virtual iron content (VIC) images were generated at quantum iterative reconstruction (QIR) strength levels 1-4. RESULTS: Significant linear correlations were observed between known fat content (FC) and VNI for pure fat phantoms (r = 0.981-0.999, p < 0.001) and between known iron content (IC) and VIC for pure iron phantoms (r = 0.897-0.975, p < 0.001). In fat-iron phantoms, the measurement for fat content of 5-30% demonstrated good linearity between FC and VNI (r = 0.919-0.990, p < 0.001), and VNI were not affected by 75, 150, and 225 µmol/g iron overload (p = 0.174-0.519). The measurement for iron demonstrated a linear range of 75-225 µmol/g between IC and VIC (r = 0.961-0.994, p < 0.001) and VIC was not confounded by the coexisting 5%, 20%, and 30% fat deposition (p = 0.943-0.999). The Bland-Altman of fat and iron measurements were not significantly different at varying tube voltages and IQ settings (all p > 0.05). No significant difference in VNI and VIC at QIR 1-4. CONCLUSION: PCD CT can accurately and simultaneously quantify fat and iron, including scan parameters with lower radiation dose.

Pathogenic role of different phenotypes of immune cells in airway allergic diseases: a study based on Mendelian randomization.

Background: Airway allergic disease (AAD) is a class of autoimmune diseases with predominantly Th2-type inflammation, mainly including allergic rhinitis (AR), allergic asthma (AS), and chronic sinusitis (CRS). There are very complex regulatory mechanisms between immune cells and AAD; however, previous reports found that the functions of the same immune cells in AAD are not identical. Objective: The aim of this study was to explore the causal relationship between different phenotypic immune cells and their association with AAD. Method: Utilizing the publicly available Genome-Wide Association Studies (GWAS) database, this study conducted a bidirectional Mendelian randomization (MR) to assess the causal relationship between immune cells of 731 different immunophenotypes and AAD. The primary assessment methods included inverse variance weighting, weighted median, and MR Egger. Additionally, sensitivity analyses such as MR-PRESSO, leave-one-out, and scatter plots were employed to eliminate the interference of heterogeneity and pleiotropy, ensuring the stability of the causal inference. Result: A total of 38 immune cells with different immunophenotypes were found to be positively and causally associated with AR, of which 26 were protective factors and 12 were risk factors. Positive associations were found between 33 immune cells and AS, of which 14 were protective factors and 19 were risk factors, as well as between 39 immune cells and CRS, of which 22 were protective factors and 17 were risk factors. Finally, the results of all relevant immune cells for the three diseases were taken and intersected, and it was found that CD3 on CD39+-activated Treg (IVWAR = 0.001, IVWCRS = 0.043, IVWAS = 0.027) may be the key immune cell that inhibits the development of AAD (ORAR = 0.940, ORAS = 0.967, ORCRS = 0.976). Conclusion: This study reveals that different immune phenotypes of immune cells are closely related to AAD at the genetic level, which provides a theoretical basis for future clinical studies.

CT-derived Radiomics Predicts the Efficacy of Tyrosine Kinase Inhibitors in Osteosarcoma Patients with Pulmonary Metastasis.

BACKGROUND: To construct and validate the CT-based radiomics model for predicting the tyrosine kinase inhibitors (TKIs) effects in osteosarcoma (OS) patients with pulmonary metastasis. METHODS: OS patients with pulmonary metastasis treated with TKIs were randomly separated into training and testing cohorts (2:1 ratio). Radiomic features were extracted from the baseline unenhanced chest CT images. The random survival forest (RSF) and Kaplan-Meier survival analyses were performed to construct and evaluate radiomics signatures (R-model-derived). The univariant and multivariant Cox regression analyses were conducted to establish clinical (C-model) and combined models (RC-model). The discrimination abilities, goodness of fit and clinical benefits of the three models were assessed and validated in both training and testing cohorts. RESULTS: A total of 90 patients, 57 men and 33 women, with a mean age of 18 years and median progression-free survival (PFS) of 7.2 months, were enrolled. The R-model was developed with nine radiomic features and demonstrated significant predictive and prognostic values. In both training and testing cohorts, the time-dependent area under the receiver operating characteristic curves (AUC) of the R-model and RC-model exhibited obvious superiority over C-model. The calibration and decision curve analysis (DCA) curves indicated that the accuracy of the R-model was comparable to RC-model, which exhibited significantly better performance than C-model. CONCLUSIONS: The R-model showed promising potential as a predictor for TKI responses in OS patients with pulmonary metastasis. It can potentially identify pulmonary metastatic OS patients most likely to benefit from TKIs treatment and help guide optimized clinical decisions.

Improvement of coronary stent visualization using ultra-high-resolution photon-counting detector CT.

OBJECTIVES: This study aimed to compare the image quality and diagnostic performance of standard-resolution (SR) and ultra-high-resolution (UHR) coronary CT angiography (CCTA) based on photon-counting detector CT (PCD-CT) of coronary stents and explore the best reconstruction kernel for stent imaging. METHODS: From July 2023 to September 2023, patients were enrolled to undergo CCTA using a dual-source PCD-CT system after coronary angioplasty with stent placement. SR images with a slice thickness/increment of 0.6/0.4 mm were reconstructed using a vascular kernel (Bv48), while UHR images with a slice thickness/increment of 0.2/0.2 mm were reconstructed using vascular kernels of six sharpness levels (Bv48, Bv56, Bv60, Bv64, Bv72, and Bv76). The in-stent lumen diameters were evaluated. Subjective image quality was also evaluated by a 5-point Likert scale. Invasive coronary angiography was conducted in 12 patients (25 stents). RESULTS: Sixty-nine patients (68.0 [61.0, 73.0] years, 46 males) with 131 stents were included. All UHR images had significantly larger in-stent lumen diameter than SR images (p < 0.001). Specifically, UHR-Bv72 and UHR-Bv76 for in-stent lumen diameter (2.17 [1.93, 2.63] mm versus 2.20 [1.93, 2.59] mm) ranked the two best kernels. The subjective analysis demonstrated that UHR-Bv72 images had the most pronounced effect on reducing blooming artifacts, showcasing in-stent lumen and stent demonstration, and diagnostic confidence (p < 0.001). Furthermore, SR and UHR-Bv72 images showed a diagnostic accuracy of 78.3% (95% confidence interval [CI]: 56.3%-92.5%) and 88.0% (95%CI: 68.8%-97.5%), respectively. CONCLUSION: UHR CCTA by PCD-CT leads to significantly improved visualization and diagnostic performance of coronary stents, and Bv72 is the optimal reconstruction kernel showing the stent struts and in-stent lumen. CLINICAL RELEVANCE STATEMENT: The significantly improved visualization of coronary stents using ultra-high resolution CCTA could increase the diagnostic accuracy for in-stent restenosis and avoid unnecessary invasive quantitative coronary angiography, thus changing the clinical management for patients after percutaneous coronary intervention. KEY POINTS: Coronary stent imaging is challenging with energy-integrating detector CT due to "blooming artifacts." UHR images using a PCD-CT enhanced coronary stent visualization. UHR coronary stent imaging demonstrated improved diagnostic accuracy in clinical settings.

CT radiomic features reproducibility of virtual non-contrast series derived from photon-counting CCTA datasets using a novel calcium-preserving reconstruction algorithm compared with standard non-contrast series: focusing on epicardial adipose tissue.

PURPOSE: We aimed to evaluate the reproducibility of computed tomography (CT) radiomic features (RFs) about Epicardial Adipose Tissue (EAT). The features derived from coronary photon-counting computed tomography (PCCT) angiography datasets using the PureCalcium (VNCPC) and conventional virtual non-contrast (VNCConv) algorithm were compared with true non-contrast (TNC) series. METHODS: RFs of EAT from 52 patients who underwent PCCT were quantified using VNCPC, VNCConv, and TNC series. The agreement of EAT volume (EATV) and EAT density (EATD) was evaluated using Pearson's correlation coefficient and Bland-Altman analysis. A total of 1530 RFs were included. They are divided into 17 feature categories, each containing 90 RFs. The intraclass correlation coefficients (ICCs) and concordance correlation coefficients (CCCs) were calculated to assess the reproducibility of RFs. The cutoff value considered indicative of reproducible features was > 0.75. RESULTS: the VNCPC and VNCConv tended to underestimate EATVs and overestimate EATDs. Both EATV and EATD of VNCPC series showed higher correlation and agreement with TNC than VNCConv series. All types of RFs from VNCPC series showed greater reproducibility than VNCConv series. Across all image filters, the Square filter exhibited the highest level of reproducibility (ICC = 67/90, 74.4%; CCC = 67/90, 74.4%). GLDM_GrayLevelNonUniformity feature had the highest reproducibility in the original image (ICC = 0.957, CCC = 0.958), exhibiting a high degree of reproducibility across all image filters. CONCLUSION: The accuracy evaluation of EATV and EATD and the reproducibility of RFs from VNCPC series make it an excellent substitute for TNC series exceeding VNCConv series.

Resting-state functional connectivity of amygdala subregions predicts treatment outcome for cognitive behavioral therapy in obsessive-compulsive disorder at a 4-month follow-up.

BACKGROUND: Cognitive behavioral therapy (CBT) is considered as the first-line treatment for obsessive-compulsive disorder (OCD). However, the underlying neural mechanisms through which CBT exerts its effects in OCD remain unclear. This study aims to investigate whether the improvement of clinical symptoms in OCD patients after CBT treatment is associated with changes in resting-state functional connectivity (FC) of the amygdala subregion, and whether these changes can be served as potential predictors of four-months treatment efficacy. METHODS: We collected resting-state functional magnetic resonance imaging (rs-fMRI) data from 57 OCD patients and 50 healthy subjects at baseline. In the patient group, rs-fMRI was also obtained after completion of an 8-week CBT treatment and 4 months post-treatment. A whole-brain rsFC analysis was conducted using the amygdala subregion as the seed point. We analyzed the FC patterns in relation to 4 months clinical outcomes to elucidate the long-term efficacy of CBT in OCD patients. RESULTS: Treatment responseat at pre-treatment was found to be associated with reduced rsFC between the left basolateral amygdala(BLA)and left superior temporal gyrus(STG) at baseline. Lower pre-treatment FC were negatively correlated with the severity of OCD symptoms as measured by the Yale-Brown Obsessive Compulsive Severity Scale (Y-BOCS). Moreover, the area under the receiver operating characteristic (ROC) curve for the FC between the left BLA and STG at the end of treatment was 73.0% and 70.4% for the effective-ineffective and remitted or unremitted groups, respectively. At the 4-month follow-up, the area under the ROC curve for the effective-ineffective and remitted or unremitted groups was 83.9% and 76.5%, respectively. CONCLUSION: These findings suggest that brain functional activity in patients with OCD can predict treatment response to CBT, and longitudinal changes in relevant brain functional activity following CBT treatment are associated with treatment response in OCD.

A Bibliometric Analysis of Scientific Publications on Eating Disorder Prevention in the Past Three Decades.

BACKGROUND: Eating disorders (EDs) present a growing concern due to their widespread occurrence and chronic course, the low access to evidence-based treatment, and the significant burden they place on the patients and society. This picture justifies intensive focus on the prevention of EDs. The current study provides the first bibliometric analysis of research on the prevention of EDs, focusing on trends and contributions, to prompt further prevention research. METHODS: We conducted a bibliometric analysis of publications on the prevention of EDs using the Web of Science database, from 1993 to 2023. Focusing on universal and selective prevention strategies, our study involved a rigorous selection process, narrowing down from 10,546 to 383 relevant papers through manual screening. The analysis utilized the "bibliometrix" R package (version 4.2.2) and Python (version 3.9.6) for data processing, with VOSviewer employed for mapping collaboration networks. RESULTS: Our analysis revealed a consistent annual growth rate of 10.85% in ED prevention research publications, with significant contributions from the "International Journal of Eating Disorders" and some notable authors. The United States emerged as the dominant contributor. The analysis also highlighted key trends, including a surge in publications between 2010 and 2017, and the role of major institutions in advancing research in this field. DISCUSSION: The increasing rate of publications on the prevention of EDs is encouraging. However, the actual number of studies on the prevention of EDs are limited, and the majority of this work is performed by a few research groups. Given the high concentration of publications within a few countries and research groups, increased funding, facilitation of prevention research on a wider scale, and engagement of more researchers and further collaboration are called for.

Comparison of machine learning-based CT fractional flow reserve with cardiac MR perfusion mapping for ischemia diagnosis in stable coronary artery disease.

OBJECTIVES: To compare the diagnostic performance of machine learning (ML)-based computed tomography-derived fractional flow reserve (CT-FFR) and cardiac magnetic resonance (MR) perfusion mapping for functional assessment of coronary stenosis. METHODS: Between October 2020 and March 2022, consecutive participants with stable coronary artery disease (CAD) were prospectively enrolled and underwent coronary CTA, cardiac MR, and invasive fractional flow reserve (FFR) within 2 weeks. Cardiac MR perfusion analysis was quantified by stress myocardial blood flow (MBF) and myocardial perfusion reserve (MPR). Hemodynamically significant stenosis was defined as FFR ≤ 0.8 or > 90% stenosis on invasive coronary angiography (ICA). The diagnostic performance of CT-FFR, MBF, and MPR was compared, using invasive FFR as a reference. RESULTS: The study protocol was completed in 110 participants (mean age, 62 years ± 8; 73 men), and hemodynamically significant stenosis was detected in 36 (33%). Among the quantitative perfusion indices, MPR had the largest area under receiver operating characteristic curve (AUC) (0.90) for identifying hemodynamically significant stenosis, which is in comparison with ML-based CT-FFR on the vessel level (AUC 0.89, p = 0.71), with comparable sensitivity (89% vs 79%, p = 0.20), specificity (87% vs 84%, p = 0.48), and accuracy (88% vs 83%, p = 0.24). However, MPR outperformed ML-based CT-FFR on the patient level (AUC 0.96 vs 0.86, p = 0.03), with improved specificity (95% vs 82%, p = 0.01) and accuracy (95% vs 81%, p < 0.01). CONCLUSION: ML-based CT-FFR and quantitative cardiac MR showed comparable diagnostic performance in detecting vessel-specific hemodynamically significant stenosis, whereas quantitative perfusion mapping had a favorable performance in per-patient analysis. CLINICAL RELEVANCE STATEMENT: ML-based CT-FFR and MPR derived from cardiac MR performed well in diagnosing vessel-specific hemodynamically significant stenosis, both of which showed no statistical discrepancy with each other. KEY POINTS: • Both machine learning (ML)-based computed tomography-derived fractional flow reserve (CT-FFR) and quantitative perfusion cardiac MR performed well in the detection of hemodynamically significant stenosis. • Compared with stress myocardial blood flow (MBF) from quantitative perfusion cardiac MR, myocardial perfusion reserve (MPR) provided higher diagnostic performance for detecting hemodynamically significant coronary artery stenosis. • ML-based CT-FFR and MPR from quantitative cardiac MR perfusion yielded similar diagnostic performance in assessing vessel-specific hemodynamically significant stenosis, whereas MPR had a favorable performance in per-patient analysis.

Effect of tempo on the age-related changes in temporal expectation driven by rhythms.

Temporal expectation refers to the capacity to allocate resources at a particular point in time, enabling us to enhance our behavior performance. Empirical evidence indicates that, among younger adults, temporal expectation can be driven by rhythm (i.e., regular sequences of stimuli). However, whether there are age-related changes in rhythm-based temporal expectation has not been clearly established. Furthermore, whether tempo can influence the relationship between rhythm-based temporal expectation and aging remains unexplored. To address these questions, both younger and older participants took part in a rhythm-based temporal expectation task, engaging three distinct tempos: 600 ms (fast), 1800 ms (moderate), or 3000 ms (slow). The results demonstrated that temporal expectation effects (i.e., participants exhibited significantly faster responses during the regular trials compared to the irregular trials) were observed in both the younger and older participants under the moderate tempo condition. However, in the fast and slow tempo conditions, the temporal expectation effects were solely observed in the younger participants. These findings revealed that rhythm-based temporal expectations can be preserved during aging but within a specific tempo range. When the tempo falls within the range of either being too fast or too slow, it can manifest age-related declines in temporal expectations driven by rhythms.