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.

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.

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.

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.

Consistency of Monoenergetic Attenuation Measurements for a Clinical Dual-Source Photon-Counting Detector CT System Across Scanning Paradigms: A Phantom Study.

BACKGROUND. Use of virtual monoenergetic images (VMIs) from multienergy CT scans can mitigate inconsistencies in traditional attenuation measurements that result from variation in scan-related factors. Photon-counting detector (PCD) CT systems produce VMIs as standard image output under flexible scanning conditions. OBJECTIVE. The purpose of this article was to evaluate the consistency of monoenergetic attenuation measurements obtained from a clinical PCD CT scanner across a spectrum of scanning paradigms. METHODS. A phantom with 10 tissue-simulating inserts was imaged using a clinical dual-source PCD CT scanner. Nine scanning paradigms were obtained across combinations of tube voltages (90, 120, and 140 kVp) and image quality (IQ) levels (80, 145, and 180). Images were reconstructed at VMI levels of 50, 60, 70, and 80 keV. Consistency of attenuation measurements was assessed, using the 120 kVp with IQ level of 145 scanning paradigm as the reference scan. RESULTS. For all scanning paradigms, attenuation measurements showed intra-class correlation of 0.999 and higher with respect to the reference scan. Across inserts, mean bias relative to the reference scan ranged from -14.9 to 13.6 HU, -2.7 to 1.7 HU, and -3.9 to 3.8 HU at tube voltages of 90, 120, and 140 kVp, respectively; and from -14.9 to 13.6 HU, -6.4 to 3.8 HU, -3.7 to 1.4 HU, and -7.2 to 4.3 HU at VMI levels of 50, 60, 70, and 80 keV, respectively. Thus, mean bias did not exceed 5 HU for any insert at tube potentials of 120 kVp and 140 kVp, nor for any insert at a VMI level of 70 keV. At a VMI level of 50 keV and tube potential of 90 kVp, mean bias exceeded 5 HU for 14 of 30 possible combinations of inserts and scanning paradigms and exceeded 10 HU for four of 30 such combinations. At VMI levels of both 60 and 80 keV, mean bias exceeded 5 HU for only two combinations of inserts and scanning paradigms, all at a tube potential of 90 kVp. CONCLUSION. PCD CT generally provided consistent attenuation measurements across combinations of scanning paradigms and VMI levels. CLINICAL IMPACT. PCD CT may facilitate quantitative applications of CT data in clinical practice.

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.

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.

Abnormalities of structural covariance of insular subregions in drug-naïve OCD patients.

The insula plays a significant role in the neural mechanisms of obsessive-compulsive disorder. Previous studies have identified functional and structural abnormalities in insula in obsessive-compulsive disorder patients. The predictive coding model in the context of interoception can explain the psychological and neuropathological manifestations observed in obsessive-compulsive disorder. The model is based on the degree of laminar differentiation of cerebral cortex. The interindividual differences in a local measure of brain structure often covary with interindividual differences in other brain regions. We investigated the anatomical network involving the insula in a drug-naïve obsessive-compulsive disorder sample. We recruited 58 obsessive-compulsive disorder patients and 84 matched health controls. The cortical thickness covariance maps between groups were compared at each vertex. We also evaluated the modulation of Yale-Brown Obsessive-Compulsive Scale scores and obsessive-compulsive disorder duration on thickness covariance. Our findings indicated that the thickness covariance seeded from granular and dysgranular insula are different compared with controls. The duration and severity of obsessive-compulsive disorder can modulate the thickness covariance of granular and dysgranular insula with posterior cingulate cortex and rostral anterior cingulate cortex. Our results revealed aberrant insular structural characteristics and cortical thickness covariance in obsessive-compulsive disorder patients, contributing to a better understanding of the involvement of insula in the pathological mechanisms underlying obsessive-compulsive disorder.

Altered brain functional network topology in Obsessive-Compulsive Disorder: A comparison of patients with varying severity of depressive symptoms and the impact on psychosocial functioning.

BACKGROUND: Obsessive-compulsive disorder (OCD) is associated with psychosocial impairment, which can be exacerbated by depressive symptoms. In this study, we employed graph theory analysis to investigate the association among neuroimaging, clinical features, and psychosocial functioning in OCD patients, with a specific focus on the differential impact of depressive symptoms. METHODS: 216 OCD patients were divided into two subgroups based on depressive symptoms. Resting-state functional MRI data were acquired from a subset of 106 OCD patients along with 77 matched healthy controls (HCs). We analyzed the topological characteristics of the entire brain and the cognition-related subnetworks and performed Pearson correlation analyses to further explore the relationship with psychosocial functioning. RESULTS: OCD patients with more severe depressive symptoms exhibited greater impairment across all dimensions of psychosocial functioning. Graph theory analysis revealed more pronounced reductions in network efficiency within the entire brain, the default mode network (DMN), and the cingulo-opercular network (CON) among patients with non or mild depressive symptoms. Lower nodal efficiency and degree centrality of the right superior temporal gyrus (STG) were found in OCD patients and these variables were positively correlated with psychosocial functioning impairment. CONCLUSIONS: This study revealed that the presence of depressive symptoms generally exacerbated psychosocial functioning impairment in OCD patients. Abnormalities in the functional integration of the entire brain, the DMN, and the CON in OCD patients may comprise the basis of cognitive deficits, while dysfunction of the right STG may affect the psychosocial functioning through its role in emotion, intention perception, and insight.

Quantification of bone quality and distribution of the proximal humerus with dual-energy computed tomography.

Background: The proximal humerus is a common site of osteoporotic fractures, and bone quality is a predictor of surgical reduction quality. Dual-energy computed tomography (DECT) is assuming an increasingly important role in the quantification of bone mineral density (BMD) due it is ability to perform three-material decomposition. We aimed to analyze the bone quality and distribution of the proximal humerus with DECT quantitatively. Methods: Sixty-five consecutive patients (average age 49.5±15.2 years; male: female ratio 32:33) without proximal humerus fractures who had undergone DECT were retrospectively selected. The humeral head was divided into 4 regions on a cross section in the medial plane between the greater tuberosity and the surgical neck. The quantitative parameters, including virtual noncalcium (VNCa) value, computed tomography value of calcium (CaCT), computed tomography value of mixed-energy images (regular CT value) (rCT), and relative calcium density (rCaD), were measured. The correlations between the quantitative parameters and age and body mass index (BMI) were analyzed, and the correlations of age, sex, BMI, region of the humeral head, and VNCa value on CaCT were evaluated. Results: The differences in CaCT, rCT, and rCaD between the 4 regions of proximal humerus were statistically significant (P<0.001), while the difference in VNCa values was not (P=0.688). The calcium concentration (CaCT and rCaD) was the densest in the posteromedial zone. The differences of CaCT, rCT, and rCaD between males and females in the 4 regions of proximal humerus were statistically significant (P<0.05), while those of the posterolateral zone were not (rCT; P>0.05). The differences in VNCa values between males and females were also not significant (P>0.05). Multivariable linear regression analysis indicated that sex, age, BMI, regions, and VNCa were significant (P<0.05) predictors of the CaCT value. Conclusions: The concentration of calcium was the densest in the posteromedial region of proximal humerus, and the VNCa value of DECT may be used for quantifying the BMD of the proximal humerus.

Aging effect of cross-modal interactions during audiovisual detection and discrimination by behavior and ERPs.

Introduction: Numerous studies have shown that aging greatly affects audiovisual integration; however, it is still unclear when the aging effect occurs, and its neural mechanism has yet to be fully elucidated. Methods: We assessed the audiovisual integration (AVI) of older (n = 40) and younger (n = 45) adults using simple meaningless stimulus detection and discrimination tasks. The results showed that the response was significantly faster and more accurate for younger adults than for older adults in both the detection and discrimination tasks. The AVI was comparable for older and younger adults during stimulus detection (9.37% vs. 9.43%); however, the AVI was lower for older than for younger adults during stimulus discrimination (9.48% vs. 13.08%) behaviorally. The electroencephalography (EEG) analysis showed that comparable AVI amplitude was found at 220-240 ms for both groups during stimulus detection and discrimination, but there was no significant difference between brain regions for older adults but a higher AVI amplitude in the right posterior for younger adults. Additionally, a significant AVI was found for younger adults in 290-310 ms but was absent for older adults during stimulus discrimination. Furthermore, significant AVI was found in the left anterior and right anterior at 290-310 ms for older adults but in the central, right posterior and left posterior for younger adults. Discussion: These results suggested that the aging effect of AVI occurred in multiple stages, but the attenuated AVI mainly occurred in the later discriminating stage attributed to attention deficit.

Sustained visual attentional load modulates audiovisual integration in older and younger adults.

Previous studies have shown that attention influences audiovisual integration (AVI) in multiple stages, but it remains unclear how AVI interacts with attentional load. In addition, while aging has been associated with sensory-functional decline, little is known about how older individuals integrate cross-modal information under attentional load. To investigate these issues twenty older adults and 20 younger adults were recruited to conduct a dual task including a multiple object tracking (MOT) task, which manipulated sustained visual attentional load, and an audiovisual discrimination task, which assesses AVI. The results showed that response times were shorter and hit rate was higher for audiovisual stimuli than for auditory or visual stimuli alone and in younger adults than in older adults. The race model analysis showed that AVI was higher under the load_3 condition (monitoring two targets of the MOT task) than under any other load condition (no-load [NL], one or three targets monitoring). This effect was found regardless of age. However, AVI was lower in older adults than younger adults under NL condition. Moreover, the peak latency was longer, and the time window of AVI was delayed in older adults compared to younger adults under all conditions. These results suggest that slight visual sustained attentional load increased AVI but that heavy visual sustained attentional load decreased AVI, which supports the claim that attention resource was limited, and we further proposed that AVI was positively modulated by attentional resource. Finally, there were substantial impacts of aging on AVI; AVI was delayed in older adults.

Computed Tomography Radiomics Model Predicts Procedure Success of Coronary Chronic Total Occlusions.

BACKGROUND: Coronary computed tomography (CT) angiography imaging is useful for the preprocedural evaluation of chronic total occlusion (CTO). However, the predictive value of CT radiomics model for successful percutaneous coronary intervention (PCI) has not been studied. We aimed to develop and validate a CT radiomics model for predicting PCI success of CTOs. METHODS: In this retrospective study, a radiomics-based model for predicting PCI success was developed on the training and internal validation sets of 202 and 98 patients with CTO, collected from 1 tertiary hospital. The proposed model was validated on an external test set of 75 CTO patients enrolled from another tertiary hospital. CT radiomics features of each CTO lesion were manually labeled and extracted. Other anatomical parameters, including occlusion length, entry morphology, tortuosity, and calcification burden, were also measured. Fifteen radiomics features, 2 quantitative plaque features, and CT-derived Multicenter CTO Registry of Japan score were used to train different models. The predictive values of each model were evaluated for predicting revascularization success. RESULTS: In the external test set, 75 patients (60 men; 65 years [58.5, 71.5]) with 83 CTO lesions were assessed. Occlusion length was shorter (13.00 mm versus 29.30 mm, P=0.007) in PCI success group whereas the presence of tortuous course was more commonly presented in PCI failure group (1.49% versus 25.00%, P=0.004). The radiomics score was significantly smaller in PCI success group (0.10 versus 0.55, P<0.001). The area under the curve of CT radiomics-based model was significantly higher than that of CT-derived Multicenter CTO Registry of Japan score for predicting PCI success (area under the curve=0.920 versus 0.752, P=0.008). The proposed radiomics model accurately identified 89.16% (74/83) CTO lesions with procedure success. CONCLUSIONS: CT radiomics-based model outperformed CT-derived Multicenter CTO Registry of Japan score for predicting PCI success. The proposed model is more accurate than the conventional anatomical parameters to identify CTO lesions with PCI success.

A copper foam-based surface-enhanced Raman scattering substrate for glucose detection.

Raman spectroscopy can quickly achieve non-destructive, qualitative and quantitative detection, and analysis the molecular structure of substances. Herein, a facile and low-cost method for preparation of highly sensitivity SERS substrates was implemented through the displacement reaction of copper foam immersed in AgNO3 ethanol solution. Due to the 3D structure of copper film and homogenous displacement, the Ag-Cu substrate showed high performance SERS enhancement (1.25 × 107), and the lowest detection concentration for R6G reached 10-10 Mol/L. For glucose detection, mixed decanethiol (DT)/mercaptohexanol (MH) interlayer was used to enable glucose attach to the substrate surface, and the limit of detection reached to 1 uM/L. SERS substrate makes the Ag-Cu SERS substrate promising for biological applications.

CT-Based Radiomic Score: A Risk Stratifier in Far-Advanced Gastric Cancer Patients.

OBJECTIVES: To prolong the survival, the value of a computed tomography-based radiomic score (RS) in stratifying survival and guiding personalized chemotherapy strategies in far-advanced gastric cancer (FGC) was investigated. MATERIALS AND METHODS: This retrospective multicenter study enrolled 283 FGC patients (cT4a/bNxM0-1) from three centers. Patients from one center were randomly divided into the training (n = 166) and internal validation (n = 83) cohorts, whereas the external validation cohort (n = 34) consisted of patients from the two other centers. The RS was calculated for each patient to predict progression-free survival (PFS). Features from the primary tumor and main metastasis (peritoneum, liver, and lymph node) were integrated in the training cohort and then validated for its ability to stratify PFS and overall survival (OS) in the validation cohort. The association between the RS and efficacy of neoadjuvant intraperitoneal and systemic (NIPS) therapy was also explored. RESULTS: The RS demonstrated a favorable prognostic ability to predict PFS in all cohorts (training: C-index 0.83, 95% confidence interval [CI]: 0.788-0.872; internal validation: C-index 0.75, 95% CI: 0.682-0.818; external validation: C-index 0.76, 95% CI: 0.669-0.851; all p < 0.05), as well as an excellent ability to stratify the PFS and OS in both the whole population and metastatic subgroups (p < 0.05). Patients with a low score were more likely to undergo surgery after perioperative chemotherapy (p < 0.05). Furthermore, only high-scoring patients with peritoneal metastasis benefited from NIPS. CONCLUSION: The RS may be an effective risk stratifier for the outcomes of FGC patients and may be used to select patients who can benefit from NIPS therapy.

Prognostic value of preoperative CT features for disease-free survival in patients with primary gastric gastrointestinal stromal tumors after resection.

PURPOSE: Tumor size is an important prognostic factor without consideration of the necrotic and cystic components within tumor for patients with gastrointestinal stromal tumors (GISTs). We aimed to extract the enhancing viable component from the tumor using computed tomography (CT) post-processing software and evaluate the value of preoperative CT features for predicting the disease-free survival (DFS) after curative resection for patients with primary gastric GISTs. METHODS: 132 Patients with primary gastric GISTs who underwent preoperative contrast-enhanced CT and curative resection were retrospectively analyzed. We used a certain CT attenuation of 30 HU to extract the enhancing tissue component from the tumor. Enhancing tissue volume and other CT features were assessed on venous-phase images. We evaluated the value of preoperative CT features for predicting the DFS after surgery. Univariate and multivariate Cox regression analyses were performed to find the independent risk factor for predicting the DFS. RESULTS: Of the 132 patients, 68 were males and 64 were females, with a mean age of 61 years. The median follow-up duration was 60 months, and 28 patients experienced disease recurrence and distant metastasis during the follow-up period. Serosal invasion (p < 0.001; HR = 5.277) and enhancing tissue volume (p = 0.005; HR = 1.447) were the independent risk factors for predicting the DFS after curative resection for patients with primary gastric GISTs. CONCLUSION: Preoperative contrast-enhanced CT could be useful for predicting the DFS after the surgery of gastric GISTs, and serosal invasion and enhancing tissue volume were the independent risk factors.

Efficacy and prognostic value of delta radiomics on dual-energy computed tomography for gastric cancer with neoadjuvant chemotherapy: a preliminary study.

BACKGROUND: A non-invasive tool for tumor regression grade (TRG) evaluation is urgently needed for gastric cancer (GC) treated with neoadjuvant chemotherapy (NAC). PURPOSE: To develop and validate a radiomics signature (RS) to evaluate TRG for locally advanced GC after NAC and assess its prognostic value. MATERIAL AND METHODS: A total of 103 patients with GC treated with NAC were retrospectively recruited from April 2018 to December 2019 and were randomly allocated into a training cohort (n = 69) and a validation cohort (n = 34). Delineation was performed on both mixed and iodine-uptake images based on dual-energy computed tomography (DECT). A total of 4094 radiomics features were extracted from the pre-NAC, post-NAC, and delta feature sets. Spearman correlation and the least absolute shrinkage and selection operator were used for dimensionality reduction. Multivariable logistic regression was used for TRG evaluation and generated the optimal RS. Kaplan-Meier survival analysis with the log-rank test was implemented in an independent cohort of 40 patients to validate the prognostic value of the optimal RS. RESULTS: Three, five, and six radiomics features were finally selected for the pre-NAC, post-NAC, and delta feature sets. The delta model demonstrated the best performance in assessing TRG in both the training and the validation cohorts (AUCs=0.91 and 0.76, respectively; P>0.1). The optimal RS from the delta model showed a significant capability to predict survival in the independent cohort (P<0.05). CONCLUSION: Delta radiomics based on DECT images serves as a potential biomarker for TRG evaluation and shows prognostic value for patients with GC treated with NAC.

Correction: A hybrid GaN/Ga2O3 structure anchored on carbon cloth as a high-performance electrode of supercapacitors.

Correction for 'A hybrid GaN/Ga2O3 structure anchored on carbon cloth as a high-performance electrode of supercapacitors' by Yan-Ling Hu, et al., Dalton Trans., 2022, https://doi.org/10.1039/d2dt02904a.