Deep learning-based fully automatic screening of carotid artery plaques in computed tomography angiography: a multicenter study.

AIM: To develop and validate a deep learning (DL) algorithm for the automated detection and classification of carotid artery plaques (CAPs) on computed tomography angiography (CTA) images. MATERIALS AND METHODS: This retrospective study enrolled 400 patients (300 in the Center Ⅰ and 100 in Ⅱ). Three radiologists co-labeled CAPs, and their revised calcification status (noncalcified, mixed, and calcified) was regarded as ground truth. Center Ⅰ patients were randomly divided into training and internal validation datasets, while Center Ⅱ patients served as the external validation dataset. Carotid artery regions were segmented using a modified 3D-UNet network, followed by CAPs detection and classification using a ResUNet-based architecture in a two-step DL system. The DL model's detection and classification performance were evaluated on the validation dataset using precision-recall curve, free-response receiver operating characteristic (fROC) curve, Cohen's kappa, and ROC curve analysis. RESULTS: The DL model had achieved 83.4% sensitivity at 3.0 false positives (FPs)/CTA scan in internal validation and 78.9% in external validation. F1-scores were 0.764 and 0.769 at the optimal threshold, and area under fROC curves were 0.756 and 0.738, respectively, indicating good overall accuracy for CAP detection. The DL model also showed good performance for the ternary classification of CAPs, with Cohen's kappa achieved 0.728 and 0.703 in both validation datasets. CONCLUSION: This study demonstrated the feasibility of using a fully automated DL-based algorithm for the detection and ternary classification of CAPs, which could be helpful for the workloads of radiologists.

Development and validation of a multiphase CT radiomics nomogram for the preoperative prediction of lymphovascular invasion in patients with gastric cancer.

AIM: To develop a nomogram to predict lymphovascular invasion (LVI) in gastric cancer by integrating multiphase computed tomography (CT) radiomics and clinical risk factors. MATERIALS AND METHODS: One hundred and seventy-two gastric cancer patients (121 training and 51 validation) with preoperative contrast-enhanced CT images and clinicopathological data were collected retrospectively. The clinical risk factors were selected by univariate and multivariate regression analysis. Radiomic features were extracted and selected from the arterial phase (AP), venous phase (VP), and delayed phase (DP) CT images of each patient. Clinical risk factors, radiomic features, and integration of both were used to develop the clinical model, radiomic models, and nomogram, respectively. RESULTS: Radiomic features from AP (n=6), VP (n=6), DP (n=7) CT images and three selected clinical risk factors were used for model development. The nomogram showed better performance than the AP, VP, DP, and clinical models in the training and validation datasets, providing areas under the curves (AUCs) of 0.890 (95% CI: 0.820-0.940) and 0.885 (95% CI:0.765-0.957), respectively. All models indicated good calibration, and decision curve analysis proved that the net benefit of the nomogram was superior to that of the clinical and radiomic models throughout the vast majority of the threshold probabilities. CONCLUSIONS: The nomogram integrating multiphase CT radiomics and clinical risk factors showed favourable performance in predicting LVI of gastric cancer, which may benefit clinical practice.

TBMaLT, a flexible toolkit for combining tight-binding and machine learning.

Tight-binding approaches, especially the Density Functional Tight-Binding (DFTB) and the extended tight-binding schemes, allow for efficient quantum mechanical simulations of large systems and long-time scales. They are derived from ab initio density functional theory using pragmatic approximations and some empirical terms, ensuring a fine balance between speed and accuracy. Their accuracy can be improved by tuning the empirical parameters using machine learning techniques, especially when information about the local environment of the atoms is incorporated. As the significant quantum mechanical contributions are still provided by the tight-binding models, and only short-ranged corrections are fitted, the learning procedure is typically shorter and more transferable as it were with predicting the quantum mechanical properties directly with machine learning without an underlying physically motivated model. As a further advantage, derived quantum mechanical quantities can be calculated based on the tight-binding model without the need for additional learning. We have developed the open-source framework-Tight-Binding Machine Learning Toolkit-which allows the easy implementation of such combined approaches. The toolkit currently contains layers for the DFTB method and an interface to the GFN1-xTB Hamiltonian, but due to its modular structure and its well-defined interfaces, additional atom-based schemes can be implemented easily. We are discussing the general structure of the framework, some essential implementation details, and several proof-of-concept applications demonstrating the perspectives of the combined methods and the functionality of the toolkit.

Independent and combined associations of upper and lower limb strength with all-cause mortality in community-based older adults: findings from the Chinese Longitudinal Healthy Longevity Survey.

OBJECTIVES: Life expectancy is increasing around the world, and it has been projected that China will have the largest elderly population globally by 2033. This study aimed to examine the association of upper limb strength (ULS) and lower limb strength (LLS) with all-cause mortality based on data from the Chinese Longitudinal Healthy Longevity Survey (2012-2018). STUDY DESIGN: This is a prospective cohort study. METHODS: Participants were 2442 older adults (aged 84.98 ± 11.94 years) recruited from eight regions with a high elderly population in China. Limb muscle strength was evaluated using handgrip strength and objective physical examinations. Cox proportional hazards regression was used to analyse the association of limb muscle strength with all-cause mortality. Demographic characteristics, health status and biological markers were included as confounders. RESULTS: Over a median follow-up period of 42.2 months, 993 participants died. After adjusting for all covariates, low ULS was associated with a higher mortality risk (hazard ratio [HR] = 1.51, 95% confidence interval [CI] = 1.25-1.84), and the association of low LLS with all-cause mortality was only significant for men (HR = 1.36, 95% CI = 1.04-1.79). Participants with combined low ULS and low LLS had the highest risk of mortality compared with participants with normal limb muscle strength (HR = 2.06, 95% CI = 1.61-2.63). The combined association of ULS and LLS with mortality was robust in subgroup and sensitivity analyses. CONCLUSION: Low ULS and low LLS were independently and synergistically associated with a higher all-cause mortality risk. Considering the high prevalence of limb muscle weakness among older adults in China, especially in those aged ≥80 years, limb strength could be considered as an easy-to-perform potential mortality predictor in community health care.

Few-cycle Yb laser source at 20 kHz using multidimensional solitary states in hollow-core fibers.

We demonstrate ultrashort pulse compression from 300 fs down to 17 fs at a repetition rate of 20 kHz and 160-µJ output pulse energy (3.2 W of average power) using multidimensional solitary states (MDSS) in a 1-meter hollow-core fiber (HCF) filled with N2O. Under static pressure, thermal limitations at this repetition rate annihilate the MDSS with suppression of spectral broadening. The results obtained in differential pressure configuration mitigate thermal effects and significantly increase the range of repetition rate over which MDSS can be used to compress sub-picosecond laser pulses.

Low-dose three-dimensional CT angiography for the evaluation of posterolateral protrusion of the vertebral artery over the posterior arch of the atlas: a quantitative anatomical comparison study of the rotational and neutral positions.

AIM: To investigate the changes in relevant anatomical parameters of posterolateral protrusion of the vertebral artery (VA) between head-neck rotational and neutral positions using low-dose three-dimensional computed tomography angiography (3D-CTA). MATERIALS AND METHODS: Low-dose 3D-CTA images obtained for various craniocervical diseases in 36 non-dominant VA side patients with neutral, left and right head-neck rotational positions were evaluated. The relevant parameters from superior and inferior views, including external diameter (ED), internal diameter (ID), transverse diameter (TD), heights and diameters of posterolateral protrusion of the VA over the posterior arch of the atlas in the neutral and rotational positions, were recorded and compared. RESULTS: There was no significant differences in the rotational angle (left/right: 31.23 ± 6.60/29.94 ± 6.09°, p>0.05). There were no significant differences in heights and diameters of bilateral VA between rotational and neutral positions (all p>0.05). The contralateral ID, ED, and TD of the rotational positions were significantly shorter than those of the neutral position (all p<0.05), while there were no significant differences in the three ipsilateral diameters (all p>0.05). CONCLUSIONS: Posterolateral protrusion of the VA is not uncommon in the population, and surgeons should be aware of its presence, especially the increased possibility of injury to the VA caused by head-neck rotation, during the operation; thus, preoperative evaluation by low-dose 3D-CTA should be considered.

COVID 19 pandemic: Impact of changes experienced on social workers' professional quality of life in Singapore.

COVID-19 has impacted all spheres of life massively. Among the emerging studies on the psychosocial impact of the pandemic, few studies look specifically at how social workers are impacted. To understand this gap, this study surveyed 337 social workers. The findings showed that changes experienced in the workplace were enormous and caused secondary traumatic stress while engendering compassion satisfaction among social workers, but the presence of social support moderated to keep the secondary traumatic stress at bay. Resilience mediated association between social and workplace support and compassion fatigue. Social support seemed to have the largest effect on reducing stress through resilience. Workplace support also helped mitigate burnout. In conclusion, continued social and workplace support will be key to supporting social workers during a pandemic.

[Renal insufficiency and venous thromboembolism].

Venous thromboembolism (VTE) is of high incidence and prevalence worldwide. Renal insufficiency has high disease burden with insidious development and is accompanied with disorder of coagulation system. A higher prevalence of VTE has been observed among patients with renal insufficiency whereas VTE patient with renal insufficiency had higher rates of adverse outcomes. Recent evidence indicated that renal insufficiency was an important risk factor for both short and long-term prognosis for VTE. Renal function also affects the choice of anticoagulation therapy and dosage adjustment of drugs. We conducted a comprehensive review of the pathogenesis, mechanism, prognosis and treatment strategy for VTE patients who comorbid renal insufficiency by searching the latest and most advanced national and international articles, to provide integrated information for the prevention and treatment for VTE patients.

70 mJ nonlinear compression and scaling route for an Yb amplifier using large-core hollow fibers.

In this Letter, we investigate the energy-scaling rules of hollow-core fiber (HCF)-based nonlinear pulse propagation and compression merged with high-energy Yb-laser technology, in a regime where the effects such as plasma disturbance, optical damages, and setup size become important limiting parameters. As a demonstration, 70 mJ 230 fs pulses from a high-energy Yb laser amplifier were compressed down to 40 mJ 25 fs by using a 2.8-m-long stretched HCF with a core diameter of 1 mm, resulting in a record peak power of 1.3 TW. This work presents a critical advance of a high-energy pulse (hundreds of mJ level) nonlinear interactions platform based on high energy sub-ps Yb technology with considerable applications, including driving intense THz, X-ray pulses, Wakefield acceleration, parametric wave mixing and ultraviolet generation, and tunable long-wavelength generation via enhanced Raman scattering.

[Preoperative plasma predictive factors of new-onset atrial fibrillation after coronary artery bypass graft surgery: A propensity score matching study].

OBJECTIVE: To study the relationship between preoperative plasma interleukin-1 (IL-1), interleukin-6 (IL-6), tumor necrosis factor-α (TNF-α), homocysteine (Hcy), endothelin-1 (ET-1) levels and new-onset atrial fibrillation (AF) after coronary artery bypass grafting (CABG). METHODS: In the study, 148 patients who underwent isolated CABG in Peking University People's Hospital from January 1, 2017 to December 30, 2017 were enrolled, of whom 39 had new-onset AF. The fasting venous blood was collected within 24 hours before the surgery. The preoperative plasma IL-1, IL-6, TNF-α, Hcy, ET-1 levels were detected by enzyme-linked immunosorbent assay (ELISA). The patients were divided into AF group and non-AF group according to whether new-onset AF occurred after operation. After 1 ∶1 propensity score matching (PSM), 38 people were in each group. The paired sample t-tests were performed on the five factors' concentrations of the matched AF group and the non-AF group respectively. If the concentration values did not conform to the normal distribution, the Wilcoxon signed rank sum test was performed. Conditional Logistic regression analysis was performed on the concentrations of the five indicators to explore the correlation between preoperative plasma concentrations of IL-1, IL-6, TNF-α, Hcy, ET-1 and postoperative new-onset AF after CABG. RESULTS: After a 1 ∶1 propensity score matching, the AF group was comparable to the non-AF group. The concentrations of IL-1, IL-6, TNF-α, and Hcy in the AF group were higher than those in the non-AF group[(0.867±0.589) ng/L vs. (0.742±0.262) ng/L, 21.55 (6.50, 209.90) ng/L vs. 17.95 (3.60, 86.70) ng/L, 20.30 (5.70, 361.00) ng/L vs. 21.50 (7.50, 251.80) ng/L, (0.29±0.11) µmol/L vs. (0.27±0.09) µmol/L], but the differences were not statistically significant (P=0.165, P=0.891, P=0.817, P=0.285). After the conditional Logistic regression analysis, the above four variables were not predictors of new-onset AF after CABG. The concentrations of ET-1 in the matched AF group and non-AF group were (25.80±6.20) ng/L and (29.10±8.54) ng/L, respectively. The correlation between preoperative low plasma ET-1 concentration and the new-onset AF after CABG were statistically significant (P=0.003). After conditional Logistic regression analysis, preoperative plasma ET-1 concentration was correlated with postoperative new-onset AF after CABG (P=0.039, adjusted OR=0.637, 95%CI: 0.415-0.977). CONCLUSION: The levels of preoperative plasma IL-1, IL-6, TNF-α and Hcy in the patients with new-onset AF after CABG were higher than those in the patients without AF, but the difference was not statistically significant. Preoperative plasma low ET-1 concentration was statistically associated with new-onset AF after CABG.

[Differential diagnosis of pure ground glass nodules in lung with spectral CT imaging].

Objective: To evaluate the differential diagnostic performance of quantitative parameters derived from the spectral CT imagingin pure ground-glass nodules. Methods: A total of 44 patients with pure ground glass nodules underwent chest energy spectrum CT and with known subsequently pathological findings in the Imaging Department of the Second Affiliated Hospital of Soochow University from August 2017 to September 2019 were retrospectively analyzed. Among them, there are 18 males and 26 females, aged from 26 to 79 (51±12) years. They were divided into as the inflammatory group (n=12), pre-invasive adenocarcinoma group (n=17) and invasive adenocarcinoma group (n=15). The aforementioned three groups were further reclassified as non-invasive adenocarcinoma group (inflammatory lesion+pre-invasive lesion) and invasive adenocarcinoma group in order to evaluating the values of water concentration (WC) for the determination of adenocarcinoma infiltration status. The values of WC derived from the arterial and venous phase of the lesion, iodine concentration (IC), standardized iodine concentration (NIC) were measured respectively.The slope of the energy spectral curve (K40-70KeV) derived from the arterial and venous phase of the lesion was also calculated. One-way ANOVA analysis was performed to compare the differences of the three groups and the multiple comparison method was used for further comparing. Intraclass correlation efficient (ICC) was used to assess the consistency of the three times of measurements. The area under curve(AUC) of Receiver Operating Characteristic (ROC) was conducted to evaluate the diagnostic performance of water based values. Results: The values of WC in the arterial and venous phases were significantly different. As in the inflammatory group, the pre-invasive lesion group and the invasive adenocarcinoma group, the values of WC was (291.95±58.66) mg/cm3, (297.61±63.96) mg/cm3and (374.52±60.62) mg/cm3 of the arterial phase, and (277.07±33.78) mg/cm3, (291.74±50.49) mg/cm3 and (373.33±75.12) mg/cm3 of the venous phase, respectively(all P<0.05). Further comparison demonstrated that no significant difference was observed for the values of WC derived from the arterial phases and venous phases between the inflammatory lesion group and the pre-invasive lesion group (all P>0.05).There were an significant differences between the invasive adenocarcinoma group, the inflammatory lesion group and the pre-invasive lesion group (all P<0.05). The values of WC derived from the venous phase achieved the largest AUC (0.770) for differentiating invasive adenocarcinoma from non-invasive adenocarcinoma (inflammatory lesions+pre-invasive lesions) in the pure ground glass nodules. The sensitivity and specificity were 66.67% and 93.10%, respectively, when using 349.31 mg/cm³ as the optimal threshold. The slope of the spectral curve and iodine-related parameters (IC, NIC) derived from arterial or venous phases among the three groups were not significantly different (all P>0.05). Conclusion: The values of WC derived from the spectral CT can better distinguish inflammatory, pre-invasive lesions and invasive adenocarcinoma, which is helpful for the qualitative analysis for pure ground glass nodules.

[Establishment of a nomogram model for predicting hematoma expansion in intracerebral hemorrhage and its multidimensional evaluation].

Objective: To establish a nomogram model for hematoma expansion (HE) prediction after intracerebral hemorrhage (ICH) and evaluate its performance in a multidimensionally way. Methods: A total of 348 ICH patients who were firstly diagnosed and hospitalized in the Second Affiliated Hospital of Soochow University from January 2017 to December 2019 were collected retrospectively. There were 236 males and 112 females, and their age ranged from 18 to 94 (62.0±14.6) years. All patients were divided into HE group (n=121) or non-HE group (n=227) according to the presence or absence of HE. The clinical and imaging features were compared between the two groups. Multivariate logistic regression analysis was performed for determining the independent predicting factors for HE prediction and a Nomogram model was established by using these factors. Receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA) were used to evaluate the prediction effectiveness, accuracy and clinical practicability of the model, respectively. Bootstrap method was used for internal validation. Results: There were significant differences in onset time, swirl sign, history of anticoagulants administrations, systolic blood pressure when admission, Glasgow coma scale (GCS) scores and RBC distribution width between the two groups[(1.77(1.0, 2.5) h vs 2(1, 3) h, 72 cases (59.5%) vs 94 cases (41.4%), 17 cases (14.0%) vs 15 cases (6.6%), (170.69±29.19) mmHg(1 mmHg=0.133 kPa) vs (163.84±26.07) mmHg, 11(8, 14) scores vs 14(10, 15) scores, 44.3% (41.2%, 46.8%) vs 42.4% (40.1%, 45.3%);respectively, all P<0.05]. Multivariate logistic regression analysis demonstrated that onset time (OR=0.809, 95%CI: 0.682-1.961, P=0.015), swirl sign (OR=0.562, 95%CI:0.349-0.905, P=0.018), history of anticoagulants administrations (OR=0.394, 95%CI: 0.180-1.861, P=0.020), and GCS (OR=0.881, 95%CI: 0.815-1.952, P=0.001) were the predicting factors for HE. The area under the curve (AUC) of the Nomogram model was 0.735(95%CI: 0.687-0.805), which demonstrated that the model has an ideal prediction effectiveness. The calibration curve showed that the prediction probability of HE of the model fits well with the actual probability, and with high calibration. DCA showed relatively wide range of optional threshold probability of the model (ranging from 14% to 72%), the clinical practicability of this model was high. The internal validation results showed a C-index of 0.703, indicated a good discrimination power. Conclusion: The established Nomogram model can predict the HE of ICH with good prediction effectiveness, discrimination power and with good clinical practicability, which can be capable of providing an intuitive and visual guidance tool for timely identifying ICH patients who may have HE.

[Research study on nucleic acid testing of hemostatic stickers used and the surface of the recipients' hands after the inoculation of inactivated SARS-CoV-2 vaccine].

Among the staff of Beijing Chao-Yang Hospital, Capital Medical University, who received the inactivated SARS-CoV-2 vaccine on January 30 in 2021, 28 recipients were selected for this research. Samples for nucleic acid tests were collected from the surface of the recipients' both hands before and after vaccination. The hemostatic stickers used after the inoculation were also collected for nucleic acid tests. The nucleic acid tests of the samples collected from the surface of both hands of the 28 recipients before vaccination were all negative. After vaccination, the nucleic acid tests of the samples collected from the surface of both hands of recipients were positive in 3 cases, and suspicious in 8 cases, with a positive rate of 10.7%. A total of 25 hemostatic stickers used were collected, 24 of them had positive nucleic acid tests, and the rest one had suspicious nucleic acid test result, with a positive rate of 96%. The hemostatic stickers used after the inoculation have the risk of nucleic acid contamination.

High energy redshifted and enhanced spectral broadening by molecular alignment.

We demonstrate an efficient approach for enhancing the spectral broadening of long laser pulses and for efficient frequency redshifting by exploiting the intrinsic temporal properties of molecular alignment inside a gas-filled hollow-core fiber (HCF). We find that laser-induced alignment with durations comparable to the characteristic rotational time scale TRotAlign enhances the efficiency of redshifted spectral broadening compared to noble gases. The applicability of this approach to Yb lasers with (few hundred femtoseconds) long pulse duration is illustrated, for which efficient broadening based on conventional Kerr nonlinearity is challenging to achieve. Furthermore, this approach proposes a practical solution for high energy broadband long-wavelength light sources, and it is attractive for many strong field applications.

Diagnostic accuracy of deep learning in orthopaedic fractures: a systematic review and meta-analysis.

AIM: To gather and compare related clinical studies, and to investigate the accuracy and reliability of deep learning in detecting orthopaedic fractures. MATERIALS AND METHODS: This study is a retrospective combination and interpretation of prospectively acquired data. Articles from PubMed, EMBASE, the Cochrane library databases, and reference lists of the qualified articles were retrieved. Heterogeneity between studies was assessed using a random effective model. Pooled sensitivity, specificity, diagnostic odds ratio, and area under the receiver operating characteristic curve (AUC) were obtained by a random model. This work was managed from October 2018 to March 2020. RESULTS: Fourteen studies were included in this systematic review and nine were synthesized in the meta-analysis. The pooled sensitivity and specificity for the whole group (17 trials, 5,434 images) were 0.87 and 0.91, respectively. The AUC was 0.95. Eight trials (1,574 images) were included in the long-bone group, which contained seven studies. The pooled sensitivity was 0.96 and specificity was 0.94. The AUC was 0.99. Heterogeneity existed in the four pooled results of the whole group and the pooled specificity of the long-bone group. CONCLUSIONS: Deep learning is reliable in fracture diagnosis and has high diagnostic accuracy, which is similar to that of general physicians and is unlikely to produce a large number of false diagnoses; however, the ability of deep learning to localize the fracture needs more attention and testing. Deep learning can be extremely helpful with pre-classification of clinical diagnoses.

Serial low-dose quantitative CT perfusion for the evaluation of delayed cerebral ischaemia following aneurysmal subarachnoid haemorrhage.

AIM: To investigate the appropriate time and computed tomography perfusion (CTP) parameters for predicting delayed cerebral ischaemia (DCI) following aneurysmal subarachnoid haemorrhage (aSAH). MATERIALS AND METHODS: All patients underwent baseline CTP within 24 hours and follow-up CTP on day 4 and day 7 after aSAH. The quantitative and semi-quantitative parameters, cerebral blood volume (CBV), cerebral blood flow (CBF), mean transit time (MTT), time to peak (TTP), relative CBV and CBF (rCBV, rCBF), and MTT and TTP difference (ΔMTT, ΔTTP) were compared between the DCI and non-DCI (NDCI) groups at the three time points. RESULTS: Thirty-nine patients were included. Twelve patients developed DCI. CBF, rCBF, and ΔMTT were significantly different in the DCI group among all time points (p<0.05), but these parameters did not significantly change from day 4 to day 7. CBF and rCBF in the DCI group were lower than in the NDCI group. ΔMTT in the DCI group was longer than in the NDCI group, but significant differences were only found in the two follow-up CTPs (both p<0.05). The optimal threshold values distinguishing DCI and NDCI were 40.1 ml/100 g/min for CBF, 0.90 for rCBF and 0.33 seconds for ΔMTT. The follow-up CTP on day 4 was an appropriate time to predict DCI after aSAH. CONCLUSIONS: The follow-up CTP on day 4 after aSAH can be helpful for the early identification of DCI. CBF, rCBF, and ΔMTT were found to be the best prognosticators for the development of DCI.

The accuracy of bone mineral density measurement using dual-energy spectral CT and quantitative CT: a comparative phantom study.

AIM: To compare bone mineral density (BMD) measurement accuracy by dual-energy spectral computed tomography (CT) and quantitative CT (QCT) using an anthropomorphic European spine phantom (ESP). MATERIALS AND METHODS: An ESP containing three hydroxyapatite inserts with densities of 50, 100, and 200 mg/cm3 was scanned 10 times each using spectral CT and QCT protocols. Their BMD values were measured using hydroxyapatite-based spectral CT material decomposition images and QCT images and compared with the true values in ESP. RESULTS: Both protocols had good repeatability in BMD measurement with low coefficient-of-variance (spectral CT: <2.31%; QCT: <1.17%). There were biases in BMD measurement for the 50, 100, and 200 mg/cm3 hydroxyapatite insert with relative errors of 2.34% (48.83±1.13 mg/cm3), 2% (98±1.25 mg/cm3) and 5.96% (188.09±2.11 mg/cm3), in spectral CT, and 11% (55.5±0.65 mg/cm3), 9.85% (109.85±0.42 mg/cm3) and 4.04% (208.07±0.54 mg/cm3) in QCT, respectively. CONCLUSION: BMD can be accurately measured using either QCT or spectral CT, and spectral CT has smaller bias than QCT.

Identification of factors associated with minimal erythema dose variations in a large-scale population study of 22 146 subjects.

BACKGROUND: Minimal erythema dose (MED) has substantial inter- and intraindividual variations, reflecting the influence of very diverse factors. However, related studies showed little consistency probably because of their limited sample size. OBJECTIVE: To identify the factors associated with MED variations in a large-scale population study. METHODS: The MED test was performed by following the international standard procedure on 22 146 subjects. The results were analysed in adjusted multivariable linear and logistic regression models. RESULTS: This large-scale study revealed that lower MED was consistently associated with lighter skin [ß-coefficient = -0.33, 95% confidence interval (CI) -0.36 to 0.30, P = 6.41 × 10-84 ]. Females had significantly higher MED than male (ß = 0.91, 0.32-1.50, P = 2.93 × 10-3 ). Stratified analyses showed that MED was not associated with age [female: odds ratio (OR) = 0.99, 0.98-1.01; male: OR = 0.99, 0.97-1.00]. MED was lower in summer than in other seasons (spring: OR = 1.08, 1.06-1.11; autumn: OR = 1.11, 1.08-1.13; winter: OR = 1.20, 1.18-1.22). Furthermore, MED was associated with air temperature (ß = -0.36, -0.49 to 0.23, P = 4.81 × 10-8 ) and air pressure (ß = -0.64, -0.82 to 0.46, P = 8.01 × 10-12 ) in summer only while not in other seasons. CONCLUSIONS: This study provides unprecedented evidence that MED is associated with skin colour, sex, season and meteorological factors, but not with age.

Optimal reperfusion strategy in patients with acute STEMI and multivessel disease-an updated meta-analysis.

BACKGROUND: This meta-analysis compared the efficacy and safety of culprit-only revascularization (COR) and complete revascularization (CR) in the treatment of patients with acute ST-elevation myocardial infarction (STEMI) and multivessel disease to determine the optimal reperfusion strategy. METHOD: We analyzed published multicenter randomized controlled trials to compare COR and CR in patients with acute STEMI and multivessel disease. The PubMed, Cochrane Library, and Ovid databases were searched, and the meta-analysis was performed using Review Manager 5.3 software. RESULTS: Eight multicenter randomized controlled trials were selected involving 2870 patients, of whom 1604 underwent COR and 1266 underwent CR. No significant heterogeneity was identified across these selected studies. The CR strategy significantly decreased the incidence of major adverse cardiac events (MACE; odds ratio [OR]: 2.44, 95% CI [95% confidence interval]: 1.96-3.03, p < 0.001), mortality (OR: 1.76, 95% CI: 1.25-2.47, p = 0.001), myocardial infarction (MI, OR: 1.62, 95% CI: 1.12-2.35, p = 0.01), and repeat revascularization (OR: 3.20, 95% CI: 2.41-4.24, p < 0.001) compared with the COR approach. Moreover, no significant difference was identified in the safety indexes, including contrast-induced nephropathy, stroke, and bleeding, between the CR and the COR group (p > 0.05). CONCLUSION: The present meta-analysis determined that CR is an efficacious and safe reperfusion strategy in patients with acute STEMI and multivessel disease.

[The value of 3.0T magnetic resonance -diffusion kurtosis imaging in the differential diagnosis of rectal mucinous adenocarcinoma and common adenocarcinoma].

Objective: To investigate the value of 3.0T MRI diffusion kurtosis imaging (DKI) quantitative histogram parameters in the differential diagnosis of rectal mucinous adenocarcinoma (MC) and common adenocarcinoma (AC). Methods: One hundred and ten patients from Department of Radiology, the Second Affiliated Hospital of Soochow University between September 2015 and September 2019 with complete magnetic resonance imaging (MRI) and DKI results confirmed by surgery and pathology were retrospectively analyzed, including 16 patients in MC group and 94 patients in AC group. Two physicians outlined the region of interest (ROI) on the DKI image with b=1 000 s/mm(2), and obtained quantitative DKI parameters, including the diffusion coefficient (D value) and kurtosis coefficient (K value) corrected for non-Gaussian distribution. The apparent diffusion coefficient (ADC) values of quantitative parameters of diffusion-weighted imaging (DWI) were obtained through image registration, and histogram analysis was performed to obtain the mean value, 25th percentile, 50th percentile, 75th percentile, skewness and kurtosis of the above parameters, respectively. The difference between the quantitative histogram parameter analysis results of the rectal MC group and the AC group was evaluated, and the main indicators and multivariate comprehensive analysis indicators was screened, and the effectiveness of quantitative histogram parameters related to histopathological classification in the differential diagnosis of rectal MC and AC was evaluated. Results: There was no significant differences in gender, age, lesion location, T stage or N stage between MC group and AC group (all P>0.05). The multivariate binary logistic stepwise regression screening showed that D50th percentile and K25th percentile are statistically significant indicators (B values were 2 966.166 and -4.550, respectively; Wals values were 9.000 and 15.720, respectively; and P values were 0.003 and <0.001, respectively). The combined area under the curve of the two indictors was 0.85, but there was no statistically significant difference in pairwise comparison using DeLong method (P>0.05). The results of histogram analysis of quantitative parameters measured by the two physicians were consistent, and the inter-group correlation coefficient ranged from 0.880 to 0.981. Conclusions: The quantitative parameter histogram analysis of the DKI double-index model is helpful for the differentiation of rectal MC and AC, in which the D50th percentile and K25th percentile have differential diagnosis significance, and are superior to the ADC value of the single-index model.