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1.
Front Med (Lausanne) ; 8: 744587, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-34660649

RESUMO

Background: Computed tomography plays an important role in the identification and characterization of thymomas. It has been mainly used during preoperative evaluation for clinical staging. However, the reliable prediction of histological risk types of thymomas based on CT imaging features requires further study. In this study, we developed and validated a nomogram based on CT imaging and included new indices for individualized preoperative prediction of the risk classification of thymomas. Methods: We conducted a retrospective, multicenter study that included 229 patients from two Chinese medical centers. All the patients underwent cross-sectional CT imaging within 2 weeks before surgery. The results of pathological assessments were retrieved from existing reports of the excised lesions. The tumor perimeter that contacted the lung (TPCL) was evaluated and a new quantitative indicator, the acute angle (AA) formed by adjacent lobulations, was measured. Two predictive models of risk classification were created using the least absolute shrinkage and selection operator (LASSO) method in a training cohort for features selection. The model with a smaller Akaike information criterion was then used to create an individualized imaging nomogram, which we evaluated regarding its prediction ability and clinical utility. Results: A new CT imaging-based model incorporating AA was developed and validated, which had improved predictive performance during risk classification of thymomas when compared with a model using traditional imaging predictors. The new imaging nomogram with AA demonstrated its clinical utility by decision curve analysis. Conclusions: Acute angle can improve the performance of a CT-based predictive model during the preoperative risk classification of thymomas and should be considered a new imaging marker for the evaluation and treatment of patients with thymomas. On the contrary, TPCL is not useful as a predictor for the risk classification of thymomas in this study.

2.
Front Neurosci ; 15: 713760, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-34456678

RESUMO

Purpose: This study aimed to determine if people living with HIV (PLWH) in preclinical human immunodeficiency virus (HIV)-associated neurocognitive disorder (HAND), with no clinical symptoms and without decreased daily functioning, suffer from brain volumetric alterations and its patterns. Method: Fifty-nine male PLWH at the HAND preclinical stage were evaluated, including 19 subjects with asymptomatic neurocognitive impairment (ANI), 17 subjects with cognitive abnormality that does not reach ANI (Not reach ANI), and 23 subjects with cognitive integrity. Moreover, 23 healthy volunteers were set as the seronegative normal controls (NCs). These individuals underwent sagittal three-dimensional T1-weighted imaging (3D T1WI). Quantified data and volumetric measures of brain structures were automatically segmented and extracted using AccuBrain®. In addition, the multiple linear regression analysis was performed to analyze the relationship of volumes of brain structures and clinical variables in preclinical HAND, and the correlations of the brain volume parameters with different cognitive function states were assessed by Pearson's correlation analysis. Results: The significant difference was shown in the relative volumes of the ventricular system, bilateral lateral ventricle, thalamus, caudate, and left parietal lobe gray matter between the preclinical HAND and NCs. Furthermore, the relative volumes of the bilateral thalamus in preclinical HAND were negatively correlated with attention/working memory (left: r = -0.271, p = 0.042; right: r = -0.273, p = 0.040). Higher age was associated with increased relative volumes of the bilateral lateral ventricle and ventricular system and reduced relative volumes of the left thalamus and parietal lobe gray matter. The lower CD4+/CD8+ ratio was associated with increased relative volumes of the left lateral ventricle and ventricular system. Longer disease course was associated with increased relative volumes of the bilateral thalamus. No significant difference was found among preclinical HAND subgroups in all indices, and the difference between the individual groups (Not reach ANI and Cognitive integrity groups) and NCs was also insignificant. However, there was a significant difference between ANI and NCs in the relative volumes of the bilateral caudate and lateral ventricle. Conclusion: Male PLWH at the HAND preclinical stage suffer from brain volumetric alterations. AccuBrain® provides potential value in evaluating HIV-related neurocognitive dysfunction.

4.
J Thorac Imaging ; 36(5): 326-332, 2021 Sep 01.
Artigo em Inglês | MEDLINE | ID: mdl-34269751

RESUMO

PURPOSE: Nephrotic syndrome (NS) is highly associated with an increased risk of pulmonary embolism (PE) in children and young adults. However, few studies have specified the risk factors of PE in children and young adults with NS. We sought to determine the prevalence and associated factors of PE confirmed with computed tomography pulmonary angiography in Chinese children and young adults with NS. METHODS: Data from 444 children and young adults with NS who had computed tomography pulmonary angiography from December 2010 to October 2018 were retrospectively analyzed. The prevalence of PE was estimated for different age, sex, and histopathologic types of NS. Multivariable logistic regression was used to identify independent risk factors of PE in children and young adults with NS. Models incorporating the independent risk factors were evaluated using receiver operation characteristic curves. Area under the curve was used to determine the best-performing prognosticators for predicting PE. RESULTS: There were 444 patients in the study cohort (310 male patients, 134 female patients; mean age 19±3 y; range: 6 to 25 y). PE was present in 24.8% of the participants (110 of 444, 18.2% female). Children and young adult NS patients with PE tend to be older, male, to have a previous thromboembolism history and smoking, and have a higher level of proteinuria, D-dimer, and serum albumin (P<0.05 for all). Children and young adults with membranous nephropathy are likely to have a higher incidence of PE than those with other types of nephropathy. Membranous nephropathy and proteinuria were significant predictors of PE in children and young adults with NS (P<0.05 for all). The area under the curves of each model for the presence of PE in children and young adults with NS based on biochemical parameters and clinical information (model 1), adjusted for proteinuria (model 2), and adjusted for membranous nephropathy (model 3) were 0.578, 0.657, and 0.709, respectively. Compared with model 1, model 2, and model 3 showed statistically significant differences (model 1 vs. model 2, P=0.0336; model 1 vs. model 3, P=0.0268). There was no statistically significant difference between model 2 and model 3 (P=0.2947). CONCLUSION: This study identified membranous nephropathy and proteinuria as independent associated factors of PE in children and young adults with NS, which can be noted as a risk factor to guide clinician management in this population.

5.
Quant Imaging Med Surg ; 11(6): 2658-2668, 2021 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-34079731

RESUMO

Background: Nephron-sparing surgery has been widely applied in the treatment of renal tumors. Previous studies have confirmed the advantages of mixed reality technology in surgery. The study aimed to explore the optimization of mixed reality technology and its application value in nephron-sparing surgery. Methods: In this prospective study of 150 patients with complex renal tumors (RENAL nephrometry score ≥7) who underwent nephron-sparing surgery, patients were randomly divided into Group A (the normal-dose mixed reality group, n=50), Group B (the low-dose mixed reality group, n=50), and Group C (the traditional computed tomography image group, n=50). Group A and Group C received the normal-dose computed tomography scan protocol: 120 kVp, 400 mA, and 350 mgI/mL, while Group B received the low-dose computed tomography scan protocol: 80 kVp, automatic tube current modulation, and 320 mgI/mL. All computed tomography data were transmitted to a three-dimensional visualization workstation and underwent modeling and mixed reality imaging. Two senior surgeons evaluated mixed reality quality. Objective indexes and perioperative indexes were calculated and compared. Results: Compared with Group A, the radiation effective dose in Group B was decreased by 39.6%. The subjective scores of mixed reality quality in Group B were significantly higher than those of Group A (Z=-4.186, P<0.001). The inter-observer agreement between the two senior surgeons in mixed reality quality was excellent (K=0.840, P<0.001). The perioperative indexes showed that the mixed reality groups were significantly different from the computed tomography image group (all P<0.017). More cases underwent nephron-sparing surgery in the mixed reality groups than in the computed tomography image group (P<0.0017). Conclusions: Low-dose computed tomography technology can be effectively applied to mixed reality optimization, reducing the effective dose and improving mixed reality quality. Optimized mixed reality can significantly increase the cases of successful nephron-sparing surgery and improve perioperative indexes.

6.
Respir Res ; 22(1): 189, 2021 Jun 28.
Artigo em Inglês | MEDLINE | ID: mdl-34183009

RESUMO

BACKGROUND: In this study, we tested whether a combination of radiomic features extracted from baseline pre-immunotherapy computed tomography (CT) images and clinicopathological characteristics could be used as novel noninvasive biomarkers for predicting the clinical benefits of non-small cell lung cancer (NSCLC) patients treated with immune checkpoint inhibitors (ICIs). METHODS: The data from 92 consecutive patients with lung cancer who had been treated with ICIs were retrospectively analyzed. In total, 88 radiomic features were selected from the pretreatment CT images for the construction of a random forest model. Radiomics model 1 was constructed based on the Rad-score. Using multivariate logistic regression analysis, the Rad-score and significant predictors were integrated into a single predictive model (radiomics nomogram model 1) to predict the durable clinical benefit (DCB) of ICIs. Radiomics model 2 was developed based on the same Rad-score as radiomics model 1.Using multivariate Cox proportional hazards regression analysis, the Rad-score, and independent risk factors, radiomics nomogram model 2 was constructed to predict the progression-free survival (PFS). RESULTS: The models successfully predicted the patients who would benefit from ICIs. For radiomics model 1, the area under the receiver operating characteristic curve values for the training and validation cohorts were 0.848 and 0.795, respectively, whereas for radiomics nomogram model 1, the values were 0.902 and 0.877, respectively. For the PFS prediction, the Harrell's concordance indexes for the training and validation cohorts were 0.717 and 0.760, respectively, using radiomics model 2, whereas they were 0.749 and 0.791, respectively, using radiomics nomogram model 2. CONCLUSIONS: CT-based radiomic features and clinicopathological factors can be used prior to the initiation of immunotherapy for identifying NSCLC patients who are the most likely to benefit from the therapy. This could guide the individualized treatment strategy for advanced NSCLC.

7.
Nat Biomed Eng ; 5(6): 509-521, 2021 06.
Artigo em Inglês | MEDLINE | ID: mdl-33859385

RESUMO

Common lung diseases are first diagnosed using chest X-rays. Here, we show that a fully automated deep-learning pipeline for the standardization of chest X-ray images, for the visualization of lesions and for disease diagnosis can identify viral pneumonia caused by coronavirus disease 2019 (COVID-19) and assess its severity, and can also discriminate between viral pneumonia caused by COVID-19 and other types of pneumonia. The deep-learning system was developed using a heterogeneous multicentre dataset of 145,202 images, and tested retrospectively and prospectively with thousands of additional images across four patient cohorts and multiple countries. The system generalized across settings, discriminating between viral pneumonia, other types of pneumonia and the absence of disease with areas under the receiver operating characteristic curve (AUCs) of 0.94-0.98; between severe and non-severe COVID-19 with an AUC of 0.87; and between COVID-19 pneumonia and other viral or non-viral pneumonia with AUCs of 0.87-0.97. In an independent set of 440 chest X-rays, the system performed comparably to senior radiologists and improved the performance of junior radiologists. Automated deep-learning systems for the assessment of pneumonia could facilitate early intervention and provide support for clinical decision-making.


Assuntos
COVID-19/diagnóstico por imagem , Bases de Dados Factuais , Aprendizado Profundo , SARS-CoV-2 , Tomografia Computadorizada por Raios X , Diagnóstico Diferencial , Feminino , Humanos , Masculino , Índice de Gravidade de Doença
8.
Eur Radiol ; 31(11): 8765-8774, 2021 Nov.
Artigo em Inglês | MEDLINE | ID: mdl-33909133

RESUMO

OBJECTIVES: To develop and evaluate machine learning models using baseline and restaging computed tomography (CT) for predicting and early detecting pathological downstaging (pDS) with neoadjuvant chemotherapy in advanced gastric cancer (AGC). METHODS: We collected 292 AGC patients who received neoadjuvant chemotherapy. They were classified into (a) primary cohort (206 patients with 3-4 cycles chemotherapy) for model development and internal validation, (b) testing cohort I (46 patients with 3-4 cycles chemotherapy) for evaluating models' predictive ability before and after the complete course, and (c) testing cohort II (n = 40) for model evaluation on its performance at early treatment. We extracted 1,231 radiomics features from venous phase CT at baseline and restaging. We selected radiomics models based on 28 cross-combination models and measured the areas under the curve (AUC). Our prediction radiomics (PR) model is designed to predict pDS outcomes using baseline CT. Detection radiomics (DR) model is applied to restaging CT for early pDS detection. RESULTS: PR model achieved promising outcomes in two testing cohorts (AUC 0.750, p = .009 and AUC 0.889, p = .000). DR model also showed a good predictive ability (AUC 0.922, p = .000 and AUC 0.850, p = .000), outperforming the commonly used RECIST method (NRI 39.5% and NRI 35.4%). Furthermore, the improved DR model with averaging outcome scores of PR and DR models showed boosted results in two testing cohorts (AUC 0.961, p = .000 and AUC 0.921, p = .000). CONCLUSIONS: CT-based radiomics models perform well on prediction and early detection tasks of pDS and can potentially assist surgical decision-making in AGC patients. KEY POINTS: • Baseline contrast-enhanced computed tomography (CECT)-based radiomics features were predictive of pathological downstaging, allowing accurate identification of non-responders before therapy. • Restaging CECT-based radiomics features were predictive to achieve pDS after and even at an early stage of neoadjuvant chemotherapy. • Combination of baseline and restaging CECT-based radiomics features was promising for early detection and preoperative evaluation of pathological downstaging of AGC.


Assuntos
Terapia Neoadjuvante , Neoplasias Gástricas , Detecção Precoce de Câncer , Humanos , Estudos Retrospectivos , Neoplasias Gástricas/diagnóstico por imagem , Neoplasias Gástricas/tratamento farmacológico , Tomografia Computadorizada por Raios X
9.
NPJ Digit Med ; 4(1): 75, 2021 Apr 22.
Artigo em Inglês | MEDLINE | ID: mdl-33888856

RESUMO

The COVID-19 pandemic overwhelms the medical resources in the stressed intensive care unit (ICU) capacity and the shortage of mechanical ventilation (MV). We performed CT-based analysis combined with electronic health records and clinical laboratory results on Cohort 1 (n = 1662 from 17 hospitals) with prognostic estimation for the rapid stratification of PCR confirmed COVID-19 patients. These models, validated on Cohort 2 (n = 700) and Cohort 3 (n = 662) constructed from nine external hospitals, achieved satisfying performance for predicting ICU, MV, and death of COVID-19 patients (AUROC 0.916, 0.919, and 0.853), even on events happened two days later after admission (AUROC 0.919, 0.943, and 0.856). Both clinical and image features showed complementary roles in prediction and provided accurate estimates to the time of progression (p < 0.001). Our findings are valuable for optimizing the use of medical resources in the COVID-19 pandemic. The models are available here: https://github.com/terryli710/COVID_19_Rapid_Triage_Risk_Predictor .

10.
Sci Total Environ ; 781: 146712, 2021 Aug 10.
Artigo em Inglês | MEDLINE | ID: mdl-33812102

RESUMO

Potential release quantity and quality of dissolved organic matter (DOM) from hydrochar (HDOM) in various environmental conditions were investigated. Corn cobs were utilized as model agricultural residue to prepare the hydrochar. Four extracts, ultra-pure water, acid solution, alkali solution and salt solution, and two temperatures, 20 °C and 60 °C, were adopted to imitate various environmental conditions. Excitation-emission spectrophotometry with parallel factor analysis was used to evaluate the chemical properties of HDOM. The results showed that the dissolved organic carbon in the HDOM was high, ranging from 46 to 268 mg g-1. Four components were confirmed in the HDOM: mixed substances of humic-like and protein-like components, marine humic-like substances, terrestrial humic-like substances and tyrosine-like substances. Alkalinity and high temperature conditions could enhance the leaching amount of HDOM, particularly humic-like substances, and change the relative proportion of components and the chemical quality. In addition, values of the fluorescence indexes indicated that the HDOM was high microbial availability. Released HDOM may result in significant impacts in ecosystem functionality. These findings reveal the potential release characteristics of HDOM in the environment, opening new doors to understanding the environmental impacts of hydrochar and guiding its rational application.

11.
Kidney Dis (Basel) ; 7(2): 131-142, 2021 Mar.
Artigo em Inglês | MEDLINE | ID: mdl-33824869

RESUMO

Background: Renal fibrosis is a key driver of progression in chronic kidney disease (CKD). Recent advances in diagnostic imaging techniques have shown promising results for the noninvasive assessment of renal fibrosis. However, the specificity and accuracy of these techniques are controversial because they indirectly assess renal fibrosis. This limits fibrosis assessment by imaging in CKD for clinical practice. To validate magnetic resonance imaging (MRI) assessment for fibrosis, we derived representative models by mapping histology-proven renal fibrosis and imaging in CKD. Methods: Ninety-seven adult Chinese CKD participants with histology were studied. The kidney cortex interstitial extracellular matrix volume was calculated by the Aperio ScanScope system using Masson's trichrome slices. The kidney cortex microcirculation was quantitatively assessed by peritubular capillary density using CD34 staining. The imaging techniques included intravoxel incoherent motion diffusion-weighted imaging and magnetic resonance elastography (MRE) imaging. Relevant analyses were performed to evaluate the correlations between MRI parameters and histology variables. Multiple linear regression models were used to describe the relationships between a response variable and other variables. The best-fit lines, which minimize the sum of squared residuals of the multiple linear regression models, were generated. Results: MRE values were negatively associated with the interstitial extracellular matrix volume (Rho = -0.397, p < 0.001). The best mapping model of extracellular matrix volume with the MRE value and estimated glomerular filtration rate (eGFR) we obtained was as follows: Interstitial extracellular matrix volume = 218.504 - 14.651 × In(MRE) - 18.499 × In(eGFR). DWI-fraction values were positively associated with peritubular capillary density (Rho = 0.472, p < 0.001). The best mapping model of peritubular capillary density with DWI-fraction value and eGFR was as follows: Peritubular capillaries density = 17.914 + 9.403 × (DWI - fraction) + 0.112 × (eGFR). Conclusions: The study provides histological evidence to support that MRI can effectively evaluate fibrosis in the kidney. These findings picture the graphs of the mapping model from imaging and eGFR into fibrosis, which has significant value for clinical implementation.

12.
Cancer Med ; 10(9): 3077-3084, 2021 05.
Artigo em Inglês | MEDLINE | ID: mdl-33797861

RESUMO

PURPOSE: The aim of this study was to explore the feasibility of 3D printing of kidney and perinephric fat based on low-dose CT technology. PATIENTS AND METHODS: A total of 184 patients with stage T1 complex renal tumors who underwent laparoscopic nephrectomy were prospectively enrolled and divided into three groups: group A (conventional dose kidney and perinephric fat 3D printing group, n = 62), group B (low-dose kidney and perinephric fat 3D printing, n = 64), and group C (conventional dose merely kidney 3D printing group, n = 58). The effective dose (ED), signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) were determined. The 3D printing quality was evaluated using a 4-point scale, and interobserver agreement was assessed using the intraclass correlation coefficient (ICC). RESULTS: The ED of group B was lower than that of group A, with a decrease of 55.1%. The subjective scores of 3D printing quality in all groups were 3 or 4 points. The interobserver agreement among the three observers in 3D printing quality was good (ICC = 0.84-0.92). The perioperative indexes showed that operation time (OT), warm ischemia time (WIT), estimated blood loss (EBL), and laparoscopic partial nephrectomy (LPN) conversion to laparoscopic radical nephrectomy (LRN) in groups A or B were significantly less than those in group C. LPN was more frequent in group A and group B than in group C (all p < 0.017). There were no significant differences in perioperative indexes between group A and group B (all p > 0.017). CONCLUSION: Low-dose CT technology can be effectively applied to 3D printing of kidney and perinephric fat and reduce the patient's radiation dose without compromising 3D printing quality. 3D printing of kidney and perinephric fat can significantly increase the success rate of LPN and decrease OT, WIT, and EBL.


Assuntos
Tecido Adiposo/diagnóstico por imagem , Rim/diagnóstico por imagem , Nefrectomia/métodos , Impressão Tridimensional/normas , Tomografia Computadorizada por Raios X/métodos , Adulto , Idoso , Idoso de 80 Anos ou mais , Perda Sanguínea Cirúrgica , Meios de Contraste/administração & dosagem , Estudos de Viabilidade , Feminino , Humanos , Isquemia , Rim/irrigação sanguínea , Rim/cirurgia , Neoplasias Renais/cirurgia , Laparoscopia/estatística & dados numéricos , Masculino , Pessoa de Meia-Idade , Nefrectomia/estatística & dados numéricos , Duração da Cirurgia , Doses de Radiação , Razão Sinal-Ruído
13.
Circ Cardiovasc Imaging ; 14(3): e011747, 2021 03.
Artigo em Inglês | MEDLINE | ID: mdl-33722057

RESUMO

Radiomics uses advanced image analysis to extract massive amounts of quantitative information from digital images, which is not otherwise distinguishable to the human eye. The mined data can be used to explore and establish new and undiscovered correlations between these imaging features and clinical end points. Cardiac computed tomography (CT) is a first-line imaging modality for evaluating coronary artery disease and has a primary role in the assessment of cardiac structures. Conventional interpretation of cardiac CT images relies mostly on subjective and qualitative analysis, as well as basic geometric quantification. To date, some proof-of-concept studies have demonstrated the feasibility and diagnostic performance of cardiac CT radiomics analysis. This review describes the current literature on radiomics in cardiac CT and discusses its advantages, challenges, and future directions. Although much evidences are needed in this field, cardiac CT radiomics has a lot to offer to patients and physicians with potential to define cardiac disease phenotypes on imaging with higher precision.


Assuntos
Doença da Artéria Coronariana/diagnóstico , Processamento de Imagem Assistida por Computador/métodos , Tomografia Computadorizada por Raios X/métodos , Humanos
14.
Lung Cancer ; 155: 78-86, 2021 05.
Artigo em Inglês | MEDLINE | ID: mdl-33761380

RESUMO

PURPOSE: To propose a practical strategy for the clinical application of deep learning algorithm, i.e., Hierarchical-Ordered Network-ORiented Strategy (HONORS), and a new approach to pulmonary nodule classification in various clinical scenarios, i.e., Filter-Guided Pyramid NETwork (FGP-NET). MATERIALS AND METHODS: We developed and validated FGP-NET on a collection of 2106 pulmonary nodules on computed tomography images which combined screened and clinically detected nodules, and performed external test (n = 341). The area under the curves (AUCs) of FGP-NET were assessed. A comparison study with a group of 126 skilled radiologists was conducted. On top of FGP-NET, we built up our HONORS which was composed of two solutions. In the Human Free Solution, we used the high sensitivity operating point for screened nodules, but the high specificity operating point for clinically detected nodules. In the Human-Machine Coupling Solution, we used the Youden point. RESULTS: FGP-NET achieved AUCs of 0.969 and 0.847 for internal and external test. The AUCs of the subsets of the external test set ranged from 0.890 to 0.942. The average sensitivity and specificity of the 126 radiologists were 72.2 ±â€¯15.1 % and 71.7 ±â€¯15.5 %, respectively, while a higher sensitivity (93.3 %) but a relatively inferior specificity (64.0 %) were achieved by FGP-NET. HONORS-guided FGP-NET identified benign nodules with high sensitivity (sensitivity,95.5 %; specificity, 72.5 %) in the screened nodules, and identified malignant nodules with high specificity (sensitivity, 31.0 %; specificity, 97.5 %) in the clinically detected nodules. These nodules could be reliably diagnosed without any intervention from radiologists, via the Human Free Solution. The remaining ambiguous nodules were diagnosed with high performance, which however required manual confirmation by radiologists, via the Human-Machine Coupling Solution. CONCLUSIONS: FGP-NET performed comparably to skilled radiologists in terms of diagnosing pulmonary nodules. HONORS, due to its high performance, might reliably contribute a second opinion, aiding in optimizing the clinical workflow.


Assuntos
Aprendizado Profundo , Neoplasias Pulmonares , Nódulos Pulmonares Múltiplos , Nódulo Pulmonar Solitário , Humanos , Neoplasias Pulmonares/diagnóstico por imagem , Nódulos Pulmonares Múltiplos/diagnóstico por imagem , Estudos Retrospectivos , Nódulo Pulmonar Solitário/diagnóstico por imagem , Tomografia Computadorizada por Raios X
15.
Eur Radiol ; 31(5): 2687-2695, 2021 May.
Artigo em Inglês | MEDLINE | ID: mdl-33151395

RESUMO

OBJECTIVES: To evaluate the utility of arterial spin labeling (ASL) for the identification of kidney allografts with underlying pathologies, particularly those with stable graft function. METHODS: A total of 75 patients, including 18 stable grafts with normal histology (normal group), 21 stable grafts with biopsy-proven pathology (subclinical pathology group), and 36 with unstable graft function (unstable graft group), were prospectively examined by ASL magnetic resonance imaging. Receiver operating characteristic curves were generated to calculate the area under the curve (AUC), sensitivity, and specificity. RESULTS: Patient demographics among the 3 groups were comparable. Compared with the normal group, kidney allograft cortical ASL values decreased in the subclinical pathology group and the unstable graft group (204.7 ± 44.9 ml/min/100 g vs 152.5 ± 38.9 ml/min/100 g vs 92.3 ± 37.4 ml/min/100 g, p < 0.001). The AUC, sensitivity, and specificity for discriminating allografts with pathologic changes from normal allografts were 0.92 (95% CI, 0.83-0.97), 71.9%, and 100% respectively by cortical ASL and 0.82 (95% CI, 0.72-0.90), 54.4%, and 100% respectively by serum creatinine. The cortical ASL identified allografts with subclinical pathology among patients with stable graft function with an AUC of 0.80 (95% CI, 0.64-0.91), sensitivity of 57.1%, and specificity of 88.9%. Combined use of proteinuria and cortical ASL could improve the sensitivity and specificity to 76.2% and 100% respectively for distinguishing the subclinical pathology group from the normal group. CONCLUSIONS: Cortical ASL is useful for the identification of allografts with underlying pathologies. More importantly, ASL showed promise as a non-invasive tool for the clinical translation of identifying kidney allografts with subclinical pathology. KEY POINTS: • Cortical ASL values were decreased in kidney allografts with subclinical pathologic changes as compared with normal allografts (152.5 ± 38.9 ml/min/100 g vs 204.7 ± 44.9 ml/min/100 g, p < 0.001). • Cortical ASL differentiated allografts with pathologic changes and subclinical pathology group from normal group with an AUC of 0.92 (95% CI, 0.83-0.97) and 0.80 (95% CI, 0.64-0.91) respectively. • Cortical ASL discriminated allografts with underlying pathologic changes from normal allografts with a specificity of 100%, and combined use of proteinuria and cortical ASL values could also achieve 100% specificity for discriminating allografts with subclinical pathology from normal allografts.


Assuntos
Transplante de Rim , Humanos , Rim/diagnóstico por imagem , Imageamento por Ressonância Magnética , Circulação Renal , Marcadores de Spin
16.
Eur Radiol ; 31(6): 4130-4137, 2021 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-33247346

RESUMO

OBJECTIVE: To compare the DWI-Alberta Stroke Program Early Computed Tomography Score calculated by a deep learning-based automatic software tool (eDWI-ASPECTS) with the neuroradiologists' evaluation for the acute stroke, with emphasis on its performance on 10 individual ASPECTS regions, and to determine the reasons for inconsistencies between eDWI-ASPECTS and neuroradiologists' evaluation. METHODS: This retrospective study included patients with middle cerebral artery stroke who underwent MRI from 2010 to 2019. All scans were evaluated by eDWI-ASPECTS and two independent neuroradiologists (with 15 and 5 years of experience in stroke study). Inter-rater agreement and agreement between manual vs. automated methods for total and each region were evaluated by calculating Kendall's tau-b, intraclass correlation coefficient (ICC), and kappa coefficient. RESULTS: In total, 309 patients met our study criteria. For total ASPECTS, eDWI-ASPECTS and manual raters had a strong positive correlation (Kendall's tau-b = 0.827 for junior raters vs. eDWI-ASPECTS; Kendall's tau-b = 0.870 for inter-raters; Kendall's tau-b = 0.848 for senior raters vs. eDWI-ASPECTS) and excellent agreement (ICC = 0.923 for junior raters and automated scores; ICC = 0.954 for inter-raters; ICC = 0.939 for senior raters and automated scores). Agreement was different for individual ASPECTS regions. All regions except for M5 region (κ = 0.216 for junior raters and automated scores), internal capsule (κ = 0.525 for junior raters and automated scores), and caudate (κ = 0.586 for senior raters and automated scores) showed good to excellent concordance. CONCLUSION: The eDWI-ASPECTS performed equally well as senior neuroradiologists' evaluation, although interference by uncertain scoring rules and midline shift resulted in poor to moderate consistency in the M5, internal capsule, and caudate nucleus regions. KEY POINTS: • The eDWI-ASPECTS based on deep learning perform equally well as senior neuroradiologists' evaluations. • Among the individual ASPECTS regions, the M5, internal capsule, and caudate regions mainly affected the overall consistency. • Uncertain scoring rules and midline shift are the main reasons for regional inconsistency.


Assuntos
Isquemia Encefálica , AVC Isquêmico , Acidente Vascular Cerebral , Alberta , Isquemia Encefálica/diagnóstico por imagem , Humanos , Variações Dependentes do Observador , Reprodutibilidade dos Testes , Estudos Retrospectivos , Acidente Vascular Cerebral/diagnóstico por imagem
17.
J Hazard Mater ; 407: 124785, 2021 04 05.
Artigo em Inglês | MEDLINE | ID: mdl-33348203

RESUMO

Nitrogen-doped porous biochar (NPB) with a large specific surface area, wide pore size distribution, graphitized structure, nitrogen doping, and hydrophobicity was fabricated by high-temperature modification of algal biochar with potassium carbonate. This NPB was then uniformly coated on stainless steel wire as a novel solid-phase microextraction (SPME) fiber. The extraction efficiency of NPB-coated fiber for seven chlorobenzenes (CBs) was excellent; it was 1.0-112.2 times higher than that of commercial SPME fibers. A trace determination method was developed for seven CBs in water with the optimized extraction conditions by NPB-coated fiber and gas chromatography-electron capture detector, which showed wide linear ranges (1-1000 ng L-1), low detection limits (0.007-0.079 ng L-1), great repeatability (2.5-6.5% for intra-day, and 3.1-6.8% for inter-day), and excellent reproducibility (3.5-6.3%, n = 5). The practicality of the developed method was evaluated using real water samples and showed great recoveries (89.55-105.19%). This study showed that low-cost biomass wastes could be converted to advanced biochar materials by a facile method, and displayed excellent performance in SPME applications.


Assuntos
Microextração em Fase Sólida , Poluentes Químicos da Água , Carvão Vegetal , Clorobenzenos , Nitrogênio , Porosidade , Reprodutibilidade dos Testes , Água , Poluentes Químicos da Água/análise
18.
Front Oncol ; 10: 567160, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-33262942

RESUMO

Objectives: To investigate the development and validation of a radiomics nomogram based on PET/CT for guiding personalized targeted therapy in patients with lung adenocarcinoma mutation(s) in the EGFR gene. Methods: A cohort of 109 (77/32 in training/validation cohort) consecutive lung adenocarcinoma patients with an EGFR mutation was enrolled in this study. A total of 1672 radiomic features were extracted from PET and CT images, respectively. The least absolute shrinkage and selection operator (LASSO) Cox regression was used to select the radiomic features and construct the radiomics nomogram for the estimation of overall survival (OS), which was then assessed with respect to calibration and clinical usefulness. Patients with an EGFR mutation were divided into high- and low- risk groups according to their nomogram score. The treatment strategy for high- and low-risk groups was analyzed using Kaplan-Meier analysis and a log-rank test. Results: The C-index of the radiomics nomogram for the prediction of OS in lung adenocarcinoma in patients with an EGFR mutation was 0.840 and 0.803 in the training and validation cohorts, respectively. Distant metastasis [(Hazard ratio, HR),1.80], metabolic tumor volume (MTV, HR, 1.62), and rad score (HR, 17.23) were the independent risk factors for patients with an EGFR mutation. The calibration curve showed that the predicted survival time was remarkably close to the actual time. Decision curve analysis demonstrated that the radiomics nomogram was clinically useful. Targeted therapy for patients with high-risk EGFR mutations attained a greater benefit than other therapies (p < 0.0001), whereas the prognoses of the two therapies were similar in the low-risk group (p = 0.85). Conclusions: Development and validation of a radiomics nomogram based on PET/CT radiomic features combined with clinicopathological factors may guide targeted therapy for patients with lung adenocarcinoma with EGFR mutations. This is conducive to the advancement of precision medicine.

19.
medRxiv ; 2020 Nov 06.
Artigo em Inglês | MEDLINE | ID: mdl-33173894

RESUMO

The wave of COVID-19 continues to overwhelm the medical resources, especially the stressed intensive care unit (ICU) capacity and the shortage of mechanical ventilation (MV). Here we performed CT-based analysis combined with electronic health records and clinical laboratory results on Cohort 1 (n = 1662 from 17 hospitals) with prognostic estimation for the rapid stratification of PCR confirmed COVID-19 patients. These models, validated on Cohort 2 (n = 700) and Cohort 3 (n = 662) constructed from 9 external hospitals, achieved satisfying performance for predicting ICU, MV and death of COVID-19 patients (AUROC 0.916, 0.919 and 0.853), even on events happened two days later after admission (AUROC 0.919, 0.943 and 0.856). Both clinical and image features showed complementary roles in events prediction and provided accurate estimates to the time of progression (p<.001). Our findings are valuable for delivering timely treatment and optimizing the use of medical resources in the pandemic of COVID-19.

20.
Archaea ; 2020: 8841490, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-33223962

RESUMO

Thermophilic solid-state anaerobic digestion (SS-AD) of agricultural wastes, i.e., corn straw, cattle manure, and vegetable waste, was carried out in this study. The effects of temperature (40-60°C), initial solid content (ISC, 17.5-32.5%), and C/N ratio (15-32 : 1) on biogas production were evaluated using a Box-Behnken experimental design (BBD) combined with response surface methodology (RSM). The results showed that optimization of process parameters is important to promote the SS-AD performance. All the factors, including interactive terms (except the ISC), were significant in the quadratic model for biogas production with SS-AD. Among the three operation parameters, the C/N ratio had the largest effect on biogas production, followed by temperature, and a maximum biogas yield of 241.4 mL gVS-1 could be achieved at 47.3°C, ISC = 24.81%, and C/N = 22.35. After 20 d of SS-AD, the microbial community structure under different conditions was characterized by high-throughput sequencing, showing that Firmicutes, Bacteroidetes, Chloroflexi, Synergistetes, and Proteobacteria dominated the bacterial community, and that Firmicutes had a competitive advantage over Bacteroidetes at elevated temperatures. The biogas production values and relative abundance of OPB54 and Bacteroidia after 20 d of SS-AD can be fitted well using a quadratic model, implying that OPB54 and Bacteroidia play important roles in the methanogenic metabolism for agricultural waste thermophilic SS-AD.

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