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Qi Zhang

Bio: Qi Zhang is an academic researcher from Fudan University. The author has contributed to research in topics: Medicine & Ultrasound. The author has an hindex of 20, co-authored 100 publications receiving 1563 citations. Previous affiliations of Qi Zhang include Minjiang University & Duke University.


Papers
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Journal ArticleDOI
Qi Zhang1, Lili Wu1, Daohui Yang, Yijie Qiu1, Lingyun Yu, Yi Dong1, Wen-Ping Wang1 
TL;DR: Depending on its unique advantages as non-radiation, effective and convenient, D-CEUS analysis and quantitative parameters, particularly MI, has potential application value in following up of the CRT treatment response in LAPC patients.
Abstract: OBJECTIVES To investigate the value of dynamic contrast enhanced ultrasound (D-CEUS) in monitoring the chemoradiotherapy (CRT) therapeutic response of local advanced pancreatic ductal adenocarcinoma (LAPC). PATIENTS AND METHODS From October 2017 to December 2018, 11 patients diagnosed as LAPC were included (7 men, 4 women; mean age: 61.1±8.6 years). The algorithm of CRT was as following: the radiotherapy dose was 50.4 Gy/28Fx with S-1 40 mg bid orally taken in radiotherapy day. Conventional ultrasound scan and CEUS were performed before and 4 weeks after CRT. All ultrasound examinations were performed by an ACUSON Oxana 2 ultrasound equipment (Siemens Medical Solutions, Germany) with a C 6-1 convex array transducer (1-6 MHz). Time intensity curves (TICs) were generated in the region of interests (ROIs) both in LAPC lesions and in its surrounding pancreas parenchyma by SonoLiver software (TOMTEC Imaging Systems). Quantitative perfusion parameters including maximum intensity (MI), rise time (RT), mean transit time (mTT) and time to peak (TTP) were analyzed and compared before and after CRT. RESULTS No significant difference could be found by conventional B mode ultrasound scan after CRT. TICs of CEUS showed lower ascending and descending slopes rate after CRT. Among all perfusion quantitative parameters, MI decreased significantly after CRT (42.1±18.8% vs 27.8±17.2%, P < 0.05). CONCLUSIONS Depending on its unique advantages as non-radiation, effective and convenient, D-CEUS analysis and quantitative parameters, particularly MI, has potential application value in following up of the CRT treatment response in LAPC patients.

7 citations

Journal ArticleDOI
TL;DR: Computer-extracted CEUS features show reduced and more heterogeneous neovascularization of cancer after NAC, and achieve high accuracy for discriminating between pre- and post-chemotherapy cancers in responders and thus are potentially valuable for tumor response evaluation in clinical practice.

7 citations

Journal ArticleDOI
TL;DR: Ultrasound radiomic analysis based on the spatial and morphological features extracted from ultrasound images effectively contributed to the preoperative diagnosis of true and pseudo gallbladder polyps and may be valuable in their clinical management.
Abstract: Purpose: To explore the value of ultrasound radiomics in the preoperative identification of true and pseudo gallbladder polyps and to evaluate the associated diagnostic accuracy. Methods: Totally, 99 pathologically proven gallbladder polyps in 96 patients were enrolled, including 58 cholesterol polyps (55 patients) and 41 gallbladder tubular adenomas (41 patients). Features on preoperative ultrasound images, including spatial and morphological features, were acquired for each lesion. Following this, two-stage feature selection was adopted using Fisher's inter-intraclass variance ratios and Z-scores for the selection of intrinsic features important for differential diagnosis achievement with support vector machine use. Results: Eighty radiomic features were extracted from each polyp. Eight intrinsic features were identified after two-stage selection. The contrast 14 (Cont14) and entropy 6 (Entr6) values in the cholesterol polyp group were significantly higher than those in the gallbladder adenoma group (4.063 ± 1.682 vs. 2.715 ± 1.867, p < 0.001 for Cont14; 4.712 ± 0.427 vs. 4.380 ± 0.720, p = 0.003 for Entr6); however, the homogeneity 13 (Homo13) and energy 8 (Ener8) values in the cholesterol polyp group were significantly lower (0.500 ± 0.069 vs. 0.572 ± 0.057, p < 0.001 for Homo13; 0.050 ± 0.023 vs. 0.068 ± 0.038, p = 0.002 for Ener8). These results indicate that the pixel distribution of cholesterol polyps was more uneven than that of gallbladder tubular adenomas. The dispersion degree was also significantly lower in the cholesterol polyp group than the gallbladder adenoma group (0.579 ± 0.054 vs. 0.608 ± 0.041, p = 0.005), indicating a lower dispersion of high-intensity areas in the cholesterol polyps. The long axis length of the fitting ellipse (Maj.Len), diameter of a circle equal to the lesion area (Eq.Dia) and perimeter (Per) values in the cholesterol polyp group were significantly lower than those in the gallbladder adenoma group (0.971 ± 0.485 vs. 1.738 ± 0.912, p < 0.001 for Maj.Len; 0.818 ± 0.393 vs. 1.438 ± 0.650, p < 0.001 for Eq.Dia; 2.637 ± 1.281 vs. 5.033 ± 2.353, p < 0.001 for Per), demonstrating that the cholesterol polyps were smaller and more regular in terms of morphology. The classification accuracy, sensitivity, specificity, and area under the curve values were 0.875, 0.885, 0.857, and 0.898, respectively. Conclusions: Ultrasound radiomic analysis based on the spatial and morphological features extracted from ultrasound images effectively contributed to the preoperative diagnosis of true and pseudo gallbladder polyps and may be valuable in their clinical management.

7 citations

Journal ArticleDOI
TL;DR: Real time visualization of contrast enhancement without radiation exposure is one of the main advantages of CEUS over other diagnostic modalities to differentiate ascariasis debris in the gallbladder from enhancing neoplasia and thus, surgery and other interventions and their complications could be avoided.
Abstract: Ascariasis debris of the gallbladder is a very rare incidental or symptomatic presentation. Ascaris debris has a pseudotumorous appearance and may be confused with neoplasia. The aim of the current retrospective study is to investigate the value of contrast enhanced ultrasound (CEUS) for the differential diagnosis of ascariasis debris and neoplasia of the gallbladder. Material and methods: Conventional B-mode ultrasound (BMUS) and CEUS were performed for solitary echo-rich gallbladder lesions. Analysis of the CEUS enhancement pattern of the lesions was conducted according to the current EFSUMB guidelines. Two radiologists assessed the CEUS enhancement patterns in consensus. The final gold standard was surgery with histological examination or imaging follow-up. Results: A total of 9 patients with final diagnoses of gallbladder ascariasis debris were included. As a control group 26 solitary hyperechoic gallbladder lesions without shadowing were included as a control group. The typical zigzag morphology with multiple echogenic parallel lines without shadow were detected inside the lumen of the gallbladder in 6 patients. After injection of 2.4 ml ultrasound contrast agents, all hyperechoic gallbladder ascariasis debris lesions showed no enhancement. All patients in the control group with similar BMUS morphology showed contrast enhancement. Conclusions: Real time visualization of contrast enhancement without radiation exposure is one of the main advantages of CEUS over other diagnostic modalities to differentiate ascariasis debris in the gallbladder from enhancing neoplasia. Thus, surgery and other interventions and their complications could be avoided.

7 citations

Journal ArticleDOI
TL;DR: The results indicate that acoustic tweezers based on 2D matrix arrays can realize complex and selective manipulation of living cells and organisms, thereby demonstrating their value for advancing research in the fields of cell assembly, tissue engineering, and micro-robot driving.
Abstract: Flexible manipulation techniques for living cells and organisms are extremely useful tools for fundamental biomedical and life science research. Acoustic tweezers, which permit non-contact, label-free manipulation, are particularly suited to micromanipulation tasks as they provide a large acoustic radiation force and can be applied in various media. Here, we describe the design and fabrication of a 3 MHz, 64-element (8 8), 2D planar ultrasound array that realizes the multidimensional translation, rotation, orientation, and levitation of living cells and organisms. The focusing vortex and twin fields are generated using the holographic acoustic elements framework method. We demonstrate that the eggs and larvae of brine shrimp can be translated along a preset trajectory by controlling the central position of the vortex. By multiplexing counterclockwise vortices, clockwise vortices, and twin trap fields in a time sequence, the rotation direction of the shrimp eggs can be switched in real time, while non-spherical larvae can be reoriented. Moreover, the reflection of the acoustic beam can lift eggs and larvae from the bottom of the culture dish and further manipulate them in the vertical and horizontal directions. Additionally, we present quantitative analyses of the relationships between the shrimp-egg rotation frequency and the focal depth, topological charge of the vortex, and excitation voltage. These results indicate that acoustic tweezers based on 2D matrix arrays can realize complex and selective manipulation of living cells and organisms, thereby demonstrating their value for advancing research in the fields of cell assembly, tissue engineering, and micro-robot driving.

7 citations


Cited by
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Christopher M. Bishop1
01 Jan 2006
TL;DR: Probability distributions of linear models for regression and classification are given in this article, along with a discussion of combining models and combining models in the context of machine learning and classification.
Abstract: Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.

10,141 citations

Journal ArticleDOI
TL;DR: This paper reviews the major deep learning concepts pertinent to medical image analysis and summarizes over 300 contributions to the field, most of which appeared in the last year, to survey the use of deep learning for image classification, object detection, segmentation, registration, and other tasks.

8,730 citations

01 Jan 2020
TL;DR: Prolonged viral shedding provides the rationale for a strategy of isolation of infected patients and optimal antiviral interventions in the future.
Abstract: Summary Background Since December, 2019, Wuhan, China, has experienced an outbreak of coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Epidemiological and clinical characteristics of patients with COVID-19 have been reported but risk factors for mortality and a detailed clinical course of illness, including viral shedding, have not been well described. Methods In this retrospective, multicentre cohort study, we included all adult inpatients (≥18 years old) with laboratory-confirmed COVID-19 from Jinyintan Hospital and Wuhan Pulmonary Hospital (Wuhan, China) who had been discharged or had died by Jan 31, 2020. Demographic, clinical, treatment, and laboratory data, including serial samples for viral RNA detection, were extracted from electronic medical records and compared between survivors and non-survivors. We used univariable and multivariable logistic regression methods to explore the risk factors associated with in-hospital death. Findings 191 patients (135 from Jinyintan Hospital and 56 from Wuhan Pulmonary Hospital) were included in this study, of whom 137 were discharged and 54 died in hospital. 91 (48%) patients had a comorbidity, with hypertension being the most common (58 [30%] patients), followed by diabetes (36 [19%] patients) and coronary heart disease (15 [8%] patients). Multivariable regression showed increasing odds of in-hospital death associated with older age (odds ratio 1·10, 95% CI 1·03–1·17, per year increase; p=0·0043), higher Sequential Organ Failure Assessment (SOFA) score (5·65, 2·61–12·23; p Interpretation The potential risk factors of older age, high SOFA score, and d-dimer greater than 1 μg/mL could help clinicians to identify patients with poor prognosis at an early stage. Prolonged viral shedding provides the rationale for a strategy of isolation of infected patients and optimal antiviral interventions in the future. Funding Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences; National Science Grant for Distinguished Young Scholars; National Key Research and Development Program of China; The Beijing Science and Technology Project; and Major Projects of National Science and Technology on New Drug Creation and Development.

4,408 citations

Journal ArticleDOI
TL;DR: In this article, the authors describe the long-term health consequences of patients with COVID-19 who have been discharged from hospital and investigate the associated risk factors, in particular disease severity.

2,933 citations

Journal ArticleDOI
07 Apr 2020-BMJ
TL;DR: Proposed models for covid-19 are poorly reported, at high risk of bias, and their reported performance is probably optimistic, according to a review of published and preprint reports.
Abstract: Objective To review and appraise the validity and usefulness of published and preprint reports of prediction models for diagnosing coronavirus disease 2019 (covid-19) in patients with suspected infection, for prognosis of patients with covid-19, and for detecting people in the general population at increased risk of covid-19 infection or being admitted to hospital with the disease. Design Living systematic review and critical appraisal by the COVID-PRECISE (Precise Risk Estimation to optimise covid-19 Care for Infected or Suspected patients in diverse sEttings) group. Data sources PubMed and Embase through Ovid, up to 1 July 2020, supplemented with arXiv, medRxiv, and bioRxiv up to 5 May 2020. Study selection Studies that developed or validated a multivariable covid-19 related prediction model. Data extraction At least two authors independently extracted data using the CHARMS (critical appraisal and data extraction for systematic reviews of prediction modelling studies) checklist; risk of bias was assessed using PROBAST (prediction model risk of bias assessment tool). Results 37 421 titles were screened, and 169 studies describing 232 prediction models were included. The review identified seven models for identifying people at risk in the general population; 118 diagnostic models for detecting covid-19 (75 were based on medical imaging, 10 to diagnose disease severity); and 107 prognostic models for predicting mortality risk, progression to severe disease, intensive care unit admission, ventilation, intubation, or length of hospital stay. The most frequent types of predictors included in the covid-19 prediction models are vital signs, age, comorbidities, and image features. Flu-like symptoms are frequently predictive in diagnostic models, while sex, C reactive protein, and lymphocyte counts are frequent prognostic factors. Reported C index estimates from the strongest form of validation available per model ranged from 0.71 to 0.99 in prediction models for the general population, from 0.65 to more than 0.99 in diagnostic models, and from 0.54 to 0.99 in prognostic models. All models were rated at high or unclear risk of bias, mostly because of non-representative selection of control patients, exclusion of patients who had not experienced the event of interest by the end of the study, high risk of model overfitting, and unclear reporting. Many models did not include a description of the target population (n=27, 12%) or care setting (n=75, 32%), and only 11 (5%) were externally validated by a calibration plot. The Jehi diagnostic model and the 4C mortality score were identified as promising models. Conclusion Prediction models for covid-19 are quickly entering the academic literature to support medical decision making at a time when they are urgently needed. This review indicates that almost all pubished prediction models are poorly reported, and at high risk of bias such that their reported predictive performance is probably optimistic. However, we have identified two (one diagnostic and one prognostic) promising models that should soon be validated in multiple cohorts, preferably through collaborative efforts and data sharing to also allow an investigation of the stability and heterogeneity in their performance across populations and settings. Details on all reviewed models are publicly available at https://www.covprecise.org/. Methodological guidance as provided in this paper should be followed because unreliable predictions could cause more harm than benefit in guiding clinical decisions. Finally, prediction model authors should adhere to the TRIPOD (transparent reporting of a multivariable prediction model for individual prognosis or diagnosis) reporting guideline. Systematic review registration Protocol https://osf.io/ehc47/, registration https://osf.io/wy245. Readers’ note This article is a living systematic review that will be updated to reflect emerging evidence. Updates may occur for up to two years from the date of original publication. This version is update 3 of the original article published on 7 April 2020 (BMJ 2020;369:m1328). Previous updates can be found as data supplements (https://www.bmj.com/content/369/bmj.m1328/related#datasupp). When citing this paper please consider adding the update number and date of access for clarity.

2,183 citations