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Automatic Detection of AMD and DME Retinal Pathologies Using Deep Learning. 利用深度学习自动检测AMD和DME视网膜病变。
IF 7.6 Q1 Medicine Pub Date : 2023-11-24 eCollection Date: 2023-01-01 DOI: 10.1155/2023/9966107
Latifa Saidi, Hajer Jomaa, Haddad Zainab, Hsouna Zgolli, Sonia Mabrouk, Désiré Sidibé, Hedi Tabia, Nawres Khlifa

Diabetic macular edema (DME) and age-related macular degeneration (AMD) are two common eye diseases. They are often undiagnosed or diagnosed late. This can result in permanent and irreversible vision loss. Therefore, early detection and treatment of these diseases can prevent vision loss, save money, and provide a better quality of life for individuals. Optical coherence tomography (OCT) imaging is widely applied to identify eye diseases, including DME and AMD. In this work, we developed automatic deep learning-based methods to detect these pathologies using SD-OCT scans. The convolutional neural network (CNN) from scratch we developed gave the best classification score with an accuracy higher than 99% on Duke dataset of OCT images.

糖尿病性黄斑水肿(DME)和老年性黄斑变性(AMD)是两种常见的眼病。它们通常未被诊断或诊断较晚。这可能导致永久性和不可逆转的视力丧失。因此,早期发现和治疗这些疾病可以预防视力下降,节省资金,并为个人提供更好的生活质量。光学相干断层扫描(OCT)被广泛应用于眼病的识别,包括DME和AMD。在这项工作中,我们开发了基于自动深度学习的方法,使用SD-OCT扫描来检测这些病理。我们从零开始开发的卷积神经网络(CNN)在杜克大学OCT图像数据集上的分类得分最高,准确率超过99%。
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引用次数: 0
Assessment of the Impact of Turbo Factor on Image Quality and Tissue Volumetrics in Brain Magnetic Resonance Imaging Using the Three-Dimensional T1-Weighted (3D T1W) Sequence. 利用三维t1加权(3D T1W)序列评估Turbo因子对脑磁共振成像图像质量和组织体积的影响。
IF 7.6 Q1 Medicine Pub Date : 2023-11-15 eCollection Date: 2023-01-01 DOI: 10.1155/2023/6304219
Eric Naab Manson, Stephen Inkoom, Abdul Nashirudeen Mumuni, Issahaku Shirazu, Adolf Kofi Awua

Background: The 3D T1W turbo field echo sequence is a standard imaging method for acquiring high-contrast images of the brain. However, the contrast-to-noise ratio (CNR) can be affected by the turbo factor, which could affect the delineation and segmentation of various structures in the brain and may consequently lead to misdiagnosis. This study is aimed at evaluating the effect of the turbo factor on image quality and volumetric measurement reproducibility in brain magnetic resonance imaging (MRI).

Methods: Brain images of five healthy volunteers with no history of neurological diseases were acquired on a 1.5 T MRI scanner with varying turbo factors of 50, 100, 150, 200, and 225. The images were processed and analyzed with FreeSurfer. The influence of the TFE factor on image quality and reproducibility of brain volume measurements was investigated. Image quality metrics assessed included the signal-to-noise ratio (SNR) of white matter (WM), CNR between gray matter/white matter (GM/WM) and gray matter/cerebrospinal fluid (GM/CSF), and Euler number (EN). Moreover, structural brain volume measurements of WM, GM, and CSF were conducted.

Results: Turbo factor 200 produced the best SNR (median = 17.01) and GM/WM CNR (median = 2.29), but turbo factor 100 offered the most reproducible SNR (IQR = 2.72) and GM/WM CNR (IQR = 0.14). Turbo factor 50 had the worst and the least reproducible SNR, whereas turbo factor 225 had the worst and the least reproducible GM/WM CNR. Turbo factor 200 again had the best GM/CSF CNR but offered the least reproducible GM/CSF CNR. Turbo factor 225 had the best performance on EN (-21), while turbo factor 200 was next to the most reproducible turbo factor on EN (11). The results showed that turbo factor 200 had the least data acquisition time, in addition to superior performance on SNR, GM/WM CNR, GM/CSF CNR, and good reproducibility characteristics on EN. Both image quality metrics and volumetric measurements did not vary significantly (p > 0.05) with the range of turbo factors used in the study by one-way ANOVA analysis.

Conclusion: Since no significant differences were observed in the performance of the turbo factors in terms of image quality and volume of brain structure, turbo factor 200 with a 74% acquisition time reduction was found to be optimal for brain MR imaging at 1.5 T.

背景:3D T1W涡轮场回波序列是获取高对比度大脑图像的标准成像方法。然而,噪声对比比(CNR)会受到涡轮系数的影响,从而影响对大脑各种结构的描绘和分割,从而可能导致误诊。本研究旨在评估涡轮系数对脑磁共振成像(MRI)图像质量和体积测量再现性的影响。方法:对5名无神经系统疾病史的健康志愿者进行1.5 T磁共振成像(MRI)扫描,turbo因子分别为50、100、150、200和225。使用FreeSurfer对图像进行处理和分析。研究了TFE因子对脑容量测量图像质量和再现性的影响。评估的图像质量指标包括白质(WM)的信噪比(SNR)、灰质/白质(GM/WM)与灰质/脑脊液(GM/CSF)之间的CNR和欧拉数(EN)。此外,还进行了WM、GM和CSF的结构脑体积测量。结果:Turbo因子200产生了最好的信噪比(中位数= 17.01)和GM/WM的CNR(中位数= 2.29),而Turbo因子100产生了最好的再现信噪比(IQR = 2.72)和GM/WM的CNR (IQR = 0.14)。涡轮因子50具有最差和最低的可重复信噪比,而涡轮因子225具有最差和最低的可重复GM/WM信噪比。Turbo factor 200仍然具有最佳的GM/CSF CNR,但提供了最低的再现性GM/CSF CNR。涡轮因子225在EN(-21)上的表现最好,而涡轮因子200在EN(11)上的再现性仅次于涡轮因子225。结果表明,turbo因子200的数据采集时间最短,在信噪比、GM/WM、GM/CSF CNR上表现优异,在EN上具有良好的再现性。通过单因素方差分析,图像质量指标和体积测量值与研究中使用的涡轮因子范围没有显著差异(p > 0.05)。结论:由于turbo因子在图像质量和脑结构体积方面的性能没有显著差异,因此在1.5 T时,turbo因子200的采集时间减少74%,是脑MR成像的最佳选择。
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引用次数: 0
Assessing Predictive Ability of Dynamic Time Warping Functional Connectivity for ASD Classification. 评估ASD分类的动态时间扭曲函数连接性的预测能力。
IF 7.6 Q1 Medicine Pub Date : 2023-10-25 eCollection Date: 2023-01-01 DOI: 10.1155/2023/8512461
Christopher Liu, Juanjuan Fan, Barbara Bailey, Ralph-Axel Müller, Annika Linke

Functional connectivity MRI (fcMRI) is a technique used to study the functional connectedness of distinct regions of the brain by measuring the temporal correlation between their blood oxygen level-dependent (BOLD) signals. fcMRI is typically measured with the Pearson correlation (PC), which assumes that there is no lag between time series. Dynamic time warping (DTW) is an alternative measure of similarity between time series that is robust to such time lags. We used PC fcMRI data and DTW fcMRI data as predictors in machine learning models for classifying autism spectrum disorder (ASD). When combined with dimension reduction techniques, such as principal component analysis, functional connectivity estimated with DTW showed greater predictive ability than functional connectivity estimated with PC. Our results suggest that DTW fcMRI can be a suitable alternative measure that may be characterizing fcMRI in a different, but complementary, way to PC fcMRI that is worth continued investigation. In studying different variants of cross validation (CV), our results suggest that, when it is necessary to tune model hyperparameters and assess model performance at the same time, a K-fold CV nested within leave-one-out CV may be a competitive contender in terms of performance and computational speed, especially when sample size is not large.

功能连接MRI(fcMRI)是一种用于通过测量大脑不同区域的血氧水平依赖性(BOLD)信号之间的时间相关性来研究其功能连接性的技术。fcMRI通常使用Pearson相关性(PC)进行测量,该相关性假设时间序列之间没有滞后。动态时间扭曲(DTW)是一种衡量时间序列之间相似性的替代方法,对这种时滞具有鲁棒性。我们使用PC fcMRI数据和DTW fcMRI数据作为机器学习模型中的预测因素,对自闭症谱系障碍(ASD)进行分类。当与主成分分析等降维技术相结合时,用DTW估计的功能连接性比用PC估计的功能连通性显示出更大的预测能力。我们的结果表明,DTW-fcMRI可以是一种合适的替代测量方法,可以以不同但互补的方式来表征fcMRI,值得继续研究的PC fcMRI方法。在研究交叉验证(CV)的不同变体时,我们的结果表明,当需要调整模型超参数并同时评估模型性能时,嵌套在保留一个CV中的K折叠CV在性能和计算速度方面可能是一个有竞争力的竞争者,尤其是在样本量不大的情况下。
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引用次数: 0
Prediction of Esophageal Varices in Viral Hepatitis C Cirrhosis: Performance of Combined Ultrasonography and Clinical Predictors. 病毒性丙型肝炎肝硬化食管静脉曲张的预测:联合超声检查和临床预测指标的表现。
IF 7.6 Q1 Medicine Pub Date : 2023-09-15 eCollection Date: 2023-01-01 DOI: 10.1155/2023/7938732
Puwitch Charoenchue, Wittanee Na Chiangmai, Amonlaya Amantakul, Wasuwit Wanchaitanawong, Taned Chitapanarux, Suwalee Pojchamarnwiputh

Objectives: This study is aimed at evaluating the diagnostic performance of clinical predictors and the Doppler ultrasonography in predicting esophageal varices (EV) in patients with hepatitis C-related cirrhosis and exploring the practical predictors of EV.

Methods: We conducted a prospective study from July 2020 to January 2021, enrolling 65 patients with mild hepatitis C-related cirrhosis. We obtained clinical data and performed grayscale and the Doppler ultrasound to explore the predictors of EV. Esophagogastroduodenoscopy (EGD) was performed as the reference test by the gastroenterologist within a week.

Results: The prevalence of EV in the study was 41.5%. Multivariable regression analysis revealed that gender (female, OR = 4.04, p = 0.02), platelet count (<150000 per ml, OR = 3.13, p = 0.09), splenic length (>11 cm, OR = 3.64, p = 0.02), and absent right hepatic vein (RHV) triphasicity (OR = 3.15, p = 0.03) were significant predictors of EV. However, the diagnostic accuracy indices for isolated predictors were not good (AUROC = 0.63-0.66). A combination of these four predictors increases the diagnostic accuracy in predicting the presence of EV (AUROC = 0.80, 95% CI 0.69-0.91). Furthermore, the Doppler assessment of the right hepatic vein waveform showed good reproducibility (κ = 0.76).

Conclusion: Combining clinical and Doppler ultrasound features can be used as a screening test for predicting the presence of EV in patients with hepatitis C-related cirrhosis. The practical predictors identified in this study could serve as an alternative to invasive EGD in EV diagnosis. Further studies are needed to explore the diagnostic accuracy of additional noninvasive predictors, such as elastography, to improve EV screening.

目的:本研究旨在评估临床预测指标和多普勒超声在预测丙型肝炎相关肝硬化患者食管静脉曲张(EV)方面的诊断性能,并探索EV的实用预测指标。方法:我们于2020年7月至2021年1月进行了一项前瞻性研究,纳入65名轻度丙型肝炎相关肝硬变患者。我们获得了临床数据,并进行了灰阶和多普勒超声检查,以探索EV的预测因素。胃肠科医生在一周内进行了食管胃十二指肠镜检查(EGD)作为参考测试。结果:研究中EV的患病率为41.5%。多因素回归分析显示,性别(女性,OR=4.04,p=0.02)、血小板计数(p=0.09)、脾脏长度(>11 cm,OR=3.64,p=0.02)和无右肝静脉(RHV)三相性(OR=3.15,p=0.03)是EV的显著预测因素。然而,单独预测因素的诊断准确性指数不好(AUROC=0.63-0.66)。这四个预测因素的组合提高了预测EV存在的诊断准确性(AUROC=0.80,95%CI 0.69-0.91)。此外,结论:结合临床和多普勒超声特征,可以作为预测丙型肝炎相关肝硬化患者EV存在的筛查试验。本研究中确定的实用预测因子可作为EV诊断中侵入性EGD的替代方案。需要进一步的研究来探索其他非侵入性预测因子的诊断准确性,如弹性成像,以改进EV筛查。
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引用次数: 0
Multiparametric Magnetic Resonance Imaging and Magnetic Resonance Elastography to Evaluate the Early Effects of Bariatric Surgery on Nonalcoholic Fatty Liver Disease. 多参数磁共振成像和磁共振弹性成像评估减肥手术对非酒精性脂肪性肝病的早期影响。
IF 7.6 Q1 Medicine Pub Date : 2023-01-01 DOI: 10.1155/2023/4228321
Hong Chang Tan, Elizabeth Shumbayawonda, Cayden Beyer, Lionel Tim-Ee Cheng, Albert Low, Chin Hong Lim, Alvin Eng, Weng Hoong Chan, Phong Ching Lee, Mei Fang Tay, Stella Kin, Jason Pik Eu Chang, Yong Mong Bee, George Boon Bee Goh

Background: Bariatric surgery is the most effective treatment for morbid obesity and reduces the severity of nonalcoholic fatty liver disease (NAFLD) in the long term. Less is known about the effects of bariatric surgery on liver fat, inflammation, and fibrosis during the early stages following bariatric surgery.

Aims: This exploratory study utilises advanced imaging methods to investigate NAFLD and fibrosis changes during the early metabolic transitional period following bariatric surgery.

Methods: Nine participants with morbid obesity underwent sleeve gastrectomy. Multiparametric MRI (mpMRI) and magnetic resonance elastography (MRE) were performed at baseline, during the immediate (1 month), and late (6 months) postsurgery period. Liver fat was measured using proton density fat fraction (PDFF), disease activity using iron-correct T1 (cT1), and liver stiffness using MRE. Repeated measured ANOVA was used to assess longitudinal changes and Dunnett's method for multiple comparisons.

Results: All participants (Age 45.1 ± 9.0 years, BMI 39.7 ± 5.3 kg/m2) had elevated hepatic steatosis at baseline (PDFF >5%). In the immediate postsurgery period, PDFF decreased significantly from 14.1 ± 7.4% to 8.9 ± 4.4% (p = 0.016) and cT1 from 826.9 ± 80.6 ms to 768.4 ± 50.9 ms (p = 0.047). These improvements continued to the later postsurgery period. Bariatric surgery did not reduce liver stiffness measurements.

Conclusion: Our findings support using MRI as a noninvasive tool to monitor NAFLD in patient with morbid obesity during the early stages following bariatric surgery.

背景:减肥手术是治疗病态肥胖最有效的方法,并能长期降低非酒精性脂肪性肝病(NAFLD)的严重程度。在减肥手术后的早期阶段,减肥手术对肝脏脂肪、炎症和纤维化的影响尚不清楚。目的:本探索性研究利用先进的成像方法研究减肥手术后早期代谢过渡期NAFLD和纤维化的变化。方法:9例病态肥胖患者行袖式胃切除术。在基线、术后即刻(1个月)和后期(6个月)分别进行多参数MRI (mpMRI)和磁共振弹性成像(MRE)检查。使用质子密度脂肪分数(PDFF)测量肝脏脂肪,使用铁校正T1 (cT1)测量疾病活动性,使用MRE测量肝脏硬度。采用重复测量方差分析评估纵向变化,采用Dunnett法进行多重比较。结果:所有参与者(年龄45.1±9.0岁,BMI 39.7±5.3 kg/m2)在基线时肝脏脂肪变性升高(PDFF >5%)。术后即刻PDFF由14.1±7.4%降至8.9±4.4% (p = 0.016), cT1由826.9±80.6 ms降至768.4±50.9 ms (p = 0.047)。这些改善持续到手术后期。减肥手术没有降低肝脏硬度测量值。结论:我们的研究结果支持使用MRI作为一种无创工具来监测减肥手术后早期病态肥胖患者的NAFLD。
{"title":"Multiparametric Magnetic Resonance Imaging and Magnetic Resonance Elastography to Evaluate the Early Effects of Bariatric Surgery on Nonalcoholic Fatty Liver Disease.","authors":"Hong Chang Tan,&nbsp;Elizabeth Shumbayawonda,&nbsp;Cayden Beyer,&nbsp;Lionel Tim-Ee Cheng,&nbsp;Albert Low,&nbsp;Chin Hong Lim,&nbsp;Alvin Eng,&nbsp;Weng Hoong Chan,&nbsp;Phong Ching Lee,&nbsp;Mei Fang Tay,&nbsp;Stella Kin,&nbsp;Jason Pik Eu Chang,&nbsp;Yong Mong Bee,&nbsp;George Boon Bee Goh","doi":"10.1155/2023/4228321","DOIUrl":"https://doi.org/10.1155/2023/4228321","url":null,"abstract":"<p><strong>Background: </strong>Bariatric surgery is the most effective treatment for morbid obesity and reduces the severity of nonalcoholic fatty liver disease (NAFLD) in the long term. Less is known about the effects of bariatric surgery on liver fat, inflammation, and fibrosis during the early stages following bariatric surgery.</p><p><strong>Aims: </strong>This exploratory study utilises advanced imaging methods to investigate NAFLD and fibrosis changes during the early metabolic transitional period following bariatric surgery.</p><p><strong>Methods: </strong>Nine participants with morbid obesity underwent sleeve gastrectomy. Multiparametric MRI (mpMRI) and magnetic resonance elastography (MRE) were performed at baseline, during the immediate (1 month), and late (6 months) postsurgery period. Liver fat was measured using proton density fat fraction (PDFF), disease activity using iron-correct T1 (cT1), and liver stiffness using MRE. Repeated measured ANOVA was used to assess longitudinal changes and Dunnett's method for multiple comparisons.</p><p><strong>Results: </strong>All participants (Age 45.1 ± 9.0 years, BMI 39.7 ± 5.3 kg/m<sup>2</sup>) had elevated hepatic steatosis at baseline (PDFF >5%). In the immediate postsurgery period, PDFF decreased significantly from 14.1 ± 7.4% to 8.9 ± 4.4% (<i>p</i> = 0.016) and cT1 from 826.9 ± 80.6 ms to 768.4 ± 50.9 ms (<i>p</i> = 0.047). These improvements continued to the later postsurgery period. Bariatric surgery did not reduce liver stiffness measurements.</p><p><strong>Conclusion: </strong>Our findings support using MRI as a noninvasive tool to monitor NAFLD in patient with morbid obesity during the early stages following bariatric surgery.</p>","PeriodicalId":47063,"journal":{"name":"International Journal of Biomedical Imaging","volume":null,"pages":null},"PeriodicalIF":7.6,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10372298/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9919473","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Enhanced Extraction of Blood and Tissue Time-Activity Curves in Cardiac Mouse FDG PET Imaging by Means of Constrained Nonnegative Matrix Factorization. 约束非负矩阵分解增强提取心脏小鼠FDG PET成像血液和组织时间-活性曲线。
IF 7.6 Q1 Medicine Pub Date : 2023-01-01 DOI: 10.1155/2023/5366733
Otman Sarrhini, Pedro D'Orléans-Juste, Jacques A Rousseau, Jean-François Beaudoin, Roger Lecomte

We propose an enhanced method to accurately retrieve time-activity curves (TACs) of blood and tissue from dynamic 2-deoxy-2-[18F]fluoro-D-glucose ([18F]FDG) positron emission tomography (PET) cardiac images of mice. The method is noninvasive and consists of using a constrained nonnegative matrix factorization algorithm (CNMF) applied to the matrix (A) containing the intensity values of the voxels of the left ventricle (LV) PET image. CNMF factorizes A into nonnegative matrices H and W, respectively, representing the physiological factors (blood and tissue) and their associated weights, by minimizing an extended cost function. We verified our method on 32 C57BL/6 mice, 14 of them with acute myocardial infarction (AMI). With CNMF, we could break down the mouse LV into myocardial and blood pool images. Their corresponding TACs were used in kinetic modeling to readily determine the [18F]FDG influx constant (Ki) required to compute the myocardial metabolic rate of glucose. The calculated Ki values using CNMF for the heart of control mice were in good agreement with those published in the literature. Significant differences in Ki values for the heart of control and AMI mice were found using CNMF. The values of the elements of W agreed well with the LV structural changes induced by ligation of the left coronary artery. CNMF was compared with the recently published method based on robust unmixing of dynamic sequences using regions of interest (RUDUR). A clear improvement of signal separation was observed with CNMF compared to the RUDUR method.

我们提出了一种增强的方法,可以准确地从小鼠动态2-脱氧-2-[18F]氟-d -葡萄糖([18F]FDG)正电子发射断层扫描(PET)心脏图像中检索血液和组织的时间-活性曲线(tac)。该方法是非侵入性的,使用约束非负矩阵分解算法(CNMF)应用于包含左心室(LV) PET图像体素强度值的矩阵(a)。CNMF通过最小化扩展成本函数,将A分解为非负矩阵H和W,分别表示生理因素(血液和组织)及其相关权重。我们在32只C57BL/6小鼠身上验证了我们的方法,其中14只患有急性心肌梗死(AMI)。利用CNMF,我们可以将小鼠左室分解成心肌和血池图像。将它们对应的tac用于动力学建模,以方便地确定计算心肌葡萄糖代谢率所需的[18F]FDG内流常数(Ki)。使用CNMF计算的对照小鼠心脏Ki值与文献中发表的值一致。使用CNMF发现对照组和AMI小鼠心脏的Ki值有显著差异。W元素值与左冠状动脉结扎引起的左室结构改变吻合较好。将CNMF与最近发表的基于感兴趣区域(RUDUR)的动态序列鲁棒解混方法进行了比较。与RUDUR方法相比,CNMF方法明显改善了信号分离。
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引用次数: 2
In Vivo Fluorine Imaging Using 1.5 Tesla MRI for Depiction of Experimental Myocarditis in a Rodent Animal Model. 使用1.5特斯拉磁共振成像在体内氟成像描绘实验性心肌炎在啮齿动物模型。
IF 7.6 Q1 Medicine Pub Date : 2023-01-01 DOI: 10.1155/2023/4659041
Thore Dietrich, Stephan Theodor Bujak, Thorsten Keller, Bernhard Schnackenburg, Riad Bourayou, Rolf Gebker, Kristof Graf, Eckart Fleck

The usefulness of perfluorocarbon nanoemulsions for the imaging of experimental myocarditis has been demonstrated in a high-field 9.4 Tesla MRI scanner. Our proof-of-concept study investigated the imaging capacity of PFC-based 19F/1H MRI in an animal myocarditis model using a clinical field strength of 1.5 Tesla. To induce experimental myocarditis, five male rats (weight ~300 g, age ~50 days) were treated with one application per week of doxorubicin (2 mg/kg BW) over a period of six weeks. Three control animals received the identical volume of sodium chloride 0.9% instead. Following week six, all animals received a single 4 ml injection of an 20% oil-in-water perfluorooctylbromide nanoemulsion 24 hours prior to in vivo1H/19F imaging on a 1.5 Tesla MRI. After euthanasia, cardiac histology and immunohistochemistry using CD68/ED1 macrophage antibodies were performed, measuring the inflamed myocardium in μm2 for further statistical analysis to compare the extent of the inflammation with the 19F-MRI signal intensity. All animals treated with doxorubicin showed a specific signal in the myocardium, while no myocardial signal could be detected in the control group. Additionally, the doxorubicin group showed a significantly higher SNR for 19F and a stronger CD68/ED1 immunhistoreactivity compared to the control group. This proof-of-concept study demonstrates that perfluorocarbon nanoemulsions could be detected in an in vivo experimental myocarditis model at a currently clinically relevant field strength.

全氟碳纳米乳对实验性心肌炎成像的有用性已在高场9.4特斯拉MRI扫描仪中得到证实。我们的概念验证研究考察了基于pfc的19F/1H MRI在动物心肌炎模型中使用1.5特斯拉临床场强的成像能力。为了诱导实验性心肌炎,将5只体重~300 g、年龄~50日龄的雄性大鼠,每周1次给予阿霉素(2 mg/kg BW),持续6周。而对照组的三只动物则注射了相同体积的0.9%氯化钠。第六周后,所有动物在1.5特斯拉MRI 1h /19F成像前24小时接受单次4 ml 20%水包油全氟辛基溴纳米乳注射。安乐死后采用CD68/ED1巨噬细胞抗体进行心脏组织学和免疫组化,以μm2为单位测量炎症心肌,进一步统计分析炎症程度与19F-MRI信号强度的比较。阿霉素处理的所有动物心肌均有特异信号,而对照组未检测到心肌信号。此外,与对照组相比,阿霉素组显示出更高的19F信噪比和更强的CD68/ED1免疫组化活性。这项概念验证研究表明,全氟碳纳米乳剂可以在体内实验心肌炎模型中以当前临床相关的场强检测到。
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引用次数: 0
Chest X-Ray Images to Differentiate COVID-19 from Pneumonia with Artificial Intelligence Techniques. 利用人工智能技术通过胸部 X 光图像区分 COVID-19 和肺炎
IF 3.3 Q2 ENGINEERING, BIOMEDICAL Pub Date : 2022-12-22 eCollection Date: 2022-01-01 DOI: 10.1155/2022/5318447
Rumana Islam, Mohammed Tarique

This paper presents an automated and noninvasive technique to discriminate COVID-19 patients from pneumonia patients using chest X-ray images and artificial intelligence. The reverse transcription-polymerase chain reaction (RT-PCR) test is commonly administered to detect COVID-19. However, the RT-PCR test necessitates person-to-person contact to administer, requires variable time to produce results, and is expensive. Moreover, this test is still unreachable to the significant global population. The chest X-ray images can play an important role here as the X-ray machines are commonly available at any healthcare facility. However, the chest X-ray images of COVID-19 and viral pneumonia patients are very similar and often lead to misdiagnosis subjectively. This investigation has employed two algorithms to solve this problem objectively. One algorithm uses lower-dimension encoded features extracted from the X-ray images and applies them to the machine learning algorithms for final classification. The other algorithm relies on the inbuilt feature extractor network to extract features from the X-ray images and classifies them with a pretrained deep neural network VGG16. The simulation results show that the proposed two algorithms can extricate COVID-19 patients from pneumonia with the best accuracy of 100% and 98.1%, employing VGG16 and the machine learning algorithm, respectively. The performances of these two algorithms have also been collated with those of other existing state-of-the-art methods.

本文介绍了一种利用胸部 X 光图像和人工智能区分 COVID-19 患者和肺炎患者的自动化、无创技术。逆转录聚合酶链反应(RT-PCR)测试是检测 COVID-19 的常用方法。然而,RT-PCR 检测需要人与人之间的接触才能进行,产生结果所需的时间不固定,而且价格昂贵。此外,这种检测方法仍无法惠及全球大量人口。胸部 X 光图像在这方面可以发挥重要作用,因为任何医疗机构都有 X 光机。然而,COVID-19 和病毒性肺炎患者的胸部 X 光图像非常相似,往往会导致主观误诊。这项研究采用了两种算法来客观地解决这一问题。一种算法使用从 X 光图像中提取的低维编码特征,并将其应用于机器学习算法进行最终分类。另一种算法则依靠内置的特征提取器网络从 X 光图像中提取特征,并通过预训练的深度神经网络 VGG16 进行分类。仿真结果表明,采用 VGG16 和机器学习算法,所提出的两种算法可将 COVID-19 患者从肺炎中解救出来,准确率分别达到 100%和 98.1%。这两种算法的性能还与其他现有的先进方法进行了比较。
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引用次数: 0
Comparison of Diffusion Tensor Imaging Metrics in Normal-Appearing White Matter to Cerebrovascular Lesions and Correlation with Cerebrovascular Disease Risk Factors and Severity. 正常脑白质弥散张量成像指标与脑血管病变的比较及其与脑血管疾病危险因素和严重程度的相关性
IF 7.6 Q1 Medicine Pub Date : 2022-10-21 eCollection Date: 2022-01-01 DOI: 10.1155/2022/5860364
Seyyed M H Haddad, Christopher J M Scott, Miracle Ozzoude, Courtney Berezuk, Melissa Holmes, Sabrina Adamo, Joel Ramirez, Stephen R Arnott, Nuwan D Nanayakkara, Malcolm Binns, Derek Beaton, Wendy Lou, Kelly Sunderland, Sujeevini Sujanthan, Jane Lawrence, Donna Kwan, Brian Tan, Leanne Casaubon, Jennifer Mandzia, Demetrios Sahlas, Gustavo Saposnik, Ayman Hassan, Brian Levine, Paula McLaughlin, J B Orange, Angela Roberts, Angela Troyer, Sandra E Black, Dar Dowlatshahi, Stephen C Strother, Richard H Swartz, Sean Symons, Manuel Montero-Odasso, Ondri Investigators, Robert Bartha

Alterations in tissue microstructure in normal-appearing white matter (NAWM), specifically measured by diffusion tensor imaging (DTI) fractional anisotropy (FA), have been associated with cognitive outcomes following stroke. The purpose of this study was to comprehensively compare conventional DTI measures of tissue microstructure in NAWM to diverse vascular brain lesions in people with cerebrovascular disease (CVD) and to examine associations between FA in NAWM and cerebrovascular risk factors. DTI metrics including fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) were measured in cerebral tissues and cerebrovascular anomalies from 152 people with CVD participating in the Ontario Neurodegenerative Disease Research Initiative (ONDRI). Ten cerebral tissue types were segmented including NAWM, and vascular lesions including stroke, periventricular and deep white matter hyperintensities, periventricular and deep lacunar infarcts, and perivascular spaces (PVS) using T1-weighted, proton density-weighted, T2-weighted, and fluid attenuated inversion recovery MRI scans. Mean DTI metrics were measured in each tissue region using a previously developed DTI processing pipeline and compared between tissues using multivariate analysis of covariance. Associations between FA in NAWM and several CVD risk factors were also examined. DTI metrics in vascular lesions differed significantly from healthy tissue. Specifically, all tissue types had significantly different MD values, while FA was also found to be different in most tissue types. FA in NAWM was inversely related to hypertension and modified Rankin scale (mRS). This study demonstrated the differences between conventional DTI metrics, FA, MD, AD, and RD, in cerebral vascular lesions and healthy tissue types. Therefore, incorporating DTI to characterize the integrity of the tissue microstructure could help to define the extent and severity of various brain vascular anomalies. The association between FA within NAWM and clinical evaluation of hypertension and disability provides further evidence that white matter microstructural integrity is impacted by cerebrovascular function.

通过弥散张量成像(DTI)分数各向异性(FA)测量的正常白质(NAWM)组织微观结构的改变与脑卒中后的认知结果有关。本研究的目的是全面比较脑血管疾病(CVD)患者NAWM组织微观结构的常规DTI测量,并研究NAWM中FA与脑血管危险因素之间的关系。DTI指标包括分数各向异性(FA)、平均扩散率(MD)、轴向扩散率(AD)和径向扩散率(RD),测量了参加安大略省神经退行性疾病研究计划(ONDRI)的152名CVD患者的脑组织和脑血管异常。采用t1加权、质子密度加权、t2加权和液体衰减反转恢复MRI扫描,对包括NAWM在内的10种脑组织进行分割,并对包括脑卒中、脑室周围和深部白质高信号、脑室周围和深部腔隙梗死以及血管周围间隙(PVS)在内的血管病变进行分割。使用先前开发的DTI处理管道测量每个组织区域的平均DTI指标,并使用多变量协方差分析比较组织之间的差异。NAWM中FA与几种CVD危险因素之间的关系也进行了研究。血管病变的DTI指标与健康组织有显著差异。具体而言,所有组织类型的MD值都有显著差异,而FA在大多数组织类型中也存在差异。NAWM患者FA与高血压、改良Rankin量表(mRS)呈负相关。本研究证明了常规DTI指标FA、MD、AD和RD在脑血管病变和健康组织类型中的差异。因此,结合DTI来表征组织微观结构的完整性有助于确定各种脑血管异常的程度和严重程度。NAWM内FA与高血压和残疾的临床评估之间的关联进一步证明了白质微结构完整性受到脑血管功能的影响。
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引用次数: 2
Towards an Accurate MRI Acute Ischemic Stroke Lesion Segmentation Based on Bioheat Equation and U-Net Model. 基于生物热方程和U-Net模型的MRI急性缺血性脑卒中病灶精确分割。
IF 7.6 Q1 Medicine Pub Date : 2022-07-16 eCollection Date: 2022-01-01 DOI: 10.1155/2022/5529726
Abdelmajid Bousselham, Omar Bouattane, Mohamed Youssfi, Abdelhadi Raihani

Acute ischemic stroke represents a cerebrovascular disease, for which it is practical, albeit challenging to segment and differentiate infarct core from salvageable penumbra brain tissue. Ischemic stroke causes the variation of cerebral blood flow and heat generation due to metabolism. Therefore, the temperature is modified in the ischemic stroke region. In this paper, we incorporate acute ischemic stroke temperature profile to reinforce segmentation accuracy in MRI. Pennes bioheat equation was used to generate brain thermal images that may provide rich information regarding the temperature change in acute ischemic stroke lesions. The thermal images were generated by calculating the temperature of the brain with acute ischemic stroke. Then, U-Net was used in this paper for the segmentation of acute ischemic stroke. A dataset of 3192 images was created to train U-Net using k-fold crossvalidation. The training time was about 10 hours and 35 minutes in NVIDIA GPU. Next, the obtained trained model was compared with recent methods to analyze the effect of the ischemic stroke temperature profile in segmentation. The obtained results show that significant parts of acute ischemic stroke and background areas are segmented only in thermal images, which proves the importance of using thermal information to improve the segmentation outcomes in MRI diagnosis.

急性缺血性脑卒中是一种脑血管疾病,尽管从可抢救的半暗区脑组织中分割和区分梗死核心具有挑战性,但它是实用的。缺血性脑卒中由于代谢引起脑血流量和产热的变化。因此,缺血性脑卒中区域的温度被修改。在本文中,我们结合急性缺血性脑卒中温度剖面来增强MRI分割的准确性。利用Pennes生物热方程生成脑热图像,可以提供关于急性缺血性脑卒中病变温度变化的丰富信息。热图像是通过计算急性缺血性脑卒中患者的大脑温度生成的。然后,本文采用U-Net方法对急性缺血性脑卒中进行图像分割。创建了3192张图像的数据集,使用k-fold交叉验证来训练U-Net。在NVIDIA GPU下的训练时间约为10小时35分钟。然后,将得到的训练模型与现有方法进行比较,分析脑缺血温度分布对分割的影响。结果表明,急性缺血性脑卒中的重要部分和背景区域仅在热图像中被分割,这证明了利用热信息改善MRI诊断分割结果的重要性。
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引用次数: 0
期刊
International Journal of Biomedical Imaging
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