AIM: To compare breath-hold cartesian volumetric interpolated breath-hold examination(cVIBE) and freebreathing radial VIBE(rVIBE) and determine whether rVIBE could replace cVIBE in routine liver magnetic resonance ima...AIM: To compare breath-hold cartesian volumetric interpolated breath-hold examination(cVIBE) and freebreathing radial VIBE(rVIBE) and determine whether rVIBE could replace cVIBE in routine liver magnetic resonance imaging(MRI).METHODS: In this prospective study, 15 consecutive patients scheduled for routine MRI of the abdomen underwent pre- and post-contrast breath-hold cVIBE imaging(19 s acquisition time) and free-breathing rVIBE imaging(111 s acquisition time) on a 1.5T Siemens scanner. Three radiologists with 2, 4, and 8 years post-fellowship experience in abdominal imaging evaluated all images. The radiologists were blinded to the sequence types, which were presented in a random order for each patient. For each sequence, the radiologists scored the cVIBE and rVIBE images for liver edge sharpness, hepatic vessel clarity, presence of artifacts, lesion conspicuity, fat saturation, and overall image quality using a five-point scale. RESULTS: Compared to rVIBE, cVIBE yielded significantly(P < 0.001) higher scores for liver edge sharpness(mean score, 3.87 vs 3.37), hepatic-vessel clarity(3.71 vs 3.18), artifacts(3.74 vs 3.06), lesion conspicuity(3.81 vs 3.2), and overall image quality(3.91 vs 3.24). cVIBE and rVIBE did not significantly differ in quality of fat saturation(4.12 vs 4.03, P = 0.17). The inter-observer variability with respect to differences between rVIBE and cVIBE scores was close to zero compared to random error and inter-patient variation. Quality of rVIBE images was rated as acceptable for all parameters. CONCLUSION: rVIBE cannot replace cVIBE in routine liver MRI. At 1.5T, free-breathing rVIBE yields acceptable, although slightly inferior image quality compared to breath-hold cVIBE.展开更多
BACKGROUND Diffusion-weighted imaging(DWI)has become a useful tool in the detection,characterization,and evaluation of response to treatment of many cancers,including malignant liver lesions.DWI offers higher image co...BACKGROUND Diffusion-weighted imaging(DWI)has become a useful tool in the detection,characterization,and evaluation of response to treatment of many cancers,including malignant liver lesions.DWI offers higher image contrast between lesions and normal liver tissue than other sequences.DWI images acquired at two or more b-values can be used to derive an apparent diffusion coefficient(ADC).DWI in the body has several technical challenges.This include ghosting artifacts,mis-registration and susceptibility artifacts.New DWI sequences have been developed to overcome some of these challenges.Our goal is to evaluate 3 new DWI sequences for liver imaging.AIM To qualitatively and quantitatively compare 3 DWI sequences for liver imaging:free-breathing(FB),simultaneous multislice(SMS),and prospective acquisition correction(PACE).METHODS Magnetic resonance imaging(MRI)was performed in 20 patients in this prospective study.The MR study included 3 separate DWI sequences:FB-DWI,SMS-DWI,and PACE-DWI.The image quality,mean ADC,standard deviations(SD)of ADC,and ADC histogram were compared.Wilcoxon signed-rank tests were used to compare qualitative image quality.A linear mixed model was used to compare the mean ADC and the SDs of the ADC values.All tests were 2-sided and P values of<0.05 were considered statistically significant.RESULTS There were 56 lesions(50 malignant)evaluated in this study.The mean qualitative image quality score of PACE-DWI was 4.48.This was significantly better than that of SMS-DWI(4.22)and FB-DWI(3.15)(P<0.05).Quantitatively,the mean ADC values from the 3 different sequences did not significantly differ for each liver lesion.FB-DWI had a markedly higher variation in the SD of the ADC values than did SMS-DWI and PACE-DWI.We found statistically significant differences in the SDs of the ADC values for FB-DWI vs PACE-DWI(P<0.0001)and for FB-DWI vs SMS-DWI(P=0.03).The SD of the ADC values was not statistically significant for PACE-DWI and SMS-DWI(P=0.18).The quality of the PACE-DWI ADC histograms were considered better than the SMS-DWI and FB-DWI.CONCLUSION Compared to FB-DWI,both PACE-DWI and SMS-DWI provide better image quality and decreased quantitative variability in the measurement of ADC values of liver lesions.展开更多
Tissue-classification-based attenuation correction strategies have been previously proposed to correct for bone attenuation in PET/MR imaging and simulated using computed tomography. However, the complication of voxel...Tissue-classification-based attenuation correction strategies have been previously proposed to correct for bone attenuation in PET/MR imaging and simulated using computed tomography. However, the complication of voxel averaging uniquely associated with bone has not been considered explicitly in the past. This study investigated the effect of voxel averaging between bone and soft tissue in attenuation images and determined how accurately bone must be detected in MR images in order to perform acceptable attenuation correction of PET data by using CT-simulated attenuation correction. We found out that treating bone as soft tissue caused a mean quantification difference of -9.9% ± 5.5% in all 119 bone lesions. There were no significant differences between lesions in the pelvis and the vertebrae. The nominal difference in lesions in the ribs was significantly lower, likely due to the spatial misregistration between the emission and attenuation images. Interestingly, a non-monotonic relationship between the bone imaging ability and the absolute PET quantification accuracy was observed, with the minimal quantification difference achieved at a BVF around 40% for skull lesions (2.6% ± 2.1%), and 30% for non-skull lesions (1.4% ± 1.1%) and all lesions (1.5% ± 1.3%). This study established that a bone classification sensitivity of approximately 30% BVF is required in order for MR-based attenuation correction methods to achieve optimal quantification in whole-body PET/MR studies. For this purpose, higher bone imaging ability of MR may not be necessary.展开更多
BACKGROUND Impressive survival outcome of our previous study in unresectable hepatocellular carcinoma(HCC)patients undergoing yttrium-90 glass microspheres transarterial radioembolization(TARE)with/without sorafenib a...BACKGROUND Impressive survival outcome of our previous study in unresectable hepatocellular carcinoma(HCC)patients undergoing yttrium-90 glass microspheres transarterial radioembolization(TARE)with/without sorafenib according to individuals’disease burden,i.e.,intrahepatic tumor load(IHT)and adverse disease features(ADFs)might partly be confounded by other treatments and underlying hepatic function.Therefore,a dedicated study focusing on treatment response and assessment of failure patterns might be a way to improve treatment outcome in addition to patient selection based on the disease burden.AIM To assess the tumor response,disease control and patterns of disease progression following TARE with/without sorafenib in unresectable HCC patients.METHODS This retrospective study was conducted in successful TARE procedures with available pre-and post-treatment imaging studies(n=169).Three treatment subgroups were(1)TARE only(TARE_alone)for IHT≤50%without ADFs,i.e.,macrovascular invasion,extrahepatic disease(EHD)and infiltrative/ill-defined HCC(n=63);(2)TARE with sorafenib(TARE_sorafenib)for IHT>50%and/or presence of ADFs(n=81);and(3)TARE only for patients who could not receive sorafenib due to contraindication or intolerance(TARE_no_sorafenib)(n=25).Objective response rate(ORR;consisted of complete response(CR)and partial response(PR)),disease control rate(DCR;consisted of CR,PR and stable disease)and failure patterns of treated,intrahepatic and extrahepatic sites were assessed using the modified response evaluation criteria in solid tumors.Time to progression(TTP)was calculated from TARE to the first radiologic progression at any site using Kaplan-Meier method.Identification of prognostic factors for TTP using the univariate Kaplan-Meier method and multivariate Cox proportional hazard model were performed in major population subgroups,TARE_alone and TARE_sorafenib.RESULTS The median radiologic follow-up time was 4.4 mo(range 0.5-48.8).In treated area,ORR was highest in TARE_sorafenib(53.1%),followed by TARE_alone(41.3%)and TARE_no_sorafenib(16%).In intrahepatic area,DCR remained highest in TARE_sorafenib(84%),followed by TARE_alone(79.4%)and TARE_no_sorafenib(44%).The overall DCR was highest in TARE_alone(79.4%),followed by TARE_sorafenib(71.6%)and TARE_no_sorafenib(40%).Dominant failure patterns were intrahepatic for both TARE_alone(44.5%)and TARE_sorafenib(38.4%).Extrahepatic progression was more common in TARE_sorafenib(32%)and TARE_no_sorafenib(40%)than in TARE_alone(12.7%).TTP was longest in TARE_alone(8.6 mo;95%CI:3.4-13.8),followed by TARE_sorafenib(5.1 mo;95%CI:4.0-6.2)and TARE_no_sorafenib(2.7 mo;95%CI:2.2-3.1).Pre-existing EHD(HR:0.37,95%CI:0.24-0.56,P<0.001)was a sole prognostic factor for TTP in TARE_sorafenib with no prognostic factor for TTP in TARE_alone.CONCLUSION TARE with/without sorafenib according to individuals’disease burden provided DCR approximately 70%with intrahepatic progression as dominant failure pattern.Extrahepatic progression was more common in procedures with initially high disease burden.展开更多
The process of selecting features or reducing dimensionality can be viewed as a multi-objective minimization problem in which both the number of features and error rate must be minimized.While it is a multi-objective ...The process of selecting features or reducing dimensionality can be viewed as a multi-objective minimization problem in which both the number of features and error rate must be minimized.While it is a multi-objective problem,current methods tend to treat feature selection as a single-objective optimization task.This paper presents enhanced multi-objective grey wolf optimizer with Lévy flight and mutation phase(LMuMOGWO)for tackling feature selection problems.The proposed approach integrates two effective operators into the existing Multi-objective Grey Wolf optimizer(MOGWO):a Lévy flight and a mutation operator.The Lévy flight,a type of random walk with jump size determined by the Lévy distribution,enhances the global search capability of MOGWO,with the objective of maximizing classification accuracy while minimizing the number of selected features.The mutation operator is integrated to add more informative features that can assist in enhancing classification accuracy.As feature selection is a binary problem,the continuous search space is converted into a binary space using the sigmoid function.To evaluate the classification performance of the selected feature subset,the proposed approach employs a wrapper-based Artificial Neural Network(ANN).The effectiveness of the LMuMOGWO is validated on 12 conventional UCI benchmark datasets and compared with two existing variants of MOGWO,BMOGWO-S(based sigmoid),BMOGWO-V(based tanh)as well as Non-dominated Sorting Genetic Algorithm II(NSGA-II)and Multi-objective Particle Swarm Optimization(BMOPSO).The results demonstrate that the proposed LMuMOGWO approach is capable of successfully evolving and improving a set of randomly generated solutions for a given optimization problem.Moreover,the proposed approach outperforms existing approaches in most cases in terms of classification error rate,feature reduction,and computational cost.展开更多
We have developed a new form of intravascular optical coherence tomography(IV-OCT) that allows the extremely fast acquisition of high-resolution images of the coronary arteries.This process leads to much better image ...We have developed a new form of intravascular optical coherence tomography(IV-OCT) that allows the extremely fast acquisition of high-resolution images of the coronary arteries.This process leads to much better image quality by eliminating cardiac motion artefacts and undersampling.It relies on a catheter that incorporates a synchronous micromotor with a diameter of 1.0 mm and a rotational speed of up to5600 revolutions per second,enabling an IV-OCT frame rate of 5.6 kHz.This speed is matched by a wavelength-swept laser that generates up to 2.8 million image lines per second.With this setup,our team achieved IV-OCT imaging of up to5600 frames per second(fps) in vitro and 4000 fps in vivo,deployed at a 100 mm·s^(-1) pullback velocity.The imaging session is triggered by the electrocardiogram of the subject,and can scan a coronary artery in the phase of the heartbeat where the heart is at rest,providing a name for this new technology:the "Heartbeat OCT."展开更多
Radiochromic film with a dye incorporated into the radiation sensitive layer [Gafchromic EBT2, Ashland, Inc.] may be digitized by a color transparency scanner, digitally processed, and calibrated so that a digital ima...Radiochromic film with a dye incorporated into the radiation sensitive layer [Gafchromic EBT2, Ashland, Inc.] may be digitized by a color transparency scanner, digitally processed, and calibrated so that a digital image in units of radiation absorbed dose is obtained. A transformation from raw scanner values to dose values was developed based upon a principal component analysis of the optical densities of the red, green and blue channels of the color image of a dose of 0.942 Gy delivered by a Sr-90/Y-90 disk-shaped source. In the order of increasing eigenvalue, the three eigenimages of the principal component analysis contained, by visual inspection, 1) mainly noise;2) mainly a pattern of irregular streaks;and 3) most of the expected dose information along with some of the same background streaking that predominated in the second eigenimage. The combination of the second and third eigenimages that minimized the background streaking was converted into a transformation of the red, green and blue channels’ optical densities and applied to films with a range of doses from 0 to 63.7 Gy. The curve of dose vs. processed optical density was fit by a two-phase association curve. This processing was applied to a film exposed from its edge by a different Y-90 source in a configuration that was modeled by Monte Carlo simulation. The depth-dose curves of the measurement and simulation agree closely, suggesting that this approach is a valid method of processing EBT2 radiochromic film into maps of radiation absorbed dose.展开更多
Diabetes mellitus is a long-term condition characterized by hyperglycemia.It could lead to plenty of difficulties.According to rising morbidity in recent years,the world’s diabetic patients will exceed 642 million by...Diabetes mellitus is a long-term condition characterized by hyperglycemia.It could lead to plenty of difficulties.According to rising morbidity in recent years,the world’s diabetic patients will exceed 642 million by 2040,implying that one out of every ten persons will be diabetic.There is no doubt that this startling figure requires immediate attention from industry and academia to promote innovation and growth in diabetes risk prediction to save individuals’lives.Due to its rapid development,deep learning(DL)was used to predict numerous diseases.However,DLmethods still suffer from their limited prediction performance due to the hyperparameters selection and parameters optimization.Therefore,the selection of hyper-parameters is critical in improving classification performance.This study presents Convolutional Neural Network(CNN)that has achieved remarkable results in many medical domains where the Bayesian optimization algorithm(BOA)has been employed for hyperparameters selection and parameters optimization.Two issues have been investigated and solved during the experiment to enhance the results.The first is the dataset class imbalance,which is solved using Synthetic Minority Oversampling Technique(SMOTE)technique.The second issue is the model’s poor performance,which has been solved using the Bayesian optimization algorithm.The findings indicate that the Bayesian based-CNN model superbases all the state-of-the-art models in the literature with an accuracy of 89.36%,F1-score of 0.88.6,andMatthews Correlation Coefficient(MCC)of 0.88.6.展开更多
Generative Adversarial Networks(GANs)are neural networks that allow models to learn deep representations without requiring a large amount of training data.Semi-Supervised GAN Classifiers are a recent innovation in GAN...Generative Adversarial Networks(GANs)are neural networks that allow models to learn deep representations without requiring a large amount of training data.Semi-Supervised GAN Classifiers are a recent innovation in GANs,where GANs are used to classify generated images into real and fake and multiple classes,similar to a general multi-class classifier.However,GANs have a sophisticated design that can be challenging to train.This is because obtaining the proper set of parameters for all models-generator,discriminator,and classifier is complex.As a result,training a single GAN model for different datasets may not produce satisfactory results.Therefore,this study proposes an SGAN model(Semi-Supervised GAN Classifier).First,a baseline model was constructed.The model was then enhanced by leveraging the Sine-Cosine Algorithm and Synthetic Minority Oversampling Technique(SMOTE).SMOTE was used to address class imbalances in the dataset,while Sine Cosine Algorithm(SCA)was used to optimize the weights of the classifier models.The optimal set of hyperparameters(learning rate and batch size)were obtained using grid manual search.Four well-known benchmark datasets and a set of evaluation measures were used to validate the proposed model.The proposed method was then compared against existing models,and the results on each dataset were recorded and demonstrated the effectiveness of the proposed model.The proposed model successfully showed improved test accuracy scores of 1%,2%,15%,and 5%on benchmarking multimedia datasets;Modified National Institute of Standards and Technology(MNIST)digits,Fashion MNIST,Pneumonia Chest X-ray,and Facial Emotion Detection Dataset,respectively.展开更多
In the tumor microenvironment(TME),various types of immune cells interact with each other and with cancer cells,playing critical roles in cancer progression and treatment[1].Numerous studies have reported that the inf...In the tumor microenvironment(TME),various types of immune cells interact with each other and with cancer cells,playing critical roles in cancer progression and treatment[1].Numerous studies have reported that the infiltration levels of specific immune cells are associated with patient prognosis and response to immunotherapies[2,3].展开更多
As a two-dimensional planar material with low depth profile,a metasurface can generate non-classical phase distributions for the transmitted and reflected electromagnetic waves at its interface.Thus,it offers more fle...As a two-dimensional planar material with low depth profile,a metasurface can generate non-classical phase distributions for the transmitted and reflected electromagnetic waves at its interface.Thus,it offers more flexibility to control the wave front.A traditional metasurface design process mainly adopts the forward prediction algorithm,such as Finite Difference Time Domain,combined with manual parameter optimization.However,such methods are time-consuming,and it is difficult to keep the practical meta-atom spectrum being consistent with the ideal one.In addition,since the periodic boundary condition is used in the meta-atom design process,while the aperiodic condition is used in the array simulation,the coupling between neighboring meta-atoms leads to inevitable inaccuracy.In this review,representative intelligent methods for metasurface design are introduced and discussed,including machine learning,physics-information neural network,and topology optimization method.We elaborate on the principle of each approach,analyze their advantages and limitations,and discuss their potential applications.We also summarize recent advances in enabled metasurfaces for quantum optics applications.In short,this paper highlights a promising direction for intelligent metasurface designs and applications for future quantum optics research and serves as an up-to-date reference for researchers in the metasurface and metamaterial fields.展开更多
Background:Pulmonary sarcomatoid carcinoma(PSC)is a rare and aggressive subtype of non-small cell lung cancer(NSCLC),characterized by the presence of epithelial and sarcoma-like components.The molecular and immune lan...Background:Pulmonary sarcomatoid carcinoma(PSC)is a rare and aggressive subtype of non-small cell lung cancer(NSCLC),characterized by the presence of epithelial and sarcoma-like components.The molecular and immune landscape of PSC has not been well defined.Methods:Multiomics profiling of 21 pairs of PSCs with matched normal lung tissues was performed through targeted high-depth DNA panel,whole-exome,and RNA sequencing.We describe molecular and immune features that define subgroups of PSC with disparate genomic and immunogenic features as well as distinct clinical outcomes.Results:In total,27 canonical cancer gene mutations were identified,with TP53 the most frequently mutated gene,followed by KRAS.Interestingly,most TP53 and KRAS mutations were earlier genomic events mapped to the trunks of the tumors,suggesting branching evolution in most PSC tumors.We identified two distinct molecular subtypes of PSC,driven primarily by immune infiltration and signaling.The Immune High(IM-H)subtype was associated with superior survival,highlighting the impact of immune infiltration on the biological and clinical features of localized PSCs.Conclusions:We provided detailed insight into the mutational landscape of PSC and identified two molecular subtypes associated with prognosis.IM-H tumors were associated with favorable recurrence-free survival and overall survival,highlighting the importance of tumor immune infiltration in the biological and clinical features of PSCs.展开更多
Multimodal platforms combining electrical neural recording and stimulation,optogenetics,optical imaging,and magnetic resonance(MRI)imaging are emerging as a promising platform to enhance the depth of characterization ...Multimodal platforms combining electrical neural recording and stimulation,optogenetics,optical imaging,and magnetic resonance(MRI)imaging are emerging as a promising platform to enhance the depth of characterization in neuroscientific research.Electrically conductive,optically transparent,and MRI-compatible electrodes can optimally combine all modalities.Graphene as a suitable electrode candidate material can be grown via chemical vapor deposition(CVD)processes and sandwiched between transparent biocompatible polymers.However,due to the high graphene growth temperature(≥900℃)and the presence of polymers,fabrication is commonly based on a manual transfer process of pre-grown graphene sheets,which causes reliability issues.In this paper,we present CVD-based multilayer graphene electrodes fabricated using a wafer-scale transfer-free process for use in optically transparent and MRI-compatible neural interfaces.Our fabricated electrodes feature very low impedances which are comparable to those of noble metal electrodes of the same size and geometry.They also exhibit the highest charge storage capacity(CSC)reported to date among all previously fabricated CVD graphene electrodes.Our graphene electrodes did not reveal any photo-induced artifact during 10-Hz light pulse illumination.Additionally,we show here,for the first time,that CVD graphene electrodes do not cause any image artifact in a 3T MRI scanner.These results demonstrate that multilayer graphene electrodes are excellent candidates for the next generation of neural interfaces and can substitute the standard conventional metal electrodes.Our fabricated graphene electrodes enable multimodal neural recording,electrical and optogenetic stimulation,while allowing for optical imaging,as well as,artifact-free MRI studies.展开更多
Background:Type Ⅱ diabetes mellitus(DM2)is a significant risk factor for cancers,including breast cancer.However,a proper diabetic breast cancer mouse model is notwell-established for treatment strategy design.Additi...Background:Type Ⅱ diabetes mellitus(DM2)is a significant risk factor for cancers,including breast cancer.However,a proper diabetic breast cancer mouse model is notwell-established for treatment strategy design.Additionally,the precise diabetic signaling pathways that regulate cancer growth remain unresolved.In the present study,we established a suitable mouse model and demonstrated the pathogenic role of diabetes on breast cancer progression.Methods:We successfully generated a transgenic mouse model of human epidermal growth factor receptor 2 positive(Her2^(+) or ERBB2)breast cancer with DM2 by crossing leptin receptor mutant(Lepr^(db/+))mice with (MMTV-ErbB2/neu)mice.Themousemodelswere administrated with antidiabetic drugs to assess the impacts of controlling DM2 in affecting tumor growth.Magnetic resonance spectroscopic imaging was employed to analyze the tumor metabolism.Results:Treatment with metformin/rosiglitazone in MMTV-ErbB2/Lepr^(db/db) mousemodel reduced serum insulin levels,prolonged overall survival,decreased cumulative tumor incidence,and inhibited tumor progression.Anti-insulin resistance medications also inhibited glycolytic metabolism in tumors in vivo as indicated by the reduced metabolic flux of hyperpolarized ^(13)C pyruvate-to-lactate reaction.The tumor cells from MMTV-ErbB2/Lepr^(db/db) transgenic mice treated with metformin had reprogrammed metabolism by reducing levels of both oxygen consumption and lactate production.Metformin decreased the expression of Myc and pyruvate kinase isozyme 2(PKM2),leading to metabolism reprogramming.Moreover,metformin attenuated the mTOR/AKT signaling pathway and altered adipokine profiles.Conclusions:MMTV-ErbB2/Lepr^(db/db) mouse model was able to recapitulate diabetic HER2^(+) human breast cancer.Additionally,our results defined the signaling pathways deregulated in HER2^(+) breast cancer under diabetic condition,which can be intervened by anti-insulin resistance therapy.展开更多
In the semiconductor industry,the demand for more precise and accurate overlay metrology tools has increased because of the continued shrinking of feature sizes in integrated circuits.To achieve the required sub-nanom...In the semiconductor industry,the demand for more precise and accurate overlay metrology tools has increased because of the continued shrinking of feature sizes in integrated circuits.To achieve the required sub-nanometre precision,the current technology for overlay metrology has become complex and is reaching its limits.Herein,we present a dark-field digital holographic microscope using a simple two-element imaging lens with a high numerical aperture capable of imaging from the visible to near-infrared regions.This combination of high resolution and wavelength coverage was achieved by combining a simple imaging lens with a fast and accurate correction of non-isoplanatic aberrations.We present experimental results for overlay targets that demonstrate the capability of our computational aberration correction in the visible and near-infrared wavelength regimes.This wide-ranged-wavelength imaging system can advance semiconductor metrology.展开更多
Background:In this paper we determined the benefits of image registration on estimating longitudinal retinal nerve fiber layer thickness(RNFLT)changes.Methods:RNFLT maps around the optic nerve head(ONH)of healthy prim...Background:In this paper we determined the benefits of image registration on estimating longitudinal retinal nerve fiber layer thickness(RNFLT)changes.Methods:RNFLT maps around the optic nerve head(ONH)of healthy primate eyes were measured using Optical Coherence Tomography(OCT)weekly for 30 weeks.One automatic algorithm based on mutual information(MI)and the other semi-automatic algorithm based on log-polar transform cross-correlation using manually segmented blood vessels(LPCC_MSBV),were used to register retinal maps longitudinally.We compared the precision and recall between manually segmented image pairs for the two algorithms using a linear mixed effects model.Results:We found that the precision calculated between manually segmented image pairs following registration by LPCC_MSBV algorithm is significantly better than the one following registration by MI algorithm(p<<0.0001).Trend of the all-rings and temporal,superior,nasal and inferior(TSNI)quadrants average of RNFLT over time in healthy primate eyes are not affected by registration.RNFLT of clock hours 1,2,and 10 showed significant change over 30 weeks(p=0.0058,0.0054,and 0.0298 for clock hours 1,2 and 10 respectively)without registration,but stayed constant over time with registration.Conclusions:The LPCC_MSBV provides better registration of RNFLT maps recorded on different dates than the automatic MI algorithm.Registration of RNFLT maps can improve clinical analysis of glaucoma progression.展开更多
文摘AIM: To compare breath-hold cartesian volumetric interpolated breath-hold examination(cVIBE) and freebreathing radial VIBE(rVIBE) and determine whether rVIBE could replace cVIBE in routine liver magnetic resonance imaging(MRI).METHODS: In this prospective study, 15 consecutive patients scheduled for routine MRI of the abdomen underwent pre- and post-contrast breath-hold cVIBE imaging(19 s acquisition time) and free-breathing rVIBE imaging(111 s acquisition time) on a 1.5T Siemens scanner. Three radiologists with 2, 4, and 8 years post-fellowship experience in abdominal imaging evaluated all images. The radiologists were blinded to the sequence types, which were presented in a random order for each patient. For each sequence, the radiologists scored the cVIBE and rVIBE images for liver edge sharpness, hepatic vessel clarity, presence of artifacts, lesion conspicuity, fat saturation, and overall image quality using a five-point scale. RESULTS: Compared to rVIBE, cVIBE yielded significantly(P < 0.001) higher scores for liver edge sharpness(mean score, 3.87 vs 3.37), hepatic-vessel clarity(3.71 vs 3.18), artifacts(3.74 vs 3.06), lesion conspicuity(3.81 vs 3.2), and overall image quality(3.91 vs 3.24). cVIBE and rVIBE did not significantly differ in quality of fat saturation(4.12 vs 4.03, P = 0.17). The inter-observer variability with respect to differences between rVIBE and cVIBE scores was close to zero compared to random error and inter-patient variation. Quality of rVIBE images was rated as acceptable for all parameters. CONCLUSION: rVIBE cannot replace cVIBE in routine liver MRI. At 1.5T, free-breathing rVIBE yields acceptable, although slightly inferior image quality compared to breath-hold cVIBE.
文摘BACKGROUND Diffusion-weighted imaging(DWI)has become a useful tool in the detection,characterization,and evaluation of response to treatment of many cancers,including malignant liver lesions.DWI offers higher image contrast between lesions and normal liver tissue than other sequences.DWI images acquired at two or more b-values can be used to derive an apparent diffusion coefficient(ADC).DWI in the body has several technical challenges.This include ghosting artifacts,mis-registration and susceptibility artifacts.New DWI sequences have been developed to overcome some of these challenges.Our goal is to evaluate 3 new DWI sequences for liver imaging.AIM To qualitatively and quantitatively compare 3 DWI sequences for liver imaging:free-breathing(FB),simultaneous multislice(SMS),and prospective acquisition correction(PACE).METHODS Magnetic resonance imaging(MRI)was performed in 20 patients in this prospective study.The MR study included 3 separate DWI sequences:FB-DWI,SMS-DWI,and PACE-DWI.The image quality,mean ADC,standard deviations(SD)of ADC,and ADC histogram were compared.Wilcoxon signed-rank tests were used to compare qualitative image quality.A linear mixed model was used to compare the mean ADC and the SDs of the ADC values.All tests were 2-sided and P values of<0.05 were considered statistically significant.RESULTS There were 56 lesions(50 malignant)evaluated in this study.The mean qualitative image quality score of PACE-DWI was 4.48.This was significantly better than that of SMS-DWI(4.22)and FB-DWI(3.15)(P<0.05).Quantitatively,the mean ADC values from the 3 different sequences did not significantly differ for each liver lesion.FB-DWI had a markedly higher variation in the SD of the ADC values than did SMS-DWI and PACE-DWI.We found statistically significant differences in the SDs of the ADC values for FB-DWI vs PACE-DWI(P<0.0001)and for FB-DWI vs SMS-DWI(P=0.03).The SD of the ADC values was not statistically significant for PACE-DWI and SMS-DWI(P=0.18).The quality of the PACE-DWI ADC histograms were considered better than the SMS-DWI and FB-DWI.CONCLUSION Compared to FB-DWI,both PACE-DWI and SMS-DWI provide better image quality and decreased quantitative variability in the measurement of ADC values of liver lesions.
文摘Tissue-classification-based attenuation correction strategies have been previously proposed to correct for bone attenuation in PET/MR imaging and simulated using computed tomography. However, the complication of voxel averaging uniquely associated with bone has not been considered explicitly in the past. This study investigated the effect of voxel averaging between bone and soft tissue in attenuation images and determined how accurately bone must be detected in MR images in order to perform acceptable attenuation correction of PET data by using CT-simulated attenuation correction. We found out that treating bone as soft tissue caused a mean quantification difference of -9.9% ± 5.5% in all 119 bone lesions. There were no significant differences between lesions in the pelvis and the vertebrae. The nominal difference in lesions in the ribs was significantly lower, likely due to the spatial misregistration between the emission and attenuation images. Interestingly, a non-monotonic relationship between the bone imaging ability and the absolute PET quantification accuracy was observed, with the minimal quantification difference achieved at a BVF around 40% for skull lesions (2.6% ± 2.1%), and 30% for non-skull lesions (1.4% ± 1.1%) and all lesions (1.5% ± 1.3%). This study established that a bone classification sensitivity of approximately 30% BVF is required in order for MR-based attenuation correction methods to achieve optimal quantification in whole-body PET/MR studies. For this purpose, higher bone imaging ability of MR may not be necessary.
基金Institutional review board of The University of Texas MD Anderson Cancer Center,No.DR09-0025.
文摘BACKGROUND Impressive survival outcome of our previous study in unresectable hepatocellular carcinoma(HCC)patients undergoing yttrium-90 glass microspheres transarterial radioembolization(TARE)with/without sorafenib according to individuals’disease burden,i.e.,intrahepatic tumor load(IHT)and adverse disease features(ADFs)might partly be confounded by other treatments and underlying hepatic function.Therefore,a dedicated study focusing on treatment response and assessment of failure patterns might be a way to improve treatment outcome in addition to patient selection based on the disease burden.AIM To assess the tumor response,disease control and patterns of disease progression following TARE with/without sorafenib in unresectable HCC patients.METHODS This retrospective study was conducted in successful TARE procedures with available pre-and post-treatment imaging studies(n=169).Three treatment subgroups were(1)TARE only(TARE_alone)for IHT≤50%without ADFs,i.e.,macrovascular invasion,extrahepatic disease(EHD)and infiltrative/ill-defined HCC(n=63);(2)TARE with sorafenib(TARE_sorafenib)for IHT>50%and/or presence of ADFs(n=81);and(3)TARE only for patients who could not receive sorafenib due to contraindication or intolerance(TARE_no_sorafenib)(n=25).Objective response rate(ORR;consisted of complete response(CR)and partial response(PR)),disease control rate(DCR;consisted of CR,PR and stable disease)and failure patterns of treated,intrahepatic and extrahepatic sites were assessed using the modified response evaluation criteria in solid tumors.Time to progression(TTP)was calculated from TARE to the first radiologic progression at any site using Kaplan-Meier method.Identification of prognostic factors for TTP using the univariate Kaplan-Meier method and multivariate Cox proportional hazard model were performed in major population subgroups,TARE_alone and TARE_sorafenib.RESULTS The median radiologic follow-up time was 4.4 mo(range 0.5-48.8).In treated area,ORR was highest in TARE_sorafenib(53.1%),followed by TARE_alone(41.3%)and TARE_no_sorafenib(16%).In intrahepatic area,DCR remained highest in TARE_sorafenib(84%),followed by TARE_alone(79.4%)and TARE_no_sorafenib(44%).The overall DCR was highest in TARE_alone(79.4%),followed by TARE_sorafenib(71.6%)and TARE_no_sorafenib(40%).Dominant failure patterns were intrahepatic for both TARE_alone(44.5%)and TARE_sorafenib(38.4%).Extrahepatic progression was more common in TARE_sorafenib(32%)and TARE_no_sorafenib(40%)than in TARE_alone(12.7%).TTP was longest in TARE_alone(8.6 mo;95%CI:3.4-13.8),followed by TARE_sorafenib(5.1 mo;95%CI:4.0-6.2)and TARE_no_sorafenib(2.7 mo;95%CI:2.2-3.1).Pre-existing EHD(HR:0.37,95%CI:0.24-0.56,P<0.001)was a sole prognostic factor for TTP in TARE_sorafenib with no prognostic factor for TTP in TARE_alone.CONCLUSION TARE with/without sorafenib according to individuals’disease burden provided DCR approximately 70%with intrahepatic progression as dominant failure pattern.Extrahepatic progression was more common in procedures with initially high disease burden.
基金supported by Universiti Teknologi PETRONAS,under the Yayasan Universiti Teknologi PETRONAS (YUTP)Fundamental Research Grant Scheme (YUTPFRG/015LC0-274)support by Researchers Supporting Project Number (RSP-2023/309),King Saud University,Riyadh,Saudi Arabia.
文摘The process of selecting features or reducing dimensionality can be viewed as a multi-objective minimization problem in which both the number of features and error rate must be minimized.While it is a multi-objective problem,current methods tend to treat feature selection as a single-objective optimization task.This paper presents enhanced multi-objective grey wolf optimizer with Lévy flight and mutation phase(LMuMOGWO)for tackling feature selection problems.The proposed approach integrates two effective operators into the existing Multi-objective Grey Wolf optimizer(MOGWO):a Lévy flight and a mutation operator.The Lévy flight,a type of random walk with jump size determined by the Lévy distribution,enhances the global search capability of MOGWO,with the objective of maximizing classification accuracy while minimizing the number of selected features.The mutation operator is integrated to add more informative features that can assist in enhancing classification accuracy.As feature selection is a binary problem,the continuous search space is converted into a binary space using the sigmoid function.To evaluate the classification performance of the selected feature subset,the proposed approach employs a wrapper-based Artificial Neural Network(ANN).The effectiveness of the LMuMOGWO is validated on 12 conventional UCI benchmark datasets and compared with two existing variants of MOGWO,BMOGWO-S(based sigmoid),BMOGWO-V(based tanh)as well as Non-dominated Sorting Genetic Algorithm II(NSGA-II)and Multi-objective Particle Swarm Optimization(BMOPSO).The results demonstrate that the proposed LMuMOGWO approach is capable of successfully evolving and improving a set of randomly generated solutions for a given optimization problem.Moreover,the proposed approach outperforms existing approaches in most cases in terms of classification error rate,feature reduction,and computational cost.
文摘We have developed a new form of intravascular optical coherence tomography(IV-OCT) that allows the extremely fast acquisition of high-resolution images of the coronary arteries.This process leads to much better image quality by eliminating cardiac motion artefacts and undersampling.It relies on a catheter that incorporates a synchronous micromotor with a diameter of 1.0 mm and a rotational speed of up to5600 revolutions per second,enabling an IV-OCT frame rate of 5.6 kHz.This speed is matched by a wavelength-swept laser that generates up to 2.8 million image lines per second.With this setup,our team achieved IV-OCT imaging of up to5600 frames per second(fps) in vitro and 4000 fps in vivo,deployed at a 100 mm·s^(-1) pullback velocity.The imaging session is triggered by the electrocardiogram of the subject,and can scan a coronary artery in the phase of the heartbeat where the heart is at rest,providing a name for this new technology:the "Heartbeat OCT."
文摘Radiochromic film with a dye incorporated into the radiation sensitive layer [Gafchromic EBT2, Ashland, Inc.] may be digitized by a color transparency scanner, digitally processed, and calibrated so that a digital image in units of radiation absorbed dose is obtained. A transformation from raw scanner values to dose values was developed based upon a principal component analysis of the optical densities of the red, green and blue channels of the color image of a dose of 0.942 Gy delivered by a Sr-90/Y-90 disk-shaped source. In the order of increasing eigenvalue, the three eigenimages of the principal component analysis contained, by visual inspection, 1) mainly noise;2) mainly a pattern of irregular streaks;and 3) most of the expected dose information along with some of the same background streaking that predominated in the second eigenimage. The combination of the second and third eigenimages that minimized the background streaking was converted into a transformation of the red, green and blue channels’ optical densities and applied to films with a range of doses from 0 to 63.7 Gy. The curve of dose vs. processed optical density was fit by a two-phase association curve. This processing was applied to a film exposed from its edge by a different Y-90 source in a configuration that was modeled by Monte Carlo simulation. The depth-dose curves of the measurement and simulation agree closely, suggesting that this approach is a valid method of processing EBT2 radiochromic film into maps of radiation absorbed dose.
基金This research/paper was fully supported by Universiti Teknologi PETRONAS,under the Yayasan Universiti Teknologi PETRONAS(YUTP)Fundamental Research Grant Scheme(015LC0-311).
文摘Diabetes mellitus is a long-term condition characterized by hyperglycemia.It could lead to plenty of difficulties.According to rising morbidity in recent years,the world’s diabetic patients will exceed 642 million by 2040,implying that one out of every ten persons will be diabetic.There is no doubt that this startling figure requires immediate attention from industry and academia to promote innovation and growth in diabetes risk prediction to save individuals’lives.Due to its rapid development,deep learning(DL)was used to predict numerous diseases.However,DLmethods still suffer from their limited prediction performance due to the hyperparameters selection and parameters optimization.Therefore,the selection of hyper-parameters is critical in improving classification performance.This study presents Convolutional Neural Network(CNN)that has achieved remarkable results in many medical domains where the Bayesian optimization algorithm(BOA)has been employed for hyperparameters selection and parameters optimization.Two issues have been investigated and solved during the experiment to enhance the results.The first is the dataset class imbalance,which is solved using Synthetic Minority Oversampling Technique(SMOTE)technique.The second issue is the model’s poor performance,which has been solved using the Bayesian optimization algorithm.The findings indicate that the Bayesian based-CNN model superbases all the state-of-the-art models in the literature with an accuracy of 89.36%,F1-score of 0.88.6,andMatthews Correlation Coefficient(MCC)of 0.88.6.
基金This research was supported by Universiti Teknologi PETRONAS,under the Yayasan Universiti Teknologi PETRONAS(YUTP)Fundamental Research Grant Scheme(YUTPFRG/015LC0-308).
文摘Generative Adversarial Networks(GANs)are neural networks that allow models to learn deep representations without requiring a large amount of training data.Semi-Supervised GAN Classifiers are a recent innovation in GANs,where GANs are used to classify generated images into real and fake and multiple classes,similar to a general multi-class classifier.However,GANs have a sophisticated design that can be challenging to train.This is because obtaining the proper set of parameters for all models-generator,discriminator,and classifier is complex.As a result,training a single GAN model for different datasets may not produce satisfactory results.Therefore,this study proposes an SGAN model(Semi-Supervised GAN Classifier).First,a baseline model was constructed.The model was then enhanced by leveraging the Sine-Cosine Algorithm and Synthetic Minority Oversampling Technique(SMOTE).SMOTE was used to address class imbalances in the dataset,while Sine Cosine Algorithm(SCA)was used to optimize the weights of the classifier models.The optimal set of hyperparameters(learning rate and batch size)were obtained using grid manual search.Four well-known benchmark datasets and a set of evaluation measures were used to validate the proposed model.The proposed method was then compared against existing models,and the results on each dataset were recorded and demonstrated the effectiveness of the proposed model.The proposed model successfully showed improved test accuracy scores of 1%,2%,15%,and 5%on benchmarking multimedia datasets;Modified National Institute of Standards and Technology(MNIST)digits,Fashion MNIST,Pneumonia Chest X-ray,and Facial Emotion Detection Dataset,respectively.
基金supported by the Cancer Prevention Research Institute of Texas(CPRIT)(RR180061)the National Cancer Institute of the National Institute of Health(1R01CA269764).
文摘In the tumor microenvironment(TME),various types of immune cells interact with each other and with cancer cells,playing critical roles in cancer progression and treatment[1].Numerous studies have reported that the infiltration levels of specific immune cells are associated with patient prognosis and response to immunotherapies[2,3].
文摘As a two-dimensional planar material with low depth profile,a metasurface can generate non-classical phase distributions for the transmitted and reflected electromagnetic waves at its interface.Thus,it offers more flexibility to control the wave front.A traditional metasurface design process mainly adopts the forward prediction algorithm,such as Finite Difference Time Domain,combined with manual parameter optimization.However,such methods are time-consuming,and it is difficult to keep the practical meta-atom spectrum being consistent with the ideal one.In addition,since the periodic boundary condition is used in the meta-atom design process,while the aperiodic condition is used in the array simulation,the coupling between neighboring meta-atoms leads to inevitable inaccuracy.In this review,representative intelligent methods for metasurface design are introduced and discussed,including machine learning,physics-information neural network,and topology optimization method.We elaborate on the principle of each approach,analyze their advantages and limitations,and discuss their potential applications.We also summarize recent advances in enabled metasurfaces for quantum optics applications.In short,this paper highlights a promising direction for intelligent metasurface designs and applications for future quantum optics research and serves as an up-to-date reference for researchers in the metasurface and metamaterial fields.
基金ASCO,Cancer Prevention&Research Institute of Texas(CPRIT),University Cancer Foundation,CPRIT Research Training Program,Grant/Award Number:RP170067TJ Martell Foundation,NIH/NCI,Grant/Award Number:R01-CA207295+6 种基金University of Texas MD Anderson Cancer Center,the Happy Lungs ProjectCancer Prevention&Research Institute of TexasRexanna's Foundation for Fighting Lung CancerConquer Cancer FoundationNIH/NCI,Grant/Award Number:U01-CA213273Department of Defense,Grant/Award Number:LC170171Damon Runyon Mark Foundation Physician Scientist Award,Rexanna Foundation,Grant/Award Number:R01 CA276178-01A1。
文摘Background:Pulmonary sarcomatoid carcinoma(PSC)is a rare and aggressive subtype of non-small cell lung cancer(NSCLC),characterized by the presence of epithelial and sarcoma-like components.The molecular and immune landscape of PSC has not been well defined.Methods:Multiomics profiling of 21 pairs of PSCs with matched normal lung tissues was performed through targeted high-depth DNA panel,whole-exome,and RNA sequencing.We describe molecular and immune features that define subgroups of PSC with disparate genomic and immunogenic features as well as distinct clinical outcomes.Results:In total,27 canonical cancer gene mutations were identified,with TP53 the most frequently mutated gene,followed by KRAS.Interestingly,most TP53 and KRAS mutations were earlier genomic events mapped to the trunks of the tumors,suggesting branching evolution in most PSC tumors.We identified two distinct molecular subtypes of PSC,driven primarily by immune infiltration and signaling.The Immune High(IM-H)subtype was associated with superior survival,highlighting the impact of immune infiltration on the biological and clinical features of localized PSCs.Conclusions:We provided detailed insight into the mutational landscape of PSC and identified two molecular subtypes associated with prognosis.IM-H tumors were associated with favorable recurrence-free survival and overall survival,highlighting the importance of tumor immune infiltration in the biological and clinical features of PSCs.
基金supported by the POSITION-II project funded by the ECSEL JU under grant number Ecsel-783132Position-II-2017-IA.Microfabrication was carried out in the Else Kooi Laboratory(EKL).
文摘Multimodal platforms combining electrical neural recording and stimulation,optogenetics,optical imaging,and magnetic resonance(MRI)imaging are emerging as a promising platform to enhance the depth of characterization in neuroscientific research.Electrically conductive,optically transparent,and MRI-compatible electrodes can optimally combine all modalities.Graphene as a suitable electrode candidate material can be grown via chemical vapor deposition(CVD)processes and sandwiched between transparent biocompatible polymers.However,due to the high graphene growth temperature(≥900℃)and the presence of polymers,fabrication is commonly based on a manual transfer process of pre-grown graphene sheets,which causes reliability issues.In this paper,we present CVD-based multilayer graphene electrodes fabricated using a wafer-scale transfer-free process for use in optically transparent and MRI-compatible neural interfaces.Our fabricated electrodes feature very low impedances which are comparable to those of noble metal electrodes of the same size and geometry.They also exhibit the highest charge storage capacity(CSC)reported to date among all previously fabricated CVD graphene electrodes.Our graphene electrodes did not reveal any photo-induced artifact during 10-Hz light pulse illumination.Additionally,we show here,for the first time,that CVD graphene electrodes do not cause any image artifact in a 3T MRI scanner.These results demonstrate that multilayer graphene electrodes are excellent candidates for the next generation of neural interfaces and can substitute the standard conventional metal electrodes.Our fabricated graphene electrodes enable multimodal neural recording,electrical and optogenetic stimulation,while allowing for optical imaging,as well as,artifact-free MRI studies.
基金Fidelity Foundation,Grant/Award Number:2020YFA0803300Shenzhen Municipal GovernmentNationalNatural Science Foundation of China,Grant/Award Numbers:81702749,81630072,81773098,81803568,8160242.
文摘Background:Type Ⅱ diabetes mellitus(DM2)is a significant risk factor for cancers,including breast cancer.However,a proper diabetic breast cancer mouse model is notwell-established for treatment strategy design.Additionally,the precise diabetic signaling pathways that regulate cancer growth remain unresolved.In the present study,we established a suitable mouse model and demonstrated the pathogenic role of diabetes on breast cancer progression.Methods:We successfully generated a transgenic mouse model of human epidermal growth factor receptor 2 positive(Her2^(+) or ERBB2)breast cancer with DM2 by crossing leptin receptor mutant(Lepr^(db/+))mice with (MMTV-ErbB2/neu)mice.Themousemodelswere administrated with antidiabetic drugs to assess the impacts of controlling DM2 in affecting tumor growth.Magnetic resonance spectroscopic imaging was employed to analyze the tumor metabolism.Results:Treatment with metformin/rosiglitazone in MMTV-ErbB2/Lepr^(db/db) mousemodel reduced serum insulin levels,prolonged overall survival,decreased cumulative tumor incidence,and inhibited tumor progression.Anti-insulin resistance medications also inhibited glycolytic metabolism in tumors in vivo as indicated by the reduced metabolic flux of hyperpolarized ^(13)C pyruvate-to-lactate reaction.The tumor cells from MMTV-ErbB2/Lepr^(db/db) transgenic mice treated with metformin had reprogrammed metabolism by reducing levels of both oxygen consumption and lactate production.Metformin decreased the expression of Myc and pyruvate kinase isozyme 2(PKM2),leading to metabolism reprogramming.Moreover,metformin attenuated the mTOR/AKT signaling pathway and altered adipokine profiles.Conclusions:MMTV-ErbB2/Lepr^(db/db) mouse model was able to recapitulate diabetic HER2^(+) human breast cancer.Additionally,our results defined the signaling pathways deregulated in HER2^(+) breast cancer under diabetic condition,which can be intervened by anti-insulin resistance therapy.
文摘In the semiconductor industry,the demand for more precise and accurate overlay metrology tools has increased because of the continued shrinking of feature sizes in integrated circuits.To achieve the required sub-nanometre precision,the current technology for overlay metrology has become complex and is reaching its limits.Herein,we present a dark-field digital holographic microscope using a simple two-element imaging lens with a high numerical aperture capable of imaging from the visible to near-infrared regions.This combination of high resolution and wavelength coverage was achieved by combining a simple imaging lens with a fast and accurate correction of non-isoplanatic aberrations.We present experimental results for overlay targets that demonstrate the capability of our computational aberration correction in the visible and near-infrared wavelength regimes.This wide-ranged-wavelength imaging system can advance semiconductor metrology.
基金This study is supported by National Eye Institute at the National Institutes of Health(Grant R01EY016462).
文摘Background:In this paper we determined the benefits of image registration on estimating longitudinal retinal nerve fiber layer thickness(RNFLT)changes.Methods:RNFLT maps around the optic nerve head(ONH)of healthy primate eyes were measured using Optical Coherence Tomography(OCT)weekly for 30 weeks.One automatic algorithm based on mutual information(MI)and the other semi-automatic algorithm based on log-polar transform cross-correlation using manually segmented blood vessels(LPCC_MSBV),were used to register retinal maps longitudinally.We compared the precision and recall between manually segmented image pairs for the two algorithms using a linear mixed effects model.Results:We found that the precision calculated between manually segmented image pairs following registration by LPCC_MSBV algorithm is significantly better than the one following registration by MI algorithm(p<<0.0001).Trend of the all-rings and temporal,superior,nasal and inferior(TSNI)quadrants average of RNFLT over time in healthy primate eyes are not affected by registration.RNFLT of clock hours 1,2,and 10 showed significant change over 30 weeks(p=0.0058,0.0054,and 0.0298 for clock hours 1,2 and 10 respectively)without registration,but stayed constant over time with registration.Conclusions:The LPCC_MSBV provides better registration of RNFLT maps recorded on different dates than the automatic MI algorithm.Registration of RNFLT maps can improve clinical analysis of glaucoma progression.
