Correlation of dynamic contrast-enhanced ultrasonography and the Ki-67 labelling index in pancreatic ductal adenocarcinoma

BACKGROUND Pancreatic ductal adenocarcinoma(PDAC)is a highly malignant and aggressive tumor,and high Ki-67 expression indicates poor histological differentiation and prognosis.Therefore,one of the challenges in diagnosing preoperatively patients with PDAC is predicting the degree of malignancy.Dynamic contrast-enhanced ultrasonography(DCE-US)plays a crucial role in abdominal tumor diagnosis,and can adequately show the microvascular composition within the tumors.However,the relationship between DCE-US and the Ki-67 labelling index remains unclear at the present time.AIM To predict the correlation between Ki-67 expression and the parameters of DCEUS.METHODS Patients with PDAC who underwent DCE-US were retrospectively analyzed.Patients who had received any treatment(radiotherapy or chemotherapy)prior to DCE-US;had incomplete clinical,imaging,or pathologic information;and had poor-quality image analysis were excluded.Correlations between Ki-67 expression and the parameters of DCE-US in patients with PDAC were assessed using Spearman’s rank correlation analysis.The diagnostic performances of these parameters in high Ki-67 expression group were evaluated according to receiver operating characteristic curve.RESULTS Based on the Ki-67 labelling index,30 patients were divided into two groups,i.e.,the high expression group and the low expression group.Among the relative quantitative parameters between the two groups,relative half-decrease time(rHDT),relative peak enhancement,relative wash-in perfusion index and relative wash-in rate were significantly different between two groups(P=0.018,P=0.025,P=0.028,P=0.035,respectively).The DCE-US parameter rHDT was moderately correlated with Ki-67 expression,and rHDT≥1.07 was more helpful in accurately diagnosing high Ki-67 expression,exhibiting a sensitivity and specificity of 53.8%and 94.1%,respectively.CONCLUSION One parameter of DCE-US,rHDT,correlates with high Ki-67 expression.It demonstrates that parameters obtained noninvasively by DCE-US could better predict Ki-67 expression in PDAC preoperatively.

Apples to oranges:environmentally derived,dynamic regulation of serotonin neuron subpopulations in adulthood?

Traumatic brain injury(TBI)is a public health problem with an undue economic burden that impacts nearly every age,ethnic,and gender group across the globe(Capizzi et al.,2020).TBIs are often sustained during a dynamic range of exposures to energetic environmental forces and as such outcomes are typically heterogeneous regarding severity and pathology(Capizzi et al.,2020).

Nanograting‑Based Dynamic Structural Colors Using Heterogeneous Materials

Dynamic structuralcolors can change in response todifferent environmental stimuli.This ability remains effectiveeven when the size of the speciesresponsible for the structural coloris reduced to a few micrometers,providing a promising sensingmechanism for solving microenvironmentalsensing problems inmicro-robotics and microfluidics.However, the lack of dynamicstructural colors that can encoderapidly, easily integrate, and accuratelyreflect changes in physical quantities hinders their use in microscale sensing applications. Herein, we present a 2.5-dimensionaldynamic structural color based on nanogratings of heterogeneous materials, which were obtained by interweaving a pH-responsive hydrogelwith an IP-L photoresist. Transverse gratings printed with pH-responsive hydrogels elongated the period of longitudinal grating in the swollenstate, resulting in pH-tuned structural colors at a 45° incidence. Moreover, the patterned encoding and array printing of dynamic structuralcolors were achieved using grayscale stripe images to accurately encode the periods and heights of the nanogrid structures. Overall, dynamicstructural color networks exhibit promising potential for applications in information encryption and in situ sensing for microfluidic chips.

A Rapid Adaptation Approach for Dynamic Air‑Writing Recognition Using Wearable Wristbands with Self‑Supervised Contrastive Learning

Wearable wristband systems leverage deep learning to revolutionize hand gesture recognition in daily activities.Unlike existing approaches that often focus on static gestures and require extensive labeled data,the proposed wearable wristband with selfsupervised contrastive learning excels at dynamic motion tracking and adapts rapidly across multiple scenarios.It features a four-channel sensing array composed of an ionic hydrogel with hierarchical microcone structures and ultrathin flexible electrodes,resulting in high-sensitivity capacitance output.Through wireless transmission from a Wi-Fi module,the proposed algorithm learns latent features from the unlabeled signals of random wrist movements.Remarkably,only few-shot labeled data are sufficient for fine-tuning the model,enabling rapid adaptation to various tasks.The system achieves a high accuracy of 94.9%in different scenarios,including the prediction of eight-direction commands,and air-writing of all numbers and letters.The proposed method facilitates smooth transitions between multiple tasks without the need for modifying the structure or undergoing extensive task-specific training.Its utility has been further extended to enhance human–machine interaction over digital platforms,such as game controls,calculators,and three-language login systems,offering users a natural and intuitive way of communication.

Efficient and Stable Perovskite Solar Cells and Modules Enabled by Tailoring Additive Distribution According to the Film Growth Dynamics

Gas quenching and vacuum quenching process are widely applied to accelerate solvent volatilization to induce nucleation of perovskites in blade-coating method.In this work,we found these two pre-crystallization processes lead to different order of crystallization dynamics within the perovskite thin film,resulting in the differences of additive distribution.We then tailor-designed an additive molecule named 1,3-bis(4-methoxyphenyl)thiourea to obtain films with fewer defects and holes at the buried interface,and prepared perovskite solar cells with a certified efficiency of 23.75%.Furthermore,this work also demonstrates an efficiency of 20.18%for the large-area perovskite solar module(PSM)with an aperture area of 60.84 cm^(2).The PSM possesses remarkable continuous operation stability for maximum power point tracking of T_(90)>1000 h in ambient air.

Dynamic Multi-Graph Spatio-Temporal Graph Traffic Flow Prediction in Bangkok:An Application of a Continuous Convolutional Neural Network

The ability to accurately predict urban traffic flows is crucial for optimising city operations.Consequently,various methods for forecasting urban traffic have been developed,focusing on analysing historical data to understand complex mobility patterns.Deep learning techniques,such as graph neural networks(GNNs),are popular for their ability to capture spatio-temporal dependencies.However,these models often become overly complex due to the large number of hyper-parameters involved.In this study,we introduce Dynamic Multi-Graph Spatial-Temporal Graph Neural Ordinary Differential Equation Networks(DMST-GNODE),a framework based on ordinary differential equations(ODEs)that autonomously discovers effective spatial-temporal graph neural network(STGNN)architectures for traffic prediction tasks.The comparative analysis of DMST-GNODE and baseline models indicates that DMST-GNODE model demonstrates superior performance across multiple datasets,consistently achieving the lowest Root Mean Square Error(RMSE)and Mean Absolute Error(MAE)values,alongside the highest accuracy.On the BKK(Bangkok)dataset,it outperformed other models with an RMSE of 3.3165 and an accuracy of 0.9367 for a 20-min interval,maintaining this trend across 40 and 60 min.Similarly,on the PeMS08 dataset,DMST-GNODE achieved the best performance with an RMSE of 19.4863 and an accuracy of 0.9377 at 20 min,demonstrating its effectiveness over longer periods.The Los_Loop dataset results further emphasise this model’s advantage,with an RMSE of 3.3422 and an accuracy of 0.7643 at 20 min,consistently maintaining superiority across all time intervals.These numerical highlights indicate that DMST-GNODE not only outperforms baseline models but also achieves higher accuracy and lower errors across different time intervals and datasets.

Stability Prediction in Smart Grid Using PSO Optimized XGBoost Algorithm with Dynamic Inertia Weight Updation

Prediction of stability in SG(Smart Grid)is essential in maintaining consistency and reliability of power supply in grid infrastructure.Analyzing the fluctuations in power generation and consumption patterns of smart cities assists in effectively managing continuous power supply in the grid.It also possesses a better impact on averting overloading and permitting effective energy storage.Even though many traditional techniques have predicted the consumption rate for preserving stability,enhancement is required in prediction measures with minimized loss.To overcome the complications in existing studies,this paper intends to predict stability from the smart grid stability prediction dataset using machine learning algorithms.To accomplish this,pre-processing is performed initially to handle missing values since it develops biased models when missing values are mishandled and performs feature scaling to normalize independent data features.Then,the pre-processed data are taken for training and testing.Following that,the regression process is performed using Modified PSO(Particle Swarm Optimization)optimized XGBoost Technique with dynamic inertia weight update,which analyses variables like gamma(G),reaction time(tau1–tau4),and power balance(p1–p4)for providing effective future stability in SG.Since PSO attains optimal solution by adjusting position through dynamic inertial weights,it is integrated with XGBoost due to its scalability and faster computational speed characteristics.The hyperparameters of XGBoost are fine-tuned in the training process for achieving promising outcomes on prediction.Regression results are measured through evaluation metrics such as MSE(Mean Square Error)of 0.011312781,MAE(Mean Absolute Error)of 0.008596322,and RMSE(Root Mean Square Error)of 0.010636156 and MAPE(Mean Absolute Percentage Error)value of 0.0052 which determine the efficacy of the system.

Efficient and Stable Photoassisted Lithium‑Ion Battery Enabled by Photocathode with Synergistically Boosted Carriers Dynamics

Efficient and stable photocathodes with versatility are of significance in photoassisted lithium-ion batteries(PLIBs),while there is always a request on fast carrier transport in electrochemical active photocathodes.Present work proposes a general approach of creating bulk heterojunction to boost the carrier mobility of photocathodes by simply laser assisted embedding of plasmonic nanocrystals.When employed in PLIBs,it was found effective for synchronously enhanced photocharge separation and transport in light charging process.Additionally,experimental photon spectroscopy,finite difference time domain method simulation and theoretical analyses demonstrate that the improved carrier dynamics are driven by the plasmonic-induced hot electron injection from metal to TiO_(2),as well as the enhanced conductivity in TiO2 matrix due to the formation of oxygen vacancies after Schottky contact.Benefiting from these merits,several benchmark values in performance of TiO2-based photocathode applied in PLIBs are set,including the capacity of 276 mAh g^(−1)at 0.2 A g^(−1)under illumination,photoconversion efficiency of 1.276%at 3 A g^(−1),less capacity and Columbic efficiency loss even through 200 cycles.These results exemplify the potential of the bulk heterojunction strategy in developing highly efficient and stable photoassisted energy storage systems.

Emerging structures and dynamic mechanisms ofγ-secretase for Alzheimer’s disease

γ-Secretase,called“the proteasome of the membrane,”is a membrane-embedded protease complex that cleaves 150+peptide substrates with central roles in biology and medicine,including amyloid precursor protein and the Notch family of cell-surface receptors.Mutations inγ-secretase and amyloid precursor protein lead to early-onset familial Alzheimer’s disease.γ-Secretase has thus served as a critical drug target for treating familial Alzheimer’s disease and the more common late-onset Alzheimer’s disease as well.However,critical gaps remain in understanding the mechanisms of processive proteolysis of substrates,the effects of familial Alzheimer’s disease mutations,and allosteric modulation of substrate cleavage byγ-secretase.In this review,we focus on recent studies of structural dynamic mechanisms ofγ-secretase.Different mechanisms,including the“Fit-Stay-Trim,”“Sliding-Unwinding,”and“Tilting-Unwinding,”have been proposed for substrate proteolysis of amyloid precursor protein byγ-secretase based on all-atom molecular dynamics simulations.While an incorrect registry of the Notch1 substrate was identified in the cryo-electron microscopy structure of Notch1-boundγ-secretase,molecular dynamics simulations on a resolved model of Notch1-boundγ-secretase that was reconstructed using the amyloid precursor protein-boundγ-secretase as a template successfully capturedγ-secretase activation for proper cleavages of both wildtype and mutant Notch,being consistent with biochemical experimental findings.The approach could be potentially applied to decipher the processing mechanisms of various substrates byγ-secretase.In addition,controversy over the effects of familial Alzheimer’s disease mutations,particularly the issue of whether they stabilize or destabilizeγ-secretase-substrate complexes,is discussed.Finally,an outlook is provided for future studies ofγ-secretase,including pathways of substrate binding and product release,effects of modulators on familial Alzheimer’s disease mutations of theγ-secretase-substrate complexes.Comprehensive understanding of the functional mechanisms ofγ-secretase will greatly facilitate the rational design of effective drug molecules for treating familial Alzheimer’s disease and perhaps Alzheimer’s disease in general.

Dynamic Interaction Analysis of Coupled Axial-Torsional-Lateral Mechanical Vibrations in Rotary Drilling Systems

Maintaining the integrity and longevity of structures is essential in many industries,such as aerospace,nuclear,and petroleum.To achieve the cost-effectiveness of large-scale systems in petroleum drilling,a strong emphasis on structural durability and monitoring is required.This study focuses on the mechanical vibrations that occur in rotary drilling systems,which have a substantial impact on the structural integrity of drilling equipment.The study specifically investigates axial,torsional,and lateral vibrations,which might lead to negative consequences such as bit-bounce,chaotic whirling,and high-frequency stick-slip.These events not only hinder the efficiency of drilling but also lead to exhaustion and harm to the system’s components since they are difficult to be detected and controlled in real time.The study investigates the dynamic interactions of these vibrations,specifically in their high-frequency modes,usingfield data obtained from measurement while drilling.Thefindings have demonstrated the effect of strong coupling between the high-frequency modes of these vibrations on drilling sys-tem performance.The obtained results highlight the importance of considering the interconnected impacts of these vibrations when designing and implementing robust control systems.Therefore,integrating these compo-nents can increase the durability of drill bits and drill strings,as well as improve the ability to monitor and detect damage.Moreover,by exploiting thesefindings,the assessment of structural resilience in rotary drilling systems can be enhanced.Furthermore,the study demonstrates the capacity of structural health monitoring to improve the quality,dependability,and efficiency of rotary drilling systems in the petroleum industry.

Review of dynamic contrast-enhanced ultrasound guidance in ablation therapy for hepatocellular carcinoma

Local ablative techniques-percutaneous ethanol injection, microwave coagulation therapy and radiofrequency ablation (RFA)-have been developed to treat unresectable hepatocellular carcinoma (HCC). The success rate of percutaneous ablation therapy for HCC depends on correct targeting of the tumor via an imaging technique. However, probe insertion often is not completely accurate for small HCC nodules, which are poorly def ined on conventional B-mode ultrasound (US) alone. Thus, multiple sessions of ablation therapy are frequently required in diffi cult cases. By means of two breakthroughs in US technology, harmonic imaging and the development of second-generation contrast agents, dynamic contrast-enhanced harmonic US imaging with an intravenous contrast agent can depict tumor vascularity sensitively and accurately, and is able to evaluate small hypervascular HCCs even when B-mode US cannot adequately characterize the tumors. Therefore, dynamic contrast-enhanced US can facilitate RFA electrode placement in hypervascular HCC, which is poorly depicted by B-mode US. The use of dynamic contrast-enhanced US guidance in ablation therapy for liver cancer is an effi cient approach. Here, we present an overview of the current status of dynamic contrast-enhanced US-guided ablation therapy, and summarize the current indications and outcomes of reported clinical use in comparison with that of other modalities.

Discrimination of Metastatic from Non-metastatic Mesorectal Lymph Nodes in Rectal Cancer Using Quantitative Dynamic Contrast-Enhanced Magnetic Resonance Imaging

Preoperative detection of lymph nodes（LNs） metastasis is always highly challenging for radiologists nowadays. The utility of quantitative dynamic contrast-enhanced magnetic resonance imaging（QDCE-MRI） in identifying LNs metastasis is not well understood. In the present study, 59 patients with histologically proven rectal carcinoma underwent preoperative QDCE-MRI. The short axis diameter ratio, long axis diameter ratio, short-to-long axis diameter ratio and QDEC-MRI parameters（Ktrans, Kep, fPV and Ve） values were compared between the non-metastatic（n=44） and metastatic（n=35） LNs groups based on pathological examination. Compared with the non-metastatic group, the metastatic group exhibited significantly higher short axis diameter（7.558±0.668 mm vs. 5.427±0.285 mm）, Ktrans（0.483±0.198 min-1 vs. 0.218±0.116 min^-1） and Ve（0.399±0.118 vs. 0.203±0.096） values（all P〈0.05）. The short-to-long axis diameter ratio, long axis diameter ratio, Kep and fPV values did not show significant differences between the two groups. In conclusion, our results showed that for LNs larger than 5 mm in rectal cancer, there are distinctive differences in the Ktrans and Ve values between the metastatic and non-metastatic LNs, suggesting that QDCE-MRI may be potentially helpful in identifying LNs status.

Diagnostic value of DWI combined with dynamic contrast-enhanced scan of cervical cancer staging弥散加权成像结合动态增强扫描在宫颈癌分期中的诊断价值

目的探讨磁共振弥散加权成像（DWI）结合动态增强扫描在子宫颈癌分期中的诊断价值。方法回顾性分析2013年11月-2014年8月广州医科大学附属第四医院56例经病理证实的宫颈癌患者的DWI及动态增强扫描结果。测量病灶表观扩散系数（ADC）值判断浸润范围，并与手术病理结果进行比较。结果宫颈癌在DWI图像上表现为高信号，ADC值降低，平均ADC值为（0．92±0．16）×10^-3mm^2／s。动态增强扫描早期病灶明显快速强化，延迟期病灶中心呈低信号，病灶边缘呈稍高信号，与邻近正常宫颈组织信号明显不同，形成对比。DWI结合动态增强扫描对宫颈癌FIGO分期（2009）总准确性为93．75％，高于常规MRI分期总准确性（81．25％），对宫旁浸润评估的准确性为100．00％。结论，DWI结合动态增强扫描磁共振检查能提高宫颈癌侵犯程度评价的准确性，对宫颈癌的诊断、临床分期及制订正确的治疗方案具有重要意义。

A Comparative Study Between Tumor Blood Vessels and Dynamic Contrast-enhanced MRI for Identifying Isocitrate Dehydrogenase Gene 1(IDH1)Mutation Status in Glioma

Objective Isocitrate dehydrogenase gene(IDH)mutations are associated with tumor angiogenesis and therefore play an important role in glioma management.This study compared the performance of tumor blood vessels counted from contrast-enhanced 3D brain volume(3D-BRAVO)sequence and dynamic contrast-enhanced(DCE)MRI in differentiating IDH1 status in gliomas.Methods Forty-four glioma patients[16 with IDH1 mutant-type(IDH1-MT),28 with IDH1 wild-type(IDH1-WT)]were retrospectively analyzed.A blood vessel entering a tumor was defined as an intratumoral vessel;a blood vessel adjacent to the edge of a tumor was defined as a peritumoral vessel.Combined vessels were defined as the sum of the intratumoral and peritumoral vessels.DCE-derived metrics of tumor were normalized to the contralateral normal-appearing white matter.Results Intratumoral,peritumoral,and combined tumor blood vessels were all significantly different between IDH1-MT and IDH1-WT gliomas,and the range of area under curves(AUCs)was 0.816–0.855.For DCE-derived parameters,cerebral blood volume,cerebral blood flow,mean transit time,and volume transfer constant were significantly different between IDH1-MT and IDH1-WT gliomas,and the range of AUCs was 0.703–0.756.Combined vessels possessed the best performance for identifying IDH1 mutations in gliomas(AUC:0.855,sensitivity:0.857,specificity:0.812,P<0.001).Conclusion The number of tumor blood vessels has comparable diagnostic performance with DCE-derived parameters for differentiating IDH1 mutations and can serve as a potential imaging biomarker to reflect IDH1 mutations in gliomas.

Dynamic contrast-enhanced magnetic resonance imaging of prostate cancer: A review of current methods and applications

In many areas of oncology, dynamic contrast-enhanced magnetic resonance imaging(DCE-MRI) has proven to be a clinically useful, non-invasive functional imaging technique to quantify tumor vasculature and tumor perfusion characteristics. Tumor angiogenesis is an essential process for tumor growth, proliferation, and metastasis. Malignant lesions demonstrate rapid extravasation of contrast from the intravascular space to the capillary bed due to leaky capillaries associated with tumor neovascularity. DCE-MRI has the potential to provide information regarding blood flow, areas of hypoperfusion, and variations in endothelial permeability and microvessel density to aid treatment selection, enable frequent monitoring during treatment and assess response to targeted therapy following treatment. This review will discuss the current status of DCE-MRI in cancer imaging, with a focus on its use in imaging prostate malignancies as well as weaknesses that limit its widespread clinical use. The latest techniques for quantification of DCE-MRI parameters will be reviewed and compared.

Prediction of radiosensitivity in primary central nervous system germ cell tumors using dynamic contrast-enhanced magnetic resonance imaging

Objective： To evaluate the feasibility of dynamic contrast-enhanced magnetic resonance imaging（DCEMRI） for predicting tumor response to radiotherapy in patients with suspected primary central nervous system（CNS） germ cell tumors（GCTs）.Methods： DCE-MRI parameters of 35 patients with suspected primary CNS GCTs were obtained prior to diagnostic radiation, using the Tofts and Kermode model. Radiosensitivity was determined in tumors diagnosed 2 weeks after radiation by observing changes in tumor size and markers as a response to MRI. Taking radiosensitivity as the gold standard, the cut-off value of DCE-MRI parameters was measured by receiver operating characteristic（ROC） curve. Diagnostic accuracy of DCE-MRI parameters for predicting radiosensitivity was evaluated by ROC curve.Results： A significant elevation in transfer constant（K^trans） and extravascular extracellular space（Ve）（P=0.000）, as well as a significant reduction in rate constant（Kep）（P=0.000） was observed in tumors. K^trans, relative K^trans, and relative Kep of the responsive group were significantly higher than non-responsive groups. No significant difference was found in Kep, Ve, and relative Ve between the two groups. Relative K^trans showed the best diagnostic value in predicting radiosensitivity with a sensitivity of 100%, specificity of 91.7%, positive predictive value（PPV） of 95.8%, and negative predictive value（NPV） of 100%.Conclusions： Relative K^trans appeared promising in predicting tumor response to radiation therapy（RT）. It is implied that DCE-MRI pre-treatment is a requisite step in diagnostic procedures and a novel and reliable approach to guide clinical choice of RT.

Usefulness of dynamic contrast-enhanced MR imaging in the evaluation of pulmonary isolated lesions

Objective： The aim of our study was to investigate the value of dynamic contrast-enhanced MRI for evaluating differential diagnosis of pulmonary isolated lesions. Methods： Twenty-nine consecutive patients enrolled in this study, all of whom underwent DCE-MRI examinations and received a histologic and clinical diagnosis. Among these, lung tuberculoma 7 cases, harmatoma 3 cases, peripheral lung cancer 19 cases. DCE-MRI was acquired with 3D LAVA technique, total 18 phases were acquired, scanner time of per phase was 5-7″. After contrasting agent, twice successive scanning was acquired at 10″ and 50″. Then 1′30″, 2′, 2′30″, 3′, 3′30″, 4′, 5′, 6′, 7′, 8′, 9′, 10′, 11′, 12′ performed scanning. Region of interest was placed on the Maximum level in the tumors. According to Schaefer＇s standard, four types of time signal intensity curve （TIC） were classified, which were A, B, C and D. Compared the dynamic parameters between benign and malignant nodules. Results： Lung tuberculoma may display three curves： A type 1 case, ring-shaped enhancement 4 cases （periphery ring A type, central region D type）, D type 2 cases. Harmatoma may display three curves： A type 1 case, C type 2 case. Peripheral lung cancer may display A type. Except 2 cases D type lung tuberculoma, we compared curve data of 8 cases benign nodules （including tuberculoma Atype and periphery ring Atype, harmatoma Atype and C type） and lung cancer. SlEP%： benign nodules 0.7885 ±0.5543, lung cancer 1.2623 ±0.3059, P 〈 0.05; MER： benign nodules 1.0007 ± 0.4251, lung cancer 1.3694 ±0.2740, P 〈 0.05; washout： P 〉 0.05. Conclusion： Lung MR imaging is helpful to diagnosis and differential diagnosis of isolated benign and malignant nodules. SIEP% and MER could offer valuable information. The evolution of global tuberculosis may be from A type to ring-shaped ennoblement to D type. It was easy to do right diagnosis to lung tuberculoma with ring-shaped ennoblement and D type. Peripheral lung cancer commonly displayed A type and needed identification with acute inflammation. So, it is important to anti-inflammatory follow-up for a few A type nodules.

Dynamic contrast-enhanced MRI versus ^(18)F-FDG PET/CT: Which is better in differentiation between malignant and benign solitary pulmonary nodules?

Objective： To prospectively compare the discriminative capacity of dynamic contrast enhanced-magnetic resonance imaging（DCE-MRI） with that of^18F-fluorodeoxyglucose（^18F-FDG） positron emission tomography/computed tomography（PET/CT） in the differentiation of malignant and benign solitary pulmonary nodules（SPNs）.Methods： Forty-nine patients with SPNs were included in this prospective study. Thirty-two of the patients had malignant SPNs, while the other 17 had benign SPNs. All these patients underwent DCE-MRI and ^18F-FDG PET/CT examinations. The quantitative MRI pharmacokinetic parameters, including the trans-endothelial transfer constant（K^trans）, redistribution rate constant（Kep）, and fractional volume（Ve）, were calculated using the Extended-Tofts Linear two-compartment model. The ^18F-FDG PET/CT parameter, maximum standardized uptake value（SUV（max））, was also measured. Spearman＇s correlations were calculated between the MRI pharmacokinetic parameters and the SUV（max） of each SPN. These parameters were statistically compared between the malignant and benign nodules. Receiver operating characteristic（ROC） analyses were used to compare the diagnostic capability between the DCE-MRI and ^18F-FDG PET/CT indexes.Results： Positive correlations were found between K^trans and SUV（max）, and between K（ep） and SUV（max）（P〈0.05）.There were significant differences between the malignant and benign nodules in terms of the K^trans, K（ep） and SUV（max） values（P〈0.05）. The areas under the ROC curve（AUC） of K^trans） K（ep） and SUV（max） between the malignant and benign nodules were 0.909, 0.838 and 0.759, respectively. The sensitivity and specificity in differentiating malignant from benign SPNs were 90.6% and 82.4% for K^trans; 87.5% and 76.5% for K（ep）; and 75.0% and 70.6%for SUV（max）, respectively. The sensitivity and specificity of K^trans and K（ep） were higher than those of SUV（max）, but there was no significant difference between them（P〉0.05）.Conclusions： DCE-MRI can be used to differentiate between benign and malignant SPNs and has the advantage of being radiation free.

Prostatic Cancer: Diagnosis and Differentiation by Dynamic Contrast-Enhanced MRI

To assess the role of dynamic contrast-enhanced MRI (DCE-MRI) in thediagnosis and differentiation of prostatic cancer (PC). Methods: Five volunteers, 36 patients withbenign prostatic hyperplasia (BPH) and 13 patients with biopsy-proven prostate cancer underwentconventional MRI, DCE-MRI and delayed enhancement MRI. The value of the signal intensity in DCE-MRIwas measured and calculated to draw the time-signal intensity curve of the normal peripheral zone(PZ), the prostate cancer and the benign prostatic hyperplasia. Results: In DCE-MRI, the normalperipheral zone was enhanced mildly and slowly and the peak value was located in late phase. Theenhancement of the lesions in 36 patients with the benign prostatic hyperplasia was obvious in earlyphase and strengthened gradually, and then turned to decrease in late phase after peak value. Thelesions in 9 of 13 cases with prostate cancer were enhanced obviously in early phase and washed outrapidly, and the peak value was located in early phase, but the peak value was in mediate and latephase in the other 4 cases with diffuse lesion in the prostate on T_2WI. Conclusion: In DCE-MRI, theenhancement patterns of the normal peripheral zone, the prostate cancer and the benign prostatichyperplasia were significantly different. DCE-MRI was very useful in the diagnosis anddifferentiation of prostate cancer.

Dynamic contrast-enhanced MR imaging findings of bone metastasis in patients with prostate cancer

AIM:To evaluate the dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) findings of bone metastasis in prostate cancer patients.METHODS:Sixteen men with a diagnosis of metastatic prostate cancer to bones were examined with DCE-MRI at 1.5 Tesla.The mean contrast agent concentration vs time curves for bone metastasis and normal bone were calculated and K trans and ve values were estimated and compared.RESULTS:An early significant enhancement (wash-out:n=6,plateau:n=8 and persistent:n=2) was detected in all bone metastases (n=16).Bone metastasis from prostate cancer showed significant enhancementand high K trans and ve values compared to normal bone which does not enhance in the elderly population.The mean K trans was 0.101/mmiinn and 0.0051/mmiinn (P < 0.001),the mean ve was 0.141 and 0.0038 (P < 0.001),for bone metastases and normal bone,respectively.