Recent advances in large models demonstrate significant prospects for transforming the field of medical imaging. These models, including large language models, large visual models, and multimodal large models, offer unprecedented capabilities in processing and interpreting complex medical data across various imaging modalities. By leveraging self-supervised pretraining on vast unlabeled datasets, cross-modal representation learning, and domain-specific medical knowledge adaptation through fine-tuning, large models can achieve higher diagnostic accuracy and more efficient workflows for key clinical tasks. This review summarizes the concepts, methods, and progress of large models in medical imaging, highlighting their potential in precision medicine. The article first outlines the integration of multimodal data under large model technologies, approaches for training large models with medical datasets, and the need for robust evaluation metrics. It then explores how large models can revolutionize applications in critical tasks such as image segmentation, disease diagnosis, personalized treatment strategies, and real-time interactive systems, thus pushing the boundaries of traditional imaging analysis. Despite their potential, the practical implementation of large models in medical imaging faces notable challenges, including the scarcity of high-quality medical data, the need for optimized perception of imaging phenotypes, safety considerations, and seamless integration with existing clinical workflows and equipment. As research progresses, the development of more efficient, interpretable, and generalizable models will be critical to ensuring their reliable deployment across diverse clinical environments. This review aims to provide insights into the current state of the field and provide directions for future research to facilitate the broader adoption of large models in clinical practice.
Humans ; Diagnostic Imaging/methods* ; Precision Medicine/methods* ; Image Processing, Computer-Assisted/methods*

Animal experiments are an essential component of life sciences and medical research. However, the external validity and reliability of individual animal studies are frequently challenged by inherent limitations such as small sample sizes, high design heterogeneity, and poor reproducibility, which impede the effective translation of research findings into clinical practice. Systematic reviews and meta-analysis represent a key methodology for integrating existing evidence and enhancing the robustness of conclusions. Currently, however, the application of systematic reviews and meta-analysis in the field of animal experiments lacks standardized guidelines for their conduct and reporting, resulting in inconsistent quality and, to some extent, diminishing their evidence value. To address this issue, this paper aims to systematically delineate the reporting process for systematic reviews and meta-analysis of animal experiments and to propose a set of standardized recommendations that are both scientific and practical. The article's scope encompasses the entire process, from the preliminary preparatory phase [including formulating the population， intervention， comparison and outcome （PICO） question, assessing feasibility, and protocol pre-registration] to the key writing points for each section of the main report. In the core methods section, the paper elaborates on how to implement literature searches, establish eligibility criteria, perform data extraction, and assess the risk of bias, based on the Preferred Reporting Items for Systematic Reviews and Meta-analysis （PRISMA) statement, in conjunction with relevant guidelines and tools such as Animal Research： Reporting of in Vivo Experiments （ARRIVE) and a risk of bias assessment tool developed by the Systematic Review Centre for Laboratory Animal Experimentation (SYRCLE). For the presentation of results, strategies are proposed for clear and transparent display using flow diagrams and tables of characteristics. The discussion section places particular emphasis on how to scientifically interpret pooled effects, thoroughly analyze sources of heterogeneity, evaluate the impact of publication bias, and cautiously discuss the validity and limitations of extrapolating findings from animal studies to clinical settings. Furthermore, this paper recommends adopting the Grading of Recommendations Assessment, Development and Evaluation (GRADE) methodology to comprehensively grade the quality of evidence. Through a modular analysis of the entire reporting process, this paper aims to provide researchers in the field with a clear and practical guide, thereby promoting the standardized development of systematic reviews and meta-analysis of animal experiments and enhancing their application value in scientific decision-making and translational medicine.

ObjectiveThis study aims to develop a prediction model for the compatibility of Chinese medicinal pairs based on Graph Convolutional Networks （GCN）， named HC-GCN. The model integrates the properties of herbs with modern pharmacological mechanisms to predict pairs with specific therapeutic effects. It serves as a demonstration by applying the model to predict and validate the efficacy of blood-activating herb pairs. MethodsThe training dataset for herb pair prediction was constructed by systematically collecting commonly used herb pairs along with their characteristic data， including Qi， flavor， meridian tropism， and target genes. Integrating traditional characteristics of herb with modern bioinformatics， we developed an efficacy-oriented herb pair compatibility prediction model （HC-GCN） using graph convolutional networks （GCN）. This model leverages machine learning to capture the complex relationships in herb pair compatibility， weighted by efficacy features. The performance of the HC-GCN model was evaluated using accuracy （ACC）， recall， precision， F1 score （F1）， and area under the ROC curve （AUC）. Its predictive effectiveness was then compared to five other machine learning models： eXtreme Gradient Boosting （XGBoost）， logistic regression （LR）， Naive Bayes， K-nearest neighbor （KNN）， and support vector machine （SVM）. ResultsUsing herb pairs with blood-activating effects as a demonstration， a prediction model was constructed based on a foundational dataset of 46 blood-activating herb pairs， incorporating their Qi， flavor， meridian tropism， and target gene characteristics. The HC-GCN model outperforms other commonly used machine learning models in key performance metrics， including ACC， recall， precision， F1 score， and AUC. Through the predictive analysis of the HC-GCN model， 60 herb pairs with blood-activating effects were successfully identified. Among of these potential herb pairs， 44 include at least one herb with blood-activating effects. ConclusionIn this study， we established an efficacy-oriented compatibility prediction model for herb pairs based on GCN by integrating the unique characteristics of traditional herbs with modern pharmacological mechanisms. This model demonstrated high predictive performance， offering a novel approach for the intelligent screening and optimization of traditional Chinese medicine prescriptions， as well as their clinical applications.

ObjectiveBased on ultra performance liquid chromatography-quadrupole-time-of-flight mass spectrometry（UPLC-Q-TOF-MS）， network pharmacology， molecular docking and cell experiments， the active ingredients， possible targets and molecular mechanisms of Baoxin granules（BXG） regulating ferroptosis in the treatment of heart failure（HF） were explored. MethodsBXG intestinal absorption fluid was prepared by everted gut sac and the chemical composition contained therein were identified by UPLC-Q-TOF-MS. According to the obtained components， the potential targets of BXG were predicted， and the HF-related targets and related genes of ferroptosis were retrieved at the same time， and the intersecting targets were obtained by Venn diagram. In addition， the protein-protein interaction（PPI） network and the component-target network were constructed， and the core components and core targets were obtained by topological analysis. Then Gene Ontology（GO） function and Kyoto Encyclopedia of Genes and Genomes（KEGG） enrichment analysis were performed on the core targets， and molecular docking validation of the key targets and main components was carried out by AutoDockTools 1.5.7. H9c2 cells were used to establish a oxygen-glucose deprivation model， and the protective effect of BXG on cells was investigated by detecting cell viability， cell survival rate and reactive oxygen species（ROS） level. The protein expression levels of signal transducer and activator of transcription 3（STAT3）， phosphorylation（p）-STAT3 and glutathione peroxidase 4（GPX4） were detected by Western blot to clarify the regulatory effect of BXG on ferroptosis. ResultsA total of 61 chemical components in BXG intestinal absorption fluid were identified， and network pharmacology obtained 27 potential targets of BXG for the treatment of HF， as well as 139 signaling pathways. BXG may act on core targets such as STAT3， tumor protein p53（TP53）， epidermal growth factor receptor（EGFR）， JUN and prostaglandin-endoperoxide synthase 2（PTGS2） through core components such as glabrolide and limonin， which in turn intervene in lipid and atherosclerosis， phosphatidylinositol 3-kinase/protein kinase B（PI3K/Akt）， endocrine resistance and other signaling pathways to exert therapeutic effects on HF. Molecular docking showed that the docking results of multiple groups of targets and compounds were good. In vitro cell experiments showed that compared with the blank group， the cell viability and survival rate of the model group were significantly decreased， the level of ROS was significantly increased（P<0.01）， the expression levels of STAT3， p-STAT3， p-STAT3/STAT3 and GPX4 proteins were significantly decreased（P<0.05， P<0.01）. Compared with the model group， the cell viability and survival rate of the BXG group were significantly increased， the ROS level was significantly decreased（P<0.01）， the STAT3， p-STAT3， p-STAT3/STAT3 and GPX4 protein levels were significantly increased（P<0.05， P<0.01）. ConclusionBXG may inhibit the occurrence of ferroptosis by up-regulating the expression of STAT3 and GPX4， thus exerting a therapeutic effect on HF， and flavonoids may be the key components of this role.

ObjectiveBased on ultra performance liquid chromatography-quadrupole-time-of-flight mass spectrometry（UPLC-Q-TOF-MS）， network pharmacology， molecular docking and cell experiments， the active ingredients， possible targets and molecular mechanisms of Baoxin granules（BXG） regulating ferroptosis in the treatment of heart failure（HF） were explored. MethodsBXG intestinal absorption fluid was prepared by everted gut sac and the chemical composition contained therein were identified by UPLC-Q-TOF-MS. According to the obtained components， the potential targets of BXG were predicted， and the HF-related targets and related genes of ferroptosis were retrieved at the same time， and the intersecting targets were obtained by Venn diagram. In addition， the protein-protein interaction（PPI） network and the component-target network were constructed， and the core components and core targets were obtained by topological analysis. Then Gene Ontology（GO） function and Kyoto Encyclopedia of Genes and Genomes（KEGG） enrichment analysis were performed on the core targets， and molecular docking validation of the key targets and main components was carried out by AutoDockTools 1.5.7. H9c2 cells were used to establish a oxygen-glucose deprivation model， and the protective effect of BXG on cells was investigated by detecting cell viability， cell survival rate and reactive oxygen species（ROS） level. The protein expression levels of signal transducer and activator of transcription 3（STAT3）， phosphorylation（p）-STAT3 and glutathione peroxidase 4（GPX4） were detected by Western blot to clarify the regulatory effect of BXG on ferroptosis. ResultsA total of 61 chemical components in BXG intestinal absorption fluid were identified， and network pharmacology obtained 27 potential targets of BXG for the treatment of HF， as well as 139 signaling pathways. BXG may act on core targets such as STAT3， tumor protein p53（TP53）， epidermal growth factor receptor（EGFR）， JUN and prostaglandin-endoperoxide synthase 2（PTGS2） through core components such as glabrolide and limonin， which in turn intervene in lipid and atherosclerosis， phosphatidylinositol 3-kinase/protein kinase B（PI3K/Akt）， endocrine resistance and other signaling pathways to exert therapeutic effects on HF. Molecular docking showed that the docking results of multiple groups of targets and compounds were good. In vitro cell experiments showed that compared with the blank group， the cell viability and survival rate of the model group were significantly decreased， the level of ROS was significantly increased（P<0.01）， the expression levels of STAT3， p-STAT3， p-STAT3/STAT3 and GPX4 proteins were significantly decreased（P<0.05， P<0.01）. Compared with the model group， the cell viability and survival rate of the BXG group were significantly increased， the ROS level was significantly decreased（P<0.01）， the STAT3， p-STAT3， p-STAT3/STAT3 and GPX4 protein levels were significantly increased（P<0.05， P<0.01）. ConclusionBXG may inhibit the occurrence of ferroptosis by up-regulating the expression of STAT3 and GPX4， thus exerting a therapeutic effect on HF， and flavonoids may be the key components of this role.

Objective:To analyze the differences in heart size，shape and function between fetuses with tetralogy of Fallot（TOF）and fetuses with malalignment ventricular septal defect（VSD）and pulmonary stenosis（PS）（named as，mild TOF）by fetal heart quantification（fetal HQ）and multi-parameter fetal echocardiography.Methods:From June 2021 to June 2023，50 fetuses with TOF（TOF group）diagnosed by fetal echocardiography at the Department of Diagnostic Ultrasound & Echocardiography Sir Run Run Shaw Hospital，Zhejiang University College of Medicine and 34 fetuses with VSD and PS matched to gestational age（mild TOF group）were retrospectively selected. Cardiovascular parameters were measured by 2D echocardiography，M-mode echocardiography and fetal HQ，including aortic dimension（AO）and its Z-score（AO Z-score），pulmonary artery diameter（PA）and its Z-score（PA Z-score），PA/AO ratio，main pulmonary artery diameter（MPA）and its Z-score（MPA Z-score），left pulmonary artery diameter（LPA）and its Z-score（LPA Z-score），right pulmonary artery diameter（RPA）and its Z-score（RPA Z-score），McGoon index（MGI），tricuspid annular diameter（TV）and its Z-score（TV Z-score），mitral annular diameter（MV）and its Z-score（MV Z-score），and MV/TV ratio. Measurements of global ventricular morphologic parameters included cardiac axis，left and right ventricular transverse diameters（LVW，RVW）and their ratio（LVW/RVW），left and right ventricular long diameters（LVL，RVL）and LVL/RVL ratio，left and right ventricular areas（LVA，RVA）and LVA/RVA ratio，global spherical index（GSI）and its Z-score，four chamber view transverse diameter（4CV-Width-ED），four chamber view end-diastolic longitudinal diameter（4CV-Length-ED），four chamber view end-diastolic area（4CV-Area-ED）. Measurements of left and right global ventricular functional parameters included fractional left ventricular and right ventricular area changes（LVFAC，RVFAC），left ventricular ejection fraction（LVEF），left ventricular and right ventricular global longitudinal strains（LVGLS，RVGLS）；end diastolic width diameter（Width-ED），SI and fractional shortening rate（FS）of 24 segments of left and right ventricles. The differences of the above parameters between the two groups were analyzed and compared，and the relationships between absolute values of GLS in left and right ventricles of TOF fetus and PA Z-score，MPA Z-score and PA/AO were analyzed. Binary Logistic regression model was used to select the best variables，and ROC curve was adopted to analyze the predictive values of ultrasonic parameter variables on TOF.Results:There were statistically significant differences in MV，TV，RVW，RVL，LVL，LVA，RVA，4CV-Length-ED，LVGLS，RVGLS，RVFAC，PA/AO，MPA，RPA，LPA，MGI，PA and PA Z-score between TOF group and mild TOF group（all P<0.05）. The Width-ED values of all segments of left ventricle were statistically different between TOF group and mild TOF group（all P<0.05）. There were statistical differences in SI between LV segments 4~6 and 8~24，and RV segments 1~21（all P<0.05）. The FS values between the 8th and 10th to 18th segments of RV revealed statistical differences（all P<0.05）. There were no statistical differences in the other parameters（all P>0.05）. The absolute value of LVGLS in TOF fetuses was positively correlated with PA Z-score，MPA Z-score and PA/AO（ r = 0.313，0.344，0.304，all P<0.05），and the absolute value of RVGLS was positively correlated with PA Z-score，MPA Z-score，and PA/AO（ r = 0.323，0.334，0.357，all P<0.05）. Binary Logistic regression model analysis confirmed that LVGLS，RVFAC and PA/AO were predictive variables. ROC curve analysis showed that the areas under the curves of LVGLS，RVFAC and PA/AO for predicting TOF were 0.746，0.693 and 0.849 respectively. The combined prediction efficiency was higher，and the area under the curve was 0.906. Conclusions:Fetal HQ combined with multiple fetal echocardiographic quantification indices can evaluate the differences in fetal heart size，shape and function between TOF and mild TOF. It is expected to provide important reference information in prenatal diagnosis and consultation for fetuses with TOF and mild TOF.

The purpose of this study was to clarify the effect of Huotan Jiedu Tongluo Decoction on atherosclerosis(AS) injury in ApoE~(-/-) mice by regulating the ferroptosis pathway. Seventy-five ApoE~(-/-) mice were randomly divided into model group, low-, medium-, and high-dose of Huotan Jiedu Tongluo Decoction groups, and evolocumab group(n=15), and 15 C57BL/6J mice were selected as the blank group. Mice in the blank group were fed with a normal diet, and those in the other groups were fed with a high-fat diet to induce AS. From the 9th week, mice in Huotan Jiedu Tongluo Decoction groups were administrated with Huotan Jiedu Tongluo Decoction at corresponding doses by gavage, and those in the blank group and the model group were given an equal volume of distilled water. Mice in the evolocumab group were treated with evolocumab 18.2 mg·kg~(-1 )by subcutaneous injection every 2 weeks. After 8 weeks of continuous intervention, oil red O staining and hematoxylin-eosin(HE) staining were employed to observe the lipid deposition and plaque formation in the aortic root. Masson staining was used to evaluate the collagen content in the aortic root. The serum levels of total cholesterol(TC), triglycerides(TG), high-density lipoprotein cholesterol(HDL-C), and low-density lipoprotein cholesterol(LDL-C) were determined by biochemical kits. The levels of Fe~(2+), superoxide dismutase(SOD), malondialdehyde(MDA), and glutathione(GSH) in the aorta were measured by colorimetry. The protein and mRNA levels of nuclear factor erythroid 2-related factor 2(Nrf2), glutathione peroxidase 4(GPX4), solute carrier family 7 member 11(SLC7A11), and acyl-CoA synthetase long chain family member 4(ACSL4) in the aorta were detected by Western blot and RT-qPCR, respectively. The expression of Nrf2, GPX4, and SLC7A11 was localized by immunofluorescence. The results showed that low-, medium-, and high-dose Huotan Jiedu Tongluo Decoction reduced the plaque formation of aortic root and increased the collagen content in AS mice. At the same time, Huotan Jiedu Tongluo Decoction improved the lipid metabolism by lowering the levels of TC, LDL-C, and TG and elevating the level of HDL-C in the serum. Huotan Jiedu Tongluo Decoction enhanced the antioxidant capacity by elevating the levels of GSH and SOD and lowering the level of MDA in the aorta and inhibiting the accumulation of Fe~(2+) in the aorta. In addition, Huotan Jiedu Tongluo Decoction up-regulated the protein and mRNA levels of Nrf2, GPX4, and SLC7A11, while down-regulating the protein and mRNA levels of ACSL4. In summary, Huotan Jiedu Tongluo Decoction can effectively alleviate AS lesions in ApoE~(-/-) mice by activating the Nrf2/GPX4 pathway, reducing lipid peroxidation, and inhibiting ferroptosis.
Animals ; Ferroptosis/drug effects* ; Atherosclerosis/metabolism* ; Drugs, Chinese Herbal/administration & dosage* ; NF-E2-Related Factor 2/genetics* ; Mice ; Mice, Inbred C57BL ; Apolipoproteins E/metabolism* ; Male ; Phospholipid Hydroperoxide Glutathione Peroxidase/genetics* ; Signal Transduction/drug effects* ; Humans ; Mice, Knockout

Emodin is a hydroxyanthraquinone compound that is widely distributed and has multiple pharmacological activities, including anti-diarrheal, anti-inflammatory, and liver-protective effects. Research indicates that emodin may be one of the main components responsible for inducing hepatotoxicity. However, studies on the mechanisms of liver injury are relatively limited, particularly those related to bile acids(BAs) metabolism. This study aims to systematically investigate the effects of different dosages of emodin on BAs metabolism, providing a basis for the safe clinical use of traditional Chinese medicine(TCM)containing emodin. First, this study evaluated the safety of repeated administration of different dosages of emodin over a 5-week period, with a particular focus on its impact on the liver. Next, the composition and content of BAs in serum and liver were analyzed. Subsequently, qRT-PCR was used to detect the mRNA expression of nuclear receptors and transporters related to BAs metabolism. The results showed that 1 g·kg~(-1) emodin induced hepatic damage, with bile duct hyperplasia as the primary pathological manifestation. It significantly increased the levels of various BAs in the serum and primary BAs(including taurine-conjugated and free BAs) in the liver. Additionally, it downregulated the mRNA expression of farnesoid X receptor(FXR), retinoid X receptor(RXR), and sodium taurocholate cotransporting polypeptide(NTCP), and upregulated the mRNA expression of cholesterol 7α-hydroxylase(CYP7A1) in the liver. Although 0.01 g·kg~(-1) and 0.03 g·kg~(-1) emodin did not induce obvious liver injury, they significantly increased the level of taurine-conjugated BAs in the liver, suggesting a potential interference with BAs homeostasis. In conclusion, 1 g·kg~(-1) emodin may promote the production of primary BAs in the liver by affecting the FXR-RXR-CYP7A1 pathway, inhibit NTCP expression, and reduce BA reabsorption in the liver, resulting in BA accumulation in the peripheral blood. This disruption of BA homeostasis leads to liver injury. Even doses of emodin close to the clinical dose can also have a certain effect on the homeostasis of BAs. Therefore, when using traditional Chinese medicine or formulas containing emodin in clinical practice, it is necessary to regularly monitor liver function indicators and closely monitor the risk of drug-induced liver injury.
Emodin/administration & dosage* ; Bile Acids and Salts/metabolism* ; Animals ; Male ; Liver/injuries* ; Chemical and Drug Induced Liver Injury/genetics* ; Drugs, Chinese Herbal/adverse effects* ; Humans ; Rats, Sprague-Dawley ; Mice ; Rats

Objective To explore and identify the nutritional/inflammatory indicator with the highest predictive potential for overall survival(OS)in postoperative tumor patients so as to provide guidance for postoperative rehabilitation of tumor patients.Methods Data from 3 191 surgical patients were collected,including 15 nutritional/inflammatory indicators.The maximum selection rank statistic method was used to calculate the optimal cut-off values for continuous indicators.The Kaplan-Meier method was used to assess OS,and Cox proportional hazards models were used to analyze the association between the aforementioned 15 indicators and survival.The predictive value of these 15 indicators was evaluated with receiver operating characteristic(ROC)curves and C-index.Results Multivariate analysis showed that all 15 indicators were significantly associated with poorer OS in surgical patients(P＜0.05 for all).Time-dependent area under the curve(AUC)and C-index analysis indicated that 3 indicators with the highest predictive potential in OS in postoperative tumor patients were the nutritional risk index(NRI)(C-index:0.597),C-reactive protein-to-albumin ratio(CAR)(C-index:0.587),and C-reactive protein-to-lymphocyte ratio(CLR)(C-index:0.587).The optimal cut-off value for NRI was determined to be 104.31(i.e.,NRI＜104.31 suggests malnutrition)with the maximum selection rank statistic method,the optimal cut-off value for CAR to be 0.05(i.e.,CAR≥0.05 suggests a strong inflammatory response,often accompanied by malnutrition),and the optimal cut-off value for CLR to be 1.18(i.e.,CLR≥1.18 suggests a strong inflammatory response).Subgroup analysis indicated that NRI,CAR,and CLR had good correlation with tumor staging,and there were significant differences between tumor node metastasis(TNM)Ⅲ/Ⅳ stage patients and TNM Ⅰ/Ⅱ stage patients when there was a strong inflammatory response or malnutrition.Conclusion In postoperative tumor patients,NRI,CLR,and CAR have high prognostic value.Combining these with the patient's clinical stage,it enables more precise guidance for clinical diagnosis and treatment strategies.

Objectives:To investigate the clinical value of cardiac magnetic resonance imaging(CMR)feature-tracking strain analysis in risk stratification of diabetic heart failure with preserved ejection fraction(HFpEF).Methods:In this retrospective study,a total of 215 patients with diabetic HFpEF who underwent CMR at Chinese Academy of Medical Sciences Fuwai Hospital from January 2012 to December 2018 were included.Myocardial strain parameters were calculated using CMR feature-tracking technology.Patients were followed up by medical records or telephone calls.Composite endpoint event,all-cause death or heart failure hospitalization during follow-up were recorded.Patients were divided into event group and event-free group.Univariable and multivariable Cox proportional hazard regression analyses were performed to determine the risk factors for the outcomes in diabetic HFpEF.The effects of hypertension and obesity on the prognosis of diabetic HFpEF patients and whether they affect the prognostic value of CMR feature-tracking strain analysis were also analyzed.Results:During a follow-up of(7.1±1.8)years,93(43.3%)patients had endpoint events(event group),including 28 all-cause deaths and 65 heart failure hospitalization.Compared with the event-free group(n=122),patients in the event group had significantly lower left ventricular ejection fraction,higher prevalence and extent of late gadolinium enhancement,and significantly reduced global longitudinal strain(GLS),global circumferential strain,global radial strain,and global systolic longitudinal strain rate(all P<0.05).The absolute GLS value was significantly lower in event group than in event-free group,regardless of the presence of hypertension and obesity.Multivariate Cox regression analysis showed that estimated glomerular filtration rate(HR=0.983,95%CI:0.972-0.993,P=0.001),left atrial volume index(HR=1.015,95%CI:1.005-1.026,P=0.004),and GLS(HR=1.142,95%CI:1.060-1.231,P<0.001)were independent risk factors for adverse cardiovascular events in diabetic HFpEF patients.However,adjusted N-terminal pro-brain natriuretic peptide was not an independent prognostic factor.The cut-offvalue of GLS to predict outcome was-14.09%from ROC curve analysis.The Kaplan-Meier curve showed that in patients with and without hypertension and obesity,patients with the GLS>-14.09%had lower event-free survival compared to patients with GLS≤-14.09%(all P<0.05),and the ability of GLS to predict adverse outcomes was not affected by hypertension and obesity.Conclusions:GLS obtained by CMR feature-tracking strain analysis is an independent predictor of adverse outcomes in diabetic HFpEF,and its ability to predict adverse outcomes is independent of hypertension and obesity.