PET Imaging of Fibroblast Activation Protein in Various Cancers Using [18F]AlF­NOTA­FAPI­04: Comparison with 18F-FDG in a Single-Center, Prospective Study.

RATIONALE AND OBJECTIVES: Targeting fibroblast-activation protein is a newer diagnostic approach for the visualization of tumor stroma, and a novel aluminum-[18F] fluoride (Al18F)-labeled fibroblast-activation protein inhibitor-4 (FAPI-04), hereafter [18F] AlF-NOTA-FAPI-04, presents a promising alternative to gallium 68 (68Ga)-labeled FAPI owing to its relatively longer half-life. This study sought to evaluate the clinical usefulness of [18F] AlF-NOTA-FAPI-04 PET/CT for the diagnosis of various types of cancer, compared to [18F] FDG PET/CT. MATERIALS AND METHODS: In this prospective study conducted from October 2021 to January 2024, a total of 148 patients with 16 different tumor entities underwent contemporaneous 18F-FDG and 18F-FAPI-04 PET/CT either for an initial assessment or for recurrence detection. Uptake of 18F-FDG and 18F-FAPI-04 was quantified by the maximum standard uptake value (SUV max). Diagnostic sensitivity, specificity, and accuracy were compared by using the McNemar test between these two imaging agents. RESULTS: 18F-FAPI-04 PET/CT could clearly depict 16 different types of cancer with excellent image contrast, thereby leading to a higher detection rate of primary tumors than did 18F-FDG PET/CT (98.06% vs. 81.55%, P＜0.001). In per-lymph node analysis, the sensitivity, specificity, and accuracy in the diagnosis of metastatic lymph nodes were 92.44%, 90.44%, and 91.56%, respectively, which was much higher than that 18F-FDG PET/CT (80.23%, 79.41%, and 79.87%, respectively). Meanwhile, 18F-FAPI-04 PET/CT outperformed 18F-FDG PET/CT in identifying more suspected distant metastases (86.57% vs. 74.13%, P＜0.001). Furthermore, 18F-FAPI-04 PET/CT upgraded tumor staging in 36/101 patients (35.6%), and detected tumor recurrence or metastases in 43/47 patients (91.49%). CONCLUSION: Our findings demonstrated that primary and metastatic lesions in patients with various types of malignant tumors are well-visualized on 18F-FAPI-04 PET/CT, which exhibited a superior diagnostic performance than 18F-FDG PET/CT. Moreover, 18F-FAPI-04 PET/CT is a promising tool for tumor staging and follow-up of various malignancies.

Deep learning-based automatic segmentation of meningioma from T1-weighted contrast-enhanced MRI for preoperative meningioma differentiation using radiomic features.

BACKGROUND: This study aimed to establish a dedicated deep-learning model (DLM) on routine magnetic resonance imaging (MRI) data to investigate DLM performance in automated detection and segmentation of meningiomas in comparison to manual segmentations. Another purpose of our work was to develop a radiomics model based on the radiomics features extracted from automatic segmentation to differentiate low- and high-grade meningiomas before surgery. MATERIALS: A total of 326 patients with pathologically confirmed meningiomas were enrolled. Samples were randomly split with a 6:2:2 ratio to the training set, validation set, and test set. Volumetric regions of interest (VOIs) were manually drawn on each slice using the ITK-SNAP software. An automatic segmentation model based on SegResNet was developed for the meningioma segmentation. Segmentation performance was evaluated by dice coefficient and 95% Hausdorff distance. Intra class correlation (ICC) analysis was applied to assess the agreement between radiomic features from manual and automatic segmentations. Radiomics features derived from automatic segmentation were extracted by pyradiomics. After feature selection, a model for meningiomas grading was built. RESULTS: The DLM detected meningiomas in all cases. For automatic segmentation, the mean dice coefficient and 95% Hausdorff distance were 0.881 (95% CI: 0.851-0.981) and 2.016 (95% CI:1.439-3.158) in the test set, respectively. Features extracted on manual and automatic segmentation are comparable: the average ICC value was 0.804 (range, 0.636-0.933). Features extracted on manual and automatic segmentation are comparable: the average ICC value was 0.804 (range, 0.636-0.933). For meningioma classification, the radiomics model based on automatic segmentation performed well in grading meningiomas, yielding a sensitivity, specificity, accuracy, and area under the curve (AUC) of 0.778 (95% CI: 0.701-0.856), 0.860 (95% CI: 0.722-0.908), 0.848 (95% CI: 0.715-0.903) and 0.842 (95% CI: 0.807-0.895) in the test set, respectively. CONCLUSIONS: The DLM yielded favorable automated detection and segmentation of meningioma and can help deploy radiomics for preoperative meningioma differentiation in clinical practice.

Preoperative prediction of microsatellite instability status: development and validation of a pan-cancer PET/CT-based radiomics model.

OBJECTIVE: The purpose of this study is to verify the feasibility of preoperative prediction of patients' microsatellite instability status by applying a PET/CT-based radiation model. METHODS: This retrospective study ultimately included 142 patients. Three prediction models have been developed. The predictive performance of all models was evaluated by the receiver operating characteristic curve and area under the curve values. The PET/CT radiological histology score (Radscore) was calculated to evaluate the microsatellite instability status, and the corresponding nomogram was established. The correlation between clinical factors and radiological characteristics was analyzed to verify the value of radiological characteristics in predicting microsatellite instability status. RESULTS: Twelve features were retained to establish a comprehensive prediction model of radiological and clinical features. M phase of the tumor has been proven to be an independent predictor of microsatellite instability status. The receiver operating characteristic results showed that the area under the curve values of the training set and the validation set of the radiomics model were 0.82 and 0.75, respectively. The sensitivity, specificity, positive predictive value and negative predictive value of the training set were 0.72, 0.78, 0.83 and 0.66, respectively. The sensitivity, specificity, positive predictive value and negative predictive value of the validation set were 1.00, 0.50, 0.76 and 1.00, respectively. The risk of patients with microsatellite instability was calculated by Radscore and nomograph, and the cutoff value was -0.4385. The validity of the results was confirmed by the decision and calibration curves. CONCLUSION: Radiological models based on PET/CT can provide clinical and practical noninvasive prediction of microsatellite instability status of several different cancer types, reducing or avoiding unnecessary biopsy to a certain extent.

Superiority of FAPI-PET/CT for examining multiple malignant tumors: a retrospective study.

To compare the diagnostic value of [18F]-AlF-NOTA-FAPI-04 PET/CT and [18F]-FDG PET/CT for primary and metastatic lesions in different types of tumors. A retrospective analysis was conducted on 51 patients with 11 different types of tumors. Among them, 20 patients underwent PET/CT, and 31 patients underwent restaging. The patients were diagnosed using [18F]-AlF-NOTA-FAPI-04 PET/CT and [18F]-FDG PET/CT scan techniques, and adverse reactions were recorded. Thickness of primary lesions, metastasis, and lymph node involvement were analyzed and confirmed by histological analysis. The sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of [18F]-AlF-NOTA-FAPI-04 PET/CT and [18F]-FDG PET/CT were calculated. Neither [18F]-AlF-NOTA-FAPI-04 PET/CT nor [18F]-FDG PET/CT scan techniques caused adverse reactions in the patients. [18F]-AlF-NOTA-FAPI-04 PET/CT performed well in detecting recurrence, with a positive rate of 100%, higher than 71.0% of [18F]-FDG PET/CT. Compared with [18F]-FDG PET/CT, [18F]-AlF-NOTA-FAPI-04 PET/CT identified 6 types of malignant tumors more clearly, and could improve the detection rate of primary and metastatic tumors (97.0% vs. 84.8%, P<0.001). [18F]-AlF-NOTA-FAPI-04 PET/CT exhibited a higher sensitivity for detecting lymph node (81.8% vs. 50.0%, P<0.05) than [18F]-FDG PET/CT. Additionally, [18F]-AlF-NOTA-FAPI-04 PET/CT demonstrated higher diagnostic sensitivity (67.39% vs. 58.7%, P=0.387) and accuracy (82.14% vs. 60.71%, P=0.377) for detecting metastatic lesions compared to [18F]-FDG PET/CT. [18F]-AlF-NOTA-FAPI-04 PET/CT outperforms [18F]-FDG PET/CT in diagnosing primary and metastatic lesions across various types of tumors, especially in identifying lymph node, visceral, and peritoneal metastases. It can improve diagnostic efficiency and accuracy, thereby positively influencing clinical decision-making for optimal patient management.

Development and validation of 18F-FDG PET/CT radiomics-based nomogram to predict visceral pleural invasion in solid lung adenocarcinoma.

OBJECTIVES: This study aimed to establish a radiomics model based on 18F-FDG PET/CT images to predict visceral pleural invasion (VPI) of solid lung adenocarcinoma preoperatively. METHODS: We retrospectively enrolled 165 solid lung adenocarcinoma patients confirmed by histopathology with 18F-FDG PET/CT images. Patients were divided into training and validation at a ratio of 0.7. To find significant VPI predictors, we collected clinicopathological information and metabolic parameters measured from PET/CT images. Three-dimensional (3D) radiomics features were extracted from each PET and CT volume of interest (VOI). Receiver operating characteristic (ROC) curve was performed to determine the performance of the model. Accuracy, sensitivity, specificity and area under curve (AUC) were calculated. Finally, their performance was evaluated by concordance index (C-index) and decision curve analysis (DCA) in training and validation cohorts. RESULTS: 165 patients were divided into training cohort (n = 116) and validation cohort (n = 49). Multivariate analysis showed that histology grade, maximum standardized uptake value (SUVmax), distance from the lesion to the pleura (DLP) and the radiomics features had statistically significant differences between patients with and without VPI (P < 0.05). A nomogram was developed based on the logistic regression method. The accuracy of ROC curve analysis of this model was 75.86% in the training cohort (AUC: 0.867; C-index: 0.867; sensitivity: 0.694; specificity: 0.889) and the accuracy rate in validation cohort was 71.55% (AUC: 0.889; C-index: 0.819; sensitivity: 0.654; specificity: 0.739). CONCLUSIONS: A PET/CT-based radiomics model was developed with SUVmax, histology grade, DLP, and radiomics features. It can be easily used for individualized VPI prediction.

Differentiating thymic epithelial tumors from mediastinal lymphomas: preoperative nomograms based on PET/CT radiomic features to minimize unnecessary anterior mediastinal surgery.

PURPOSE: Clinical feasibility nomograms were developed to facilitate the differentiation between thymic epithelial tumors (TETs) and mediastinal lymphomas (MLs), aiming to minimize the occurrence of non-therapeutic thymectomy. METHODS: A total of 255 patients diagnosed with TETs or MLs underwent pre-treatment 18F-FDG PET/CT. Comprehensive clinical and imaging data were collected, including age, gender, lactate dehydrogenase (LDH) level, pathological results, presence of myasthenia gravis symptoms, B symptoms, mass size, location, morphology, margins, density, and metabolic parameters derived from PET/CT. Radiomic features were extracted from the region of interest (ROI) of the primary lesion. Feature selection techniques were employed to identify the most discriminative subset of features. Machine learning methods were utilized to build candidate models, which were subsequently evaluated based on their area under the curve (AUC). Finally, nomograms were constructed using the optimal model to provide a clinical tool for improved diagnostic accuracy. The performance of the radiomic models was evaluated by their calibration, discrimination, and clinical utility. RESULTS: Several independent risk factors were identified for distinguishing TETs from MLs, including average standardized uptake value (SUVavg), LDH, age, mass size, and radiomic score (rad-score). Significance was observed in differentiating the two types of tumors based on these factors. The best clinical efficacy was demonstrated by the combined model, with an impressive AUC of 0.954. Decision curve analysis and calibration curves indicated that the combined model was clinically advantageous for discriminating TETs from MLs. Besides, the results of external validation showed a sensitivity of 0.8 and a specificity of 0.78. CONCLUSION: Preoperatively, the differentiation of TETs from MLs can be facilitated by the utilization of the combined clinical information and radiomics model. This approach holds promise in minimizing the occurrence of unnecessary anterior mediastinal surgeries.

[18F] AlF­NOTA­FAPI­04 PET/CT as a promising tool for imaging fibroblast activation protein in gastrointestinal system cancers: a prospective investigation of comparative analysis with 18F-FDG.

PURPOSE: The radiopharmaceutical [18F]AlF-NOTA-FAPI-04 presents a promising alternative to 68 Ga-FAPI owing to its relatively longer half-life. This study aimed to evaluate the clinical usefulness of [18F]AlF-NOTA-FAPI-04 PET/CT for the diagnosis of primary and metastatic lesions in various types of gastrointestinal system cancers, compared with 18F-FDG PET/CT. METHODS: Patients diagnosed with gastrointestinal system malignancies were prospectively enrolled. All patients underwent both 18F-FDG and 18F-FAPI-04 PET/CT scans within one week, with 44 (73.3%) for cancer staging and 16 (26.7%) for tumor restaging. Diagnostic efficacy of the primary tumor, as well as the presence and number of lymph nodes and distant metastases, were assessed. Tumor uptake was quantified by the maximum standard uptake value (SUVmax). RESULTS: For detection of primary tumor, the diagnostic sensitivity of 18F-FDG PET/CT was 72.7%, while it was 97.7% for 18F-FAPI-04 PET/CT. Based on per-lymph node analysis, the sensitivity, specificity, and accuracy of 18F-FAPI-04 PET/CT in diagnosing metastatic lymph nodes were 91.89%, 92.00%, and 91.96%, respectively. These values were notably higher than those 18F-FDG PET/CT (79.72%, 81.33% and 80.80%, respectively). The 18F-FAPI-04 PET/CT surpassed 18F-FDG PET/CT in detecting suspected metastases in the brain (7 vs. 3), liver (39 vs. 20), bone (79 vs. 51), lung (11 vs. 4), and peritoneal carcinoma (48 vs. 22). Based on per-patient analysis, differential diagnostic accuracies (18F-FAPI-04 vs. 18F-FDG PET/CT) were observed in all patients (91.7% vs. 76.7%), the initial staging group (90.9% vs. 79.5%), and the re-staging group (93.8% vs. 68.7%). Additionally, 18F-FAPI-04 PET/CT revised final diagnosis in 31.7% of patients, contrasting with 18F-FDG PET/CT, and prompted changes in clinical management for 21.7% of the patients. CONCLUSION: 18F-FAPI-04 PET/CT outperforms 18F-FDG PET/CT in delineating the primary gastrointestinal tumors and detecting suspected metastatic lesions due to a higher target-to-background ratio (TBR). Moreover, 18F-FAPI-04 PET/CT could provide valuable guidance for tumor staging, thereby having a potential impact on patient management.

Development and validation of a [18F]FDG PET/CT-based radiomics nomogram to predict the prognostic risk of pretreatment diffuse large B cell lymphoma patients.

OBJECTIVE: In this study, based on PET/CT radiomics features, we developed and validated a nomogram to predict progression-free survival (PFS) for cases with diffuse large B cell lymphoma (DLBCL) treated with immunochemotherapy. METHODS: This study retrospectively recruited 129 cases with DLBCL. Among them, PET/CT scans were conducted and baseline images were collected for radiomics features along with their clinicopathological features. Radiomics features related to recurrence were screened for survival analysis using univariate Cox regression analysis with p < 0.05. Next, a weighted Radiomics-score (Rad-score) was generated and independent risk factors were obtained from univariate and multivariate Cox regressions to build the nomogram. Furthermore, the nomogram was tested for their ability to predict PFS using time-dependent receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA). RESULTS: Blood platelet, Rad-score, and gender were included in the nomogram as independent DLBCL risk factors for PFS. We found that the training cohort areas under the curve (AUCs) were 0.79, 0.84, and 0.88, and validation cohort AUCs were 0.67, 0.83, and 0.72, respectively. Further, the DCA and calibration curves confirmed the predictive nomogram's clinical relevance. CONCLUSION: Using Rad-score, blood platelet, and gender of the DLBCL patients, a PET/CT radiomics-based nomogram was developed to guide cases' recurrence risk assessment prior to treatment. The developed nomogram can help provide more appropriate treatment plans to the cases. KEY POINTS: • DLBCL cases can be classified into low- and high-risk groups using PET/CT radiomics based Rad-score. • When combined with other clinical characteristics (gender and blood platelet count), Rad-score can be used to predict the outcome of the pretreatment of DLBCL cases with a certain degree of accuracy. • A prognostic nomogram was established in this study in order to aid in assessing prognostic risk and providing more accurate treatment plans for DLBCL cases.

PET/CT Radiomic Features: A Potential Biomarker for EGFR Mutation Status and Survival Outcome Prediction in NSCLC Patients Treated With TKIs.

Backgrounds: Epidermal growth factor receptor (EGFR) mutation profiles play a vital role in treatment strategy decisions for non-small cell lung cancer (NSCLC). The purpose of this study was to evaluate the predictive efficacy of baseline 18F-FDG PET/CT-based radiomics analysis for EGFR mutation status, mutation site, and the survival benefit of targeted therapy. Methods: A sum of 313 NSCLC patients with pre-treatment 18F-FDG PET/CT scans and genetic mutations detection were retrospectively studied. Clinical and PET metabolic parameters were incorporated into independent predictors of determining mutation status and mutation site. The dataset was randomly allocated into the training and the validation sets in a 7:3 ratio. Three-dimensional (3D) radiomics features were extracted from each PET- and CT-volume of interests (VOI) singularly, and then a radiomics signature (RS) associated with EGFR mutation profiles is built by feature selection. Three different prediction models based on support vector machine (SVM), decision tree (DT), and random forest (RF) classifiers were established. Furthermore, nomograms for estimation of overall survival (OS) and progression-free survival (PFS) were established by integrating PET/CT radiomics score (Rad-score), metabolic parameters, and clinical factors. Predictive performance was assessed by the receiver operating characteristic (ROC) analysis and the calibration curve analysis. The decision curve analysis (DCA) was applied to estimate and compare the clinical usefulness of nomograms. Results: Three hundred thirteen NSCLC patients were classified into a training set (n=218) and a validation set (n=95). Multivariate analysis demonstrated that SUVmax and sex were independent indicators of EGFR mutation status and mutation site. Eight CT-derived RS, six PET-derived RS, and two clinical factors were retained to develop integrated models, which exhibited excellent ability to distinguish between EGFR wild type (EGFR-WT), EGFR 19 mutation type (EGFR-19-MT), and EGFR 21 mutation type (EGFR-21-MT). The SVM model outperformed the RF model and the DT model, yielding training area under the curves (AUC) of EGFR-WT, EGFR-19-WT, and EGFR-21-WT, with 0.881, 0.851, and 0.849, respectively, and validation AUCs of 0.926, 0.805 and 0.859, respectively. For prediction of OS, the integrated nomogram is superior to the clinical nomogram and the radiomics nomogram, with C-indexes of 0.80 in the training set and 0.83 in the validation set, respectively. Conclusions: The PET/CT-based radiomics analysis might provide a novel approach to predict EGFR mutation status and mutation site in NSCLC patients and could serve as useful predictors for the patients' survival outcome of targeted therapy in clinical practice.

Radiomics in Gastric Cancer: First Clinical Investigation to Predict Lymph Vascular Invasion and Survival Outcome Using 18F-FDG PET/CT Images.

Background: Lymph vascular invasion (LVI) is an unfavorable prognostic indicator in gastric cancer (GC). However, there are no reliable clinical techniques for preoperative predictions of LVI. The aim of this study was to develop and validate PET/CT-based radiomics signatures for predicting LVI of GC preoperatively. Radiomics nomograms were also established to predict patient survival outcomes. Methods: This retrospective study registered 148 GC patients with histopathological confirmation for LVI status, who underwent pre-operative PET/CT scans (Discovery VCT 64 PET/CT system) from December 2014 to June 2019. Clinic-pathological factors (age, gender, and tumor grade, etc.) and metabolic PET data (maximum and mean standardized uptake value, total lesion glycolysis and metabolic tumor volume) were analyzed to identify independent LVI predictors. The dataset was randomly assigned to either the training set or test set in a 7:3 ratios. Three-dimensional (3D) radiomics features were extracted from each PET- and CT-volume of interests (VOI) singularly, and then a radiomics signature (RS) associated with LVI status is built by feature selection. Four models with different modalities (PET-RS: only PET radiomics features; CT-RS: only CT radiomics features; PET/CT-RS: both PET and CT radiomics features; PET/CT-RS plus clinical data) were developed to predict LVI. Patients were postoperatively followed up with PET/CT every 6-12 months for the first two years and then annually up to five years after surgery. The PET/CT radiomics score (Rad-scores) was calculated to assess survival outcome, and corresponding nomograms with radiomics (NWR) or without radiomics (NWOR) were established. Results: Tumor grade and maximum standardized uptake value (SUVmax) were the independent LVI predictor. 1037 CT and PET 3D radiomics features were extracted separately and reduced to 4 and 5 features to build CT-RS and PET-RS, respectively. PET/CT-RS and PET/CT-RS plus clinical data (tumor grade and SUVmax) were also developed. The ROC analysis demonstrated clinical usefulness of PET/CT-RS plus clinical data (AUC values for training and validation, respectively 0.936 and 0.914) and PET/CT-RS (AUC values for training and validation, respectively 0.881 and 0.854), which both are superior to CT-RS (0.838 and 0.824) and PET-RS (0.821 and 0.812). SUVmax and LVI were independent prognostic indicators of both OS and PFS. Decision curve analysis (DCA) demonstrated NWR outperformed NWOR and was established to assess survival outcomes. For estimation of OS and PFS, the C-indexes of the NWR were 0. 88 and 0.88 in the training set, respectively, while the C-indexes of the NWOR were 0. 82 and 0.85 in the training set, respectively. Conclusions: The PET/CT-based radiomics analysis might serve as a non-invasive approach to predict LVI status in GC patients and provide effective predictors of patient survival outcomes.

Prediction Model Combining Clinical and MR Data for Diagnosis of Lymph Node Metastasis in Patients With Rectal Cancer.

BACKGROUND: Determining the status of lymph node (LN) metastasis in rectal cancer patients preoperatively is crucial for the treatment option. However, the diagnostic accuracy of current imaging methods is low. PURPOSE: To develop and test a model for predicting metastatic LNs of rectal cancer patients based on clinical data and MR images to improve the diagnosis of metastatic LNs. STUDY TYPE: Retrospective. SUBJECTS: In all, 341 patients with histologically confirmed rectal cancer were divided into one training set (120 cases) and three validation sets (69, 103, 49 cases). FIELD STRENGTH/SEQUENCE: 3.0T, axial and sagittal T2 -weighted turbo spin echo and diffusion-weighted imaging (b = 0 s/mm2 , 800 s/mm2 ) ASSESSMENT: In the training dataset, univariate logistic regression was used to identify the clinical factors (age, gender, and tumor markers) and MR data that correlated with LN metastasis. Then we developed a prediction model with these factors by multiple logistic regression analysis. The accuracy of the model was verified using three validation sets and compared with the traditional MRI method. STATISTICAL TESTS: Univariate and multivariate logistic regression. The area under the curve (AUC) value was used to quantify the diagnostic accuracy of the model. RESULTS: Eight factors (CEA, CA199, ADCmean, mriT stage, mriN stage, CRM, EMVI, and differentiation degree) were significantly associated with LN metastasis in rectal cancer patients (P<0.1). In the training set (120) and the three validation sets (69, 103, 49), the AUC values of the model were much higher than the diagnosis by MR alone (training set, 0.902 vs. 0.580; first validation set, 0.789 vs. 0.743; second validation set, 0.774 vs. 0.573; third validation set, 0.761 vs. 0.524). DATA CONCLUSION: For the diagnosis of metastatic LNs in rectal cancer patients, our proposed logistic regression model, combining clinical and MR data, demonstrated higher diagnostic efficiency than MRI alone. LEVEL OF EVIDENCE: 4 TECHNICAL EFFICACY STAGE: 2.

Cardiac Magnetic Resonance Feature Tracking: A Novel Method to Assess Left Ventricular Three-Dimensional Strain Mechanics After Chronic Myocardial Infarction.

RATIONALE AND OBJECTIVES: This study was designed to assess left ventricular deformation after chronic myocardial infarction (CMI) using cardiac magnetic resonance feature tracking (CMR-FT) technology, and analyze its relationship with left ventricular ejection fraction (LVEF) and infarcted transmurality. MATERIALS AND METHODS: Ninety-six patients with CMI and 72 controls underwent 3.0 T CMR scanning. Strain parameters were measured by dedicated software, including global peak longitudinal strain (GPLS), global peak circumferential strain (GPCS), global peak radial strain (GPRS), segmental peak longitudinal strain (PLS), peak circumferential strain (PCS), and peak radial strain (PRS). All enhanced myocardium segments were divided into subendocardial infarction (SI) and transmural infarction (TI) group. Pearson, intraclass correlation coefficient and receiver operating characteristic analysis were performed to compare the parameters' mean values between SI and TI groups. RESULTS: GPLS, GPRS, and GPCS in CMI group were significantly decreased comparing with control group. PRS and PCS in TI group were significantly lower than those in SI group, whereas no statistical difference was observed in PLS. In Pearson correlation analysis, LVEF was strongly correlated with GPLS, GPRS, and GPCS in CMI patients. Additionally, excellent reproducibility of all strain parameters was observed. In receiver operating characteristic analysis, segmental PRS and PCS might differentiate SI from TI with higher diagnostic efficiency (p < 0.05), while PLS was less valuable (p > 0.05). CONCLUSION: CMR-FT could noninvasively and quantitatively assess global and regional myocardial strain in CMI patients with excellent reproducibility and strong correlation with LVEF. Additionally, segmental myocardial strain parameters indicate potential clinical value in differentiating myocardial infarction subtype.

Advanced myocardial characterization in hypertrophic cardiomyopathy: feasibility of CMR-based feature tracking strain analysis in a case-control study.

OBJECTIVES: This study aimed to evaluate the feasibility and reproducibility of using cardiovascular magnetic resonance feature tracking (CMR-FT) for analysis of bi-ventricular strain and strain rate (SR) in hypertrophic cardiomyopathy (HCM) patients as well as to explore the correlation between right ventricular (RV) and left ventricular (LV) deformation. METHODS: A total of 60 HCM patients and 48 controls were studied. Global and segmental peak values of bi-ventricular longitudinal, circumferential, radial strain, and systolic SR were analyzed. Pearson analysis was performed to investigate the correlation of RV and LV deformation. Intra-observer and inter-observer reproducibility were also assessed. RESULTS: LV mass in the HCM group was significantly higher than that in the control group. LV end-systolic and end-diastolic volume and RV end-systolic and end-diastolic volume in the HCM group were all significantly lower than the correlated parameters in the control group (p < 0.001, respectively), whereas no statistical difference was found in ejection fraction (p > 0.05). Global longitudinal strain (GLS), global longitudinal strain rate (GLSR), global circumferential strain (GCS), global circumferential strain rate (GCSR), global radial strain (GRS), and global radial strain rate (GRSR) of the LV and RV were all significantly lower than the control group, and segmental strain and SR were also true (p < 0.001, respectively). Bi-ventricular strain and SR measurements were highly reproducible at both intra- and inter-observer levels. Additionally, Pearson analysis showed RV GCS, GLS, and GRS positively correlated with LV GCS, GLS, and GRS (r = 0.713, p < 0.001; r = 0.728, p < 0.001; r = 0.730, p < 0.001, respectively). CONCLUSIONS: CMR-FT is a promising approach to analyze impairment of global and segmental myocardium deformation in HCM patients non-invasively and quantitatively. KEY POINTS: • CMR-FT allows for advanced myocardial characterization with high reproducibility. • As compared with controls, HCM patients have significant differences in CMR-FT strain analysis while ejection fraction was similar. • CMR-FT may serve as an early biomarker of HCM in subjects at risk.

Imaging activated T cells predicts response to cancer vaccines.

In situ cancer vaccines are under active clinical investigation, given their reported ability to eradicate both local and disseminated malignancies. Intratumoral vaccine administration is thought to activate a T cell-mediated immune response, which begins in the treated tumor and cascades systemically. In this study, we describe a PET tracer (64Cu-DOTA-AbOX40) that enabled noninvasive and longitudinal imaging of OX40, a cell-surface marker of T cell activation. We report the spatiotemporal dynamics of T cell activation following in situ vaccination with CpG oligodeoxynucleotide in a dual tumor-bearing mouse model. We demonstrate that OX40 imaging was able to predict tumor responses on day 9 after treatment on the basis of tumor tracer uptake on day 2, with greater accuracy than both anatomical and blood-based measurements. These studies provide key insights into global T cell activation following local CpG treatment and indicate that 64Cu-DOTA-AbOX40 is a promising candidate for monitoring clinical cancer immunotherapy strategies.

Atherosclerotic neovasculature MR imaging with mixed manganese-gadolinium nanocolloids in hyperlipidemic rabbits.

A high r1 relaxivity manganese-gadolinium nanocolloid (αvß3-MnOL-Gd NC) was developed and effectively detected atherosclerotic angiogenesis in rabbits fed cholesterol-rich diets for 12 months using a clinical MRI scanner (3T). 3D mapping of neovasculature signal intensity revealed the spatial coherence and intensity of plaque angiogenic expansion, which may, with other high risk MR bioindicators, help identify high-risk patients with moderate (40% to 60%) vascular stenosis. Microscopy confirmed the predominant media and plaque distribution of fluorescent αvß3-MnOL-Gd NC, mirroring the MR data. An expected close spatial association of αvß3-integrin neovasculature and macrophages was noted, particularly within plaque shoulder regions. Manganese oleate bioelimination occurred via the biliary system into feces. Gd-DOTA was eliminated through the bile-fecal and renal excretion routes. αvß3-MnOL-Gd NC offers an effective vehicle for T1w neovascular imaging in atherosclerosis. From the clinical editor: Cerebrovascular accidents are a leading cause of mortality and morbidity worldwide. The acute formation of thrombus following atherosclerotic plaque rupture has been well recognized as the etiology of stroke. The authors studied microanatomical features of vulnerable atherosclerotic plaque in this article, in an attempt to identify those with high risk of rupture. Gadolinium-manganese hybrid nanocolloid (MnOL-Gd NC) was developed as a novel contrast agent for MRI. They show that this agent is effective in providing neovascular imaging.

Synergy between surface and core entrapped metals in a mixed manganese-gadolinium nanocolloid affords safer MR imaging of sparse biomarkers.

High-relaxivity T1-weighted (T1w) MR molecular imaging nanoparticles typically present high surface gadolinium payloads that can elicit significant acute complement activation (CA). The objective of this research was to develop a high T1w contrast nanoparticle with improved safety. We report the development, optimization, and characterization of a gadolinium-manganese hybrid nanocolloid (MnOL-Gd NC; 138±10 (Dav)/nm; PDI: 0.06; zeta: -27±2 mV). High r1 particulate relaxivity with minute additions of Gd-DOTA-lipid conjugate to the MnOL nanocolloid surface achieved an unexpected paramagnetic synergism. This hybrid MnOL-Gd NC provided optimal MR TSE signal intensity at 5 nM/voxel and lower levels consistent with the level expression anticipated for sparse biomarkers, such as neovascular integrins. MnOL NC produced optimal MR TSE signal intensity at 10 nM/voxel concentrations and above. Importantly, MnOL-Gd NC avoided acute CA in vitro and in vivo while retaining minimal transmetallation risk. From the clinical editor: The authors developed a gadolinium-manganese hybrid nanocolloid (MnOL-Gd NC) in this study. These were used as a high-relaxivity paramagnetic MR molecular imaging agent in experimental models. It was shown that MnOL-Gd NC could provide high T1w MR contrast for targeted imaging. As the level of gadolinium used was reduced, there was also reduced risk of systemic side effects from complement activation.

Parameters of dynamic contrast-enhanced MRI as imaging markers for angiogenesis and proliferation in human breast cancer.

BACKGROUND: Breast cancer is the most common malignancy and the leading cause of cancer death in women worldwide; however, early diagnosis has been difficult due to its complex pathological structure. This study evaluated the value of morphological examination in conjunction with dynamic contrast-enhanced MRI (DCE-MRI) for more precise diagnosis of breast cancer, as well as their correlation with angiogenesis and proliferation biomarkers. MATERIAL/METHODS: DCE-MRI parameters (including Ktrans: volume transfer coefficient reflecting vascular permeability, Kep: flux rate constant, Ve: extracellular volume ratio reflecting vascular permeability, and ADC: apparent diffusion coefficient) were obtained from 124 patients with breast cancer (124 lesions). Microvessel density (MVD) was evaluated by the immunohistochemical analysis of tumor vessels for CD31 and CD105 expression. The proliferation was assessed by analyzing Ki67. RESULTS: Ktrans values were in the order of: malignant lesions>benign lesions>normal glands. Similar results were observed for Kep. The opposite changes were seen with Ve. Ktrans and Kep values were significantly higher in invasive ductal carcinoma (IDC) and ductal carcinoma in situ (DCIS) than in mammary ductal dysplasia (MDD; ANOVA followed by Dunnett's test). In sharp contrast, ADC values were lower in IDC and DCIS than in MDD, and Ve was not significantly different among the three groups. The data from MIP (maximum intensity projection) showed that benign breast lesions had no or only one blood vessel, whereas malignant lesions had two or more blood vessels. In addition, expression of CD105 and Ki67, the commonly recognized markers for angiogenesis and proliferation, respectively, were closely correlated with MRI parameters as revealed by Pearson analysis. CONCLUSIONS: Determination of Ktrans, Kep and ADC values permits estimation of tumor angiogenesis and proliferation in breast cancer and DCE-MRI parameters can be used as imaging biomarkers to predict patient prognosis and the biologic aggressiveness of the tumor.

Anti-angiogenesis therapy in the Vx2 rabbit cancer model with a lipase-cleavable Sn 2 taxane phospholipid prodrug using α(v)ß3-targeted theranostic nanoparticles.

In nanomedicine, the hydrophobic nature of paclitaxel has favored its incorporation into many nanoparticle formulations for anti-cancer chemotherapy. At lower doses taxanes are reported to elicit anti-angiogenic responses. In the present study, the facile synthesis, development and characterization of a new lipase-labile docetaxel prodrug is reported and shown to be an effective anti-angiogenic agent in vitro and in vivo. The Sn 2 phosphatidylcholine prodrug was stably incorporated into the lipid membrane of α(v)ß3-integrin targeted perfluorocarbon (PFC) nanoparticles (α(v)ß3-Dxtl-PD NP) and did not appreciably release during dissolution against PBS buffer or plasma over three days. Overnight exposure of α(v)ß3-Dxtl-PD NP to plasma spiked with phospholipase enzyme failed to liberate the taxane from the membrane until the nanoparticle integrity was compromised with alcohol. The bioactivity and efficacy of α(v)ß3-Dxtl-PD NP in endothelial cell culture was as effective as Taxol(®) or free docetaxel in methanol at equimolar doses over 96 hours. The anti-angiogenesis effectiveness of α(v)ß3-Dxtl-PD NP was demonstrated in the Vx2 rabbit model using MR imaging of angiogenesis with the same α(v)ß3-PFC nanoparticle platform. Nontargeted Dxtl-PD NP had a similar MR anti-angiogenesis response as the integrin-targeted agent, but microscopically measured decreases in tumor cell proliferation and increased apoptosis were detected only for the targeted drug. Equivalent dosages of Abraxane(®) given over the same treatment schedule had no effect on angiogenesis when compared to control rabbits receiving saline only. These data demonstrate that α(v)ß3-Dxtl-PD NP can reduce MR detectable angiogenesis and slow tumor progression in the Vx2 model, whereas equivalent systemic treatment with free taxane had no benefit.

Characterization of early neovascular response to acute lung ischemia using simultaneous (19)F/ (1)H MR molecular imaging.

Angiogenesis is an important constituent of many inflammatory pulmonary diseases, which has been unappreciated until recently. Early neovascular expansion in the lungs in preclinical models and patients is very difficult to assess noninvasively, particularly quantitatively. The present study demonstrated that (19)F/(1)H MR molecular imaging with αvß3-targeted perfluorocarbon nanoparticles can be used to directly measure neovascularity in a rat left pulmonary artery ligation (LPAL) model, which was employed to create pulmonary ischemia and induce angiogenesis. In rats 3 days after LPAL, simultaneous (19)F/(1)H MR imaging at 3T revealed a marked (19)F signal in animals 2 h following αvß3-targeted perfluorocarbon nanoparticles [(19)F signal (normalized to background) = 0.80 ± 0.2] that was greater (p = 0.007) than the non-targeted (0.30 ± 0.04) and the sham-operated (0.07 ± 0.09) control groups. Almost no (19)F signal was found in control right lung with any treatment. Competitive blockade of the integrin-targeted particles greatly decreased the (19)F signal (p = 0.002) and was equivalent to the non-targeted control group. Fluorescent and light microscopy illustrated heavy decorating of vessel walls in and around large bronchi and large pulmonary vessels. Focal segmental regions of neovessel expansion were also noted in the lung periphery. Our results demonstrate that (19)F/(1)H MR molecular imaging with αvß3-targeted perfluorocarbon nanoparticles provides a means to assess the extent of systemic neovascularization in the lung.

Ischemic postconditioning-mediated miRNA-21 protects against cardiac ischemia/reperfusion injury via PTEN/Akt pathway.

BACKGROUND: Ischemic postconditioning (IPost) protects the reperfused heart from infarction which has drawn much attention recently. However, studies to date have rarely investigated the role of microRNAs (miRNAs) in IPost. The aims of this study were to investigate whether miR-21 is involved in the protective effect of IPost against myocardial ischemia-reperfusion (I/R) injury and disclose the potential molecular mechanisms involved. METHODS AND RESULTS: We found that miR-21 was remarkably up-regulated in mouse hearts after IPost. To determine the protective role of IPost-induced miR-21 up-regulation, the mice were divided into the following four groups: I/R group; I/R+IPost group (I/R mice treated with IPost); Antagomir-21+IPost+I/R group (I/R mice treated with anagomir-21 and IPost); Scramble+IPost+I/R group (I/R mice treated with scramble and IPost). The results showed IPost could reduce I/R injury-induced infarct size of the left ventricle, improve cardiac function, and prevent myocardial apoptosis, while knockdown of miR-21 with antagomir-21 could reverse these protective effects of IPost against mouse I/R injury. Furthermore, we confirmed that miR-21 plays a protective role in myocardial apoptosis through PTEN/Akt signaling pathway, which was abrogated by the PI3K inhibitor LY294002. The protective effect of miR-21 on myocardial apoptosis was further revealed in mouse hearts after IPost treatment in vivo. CONCLUSIONS: Our data clearly demonstrate that miR-21 is involved in IPost-mediated cardiac protection against I/R injury and dysfunction through the PTEN/Akt signaling pathway in vivo. Identifying the beneficial roles of IPost-regulated miRNAs in cardiac protection, which may be a rational target selection for ischemic cardioprotection.