19F MRI/CEUS Dual Imaging-Guided Sonodynamic Therapy Enhances Immune Checkpoint Blockade in Triple-Negative Breast Cancer.

Treatment of highly aggressive triple-negative breast cancer (TNBC) in the clinic is challenging. Here, a liposome nanodrug (LP@PFH@HMME) integrating imaging agents and therapeutic agents for bimodal imaging-guided sonodynamic therapy (SDT) is developed, which boosted immunogenicity to enable potent immunotherapy via immune checkpoint blockade (ICB) in TNBC. In the acidic tumor microenvironment (TME), LP@PFH@HMME undergoes "nano-to-micro" transformation due to a pH-responsive lipid fusion, which makes droplets much more sensitive to ultrasound (US) in contrast-enhanced ultrasound (CEUS) and SDT studies. The nanodrug demonstrates robust bimodal imaging ability through fluorine-19 magnetic resonance imaging (19F MRI) and CEUS bimodal imaging, and it exhibits excellent solubility in aqueous solution with relatively high 19F content and desirable long transverse relaxation time (T2 = 1.072 s), making it suitable for high-performance 19F MRI, in addition to effective accumulation of nanodrugs after tail vein injection. Thus, 19F MRI/CEUS dual imaging is achievable to show adequate time points for US irradiation of tumor sites to induce highly effective SDT, which produces abundant reactive oxygen species (ROS) triggering immunogenic cell death (ICD) to assist ICB-based immunotherapy. The combination treatment design of sonodynamic therapy with immunotherapy effectively inhibited TNBC growth and recurrence, highlighting the promise of multifunctional nanodrugs in treating TNBC.

Benign thyroid nodules classified as ACR TI-RADS 4 or 5: Imaging and histological features.

BACKGROUND: American College of Radiology Thyroid Imaging Reporting and Data System (ACR TI-RADS) being most widely applied in clinical practice, there is an overlap in US imaging manifestations between benign and malignant thyroid nodules. OBJECTIVES: To analyze the imaging and histological characteristics of pathological benign thyroid nodules categorized as American College of Radiology Thyroid Imaging Reporting and Data System (ACR TI-RADS) 4 or 5, and to explore the correlation between the suspicious sonographic signs resulting in the misdiagnoses and the histopathological features. MATERIALS AND METHODS: Overall, 227 benign thyroid nodules (215 patients) in ACR TI-RADS 4 or 5 sampled through surgical excision were analyzed between December 2020 and August 2022. We retrospectively reread the ultrasound (US) images of the pathological discordant cases, after which we performed a systematic analysis focusing on the histopathological characteristics of thyroid lesions and recorded the findings. Qualitative US features and pathological significance of the thyroid nodules were analyzed using the chi-square and Fisher's exact tests. RESULTS: The pathological type of 227 thyroid nodules (n = 103 in ACR TI-RADS 4 and n = 124 in ACR TI-RADS 5) was nodular goiter together with other histopathological features, namely, fibrosis (n = 103, 45.4 %), calcification (n = 70, 30.8 %), adenomatous hyperplasia (n = 31, 13.7 %), follicular epithelial hyperplasia (n = 23, 10.1 %), Hashimoto's thyroiditis (n = 18, 7.9 %), and cystic degeneration (n = 16, 7.1 %). Fibrosis was the most common histopathological feature in both ACR TI-RADS 4 (n = 42, 40.8 %) and 5 (n = 61, 49.2 %) categories of benign thyroid nodules. Thyroid nodules with fibrosis demonstrated sonographic features of "taller than wide" (p < 0.05), while lesions with follicular epithelial hyperplasia were likely to be detected with irregular and/or lobulated margins and very hypoechoic on US (p < 0.05 for both). CONCLUSION: Benign thyroid nodules with histopathological findings such as fibrosis are associated with suspicious US features, which may give inappropriately higher TIRADS stratification.

Interpretable machine learning model integrating clinical and elastosonographic features to detect renal fibrosis in Asian patients with chronic kidney disease.

BACKGROUND: Non-invasive renal fibrosis assessment is critical for tailoring personalized decision-making and managing follow-up in patients with chronic kidney disease (CKD). We aimed to exploit machine learning algorithms using clinical and elastosonographic features to distinguish moderate-severe fibrosis from mild fibrosis among CKD patients. METHODS: A total of 162 patients with CKD who underwent shear wave elastography examinations and renal biopsies at our institution were prospectively enrolled. Four classifiers using machine learning algorithms, including eXtreme Gradient Boosting (XGBoost), Support Vector Machine (SVM), Light Gradient Boosting Machine (LightGBM), and K-Nearest Neighbor (KNN), which integrated elastosonographic features and clinical characteristics, were established to differentiate moderate-severe renal fibrosis from mild forms. The area under the receiver operating characteristic curve (AUC) and average precision were employed to compare the performance of constructed models, and the SHapley Additive exPlanations (SHAP) strategy was used to visualize and interpret the model output. RESULTS: The XGBoost model outperformed the other developed machine learning models, demonstrating optimal diagnostic performance in both the primary (AUC = 0.97, 95% confidence level (CI) 0.94-0.99; average precision = 0.97, 95% CI 0.97-0.98) and five-fold cross-validation (AUC = 0.85, 95% CI 0.73-0.98; average precision = 0.90, 95% CI 0.86-0.93) datasets. The SHAP approach provided visual interpretation for XGBoost, highlighting the features' impact on the diagnostic process, wherein the estimated glomerular filtration rate provided the largest contribution to the model output, followed by the elastic modulus, then renal length, renal resistive index, and hypertension. CONCLUSION: This study proposed an XGBoost model for distinguishing moderate-severe renal fibrosis from mild forms in CKD patients, which could be used to assist clinicians in decision-making and follow-up strategies. Moreover, the SHAP algorithm makes it feasible to visualize and interpret the feature processing and diagnostic processes of the model output.

Association of renal elasticity evaluated by real-time shear wave elastography with renal fibrosis in patients with chronic kidney disease.

OBJECTIVE: Renal fibrosis is a final common pathological hallmark in the progression of chronic kidney disease (CKD). Non-invasive evaluation of renal fibrosis by mapping renal stiffness obtained by shear wave elastography (SWE) may facilitate the clinical therapeutic regimen for CKD patients. METHODS: A cohort of 162 patients diagnosed with CKD, who underwent renal biopsy, was prospectively and consecutively recruited between April 2019 and December 2021. The assessment of renal cortex stiffness was performed using SWE imaging. The patients were classified into different groups based on pathological renal fibrosis (mild group: n = 74; moderate-to-severe group: n = 88). Binary logistic regression model and generalized additive model were conducted to investigate the association of renal elasticity with renal fibrosis. RESULTS: Compared with the mildly impaired group, the moderate-to-severe group showed a significant decline in renal elasticity (P < .001). In the fully adjusted model, each 10 kPa drop in renal elasticity was associated with a 3.5-fold increment in the risk of moderate-to-severe renal fibrosis (fully adjusted odds ratio, 4.54; 95% CI, 2.41-8.57). Particularly, participants in the lowest elasticity group (≤29.92 kPa) had a 20-fold increased chance of moderate-to-severe renal fibrosis than those in the group with highest elasticity (≥37.93 kPa). An inverse linear association was observed between renal elasticity increment and moderate-to-severe renal fibrosis risk. CONCLUSION: There is a negative linear association between increased renal elasticity and moderate-to-severe renal fibrosis risk among CKD patients. Patients with diminished renal stiffness have a higher risk of moderate-to-severe renal fibrosis. ADVANCES IN KNOWLEDGE: CKD patients with reduced renal stiffness have a higher likelihood of moderate-to-severe renal fibrosis.

Integrating shear wave elastography and estimated glomerular filtration rate to enhance diagnostic strategy for renal fibrosis assessment in chronic kidney disease.

Background: Assessing renal fibrosis non-invasively in patients with chronic kidney disease (CKD) remains a considerable clinical challenge. This study aimed to investigate the diagnostic efficacy of different approaches that combine shear wave elastography (SWE) and estimated glomerular filtration rate (eGFR) in distinguishing between mild fibrosis and moderate-to-severe fibrosis in CKD patients. Methods: In this prospective study, 162 patients underwent renal SWE examinations and renal biopsies. Using SWE, the right renal cortex stiffness was measured, and the corresponding SWE value was recorded. Four diagnostic patterns were used to combine eGFR and SWE value: in isolation, in series, in parallel, and in integration. The receiver operating characteristic (ROC) curve was established, and the area under the ROC curve (AUC) was calculated to quantify diagnostic performance. Sensitivity, specificity, and accuracy were computed. Results: The eGFR demonstrated sensitivity of 68.2% and specificity of 83.8%, whereas the SWE value displayed sensitivity of 84.1% and specificity of 62.2%, yielding a similar AUC (78.2% and 77.8%, respectively). Combining in series improved specificity to 97.3%, superior to other diagnostic patterns (all P values <0.01), but compromised sensitivity to 58.0%. When combined in parallel, the sensitivity increased to 94.3%, exceeding any other strategies (all P values <0.05), but the specificity dropped to 48.7%. The integrated strategy, incorporating eGFR with SWE value via the logistic regression algorithm, exhibited an AUC of 85.8%, outperforming all existing approaches (all P values <0.01), with balanced sensitivity, specificity, and accuracy of 86.4%, 74.3%, and 80.9%, respectively. Conclusions: Using an integrated strategy to combine eGFR and SWE value could improve diagnostic performance in distinguishing between mild renal fibrosis and moderate-to-severe renal fibrosis in patients with CKD, thereby helping clinicians perform a more accurate clinical diagnosis.

Autophagy-amplifying nanoparticles evoke immunogenic cell death combined with anti-PD-1/PD-L1 for residual tumors immunotherapy after RFA.

Incomplete radiofrequency ablation (IRFA) triggers mild protective autophagy in residual tumor cells and results in an immunosuppressive microenvironment. This accelerates the recurrence of residual tumors and causes resistance to anti-PD-1/PDL1 therapy, which bringing a great clinical challenge in residual tumors immunotherapy. Mild autophagy activation can promote cancer cell survival while further amplification of autophagy contributes to immunogenic cell death (ICD). To this regard, we constructed active targeting zeolitic imidazolate framework-8 (ZIF-8) nanoparticles (NPs) loaded with STF62247 or both STF62247 and BMS202, namely STF62247@ZIF-8/PEG-FA (SZP) or STF62247-BMS202@ZIF-8/PEG-FA (SBZP) NPs. We found that SZP NPs inhibited proliferation and stimulated apoptosis of residual tumor cells exposed to sublethal heat stress in an autophagy-dependent manner. Further results discovered that SZP NPs could amplify autophagy in residual tumor cells and evoke their ICD, which dramatically boosted the maturation of dendritic cells (DCs). Through vaccination experiments, we found for the first time that vaccination with heat + SZP treatment could efficiently suppress the growth of new tumors and establish long-term immunological memory. Furthermore, SBZP NPs could remarkably promote the ICD of residual tumor cells, obviously activate the anti-tumor immune microenvironment, and significantly inhibit the growth of residual tumors. Thus, amplified autophagy coupled with anti-PD-1/PDL1 therapy is potentially a novel strategy for treating residual tumors after IRFA.

Precise localization of microvascular invasion in hepatocellular carcinoma based on three-dimensional histology-MR image fusion: an ex vivo experimental study.

Background: Microvascular invasion (MVI) is an independent risk factor for postoperative recurrence of hepatocellular carcinoma (HCC). However, MVI cannot be detected by conventional imaging. To localize MVI precisely on magnetic resonance (MR) images, we evaluated the feasibility and accuracy of 3-dimensional (3D) histology-MR image fusion of the liver. Methods: Animal models of VX2 liver tumors were established in 10 New Zealand white rabbits under ultrasonographic guidance. The whole liver lobe containing the VX2 tumor was extracted and divided into 4 specimens, for a total of 40 specimens. MR images were obtained with a T2-weighted sequence for each specimen, and then histological images were obtained by intermittent, serial pathological sections. 3D histology-MR image fusion was performed via landmark registration in 3D Slicer software. We calculated the success rate and registration errors of image fusion, and then we located the MVI on MR images. Regarding influencing factors, we evaluated the uniformity of tissue thickness after sampling and the uniformity of tissue shrinkage after dehydration. Results: The VX2 liver tumor model was successfully established in the 10 rabbits. The incidence of MVI was 80% (8/10). 3D histology-MR image fusion was successfully performed in the 39 specimens, and the success rate was 97.5% (39/40). The average registration error was 0.44±0.15 mm. MVI was detected in 20 of the 39 successfully registered specimens, resulting in a total of 166 MVI lesions. The specific location of all MVI lesions was accurately identified on MR images using 3D histology-MR image fusion. All MVI lesions showed as slightly hyperintense on the high-resolution MR T2-weighted images. The results of the influencing factor assessment showed that the tissue thickness was uniform after sampling (P=0.38), but the rates of the tissue shrinkage was inconsistent after dehydration (P<0.001). Conclusions: 3D histology-MR image fusion of the isolated liver tumor model is feasible and accurate and allows for the successful identification of the specific location of MVI on MR images.

Contrast-enhanced US with Sulfur Hexafluoride and Perfluorobutane: LI-RADS for Diagnosing Hepatocellular Carcinoma.

Background Liver Imaging Reporting and Data System (LI-RADS) was designed for contrast-enhanced US (CEUS) with pure blood pool agents to diagnose hepatocellularfcarcinoma (HCC), such as sulfur hexafluoride (SHF), but Kupffer-cell agents, such as perfluorobutane (PFB), allow additional lesion characterization in the Kupffer phase yet remain unaddressed. Purpose To compare the diagnostic performance of three algorithms for HCC diagnosis: two algorithms based on CEUS LI-RADS version 2017 for both SHF and PFB and a modified algorithm incorporating Kupffer-phase findings for PFB. Materials and Methods This multicenter prospective study enrolled high-risk patients for HCC from June 2021 to December 2021. Each participant underwent same-day SHF-enhanced US followed by PFB-enhanced US. Each liver observation was assigned three LI-RADS categories according to each algorithm: LI-RADS SHF, LI-RADS PFB, and modified PFB. For modified PFB, observations at least 10 mm with nonrim arterial phase hyperenhancement were upgraded LR-4 to LR-5 if there was no washout with a Kupffer defect and were reassigned LR-M to LR-5 if there was early washout with mild Kupffer defect. The reference standard was pathologic confirmation or composite (typical CT or MRI features, or 1-year size stability and/or reduction). Diagnostic metrics of LR-5 for HCC using the three algorithms were calculated and compared using the McNemar test. Results Overall, 375 patients (mean age, 56 years ± 11 [SD]; 318 male patients, 57 female patients) with 424 observations (345 HCCs, 40 non-HCC malignancies, 39 benign lesions) were enrolled. PFB and SHF both using LI-RADS showed no significant difference in sensitivity (60% vs 58%; P = .41) and specificity (96% vs 95%; P > .99). The modified algorithm with PFB had increased sensitivity (80% vs 58%; P < .001) and a nonsignificant decrease in specificity (92% vs 95%; P = .73) compared with LI-RADS SHF. Conclusion Based on CEUS LI-RADS version 2017, both SHF and PFB achieved high specificity and relatively low sensitivity for HCC diagnosis. When incorporating Kupffer-phase findings, PFB had higher sensitivity without loss of specificity. Chinese Clinical Trial Registry no. ChiCTR2100047035 © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Kim in this issue.

Nomogram Analysis Based on Clinical and Sonographic Characteristics for the Assessment of Postpartum Stress Urinary Incontinence.

OBJECTIVES: We aimed to develop and validate a nomogram integrating clinical and sonographic characteristics for the individualized SUI risk evaluation in the early postpartum stage. METHODS: This was a prospective cross-sectional study. From June 2020 to September 2022, singleton primiparas who underwent TPUS examination at 6-8 weeks postpartum were recruited. They were divided into the training and validation cohorts at a ratio of 8:2 according to the temporal split. All subjects were interviewed before TPUS examination. Univariate and multivariate logistic analyses were performed to develop three models: the clinical, sonographic, and combined models. The ROC curve was plotted to evaluate model discrimination ability. Finally, the combined model was selected to establish the nomogram. The nomogram's discrimination, calibration, and clinical usefulness were evaluated in the training and validation cohorts. RESULTS: The performance of the combined model was better than that of the clinical and sonographic models. Six predictors (BMI, delivery mode, lateral episiotomy, SUI during pregnancy, cystocele, and bladder neck funneling) remained in the combined model. The nomogram based on the combined model had good discrimination with AUCs of 0.848 (95% CI: 0.796-0.900) and 0.872 (95% CI: 0.789-0.955) in the training and validation cohorts, respectively, and the calibration curve showed good efficiency in assessing postpartum SUI. Decision curve analysis showed that the nomogram was clinically useful. CONCLUSIONS: The nomogram based on clinical and sonographic characteristics showed good efficiency in assessing postpartum SUI risk and can be a convenient and reliable tool for individual SUI risk assessment.

Ultrasound-based radiomics analysis in the assessment of renal fibrosis in patients with chronic kidney disease.

PURPOSE: Assessment of renal fibrosis non-invasively in chronic kidney disease (CKD) patients is still a clinical challenge. In this study, we aimed to establish a radiomics model integrating radiomics features derived from ultrasound (US) images with clinical characteristics for the assessment of renal fibrosis severity in CKD patients. METHODS: A total of 160 patients with CKD who underwent kidney biopsy and renal US examination were prospectively enrolled. Patients were classified into the mild or moderate-severe fibrosis group based on pathology results. Radiomics features were extracted from the US images, and a radiomics signature was constructed using the maximum relevance minimum redundancy (mRMR) and least absolute shrinkage and selection operator (LASSO) regression algorithms. Multivariable logistic regression was employed to construct the radiomics model, which incorporated the radiomics signature and the selected clinical variables. The established model was evaluated for discrimination, calibration, and clinical utility in the derivation cohort and internal cross-validation (CV) analysis, respectively. RESULTS: The radiomics signature, consisting of nine identified fibrosis-related features, achieved moderate discriminatory ability with an area under the receiver operating characteristic curve (AUC) of 0.72 (95% confidence interval (CI) 0.64-0.79). By combining the radiomics signature with significant clinical risk factors, the radiomics model showed satisfactory discrimination performance, yielding an AUC of 0.85 (95% CI 0.79-0.91) in the derivation cohort and a mean AUC of 0.84 (95% CI 0.77-0.92) in the internal CV analysis. It also demonstrated fine accuracy via the calibration curve. Furthermore, the decision curve analysis indicated that the model was clinically useful. CONCLUSION: The proposed radiomics model showed favorable performance in determining the individualized risk of moderate-severe renal fibrosis in patients with CKD, which may facilitate more effective clinical decision-making.

Using elastography-based multilayer perceptron model to evaluate renal fibrosis in chronic kidney disease.

BACKGROUND: Given its progressive deterioration in the clinical course, noninvasive assessment and risk stratification for the severity of renal fibrosis in chronic kidney disease (CKD) are required. We aimed to develop and validate an end-to-end multilayer perceptron (MLP) model for assessing renal fibrosis in CKD patients based on real-time two-dimensional shear wave elastography (2D-SWE) and clinical variables. METHODS: From April 2019 to December 2021, a total of 162 patients with CKD who underwent a kidney biopsy and 2D-SWE examination were included in this single-center, cross-sectional, and prospective clinical study. 2D-SWE was performed to measure the right renal cortex stiffness, and the corresponding elastic values were recorded. Patients were categorized into two groups according to their histopathological results: mild and moderate-severe renal fibrosis. The patients were randomly divided into a training cohort (n = 114) or a test cohort (n = 48). The MLP classifier using a machine learning algorithm was used to construct a diagnostic model incorporating elastic values with clinical features. Discrimination, calibration, and clinical utility were used to appraise the performance of the established MLP model in the training and test sets, respectively. RESULTS: The developed MLP model demonstrated good calibration and discrimination in both the training [area under the receiver operating characteristic curve (AUC) = 0.93; 95% confidence interval (CI) = 0.88 to 0.98] and test cohorts [AUC = 0.86; 95% CI = 0.75 to 0.97]. A decision curve analysis and a clinical impact curve also showed that the MLP model had a positive clinical impact and relatively few negative effects. CONCLUSIONS: The proposed MLP model exhibited the satisfactory performance in identifying the individualized risk of moderate-severe renal fibrosis in patients with CKD, which is potentially helpful for clinical management and treatment decision-making.

Assessment of Renal Fibrosis in Patients With Chronic Kidney Disease Using Shear Wave Elastography and Clinical Features: A Random Forest Approach.

OBJECTIVE: Renal fibrosis is the common pathological hallmark of chronic kidney disease (CKD) progression. In this study, a random forest (RF) classifier based on 2-D shear wave elastography (SWE) and clinical features for the differential severity of renal fibrosis in patients with CKD is proposed. METHODS: A total of 162 patients diagnosed with CKD who underwent 2-D SWE and renal biopsy were prospectively enrolled from April 2019 to December 2021 and then randomized into training (n = 114) and validation (n = 48) cohorts at a ratio of 7:3. The least absolute shrinkage and selection operator (LASSO) regression and recursive feature elimination for support vector machines (SVM-RFE) algorithm were employed to select renal fibrosis-related features from clinical information and elastosonographic findings. An RF model was subsequently constructed using the aforementioned informative parameters in the training cohort and evaluated in terms of discrimination, calibration and clinical utility in both cohorts. RESULTS: The LASSO and SVM-RFE analyses revealed that age, sex, blood urea nitrogen, renal resistive index, hypertension and the 2D-SWE value were independent risk variables associated with renal fibrosis severity. The established RF model incorporating these six variables exhibited fine discrimination in both the derivation (area under the curve [AUC]: 0.84, 95% confidence interval [CI]: 0.76-0.91) and validation (AUC: 0.88, 95% CI: 0.77-0.98) cohorts. Moreover, the calibration curve revealed satisfactory predictive accuracy, and the decision curve analysis revealed a significant clinical net benefit. CONCLUSION: The developed RF model, via a combination of the 2-D SWE value and clinical information, indicated satisfactory diagnostic performance and clinical practicality toward differentiating moderate-severe from mild renal fibrosis, which may provide critical insight into risk stratification for patients with CKD.

A nomogram based on shear wave elastography for assessment of renal fibrosis in patients with chronic kidney disease.

BACKGROUND: Non-invasive evaluation of renal fibrosis is still challenging. This study aimed to establish a nomogram based on shear wave elastography (SWE) and clinical features for the assessment of the severity of renal fibrosis in patients with chronic kidney disease (CKD). METHODS: One hundred and sixty-two patients with CKD who underwent kidney biopsy and SWE examination were prospectively enrolled between April 2019 and December 2021. Patients were classified into mildly or moderately-severely impaired group based on pathology results. All patients were randomly divided into a training (n = 113) or validation cohort (n = 49). Least absolute shrinkage and selection operator (LASSO) algorithm was used for data dimensionality reduction and feature selection. Then, a diagnostic nomogram incorporating the selected features was constructed using multivariable logistic regression analysis. Nomogram performance was evaluated for discrimination, calibration, and clinical utility in training and validation cohorts. RESULTS: The established SWE nomogram, which integrated SWE value, hypertension, and estimated glomerular filtration rate, showed fine calibration and discrimination in both training (area under the receiver operator characteristic curve (AUC) = 0.94; 95% confidence interval (CI) 0.89-0.98) and validation cohorts (AUC = 0.84; 95% CI 0.71-0.96). Significant improvement in net reclassification and integrated discrimination indicated that the SWE value is a valuable biomarker to assess moderate-severe renal impairment. Furthermore, decision curve analysis revealed that the SWE nomogram has clinical value. CONCLUSION: The proposed SWE nomogram showed favorable performance in determining individualized risk of moderate-severe renal pathological impairment in patients with CKD, which will help to facilitate clinical decision-making.

A Positron Emission Tomography Tracer Targeting the S2 Subunit of SARS-CoV-2 in Extrapulmonary Infections.

Tracking the pathogen of coronavirus disease 2019 (COVID-19) in live subjects may help estimate the spatiotemporal distribution of SARS-CoV-2 infection in vivo. This study developed a positron emission tomography (PET) tracer of the S2 subunit of spike (S) protein for imaging SARS-CoV-2. A pan-coronavirus inhibitor, EK1 peptide, was synthesized and radiolabeled with copper-64 after being conjugated with 1,4,7-triazacyclononane-1,4,7-triyl-triacetic acid (NOTA). The in vitro stability tests indicated that [64Cu]Cu-NOTA-EK1 was stable up to 24 h both in saline and in human serum. The binding assay showed that [64Cu]Cu-NOTA-EK1 has a nanomolar affinity (Ki = 3.94 ± 0.51 nM) with the S-protein of SARS-CoV-2. The cell uptake evaluation used HEK293T/S+ and HEK293T/S- cell lines that showed that the tracer has a high affinity with the S-protein on the cellular level. For the in vivo study, we tested [64Cu]Cu-NOTA-EK1 in HEK293T/S+ cell xenograft-bearing mice (n = 3) and pseudovirus of SARS-CoV-2-infected HEK293T/ACE2 cell bearing mice (n = 3). The best radioactive xenograft-to-muscle ratio (X/Nxenograft 8.04 ± 0.99, X/Npseudovirus 6.47 ± 0.71) was most evident 4 h postinjection. Finally, PET imaging in the surrogate mouse model of beta-coronavirus, mouse hepatic virus-A59 infection in C57BL/6 J mice showed significantly enhanced accumulation in the liver than in the uninfected mice (1.626 ± 0.136 vs 0.871 ± 0.086 %ID/g, n = 3, P < 0.05) at 4 h postinjection. In conclusion, our experimental results demonstrate that [64Cu]Cu-NOTA-EK1 is a potential molecular imaging probe for tracking SARS-CoV-2 in extrapulmonary infections in living subjects.

Nanodrugs Incorporating LDHA siRNA Inhibit M2-like Polarization of TAMs and Amplify Autophagy to Assist Oxaliplatin Chemotherapy against Colorectal Cancer.

Oxaliplatin (OXA) is a first-line chemotherapeutic agent for treating colorectal cancer (CC). However, the chemotherapeutic effect of OXA on CC is limited by the M2-like polarization of tumor-associated macrophages (TAMs) in the tumor microenvironment (TME) and protective autophagy of tumor cells. Here, a cationic polymer APEG-PAsp(PEI) (PAPEI) was prepared to deliver small-interfering RNA (siRNA) to silence the lactate dehydrogenase A (LDHA) gene (LDHA-siRNA) to enhance the chemotherapeutic effect of OXA on CC. The PAPEI/LDHA-siRNA nanocomplex effectively silenced the LDHA gene to inhibit the secretion of lactic acid from tumor cells, resulting in inhibition of the M2-like polarization of TAMs. In addition, the nanocomplex also amplified OXA-induced autophagy and transformed protective autophagy into autophagic death. Consequently, the combination treatment of OXA and PAPEI/LDHA-siRNA showed a dramatically increased chemotherapeutic effect on CC compared with the OXA-alone treatment, which also suggested its attractive potential for treating CC-like immune "cold" tumors.

Radiomics for the Preoperative Evaluation of Microvascular Invasion in Hepatocellular Carcinoma: A Meta-Analysis.

Background: Microvascular invasion (MVI) is an independent risk factor for postoperative recurrence of hepatocellular carcinoma (HCC). To perform a meta-analysis to investigate the diagnostic performance of radiomics for the preoperative evaluation of MVI in HCC and the effect of potential factors. Materials and Methods: A systematic literature search was performed in PubMed, Embase, and the Cochrane Library for studies focusing on the preoperative evaluation of MVI in HCC with radiomics methods. Data extraction and quality assessment of the retrieved studies were performed. Statistical analysis included data pooling, heterogeneity testing and forest plot construction. Meta-regression and subgroup analyses were performed to reveal the effect of potential explanatory factors [design, combination of clinical factors, imaging modality, number of participants, and Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) applicability risk] on the diagnostic performance. Results: Twenty-two studies with 4,129 patients focusing on radiomics for the preoperative prediction of MVI in HCC were included. The pooled sensitivity, specificity and area under the receiver operating characteristic curve (AUC) were 84% (95% CI: 81, 87), 83% (95% CI: 78, 87) and 0.90 (95% CI: 0.87, 0.92). Substantial heterogeneity was observed among the studies (I²=94%, 95% CI: 88, 99). Meta-regression showed that all investigative covariates contributed to the heterogeneity in the sensitivity analysis (P < 0.05). Combined clinical factors, MRI, CT and number of participants contributed to the heterogeneity in the specificity analysis (P < 0.05). Subgroup analysis showed that the pooled sensitivity, specificity and AUC estimates were similar among studies with CT or MRI. Conclusion: Radiomics is a promising noninvasive method that has high preoperative diagnostic performance for MVI status. Radiomics based on CT and MRI had a comparable predictive performance for MVI in HCC. Prospective, large-scale and multicenter studies with radiomics methods will improve the diagnostic power for MVI in the future. Systematic Review Registration: https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=259363, identifier CRD42021259363.

Augmented EPR effect post IRFA to enhance the therapeutic efficacy of arsenic loaded ZIF-8 nanoparticles on residual HCC progression.

BACKGROUND: Insufficient radiofrequency ablation (IRFA) can promote the local recurrence and distal metastasis of residual hepatocellular carcinoma (HCC), which makes clinical treatment extremely challenging. In this study, the malignant transition of residual tumors after IRFA was explored. Then, arsenic-loaded zeolitic imidazolate framework-8 nanoparticles (As@ZIF-8 NPs) were constructed, and their therapeutic effect on residual tumors was studied. RESULTS: Our data showed that IRFA can dramatically promote the proliferation, induce the metastasis, activate the epithelial-mesenchymal transition (EMT) and accelerate the angiogenesis of residual tumors. Interestingly, we found, for the first time, that extensive angiogenesis after IRFA can augment the enhanced permeability and retention (EPR) effect and enhance the enrichment of ZIF-8 nanocarriers in residual tumors. Encouraged by this unique finding, we successfully prepared As@ZIF-8 NPs with good biocompatibility and confirmed that they were more effective than free arsenic trioxide (ATO) in sublethal heat-induced cell proliferation suppression, apoptosis induction, cell migration and invasion inhibition, and EMT reversal in vitro. Furthermore, compared with free ATO, As@ZIF-8 NPs exhibited remarkably increased therapeutic effects by repressing residual tumor growth and metastasis in vivo. CONCLUSIONS: This work provides a new paradigm for the treatment of residual HCC after IRFA.

Does shear wave elastography for medullary thyroid carcinoma predict lateral cervical lymph node metastasis?

PURPOSE: To assess whether shear wave elastography (SWE) for medullary thyroid carcinoma (MTC) can independently predict lateral cervical lymph node metastasis (LNM). METHOD: Patients with MTC who were treated via primary surgery between January 2015 and May 2020 and who had undergone preoperative SWE and ultrasound (US) examinations in the Harbin Medical University Cancer Hospital were retrospectively studied. The relationships between lymphatic status and the clinicopathological and imaging characteristics were evaluated. Afterwards, associations between lateral cervical LNM and SWE parameters, as well as sex, age, invasive size, extrathyroidal extension (ETE), preoperative calcitonin levels, and US features were assessed by using multivariable logistic regressions. RESULTS: A total of 76 patients (31 men and 45 women, 48.1 ± 11.8 years) were evaluated. The following factors demonstrated significant associations with lateral cervical LNM: the male sex (P = 0.015), an age ≤ 35 years (P = 0.049), an invasive size > 1.0 cm (P = 0.028), ETE (P = 0.005), a preoperative calcitonin level > 60 pg/ml (P < 0.001), irregular shape on the US (P = 0.001), the presence of a non-circumscribed margin on the US (P = 0.009), an Emax > 66 kPa (P < 0.001), an Emean > 37.5 kPa (P < 0.001), and an ER > 1.65 (P = 0.002). In the multivariable analysis, an age ≤ 35 years (P = 0.049), a preoperative calcitonin level > 60 pg/ml (P = 0.004), an irregular shape on the US (P = 0.036), and an Emax > 66 kPa (P = 0.011) maintained independent significance. CONCLUSION: Emax was demonstrated to be an independent predictor for lateral cervical LNM of MTC. SWE may serve as a noninvasive method of preoperative lateral cervical LNM risk assessment for MTC.

Evaluation of renal fibrosis in patients with chronic kidney disease by shear wave elastography: a comparative analysis with pathological findings.

PURPOSE: To explore the elastic values obtained by shear wave elastography (SWE) in assessing renal fibrosis in chronic kidney disease (CKD). METHODS: One hundred and twenty-four patients with CKD who underwent renal biopsy were prospectively enrolled between April 2019 and June 2021. SWE was performed to measure the renal cortex stiffness, presented as SWE parameters, including the minimum, mean, and maximum elasticity (namely Emin, Emean, and Emax). Then, the patients with different kidney pathological impairment (mild, moderate, and severe groups) were compared in SWE elasticity and the discriminative capacity was also analyzed. RESULTS: For the pathology impaired grade, SWE parameter was significantly reduced in the moderately and severely impaired group than the mild one. Emax parameter achieved the best discriminative ability toward differentiating moderate-severe impairment from mild one, yielding an area under the curve (AUC) of 0.764 (95%CI: 0.681-0.848). Regarding interstitial fibrosis/tubular atrophy and global glomerular sclerosis, the Emax values were significantly reduced across the group of patients with moderate grade compared to those with mild grade. Patients in severe group were also with reduced elastic value than those in mild one, while the difference was non-significant in interstitial fibrosis/tubular atrophy but a borderline statistical significance was achieved in global glomerular sclerosis. For grade of vessel wall thickening, patients in moderate (33.04 ± 9.86 kPa, P = 0.009) and severe (31.42 ± 9.16 kPa, P < 0.001) group were with significantly lower elastic value compared with those in the mild one (39.58 ± 9.67 kPa). The SWE parameter was linearly reduced as grade of vessel wall thickening elevated (P for trend: < 0.001). CONCLUSION: SWE derived elastic values reduced as pathology grade of renal fibrosis or grade of vessel wall thickening progresses in patients with CKD, which may be attributed to renal hypo-perfusion rather than tubulo-interstitial fibrosis progression.