Dynamic Contrast-Enhanced MRI Assessing Antifibrotic Therapeutic Effects of Pancreatic Fibrosis with Curcumin - An Experimental Study at 11.7 T.

RATIONALE AND OBJECTIVES: Pancreatic fibrosis is the hallmark of chronic pancreatitis (CP), which is associated with microcirculatory disturbance. Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) can assess the perfusion and permeability of the pancreas by providing information about microcirculation. We hypothesize that DCE-MRI parameters can be utilized to assess pancreatic fibrosis and may furthermore provide an opportunity to evaluate response to antifibrotic treatment with curcumin. Our study was to evaluate the feasibility of quantitative DCE-MRI in assessing pancreatic fibrosis and the antifibrotic effect of curcumin in a rat model of CP. MATERIALS AND METHODS: Pancreatic fibrosis was induced by injecting dibutyltin dichloride (DBTC). Seventy rats were randomized to five groups: the control group (n = 10); DBTC for 2 weeks (n = 15); DBTC for 4 weeks (n = 15); DBTC + curcumin for 2 weeks (n = 15); DBTC + curcumin for 4 weeks (n = 15). DCE-MRI was performed at an 11.7 T MR scanner. DCE-MRI quantitative parameters (Ktrans, Ve, and Vp) were derived from an extended Tofts model. Fibrosis content and DCE-MRI parameters were compared among the above groups (one-way analysis of variance). The correlations between DCE-MRI parameters and pancreatic fibrosis content as well as the expression of α-SMA were computed by Spearman correlation coefficients. RESULTS: Fifty-three rats survived and underwent MR imaging. Ktrans in rats 4 weeks after DBTC injection was significantly lower than DBTC 2 weeks rats and control rats (0.30 ± 0.06 min vs 0.49 ± 0.09 vs 0.62 ± 0.09, respectively). Vp in DBTC 4 weeks rats was also significantly lower than control rats (0.048 ± 0.010 min-1 vs 0.065 ± 0.011 min-1, respectively). Ktrans and Vp significantly correlated with fibrosis content of pancreas (r = -0.619 and -0.450, all P < 0.001), and the expression of α-SMA (r = -0.688 and -0.402, all P < 0.01). Ktrans and Vp in rats with daily curcumin treatment for 4 weeks were significantly higher than DBTC 4 weeks rats (Ktrans, 0.51 ± 0.09 vs 0.30 ± 0.06; Vp, 0.064 ± 0.015 vs 0.048 ± 0.010). CONCLUSION: DCE-MRI parameters (Ktrans and Vp) have the potential to noninvasively assess pancreatic fibrosis and the antifibrotic treatment response of curcumin.

Use of Ambroxol as Therapy for Gaucher Disease.

Importance: Ambroxol was identified as an enhancer of stability and residual activity of several misfolded glucocerebrosidase variants in 2009. Objectives: To assess hematologic and visceral outcomes, biomarker changes, and safety of ambroxol therapy for patients with Gaucher disease (GD) without disease-specific treatment. Design, Setting, and Participants: Patients with GD who could not afford enzyme replacement therapy were enrolled and received oral ambroxol from May 6, 2015, to November 9, 2022, at Xinhua Hospital, affiliated with Shanghai Jiao Tong University School of Medicine, Shanghai, China. Thirty-two patients with GD (29 with GD type 1, 2 with GD type 3, and 1 with GD intermediate types 2-3) were enrolled. Of those, 28 patients were followed up for longer than 6 months; 4 were excluded due to loss of follow-up. Data analyses were performed from May 2015 to November 2022. Intervention: An escalating dose of oral ambroxol (mean [SD] dose, 12.7 [3.9] mg/kg/d). Main Outcomes and Measures: Patients with GD receiving ambroxol were followed up in a genetic metabolism center. Biomarkers of chitotriosidase activity and glucosylsphingosine level, liver and spleen volumes, and hematologic parameters were measured at baseline and various time points throughout the ambroxol treatment. Results: A total of 28 patients (mean [SD] age, 16.9 [15.3] years; 15 male patients [53.6%]) received ambroxol for a mean (SD) duration of 2.6 (1.7) years. Two patients with severe symptoms at baseline experienced deterioration of hematologic parameters and biomarkers and were deemed nonresponders; clinical response was observed in the other 26 patients. After 2.6 years of ambroxol treatment, the mean (SD) hemoglobin concentration improved from 10.4 (1.7) to 11.9 (1.7) g/dL (mean [SD], 1.6 [1.7] g/dL; 95% CI, 0.8-2.3 g/dL; P < .001), and the mean (SD) platelet count improved from 69 (25) to 78 (30) × 103/µL (mean [SD], 9 [22] × 103/µL; 95% CI, -2 to 19 × 103/µL; P = .09). The mean (SD) spleen volume decreased from 17.47 (7.18) to 12.31 (4.71) multiples of normal (MN) (mean [SD], -5.16 [5.44] MN; 95% CI, -10.19 to -0.13; P = .04), and the mean (SD) liver volume decreased from 1.90 (0.44) to 1.50 (0.53) MN (mean [SD], -0.39 [0.42] MN; 95% CI, -0.75 to -0.04; P = .03). Biomarker median percentage changes from baseline were -43.1% for chitotriosidase activity (from 14 598 [range, 3849-29 628] to 8312 [range, 1831-16 842] nmol/mL/h; z = -3.413; P = .001) and -34.1% for glucosylsphingosine level (from 251.3 [range, 73.6-944.2] to 165.7 [range, 21.3-764.8] ng/mL; z = -2.756; P = .006). Patients were divided into subgroups according to age when initiating treatment; those who received treatment at a younger age (mean [SD] age, 6.3 [2.7] years) experienced more rapid improvements: hemoglobin concentration increased by 16.5% (from 10.3 [1.5] to 12.0 [1.5] g/dL; mean [SD] change, 1.6 [1.6] g/dL; 95% CI, 0.7-2.5 g/dL; P = .002), and platelet count increased by 12.0% (from 75 [24] to 84 [33] × 103/µL; mean [SD] change, 9 [26] × 103/µL; 95% CI, -5 to 24 × 103/µL; P = .17); whereas chitotriosidase activity decreased by 64.0% (from 15 710 [range, 4092-28 422] to 5658 [range, 1146-16 843] nmol/mL/h; z = -2.803; P = .005), and glucosylsphingosine level decreased by 47.3% (from 248.5 [range, 122.8-674.9] to 131.0 [range, 41.1-448.5] ng/mL; z = -2.385; P = .02). Three of the 28 patients experienced mild and transient adverse events. Conclusions and Relevance: In this case series of ambroxol repurposing among patients with GD, long-term treatment with ambroxol was safe and associated with patient improvement. Improvements in hematologic parameters, visceral volumes, and plasma biomarkers were larger among patients with relatively mild symptoms of GD and patients who received initial treatment at younger ages.

Non-invasive detection and differentiation of apoptotic and necroptotic cell death in vitro.

Cell death plays an important role in the development of multicellular organisms and the maintenance of adult homeostasis. However, traditional methods of cell death detection can damage cells and tissues. Here, we report the use of near-infrared (NIR) spectroscopy for non-invasively distinguishing between cell death types. We found a difference between normal, apoptotic, and necroptotic mouse dermal fibroblast cells in the wavelength range of 1100-1700 nm. In particular, the differences in scattering of NIR light between cells at different states are enough to be distinguished. This feature was exploited by measuring the attenuation coefficient (δµ), which specifies the ease at which light can pass through a substance. The results showed that δµ can be used to distinguish between different types of cell death. Therefore, this study proposes a new, non-invasive, and fast method to differentiate cell death types without the additional fluorescent labeling.

Elevated serum uric acid is associated with the risk of advanced staging and vascular involvement in patients with hepatoblastoma: a 14-year retrospective study.

Background: Uric acid is the end product of the purine metabolism pathway, and has been linked to cancer risks and prognosis, but its relationship with hepatoblastoma (HB) remains unclear. This study aims to investigate the association between serum uric acid (SUA) and the advanced tumor staging and unfavorable extra-parenchymal tumor characteristics in patients with HB. Methods: This study enrolled pediatric patients from Xinhua Hospital between 2007 to 2021. A total of 101 participants with newly diagnosed HB were recruited in the study. PRETreatment EXTent of disease (PRETEXT)/PostTreatment Extent of disease (POSTTEXT) staging were evaluated at diagnosis and following neoadjuvant chemotherapy (NAC). Adjusted smoothing spline plots, subgroup analysis and multivariate logistic regression analysis were conducted to estimate the association of different levels of SUA with the advanced tumor staging and present annotation factors. Results: In accordance with SUA tertiles, those patients with higher pretreatment SUA levels showed increased percentages of PRETEXT group IV, vessel involvement and multifocality of tumors. After fully adjustment with the confounding factors, SUA was positively associated with advanced PRETEXT stage IV (OR: 1.72, 95%CI 1.15-2.57, p=0.0080), as well as vascular invasion (OR: 1.29, 95%CI 1.01-1.64, p=0.0396). Compared with the lowest SUA concentration tertile, the highest tertile were independently associated with vessel involvement of tumor in all of the adjusted models. Following NAC, SUA levels were significantly reduced in response to the downstaging of tumors. SUA remained positively associated with advanced POSTTEXT staging and vessel involvement in adjusted models. Patients with highest tertile of posttreatment SUA showed worse 5-year EFS and OS. Conclusion: Elevated SUA were associated with an increased occurrence of advanced PRETEXT/POSTTEXT staging and unfavorable vessel involvement at diagnosis and following NAC in patients with HB. High posttreatment SUA reflected poor tumor responses to NAC. This study linked SUA, a non-invasive laboratory test, with tumor staging and risk prediction for HB.

Sensing and Stimulation Applications of Carbon Nanomaterials in Implantable Brain-Computer Interface.

Implantable brain-computer interfaces (BCIs) are crucial tools for translating basic neuroscience concepts into clinical disease diagnosis and therapy. Among the various components of the technological chain that increases the sensing and stimulation functions of implanted BCI, the interface materials play a critical role. Carbon nanomaterials, with their superior electrical, structural, chemical, and biological capabilities, have become increasingly popular in this field. They have contributed significantly to advancing BCIs by improving the sensor signal quality of electrical and chemical signals, enhancing the impedance and stability of stimulating electrodes, and precisely modulating neural function or inhibiting inflammatory responses through drug release. This comprehensive review provides an overview of carbon nanomaterials' contributions to the field of BCI and discusses their potential applications. The topic is broadened to include the use of such materials in the field of bioelectronic interfaces, as well as the potential challenges that may arise in future implantable BCI research and development. By exploring these issues, this review aims to provide insight into the exciting developments and opportunities that lie ahead in this rapidly evolving field.

MRI Radiomics Signature of Pediatric Medulloblastoma Improves Risk Stratification Beyond Clinical and Conventional MR Imaging Features.

BACKGROUND: Prognostic evaluation is important for personalized treatment in children with medulloblastoma (MB). Limited data are available for risk stratification using a radiomics-based model. PURPOSE: To evaluate the incremental value of an MRI radiomics signature in stratifying the risk of pediatric MB in terms of overall survival (OS). STUDY TYPE: Retrospective. SUBJECTS: A total of 111 children (mean age 5.82 years) with pathologically confirmed MB divided into training and validation cohorts (77 and 34 children, respectively). FIELD STRENGTH/SEQUENCE: A 3 T, contrast-enhanced T1-weighted imaging with inversion recovery. ASSESSMENT: The study endpoint was OS defined as the time between the preoperative MRI study and death or last follow-up. The radiomics signature model and a clinical-MRI model were developed for personalized OS prediction. An integrative model, which combined the radiomics signature and clinical-MRI features, was also built using multivariable Cox regression model. The performance of the three models was evaluated with the C-index. The performance of integrative model was assessed by calibration curve and decision curve analysis (DCA). STATISTICAL TESTS: Independent T-test, Mann-Whitney U test, Fisher's exact tests or chi-square test, logistic regression analysis, Kaplan-Meier survival analysis, C-index, intraclass correlation coefficients (ICC). P < 0.05 was considered statistically significant. RESULTS: The media OS was 2.83 years (3.87 ± 1.85 years). Two clinical and one conventional MR imaging features (remnant, adjuvant treatment, and peritumoral edema) were selected for clinical-MRI model building. The integrative model evaluated OS (C-index 0.823) better than either the radiomics signature (C-index 0.702) or the clinical-MRI model (C-index 0.771). And it also showed good performance in the validation cohort (C-indices: 0.786, 0.756, 0.721), which was validated by the good calibration (P > 0.05) and more benefit. DATA CONCLUSIONS: This study demonstrated that the integrative model, which combined radiomics signature, clinical, and conventional MRI features, showed best performance in OS evaluation for children with MB. The radiomics signature may confer incremental value over clinical-MRI features. EVIDENCE LEVEL: 3. TECHNICAL EFFICACY: Stage 2.

Non-Farm Employment, Farmland Renting and Farming Ability: Evidence from China.

In the process of China's urbanization, non-farm employment and farmland rental activity are closely correlated. Using data from a survey on rural households in three Chinese provinces, this article examines the relationship between farmland renting activity and non-farm employment with simultaneous equations that consider the farming ability of farmers. Our results are fourfold. First, farmland renting-out promotes non-farm employment, while farmland renting-in reduces non-farm employment. Second, non-farm employment encourages farmland renting-out and decreases farmland renting-in. Third, farming ability increases farmland renting-in but decreases non-farm employment. Fourth, non-farm employment decreases the farming ability of farmers. Based on our empirical findings, we would suggest that the Chinese government further reforms its land system in rural areas, which could better facilitate land-use-right transfer and promote farmland rental market.

A Deep Learning Model Based on MRI and Clinical Factors Facilitates Noninvasive Evaluation of KRAS Mutation in Rectal Cancer.

BACKGROUND: Recent studies showed the potential of MRI-based deep learning (DL) for assessing treatment response in rectal cancer, but the role of MRI-based DL in evaluating Kirsten rat sarcoma viral oncogene homologue (KRAS) mutation remains unclear. PURPOSE: To develop a DL method based on T2-weighted imaging (T2WI) and clinical factors for noninvasively evaluating KRAS mutation in rectal cancer. STUDY TYPE: Retrospective. SUBJECTS: A total of 376 patients (108 women [28.7%]) with histopathology-confirmed rectal adenocarcinoma and KRAS mutation status. FIELD STRENGTH/SEQUENCE: A 3 T, turbo spin echo T2WI and single-shot echo-planar diffusion-weighted imaging (b = 0, 1000 sec/mm2 ). ASSESSMENT: A clinical model was constructed with clinical factors (age, gender, carcinoembryonic antigen level, and carbohydrate antigen 199 level) and MRI features (tumor length, tumor location, tumor stage, lymph node stage, and extramural vascular invasion), and two DL models based on modified MobileNetV2 architecture were evaluated for diagnosing KRAS mutation based on T2WI alone (image model) or both T2WI and clinical factors (combined model). The clinical usefulness of these models was evaluated through calibration analysis and decision curve analysis (DCA). STATISTICAL TESTS: Mann-Whitney U test, Chi-squared test, Fisher's exact test, logistic regression analysis, receiver operating characteristic curve (ROC), Delong's test, Hosmer-Lemeshow test, interclass correlation coefficients, and Fleiss kappa coefficients (P < 0.05 was considered statistically significant). RESULTS: All the nine clinical-MRI characteristics were included for clinical model development. The clinical model, image model, and combined model in the testing cohort demonstrated good calibration and achieved areas under the curve (AUCs) of 0.668, 0.765, and 0.841, respectively. The combined model showed improved performance compared to the clinical model and image model in two cohorts. DCA confirmed the higher net benefit of the combined model than the other two models when the threshold probability is between 0.05 and 0.85. DATA CONCLUSION: The proposed combined DL model incorporating T2WI and clinical factors may show good diagnostic performance. Thus, it could potentially serve as a supplementary approach for noninvasively evaluating KRAS mutation in rectal cancer. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 2.

Research and Application Validation of a Feature Wavelength Selection Method Based on Acousto-Optic Tunable Filter (AOTF) and Automatic Machine Learning (AutoML).

Near-infrared spectroscopy has been widely applied in various fields such as food analysis and agricultural testing. However, the conventional method of scanning the full spectrum of the sample and then invoking the model to analyze and predict results has a large amount of collected data, redundant information, slow acquisition speed, and high model complexity. This paper proposes a feature wavelength selection approach based on acousto-optical tunable filter (AOTF) spectroscopy and automatic machine learning (AutoML). Based on the programmable selection of sub nm center wavelengths achieved by the AOTF, it is capable of rapid acquisition of combinations of feature wavelengths of samples selected using AutoML algorithms, enabling the rapid output of target substance detection results in the field. The experimental setup was designed and application validation experiments were carried out to verify that the method could significantly reduce the number of NIR sampling points, increase the sampling speed, and improve the accuracy and predictability of NIR data models while simplifying the modelling process and broadening the application scenarios.

MRI-based radiomics signature and clinical factor for predicting H3K27M mutation in pediatric high-grade gliomas located in the midline of the brain.

OBJECTIVE: To develop a nomogram based on MRI radiomics and clinical features for preoperatively predicting H3K27M mutation in pediatric high-grade gliomas (pHGGs) with a midline location of the brain. METHODS: The institutional database was reviewed to identify patients with pHGGs with a midline location of the brain who underwent tumor biopsy with preoperative MRI scans between June 2016 and June 2021. A total of 107 patients with pHGGs, including 79 patients with H3K27M mutation, were consecutively included and randomly divided into training and test sets. Radiomics features were extracted from fluid-attenuated inversion recovery (FLAIR), diffusion-weighted (DW) and post-contrast T1-weighted images, and apparent diffusion coefficient (ADC) maps. The minimum redundancy maximum relevance (MRMR) and least absolute shrinkage and selection operator (LASSO) logistic regression were performed for radiomics signature construction. Clinical and radiological features were analyzed to select clinical predictors. A nomogram was then developed by incorporating the radiomics signature and selected clinical predictors. RESULTS: Nine radiomics features were selected to construct the radiomics signature, which showed a favorable discriminatory ability in training and test sets with an area under the curve (AUC) of 0.95 and 0.92, respectively. Ring enhancement was identified as an independent clinical predictor (p < 0.01). The nomogram, constructed with radiomics signature and ring enhancement, showed good calibration and discrimination in training and testing sets (AUC: 0.95 and 0.90 respectively). CONCLUSIONS: The nomogram which combined radiomics signature and ring enhancement had a satisfactory ability to predict H3K27M mutation in pHGGs with a midline of the brain. KEY POINTS: • Conventional MRI features were not powerful enough to predict H3K27M mutation status in pediatric high-grade gliomas (pHGGs) with a midline location of the brain. • An MRI-based radiomics signature showed satisfactory ability to predict H3K27M mutation status of pHGGs located in the midline of the brain. • Associating the radiomics signature with clinical factors improved predictive performance.

Staging Liver Fibrosis: Comparison of Native T1 Mapping, T2 Mapping, and T1ρ: An Experimental Study in Rats With Bile Duct Ligation and Carbon Tetrachloride at 11.7 T MRI.

BACKGROUND: T1, T2, and T1ρ might be potential biomarkers for assessing liver fibrosis. However, few studies reported the value of them in different animal models. PURPOSE: To investigate and compare the performances of T1, T2, and T1ρ for noninvasively staging liver fibrosis in bile duct ligation (BDL) or carbon tetrachloride (CCl4 ) model. STUDY TYPE: Prospective animal model. SUBJECTS: Liver fibrosis was induced by BDL or injection of CCl4 in 120 rats. FIELD STRENGTH/SEQUENCE: 11.7 T, T1 mapping with 10 repetition times, T2 mapping with 32 echo times, and T1ρ with 10 spin-lock times. ASSESSMENT: T1, T2, and T1ρ were measured and correlated with liver fibrosis stages, as well as the degree of inflammation, steatosis, iron deposition, and the expression of cytokeratin 19. The discriminative performance of T1, T2, and T1ρ for staging liver fibrosis was compared. STATISTICAL TESTS: One-way analysis of variance (ANOVA), Spearman's correlation analysis, factorial design ANOVA, and receiver operating characteristic curves (P < 0.05 was considered statistically significant). RESULTS: T1, T2, and T1ρ (BDL: rho = 0.73, 0.85, 0.68; CCl4 : rho = 0.80, 0.29, 0.61) were significantly correlated with liver fibrosis stages, while there was no significant difference in T2 among stage F0-F4 in the CCl4 model (P = 0.204). The area under the curves (AUCs) range of T1, T2, and T1ρ for predicting ≥F1, ≥F2, ≥F3, and F4 were 0.76-0.95, 0.89-0.98, and 0.80-0.94 in the CCl4 model. For the CCl4 model, the AUCs range of T1, T2, and T1ρ for predicting ≥F1, ≥F2, ≥F3, and F4 were 0.83-0.95, 0.61-0.74, and 0.73-0.89, respectively. T2 had significantly higher AUC in the BDL model than CCl4 model for diagnosing liver fibrosis. DATA CONCLUSION: The most sensitive and accurate method for staging liver fibrosis appeared to be T1 in our animal models followed by T1ρ. T2 may not be suitable for evaluating liver fibrosis. LEVEL OF EVIDENCE: 1 TECHNICAL EFFICACY STAGE: 2.

Applications of AOTF Spectrometers in In Situ Lunar Measurements.

Spectrometers based on acousto-optic tunable filters (AOTFs) have several advantages, such as stable temperature adaptability, no moving parts, and wavelength selection through electrical modulation, compared with the traditional grating and Fourier transform spectrometers. Therefore, AOTF spectrometers can realize stable in situ measurement on the lunar surface under wide temperature ranges and low light environments. AOTF imaging spectrometers were first employed for in situ measurement of the lunar surface in the Chinese Chang'e project. The visible and near-infrared imaging spectrometer and the lunar mineralogical spectrometer have been successfully deployed on board the Chang'e-3/4 and Chang'e-5 missions. In this review, we investigate the performance indicators, structural design, selected AOTF performance parameters, data acquisition of the three lunar in situ spectral instruments used in the Chang'e missions. In addition, we also show the scientific achievement of lunar technology based on in situ spectral data.

Clinical-MRI radiomics enables the prediction of preoperative cerebral spinal fluid dissemination in children with medulloblastoma.

BACKGROUND: Medulloblastoma (MB) is the most common pediatric embryonal tumor. Accurate identification of cerebral spinal fluid (CSF) dissemination is important in prognosis prediction. Both MRI of the central nervous system (CNS) and CSF cytology will appear false positive and negative. Our objective was to investigate the added value of preoperative-enhanced T1-weighted image-based radiomic features to clinical characteristics in predicting preoperative CSF dissemination for children with MB. MATERIALS AND METHODS: This retrospective study included 84 children with histopathologically confirmed MB between November 2006 and November 2018 (training cohort, n=60; internal validation cohort, n=24). A set of cases between December 2018 and February 2020 were used for external validation (n=40). The children with normal head and spine magnetic resonance images (MRI) and no subsequent dissemination in 1 year were diagnosed as non-CSF dissemination. The CSF dissemination was manifested as intracranial or intraspinal nodular-enhanced lesions. Clinical features were collected, and conventional MRI features of preoperative head MRI examinations were evaluated. A total of 385 radiomic features were extracted from preoperative-enhanced T1-weighted images. Minimum redundancy, maximum correlation, and least absolute shrinkage and selection operator were performed to select the features with the best performance in predicting preoperative CSF dissemination. A combined clinical-MRI radiomic prediction model was developed using multivariable logistic regression. Receiver operating curve analysis (ROC) was used to validate the predictive performance. Nomogram and decision curve analysis (DCA) were developed to evaluate the clinical utility of the combined model. RESULTS: One clinical and nine radiomic features were selected for predicting preoperative CSF dissemination. The combined model incorporating clinical and radiomic features had the best predictive performance in the training cohort with an AUC of 0.89. This was validated in the internal and external cohorts with AUCs of 0.87 and 0.73. The clinical utility of the model was confirmed by a clinical-MRI radiomic nomogram and DCA. CONCLUSIONS: The combined model incorporating clinical, conventional MRI, and radiomic features could be applied to predict preoperative CSF dissemination for children with MB as a noninvasive biomarker, which could aid in risk evaluation.

CT radiomics facilitates more accurate diagnosis of COVID-19 pneumonia: compared with CO-RADS.

BACKGROUND: Limited data was available for rapid and accurate detection of COVID-19 using CT-based machine learning model. This study aimed to investigate the value of chest CT radiomics for diagnosing COVID-19 pneumonia compared with clinical model and COVID-19 reporting and data system (CO-RADS), and develop an open-source diagnostic tool with the constructed radiomics model. METHODS: This study enrolled 115 laboratory-confirmed COVID-19 and 435 non-COVID-19 pneumonia patients (training dataset, n = 379; validation dataset, n = 131; testing dataset, n = 40). Key radiomics features extracted from chest CT images were selected to build a radiomics signature using least absolute shrinkage and selection operator (LASSO) regression. Clinical and clinico-radiomics combined models were constructed. The combined model was further validated in the viral pneumonia cohort, and compared with performance of two radiologists using CO-RADS. The diagnostic performance was assessed by receiver operating characteristics curve (ROC) analysis, calibration curve, and decision curve analysis (DCA). RESULTS: Eight radiomics features and 5 clinical variables were selected to construct the combined radiomics model, which outperformed the clinical model in diagnosing COVID-19 pneumonia with an area under the ROC (AUC) of 0.98 and good calibration in the validation cohort. The combined model also performed better in distinguishing COVID-19 from other viral pneumonia with an AUC of 0.93 compared with 0.75 (P = 0.03) for clinical model, and 0.69 (P = 0.008) or 0.82 (P = 0.15) for two trained radiologists using CO-RADS. The sensitivity and specificity of the combined model can be achieved to 0.85 and 0.90. The DCA confirmed the clinical utility of the combined model. An easy-to-use open-source diagnostic tool was developed using the combined model. CONCLUSIONS: The combined radiomics model outperformed clinical model and CO-RADS for diagnosing COVID-19 pneumonia, which can facilitate more rapid and accurate detection.

Clinico-Radiological Features and Outcomes in Pregnant Women with COVID-19 Pneumonia Compared with Age-Matched Non-Pregnant Women.

PURPOSE: To investigate the clinico-radiological findings and outcomes in pregnant women with COVID-19 pneumonia compared to age-matched non-pregnant women. METHODS: A retrospective case-controlled study was conducted to review clinical and CT data of 21 pregnant and 19 age-matched non-pregnant women with COVID-19 pneumonia. Four stages of CT images were analyzed and compared based on the time interval from symptom onset: stage 1 (0-6 days), stage 2 (7-9 days), stage 3 (10-16 days), and stage 4 (>16 days). The initial and follow-up data were analyzed and compared. RESULTS: Compared with age-matched non-pregnant women, initial absence of fever (13/21, 62%) and normal lymphocyte count (11/21, 52%) were more frequent in pregnant group. The predominant patterns of lung lesions were pure ground-glass opacity (GGO), GGO with consolidation or reticulation, and pure consolidation in both groups. Pure consolidation on chest CT was more common at presentation in pregnant cases. Pregnant women progressed with a higher consolidation frequency compared with non-pregnant group in stage 2 (95% vs 82%). Improvement was identified in stages 3 and 4 for both groups, but consolidation was still more frequent for pregnant women in stage 4. Most patients (38/40, 95%) were grouped as mild or common type. The length of hospitalization between the two groups was similar. CONCLUSION: Pregnant women with COVID-19 pneumonia did not present typical clinical features, while developing a relatively more severe disease at imaging with a slower recovery course and experiencing similar outcomes compared with the non-pregnant women.

Fibronectin-Targeting and Cathepsin B-Activatable Theranostic Nanoprobe for MR/Fluorescence Imaging and Enhanced Photodynamic Therapy for Triple Negative Breast Cancer.

Because of the lack of specific targets, the highly aggressive triple negative breast cancer (TNBC) is unable to benefit from endocrine therapy or conventional targeting therapy. Even worse, current diagnostic and therapeutic approaches have limited value for TNBC. Therefore, developing TNBC-specific theranostic probes for accurate diagnosis and further selective therapy will build a powerful toolbox for TNBC management. In this contribution, we developed a sequential strategy to enhance the specificity of TNBC theranostics. In this theranostic system, a versatile nanoprobe (Pep-SQ@USPIO) was integrated legitimately for the fibronectin-targeting MR imaging and CTSB-activatable fluorescence imaging, followed with enhanced photodynamic therapy (PDT) of TNBC. First, the fibronectin overexpressed in the extracellular matrix (ECM) of TNBC was used as a biomarker for targeting theranostics using the Cys-Arg-Glu-Lys-Ala (CREKA) peptide. For another, the fluorescence and PDT capacity of self-developed squaraine photosensitizer (SQ) were prequenched by ultrasmall superparamagnetic iron oxide (USPIO), an MR imaging contrast agent. Once the linker, Gly-Phe-Leu-Gly (GFLG) peptide, was selectively cleaved by TNBC-derived CTSB, the liberated SQ photosensitizer allowed light-up fluorescence imaging and enhanced PDT of TNBC. Remarkably, this research demonstrates that tumor-ECM-targeting and endogenous enzyme-activated nanoprobes open a new avenue for TNBC theranostics.

Clinical and CT imaging features of the COVID-19 pneumonia: Focus on pregnant women and children.

BACKGROUND: The ongoing outbreak of COVID-19 pneumonia is globally concerning. We aimed to investigate the clinical and CT features in the pregnant women and children with this disease, which have not been well reported. METHODS: Clinical and CT data of 59 patients with COVID-19 from January 27 to February 14, 2020 were retrospectively reviewed, including 14 laboratory-confirmed non-pregnant adults, 16 laboratory-confirmed and 25 clinically-diagnosed pregnant women, and 4 laboratory-confirmed children. The clinical and CT features were analyzed and compared. FINDINGS: Compared with the non-pregnant adults group (n = 14), initial normal body temperature (9 [56%] and 16 [64%]), leukocytosis (8 [50%] and 9 [36%]) and elevated neutrophil ratio (14 [88%] and 20 [80%]), and lymphopenia (9 [56%] and 16 [64%]) were more common in the laboratory-confirmed (n = 16) and clinically-diagnosed (n = 25) pregnant groups. Totally 614 lesions were detected with predominantly peripheral and bilateral distributions in 54 (98%) and 37 (67%) patients, respectively. Pure ground-glass opacity (GGO) was the predominant presence in 94/131 (72%) lesions for the non-pregnant adults. Mixed consolidation and complete consolidation were more common in the laboratory-confirmed (70/161 [43%]) and clinically-diagnosed (153/322 [48%]) pregnant groups than 37/131 (28%) in the non-pregnant adults (P = 0·007, P < 0·001). GGO with reticulation was less common in 9/161 (6%) and 16/322 (5%) lesions for the two pregnant groups than 24/131 (18%) for the non-pregnant adults (P = 0·001, P < 0·001). The pulmonary involvement in children with COVID-19 was mild with a focal GGO or consolidation. Twenty-three patients underwent follow-up CT, revealing progression in 9/13 (69%) at 3 days whereas improvement in 8/10 (80%) at 6-9 days after initial CT scans. INTERPRETATION: Atypical clinical findings of pregnant women with COVID-19 could increase the difficulty in initial identification. Consolidation was more common in the pregnant groups. The clinically-diagnosed cases were vulnerable to more pulmonary involvement. CT was the modality of choice for early detection, severity assessment, and timely therapeutic effects evaluation for the cases with epidemic and clinical features of COVID-19 with or without laboratory confirmation. The exposure history and clinical symptoms were more helpful for screening in children versus chest CT.

Native T1 mapping compared to ultrasound elastography for staging and monitoring liver fibrosis: an animal study of repeatability, reproducibility, and accuracy.

OBJECTIVES: To investigate the repeatability, reproducibility, and staging and monitoring of the performance of native T1 mapping for noninvasively assessing liver fibrosis in comparison with acoustic radiation force impulse (ARFI) elastography. METHODS: The repeatability and reproducibility were explored in 8 male Sprague-Dawley rats with intraclass correlation coefficient (ICC). Different degrees of fibrosis were induced in 52 rats by carbon-tetrachloride (CCl4) insult. Another 16 rats were used to build fibrosis progression and regression models. The native T1 values and shear wave velocity (SWV) were quantified by using native T1 mapping and ARFI elastography, respectively. The METAVIR system (F0-F4) was used for the staging of fibrosis. The area under the receiver operating characteristic curve (AUC) was determined to assess the performance of quantitative parameters for staging and monitoring fibrosis. RESULTS: Native T1 values shared similar good repeatability (ICC = 0.93) and reproducibility (ICC = 0.87) with SWV (ICC = 0.84-0.93). The AUC of native T1 values were 0.84, 0.84, and 0.75 for diagnosing significant fibrosis (≥ F2) and liver cirrhosis (F4) and detecting fibrosis progression, and those of SWV were 0.81, 0.86, and 0.7, respectively. No significant difference in performance was found between the two quantitative parameters (p ≥ 0.496). For detecting fibrosis regression, native T1 values had a better accuracy (AUC = 0.99) than SWV (AUC = 0.56; p = 0.002). CONCLUSION: Native T1 mapping may be a reliable and accurate method for noninvasively assessing liver fibrosis. Compared with ARFI elastography, it provides similar good repeatability and reproducibility, a similar high accuracy for staging fibrosis, and a better accuracy for detecting fibrosis regression. KEY POINTS: • Native T1 mapping is a valuable tool for noninvasively assessing liver fibrosis and can be measured on virtually all clinical MRI machines without additional hardware or gadolinium chelate injection. • Compared with acoustic radiation force impulse elastography, native T1 mapping yields similar good repeatability and reproducibility and a similar high accuracy for staging fibrosis. • Native T1 mapping provides a significantly better performance for detecting fibrosis regression than acoustic radiation force impulse elastography.

Diffusion Metrics for Staging Pancreatic Fibrosis and Correlating With Epithelial-Mesenchymal Transition Markers in a Chronic Pancreatitis Rat Model at 11.7T MRI.

BACKGROUND: Chronic pancreatitis (CP) is characterized by pancreatic fibrosis, in which a epithelial-mesenchymal transition (EMT)-like process is observed. However, few noninvasive approaches have been reported to evaluate pancreatic fibrosis and EMT in an animal model based on diffusion imaging. PURPOSE: To evaluate pancreatic fibrosis in CP by conventional diffusion-weighted imaging (DWI), intravoxel incoherent motion (IVIM), and diffusion kurtosis imaging (DKI) and then explore the correlation between diffusion parameters and the EMT markers in an animal model. STUDY TYPE: Prospective controlled imaging histological correlation. POPULATION: Forty-five rats with CP induced by injecting dibutyltin dichloride solution and 10 normal rats comprised the control group. FIELD STRENGTH/SEQUENCE: 11.7T MR, diffusion imaging with 10 b-values. ASSESSMENT: Apparent diffusion coefficient (ADC), IVIM-associated perfusion fraction (f), pseudodiffusion coefficient (D*), diffusion coefficient (D), DKI-associated mean kurtosis (MK), and mean corrected diffusion coefficient (MD) were quantitatively measured and correlated with pancreatic fibrosis stages as well as the EMT markers E-cadherin and α-smooth muscle actin (α-SMA) expression. The discriminative performance of diffusion parameters for staging fibrosis was compared. STATISTICAL TESTS: Spearman's correlation, Student's t-test, and a receiver operating characteristic curve was conducted for statistical analysis. RESULTS: ADC, D, and MD (r = -0.637, -0.688, and -0.535; P < 0.001) were negatively correlated with pancreatic fibrosis staging, but MK (r = 0.740, P < 0.001) had a positive correlation. ADC, D, MD, and MK were significantly correlated with α-SMA (r = -0.684, -0.728, -0.627, and 0.721, all P < 0.001), while MK was significantly correlated with E-cadherin (r = -0.606, P < 0.001). The area under the curve (AUC) was not significantly different (P > 0.05) among ADC (0.797, 0.816, 0.873), D (0.862, 0.810, 0.895), MD (0.767, 0.772, 0.801), and MK (0.836, 0.893, 0.951) for F1 or greater, F2 or greater, and F3 pancreatic fibrosis separately. DATA CONCLUSION: ADC, D, MD, and MK were helpful for assessing pancreatic fibrosis staging, and these diffusion parameters were also significantly correlated with the expression of EMT markers in pancreatic fibrosis. LEVEL OF EVIDENCE: 2 Technical Efficacy Stage: 2 J. Magn. Reson. Imaging 2020;52:197-206.

Measurement and Correction Model for Temperature Dependence of an Acousto-Optic Tunable Filter (AOTF) Infrared Spectrometer for Lunar Surface Detection.

The photoelectric response characteristics of an infrared spectrometer based on an acousto-optic tunable filter (AOTF) are greatly affected by the temperature change of the radio frequency power amplifier and shortwave infrared detector. If calibration is not conducted, that will affect the quantitative level of the data. This paper puts forward a measurement and correction method for the temperature characteristics of an AOTF infrared spectrometer which is used in lunar surface detection and sets up a temperature characteristics correction model. This model was applied to an AOTF infrared spectrometer mounted on China's unmanned lunar rover. Laboratory tests show that the temperature causes an instrument variation of ∼20% when the temperature is between -20 ℃ and + 55 ℃, but this model reduces this variation to < 6%. Evaluating data from the lunar surface also verifies the effectiveness of this method.