Pre-operative MRI in evaluating pathologic complete response to neoadjuvant chemotherapy in patients with breast cancer: a study focused on influencing factors of baseline clinical-pathological and imaging features.

Purpose: To investigate what pre-treatment clinical-pathological features and MRI characteristics influence the performance of breast MRI in assessing the pathologic complete response (pCR) of breast cancer patients to Neoadjuvant Chemotherapy (NAC). Methods: A total of 225 patients with pathologically-confirmed breast cancer who underwent pre- and post-NAC breast MRI between January 2020 and April 2023 were retrospectively analyzed. All patients were categorized into radiologic complete response (rCR) and non-rCR groups based on pre-operative MRI. Univariable and multivariable logistic regression were used to identify independent clinicopathological and imaging features associated with imaging-pathological discordance. The performance of pre-operative MRI for predicting pCR to NAC was assessed according to the baseline characteristics of the clinicopathological data and pre-NAC MRI. In addition, the discrepancy between the pre-operative MRI and post-operative pathological findings was further analyzed by a case-control approach. Results: Among 225 patients, 99 (44.0%) achieved pCR after NAC. MRI showed the overall sensitivity of 97.6%, specificity of 58.6%, accuracy of 80.4%, a positive predictive value (PPV) of 75.0%, and a negative predictive value (NPV) of 95.1% in identifying pCR. Of baseline features, presence of ductal carcinoma in situ (DCIS) (OR, 3.975 [95% CI: 1.448-10.908], p = 0.007), luminal B (OR, 5.076 [95% CI: 1.401-18.391], p = 0.013), HER2-enriched subtype (OR, 10.949 [95% CI: 3.262-36.747], p < 0.001), multifocal or multicentric lesions (OR, 2.467 [95% CI: 1.067-5.706], p = 0.035), segmental or regional distribution of NME (OR, 8.514 [95% CI: 1.049-69.098], p = 0.045) and rim enhancement of mass (OR, 4.261 [95% CI: 1.347-13.477], p = 0.014) were significantly associated with the discrepancy between MRI and pathology. Conclusion: Presence of DCIS, luminal B or HER2-enriched subtype, multicentric or multifocal lesions, segmental or regional distribution of NME and rim enhancement of mass may lead to a decrease in diagnostic accuracy of MRI in patients of breast cancer treated with NAC.

Histogram analysis comparison of readout-segmented and single-shot echo-planar imaging for differentiating luminal from non-luminal breast cancer.

To compare diffusion-kurtosis imaging (DKI) and diffusion-weighted imaging (DWI) parameters of single-shot echo-planar imaging (ss-EPI) and readout-segmented echo-planar imaging (rs-EPI) in the differentiation of luminal vs. non-luminal breast cancer using histogram analysis. One hundred and sixty women with 111 luminal and 49 non-luminal breast lesions were enrolled in this study. All patients underwent ss-EPI and rs-EPI sequences on a 3.0T scanner. Histogram metrics were derived from mean kurtosis (MK), mean diffusion (MD) and the apparent diffusion coefficient (ADC) maps of two DWI sequences respectively. Student's t test or Mann-Whitney U test was performed for differentiating luminal subtype from non-luminal subtype. The ROC curves were plotted for evaluating the diagnostic performances of significant histogram metrics in differentiating luminal from non-luminal BC. The histogram metrics MKmean, MK50th, MK75th of luminal BC were significantly higher than those of non-luminal BC for both two DWI sequences (all P<0.05). Histogram metrics from rs-EPI sequence had better diagnostic performance in differentiating luminal from non-Luminal breast cancer compared to those from ss-EPI sequence. MK75th derived from rs-EPI sequence was the most valuable single metric (AUC, 0.891; sensitivity, 78.4%; specificity, 87.8%) for differentiating luminal from non-luminal BC among all the histogram metrics. Histogram metrics of MK derived from rs-EPI yielded better diagnostic performance for distinguishing luminal from non-luminal BC than that from ss-EPI. MK75th was the most valuable metric among all the histogram metrics.

Ligand Engineering for Mitigating Exciton-Phonon Coupling in Mixed Halide Perovskite Nanocrystals.

The vulnerability of mixed halide perovskite nanocrystals (NCs) remains challenging because of the weak interaction between commonly employed ligands, oleic acid/oleylamine (OAm/OA) and halide anions, coupled with substantial surface phonon energy. Here, we introduce 3-aminopropyltriethoxysilane (APTES) as a capping ligand to modify CsPbBrI2 NCs to enhance the interactions between them. The optical properties have been significantly enhanced, and halide segregation has been suppressed, both of which can be attributed to the reduced phonon energy and exciton-phonon coupling strength. Moreover, these APTES-CsPbBrI2 NCs exhibit a broad color gamut and sustained color stability during long-term operation, indicating their promising potential in display technologies. This work may offer insights into surface engineering to enhance the properties and band stability of mixed halide perovskite NCs.

Durability Performance of Basalt Fiber-Reinforced Concrete Subjected to Sulfate-Magnesium Combined Attack.

In salt lake areas, cast-in situ concrete structures are subjected to long-term corrosion by sulfate and magnesium ions. The properties of concrete can be improved by adding materials like basalt fiber (BF). To investigate the degradation process and mechanism of cast-in situ concrete with premixed BF under the dual corrosion of sulfate and magnesium salts, concrete with a content of BF ranging from 0 to 0.5% was prepared. Specimens were subjected to different internal and external corrosion conditions and immersed for 180 days. Dimension, mass, and appearance changes at different immersion times were recorded. The compressive and flexural strength of the specimens were tested and continually observed throughout the immersion time. Mineral and microstructural changes at different immersion times were determined by the XRD, TG, and SEM analysis methods. Results indicated that external sulfate-internal magnesium combined attack had a significant negative effect on the early strength. The compressive and flexural strength of the corroded specimens decreased by 17.2% and 14.1%, respectively, compared to the control group at 28 days. The premixed magnesium ions caused the decomposition of the C-S-H gel, resulting in severe spalling and lower mechanical properties after immersing for a long time. As the BF can inhibit crack development, the properties of the concrete premixed with BF were improved. Specimens exhibited superior performance at a BF content of 0.5%, resulting in a 16.2% increase in flexural strength. This paper serves as a valuable reference for the application of basalt fiber-reinforced concrete under the challenging conditions of sulfate-magnesium combined attack.

Euglena's atypical respiratory chain adapts to the discoidal cristae and flexible metabolism.

Euglena gracilis, a model organism of the eukaryotic supergroup Discoba harbouring also clinically important parasitic species, possesses diverse metabolic strategies and an atypical electron transport chain. While structures of the electron transport chain complexes and supercomplexes of most other eukaryotic clades have been reported, no similar structure is currently available for Discoba, limiting the understandings of its core metabolism and leaving a gap in the evolutionary tree of eukaryotic bioenergetics. Here, we report high-resolution cryo-EM structures of Euglena's respirasome I + III2 + IV and supercomplex III2 + IV2. A previously unreported fatty acid synthesis domain locates on the tip of complex I's peripheral arm, providing a clear picture of its atypical subunit composition identified previously. Individual complexes are re-arranged in the respirasome to adapt to the non-uniform membrane curvature of the discoidal cristae. Furthermore, Euglena's conformationally rigid complex I is deactivated by restricting ubiquinone's access to its substrate tunnel. Our findings provide structural insights for therapeutic developments against euglenozoan parasite infections.

Ambient Degradation Anisotropy and Mechanism of van der Waals Ferroelectric NbOI2.

The spontaneous centrosymmetry-breaking and robust room-temperature ferroelectricity in niobium oxide dihalides spurs a flurry of explorations into its promising second-order nonlinear optical properties, and promises potential applications in nonvolatile electro-optical and optoelectronic devices. However, the ambient stability of the niobium oxide dihalides remains questionable, which overshadows their future development. In this work, the chemical degradation of NbOI2 is comprehensively investigated using combined chemical and optical microscopies in conjunction with spectroscopies. We unveil the highly anisotropic degradation kinetics of NbOI2 driven by the hydrolysis process of the unstable dangling iodine bonds dominantly on the (010) facet and progressing along the c axis. Knowing its degradation mechanism, the NbOI2 flake can then be stabilized by the hexagonal boron nitride encapsulation, which isolates the air moisture. These findings provide direct insights into the ambient instability of NbOI2, and they deliver possible solutions to circumvent this issue, which are essential for its practical integration in photonic and electronic devices.

Seed-Mediated Growth for High-Efficiency Perovskite Solar Cells: The Important Role of Seed Surface.

Additive engineering has emerged as one of the most promising strategies to improve the performance of perovskite solar cells (PSCs). Among additives, perovskite nanocrystals (NCs) have a similar chemical composition and matched lattice structure with the perovskite matrix, which can effectively enhance the efficiency and stability of PSCs. However, relevant studies remain limited, and most of them focus on bromide-involved perovskite NCs, which may undergo dissolution and ion exchange within the FAPbI3 host, potentially resulting in an enlarged band gap. In this work, we employ butylamine-capped CsPbI3 NCs (BPNCs) as additives in PSCs, which can be well maintained and serve as seeds for regulating the crystallization and growth of perovskite films. The resultant perovskite film exhibits larger domain sizes and fewer grain boundaries without compromising the band gap. Moreover, BPNCs can alleviate lattice strain and reduce defect densities within the active layer. The PSCs incorporating BPNCs show a champion power conversion efficiency (PCE) of up to 25.41 %, well over both Control of 22.09 % and oleic acid/oleylamine capped CsPbI3 NC (PNC)-based devices of 23.11 %. This work illustrates the key role of nanosized seed surfaces in achieving high-performance photovoltaic devices.

Unconventional polarization fatigue in van der Waals layered ferroelectric ionic conductor CuInP2S6.

Recent progress in two-dimensional ferroelectrics greatly expands the versatility and tunability in van der Waals heterostructure based electronics. However, the switching endurance issue that widely plagues conventional ferroelectrics in practical applications is hitherto unexplored for van der Waals layered ferroelectrics. Herein, we report the observation of unusual polarization fatigue behaviors in van der Waals layered CuInP2S6, which also possesses finite ionic conductivity at room temperature. The strong intertwinement of the short-range polarization switching and long-range ionic movement in conjunction with the van der Waals layered structure gives rise to unique morphological and polarization evolutions under repetitive electric cycles. With the help of concerted chemical, structural, lattice vibrational and dielectric analyses, we unravel the critical role of the synergy of ionic migration and surface oxidation on the anomalous polarization enhancement and the eventual polarization degradation. This work provides a general insight into the polarization fatigue characteristics in ionically-active van der Waals ferroelectrics and delivers potential solutions for the realization of fatigue-free capacitors.

Structures of Tetrahymena thermophila respiratory megacomplexes on the tubular mitochondrial cristae.

Tetrahymena thermophila, a classic ciliate model organism, has been shown to possess tubular mitochondrial cristae and highly divergent electron transport chain involving four transmembrane protein complexes (I-IV). Here we report cryo-EM structures of its ~8 MDa megacomplex IV2 + (I + III2 + II)2, as well as a ~ 10.6 MDa megacomplex (IV2 + I + III2 + II)2 at lower resolution. In megacomplex IV2 + (I + III2 + II)2, each CIV2 protomer associates one copy of supercomplex I + III2 and one copy of CII, forming a half ring-shaped architecture that adapts to the membrane curvature of mitochondrial cristae. Megacomplex (IV2 + I + III2 + II)2 defines the relative position between neighbouring half rings and maintains the proximity between CIV2 and CIII2 cytochrome c binding sites. Our findings expand the current understanding of divergence in eukaryotic electron transport chain organization and how it is related to mitochondrial morphology.

3D/2D Core/Shell Perovskite Nanocrystals for High-Performance Solar Cells.

All-inorganic lead halide perovskite nanocrystals (NCs) emerge as a rising star in photovoltaic fields on account of their excellent optoelectronic properties. However, it still remains challenging to further promote photovoltaic efficiency due to the susceptible surface and inevitable vacancies. Here, this work reports a 3D/2D core/shell perovskite heterojunction based on CsPbI3 NCs and its performance in solar cells. The guanidinium (GA+ ) rich 2D nanoshells can significantly passivate surface trap states and lower the capping ligand density, resulting in improved photoelectric properties and carrier transport and diminished nonradiative recombination centers via the hydrogen bonds from amino groups in GA+ ions. Consequently, an outstanding power conversion efficiency (PCE) of up to 15.53% is realized, substantially higher than the control device (13.77%). This work highlights the importance of surface chemistry and offers a feasible avenue to achieve high-performance perovskite NCs-based optoelectronic devices.

Intraobserver and Interobserver Reproducibility of Breast Diffusion-Weighted Imaging Quantitative Parameters: Readout-Segmented vs. Single-Shot Echo-Planar Imaging.

BACKGROUND: The recommended technique for breast diffusion-weighted imaging (DWI) acquisitions is not sufficiently standardized in clinical practice. PURPOSE: To investigate the intraobserver and interobserver reproducibility of DWI measurements, diffusion-kurtosis imaging (DKI) parameters, and image quality evaluation in breast lesions between single-shot echo-planar imaging (ss-EPI) and readout-segmented echo-planar imaging (rs-EPI). STUDY TYPE: Prospective. POPULATION: A total of 295 women with 209 malignant and 86 benign breast lesions. FIELD STRENGTH/SEQUENCE: A 3-T; fat-saturated T2-weighted MR imaging (T2WI); multi-b-value DWI with both ss-EPI and rs-EPI readouts; T1-weighted dynamic contrast-enhanced MRI (DCE-MRI). ASSESSMENT: Mean kurtosis (MK), mean diffusion (MD), and apparent diffusion coefficient (ADC) values were measured for each lesion on ss-EPI and rs-EPI, respectively. Image quality was visually evaluated regarding image sharpness, geometric distortion, lesion conspicuity, visualization of anatomic structures, and overall quality. Quantitative and qualitative analyses were performed twice with a time interval of 2 weeks. STATISTICAL TESTS: Intraobserver and interobserver reproducibility were evaluated using intra-class correlation coefficients (ICC), within-subject coefficient of variation (wCV), and Bland-Altman plots. RESULTS: MK, MD, and ADC quantitative parameters for breast lesions showed excellent intraobserver and interobserver reproducibility, with ICCs >0.75 and wCV values ranging from 2.51% to 7.08% for both sequences. The wCV values in both intraobserver and interobserver measurements were higher in the ss-EPI sequence (3.63%-7.08%) than that of the rs-EPI sequence (2.51%-3.62%). The wCV values differed in subgroups with different histopathological types of lesions, breast density, lesion morphology, and lesion sizes, respectively. Furthermore, rs-EPI (ICCs, 0.76-0.97; wCV values, 2.41%-6.04%) had better intraobserver and interobserver reproducibility than ss-EPI (ICCs, 0.54-0.90; wCV values, 6.18%-13.69%) with regard to image quality. DATA CONCLUSION: Compared to the ss-EPI, the rs-EPI sequence showed higher intraobserver and interobserver reproducibility for quantitative diffusion-related parameters and image quality assessments measured in breast DWI and DKI. EVIDENCE LEVEL: 2. TECHNICAL EFFICACY: Stage 2.

Histogram analysis of breast diffusion kurtosis imaging: a comparison between readout-segmented and single-shot echo-planar imaging sequence.

Background: Histogram analysis of the diffusion-weighted imaging (DWI) parameters is widely used to differentiate the breast lesions. However, histogram analysis of the diffusion-kurtosis imaging (DKI) parameters for the single-shot echo-planar imaging (ss-EPI) and readout-segmented echo planar imaging (rs-EPI) sequences has not been compared in breast cancer. Thus, this study is to investigate the diagnostic accuracy and reliability of the histogram parameters derived from the rs-EPI and ss-EPI sequences of DKI parameters in distinguishing between the benign and malignant breast lesions. Methods: This single-center, retrospective cohort study enrolled 205 consecutive patients with breast lesions (65 benign and 140 malignant). The patients underwent breast magnetic resonance imaging (MRI) with a 3T scanner using the rs-EPI and ss-EPI sequences with 4 b values (0, 50, 1,000, and 2,000 s/mm2). The regions of interest (ROIs) were manually delineated for all the lesion images from both the sequences, and the histogram parameters were extracted from the apparent diffusion coefficient (ADC) and apparent diffusional kurtosis (Kapp) maps. Statistical analysis was performed using the Kolmogorov-Smirnov test, the student's t-test, and the receiver operating characteristic (ROC) curves. Results: The mean, 25th, 50th, 75th, and 100th percentiles, skewness, and kurtosis values derived from apparent diffusion for non-Gaussian distribution (Dapp) and Kapp maps showed good or excellent intra-observer agreement (ICC: 0.695 to 0.863).The mean and the 25th, 50th, 75th, and 100th percentile values for Dapp were significantly lower and the mean and the 25th, 50th, 75th, and 100th percentile values for Kapp were significantly higher in the malignant breast lesions compared with those in the benign breast lesions for both the rs-EPI and ss-EPI sequences (all P<0.05). The majority of the histogram Kapp and Dapp parameters (except skewness and kurtosis) for the benign and malignant lesions showed significant differences between the ss-EPI and the rs-EPI sequences (P<0.05). ROC curve analysis showed that the AUC values for the 75th percentile of Kapp (0.854 for rs-EPI, 0.844 for ss-EPI) and the 25th percentile of Dapp (0.866 for rs-EPI, 0.858 for ss-EPI) were highest for both DKI sequences. The diagnostic performance of the rs-EPI sequence was better than the ss-EPI sequence for all the histogram parameters except the skewness value of Dapp. Conclusions: Histogram parameters from the rs-EPI sequence were more reliable and accurate in differentiating malignant and benign breast lesions than those from the ss-EPI sequence.

A nomogram based on radiomics signature and deep-learning signature for preoperative prediction of axillary lymph node metastasis in breast cancer.

Purpose: To develop a nomogram based on radiomics signature and deep-learning signature for predicting the axillary lymph node (ALN) metastasis in breast cancer. Methods: A total of 151 patients were assigned to a training cohort (n = 106) and a test cohort (n = 45) in this study. Radiomics features were extracted from DCE-MRI images, and deep-learning features were extracted by VGG-16 algorithm. Seven machine learning models were built using the selected features to evaluate the predictive value of radiomics or deep-learning features for the ALN metastasis in breast cancer. A nomogram was then constructed based on the multivariate logistic regression model incorporating radiomics signature, deep-learning signature, and clinical risk factors. Results: Five radiomics features and two deep-learning features were selected for machine learning model construction. In the test cohort, the AUC was above 0.80 for most of the radiomics models except DecisionTree and ExtraTrees. In addition, the K-nearest neighbor (KNN), XGBoost, and LightGBM models using deep-learning features had AUCs above 0.80 in the test cohort. The nomogram, which incorporated the radiomics signature, deep-learning signature, and MRI-reported LN status, showed good calibration and performance with the AUC of 0.90 (0.85-0.96) in the training cohort and 0.90 (0.80-0.99) in the test cohort. The DCA showed that the nomogram could offer more net benefit than radiomics signature or deep-learning signature. Conclusions: Both radiomics and deep-learning features are diagnostic for predicting ALN metastasis in breast cancer. The nomogram incorporating radiomics and deep-learning signatures can achieve better prediction performance than every signature used alone.

Self-Enhancing Photoelectrochemical Properties in van der Waals Ferroelectric CuInP2S6 by Photoassisted Acid Hydrolysis.

Transition metal thiophosphate, CuInP2S6 (CIPS), has recently emerged as a potentially promising material for photoelectrochemical (PEC) water splitting due to its intrinsic ferroelectric polarization for spontaneous photocarrier separation. However, the poor kinetics of the hydrogen evolution reaction (HER) greatly limits its practical applications. Herein, we report self-enhancing photocatalytic behavior of a CIPS photocathode due to chemically driven oxygen incorporation by photoassisted acid oxidation. The optimal oxygen-doped CIPS demonstrates a >1 order of magnitude enhancement in the photocurrent density compared to that of pristine CIPS. Through comprehensive spectroscopic and microscopic investigations combined with theoretical calculations, we disclose that oxygen doping will lower the Fermi level position and decrease the HER barrier, which further accelerates charge separation and improves the HER activity. This work may deliver a universal and facile strategy for improving the PEC performance of other van der Waals metal thiophosphates.

Pathological Networks Involving Dysmorphic Neurons in Type II Focal Cortical Dysplasia.

Focal cortical dysplasia (FCD) is one of the most common causes of drug-resistant epilepsy. Dysmorphic neurons are the major histopathological feature of type II FCD, but their role in seizure genesis in FCD is unclear. Here we performed whole-cell patch-clamp recording and morphological reconstruction of cortical principal neurons in postsurgical brain tissue from drug-resistant epilepsy patients. Quantitative analyses revealed distinct morphological and electrophysiological characteristics of the upper layer dysmorphic neurons in type II FCD, including an enlarged soma, aberrant dendritic arbors, increased current injection for rheobase action potential firing, and reduced action potential firing frequency. Intriguingly, the upper layer dysmorphic neurons received decreased glutamatergic and increased GABAergic synaptic inputs that were coupled with upregulation of the Na+-K+-Cl- cotransporter. In addition, we found a depolarizing shift of the GABA reversal potential in the CamKII-cre::PTENflox/flox mouse model of drug-resistant epilepsy, suggesting that enhanced GABAergic inputs might depolarize dysmorphic neurons. Thus, imbalance of synaptic excitation and inhibition of dysmorphic neurons may contribute to seizure genesis in type II FCD.

Prediction of Axillary Lymph Node Metastasis in Breast Cancer using Intra-peritumoral Textural Transition Analysis based on Dynamic Contrast-enhanced Magnetic Resonance Imaging.

RATIONALE AND OBJECTIVES: Intra-peritumoural textural transition (Ipris) is a new radiomics method, which includes a series of quantitative measurements of the image features that represent the differences between the inside and outside of the tumour. This study aimed to explore the feasibility of Ipris analysis for the preoperative prediction of axillary lymph node (ALN) status in patients with breast cancer based on dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). MATERIALS AND METHODS: This study was approved by the Institutional Review Board (IRB) of our hospital. One hundred sixty-six patients with clinicopathologically confirmed invasive breast cancer and ALN status were enrolled. All patients underwent preoperative breast DCE-MRI examinations. The primary breast lesion was manually segmented using the ITK-SNAP software for each patient. Two sets of image features were extracted, including Ipris features and conventional intratumoural features. Feature selection was conducted using Spearman correlation analysis and support vector machine with recursive feature elimination (SVM-RFE). Next, three models were established in training dataset: Model 1 was established by Ipris features; Model 2 was established by intratumoural features; Model 3 was established by combining Ipris features and intratumoural features. The performances of the three models were evaluated for the prediction of ALN status in testing datasets. RESULTS: Model 1 with four Ipris features achieved an AUC of 0.816 (95% CI, 0.733-0.883) and 0.829 (95% CI, 0.695-0.922) in the training and testing datasets, respectively. Model 2 with six intratumoural features achieved an AUC of 0.801 (95% CI, 0.716-0.870) and 0.824 (95% CI, 0.689-0.918) in the training and testing datasets, respectively. By incorporating the Ipris and intratumoural features, the AUC of Model 3 increased to 0.968 (95% CI, 0.916-0.992) and 0.855 (95% CI, 0.724-0.939) in the training and testing datasets, respectively. CONCLUSION: Ipris features based on DCE-MRI can be used to predict ALN status in patients with breast cancer. The model combining intratumoural and Ipris features achieved higher prediction performance.

Cascaded Algorithm Selection With Extreme-Region UCB Bandit.

AutoML aims at best configuring learning systems automatically. It contains core subtasks of algorithm selection and hyper-parameter tuning. Previous approaches considered searching in the joint hyper-parameter space of all algorithms, which forms a huge but redundant space and causes an inefficient search. We tackle this issue in a cascaded algorithm selection way, which contains an upper-level process of algorithm selection and a lower-level process of hyper-parameter tuning for algorithms. While the lower-level process employs an anytime tuning approach, the upper-level process is naturally formulated as a multi-armed bandit, deciding which algorithm should be allocated one more piece of time for the lower-level tuning. To achieve the goal of finding the best configuration, we propose the Extreme-Region Upper Confidence Bound (ER-UCB) strategy. Unlike UCB bandits that maximize the mean of feedback distribution, ER-UCB maximizes the extreme-region of feedback distribution. We first consider stationary distributions and propose the ER-UCB-S algorithm that has O(Klnn) regret upper bound with K arms and n trials. We then extend to non-stationary settings and propose the ER-UCB-N algorithm that has O(Knν) regret upper bound, where [Formula: see text]. Finally, empirical studies on synthetic and AutoML tasks verify the effectiveness of ER-UCB-S/N by their outperformance in corresponding settings.

Effect of polarization rotation on the optical and photovoltaic properties of BiFeO3thin films.

Visible-light-active ferroelectric materials are gaining increasing attention due to the unique ferroelectric photovoltaic effect. To boost the light harvesting capability, vast research is devoted to band gap engineering by chemical substitutions, regardless of the side effect on ferroelectric polarization. Here, we focus on how polar order affects the optical and photovoltaic properties. Using BiFeO3as the model system, we induce the polarization rotation by A-site La substitution, which results in continuous reduction of optical anisotropy of the samples, as revealed by the concerted optical characterizations. This further causes the decrease of angular dependence of ferroelectric photovoltaic effect on the light polarization. The results demonstrate the inner connection of the ferroelectric polarization and optical anisotropy via the lattice degree of freedom.

Accelerating acquisition of readout-segmented echo planar imaging with a simultaneous multi-slice (SMS) technique for diagnosing breast lesions.

OBJECTIVES: To investigate the feasibility and effectiveness of SMS rs-EPI for evaluating breast lesions. METHODS: This prospective study was approved by IRB. Ninety-six patients had 102 histopathologically verified lesions (80 malignant and 22 benign) that were evaluated. Conventional rs-EPI and SMS rs-EPI data were acquired on a 3T scanner. Mean kurtosis (MK), mean diffusion (MD), and apparent diffusion coefficient (ADC) values were quantitatively calculated for each lesion on both sequences. Images were qualitatively and quantitatively analyzed with respect to image sharpness, geometric distortion, lesion conspicuity, anatomic structure, overall image quality, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR). Student's t test, Pearson correlation, receiver operating characteristic curve, Wilcoxon rank sum test, and paired-sample t tests were used for statistical analysis. RESULTS: Compared to conventional rs-EPI, the acquisition time of SMS rs-EPI was markedly reduced (2:17 min vs 4:27 min). Pearson's correlations showed excellent linear relationships for each parameter between conventional rs-EPI and SMS rs-EPI (MK, r = 0.908; MD, r = 0.938; and ADC, r = 0.975; p < 0.01 for all). Furthermore, SMS rs-EPI had similar diagnostic performance compared with conventional rs-EPI. SMS rs-EPI had comparable visual image quality as conventional rs-EPI, with excellent inter-reader reliability (ICC = 0.851-0.940). No differences existed between conventional rs-EPI and SMS rs-EPI for either SNR or CNR (p > 0.05). CONCLUSIONS: Applying the SMS technique can significantly reduce the acquisition time and produce similar diagnostic accuracy while generating comparable image quality as the conventional rs-EPI. KEY POINTS: • SMS rs-EPI reduces scan time from 4:27 min to 2:17 min compared with conventional rs-EPI. • SMS rs-EPI has a comparable diagnostic performance to conventional rs-EPI in the differentiation between malignant and benign breast lesions. • SMS rs-EPI demonstrates comparable image quality to conventional rs-EPI with shorter scan time.

Chest CT imaging features and severity scores as biomarkers for prognostic prediction in patients with COVID-19.

BACKGROUND: Coronavirus disease 2019 (COVID-19) has become a pandemic. Few studies have explored the role of chest computed tomography (CT) features and severity scores for prognostic prediction. In this study, we aimed to investigate the role of chest CT severity score and imaging features in the prediction of the prognosis of COVID-19 patients. METHODS: A total of 134 patients (62 recovered and 72 deceased patients) with confirmed COVID-19 were enrolled. The clinical, laboratory, and chest CT (316 scans) data were retrospectively reviewed. Demographics, symptoms, comorbidities, and temporal changes of laboratory results, CT features, and severity scores were compared between recovered and deceased groups using the Mann-Whitney U test and logistic regression to identify the risk factors for poor prognosis. RESULTS: Median age was 48 and 58 years for recovered and deceased patients, respectively. More patients had at least one comorbidity in the deceased group than the recovered group (60% vs. 29%). Leukocytes, neutrophil, high-sensitivity C-reactive protein (hsCRP), prothrombin, D-dimer, serum ferritin, interleukin (IL)-2, and IL-6 were significantly elevated in the deceased group than the recovered group at different stages. The total CT score at the peak stage was significantly greater in the deceased group than the recovered group (20 vs. 11 points). The optimal cutoff value of the total CT scores was 16.5 points, achieving 69.4% sensitivity and 82.2% specificity for the prognostic prediction. The crazy-paving pattern and consolidation were more common in the deceased patients than those in the recovered patients. Linear opacities significantly increased with the disease course in the recovered patients. Sex, age, neutrophil, IL-2, IL-6, and total CT scores were independent risk factors for the prognosis with odds ratios of 3.8 to 8.7. CONCLUSIONS: Sex (male), older age (>60 years), elevated neutrophil, IL-2, IL-6 level, and total CT scores (≥16) were independent risk factors for poor prognosis in patients with COVID-19. Temporal changes of chest CT features and severity scores could be valuable for early identification of severe cases and eventually reducing the mortality rate of COVID-19.