Neoadjuvant gemcitabine-cisplatin plus tislelizumab in persons with resectable muscle-invasive bladder cancer: a multicenter, single-arm, phase 2 trial.

Programmed death 1 blockade (tislelizumab) has been approved for metastatic urothelial carcinoma but not as part of neoadjuvant therapy for muscle-invasive bladder cancer (MIBC). In this multicenter single-arm trial (ChiCTR2000037670), 65 participants with cT2-4aN0M0 MIBC received neoadjuvant gemcitabine-cisplatin plus tislelizumab; 57 of them underwent radical cystectomy (RC). The primary endpoint of pathologic complete response (pCR) rate was 50.9% (29/57, 95% confidence interval (CI) 37.3-64.4%) and the pathologic downstaging (secondary endpoint) rate was 75.4% (43/57, 95% CI 62.2-85.9%) in participants undergoing RC. Genomic and transcriptomic analyses revealed three MIBC molecular subtypes (S): S1 (immune-desert) with activated cell-cycle pathway, S2 (immune-excluded) with activated transforming growth factor-ß pathway and S3 (immune-inflamed) with upregulated interferon-α and interferon-γ response. Post hoc analysis showed pCR rates of 16% (3/19, S1), 77% (10/13, S2) and 80% (12/15, S3) (P = 0.006). In conclusion, neoadjuvant gemcitabine-cisplatin plus tislelizumab for MIBC was compatible with an enhanced pCR rate.

Source imaging method based on diagonal covariance bases and its applications to OPM-MEG.

Magnetoencephalography (MEG) is a noninvasive imaging technique used in neuroscience and clinical research. The source estimation of MEG involves solving a highly underdetermined inverse problem, which requires additional constraints to restrict the solution space. Traditional methods tend to obscure the extent of the sources. However, an accurate estimation of the source extent is important for studying brain activity or preoperatively estimating pathogenic regions. To improve the estimation accuracy of the extended source extent, the spatial constraint of sources is employed in the Bayesian framework. For example, the source is decomposed into a linear combination of validated spatial basis functions, which is proved to improve the source imaging accuracy. In this work, we further construct the spatial properties of the source using the diagonal covariance bases (DCB), which we summarize as the source imaging method SI-DCB. In this approach, specifically, the covariance matrix of the spatial coefficients is modeled as a weighted combination of diagonal covariance basis functions. The convex analysis is used to estimate noise and model parameters under the Bayesian framework. Extensive numerical simulations showed that SI-DCB outperformed five benchmark methods in accurately estimating the location and extent of patch sources. The effectiveness of SI-DCB was verified through somatosensory stimulation experiments performed on a 31-channel OPM-MEG system. The SI-DCB correctly identified the source area where each brain response occurred. The superior performance of SI-DCB suggests that it can provide a template approach for improving the accuracy of source extent estimations under a sparse Bayesian framework.

The application of the "perinephric fat wrapping" technique with oral mucosal graft for the management of ureter repair and reconstruction.

OBJECTIVE: The management of long-segment ureteral stenosis has posed a significant challenge for urologists. Ureteroplasty with oral mucosal graft has emerged as an effective approach for treating long-segment ureteral stenosis and defects. A key step in replacement repair surgery involves suturing the surrounding tissue with an adequate blood supply around the reconstructed ureter. The current study aims to evaluate the potential practical application of the "perinephric fat wrapping" technique in laparoscopic ureteroplasty with oral mucosal graft. METHODS: Between July 2018 and February 2023, 26 patients with ureteral stenosis underwent laparoscopic ureteroplasty with oral mucosal graft at the Second Affiliated Hospital of Anhui Medical University. We used traditional omental wrapping technique (OW group) or perinephric fat wrapping technique (PFW group) to enhance ureter repair. Perioperative and follow-up data for both groups were collected retrospectively and compared. RESULTS: There were 10 patients in OW group, including 4 males and 6 females, with BMI of 23.5±2.8 kg/m2 and stenosis length of 3.6±1.6 cm. There were 16 patients in the PFW group, including 10 males and 6 females, with a BMI of 26.1±3.3 kg/m2 and a median stenosis length of 2.3 cm (range, 1.2~6.0 cm). The operation of both groups was successfully completed, and no serious complications occurred during the operation. The mean operating time (OT) in the OW group was 200.6±41.9 min, the estimated amount of blood loss (EBL) was 25 ml (range, 10~30ml), and the median length of postoperative hospital stay (LHS) was 7.5 days (range 4.0~14.0 days). In the PFW group, the mean operating time (OT) was 211.9±38.3 min, the estimated blood loss (EBL) was 25 ml (range, 5~150ml), and the postoperative hospital stay (LHS) was 6.8±2.0 d. There was no significant difference between the two groups in the above indexes. Postoperative anal exhaust time was 1.0 d (range, 1.0~2.5d) in the PFW group and 1.9±0.5 d in the OW group, with significant difference between the two groups (P=0.009). The mean follow-up time was 36.8±15.9 months, and there was no significant difference between OW group and PFW group in the curative effect of operation. CONCLUSION: Perinephric fat wrapping technique not only avoids the potential effects of using omentum on abdominal organs, it is also as safe and effective as omentum wrapping technique in repairing and reconstructing the ureter using oral mucosal grafts.

Intratumoral calcification on CT assists in distinguishing benign and malignant upper abdomen neoplasm.

BACKGROUND: The significance of calcification and microcalcification in diagnosing malignant tumors is well established, but their role in the upper abdomen is less explored in routine radiology. OBJECTIVES: To assess the effectiveness of computed tomography (CT) imaging in detecting intratumoral calcification within upper abdominal tumors. METHODS: This study retrospectively enrolled patients with upper abdominal tumors featuring intratumoral calcifications who underwent plain and contrast-enhanced CT scans between January 2016 and December 2019. We examined the imaging characteristics of calcifications, including location, edges, shape, CT values, and association with necrosis. The diagnostic utility of calcification for distinguishing benign and malignant tumors was assessed using receiver operating characteristic curves. Univariate and multivariate logistic regression analyses were conducted to identify independent predictive factors for the diagnosis of malignancy characterized by intratumoral calcification. RESULTS: This study included 153 patients (median age 49 ± 21 years; 83 men) with pathologically confirmed tumors of the upper abdomen (including liver, pancreas, and gastrointestinal tract) with intratumoral calcifications. Significant differences in CT values between benign and malignant tumors were observed (P < .001), with high diagnostic accuracy of calcification in CT imaging (receiver operating characteristic area = 0.884, sensitivity = 0.815, specificity = 0.976). The characteristics of calcification, including its edge and shape, were significantly correlated with tumor differentiation (P < .01). Multivariate logistic regression analysis revealed that the presence of adjacent necrosis around intracalcification is an independent predictor of malignancy (odds ratio = 5.48; 95% confidence interval: 1.55, 19.41; P = .008). CONCLUSION: Intratumoral calcification in CT imaging is a key marker for distinguishing between benign and malignant epigastric tumors, offering high specificity. Key message • What is already known on this topic - Intratumoral calcification, as a highly sensitive radiological marker, has shown potential in differentiating between benign and malignant tumors in thyroid and breast cancers. However, its discriminatory role in upper abdominal tumors is often overlooked. Therefore, assessing the diagnostic accuracy of intratumoral calcification on CT scans is crucial for improving diagnostic efficiency and avoiding unnecessary examinations. • What this study adds - Intratumoral calcification on CT exhibits high specificity in differentiating between benign and malignant upper abdominal tumors, providing a simple and reliable criterion for improving diagnostic accuracy. • How this study might affect research, practice or policy - This study highlights the significance of intratumoral calcification characteristics observed on CT in determining whether upper abdominal tumors are benign or malignant. The findings could pave the way for the development of a CT-based calcification scoring system, which would facilitate rapid and accurate diagnostics in clinical practice, thereby optimizing treatment strategies and enhancing patient prognosis.

A Novel Time-Frequency Parameterization Method for Oscillations in Specific Frequency Bands and Its Application on OPM-MEG.

Time-frequency parameterization for oscillations in specific frequency bands reflects the dynamic changes in the brain. It is related to cognitive behavior and diseases and has received significant attention in neuroscience. However, many studies do not consider the impact of the aperiodic noise and neural activity, including their time-varying fluctuations. Some studies are limited by the low resolution of the time-frequency spectrum and parameter-solved operation. Therefore, this paper proposes super-resolution time-frequency periodic parameterization of (transient) oscillation (STPPTO). STPPTO obtains a super-resolution time-frequency spectrum with Superlet transform. Then, the time-frequency representation of oscillations is obtained by removing the aperiodic component fitted in a time-resolved way. Finally, the definition of transient events is used to parameterize oscillations. The performance of this method is validated on simulated data and its reliability is demonstrated on magnetoencephalography. We show how it can be used to explore and analyze oscillatory activity under rhythmic stimulation.

Metal-Phenolic Vehicles Potentiate Cycle-Cascade Activation of Pyroptosis and cGAS-STING Pathway for Tumor Immunotherapy.

The treatment of triple-negative breast cancer (TNBC) faces challenges due to its limited immune response and weak tumor immunogenicity. A collaborative strategy involves combining the activation of pyroptosis and the stimulator of interferon genes (STING) pathway to enhance tumor immunogenicity and fortify the antitumor immune response, which may improve therapeutic outcomes in TNBC. In this study, we report the fabrication of a zinc-phenolic nanocapsule (RMP@Cap), which is loaded with mitoxantrone (MTO) and anti-PD-L1 antibodies (aPD-L1) and coated with erythrocyte membrane, for TNBC immunotherapy. The delivery of RMP@Cap can induce tumor cell pyroptosis and, therefore, trigger the release of mitochondrial DNA, which further combines with zinc agonists to intensify STING activation, resulting in a cascade amplification of the therapeutic effect on tumors. Additionally, the incorporation of aPD-L1 into the zinc-phenolic nanocapsule relieves the inhibitory effect of tumor cells on recruited cytotoxic T cells, thereby improving the tumor-killing capacity. Furthermore, the incorporation of a camouflaged erythrocyte membrane coating enables nanocapsules to achieve prolonged in vivo circulation, resulting in improved tumor accumulation for effective antitumor therapy. This study demonstrates a synergistic therapeutic modality involving pyroptosis, coupled with the simultaneous activation and cyclic amplification of the STING pathway in immunotherapy.

Utilizing radiomics for differential diagnosis of inverted papilloma and chronic rhinosinusitis with polyps based on unenhanced CT scans.

To evaluate whether radiomics models based on unenhanced paranasal sinuses CT images could be a useful tool for differentiating inverted papilloma (IP) from chronic rhinosinusitis with polyps (CRSwNP). This retrospective study recruited 240 patients with CRSwNP and 106 patients with IP from three centers. 253 patients from Qilu Hospital were randomly divided into the training set (n = 151) and the internal validation set (n = 102) with a ratio of 6:4. 93 patients from the other two centers were used as the external validation set. The patients with the unilateral disease (n = 115) from Qilu Hospital were selected to further develop a subgroup analysis. Lesion segmentation was manually delineated in CT images. Least absolute shrinkage and selection operator algorithm was performed for feature reduction and selection. Decision tree, support vector machine, random forest, and adaptive boosting regressor were employed to establish the differential diagnosis models. 43 radiomic features were selected for modeling. Among the models, RF achieved the best results, with an AUC of 0.998, 0.943, and 0.934 in the training set, the internal validation set, and the external validation set, respectively. In the subgroup analysis, RF achieved an AUC of 0.999 in the training set and 0.963 in the internal validation set. The proposed radiomics models offered a non-invasion and accurate differential approach between IP and CRSwNP and has some significance in guiding clinicians determining the best treatment plans, as well as predicting the prognosis.

Risk factors for thrombotic events in systemic lupus erythematosus patients with antiphospholipid antibodies: insights from morphometric measurements of carotid arteries.

Objective: To identify the correlation between thrombosis and atherosclerosis in systemic lupus erythematosus (SLE) patients with antiphospholipid antibodies (aPLs) (SLE/aPLs) through high-resolution magnetic resonance imaging (HR-MRI) of the carotid artery. Methods: A single-center, cross-sectional study was conducted. We collected consecutive patients with SLE/aPLs and healthy controls who underwent carotid HR-MRI examinations. The morphometric characteristics of the common carotid artery (CCA), internal carotid artery (ICA), external carotid artery (ECA), and carotid bulb (Sinus) were measured, and the differences in morphometric parameters between different groups were analyzed. Results: A total of 144 carotid arteries were analyzed. Compared with the control group, the wall area, wall thickness (WT and WTmax), and normalized wall index of CCA, ICA, ECA, and Sinus were increased in patients with SLE/aPLs, and the total vascular area (TVA) of CCA, ICA, and Sinus, and the bifurcation angle (BIFA) of ICA-ECA were also increased. A negative lupus anticoagulant (LAC) (with or without positive anticardiolipin antibody (aCL) or anti-ß2glycoprotein antibody (aß2GPI)) contributed to illustrating lower increased TVA and thickened vessel walls of CCA and ICA in SLE/aPLs patients without thrombotic events. Logistic regression analysis showed that WTmaxSinus and WTmaxGlobal were independent risk factors for thrombotic events in SLE/aPLs patients. The receiver operator characteristic curve showed that the cut-off value of WTmaxSinus was 2.855 mm, and WTmaxGlobal was 3.370 mm. Conclusion: HR-MRI ensures the complete and accurate measurement of carotid morphometric parameters. Compared with the control group, the carotid artery in patients with SLE/aPLs is mainly characterized by diffusely thickened vessel walls, and the patients with thrombotic events showed additional higher vascular area of CCA and ICA, and BIFA of ICA-ECA without significant change in lumen area. The carotid arteries of SLE/aPLs patients with thrombotic events exhibited significant vessel wall thickening in all segments except ECA compared to those without thrombotic events. LAC-negative and non-thrombotic events distinguish relatively early atherosclerosis in the carotid arteries in patients with SLE/aPLs. Patients with SLE/aPLs that possess circumscribed thickened carotid vessel walls (>3.370 mm), particularly thickened at the Sinus (>2.855 mm), may require management strategies for the risk of thrombotic events.

Decoding N400m Evoked Component: A Tutorial on Multivariate Pattern Analysis for OP-MEG Data.

Multivariate pattern analysis (MVPA) has played an extensive role in interpreting brain activity, which has been applied in studies with modalities such as functional Magnetic Resonance Imaging (fMRI), Magnetoencephalography (MEG) and Electroencephalography (EEG). The advent of wearable MEG systems based on optically pumped magnetometers (OPMs), i.e., OP-MEG, has broadened the application of bio-magnetism in the realm of neuroscience. Nonetheless, it also raises challenges in temporal decoding analysis due to the unique attributes of OP-MEG itself. The efficacy of decoding performance utilizing multimodal fusion, such as MEG-EEG, also remains to be elucidated. In this regard, we investigated the impact of several factors, such as processing methods, models and modalities, on the decoding outcomes of OP-MEG. Our findings indicate that the number of averaged trials, dimensionality reduction (DR) methods, and the number of cross-validation folds significantly affect the decoding performance of OP-MEG data. Additionally, decoding results vary across modalities and fusion strategy. In contrast, decoder type, resampling frequency, and sliding window length exert marginal effects. Furthermore, we introduced mutual information (MI) to investigate how information loss due to OP-MEG data processing affect decoding accuracy. Our study offers insights for linear decoding research using OP-MEG and expand its application in the fields of cognitive neuroscience.

Source localization comparison and combination of OPM-MEG and fMRI to detect sensorimotor cortex responses.

BACKGROUND AND OBJECTIVES: The exploration of various neuroimaging techniques have become focal points within the field of neuroscience research. Magnetoencephalography based on optically pumped magnetometers (OPM-MEG) has shown significant potential to be the next generation of functional neuroimaging with the advantages of high signal intensity and flexible sensor arrangement. In this study, we constructed a 31-channel OPM-MEG system and performed a preliminary comparison of the temporal and spatial relationship between magnetic responses measured by OPM-MEG and blood-oxygen-level-dependent signals detected by functional magnetic resonance imaging (fMRI) during a grasping task. METHODS: For OPM-MEG, the ß-band (15-30 Hz) oscillatory activities can be reliably detected across multiple subjects and multiple session runs. To effectively localize the inhibitory oscillatory activities, a source power-spectrum ratio-based imaging method was proposed. This approach was compared with conventional source imaging methods, such as minimum norm-type and beamformer methods, and was applied in OPM-MEG source analysis. Subsequently, the spatial and temporal responses at the source-level between OPM-MEG and fMRI were analyzed. RESULTS: The effectiveness of the proposed method was confirmed through simulations compared to benchmark methods. Our demonstration revealed an average spatial separation of 10.57 ± 4.41 mm between the localization results of OPM-MEG and fMRI across four subjects. Furthermore, the fMRI-constrained OPM-MEG localization results indicated a more focused imaging extent. CONCLUSIONS: Taken together, the performance exhibited by OPM-MEG positions it as a potential instrument for functional surgery assessment.

Patients With Type 2 Diabetes Mellitus and Early Diabetic Kidney Disease Exhibit Lower Computed Tomography-measured Skeletal Muscle Attenuation Values: A Propensity Score-matched Study.

OBJECTIVE: To investigate the association between computed tomography-measured quality characteristics of skeletal muscle (SM) and early diagnosis of diabetic kidney disease (DKD) in patients with type 2 diabetes mellitus (T2DM). METHODS: This retrospective study included patients diagnosed with T2DM, with and without early DKD, between January 2019 and December 2021. To reduce potential bias, propensity score matching (PSM) was performed. The area and computed tomography attenuation values for SM and different abdominal adipose depots were measured. After PSM, logistic and multiple linear regression analyze were performed to analyse risk factors for early DKD. RESULTS: A total of 267 patients were enrolled (mean age, 61.67 years ± 10.87; 155 men) and divided into two groups: T2DM with early DKD (n = 133); and T2DM without DKD (n = 134). After PSM, 230 patients were matched (T2DM with early DKD [n = 115]; and T2DM without DKD [n = 115]), with no statistical differences in general characteristics between the two groups (P > .05). In multivariate logistic regression analysis, high-density lipoprotein cholesterol (odds ratio [OR] 0.14; 95% confidence interval [CI] 0.04-0.49; P = .002), uric acid (OR 1.01; 95% CI 1.00-1.01; P = .006), and SM attenuation value (OR 0.94; 95% CI 0.90-0.98; P = .003) were independent risk factors for early DKD. Multiple linear regression analysis revealed significant correlations between SM attenuation value and cystatin C (ß = -0.39, P = .004), urine albumin-to-creatinine ratio (ß = -0.26, P = .026), and estimated glomerular filtration rate (ß = 0.31 P = .009) after adjustment for confounders. CONCLUSION: Patients with T2DM and lower SM attenuation values may exhibit a higher risk for early DKD than those with higher values, which provides a potential imaging biomarker for early DKD diagnosis.

Ultrasmall Fe3O4 nanoparticles self-assembly induced dual-mode T1/T2-weighted magnetic resonance imaging and enhanced tumor synergetic theranostics.

Individual theranostic agents with dual-mode MRI responses and therapeutic efficacy have attracted extensive interest due to the real-time monitor and high effective treatment, which endow the providential treatment and avoid the repeated medication with side effects. However, it is difficult to achieve the integrated strategy of MRI and therapeutic drug due to complicated synthesis route, low efficiency and potential biosafety issues. In this study, novel self-assembled ultrasmall Fe3O4 nanoclusters were developed for tumor-targeted dual-mode T1/T2-weighted magnetic resonance imaging (MRI) guided synergetic chemodynamic therapy (CDT) and chemotherapy. The self-assembled ultrasmall Fe3O4 nanoclusters synthesized by facilely modifying ultrasmall Fe3O4 nanoparticles with 2,3-dimercaptosuccinic acid (DMSA) molecule possess long-term stability and mass production ability. The proposed ultrasmall Fe3O4 nanoclusters shows excellent dual-mode T1 and T2 MRI capacities as well as favorable CDT ability due to the appropriate size effect and the abundant Fe ion on the surface of ultrasmall Fe3O4 nanoclusters. After conjugation with the tumor targeting ligand Arg-Gly-Asp (RGD) and chemotherapy drug doxorubicin (Dox), the functionalized Fe3O4 nanoclusters achieve enhanced tumor accumulation and retention effects and synergetic CDT and chemotherapy function, which serve as a powerful integrated theranostic platform for cancer treatment.

Prognostic significance and immune landscape of a cell cycle progression-related risk model in bladder cancer.

BACKGROUND: A greater emphasis has been placed on the part of cell cycle progression (CCP) in cancer in recent years. Nevertheless, the precise connection between CCP-related genes and bladder cancer (BCa) has remained elusive. This study endeavors to establish and validate a reliable risk model incorporating CCP-related factors, aiming to predict both the prognosis and immune landscape of BCa. METHODS: Clinical information and RNA sequencing data were collected from the GEO and TCGA databases. Univariate and multivariate Cox regression analyses were conducted to construct a risk model associated with CCP. The performance of the model was assessed using ROC and Kaplan-Meier survival analyses. Functional enrichment analysis was employed to investigate potential cellular functions and signaling pathways. The immune landscape was characterized using CIBERSORT algorithms. Integration of the risk model with various clinical variables led to the development of a nomogram. RESULTS: To build the risk model, three CCP-related genes (RAD54B, KPNA2, and TPM1) were carefully chosen. ROC and Kaplan-Meier survival analysis confirm that our model has good performance. About immunological infiltration, the high-risk group showed decreased levels of regulatory T cells and dendritic cells coupled with increased levels of activated CD4 + memory T cells, M2 macrophages, and neutrophils. Furthermore, the nomogram showed impressive predictive power for OS at 1, 3, and 5 years. CONCLUSION: This study provides new insights into the association between the CCP-related risk model and the prognosis of BCa, as well as its impact on the immune landscape.

SPFS: SNR peak-based frequency selection method to alleviate resolution degradation in MPI real-time imaging.

Objective. The primary objective of this study is to address the reconstruction time challenge in magnetic particle imaging (MPI) by introducing a novel approach named SNR-peak-based frequency selection (SPFS). The focus is on improving spatial resolution without compromising reconstruction speed, thereby enhancing the clinical potential of MPI for real-time imaging.Approach. To overcome the trade-off between reconstruction time and spatial resolution in MPI, the researchers propose SPFS as an innovative frequency selection method. Unlike conventional SNR-based selection, SPFS prioritizes frequencies with signal-to-noise ratio (SNR) peaks that capture crucial system matrix information. This adaptability to varying quantities of selected frequencies enhances versatility in the reconstruction process. The study compares the spatial resolution of MPI reconstruction using both SNR-based and SPFS frequency selection methods, utilizing simulated and real device data.Main results.The research findings demonstrate that the SPFS approach substantially improves image resolution in MPI, especially when dealing with a limited number of frequency components. By focusing on SNR peaks associated with critical system matrix information, SPFS mitigates the spatial resolution degradation observed in conventional SNR-based selection methods. The study validates the effectiveness of SPFS through the assessment of MPI reconstruction spatial resolution using both simulated and real device data, highlighting its potential to address a critical limitation in the field.Significance.The introduction of SPFS represents a significant breakthrough in MPI technology. The method not only accelerates reconstruction time but also enhances spatial resolution, thus expanding the clinical potential of MPI for various applications. The improved real-time imaging capabilities of MPI, facilitated by SPFS, hold promise for advancements in drug delivery, plaque assessment, tumor treatment, cerebral perfusion evaluation, immunotherapy guidance, andin vivocell tracking.

Design Principles and Mechanistic Understandings of Non-Noble-Metal Bifunctional Electrocatalysts for Zinc-Air Batteries.

Zinc-air batteries (ZABs) are promising energy storage systems because of high theoretical energy density, safety, low cost, and abundance of zinc. However, the slow multi-step reaction of oxygen and heavy reliance on noble-metal catalysts hinder the practical applications of ZABs. Therefore, feasible and advanced non-noble-metal electrocatalysts for air cathodes need to be identified to promote the oxygen catalytic reaction. In this review, we initially introduced the advancement of ZABs in the past two decades and provided an overview of key developments in this field. Then, we discussed the working mechanism and the design of bifunctional electrocatalysts from the perspective of morphology design, crystal structure tuning, interface strategy, and atomic engineering. We also included theoretical studies, machine learning, and advanced characterization technologies to provide a comprehensive understanding of the structure-performance relationship of electrocatalysts and the reaction pathways of the oxygen redox reactions. Finally, we discussed the challenges and prospects related to designing advanced non-noble-metal bifunctional electrocatalysts for ZABs.

Study of radiomics based on dual-energy CT for nuclear grading and T-staging in renal clear cell carcinoma.

INTRODUCTION: Clear cell renal cell carcinoma (ccRCC) is the most lethal subtype of renal cell carcinoma with a high invasive potential. Radiomics has attracted much attention in predicting the preoperative T-staging and nuclear grade of ccRCC. OBJECTIVE: The objective was to evaluate the efficacy of dual-energy computed tomography (DECT) radiomics in predicting ccRCC grade and T-stage while optimizing the models. METHODS: 200 ccRCC patients underwent preoperative DECT scanning and were randomized into training and validation cohorts. Radiomics models based on 70 KeV, 100 KeV, 150 KeV, iodine-based material decomposition images (IMDI), virtual noncontrasted images (VNC), mixed energy images (MEI) and MEI + IMDI were established for grading and T-staging. Receiver operating characteristic analysis and decision curve analysis (DCA) were performed. The area under the curve (AUC) values were compared using Delong test. RESULTS: For grading, the AUC values of these models ranged from 0.64 to 0.97 during training and from 0.54 to 0.72 during validation. In the validation cohort, the performance of MEI + IMDI model was optimal, with an AUC of 0.72, sensitivity of 0.71, and specificity of 0.70. The AUC value for the 70 KeV model was higher than those for the 100 KeV, 150 KeV, and MEI models. For T-staging, these models achieved AUC values of 0.83 to 1.00 in training and 0.59 to 0.82 in validation. The validation cohort demonstrated AUCs of 0.82 and 0.70, sensitivities of 0.71 and 0.71, and specificities of 0.80 and 0.60 for the MEI + IMDI and IMDI models, respectively. In terms of grading and T-staging, the MEI + IMDI model had the highest AUC in validation, with IMDI coming in second. There were statistically significant differences between the MEI + IMDI model and the 70 KeV, 100 KeV, 150 KeV, MEI, and VNC models in terms of grading (P < .05) and staging (P ≤ .001). DCA showed that both MEI + IDMI and IDMI models outperformed other models in predicting grade and stage of ccRCC. CONCLUSIONS: DECT radiomics models were helpful in grading and T-staging of ccRCC. The combined model of MEI + IMDI achieved favorable results.

pH-responsive iron-loaded carbonaceous nanoparticles for chemodynamic therapy based on the Fenton reaction.

The Fenton reaction-based chemodynamic therapy is a form of cancer therapy, and its efficacy can be significantly improved by promoting catalytic reactions involving iron ions. A system with high catalytic capacity and low biological toxicity that effectively inhibits tumor progression is required for optimal treatment. In this study, iron-loaded carbonaceous nanoparticles (CNPs@Fe) with Fenton catalytic activity were fabricated and applied for the chemodynamic therapy of cancer. The carbonaceous nanoparticles derived from glucose via a caramelization reaction demonstrated high biocompatibility. Besides, aromatic structures in the carbonaceous nanoparticles helped accelerate electron transfer to enhance the catalytic decomposition of H2O2, resulting in the formation of highly reactive hydroxyl radicals (˙OH). At pH 6.0 (representing weak acidity in the tumor microenvironment), the Fenton catalytic activity of CNPs@Fe in the decomposition of H2O2 was 15.3 times higher than that of Fe2+ and 28.3 times higher than that of Fe3O4via a chromogenic reaction. The reasons for the enhancement were revealed by analyzing the chemical composition of carbonaceous nanoparticles using high-resolution mass spectra. The developed Fenton agent also demonstrated significant therapeutic effectiveness and minimal side effects in in vitro and in vivo anticancer studies. This work proposes a novel approach to promote the generation of reactive oxygen species (ROS) for the chemodynamic therapy of cancer.

Diffusion-weighted imaging-based radiomics model using automatic machine learning to differentiate cerebral cystic metastases from brain abscesses.

OBJECTIVES: To develop a radiomics model based on diffusion-weighted imaging (DWI) utilizing automated machine learning method to differentiate cerebral cystic metastases from brain abscesses. MATERIALS AND METHODS: A total of 186 patients with cerebral cystic metastases (n = 98) and brain abscesses (n = 88) from two clinical institutions were retrospectively included. The datasets (129 from institution A) were randomly portioned into separate 75% training and 25% internal testing sets. Radiomics features were extracted from DWI images using two subregions of the lesion (cystic core and solid wall). A thorough image preprocessing method was applied to DWI images to ensure the robustness of radiomics features before feature extraction. Then the Tree-based Pipeline Optimization Tool (TPOT) was utilized to search for the best optimized machine learning pipeline, using a fivefold cross-validation in the training set. The external test set (57 from institution B) was used to evaluate the model's performance. RESULTS: Seven distinct TPOT models were optimized to distinguish between cerebral cystic metastases and abscesses either based on different features combination or using wavelet transform. The optimal model demonstrated an AUC of 1.00, an accuracy of 0.97, sensitivity of 1.00, and specificity of 0.93 in the internal test set, based on the combination of cystic core and solid wall radiomics signature using wavelet transform. In the external test set, this model reached 1.00 AUC, 0.96 accuracy, 1.00 sensitivity, and 0.93 specificity. CONCLUSION: The DWI-based radiomics model established by TPOT exhibits a promising predictive capacity in distinguishing cerebral cystic metastases from abscesses.

CT­based radiomics analysis of consolidation characteristics in differentiating pulmonary disease of non­tuberculous mycobacterium from pulmonary tuberculosis.

Global incidence rate of non-tuberculous mycobacteria (NTM) pulmonary disease has been increasing rapidly. In some countries and regions, its incidence rate is higher than that of tuberculosis. It is easily confused with tuberculosis. The topic of this study is to identify two diseases using CT radioomics. The aim in the present study was to investigate the value of CT-based radiomics to analyze consolidation features in differentiation of non-tuberculous mycobacteria (NTM) from pulmonary tuberculosis (TB). A total of 156 patients (75 with NTM pulmonary disease and 81 with TB) exhibiting consolidation characteristics in Shandong Public Health Clinical Center were retrospectively analyzed. Subsequently, 305 regions of interest of CT consolidation were outlined. Using a random number generated via a computer, 70 and 30% of consolidations were allocated to the training and the validation cohort, respectively. By means of variance threshold, when investigating the effective radiomics features, SelectKBest and the least absolute shrinkage and selection operator regression method were employed for feature selection and combined to calculate the radiomics score. K-nearest neighbor (KNN), support vector machine (SVM) and logistic regression (LR) were used to analyze effective radiomics features. A total of 18 patients with NTM pulmonary disease and 18 with TB possessing consolidation characteristics in Jinan Infectious Disease Hospital were collected for external validation of the model. A total of three methods was used in the selection of 52 optimal features. For KNN, the area under the curve (AUC; sensitivity, specificity) for the training and validation cohorts were 0.98 (0.93, 0.94) and 0.90 (0.88, 083), respectively; for SVM, AUC was 0.99 (0.96, 0.96) and 0.92 (0.86, 0.85) and for LR, AUC was 0.99 (0.97, 0.97) and 0.89 (0.88, 0.85). In the external validation cohort, AUC values of models were all >0.84 and LR classifier exhibited the most significant precision, recall and F1 score (0.87, 0.94 and 0.88, respectively). LR classifier possessed the best performance in differentiating diseases. Therefore, CT-based radiomics analysis of consolidation features may distinguish NTM pulmonary disease from TB.