OBJECTIVES:This study evaluated the diagnostic accuracy of 3 ultrasound-based parameters-median nerve cross-sectional area (CSA), elasticity (E value), and blood flow pixel ratio (BFPR)-in grading carpal tunnel syndrome (CTS) severity. These parameters were assessed using high-frequency ultrasound, shear wave elastography (SWE), and superb microvascular imaging (SMI), with nerve conduction studies (NCS) as the reference standard. METHODS:A prospective study conducted between April 2024 and January 2025 included 128 patients with suspected CTS and 25 healthy controls, totalling 223 median nerves. CTS severity was categorized as mild, moderate, or severe based on NCS results. RESULTS:CSA increased from 10.05 mm2 in controls to 17.35 mm2 in severe CTS, E value rose from 42.35 kPa to 128.39 kPa, and BFPR increased from 3.99% to 19.76%. BFPR had the highest sensitivity for detecting mild CTS (cut-off 5.9%). Significant correlations (r > 0.78, P < .0001) were found among CSA, E value, and BFPR. ROC analysis showed excellent diagnostic accuracy with AUC values of 0.90-0.97 for distinguishing controls from CTS patients and 0.93-0.95 for differentiating mild from moderate-to-severe CTS. CONCLUSION:Multiparametric ultrasound, particularly BFPR via SMI, provides a reliable, non-invasive alternative to NCS for early CTS detection and severity grading, with potential for standardizing diagnostic guidelines. ADVANCEMENT IN KNOWLEDGE:This study improves ultrasound-based CTS diagnosis by integrating CSA, E value, and BFPR, offering an effective method for early detection and severity grading. BFPR, especially via SMI, demonstrates high sensitivity for mild CTS and could standardize diagnostic approaches.

Chemodynamic therapy (CDT) has played an important role in osteosarcoma (OS) treatment. However, the insufficient content of endogenous H2O2 and high expression of glutathione (GSH) in tumor tissues limit the antitumor efficacy of CDT. In this work, we developed polydopamine (PDA) coated and CuO2 NPs loaded ZIF8 nanoparticles (CuO2@ZIF8@PDA NPs) for thermally reinforced CDT treatment of OS. The CuO2@ZIF8@PDA NPs exhibited excellent stability in neutral solutions while degraded in weakly acidic environments to generate hydrogen peroxide (H2O2) and Cu2+. Cu2+ consumes GSH in tumor tissues to generate Cu+. Both Cu2+ and Cu+ catalyzed the decomposition of H2O2, triggering a Fenton-like reaction to produce hydroxyl radicals (center dot OH). The PDA coating endowed the nanosystem with photothermal conversion capabilities under near-infrared laser irradiation, further promoting the generation of center dot OH, and inducing tumor cell death. In vitro experiments demonstrated that CuO2@ZIF8@PDA NPs exhibited significant toxicity towards K7M2 cells while remaining non-toxic to normal cells. In vivo studies revealed that under 808 nm laser irradiation, CuO2@ZIF8@PDA NPs exhibited stronger killing ability against K7M2 cells than CuO2@ZIF8@PDA NPs alone. This system, which combines GSH depletion, intratumoral H2O2 self-generation, and photothermally enhanced CDT, holds great promise for playing a pivotal role in the treatment of osteosarcoma.

Background:Carotid artery disease (CAD) is a serious disease caused by atherosclerosis, resulting in reduced cerebral blood flow and an increased risk of stroke. Traditionally, CAD diagnosis involves manual segmentation of computed tomography angiography (CTA) images, a time-consuming and complex process. This study aimed to address the need for an automated and accurate method for three-dimensional (3D) carotid artery segmentation using deep learning (DL) techniques. Methods:A total of 214 CTA images from patients at the Affiliated Hospital of Nantong University and Nantong First People's Hospital were collected. The data were annotated using 3Dslicer software and calibrated by experienced radiologists. Preprocessing and augmentation of the CTA images were conducted using a novel window/level (W/L) adjustment method to enhance vascular imaging. The segmentation is performed using the Multi-Flux-Swin-Deepsup-UNet (MFSD-UNet) model, which incorporates multi-scale deep supervision and multi-flux fusion architecture. Performance was evaluated based on accuracy, dice coefficient, sensitivity, and specificity, and compared with state-of-the-art models. Ablation studies were conducted, removing the Swin transformer and deep supervision components to demonstrate the superiority of our method. Results:The proposed model showed excellent performance, achieving an average dice coefficient of 0.9119 and an accuracy of 0.9819, outperforming the average dice coefficients of 0.8770 and 0.8910 for the two state-of-the-art models. Furthermore, it demonstrated high stability across various segmentation categories. Ablation studies revealed that removing the Swin transformer and deep supervision components resulted in a decrease in the dice coefficient to 0.8630 and 0.8371. Significant differences were observed when comparing these four models with MFSD-UNet (P<0.05), and seven-fold cross-validations were performed on MFSD-UNet to demonstrate its robustness. Conclusions:This study introduced a novel DL-based method for automatic 3D carotid artery segmentation from CTA images. The integration of Swin transformers, deep supervision mechanisms, and innovative data augmentation techniques significantly enhanced the accuracy and robustness of segmentation. This method offers valuable support for the clinical diagnosis and treatment of CAD and exhibits great potential for future medical image segmentation.

PURPOSE:To assess the protective effects of intragastric Vitamin C and N-acetylcysteine (NAC) against DNA damage from CT scan radiation in rats. MATERIALS AND METHODS:The male Sprague Dawley rats (n = 8 per group) were allocated into four distinct groups: control (no CT radiation), IR (CT radiation only), Vitamin C (200 mg/kg with CT radiation), and NAC (200 mg/kg with CT radiation). Antioxidants were administered intragastrically 3 hours before scanning. Non-control groups underwent CT radiation at 120 kVp and 110 mA for 3 scans. Surface absorbed dose was measured with thermoluminescent dosimeter chips. Serum total antioxidant capacity (TAC) was measured pre- and post-scanning. γ-H2AX foci in peripheral blood lymphocytes were assessed at baseline, 1 hour, and 24 hours post-scan. Bone marrow smears were prepared 24 hours post-scan, stained with Giemsa, and micronucleus (MN) frequency in polychromatic erythrocytes was evaluated. RESULTS:TAC levels increased by 68.2% in the Vitamin C group and 152.3% in the NAC group compared to the IR group. γ-H2AX foci rates decreased by 10.3% in the Vitamin C group and 14.3% in the NAC group compared to the IR group. MN frequency decreased by 28.6% in the Vitamin C group and 34.9% in the NAC group compared to the IR group. No significant difference was found between Vitamin C and NAC. CONCLUSION:Oral Vitamin C and NAC significantly mitigate radiation exposure from CT imaging in rats. Both antioxidants effectively reduce γ-H2AX foci and micronucleus formation, offering substantial protection against radiation-induced DNA damage.

Background:Esophageal cancer (ESCA) is a highly aggressive malignancy characterized by poor prognosis, primarily due to late diagnosis and limited treatment efficacy. Immunotherapies, such as vaccines, necessitate a more comprehensive understanding of the tumor immune microenvironment and tumor-specific antigens. The immune heterogeneity of ESCA, which is shaped by immune cell infiltration and antigen presentation, remains largely unexplored, particularly in terms of its interactions with autoimmune mechanisms. This study employs multi-omics analysis to profile the immunophenotype of ESCA, aiming to identify immune evasion mechanisms, tumor antigens, and autoimmune-related pathways. By elucidating these features, we seek to uncover potential targets for vaccine development and personalized immunotherapies, thereby improving therapeutic outcomes. Methods:To screen for potential antigen genes, we examined the overexpressed and mutated genes specific to ESCA. Additionally, we employed Kaplan-Meier survival and Cox analysis to evaluate the prognostic relevance of these potential tumor antigens. To achieve data aggregation and construct a consistency matrix, we used consistency clustering. Subsequently, a graph learning-based dimensionality reduction method was implemented to clarify the immune subtypes. Furthermore, weighted gene coexpression network analysis (WGCNA) was used to cluster potential antigen genes and identify hub genes. Results:Our analysis identified six overexpressed and mutated tumor antigens that were strongly associated with poor prognosis and antigen-presenting cell (APC) infiltration in ESCA. Analysis of The Cancer Genome Atlas (TCGA) data consistently identified three immune subtypes. These findings allowed for the construction of the immune landscape of TCGA samples based on the respective immune subtypes. The integration of immunogenomics analysis further allowed for the characterization of the immune microenvironment for each immune subtype. WGCNA successfully screened for three prognostic factors. Conclusions:In our analysis, BTN2A1, MICA, and HHLA2 displayed significant potential as antigens for the development of anti-ESCA messenger RNA (mRNA) vaccines. The identification of three stable and reproducible immune subtypes specific to ESCA may prove essential in predicting the outcome of mRNA vaccines.

The viability of using thrombus heterogeneity (TH) data derived from dual-energy CT (DECT) as a visual thrombotic biomarker is unclear. The first aim of this study is to develop a quantitative measure of TH on DECT and test its performance for predicting the stroke source (cardiogenic vs. non-cardiogenic) and clinical outcomes (functional status assessed by the modified Rankin Scale score at 90 days) following machine thrombectomy (MT). The second aim is to associate thrombus subregions with the thrombus composition to facilitate visualization of thrombus constituents. Radiomics data are extracted from the whole thrombus and subregions in CT/DECT to construct predictive models. The performances of all models are evaluated and compared in the validation and comparative cohorts. Histopathologic analysis is performed to correlate the subregion data with the actual thrombus composition. This study included 221 and 255 participants who underwent DECT and CT examinations, respectively. DECT outperformed CT in predicting stroke source and clinical outcomes, with the TH-related models showing the highest performance in the validation and comparative cohorts. Thrombus composition is correlated with the different CT/DECT-based subregions, with DECT-habitat_c showing the strongest association. Thrombus subregion analyses may help visualize the related constituents.

Background:Developing nanodrugs with passive targeting capabilities that can effectively overcome the oxidative-redox homeostasis-inhibiting microenvironment of tumors offers new insights into the precise treatment of osteosarcoma. Methods:CoFe2O4 nanoparticles were synthesized via the hydrothermal method and modified with polyethylene glycol 4000 on their surface, obtaining CF@P nanozymes with multi-catalytic activities similar to catalase (CAT), peroxidase (POD), oxidase (OD), and glutathione peroxidase (GPx). These nanozymes could overcome the hypoxic microenvironment and redox homeostasis in osteosarcoma treatment. Results:CF@P has a size of approximately 100 nm and can stably exist under physiological conditions. It exhibits excellent photothermal effects under near-infrared II (1064 nm) laser irradiation, synergistically enhancing its catalytic activity. CF@P alleviates hypoxia by decomposing endogenous H2O2 within tumors to generate oxygen and hydroxyl radicals (·OH). Meanwhile, it consumes reduced glutathione (GSH) within tumors, inducing ferroptosis and apoptosis. CF@P exhibits low toxicity to normal cells (HUVEC) and selective killing ability against osteosarcoma cells (U2OS). In vivo, it accumulates in tumor tissues via the enhanced permeability and retention (EPR) effect, significantly inhibiting tumor growth in combination with photothermal therapy without causing significant organ toxicity, thereby prolonging the survival of tumor-bearing mice. Conclusion:The CF@P nanozyme integrates the properties of multi-enzyme catalysis and photothermal therapy, disrupting the oxidative-redox homeostasis of tumor tissues, generating highly toxic hydroxyl radicals, and efficiently inducing apoptosis in osteosarcoma cells. This approach provides a new, efficient, and safe strategy for the precise treatment of hypoxic solid tumors like osteosarcoma.

Background:The superior mesenteric artery (SMA) has numerous branches and a high rate of anatomical variation, making it challenging to manage during surgery. This study aimed to evaluate the clinical utility of dual energy computed tomography (CT) three-dimensional (3D) reconstruction combined with arteriovenous image fusion technology for assessing SMA variations. The goal is to aid in surgical planning for laparoscopic radical resection of right colon cancer, using the SMA as the primary surgical approach. Methods:We performed a retrospective analysis of clinical and imaging data from patients with right colon cancer who underwent enhanced spectral CT of the abdomen and pelvis before surgery at Nantong University Affiliated Hospital from January 2020 to June 2024. Using post-processing techniques to reconstruct SMA images, the study evaluated the SMA root position, measured the distance between the roots of the right branches of the SMA, analyzed their relationship with patient gender and body mass index (BMI), and summarized the types of right branches of the SMA. Additionally, the relationship between the middle colic artery (MCA), right colic artery (RCA), ileocolic artery (ICA), and the superior mesenteric vein (SMV) positions were analyzed in relation to patient clinical characteristics. Results:The SMA root was mostly located at the L1 vertebral level (74.68%, 236/316), with a vertebral range between T12-L2. The distance from the SMA root to the abdominal aorta (DSMA-AB) was 115.97±11.82 mm, and this distance increased with higher BMI in males. Type I SMA (presence of RCA) accounted for 39.87% (126/316), Type II (absence of RCA) accounted for 60.13% (190/316), with the distance between the root of the MCA and the ICA (dMCA-ICA) being longer in type II. 91.27% (115/126) of the RCA was anterior to the SMV. When the RCA was posterior, the ICA was always posterior to the SMV. The ICA was anterior to the SMV in about 50.63% (160/316) of cases, with a higher incidence in males and those with a shorter dMCA-ICA. Conclusions:Spectral CT 3D reconstruction and arteriovenous image fusion technology can accurately assess the anatomical features of the SMA and the relationship between the right branch vessels and the SMV, helping to develop reasonable surgical plans for laparoscopic radical right hemicolectomy in patients with right colon cancer using an "SMA-prioritized approach".

Objectives: This study aimed to assess the predictive performance of radiomics derived from computed tomography (CT) images of thrombus regions in predicting the risk of intracranial hemorrhage (ICH) following endovascular thrombectomy (EVT). Materials and Methods: This retrospective multicenter study included 336 patients who underwent admission CT and EVT for acute anterior-circulation large vessel occlusion between December 2018 and December 2023. Follow-up imaging was performed 24 h post-procedure to evaluate the occurrence of ICH. 230 patients from centers A and B were randomly allocated into training and test groups in a 7:3 ratio, while the remaining 106 patients from center C comprised the validation cohort. Radiologists manually segmenting the thrombus on CT images, and the perithrombus region was defined by expanding the initial region of interest (ROI). A total of 428 radiomics features were extracted from both intrathrombus and perithrombus regions on CT images. The Mann-Whitney U test was used for feature selection, and least absolute shrinkage and selection operator (LASSO) regression was employed for model development, followed by validation using a 5-fold cross-validation approach. Model performance was assessed using the area under the curve (AUC) of the receiver operating characteristic (ROC). Results: Among the eligible patients, 128 (38.1 %) experienced ICH after EVT. The combined model exhibited superior performance in the training cohort (AUC: 0.913, 95 % CI: 0.861-0.965), test cohort (AUC: 0.868, 95 % CI: 0.775-0.962), and validation cohort (AUC: 0.850, 95 % CI: 0.768-0.912). Notably, in the validation group, both the perithrombus and combined models demonstrated higher predictive accuracy compared to the intrathrombus model (0.837 vs. 0.684, p = 0.02; AUC: 0.850 vs. 0.684, p = 0.01). Conclusions: Radiomics features derived from the perithrombus region significantly enhance the prediction of ICH after EVT, providing valuable insights for optimizing post-procedural clinical decisions. Clinical relevance statement: This study highlights the importance of radiomics extracted from intrathrombus and perithrombus region in predicting intracranial hemorrhage following endovascular thrombectomy, which can aid in improving patient outcomes.

Background Coronary CT-derived fractional flow reserve (CT-FFR) has been used in patients with suspected coronary artery disease (CAD); however, whether it decreases invasive coronary angiography (ICA) use and affects prognosis remains insufficiently evidenced. Purpose To explore the effectiveness of adding CT-FFR to routine coronary CT angiography (CCTA) on short-term ICA rate and major adverse cardiovascular events (MACE) in a Chinese setting. Materials and Methods A multicenter randomized controlled trial was conducted in 17 Chinese centers, with patient inclusion from May 2021 to September 2021. Eligible individuals with 25%-99% stenosis at CCTA were randomly assigned 1:1 to a strategy of CCTA plus automated CT-FFR or CCTA alone for guiding downstream care. The primary end point was the ICA rate 90 days after enrollment. Secondary end points included 90-day and 1-year MACE rates (comprised of all-cause mortality, nonfatal myocardial infarction, and urgent revascularization) and 1-year cardiac events (comprised of cardiac death, nonfatal myocardial infarction, and urgent revascularization). The Cox proportional hazards model with center effect adjustment was used for survival comparisons. Results A total of 5297 participants (mean age, 63.5 years ± 10.8 [SD]; 3178 male) were included. During the 90-day follow-up, ICA was performed in 263 of 2633 participants (10.0%) in the CCTA plus CT-FFR group and 327 of 2640 participants (12.4%) in the CCTA-alone group (absolute rate difference: -2.40%; 95% CI: -4.10, -0.70; P = .006). The MACE rates at 90 days (0.5% [12 of 2633 participants] vs 0.8% [21 of 2640 participants]; P = .12) and 1 year (2.9% [74 of 2546 participants] vs 2.8% [72 of 2531 participants]; P = .90) were similar for both groups. At 1-year follow-up, fewer cardiac events were observed in the CCTA plus CT-FFR group compared with the CCTA-alone group (0.5% vs 1.1%; adjusted hazard ratio: 0.52; 95% CI: 0.27, 0.99; P = .047). Conclusion CT-FFR added to CCTA led to a lower 90-day ICA rate and similar 1-year MACE rate in a Chinese real-world setting. Further follow-up is warranted to demonstrate the long-term prognostic value of this management approach. © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Pundziute-do Prado in this issue.

Breast cancer (BC) is the most prevalent malignant tumor among women worldwide and a significant cause of cancer-related deaths in females. Recent studies have shown that lipid metabolism-related genes (LMRGs) exhibit prognostic potential in various types of tumors, including BC. Our study aimed to establish a novel model to predict the metastasis of BC. Clinical information and corresponding RNA data of patients with BC were downloaded from The Cancer Genome Atlas and Gene Expression Omnibus databases. Consensus clustering was performed to identify novel molecular subgroups. Estimation of Stromal and Immune Cells in Malignant Tumor Tissues using Expression, microenvironment cell populations counter, microenvironment cell populations counter, and single-sample gene set enrichment analyses were employed to determine the tumor immune microenvironment and immune status of the identified subgroups. Functional analyses, including Gene Ontology and gene set enrichment analyses, were conducted to elucidate the underlying mechanisms. A prognostic risk model was constructed using the Least Absolute Shrinkage and Selection Operator algorithm and multivariate Cox regression analysis. This study identified differential gene expression between patients with BC exhibiting metastasis and those without metastasis using public databases. Using the obtained data, we established predictive models based on six LMRGs. Furthermore, consensus clustering and prognostic score grouping analysis revealed that differentially expressed LMRGs influence tumor prognosis by regulating tumor immunity. To facilitate clinical application, we developed a nomogram integrating the risk model and clinical characteristics to accurately predict the prognosis of patients with BC. We developed and validated a novel signature associated with LMRGs for predicting disease-free survival in patients with BC. The expression of LMRGs correlates with the immune microenvironment of patients with BC, providing new insights and improved strategies for the diagnosis and treatment of BC.

The current radiation protection reference standards on stochastic cancer risk, drafted by the International Committee on Radiation Protection, are mostly based on the Life Span Study (LSS), though sufficient epidemiological and basic research evidence is lacking. The relationship between low-dose ionizing radiation (LDIR) and cancer risk is currently modeled with linear non-threshold (LNT) models. However, with the widespread use of medical examinations, the demand for substantial evidence of cancer risk under LDIR and the establishment of a threshold has become more significant. In the first part of the review, we summarize pivotal research in epidemiology, which includes the LSS, medical radiation studies, and occupational and environmental exposure studies. We describe and discuss solid cancers and hematopoietic malignancies induced by LDIR separately, attempting to identify the consistency and differences in the research results, and offering suggestions for future research directions. In the second part, we review recent progress in the underlying biology of cancer associated with LDIR. Besides the obvious harmful effect of DNA damage, chromosome aberrations caused by LDIR, epigenetic regulation also requires attention due to their relationship with carcinogenic and genetic risk. The multistage carcinogenesis model of stem cells, along with the varying effects of radiation on different tumors, may challenge the LNT model. Related research of stem cells, mitochondria and omic biology also offers promising directions for future research in this field.

Background:The discovery of biomarkers has facilitated the treatment of cancer. At present, the relationship between activin A receptor type-1 (ACVR1) and gastric cancer is gradually discovered. The aim of this study was to explore the expression of ACVR1 in gastric cancer and its clinical significance, to study the relationship between ACVR1 and tumor microenvironment (TME) for the prognosis of gastric cancer, and to further identify new targets for immunotherapy in gastric cancer.Methods:ACVR1 was first selected as a study gene according to several cancer and gastric cancer public datasets. Its pancancer expression was explored using the UCSC Xena database. The expression level, prognosis, and clinicopathological features of ACVR1 in gastric cancer were analyzed using The Cancer Genome Atlas (TCGA) database. Immunohistochemistry (IHC)-based experiments were conducted to study the expression of ACVR1 at the protein level. The IHC data were analyzed for correlations between ACVR1 expression and various clinicopathological factors and prognosis. The correlation of this gene with the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, immune infiltration, immune checkpoints, drug therapy, tumor mutation burden (TMB), microsatellite instability (MSI), and mismatch repair (MMR) system was analyzed using R software.Results:TCGA data showed that the expression of ACVR1 was higher in gastric cancer tissues than in paracancerous tissues. Moreover, the IHC experiments indicated that ACVR1 was upregulated in gastric cancer tissues at the protein level. Both univariate Cox and multivariate Cox results showed that the increase of ACVR1 was closely associated with tumor stage, size, lymph node metastasis, and age. High ACVR1 expression was linked to a poor prognosis of gastric cancer. The results also revealed that ACVR1 was closely related to suppressive immune cells and pathways. Analyses of immune checkpoints, antitumor drug, TMB, and immune microenvironment indicated that ACVR1 had an antitumor immune effect, promoting gastric cancer development and leading to poor immunotherapy.Conclusions:High ACVR1 expression can be used as an independent prognostic factor to predict the prognostic survival of patients with gastric cancer. ACVR1 expression in gastric cancer tissues was significantly correlated with immune infiltration and may thus serve as a potential therapeutic target for gastric cancer immunotherapy.

Objective: To observe the radiological characteristics of Neuronal Intranuclear Inclusion Disease (NIID) on lesion locations and diffusion property using quantitative imaging analysis. Methods: Visual inspection and quantitative analyses were performed on MRI data from 31 retrospectively included patients with NIID. Frequency heatmaps of lesion locations on T2WI and DWI were generated using voxel-wise analysis. Gray matter volume (GMV), white matter volume (WMV) and diffusion property of apparent diffusion coefficient (ADC) values of patients were voxel-wisely compared with healthy controls. Moreover, the ADC values within the DWI-detected lesion were compared with those within the adjacent cortical gray matter and white matter. Voxel-based lesion symptom mapping (VLSM) techniques, were used to determine the relationship between DWI lesion location and disease durations. Results: By visual inspection on the imaging findings, we proposed an "cockscomb flower sign" for describing the radiological feature of DWI hyperintensity within the corticomedullary junction. A "T2WI-DWI mismatch of spatial distribution" pattern was also revealed with visual inspection and frequency heatmaps, for describing the feature of a wider lesion distribution covering white matter shown on T2WI than that on DWI. Voxelbased morphometry comparison revealed that wildly reduced GMV and WMV, both the lesion areas detected by DWI and T2WI demonstrated ADC increase in patients. Furthermore, the ADC values within the DWIdetected lesion were intermediate between the adjacent cortex and the deep white matter with highest ADC. VLSM analysis revealed that frontal lobe, parietal lobe and internal capsule damage were associated with higher NIID durations. Conclusion: NIID features with "cockscomb flower-like" DWI hyperintensity in area of corticomedullary junction, based on a "T2WI-DWI mismatch of spatial distribution" of lesion locations. The pathological substrate of corticomedullary junction hyperintensity on DWI, can not be explained as diffusion restriction. These typical radiological features of brain MRI would be helpful for diagnosis of NIID. (c) 2023 Elsevier Masson SAS. All rights reserved.

目的 观察弥散峰度成像(DKI)评估慢性肾小球肾炎(CGN)患者肾功能及病理损伤程度的价值.方法 对46例经肾活检确诊的CGN患者[27例慢性肾脏病(CKD)1～2级(CGN轻度损伤组)、19例CKD 3～4级(CGN中重度损伤组)]及19名健康志愿者(对照组)采集肾DKI,比较3组间肾皮、髓质平均弥散峰度(MK)和平均弥散系数(MD)的差异,以及各组内肾皮质与髓质MK和MD的差异,分析CGN患者肾脏MK和MD与肾功能指标[估算肾小球滤过率(eGFR)和胱抑素C]及肾脏损伤病理积分的相关性;绘制受试者工作特征(ROC)曲线,计算曲线下面积(AUC),评估肾脏MK及MD鉴别不同程度损伤CGN的效能.结果 随肾损伤程度加重,肾皮髓质MK均升高、MD均降低(P均＜0.01).各组内肾皮质MD均高于、MK均低于髓质(P均＜0.01).肾脏MK与胱抑素C及肾脏损伤病理积分呈正相关、与eGFR呈负相关(P均＜0.05),肾脏MD与胱抑素C及肾脏损伤病理积分呈负相关、与eGFR呈正相关(P均＜0.05).肾脏皮髓质MK和MD鉴别轻度与中重度损伤CGN的AUC为0.731～0.840.结论 DKI能无创、定量评估CGN患者肾功能和病理损伤程度.

Purpose:Current reports of adenoid cystic carcinoma of the head and neck (ACC) are all case reports, and there is no basilar summary of its imaging findings. This study aims to summarise ACC's computed tomography (CT) and magnetic resonance imaging (MRI) findings to improve radiologists' knowledge of this disease.Methods:We collected clinical and imaging data of patients with ACC during the last decade, and two radiologists retrospectively analysed the imaging characteristics.Results:Of the 16 patients included, six were able to self-perceive bulkiness, and 11 had regional pain. Tumour morphology was regular in six cases, with clear borders in 11 cases, invasion of the surrounding bony mass in 12 cases, and invasion of peripheral nerves in 15 cases. CT mostly shows an irregular soft-tissue density mass with mild-to-moderate enhancement after contrast medium administration. On MRI, the ACC showed isointense or hypointense signals on T1-weighted images (T1WI) and hyperintense or slightly hyperintense signals on T2-weighted images (T2WI). All signals were markedly enhanced after gadolinium enhancement.Conclusions:ACC often has an irregular morphology, sometimes with a cystic component, enhancement on enhancement scans, easy destruction of adjacent bone, and invasion of peripheral nerves. The diagnosis should be considered when these features are encountered in clinical practice.

Background The primary objective of the research was to develop a method using radiomics-based computed tomography (CT) to predict muscle invasion in bladder cancer (BCa) before surgery. Methods A total of 269 patients with bladder cancer were divided into two groups; training group (n = 188 cases) and validation group (n = 81 cases). Radiomics characteristics were determined by analyzing the CT images of each patient. The least absolute shrinkage and selection operator (LASSO) technique was used for developing a radiomics signature. Furthermore, logistic regression (LR), the support vector machine (SVM), decision tree (DT), and Artificial Neural Network (ANN) models were applied to differentiate between non-muscle-invasive bladder cancer (NMIBC) and muscle-invasive bladder cancer (MIBC). Their performance was determined using the area under the receiver operating characteristic curve (AUC-ROC). In addition, accuracy, specificity, and sensitivity evaluations were also conducted. Results The radiomics signature was found to be successful in its prediction. A total of 1036 radiomics features were found in the 269 patients, and out of those, 16 were selected as the best predictors of radiomics features. The results revealed that the ANN classifier had the best performance, with a validation set accuracy of 0.950. Conclusions The current work used machine learning and radiomics techniques to successfully construct a prediction model for muscle invasion in bladder cancer. The ANN model produced significant outcomes that may be used in clinical diagnosis or therapy.

目的 探讨基于增强CT的影像组学及临床血生化资料用于预测食管鳞状细胞癌(ESCC)术前T分期的可行性.方法 回顾性分析经病理证实的ESCC患者资料,手工勾画感兴趣区(ROI)并提取影像组学特征,特征降维后构建逻辑回归模型并计算影像组学评分(Radscore).使用逻辑回归分析临床资料后联合Radscore构建模型判断食管癌T分期.结果 共146例纳入研究,T3～T4a期患者71例.临床资料分析显示平均血小板体积(MPV)是ESCC患者进展至T3、T4a分期的独立危险因素.受试者工作特征(ROC)曲线的曲线下面积(AUC)分别为0.66,0.85(DeLong检验,P=0.022),决策曲线分析(DCA)显示联合模型的临床应用价值更优.结论 影像组学特征有望成为潜在的影像生物标志物,作为临床资料的有益补充,建立联合模型用于手术前评估ESCC患者T分期,为临床制订个性化治疗方案提供定量参考信息.