OBJECTIVES:This is a protocol for a Cochrane review (prognosis). The objectives are as follows: Primary objective To systematically review and critically appraise multivariable prognostic models developed for adults (≥ 18 years) with carotid stenosis in which imaging biomarkers (e.g. plaque characteristics derived from magnetic resonance imaging (MRI), computed tomography (CT), or ultrasound) constitute the core predictors. The primary focus is to evaluate the predictive performance of these models for cerebrovascular complications - specifically ipsilateral ischaemic stroke and transient ischaemic attack (TIA) - which are the clinical outcomes to be predicted. Where feasible, we will summarise and compare the models' discrimination (C‑statistic/area under the curve (AUC)) and calibration (calibration‑in‑the‑large, calibration slope, observed‑to‑expected ratio) across studies, and assess their potential for clinical application and external validation. For the purpose of defining symptomatic carotid stenosis as an eligibility criterion and subgroup variable, we will include studies that also considered retinal ischaemia (e.g. retinal embolism, amaurosis fugax) as a qualifying event. Secondary objectives To describe the combinations of imaging markers, modelling techniques, sample sizes, and variable‑selection strategies used in the development of the included models To evaluate the performance of these models for additional secondary clinical outcomes: plaque progression or regression, incident high‑risk imaging features, and the transition from asymptomatic to symptomatic disease To explore whether predictive performance differs according to imaging modality (MRI versus CT versus contrast‑enhanced ultrasound (CEUS)) or technical protocol (e.g. 3 T versus 1.5 T, spectral CT versus conventional CT) For studies that report both cerebrovascular and broader cardiovascular outcomes (major adverse cardiovascular events, myocardial infarction, etc.), we will only extract the performance metrics relating to cerebrovascular events for the primary analysis. Performance metrics for cardiovascular outcomes will be considered exploratory and will not form part of the main synthesis.

RATIONALE AND OBJECTIVES:The clinical feature and long-term prognosis of unilateral moyamoya disease (MMD) have not been fully described and studied. The study aimed to investigate independent risk factors for stroke in unilateral MMD patients during a long-term follow-up. MATERIALS AND METHODS:A total of 393 unilateral MMD patients (median age, 40 years) were assessed at baseline and followed for an average time of 68.9 months. Ischemic and hemorrhagic stroke incidence rates were determined. Multiple demographic, clinical and neuroimaging factors at baseline were considered as potential predictors of stroke during the follow-up period. Hazard ratios (HR) and corresponding 95% confidence interval (CI) for stroke were calculated by univariable and multivariable Cox proportional hazards models. Cumulative risk of stroke was estimated by the Kaplan-Meier product-limit method. RESULTS:During the follow-up period, 43 patients experienced stroke events (10.9%). 5 children experienced stroke events (5/46, 10.9%) and 38 adults experienced stroke events (38/347, 11.0%) (P>0.05). 21 patients with encephaloduroarteriosynangiosis (EDAS) experienced stroke events (21/254, 8.3%) and 22 patients with conservative treatment experienced stroke events (22/139, 15.8%) (P<0.05). After adjustment for clinical characteristics, multivariable analysis showed that involvement of posterior cerebral artery (HR, 2.199; 95% CI, 1.100-4.398), decreased cerebral blood flow (CBF) (HR, 2.292; 95% CI, 1.182-4.446) and concentric enhancement of the arterial wall (HR, 3.093; 95% CI, 1.617-5.915) were significantly associated with stroke, and EDAS (HR, 0.385; 95% CI, 0.203-0.730) and compensatory blood supply by anterior communicating artery (HR, 0.413; 95% CI, 0.206-0.830) were protective factors for stroke. CONCLUSION:Involvement of posterior cerebral artery, decreased CBF, concentric enhancement of the arterial wall, EDAS and compensatory blood supply by anterior communicating artery may help stratify the risk of stroke and improve therapeutic decisions in unilateral MMD. Unilateral MMD could benefit from EDAS and have a lower risk of future stroke.

To evaluate the role of vessel wall enhancement in the efficacy of antiplatelet therapy (APT) on reducing the stroke risk in patients with Moyamoya disease (MMD) based on postcontrast MR vessel wall imaging. Consecutive patients with MMD underwent postcontrast MR vessel wall imaging and were divided into APT and non-APT groups according to the prescribed antiplatelet agents. Kaplan−Meier survival and Cox regression analyses were performed to determine the association between APT and stroke risk of patients with MMD, and subgroup analysis was performed to determine the role of vessel wall enhancement in reducing stroke risk after APT. A total of 1262 patients (mean age: 42.6 ± 11.1 years) were finally included for analysis. Compared with patients without APT, those with APT were older (p = 0.023) and had a higher incidence of hypertension (p = 0.015), and with advanced Suzuki stage (≥ IV) (p < 0.001). During an average follow-up of 37.9 months, patients without APT had a marginally greater incidence of cerebrovascular events (12.9

BACKGROUND: Moyamoya disease (MMD) is a cerebrovascular disorder characterized by the progressive stenosis of the intracranial internal carotid artery and the development of a collateral network in the brain. As medical imaging technology and artificial intelligence have advanced, various imaging methods have been widely used in the clinical diagnosis of MMD. In this study, we conducted bibliometric visualization of research papers about MMD and radiological features between 2000 and 2024, intending to explore the development status quo, hotspots, and future developments and contributing to studies on imaging in diagnosis of cerebrovascular diseases. METHODS: The Web of Science Core Collection was chosen as the source of publications for this study. By using VOSviewer and CiteSpace, articles were analyzed in terms of authors, countries, institutions, references, keywords, cited literatures, and so on. RESULTS: We retrieved a collection of 1003 articles that substantiate a progressively ascendant trend in articles over the past 24 years. Japan, South Korea, and China were 3 major countries in this field. China's Capital Medical University was the leader in publication output, followed by Hokkaido University from Japan and Seoul National University from South Korea. The 3 authors with the most publications were Miki Fujimura, Teiji Tominaga, and Dong Zhang. World Neurosurgery was the journal with the most publications (85), while Stroke was the journal with the most cocitations (3305) in this field. Excluding MMD, the top 3 most frequently occurring keywords were "revascularization", "stroke", and "magnetic resonance imaging (MRI)". "High-resolution magnetic resonance imaging (HRMRI)", "digital subtraction angiography (DSA)", and "vessel wall imaging" were the top 3 keywords of recent interest in the field of radiological features. CONCLUSIONS: This article provides a scientific perspective from which researchers, especially doctors in neurosurgery and radiodiagnosis departments can visually find out about important trends and new areas of research directions in the field of MMD and radiological features.

Malignant tumors pose a great threat to human health due to their abnormal vascular system and high interstitial density, leading to high invasiveness and low curability. Tumor vasodilation and ensuring deep drug delivery are essential to elevating tumor elimination efficiency. Herein, a powerful nanoregulator is reported with tumor vessel vasodilation and tumor microenvironment (TME) reconstruction capacity for photoacoustic/magnetic resonance imaging-guided tumor starvation and ferroptosis therapy. This nanoregulator uses ultra-small ferrous sulfide (FeS) nanoparticles as a Fenton agent and hydrogen sulfide (H2S) as a donor. Additionally, glucose oxidase (GOx) serves as a glucose-depleting agent and poly (lactic-co-glycolic) acid (PLGA) functions as a building block. PLGA@ultra-small FeS-GOx nanoregulators can simultaneously promote accumulation and enhance penetration deep into tumors through H2S-induced vasodilation and acid-responsive degradation. Further, the TME can be regulated toward aggravated acidity, hydrogen peroxide up-regulation, glutathione down-regulation, and triphosadenine down-regulation by the released ferrous ion (Fe2+), H2S, and GOx. A large amount of lipid hydroperoxides (LPOs) accumulate in this antioxidant system-disabled microenvironment through the Fe2+-mediated Fenton reaction. In vivo data reveal that this synergistic energy depletion-induced starvation and LPO accumulation-driven ferroptosis efficiently kill tumor cells. This approach can guide the development of nanomedicines with clinical translation potential.

OBJECTIVE:Given the poor prognosis associated with hemorrhagic events in Moyamoya disease (MMD), the early identification of patients at high risk is of paramount importance for improving clinical outcomes. This study aims to explore the predictive value of champagne bottle neck sign (CBNS) at baseline for post-treatment intracranial hemorrhage (ICH) occurrence in adult MMD patients. METHODS:This retrospective analysis included MMD patients without a history of ICH who were recruited from July 2014 to December 2020. All patients underwent preoperative digital subtraction angiography (DSA) and had a median follow-up of 6.5 years (1-10 years) to record ICH occurrence. The DSA features, including choroidal anastomosis and CBNS (ICA/CCA diameter ratio ≤ 0.5), were evaluated. Cox regression analysis was utilized to determine the associations between clinical and DSA characteristics and the occurrence of post-treatment ICH in MMD patients. Subsequently, receiver operating characteristic (ROC) curve analysis was conducted to calculate the area under the curve (AUC) of imaging characteristics in predicting ICH occurrence. RESULTS:Among 74 recruited MMD patients (mean age: 42.5 ± 10.4 years; 35 males), 9 (12.2 %) experienced ICH over up to ten years. Patients who experienced ICH during follow-up had significantly smaller ICA/CCA diameter ratio (0.39 ± 0.10 vs. 0.51 ± 0.12, P = 0.004) and higher CBNS incidence (88.9 % vs. 46.2 %, P = 0.03) at baseline. Multivariate Cox regression analysis demonstrated that choroidal anastomosis (HR = 3.82, 95 % CI: 1.02-14.35, P = 0.047) and CBNS (HR = 9.46, 95 % CI: 1.17-76.47, P = 0.035) were independent predictors of ICH occurrence. ROC analysis revealed that in predicting post-treatment ICH, the AUC value of CBNS was 0.714 (95 %CI: 0.558 - 0.870) to distinguish MMD patients with hemorrhage from those without, P = 0.039). When combined CBNS with choroidal anastomosis, the AUC value reached 0.785 (95 %CI: 0.650 - 0.919). CONCLUSIONS:The CBNS has independent predictive value for risk of post-treatment ICH in adult MMD patients. This study suggests that CBNS might be a useful imaging biomarker for adverse outcome of MMD.

Increasing evidence suggests that non-operative management (NOM) with antibiotics could serve as a safe alternative to surgery for the treatment of uncomplicated acute appendicitis (AA). However, accurately differentiating between uncomplicated and complicated AA remains challenging. Our aim was to develop and validate machine-learning-based diagnostic models to differentiate uncomplicated from complicated AA. This was a multicenter cohort trial conducted from January 2021 and December 2022 across five tertiary hospitals. Three distinct diagnostic models were created, namely, the clinical-parameter-based model, the CT-radiomics-based model, and the clinical-radiomics-fused model. These models were developed using a comprehensive set of eight machine-learning algorithms, which included logistic regression (LR), support vector machine (SVM), random forest (RF), decision tree (DT), gradient boosting (GB), K-nearest neighbors (KNN), Gaussian Naïve Bayes (GNB), and multi-layer perceptron (MLP). The performance and accuracy of these diverse models were compared. All models exhibited excellent diagnostic performance in the training cohort, achieving a maximal AUC of 1.00. For the clinical-parameter model, the GB classifier yielded the optimal AUC of 0.77 (95% confidence interval [CI]: 0.64-0.90) in the testing cohort, while the LR classifier yielded the optimal AUC of 0.76 (95% CI: 0.66-0.86) in the validation cohort. For the CT-radiomics-based model, GB classifier achieved the best AUC of 0.74 (95% CI: 0.60-0.88) in the testing cohort, and SVM yielded an optimal AUC of 0.63 (95% CI: 0.51-0.75) in the validation cohort. For the clinical-radiomics-fused model, RF classifier yielded an optimal AUC of 0.84 (95% CI: 0.74-0.95) in the testing cohort and 0.76 (95% CI: 0.67-0.86) in the validation cohort. An open-access, user-friendly online tool was developed for clinical application. This multicenter study suggests that the clinical-radiomics-fused model, constructed using RF algorithm, effectively differentiated between complicated and uncomplicated AA.

BACKGROUND:Little is known about the association between stroke and imaging and clinical features in conservatively treated patients with moyamoya disease (MMD). PURPOSE:To investigate independent risk factors for stroke in conservatively treated patients with MMD during a long-term follow-up. STUDY TYPE:Prospective study. SUBJECTS:One hundred sixty conservatively managed patients with MMD (median age 46 years, 89 male). FIELD STRENGTH/SEQUENCE:Time of flight, turbo inversion recovery magnitude T1WI, turbo spin echo (TSE) T2WI, echo-planar imaging DWI, T2-fluid attenuated inversion recovery, dynamic susceptibility contrast-magnetic resonance imaging, and pre- and post-contrast 3D TSE T1WI sequences at 3.0 Tesla. ASSESSMENT:Patients were assessed at baseline and followed yearly. Ischemic and hemorrhagic stroke incidence rates were determined. Multiple demographic, clinical (modified Rankin score [mRS]), and cerebral imaging (cerebral blood volume [CBV] and concentric enhancement of arterial wall) factors at baseline were considered as potential predictors of stroke during the follow-up period. STATISTICAL TESTS:Univariable and multivariable Cox proportional hazards models to calculate the hazard ratios (HRs) and corresponding 95% confidence interval (CI) for stroke. Cumulative risk of stroke was estimated by the Kaplan-Meier product-limit method. A P value <0.05 was considered statistically significant. RESULTS:The median follow-up duration was 47 months. During the follow-up period, 18 (11.25%) patients experienced stroke events (13 [8.13%] ischemic, 5 [3.12%] hemorrhagic). Univariable analysis showed that 11 factors were significantly associated with stroke. After adjustment for clinical characteristics, multivariable analysis showed that mRS score ≥3 (HR, 1.99; 95% CI, 1.26-3.14), decreased CBV (HR, 5.31; 95% CI, 2.32-12.13), and concentric enhancement of the arterial wall (HR, 4.16; 95% CI, 1.55-11.15) were significantly associated with stroke. DATA CONCLUSION:Decreased CBV, mRS score ≥ 3, and concentric enhancement of the arterial wall were significantly associated with increased incidence of stroke in conservatively treated MMD. EVIDENCE LEVEL:2 TECHNICAL EFFICACY: Stage 4.

BACKGROUND:The features of intracranial arteries in patients with Moyamoya disease (MMD) have been widely investigated. However, the MR characteristics of extracranial internal carotid artery (EICA) and their effect on outcomes of revascularization treatment are not fully understood. PURPOSE:To investigate the characteristics of EICA and their relationship with outcomes of revascularization treatment in adult patients with MMD based on higher-resolution MRI (HRMRI). STUDY TYPE:Prospective interventional outcomes. SUBJECTS:Two hundred eighty-eight consecutive patients with MMD (mean age: 43.7 ± 11.2 years; 140 male). FIELD STRENGTH/SEQUENCE:Turbo inversion recovery magnitude T1-weighted imaging and turbo spin echo (TSE) T2-weighted imaging, three-dimensional time-of-flight MR angiography, T2-fluid attenuated inversion recovery, and 3D T1-SPACE vessel wall imaging at 3.0 T. ASSESSMENT:The HRMRI characteristics of EICA were determined. The relationship between the characteristics of EICA (proximal stenosis, diffuse wall thickening, carotid plaques, and luminal thrombosis) and stroke outcomes of revascularization treatment in patients with MMD was analyzed. The discriminative ability of EICA characteristics in combination with intracranial carotid artery features (involvement of vessel segments, bilateral involvement, and Suzuki stage) to determine stroke outcomes was compared with that of intracranial artery features alone during a mean 8.0 months follow-up period. STATISTICAL TESTS:Cox proportional hazards models and Kaplan-Meier curves to calculate the hazard ratios (HRs) for stroke with 95% confidence intervals (CIs). Area under the receiver operating characteristic curve (AUC) for assessing discriminative performance. A P value <0.05 was considered statistically significant. RESULTS:During a mean 8.0 ± 2.2 months follow-up, of the 288 participants, 137 had proximal stenosis (47.6%), 106 had diffuse wall thickening (36.8%), 60 had carotid plaques (20.8%), and 27 had luminal thrombosis (9.4%) of EICA. Of these features, proximal stenosis (HR = 2.86; 95% CI = 1.13-7.29) and diffuse wall thickening (HR = 2.62; 95% CI = 1.16-5.94) of EICA were significantly associated with stroke after surgery, before and after adjusting for confounding factors. In discriminating the stroke outcomes after surgery, combining characteristics of EICA with features of intracranial arteries resulted in a significant incremental improvement (DeLong test, P < 0.05) in the AUC over that obtained with features of intracranial arteries alone (AUC: 0.73 vs. 0.60-0.64). CONCLUSION:Proximal stenosis and diffuse wall thickening of EICA were significantly associated with stroke outcomes after surgery in patients with MMD. Our findings suggest that understanding the characteristics of EICA has added value for intracranial vessels in predicting future events after surgery in patients with MMD. EVIDENCE LEVEL:2 TECHNICAL EFFICACY: Stage 4.

目的 探讨脾原发淋巴瘤的MRI表现.方法 回顾性分析2010-01至2019-06解放军总医院第一医学中心符合入选标准的经病理证实为脾原发淋巴瘤患者的临床资料和MRI表现.观察肿瘤信号、坏死、出血、囊变、假包膜、动态增强特点以及周围结构受侵情况.根据病灶单发或多发分为两组,比较两组间的临床资料和病灶MRI影像特征.结果 共收集13例脾原发淋巴瘤患者,脾单发8例,多发5例,共34个病灶.肿瘤T2WI呈等高信号14个(41.2％),低信号20个(58.8％);T1WI呈等低信号30个(88.2％),呈高信号4个(11.8％);扩散加权成像(DWI)呈高信号15个(44.1％),其中不均匀高信号6个(40.0％),等低信号19个(55.9％);肿瘤出现坏死11个(32.4％),出血6个(17.7％),无病灶出现囊变;20个病灶可见假包膜(58.8％),其中11个病灶假包膜不完整(55.0％).MRI动态增强扫描病灶全部呈动脉期轻度强化并逐渐增强.1例(7.7％)伴有胰腺受侵,1例(7.7％)伴有结肠脾曲受侵.其中病灶大小、T2WI信号特点、DWI信号特点以及有无假包膜在两组中有统计学差异(P<0.05).结论 脾原发淋巴瘤,单发病灶直径较大,T2 WI和DWI多呈等高信号,假包膜多见,而多发病灶时T2 WI和DWI多呈低信号,两组病灶在T1 WI多呈等低信号,都可以发生出血和坏死,增强扫描呈轻度渐进性强化.

The development of smart drug delivery systems (SDDSs) based on engineered nanomaterials is important for clinical applications. Nevertheless, controllable administration of chemotherapeutic drugs for deep tumors and the avoidance of side effects caused by off-targeting during delivery remain a great challenge. Herein, a stimulus-responsive system of mesoporous nanospheres (composed of Cu@Fe2C@mSiO(2)) with good magnetothermal effect is introduced into the tumor microenvironment. This system plays an important role in image-guided controllable targeted drug delivery that is independent of tumor depth. Aggregation-induced emission luminogen-based fluorescence imaging and magnetic resonance imaging were utilized since these techniques visualize the delivery process in real time. In addition, the degraded nanocarriers showed high catalytic activity for Fenton and Fenton-like reactions, upregulating the level of hydroxyl radicals (center dot OH) in cancer cells to realize chemodynamic therapy. The induced center dot OH led to the overexpression of pho-STAT3, activating the STAT3 signaling pathway, eventually inducing cancer cell apoptosis. Through metabolic monitoring, this SDDS is removed from the body after its degradation in vivo. The synergistically enhanced therapeutic effect was obtained in the chemo-chemodynamic therapy of 4T1 tumor-bearing mice, offering a platform for efficient cancer therapy with a personalized theranostic strategy. [GRAPHICS] .

目的:分析乳腺单纯型浸润性筛状癌(ICC)MRI及超声影像表现,并与叶状瘤(PTs)鉴别,提高乳腺单纯型ICC的诊断水平.方法:收集解放军总医院第五医学中心经手术病理证实的乳腺单纯型ICC 10 例、PTs 39 例,回顾性分析乳腺单纯型ICC MRI及超声影像表现,并比较单纯型ICC与PTs的不同点.结果:单纯型ICC多表现为边界清楚的分叶状肿块、信号/回声均匀,MRI动态增强扫描延迟期病灶可见中心瘢痕样强化、边缘假包膜强化;PTs多数表现为分叶状肿块,信号/回声大多数不均匀;二者在形态学及超声表现上无统计学差异(P>0.05),在MRI内部信号及强化特征、TIC 曲线及ADC 值有统计学差异(P<0.05).单纯型ICC超声诊断假阴性率 70%,灵敏度 30%,诊断准确率 30%,MRI检查灵敏度 100%,诊断准确率 100%.结论:乳腺ICC是极少见的特殊类型乳腺癌,具有特殊的影像表现,与PTs的影像表现有部分重叠,MRI对乳腺ICC诊断的灵敏度、准确率均高于超声,有助于其与PTs的鉴别诊断.

Biomedical micro/nanorobots as active delivery systems with the features of self-propulsion and controllable navigation have made tremendous progress in disease therapy and diagnosis, detection, and biodetoxification. However, existing micro/nanorobots are still suffering from complex drug loading, physiological drug stability, and uncontrollable drug release. To solve these problems, micro/nanorobots and nanocatalytic medicine as two independent research fields were integrated in this study to achieve self-propulsion-induced deeper tumor penetration and catalytic reaction-initiated tumor therapy in vivo. We presented self-propelled Janus nanocatalytic robots (JNCRs) guided by magnetic resonance imaging (MRI) for in vivo enhanced tumor therapy. These JNCRs exhibited active movement in H2O2 solution, and their migration in the tumor tissue could be tracked by non-invasive MRI in real time. Both increased temperature and reactive oxygen species production were induced by near-infrared light irradiation and iron-mediated Fenton reaction, showing great potential for tumor photothermal and chemodynamic therapy. In comparison with passive nanoparticles, these self-propelled JNCRs enabled deeper tumor penetration and enhanced tumor therapy after intratumoral injection. Importantly, these robots with biocompatible components and byproducts exhibited biosecurity in the mouse model. It is expected that our work could promote the combination of micro/nanorobots and nanocatalytic medicine, resulting in improved tumor therapy and potential clinical transformations.

RATIONALE AND OBJECTIVES:To explore the differential diagnosis of benign and malignant papillary neoplasms on MRI with non-mass enhancement. MATERIALS AND METHODS:A total of 48 patients with surgically confirmed papillary neoplasms showing non-mass enhancement were included. Clinical findings, mammography and MRI features were retrospectively analyzed, and lesions were described according to the breast imaging report and data system (BI-RADS). Multivariate analysis of variance was used to compare the clinical and imaging features of benign and malignant lesions. RESULTS:Fifty-three papillary neoplasms were shown on MR images with non-mass enhancement, including 33 intraductal papilloma and 20 papillary carcinomas (9 intraductal papillary carcinoma, 6 solid papillary carcinomas, and 5 invasive papillary carcinoma). Mammography showed amorphous calcification in 20% (6/30), of which 4 were in papilloma and 2 were in papillary carcinoma. On MRI, papilloma mostly showed linear distribution in 54.55% (18/33), clumped enhancement in 36.36% (12/33). Papillary carcinoma showed segmental distribution in 50% (10/20), clustered ring enhancement in 75% (15/20). ANOVA showed age (p = 0.025), clinical symptoms (p < 0.001), apparent diffusion coefficient (ADC) value (p = 0.026), distribution pattern (p = 0.029) and internal enhancement pattern (p < 0.001) were statistically significant between benign and malignant of papillary neoplasms. Multivariate analysis of variance suggested that the internal enhancement pattern was the only statistically significant factor (p = 0.010). CONCLUSIONS:Papillary carcinoma on MRI with non-mass enhancement mostly showed internal clustered ring enhancement, while papilloma mostly showed internal clumped enhancement; additional mammography is of limited diagnostic value, and suspected calcification occurs mostly in papilloma.

OBJECTIVES:To evaluate the diagnostic performance of high-resolution magnetic resonance-vessel wall imaging (HRMR-VWI) in differentiating moyamoya disease (MMD) from atherosclerosis-associated moyamoya vasculopathy (AS-MMV) and investigate an accurate approach for the differential diagnosis.METHODS:Adult patients who were diagnosed as MMD or AS-MMV and underwent HRMR-VWI were retrospectively included. The three vessel wall features (outer diameter (OD), remodeling index (RI), and pattern of vessel wall thickening) of middle cerebral artery (MCA) in identifying MMD from AS-MMV were assessed and compared. Furthermore, subgroup analysis stratified by degree of luminal stenosis was performed and the cutoff values of different vessel wall features in differentiating MMD from AS-MMV were also calculated.RESULTS:A total of 265 patients (160 cases of MMD and 105 AS-MMV) were included. Patients with AS-MMV had greater OD and RI and were more likely to exhibit eccentric thickening of vessel wall compared to those with MMD (all p < 0.001). The ROC analysis showed that the AUC value of OD was greater than that of RI (0.912 vs. 0.889, p = 0.007) in differentiating MMD from AS-MMV, and their corresponding cutoff values were 1.77 mm and 0.27, respectively. And the AUC value of pattern of vessel wall thickening was 0.786 in non-occluded patients. With the increase of lumen stenosis, the discrimination power of the three indicators enhanced correspondingly.CONCLUSIONS:HRMR-VWI is valuable in distinguishing MMD from AS-MMV. The OD of MCA has better diagnostic performance in differentiating AS-MMV from MMD compared to RI and pattern of vessel wall thickening.CLINICAL RELEVANCE STATEMENT:The outer diameter of the involved artery proved to be both accurate and convenient in distinguishing atherosclerosis-associated moyamoya vasculopathy from moyamoya disease and may provide a quantitative reference for clinical diagnosis.KEY POINTS:High-resolution magnetic resonance-vessel wall imaging is valuable in distinguishing atherosclerosis-associated moyamoya vasculopathy from moyamoya disease. Compared to remodeling index and pattern of vessel wall thickening, outer diameter is more accurate in differentiating atherosclerosis-associated moyamoya vasculopathy from moyamoya disease. With the increase of lumen stenosis, the discrimination power of outer diameter, remodeling index, and pattern of vessel wall thickening enhanced correspondingly.

The ferroptosis pathway is recognized as an essential strategy for tumor treatment. However, killing tumor cells in deep tumor regions with ferroptosis agents is still challenging because of distinct size requirements for intratumoral accumulation and deep tumor penetration. Herein, intelligent nanocapsules with size-switchable capability that responds to acid/hyperthermia stimulation to achieve deep tumor ferroptosis are developed. These nanocapsules are constructed using poly(lactic-co-glycolic) acid and Pluronic F127 as carrier materials, with Au-Fe2 C Janus nanoparticles serving as photothermal and ferroptosis agents, and sorafenib (SRF) as the ferroptosis enhancer. The PFP@Au-Fe2 C-SRF nanocapsules, designed with an appropriate size, exhibit superior intratumoral accumulation compared to free Au-Fe2 C nanoparticles, as evidenced by photoacoustic and magnetic resonance imaging. These nanocapsules can degrade within the acidic tumor microenvironment when subjected to laser irradiation, releasing free Au-Fe2 C nanoparticles. This enables them to penetrate deep into tumor regions and disrupt intracellular redox balance. Under the guidance of imaging, these PFP@Au-Fe2 C-SRF nanocapsules effectively inhibit tumor growth when exposed to laser irradiation, capitalizing on the synergistic photothermal and ferroptosis effects. This study presents an intelligent formulation based on iron carbide for achieving deep tumor ferroptosis through size-switchable cascade delivery, thereby advancing the comprehension of ferroptosis in the context of tumor theranostics.

Background:There is an urgent need to find an effective and accurate method for triaging coronavirus disease 2019 (COVID-19) patients from millions or billions of people. Therefore, this study aimed to develop a novel deep-learning approach for COVID-19 triage based on chest computed tomography (CT) images, including normal, pneumonia, and COVID-19 cases.Methods:A total of 2,809 chest CT scans (1,105 COVID-19, 854 normal, and 850 non-3COVID-19 pneumonia cases) were acquired for this study and classified into the training set (n = 2,329) and test set (n = 480). A U-net-based convolutional neural network was used for lung segmentation, and a mask-weighted global average pooling (GAP) method was proposed for the deep neural network to improve the performance of COVID-19 classification between COVID-19 and normal or common pneumonia cases.Results:The results for lung segmentation reached a dice value of 96.5% on 30 independent CT scans. The performance of the mask-weighted GAP method achieved the COVID-19 triage with a sensitivity of 96.5% and specificity of 87.8% using the testing dataset. The mask-weighted GAP method demonstrated 0.9% and 2% improvements in sensitivity and specificity, respectively, compared with the normal GAP. In addition, fusion images between the CT images and the highlighted area from the deep learning model using the Grad-CAM method, indicating the lesion region detected using the deep learning method, were drawn and could also be confirmed by radiologists.Conclusions:This study proposed a mask-weighted GAP-based deep learning method and obtained promising results for COVID-19 triage based on chest CT images. Furthermore, it can be considered a convenient tool to assist doctors in diagnosing COVID-19.

Objectives We aimed to compare the long-term outcomes and surgical benefits between moyamoya disease (MMD) and atherosclerosis-associated moyamoya vasculopathy (AS-MMV) using high-resolution MRI (HRMRI). Methods MMV patients were retrospectively included and divided into the MMD and AS-MMV groups according to vessel wall features on HRMRI. Kaplan-Meier survival and Cox regression were performed to compare the incidence of cerebrovascular events and prognosis of encephaloduroarteriosynangiosis (EDAS) treatment between MMD and AS-MMV. Results Of the 1173 patients (mean age: 42.4±11.0 years; male: 51.0%) included in the study, 881 were classified into the MMD group and 292 into the AS-MMV group. During the average follow-up of 46.0±24.7 months, the incidence of cerebrovascular events in the MMD group was higher compared with that in the AS-MMV group before (13.7% vs 7.2%; HR 1.86; 95% CI 1.17 to 2.96; p=0.008) and after propensity score matching (6.1% vs 7.3%; HR 2.24; 95% CI 1.34 to 3.76; p=0.002). Additionally, patients treated with EDAS had a lower incidence of events than those not treated with EDAS, regardless of whether they were in the MMD (HR 0.65; 95% CI 0.42 to 0.97; p=0.043) or AS-MMV group (HR 0.49; 95% CI 0.51 to 0.98; p=0.048). Conclusions Patients with MMD had a higher risk of ischaemic stroke than those with AS-MMV, and patients with both MMD and AS-MMV could benefit from EDAS. Our findings suggest that HRMRI could be used to identify those who are at a higher risk of future cerebrovascular events.

目前医学领域关注的重点已经转移到细胞和分子水平.磁共振成像(MRI)作为一种能获得清晰的解剖信息的成像技术,对于分子成像其敏感度还远远不够.作为对比剂的超顺磁性纳米材料具有低毒性、多功能性、良好的生物相容性和在外加磁场下的定向移动等性质,显著提高了MRI在分子成像中的价值,在某些生物化学过程方面显示出巨大的潜力,基于可修饰性和稳定性,通过化学修饰可以与一些生物大分子或者体内细胞结合,形成聚合载体,从而牢固地吸附在有机分子的结构体内.如何利用这些材料进行无创可视化诊断和治疗是现在所面临的一个挑战.本综述介绍了超顺磁性纳米材料在分子影像学研究原发肿瘤、转移性淋巴结、免疫系统及干细胞、移植和炎症方面的进展,证明了其在分子影像研究领域的广泛应用和为精准医疗提供的新方向,阐述了目前的进展和存在的一些问题.

Objective The aim of the study is to demonstrate whether radiomics based on an automatic segmentation method is feasible for predicting molecular subtypes. Methods This retrospective study included 516 patients with confirmed breast cancer. An automatic segmentation—3-dimensional UNet-based Convolutional Neural Networks, trained on our in-house data set—was applied to segment the regions of interest. A set of 1316 radiomics features per region of interest was extracted. Eighteen cross-combination radiomics methods—with 6 feature selection methods and 3 classifiers—were used for model selection. Model classification performance was assessed using the area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, and specificity. Results The average dice similarity coefficient value of the automatic segmentation was 0.89. The radiomics models were predictive of 4 molecular subtypes with the best average: AUC = 0.8623, accuracy = 0.6596, sensitivity = 0.6383, and specificity = 0.8775. For luminal versus nonluminal subtypes, AUC = 0.8788 (95% confidence interval [CI], 0.8505–0.9071), accuracy = 0.7756, sensitivity = 0.7973, and specificity = 0.7466. For human epidermal growth factor receptor 2 (HER2)–enriched versus non-HER2–enriched subtypes, AUC = 0.8676 (95% CI, 0.8370–0.8982), accuracy = 0.7737, sensitivity = 0.8859, and specificity = 0.7283. For triple-negative breast cancer versus non–triple-negative breast cancer subtypes, AUC = 0.9335 (95% CI, 0.9027–0.9643), accuracy = 0.9110, sensitivity = 0.4444, and specificity = 0.9865. Conclusions Radiomics based on automatic segmentation of magnetic resonance imaging can predict breast cancer of 4 molecular subtypes noninvasively and is potentially applicable in large samples.