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Our study aimed to comprehensively investigate the age of onset, magnetic resonance imaging (MRI) features, and prognosis of children with trilateral retinoblastoma (TRB).

We included 14 patients with TRB diagnosed or followed up in our hospital. The age of onset and MRI features of the intraocular tumor and intracranial lesions were evaluated. A follow-up study was also conducted.

A total of 11 participants were diagnosed with concurrent TRB at the age of 11.1±7.4 months, and 3 participants had late-onset TRB at age 37±19.1 months. The incidence of TRB with unilateral eye involvement was 7.1% (1/14). The intraocular tumors showed intense enhancement in contrast-enhanced T1-weighted images (WI) and significant diffusion restriction in diffusion WI (DWI) with an apparent diffusion coefficient (ADC) of (0.619±0.22)×10

mm

/s. The intracranial lesions showed similar DWI aspects with an ADC value of (0.680±0.206)×10

mm

/s. Therapeutically, 8 participants had a period of intraocular tumor stabilization e is necessary for screening later-onset TRB patients.

The choice of surgical treatment for meningiomas is affected by the subtype and clinical characteristics. Therefore, an accurate preoperative diagnosis is essential. Current magnetic resonance imaging (MRI) technology is unable to distinguish between meningioma subtypes. In the present study, we compared and evaluated the utility of conventional MRI, magnetic resonance fingerprinting (MRF), and diffusion-weighted imaging (DWI) in differentiating World Health Organization grade I transitional and fibrous meningiomas from meningothelial meningiomas.

Forty-six patients with pathologically confirmed meningiomas (15 meningothelial, 18 transitional, and 13 fibrous) were enrolled in the present study. All patients underwent conventional MRI, MRF, and DWI scans before surgery using a 3T scanner. The Jonckheere-Terpstra test was used to analyze differences in the signal and enhancement characteristics of the three groups from T

-weighted imaging (T1WI) and T

-weighted imaging (T2WI). To investigate the differencnal and fibrous meningiomas. There were also no statistically significant differences in the conventional MRI (including T1WI, T2WI, and contrast-enhanced T1WI) and ADC values between the three meningioma subtypes (all P>0.05).

MRF may provide more quantitative information than either conventional MRI or DWI for differentiating transitional and fibrous meningiomas from meningothelial meningiomas. T1 and T2 values derived from MRF may distinguish transitional and fibrous meningiomas from meningothelial meningiomas, and the combination of T1 and T2 values provides the highest diagnostic efficacy.

MRF may provide more quantitative information than either conventional MRI or DWI for differentiating transitional and fibrous meningiomas from meningothelial meningiomas. T1 and T2 values derived from MRF may distinguish transitional and fibrous meningiomas from meningothelial meningiomas, and the combination of T1 and T2 values provides the highest diagnostic efficacy.

The treatment of malignant stenosis involving the carina or bronchi is challenging due to complicated anatomy with individual variation, which makes it necessary to customize stents for each patient. Therefore, this study aims to evaluate the feasibility of a novel metallic segmented airway stent customized with the aid of three-dimensional (3D) printing for such cases.

The stents were individually customized with the aid of a 3D printed mold based on computed tomography (CT) images according to the anatomical features of the airway. A segmented design was applied on the junction part of the main stem and the branches to fit the dynamic changes of the carina angle. In 12 patients with airway stenosis caused by malignancies including esophageal cancer (EC) and lung cancer (LC), the stents were implanted. The technical and clinical success of the stenting procedure, Hugh-Jones (HJ) classification, Karnofsky performance status (KPS), and stent-related complications of patients were evaluated.

The stenting procedure was technically successful in all patients, and 11 patients showed significant palliation of dyspnea after stenting. The HJ and KPS classification of patients after stent insertion improved significantly compared with those before stenting (P=0.003 and P=0.006, respectively). During follow-up, granulation tissue proliferation and sputum retention were found in two and four patients, respectively.

This study shows that the implantation of a novel stent designed with the aid of 3D printing is feasible for relieving dyspnea and improving performance status of patients with inoperable malignant stenosis involving the carina or bronchi.

This study shows that the implantation of a novel stent designed with the aid of 3D printing is feasible for relieving dyspnea and improving performance status of patients with inoperable malignant stenosis involving the carina or bronchi.

Cardiovascular magnetic resonance based tissue tracking (CMR-TT) was reported to provide detailed insight into left ventricular (LV) contractile function and deformation with both of two- and three-dimensional (2/3D) algorithms. learn more This study was designed to investigate the feasibility and reproducibility of these two techniques for measuring LV global and segmental strain, and establish gender- and age-related reference values of global multi-dimensional peak strains among large healthy population.

We retrospectively recruited 150 healthy volunteers (75 males/females) and divided them into three age groups (G

, G

and G

). LV global mean and peak strains as well as segmental strains in radial, circumferential and longitudinal directions were derived from post-hoc 2/3D CMR-TT analysis of standard steady-state free precession (SSFP) cine images acquired at 1.5T field strength.

Both 2D and 3D CMR-TT modalities enable the tracking of LV myocardial tissues and generate global and segmental strain data. By cion, especially at the global level. The establishment of specific reference values of LV global and segmental systolic strains and the investigation of dimension-, gender- and age-related differences provide a fundamental insight into the features of LV contraction and works as an essential step in clinical routine.

CMR-TT is a feasible and reproducible technique for assessing LV myocardial deformation, especially at the global level. The establishment of specific reference values of LV global and segmental systolic strains and the investigation of dimension-, gender- and age-related differences provide a fundamental insight into the features of LV contraction and works as an essential step in clinical routine.

Non-invasive left ventricular (LV) pressure-strain loops (PSLs), which are generated by combining LV longitudinal strain with brachial artery blood pressure, provide a novel method of quantifying global and segmental myocardial work (MW) indices with potential advantages over conventional echocardiographic strain data, which suffers from being load-dependent. This method has been recently introduced in echocardiographic software, enhancing the efficiency of MW calculations. This study aimed to evaluate the role of non-invasive MW indices derived from LV PSLs in predicting cardiac resynchronization therapy (CRT) response.

A total of 106 heart failure (HF) patients scheduled for CRT were included in the MW analysis. Global and segmental (septal and lateral at the mid-ventricular level) MW indices were assessed before CRT and at a 6-month follow-up. Response to CRT was defined as ≥15% reduction in LV end-systolic volume and ≥1 NYHA functional class improvement at 6-month follow-up compared to baseline.

CRT as a reliable complementary tool for guiding patient selection for CRT in clinical practice.

Assessment of MW indices before CRT could identify the marked imbalance in LV MW distribution and can be widely used as a reliable complementary tool for guiding patient selection for CRT in clinical practice.

Recurrence and distant metastasis are still the main problems affecting the long-term prognosis of nasopharyngeal carcinoma (NPC) patients, and may be related to the Ki-67 proliferation status. We therefore explored the potential correlation between Ki-67 proliferation status in NPC with the parameters derived from two imaging techniques three-dimensional pulsed continuous arterial spin labeling (3D pCASL) and intravoxel incoherent motion (IVIM).

Thirty-six patients with pathologically confirmed NPC were included, and the Ki-67 labeling index (LI) was measured by immunohistochemistry. All patients underwent plain and contrast-enhanced magnetic resonance imaging (MRI), IVIM, and 3D pCASL examination. The mean, maximum, and minimum of blood flow (BF), minimum of apparent diffusion coefficient (ADC), pure diffusion coefficient (D), pseudodiffusion coefficient (D*), and perfusion fraction (f) parameters were all measured, and Spearman's correlation analysis was performed to evaluate the relationships between iques that can evaluate perfusion information and perfusion parameters. Our study suggests that 3D pCASL is more effective than IVIM for assessing the proliferation status of NPC, which is beneficial for evaluating the prognosis of patients. Furthermore, BFmax is the best biomarker for distinguishing high from low Ki-67 levels.

In recent years, there was an increasing popularity in applying artificial intelligence in the medical field from computer-aided diagnosis (CAD) to patient prognosis prediction. Given the fact that not all healthcare professionals have the required expertise to develop a CAD system, the aim of this study was to investigate the feasibility of using AutoML Vision, a highly automatic machine learning model, for future clinical applications by comparing AutoML Vision with some commonly used CAD algorithms in the differentiation of benign and malignant breast lesions on ultrasound.

A total of 895 breast ultrasound images were obtained from the two online open-access ultrasound breast images datasets. Traditional machine learning models (comprising of seven commonly used CAD algorithms) with three content-based radiomic features (Hu Moments, Color Histogram, Haralick Texture) extracted, and a convolutional neural network (CNN) model were built using python language. AutoML Vision was trained in Google Cloud Pla83; AUCPR 0.95) based on Cochran's Q test (P>0.05).

In this study, the performance of AutoML Vision was not significantly different from that of Random Forest (the best classifier among traditional machine learning models) and CNN. AutoML Vision showed relatively high accuracy and comparable to current commonly used classifiers which may prompt for future application in clinical practice.

In this study, the performance of AutoML Vision was not significantly different from that of Random Forest (the best classifier among traditional machine learning models) and CNN. AutoML Vision showed relatively high accuracy and comparable to current commonly used classifiers which may prompt for future application in clinical practice.

The aim of this study was to construct a deep convolutional neural network (CNN) model for localization and diagnosis of thyroid nodules on ultrasound and evaluate its diagnostic performance.

We developed and trained a deep CNN model called the Brief Efficient Thyroid Network (BETNET) using 16,401 ultrasound images. According to the parameters of the model, we developed a computer-aided diagnosis (CAD) system to localize and differentiate thyroid nodules. The validation dataset (1,000 images) was used to compare the diagnostic performance of the model using three state-of-the-art algorithms. We used an internal test set (300 images) to evaluate the BETNET model by comparing it with diagnoses from five radiologists with varying degrees of experience in thyroid nodule diagnosis. Lastly, we demonstrated the general applicability of our artificial intelligence (AI) system for diagnosing thyroid cancer in an external test set (1,032 images).

The BETNET model accurately detected thyroid nodules in visualization experiments.