Accelerated 3D MR neurography of the brachial plexus using deep learning-constrained compressed sensing.

Objectives: To explore the use of deep learning-constrained compressed sensing (DLCS) in improving image quality and acquisition time for 3D MRI of the brachial plexus.

Methods: Fifty-four participants who underwent contrast-enhanced imaging and forty-one participants who underwent unenhanced imaging were included. Sensitivity encoding with an acceleration of 2 × 2 (SENSE4x), CS with an acceleration of 4 (CS4x), and DLCS with acceleration of 4 (DLCS4x) and 8 (DLCS8x) were used for MRI of the brachial plexus.

Cardiac magnetic resonance T1 mapping for evaluating myocardial fibrosis in patients with type 2 diabetes mellitus: correlation with left ventricular longitudinal diastolic dysfunction.

Objectives: We aimed to evaluate myocardial fibrosis using cardiac magnetic resonance (CMR) T1 mapping in type 2 diabetes mellitus (T2DM) patients and investigate the association between left ventricular (LV) subclinical myocardial dysfunction and myocardial fibrosis.

Methods: The study included 37 short-term (≤ 5 years) and 44 longer-term (> 5 years) T2DM patients and 41 healthy controls. The LV global strain parameters and T1 mapping parameters were compared between the abovementioned three groups.

Distinguishing Cardiac Amyloidosis and Hypertrophic Cardiomyopathy by Thickness and Myocardial Deformation of the Right Ventricle.

Objectives: To compare right ventricular thickness (RVT) and deformation of cardiac amyloidosis (CA) and hypertrophic cardiomyopathy (HCM) patients.

Methods: Sixty CA (mean age 58 ± 10 years; 33 males (55%)) and sixty HCM patients (mean age 55 ± 14 years; 27 males (45%)) were retrospectively enrolled. RVT, global radical peak strain (GRPS), global longitudinal peak strain (GLPS), and global circumferential peak stain (GCPS) were analyzed.

Association Between Heart Failure With Preserved Left Ventricular Ejection Fraction and Impaired Left Atrial Phasic Function in Hypertrophic Cardiomyopathy: Evaluation by Cardiac MRI Feature Tracking.

Background: The majority of heart failure (HF) in hypertrophic cardiomyopathy (HCM) manifests as a phenotype with preserved left ventricular (LV) ejection fraction; however, the exact contribution of left atrial (LA) phasic function to HF with preserved ejection fraction (HFpEF) in HCM remains unresolved.

Purpose: To define the association between LA function and HFpEF in HCM patients using cardiac magnetic resonance imaging (MRI) feature tracking.

Study Type: Retrospective.

[Early Assessment of Myocardial Fibrosis of Hypertrophic Cardiomyopathy with Native-T1-Mapping-Based Deep Learning: A Preliminary Study].

Objective: To explore the diagnostic performance of deep learning (DL) model in early detection of the interstitial myocardial fibrosis using native T1 maps of hypertrophic cardiomyopathy (HCM) without late gadolinium enhancement (LGE).

Methods: Sixty HCM patients and 44 healthy volunteers who underwent cardiac magnetic resonance were enrolled in this study. Each native T1 map was labeled according to its LGE status.

[Application of Deep Learning Reconstruction Algorithm in Low-Dose Thin-Slice Liver CT of Healthy Volunteers].

Objective: To explore the clinical feasibility of applying deep learning (DL) reconstruction algorithm in low-dose thin-slice liver CT examination of healthy volunteers by comparing the reconstruction algorithm based on DL, filtered back projection (FBP) reconstruction algorithm and iterative reconstruction (IR) algorithm.

Methods: A standard water phantom with a diameter of 180 mm was scanned, using the 160 slice multi-detector CT scanning of United Imaging Healthcare, to compare the noise power spectrums of DL, FBP and IR algorithms. 100 healthy volunteers were prospectively enrolled, with 50 assigned to the normal dose group (ND) and 50 to the low dose group (LD).

Automatic machine learning based on native T1 mapping can identify myocardial fibrosis in patients with hypertrophic cardiomyopathy.

Objectives: To investigate the feasibility of automatic machine learning (autoML) based on native T1 mapping to predict late gadolinium enhancement (LGE) status in hypertrophic cardiomyopathy (HCM).

Methods: Ninety-one HCM patients and 44 healthy controls who underwent cardiovascular MRI were enrolled. The native T1 maps of HCM patients were classified as LGE ( +) or LGE (-) based on location-matched LGE images.

[Application of Automated Machine Learning Based on Radiomics Features of T2WI and RS-EPI DWI to Predict Preoperative T Staging of Rectal Cancer].

Objective: To explore the radiomics features of T2 weighted image (T2WI) and readout-segmented echo-planar imaging (RS-EPI) plus difusion-weighted imaging (DWI), to develop an automated mahchine-learning model based on the said radiomics features, and to test the value of this model in predicting preoperative T staging of rectal cancer.

Methods: The study retrospectively reviewed 131 patients who were diagnosed with rectal cancer confirmed by the pathology results of their surgical specimens at West China Hospital of Sichuan University between October, 2017 and December, 2018. In addition, these patients had preoperative rectal MRI.

Increased oxygenation is associated with myocardial inflammation and adverse regional remodeling after acute ST-segment elevation myocardial infarction.

Objectives: To explore the relationships between oxygenation signal intensity (SI) with myocardial inflammation and regional left ventricular (LV) remodeling in reperfused acute ST-segment elevation myocardial infarction (STEMI) using oxygenation-sensitive cardiovascular magnetic resonance (OS-CMR).

Methods: Thirty-three STEMI patients and 22 age- and sex-matched healthy volunteers underwent CMR. The protocol included cine function, OS imaging, precontrast T1 mapping, T2 mapping, and late gadolinium enhancement (LGE) imaging.

[Application of MRI-based Radiomics Models in the Assessment of Hepatic Metastasis of Rectal Cancer].

Obejective: To explore the clinical value of using radiomics models based on different MRI sequences in the assessment of hepatic metastasis of rectal cancer.

Methods: 140 patients with pathologically confirm edrectal cancer were included in the study. They underwent baseline magnetic resonance imaging (MRI) between April 2015 and May 2018 before receiving any treatment.

[The Clinical Effectiveness of Neural Network-based Boundary Recognition of Upper Abdominal Organs on CT Images].

Objective: To assess the clinical effectiveness of boundary recognition of upper abdomen organs on CT images based on neural network model and the combination of different slices.

Methods: A total of 2 000 patients who underwent upper abdomen enhanced CT scans from March 2018 to March 2019 were included in the study. The quality of the CT images met the requirements for clinical diagnosis.

[A Preliminary Study of Applying Geometric Deep Learning in Brain Morphometry for Diagnosis of Alzheimer's Disease].

Objective: A predictive model of Alzheimer's disease (AD) was established based on brain surface meshes and geometric deep learning, and its performance was evaluated.

Methods: Seventy-six clinically diagnosed AD patients and 83 healthy older adults were enrolled and randomly assigned to the training set and the test set according to a 4-to-1 ratio. Brain surface mesh was constructed from 3-D T1-weighted high-resolution structural MR volumes of each participant.

[The Application Value of Artificial Intelligence-based Filtering and Interpolated Image Reconstruction Algorithm in Abdominal Magnetic Resonance Image Denoising].

Objective: To compare the noise reduction performance of conventional filtering and artificial intelligence-based filtering and interpolation (AIFI) and to explore for optimal parameters of applying AIFI in the noise reduction of abdominal magnetic resonance imaging (MRI).

Methods: Sixty patients who underwent upper abdominal MRI examination in our hospital were retrospectively included. The raw data of T1-weighted image (T1WI), T2-weighted image (T2WI), and dualecho sequences were reconstructed with two image denoising techniques, conventional filtering and AIFI of different levels of intensity.

[Noise Reduction Effect of Deep-learning-based Image Reconstruction Algorithms in Thin-section Chest CT].

Objective: To evaluate the noise reduction effect of deep learning-based reconstruction algorithms in thin-section chest CT images by analyzing images reconstructed with filtered back projection (FBP), adaptive statistical iterative reconstruction (ASIR), and deep learning image reconstruction (DLIR) algorithms.

Methods: The chest CT scan raw data of 47 patients were included in this study. Images of 0.

Characterization of infarcted myocardium by T1-mapping and its association with left ventricular remodeling.

Purpose: Acutely infarcted native T1 (native T1) and extracellular volume (ECV) could quantify myocardial injury after acute myocardial infarction (AMI). Therefore, we sought to further explore their association with left ventricular (LV) remodeling during follow-up.

Methods: 56 ST-segment-elevation MI patients were prospectively recruited and completed acute and 3-month cardiac magnetic resonance scans.

[Application of 3.0T Time-of-flight Magnetic Resonance Angiography with Sparse Undersampling and Iterative Reconstruction in the Diagnosis of Unruptured Intracranial Aneurysms].

Objective: To evaluate the diagnostic value of 3.0T time-of-flight MR angiography with sparse undersampling and iterative reconstruction (TOFu-MRA) for unruptured intracranial aneurysms (UIAs) on the basis of using digital subtraction angiography (DSA) as the reference standard.

Methods: A total of 65 patients with suspected UIAs were prospectively enrolled and all patients underwent TOFu-MRA and DSA.

Noninvasive oxygenation assessment after acute myocardial infarction with breathing maneuvers-induced oxygenation-sensitive magnetic resonance imaging.

The safety profiles when performing stress oxygenation-sensitive magnetic resonance imaging (OS-MRI) have raised concerns in clinical practice. Adenosine infusion can cause side effects such as chest pain, dyspnea, arrhythmia, and even cardiac death. The aim of this study was to investigate the feasibility of breathing maneuvers-induced OS-MRI in acute myocardial infarction (MI).

Retraction Note: Prognostic value of heart failure in hemodialysis-dependent end-stage renal disease patients with myocardial fibrosis quantification by extracellular volume on cardiac magnetic resonance imaging.

An amendment to this paper has been published and can be accessed via the original article.

Assessment of left ventricular deformation in patients with type 2 diabetes mellitus by cardiac magnetic resonance tissue tracking.

To quantify the global and regional left ventricular (LV) myocardial strain in type 2 diabetes mellitus (T2DM) patients using cardiac magnetic resonance (CMR) tissue-tracking techniques and to determine the ability of myocardial strain parameters to assessment the LV deformation. Our study included 98 adult T2DM patients (preserved LV ejection fraction [LVEF], 72; reduced LVEF, 26) and 35 healthy controls. Conventional LV function, volume-time curve parameters and LV remodeling index were measured using CMR.

The combined effects of cardiac geometry, microcirculation, and tissue characteristics on cardiac systolic and diastolic function in subclinical diabetes mellitus-related cardiomyopathy.

Background: Diabetes mellitus-related cardiomyopathy has recently been described as a distinct progression of left ventricular (LV) systolic and diastolic dysfunction. Pathological changes in the myocardium may explain the development of two different phenotypes. We evaluated the effects of LV geometry, myocardial microcirculation, and tissue characteristics on cardiac deformation in patients with subclinical type 2 diabetes mellitus (T2DM) utilizing multiparametric cardiac magnetic resonance (CMR) imaging.

Multi-modal radiomics model to predict treatment response to neoadjuvant chemotherapy for locally advanced rectal cancer.

Background: Neoadjuvant chemotherapy is currently recommended as preoperative treatment for locally advanced rectal cancer (LARC); however, evaluation of treatment response to neoadjuvant chemotherapy is still challenging.

Aim: To create a multi-modal radiomics model to assess therapeutic response after neoadjuvant chemotherapy for LARC.

Methods: This retrospective study consecutively included 118 patients with LARC who underwent both computed tomography (CT) and magnetic resonance imaging (MRI) before neoadjuvant chemotherapy between October 2016 and June 2019.

The prognostic value of right ventricular deformation derived from cardiac magnetic resonance tissue tracking for all-cause mortality in light-chain amyloidosis patients.

Background: Early detection of right ventricular (RV) dysfunction is vital for determining the prognosis of light-chain amyloidosis (AL) patients. While few studies focused on RV deformation due to the limitation of research methods. The aim of this study was to determine the prognostic significance of RV myocardial strain in AL patients assessed by cardiac magnetic resonance (CMR) tissue tracking.

The additive effects of obesity on myocardial microcirculation in diabetic individuals: a cardiac magnetic resonance first-pass perfusion study.

Background: The microvascular effects of obesity should be considered in diabetic individuals for elucidating underlying mechanisms and developing targeted therapies. This study aims to determine the effect of obesity on myocardial microvascular function in type 2 diabetes mellitus (T2DM) patients using cardiac magnetic resonance (CMR) first-pass perfusion imaging and assessed significant risk factors for microvascular dysfunction.

Materials And Methods: Between September 2016 and May 2018, 120 patients with T2DM (45.

Assessing right ventricular deformation in hypertrophic cardiomyopathy patients with preserved right ventricular ejection fraction: a 3.0-T cardiovascular magnetic resonance study.

To assess the global and regional right ventricular (RV) deformation in hypertrophic cardiomyopathy (HCM) patients with preserved right ventricular ejection fraction (RVEF) using 3.0-T cardiovascular magnetic resonance tissue tracking (CMR-TT). Eighty-two HCM patients and 32 age- and sex-matched healthy controls were enrolled.

Prognostic value of heart failure in hemodialysis-dependent end-stage renal disease patients with myocardial fibrosis quantification by extracellular volume on cardiac magnetic resonance imaging.

Background: End-stage renal disease (ESRD) patients are at high cardiovascular risk, and myocardial fibrosis (MF) accounts for most of their cardiac events. The purpose of this study is to investigate the prognostic value and risk stratification of MF as measured by extracellular volume (ECV) on cardiac magnetic resonance (CMR) for heart failure (HF) in patients with hemodialysis-dependent ESRD.

Methods: Sixty-six hemodialysis ESRD patients and 25 matched healthy volunteers were prospectively enrolled and underwent CMR to quantify multiple parameters of MF by T1 mapping and late gadolinium enhancement (LGE).