Clinical feasibility of a deep learning approach for conventional and synthetic diffusion-weighted imaging in breast cancer: Qualitative and quantitative analyses.

Purpose: In this study, we aimed to investigate the clinical feasibility of deep learning (DL)-based reconstruction applied to conventional diffusion-weighted imaging (cDWI) and synthetic diffusion-weighted imaging (sDWI) by comparing the DL reconstructions to cDWIs and sDWIs in patients with various breast malignancies.

Methods: We retrospectively analyzed 115 patients with biopsy-proven breast malignancies who underwent breast magnetic resonance imaging from July 2022 to June 2023, including cDWI with b-value of 800 s/mm (cDWI) sDWI with b-value of 1500 s/mm (sDWI), DWI using DL-based reconstruction (DL-DWI) with b-value of 800 s/mm, and synthetic DL-DWI with b-value of 1500 s/mm (DL-DWI and sDL-DWI). Two radiologists independently performed the qualitative analyses using a 5-point Likert scale for all DWI sets.

High-intensity resistance training and collagen supplementation improve patellar tendon adaptations in professional female soccer athletes.

We investigated whether 10 weeks of pre-season soccer training (including high-intensity resistance exercise) with hydrolysed collagen (COL) supplementation would confer greater changes in patellar tendon (PT) mechanical and material properties compared with placebo (PLA) in professional female soccer athletes. Eleven athletes from the first team squad of a Football Association Women's Championship soccer club volunteered to participate in this study (age, 25.7 ± 4.

Thin-slice elbow MRI with deep learning reconstruction: Superior diagnostic performance of elbow ligament pathologies.

Purpose: With the slice thickness routinely used in elbow MRI, small or subtle lesions may be overlooked or misinterpreted as insignificant. To compare 1 mm slice thickness MRI (1 mm MRI) with deep learning reconstruction (DLR) to 3 mm slice thickness MRI (3 mm MRI) without/with DLR, and 1 mm MRI without DLR regarding image quality and diagnostic performance for elbow tendons and ligaments.

Methods: This retrospective study included 53 patients between February 2021 and January 2022, who underwent 3 T elbow MRI, including T2-weighted fat-saturated coronal 3 mm and 1 mm MRI without/with DLR.

Three-dimensional heavily T2-weighted FLAIR in the detection of blood-labyrinthine barrier leakage in patients with sudden sensorineural hearing loss: comparison with T1 sequences and application of deep learning-based reconstruction.

Objective: Blood-labyrinthine barrier leakage has been reported in sudden sensorineural hearing loss (SSNHL). We compared immediate post-contrast 3D heavily T2-weighted fluid-attenuated inversion recovery (FLAIR), T1 spin echo (SE), and 3D T1 gradient echo (GRE) sequences, and heavily T2-weighted FLAIR (hvT2F) with and without deep learning-based reconstruction (DLR) in detecting perilymphatic enhancement.

Methods: Fifty-four patients with unilateral SSNHL who underwent ear MRI with three sequences were included.

Impact of deep learning-based reconstruction and anti-peristaltic agent on the image quality and diagnostic performance of magnetic resonance enterography comparing single breath-hold single-shot fast spin echo with and without anti-peristaltic agent.

Background: While anti-peristaltic agents are beneficial for high quality magnetic resonance enterography (MRE), their use is constrained by potential side effects and increased examination complexity. We explored the potential of deep learning-based reconstruction (DLR) to compensate for the absence of anti-peristaltic agent, improve image quality and reduce artifact. This study aimed to evaluate the need for an anti-peristaltic agent in single breath-hold single-shot fast spin-echo (SSFSE) MRE and compare the image quality and artifacts between conventional reconstruction (CR) and DLR.

Impact of Deep-Learning Based Reconstruction on Single-Breath-Hold, Single-Shot Fast Spin-Echo in MR Enterography for Crohn's Disease.

Purpose: To assess the quality of four images obtained using single-breath-hold (SBH), single-shot fast spin-echo (SSFSE) and multiple-breath-hold (MBH) SSFSE with and without deep-learning based reconstruction (DLR) in patients with Crohn's disease.

Materials And Methods: This study included 61 patients who underwent MR enterography (MRE) for Crohn's disease. The following images were compared: SBH-SSFSE with (SBH-DLR) and without (SBH-conventional reconstruction [CR]) DLR and MBH-SSFSE with (MBH-DLR) and without (MBH-CR) DLR.

The Collagen Synthesis Response to an Acute Bout of Resistance Exercise Is Greater when Ingesting 30 g Hydrolyzed Collagen Compared with 15 g and 0 g in Resistance-Trained Young Men.

Background: Resistance exercise (RE) stimulates collagen synthesis in skeletal muscle and tendon but there is limited and equivocal evidence regarding an effect of collagen supplementation and exercise on collagen synthesis. Furthermore, it is not known if a dose-response exists regarding the effect of hydrolyzed collagen (HC) ingestion and RE on collagen synthesis.

Objective: To determine the HC dose-response effect on collagen synthesis after high-intensity RE in resistance-trained young men.

LAVA HyperSense and deep-learning reconstruction for near-isotropic (3D) enhanced magnetic resonance enterography in patients with Crohn's disease: utility in noise reduction and image quality improvement.

Purpose: This study aimed to compare near-isotropic contrast-enhanced T1-weighted (CE-T1W) magnetic resonance enterography (MRE) images reconstructed with vendor-supplied deep-learning reconstruction (DLR) with those reconstructed conventionally in terms of image quality.

Methods: A total of 35 patients who underwent MRE for Crohn's disease between August 2021 and February 2022 were included in this retrospective study. The enteric phase CE-T1W MRE images of each patient were reconstructed with conventional reconstruction and no image filter (original), with conventional reconstruction and image filter (filtered), and with a prototype version of AIR Recon DL 3D (DLR), which were then reformatted into the axial plane to generate six image sets per patient.

Comparison of deep learning-based reconstruction of PROPELLER Shoulder MRI with conventional reconstruction.

Objective: To compare the image quality and agreement among conventional and accelerated periodically rotated overlapping parallel lines with enhanced reconstruction (PROPELLER) MRI with both conventional reconstruction (CR) and deep learning-based reconstruction (DLR) methods for evaluation of shoulder.

Materials And Methods: We included patients who underwent conventional (acquisition time, 8 min) and accelerated (acquisition time, 4 min and 24 s; 45% reduction) PROPELLER shoulder MRI using both CR and DLR methods between February 2021 and February 2022 on a 3 T MRI system. Quantitative evaluation was performed by calculating the signal-to-noise ratio (SNR).

Collagen supplementation augments changes in patellar tendon properties in female soccer players.

We investigated the effect of collagen hydrolysate supplementation on changes in patellar tendon (PT) properties after 10 weeks' training in female soccer players from a Football Association Women's Super League Under 21 s squad. We pair-matched = 17 players (age: 17 ± 0.9 years; height: 1.

Results From South Korean 2022 Para Report Card on Physical Activity for Children and Adolescents With Disabilities.

South Korea has developed its first Para Report Card on physical activity (PA) for children and adolescents with disabilities. Five national surveillance databases were used to evaluate PA indicators based on the benchmarks and grading rubric provided by Active Healthy Kids Global Alliance. Report card evaluation committees were invited to grade and assess the results using strengths, weaknesses, opportunities, and threats analysis.

Deep learning-based image reconstruction improves radiologic evaluation of pituitary axis and cavernous sinus invasion in pituitary adenoma.

Purpose: To compare performance of 1-mm deep learning reconstruction (DLR) with 3-mm routine MRI imaging for the delineation of pituitary axis and identification of cavernous sinus invasion for pituitary macroadenoma.

Method: This retrospective study included 104 patients (59.4 ± 13.

Clinical experience of tensor-valued diffusion encoding for microstructure imaging by diffusional variance decomposition in patients with breast cancer.

Background: Diffusion-weighted imaging plays a key role in magnetic resonance imaging (MRI) of breast tumors. However, it remains unclear how to interpret single diffusion encoding with respect to its link with tissue microstructure. The purpose of this retrospective cross-sectional study was to use tensor-valued diffusion encoding to investigate the underlying microstructure of invasive ductal carcinoma (IDC) and evaluate its potential value in a clinical setting.

Application of Highly Flexible Adaptive Image Receive Coil for Lung MR Imaging Using Zero TE Sequence: Comparison with Conventional Anterior Array Coil.

(1) Background: Highly flexible adaptive image receive (AIR) coil has become available for clinical use. The present study aimed to evaluate the performance of AIR anterior array coil in lung MR imaging using a zero echo time (ZTE) sequence compared with conventional anterior array (CAA) coil. (2) Methods: Sixty-six patients who underwent lung MR imaging using both AIR coil (ZTE-AIR) and CAA coil (ZTE-CAA) were enrolled.

Deep learning-based thin-section MRI reconstruction improves tumour detection and delineation in pre- and post-treatment pituitary adenoma.

Even a tiny functioning pituitary adenoma could cause symptoms; hence, accurate diagnosis and treatment are crucial for management. However, it is difficult to diagnose a small pituitary adenoma using conventional MR sequence. Deep learning-based reconstruction (DLR) using magnetic resonance imaging (MRI) enables high-resolution thin-section imaging with noise reduction.

Image Quality and Diagnostic Performance of Accelerated Shoulder MRI With Deep Learning-Based Reconstruction.

Shoulder MRI using standard multiplanar sequences requires long scan times. Accelerated sequences have tradeoffs in noise and resolution. Deep learning-based reconstruction (DLR) may allow reduced scan time with preserved image quality.

Offset of apparent hyperpolarized C lactate flux by the use of adjuvant metformin in ionizing radiation therapy in vivo.

An increase in hyperpolarized (HP) [1- C]lactate production has been suggested as a biomarker for cancer occurrence as well as for response monitoring of cancer treatment. Recently, the use of metformin has been suggested as an anticancer or adjuvant treatment. By regulating the cytosolic NAD /NADH redox state, metformin stimulates lactate production and increases the HP [1- C]lactate conversion rate in the kidney, liver, and heart.

T2 relaxation time shortening in the cochlea of patients with sudden sensory neuronal hearing loss: a retrospective study using quantitative synthetic magnetic resonance imaging.

Objectives: High cochlear signal intensity on three-dimensional (3D) T2 fluid-attenuated inversion recovery (FLAIR) sequences in patients with sudden sensorineural hearing loss (SSNHL) has been reported. Here, we evaluated the cochlear T2 relaxation time differences in patients with idiopathic SSNHL using quantitative synthetic MRI (SyMRI).

Methods: Twenty-four patients with unilateral SSNHL who underwent precontrast conventional 3D FLAIR and SyMRI were retrospectively included.

Thin-Slice Pituitary MRI with Deep Learning-based Reconstruction: Diagnostic Performance in a Postoperative Setting.

Background Achieving high-spatial-resolution pituitary MRI is challenging because of the trade-off between image noise and spatial resolution. Deep learning-based MRI reconstruction enables image denoising with sharp edges and reduced artifacts, which improves the image quality of thin-slice MRI. Purpose To assess the diagnostic performance of 1-mm slice thickness MRI with deep learning-based reconstruction (DLR) (hereafter, 1-mm MRI+DLR) compared with 3-mm slice thickness MRI (hereafter, 3-mm MRI) for identifying residual tumor and cavernous sinus invasion in the evaluation of postoperative pituitary adenoma.

A new ultrafast 3D gradient echo-based imaging method using quadratic-phase encoding.

Purpose: To propose a novel 3D ultrafast gradient echo-based MRI method, dubbed RASE, using quadratic-phase encoding.

Theory And Methods: Several characteristics of RASE, including spin behaviors, spatial resolution, SNR, and reduction of susceptibility-induced signal loss, were analytically described. A way of compensating for TE variation was suggested in the quadratic phase-encoding direction.

Mouse fMRI under ketamine and xylazine anesthesia: Robust contralateral somatosensory cortex activation in response to forepaw stimulation.

Mouse fMRI is critically useful to investigate functions of mouse models. Until now, the somatosensory-evoked responses in anesthetized mice are often widespread and inconsistent across reports. Here, we adopted a ketamine and xylazine mixture for mouse fMRI, which is relatively new anesthetics in fMRI experiments.

Magnetic resonance electrical properties tomography for small anomalies using boundary conditions: A simulation study.

Purpose: Magnetic resonance electrical property tomography (MREPT) is an emerging imaging modality using measured B maps from magnetic resonance imaging (MRI) to measure a distribution of electric conductivity and permittivity of the subject at the Larmor frequency. Conventional MREPT approaches at single transmit channel system using the Helmholtz equation rely on an assumption that conductivity and permittivity of the subject are locally homogeneous. For small tissue structures and tissue boundaries, in which the assumption of locally homogeneous conductivity and permittivity does not hold, the reconstructed conductivity values deviated from the actual values, so called "Boundary Artifacts.

An indirect method for in vivo T mapping of [1- C] pyruvate using hyperpolarized C CSI.

An indirect method for in vivo T mapping of C-labeled metabolites using T and T * information of water protons obtained a priori is proposed. The T values of C metabolites are inferred using the relationship to T ' of coexisting H and the T * of C metabolites, which is measured using routine hyperpolarized C CSI data. The concept is verified with phantom studies.