Hyperthermia is a treatment that applies heat to damage or kill cancer cells and can be also used for drug deliveries. It is important to apply the heat into the specific area in order to target the cancer tissue and avoid damaging healthy tissue. For this reason, the development of heat applicators that have the capability to deliver the heat to the target area is vital. In this study, we present an optimization of an array coil for brain hyperthermia that can be used in combination with MRI, such that the heat can be delivered to the cancer area.

Two-pulse phase-modulated (TPPM) H-decoupling pulse sequence repeats a pair of 180 RF pulses while changing the signs of the RF phase modulation angle and has been widely used for the C NMR of organic solids. TPPM was introduced into the C MRS pulse sequence on a clinical 3T MR scanner, and the H-decoupling performance was compared with conventional H-decoupling schemes using aqueous solutions containing glucose and oyster glycogen. The C C1-glucose peaks were H-decoupled using TPPM with B = 500 Hz, and the optimal RF phase modulation angle was up to 30. Cycling sidebands were not observed when TPPM was used but were observed when WALTZ-16 was used. The C C1-glycogen peak was H-decoupled even with reducing TPPM duration to 8 ms, which reduced simulated specific absorption rate (SAR) to 39%. In conclusion, the TPPM H decoupling is applicable to clinical MR scanners, and the low-SAR sequence may be more valuable at 7T.

To compare diagnostic reliability between an intravoxel incoherent motion (IVIM) imaging and an arterial spin labeling (ASL) in assessment of renal blood flow in rodents.

This study aims to assess thalamocortical tract fiber injury using diffusion-tensor imaging (DTI) and to characterize metabolic alterations in the dorsal thalamus with proton magnetic resonance spectroscopy (MRS) in patients with cervical spondylotic myelopathy (CSM).

To investigate the potential of 4D flow MRI-derived pulmonary hemodynamic parameters as sensitive markers for chronic obstructive pulmonary disease (COPD) patients with right ventricular dysfunction (RVD).

This study investigated the ability of three-dimentional motion-sensitized driven-equilibrium prepared T-weighted fast spin echo (3D MSDE-FSE) imaging to identify distal dural rings (DDRs) and paraclinoid aneurysms (ParaC-ANs) and differentiate between intradural and extradural ParaC-ANs and compared it with that of established MR cisternography-based techniques.

The aim of our study was to investigate the technical accuracy of susceptibility-weighted imaging (SWI) and quantitative susceptibility mapping (QSM) created to detect intramammary-like calcifications depending on different TEs, volume, and type of calcification samples at 1.5T.

The purposes of this study were 1) to improve vessel visibility of our MR sequence by modifying k-space filling and 2) to verify the usefulness of applying artificial intelligence (AI) for volume isotropic simultaneous interleaved bright- and black-blood examination (VISIBLE) with compressed sensitivity encoding (CS) in autodetecting brain metastases.

To re-evaluate images recovered from JCOG0911, a randomized phase 2 trial for newly diagnosed glioblastoma (nGBM) conducted by the Japan Clinical Oncology Group (JCOG) Brain Tumor Study Group.

A cyst-like structure near superior sagittal sinus (Arachnoid Cuff Exit Site cysts: ACES cysts) has been reported in MRI. The purpose of this study was to investigate the association between presence of ACES cysts and cognitive function, as assessed using mini-mental state examination (MMSE) scores.

This review explores the significant progress and applications of artificial intelligence (AI) in obstetrics and gynecological MRI, charting its development from foundational algorithmic techniques to deep learning strategies and advanced radiomics. This review features research published over the last few years that has used AI with MRI to identify specific conditions such as uterine leiomyosarcoma, endometrial cancer, cervical cancer, ovarian tumors, and placenta accreta. In addition, it covers studies on the application of AI for segmentation and quality improvement in obstetrics and gynecology MRI. The review also outlines the existing challenges and envisions future directions for AI research in this domain. The growing accessibility of extensive datasets across various institutions and the application of multiparametric MRI are significantly enhancing the accuracy and adaptability of AI. This progress has the potential to enable more accurate and efficient diagnosis, offering opportunities for personalized medicine in the field of obstetrics and gynecology.

To evaluate the clinical value of early renal changes in type 2 diabetes mellitus (T2DM) using multiparameter MRI.

The integration of deep learning (DL) in breast MRI has revolutionized the field of medical imaging, notably enhancing diagnostic accuracy and efficiency. This review discusses the substantial influence of DL technologies across various facets of breast MRI, including image reconstruction, classification, object detection, segmentation, and prediction of clinical outcomes such as response to neoadjuvant chemotherapy and recurrence of breast cancer. Utilizing sophisticated models such as convolutional neural networks, recurrent neural networks, and generative adversarial networks, DL has improved image quality and precision, enabling more accurate differentiation between benign and malignant lesions and providing deeper insights into disease behavior and treatment responses. DL's predictive capabilities for patient-specific outcomes also suggest potential for more personalized treatment strategies. The advancements in DL are pioneering a new era in breast cancer diagnostics, promising more personalized and effective healthcare solutions. Nonetheless, the integration of this technology into clinical practice faces challenges, necessitating further research, validation, and development of legal and ethical frameworks to fully leverage its potential.

Fresh blood imaging (FBI) utilizes physiological blood signal differences between diastole and systole, causing a long acquisition time. The purpose of this study is to develop a fast FBI technique using a centric k - k k-space trajectory (cFBI) and an exponential refocusing flip angle (eFA) scheme with fast longitudinal restoration.

To assess the utility of apparent diffusion coefficient maps (ADC) for diagnosing myometrial invasion (MI) in endometrial cancer (EC).

This study investigated the breast lesion conspicuity and apparent diffusion coefficient (ADC) reliability for three different diffusion-weighted imaging (DWI) protocols: spatiotemporal encoding (SPEN), single-shot echo-planar imaging (SS-EPI), and readout segmentation of long variable echo-trains (RESOLVE).

T values are hypothesized to be reduced where protein accumulates in the cerebrospinal fluid (CSF). We aimed to verify the accuracy of Carr-Purcell-Meiboom-Gil (CPMG) pulses and non-negative least squares (NNLS) analysis in visualizing protein concentrations by mapping the T values.

This study aimed to evaluate the feasibility of single-shot echo planar diffusion-weighted imaging with compressed SENSE (EPICS-DWI) for pancreas assessment by comparing with single-shot echo planar DWI with parallel imaging (PI-DWI).

The quantitative analysis of pulsed-chemical exchange saturation transfer (CEST) using a full model-based method is computationally challenging, as it involves dealing with varying RF values in pulsed saturation. A power equivalent continuous approximation of B power was usually applied to accelerate the analysis. In line with recent consensus recommendations from the CEST community for pulsed-CEST at 3T, particularly recommending a high RF saturation power (B = 2.0 µT) for the clinical application in brain tumors, this technical note investigated the feasibility of using average power (AP) as the continuous approximation. The simulated results revealed excellent performance of the AP continuous approximation in low saturation power scenarios, but discrepancies were observed in the z-spectra for the high saturation power cases. Cautions should be taken, or it may lead to inaccurate fitted parameters, and the difference can be more than 10% in the high saturation power cases.

This study aimed to compare MRI findings among benign, borderline, and malignant ovarian seromucinous neoplasms.

High b-value acquisition and diffusion-weighted imaging with background suppression (DWIBS) are desirable in high-specificity breast cancer diagnosis on non-contrast-enhanced magnetic resonance imaging; however, this inherently results in a lower signal-to-noise ratio (SNR). Compressed sensitivity encoding (C-SENSE), which combines SENSE with compressed sensing, improves the SNR by reducing noise. Recent technological improvements allow us to incorporate this acceleration technique into echo-planar imaging, called echo-planar imaging with C-SENSE (EPICS). This study aimed to compare image quality and reliability of the apparent diffusion coefficient (ADC) between DWIBS obtained using SENSE and EPICS in patients with small breast cancers.