Magnetic Resonance in Medical Sciences

Toward Clinical Implementation of Magnetic Resonance Imaging for Placental Function
Himoto Y, Fujimoto K, Chigusa Y, Yoshida A, Minamiguchi S, Kido A and Nakamoto Y
Placental insufficiency is a critical condition in perinatal medicine, clinically manifesting as fetal growth restriction or preeclampsia. In addition to ultrasound and Doppler velocimetry, MRI has been assessed intensively for its potential to evaluate placental function directly. Several methods investigated to date include anthropometry, visual assessments using T2-weighted images, and quantitative evaluations based on T2 values, hypoxia indicators (T2* values and blood oxygenation level-dependent imaging), and perfusion metrics (intravoxel incoherent motion and arterial spin labeling). Anthropometry and visual assessments are easily implemented clinically because they require no specific technique or post-processing. By contrast, quantitative approaches provide objective numerical indicators, making them promising imaging biomarkers. Despite their potential, translating these methods into clinical practice presents challenges, especially for quantitative techniques, because of limited availability, lack of standardization, and inadequate clinician awareness. This review was conducted to overview the clinical aspects of placental insufficiency, summarize the anthropometry, visual assessments, and quantitative methods reported, and highlight the latest advancements. It also presents discussion of related challenges and future prospects for clinical implementation.
Breast Diffusion-weighted MR Imaging: Current Applications, Insights from Screening, and Future Directions
Cho N
Breast diffusion weighted MR imaging (DWI) is increasingly used, because it is fast and easy to be added in clinical protocol without contrast agent and provides information of cellularity or tissue microstructure. This review article explores the principles of breast DWI, the standardization of acquisition techniques, and its current clinical applications. We emphasize its role in differentiating benign from malignant lesions, reducing unnecessary biopsies, and discuss the evidence supporting DWI as a potential standalone screening tool. Prognostic indicators derived from DWI parameters and its utility in monitoring treatment responses are discussed. Finally, we look to the future, discussing emerging techniques. This review provides a comprehensive overview of breast DWI's current status and future potential.
MR Imaging Indices for Brain Interstitial Fluid Dynamics and the Effects of Orexin Antagonists on Sleep
Taoka T, Iwamoto K, Miyata S, Ito R, Nakamichi R, Nakane T, Okada I, Ichikawa K, Kan H, Kamagata K, Kikuta J, Aoki S, Fujimoto A, Kogo Y, Ichinose N, Naganawa S and Ozaki N
The purpose of this study was to assess the extent to which improvement in sleep with lemborexant contributed to changes in interstitial fluid dynamics.
Institutional Variability in Ultrafast Breast MR Imaging: Comparing Compressed Sensing and View Sharing Techniques with Different Patient Populations and Contrast Injection Protocols
Honda M, Kataoka M, Iima M, Ota R, Okazawa A, Fukushima Y, Nickel MD, Sato F, Masuda N, Okada T and Nakamoto Y
To assess the institutional variability in ultrafast dynamic contrast-enhanced (UF-DCE) breast MRI using time-resolved angiography with stochastic trajectories (TWIST)-volumetric interpolated breath-hold examination (VIBE) and compressed sensing (CS)-VIBE sequences acquired at 2 different institutions with different patient populations and contrast injection protocols.
Using Deep Learning to Simultaneously Reduce Noise and Motion Artifacts in Brain MR Imaging
Muro I, Isoiwa T, Shibukawa S, Usui K and Otsuka Y
To reduce motion artifacts (MA) and noise in brain MRI using deep learning to promote clinical utility.
Improved Assessment of Juxtacortical Lesions in Multiple Sclerosis Using Highly-accelerated High-resolution Double Inversion Recovery MR Imaging with Deep Learning-based Reconstruction
Shintaku T, Ide S, Nagaya H, Ishimoto Y, Watanabe K, Oyu K, Kasai S, Umemura Y, Sasaki M, Saito K, Ozawa A, Nozaki A, Zhu X, Wakayama T, Nishijima H, Suzuki C, Tomiyama M and Kakeda S
Recently, a novel deep learning (DL)-based technique for reconstructing highly undersampled MR data (DL-Speed, DLS) has been developed, which demonstrated superior performance over compressed sensing. This study aimed to achieve high-resolution double inversion recovery (DIR) imaging using DLS (DLS-DIR) and compare its diagnostic performance in the detection of juxtacortical multiple sclerosis (MS) lesions with that of conventional DIR (C-DIR).
Implementation of Two-pulse Phase-modulated (TPPM) H Decoupling in a Clinical MR Scanner for the Detection of the C1-glycogen Peak in C MRS
Kuribayashi H and Inubushi T
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.
Computational Design of a Thermal Applicator for Brain Hyperthermia Controlled by Capacitor Positioning in Loop Coils
Hernandez D, Nam T, Lee E, Ryu Y, Chung JY and Kim KN
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.
Changes to Dorsal Thalamic Metabolites and Thalamocortical Tract Fiber Injury in Patients with Cervical Spondylotic Myelopathy
Zhang L, Zhang YJ, Wang N, Wang Y and Tian XN
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).
Pulmonary Hemodynamic Parameters Derived from 4D Flow MR Imaging Can Provide Sensitive Markers for Chronic Obstructive Pulmonary Disease (COPD) Patients with Right Ventricular Dysfunction
Sun J, Wang W, Yu A, Zhou L, Hua M, Chen Y and Zhang H
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).
Evaluation of Renal Perfusion: A Comparative Study between Intravoxel Incoherent Motion (IVIM) Imaging and Arterial Spin Labeling (ASL) to Assess Renal Blood Flow in Rodents
Ishimatsu K, Kikuchi K, Moe OW, Oshio K, Ishigami K and Takahashi M
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.
Identification of the Distal Dural Ring Using Three-dimensional Motion-sensitized Driven-equilibrium Prepared T-weighted Fast Spin Echo Imaging: Application to Paraclinoid Aneurysms
Oki M, Oki T, Ito R, Roberts N and Watanabe Y
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.
In-vitro Detection of Intramammary-like Macrocalcifications Using Susceptibility-weighted MR Imaging Techniques at 1.5T
Lebenatus A, Kuster J, Straub S, Naujokat H, Tesch K, Jansen O and Salehi Ravesh M
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.
Improving Vessel Visibility and Applying Artificial Intelligence to Autodetect Brain Metastasis for a 3D MR Imaging Sequence Capable of Simultaneous Images with and without Blood Vessel Suppression
Kikuchi K, Obara M, Kikuchi Y, Yamashita K, Wada T, Hiwatashi A, Ishigami K and Togao O
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.
Image-based Re-evaluation of the JCOG0911 Study Focusing on Tumor Volume and Survival, Disease Progression Diagnosis, and Radiomic Prognostication for Newly Diagnosed Glioblastoma
Kinoshita M, Fushimi Y, Masumoto T, Sasaki K, Sekita T, Natsume A, Wakabashi T, Komori T, Tsuzuki S, Muragaki Y, Motomura K, Saito R, Sato K, Beppu T, Takahashi M, Kuroda JI, Sonoda Y, Kobayashi K, Mishima K, Mitsuya K, Yamasaki F, Inoue A, Matsutani T, Nakamura H, Yamaguchi S, Ishikawa E, Nakaya M, Tanaka S, Ujifuku K, Uchida H, Kanamori M, Otani R, Kijima N, Nishida N, Yoshino A, Mineharu Y, Arakawa Y, Fukuda H, Narita Y and
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.
Association between the Presence of the Parasagittal Cyst-like Structures and Cognitive Function
Ohashi T, Ito R, Yamamoto R, Ukai K and Naganawa S
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.
Evaluation of Early Renal Changes in Type 2 Diabetes Mellitus Using Multiparametric MR Imaging
Chen X, Ge C, Zhang Y, Ma Y, Zhang Y, Li B, Chu Z and Ji Q
To evaluate the clinical value of early renal changes in type 2 diabetes mellitus (T2DM) using multiparameter MRI.
Artificial Intelligence in Obstetric and Gynecological MR Imaging
Saida T, Gu W, Hoshiai S, Ishiguro T, Sakai M, Amano T, Nakahashi Y, Shikama A, Satoh T and Nakajima T
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.
The Evolution and Clinical Impact of Deep Learning Technologies in Breast MRI
Fujioka T, Fujita S, Ueda D, Ito R, Kawamura M, Fushimi Y, Tsuboyama T, Yanagawa M, Yamada A, Tatsugami F, Kamagata K, Nozaki T, Matsui Y, Fujima N, Hirata K, Nakaura T, Tateishi U and Naganawa S
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.
Comparing Lesion Conspicuity and ADC Reliability in High-resolution Diffusion-weighted Imaging of the Breast
Iima M, Nakayama R, Kataoka M, Otikovs M, Nissan N, Frydman L, Urushibata Y, Honda M, Okazawa A, Satake H, Naganawa S and Nakamoto Y
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).
Characterizing Protein Concentration in Cerebrospinal Fluid with T Component Analysis
Koizumi T, Shimizu S, Akiba C, Kakizoe H, Bandai H, Sato K, Nagasawa H, Ogino I, Nakajima M, Yamada S, Oshio K and Miyajima M
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.