Application Of Magnetic Resonance Imaging Research Articles

Application of preoperative advanced diffusion magnetic resonance imaging in evaluating the postoperative recurrence of lower grade gliomas

BackgroundRecurrence of lower grade glioma (LrGG) appeared to be unavoidable despite considerable research performed in last decades. Thus, we evaluated the postoperative recurrence within two years after the surgery in patients with LrGG by preoperative advanced diffusion magnetic resonance imaging (dMRI).Materials and methods48 patients with lower-grade gliomas (23 recurrence, 25 nonrecurrence) were recruited into this study. Different models of dMRI were reconstructed, including apparent fiber density (AFD), white matter tract integrity (WMTI), diffusion tensor imaging (DTI), diffusion kurtosis imaging (DKI), neurite orientation dispersion and density imaging (NODDI), Bingham NODDI and standard model imaging (SMI). Orthogonal Partial Least Squares-Discriminant Analysis (OPLS-DA) was used to construct a multiparametric prediction model for the diagnosis of postoperative recurrence.ResultsThe parameters derived from each dMRI model, including AFD, axon water fraction (AWF), mean diffusivity (MD), mean kurtosis (MK), fractional anisotropy (FA), intracellular volume fraction (ICVF), extra-axonal perpendicular diffusivity (De⊥), extra-axonal parallel diffusivity (De∥) and free water fraction (fw), showed significant differences between nonrecurrence group and recurrence group. The extra-axonal perpendicular diffusivity (De⊥) had the highest area under curve (AUC = 0.885), which was significantly higher than others. The variable importance for the projection (VIP) value of De⊥ was also the highest. The AUC value of the multiparametric prediction model merging AFD, WMTI, DTI, DKI, NODDI, Bingham NODDI and SMI was up to 0.96.ConclusionPreoperative advanced dMRI showed great efficacy in evaluating postoperative recurrence of LrGG and De⊥ of SMI might be a valuable marker.

A Simple Overview in Magnetic Resonance Imaging Application in Evaluation of Food Quantity and Quality Aspects

A Simple Overview in Magnetic Resonance Imaging Application in Evaluation of Food Quantity and Quality Aspects

Synergistic response of PEG coated manganese dioxide nanoparticles conjugated with doxorubicin for breast cancer treatment and MRI application

In this research work, we designed a smart biodegradable PEG-coated MnO2 nanoparticles conjugated with doxorubicin (PMnO2-Dox NPs) for dual chemo-photodynamic therapy and magnetic resonance imaging (MRI) application. This highly sensitive pH-responsive PMnO2-Dox NPs causes effective drug release under acidic pH environment. PMnO2-Dox NPs not only improves the efficacy of chemo-photodynamic therapy due to synergistic response as well as improved MRI imaging via boosting T1 MRI contrast. Manifold characterization techniques have been employed for materials investigation. Crystallography of PMnO2-Dox NPs were performed by using XRD analysis, which confirmed tetragonal crystal structure with an approximate crystallite size of 20–30 nm. Surface morphology was confirmed via SEM analysis, results indicated the spherical and asymmetric agglomerated nanocluster of PMnO2-Dox NPs. In in vitro bioassay, the anticancer activity of PMnO2-Dox NPs were tested against breast cancer (MCF-7) cell line using MTT test. Moreover, it can also inhibit the growth of primary and secondary cancers without light exposure. Results suggested that PMnO2-Dox NPs not only convenient for cancer treatment via combined chemo-photodynamic therapy but also address the way towards a comprehensive strategy for MRI application via bright contrast agent T1 after overcoming the problem of multidrug resistance (MDR) and synergistic response of therapeutic analysis.

Clustered ultra-small iron oxide nanoparticles as potential T1/T2dual-modal magnetic resonance imaging contrast agents and application to tumor model.

Many studies have been conducted on the use of ultra-small iron oxide nanoparticles (USIONs) (d < 3 nm) as potential positive magnetic resonance imaging (MRI)-contrast agents (CAs); however, there is dearth of research on clustered USIONs. In this study, nearly monodispersed clustered USIONs were synthesized using a simple two-step one-pot polyol method. First, USIONs (d = 2.7 nm) were synthesized, and clustered USIONs (d = 27.9 nm) were subsequently synthesized through multiple cross-linking of USIONs with poly(acrylic acid-co-maleic acid) (PAAMA) polymers with many -COOH groups. The clustered PAAMA-USIONs exhibited very weak ferromagnetism owing to the magnetic interaction between superparamagnetic USIONs; this was evidenced by their appreciable r1= 3.9 s‒1mM‒1and high r2/r1ratio of 14.6. Their ability to function as a dual-modal T1/T2MRI-CA in T1-weighted MRI was demonstrated when they simultaneously exhibited positive and negative contrasts in T1-weighted MRI of tumor model mice after intravenous injection. They displayed positive contrasts at the kidneys, bladder, heart, and aorta and negative contrasts at the liver and tumor.&#xD.

Magnetic Resonance Imaging of Endometriosis: The Role of Advanced Techniques

Endometriosis is a chronic inflammatory disease that affects about 10% of women, and it is characterized by the presence of endometrial tissue outside the uterine cavity. Associated symptoms are dyspareunia, chronic pelvic pain, and infertility. The diagnosis of endometriosis can be challenging due to various clinical and imaging presentations. Laparoscopy is the gold standard for the diagnosis, but it is an invasive procedure. The literature has increasingly promoted a switch to less invasive imaging techniques, such as ultrasound and magnetic resonance imaging (MRI). The latter, also in relation to the latest technological advances, allows a comprehensive and accurate assessment of the pelvis and it can also identify sites of endometriosis that escape laparoscopic evaluation. Furthermore, MRI has been found to be more accurate than other imaging techniques in relation to its improved sensitivity and specificity in identifying disease sites, also due to the role of new emerging sequences. This article aims to review the current role of advanced MRI applications in the assessment of endometriosis.

Evolution in Spinal Fracture Diagnosis and Brain Tumor Detection in the Last two Decades: A Timeline-Based Study

Computed Tomography (CT) and Magnetic Resonance Imaging (MRI) are arguably the most prominent and most widely used healthcare diagnostic modalities for a wide range of applications. There are certain specific applications for which a particular modality is specifically used or has been adopted over a period of time because of reasons like good diagnostic accuracy, fast diagnosis, etc. One such application for CT has been “Spinal Fracture Diagnosis” and for MRI has been “Brain Tumor Detection”. This study presents case studies from different time periods to demonstrate the evolution of these respective applications and emphasizes the role of Artificial Intelligence (AI) based techniques like machine learning, deep learning, etc. for advancements in the diagnostic process. The case studies will enable the new researchers to understand the background and the work done in the respective time period. The time period of the studies referred to is between the years 2000 and 2023 (Present date). The purpose of this study is to enlighten the reader about the evolution of spinal fractures and brain tumor diagnosis which are understood to be primary applications of CT and MRI, respectively and, encourage further study into topics pertaining to AI-based tools used in diagnostic modalities for applications like automatic detection and prediction, smart decision making, early detection, etc.

229 Awardee Talk: The quest for an ideal in-field embryo evaluation tool in cattle: Opportunities and challenges

Abstract Accurately evaluating bovine embryos to select the most viable ones for transfer and successful pregnancy has been a challenge since embryo transfer began in cattle over six decades ago. Despite more than 3,100 peer-reviewed studies on bovine embryo evaluation published in PubMed from 1964 to 2023, there is still no consensus or gold standard method for assessing their developmental potential. The evaluation “problem” in assisted reproduction extends beyond embryos to gametes as well. Numerous microscopic techniques (e.g., differential interference contrast, electron, fluorescent, time-lapse, and artificial intelligence-based microscopy) and non-microscopic methodologies (e.g., genomics, transcriptomics, epigenomics, proteomics, metabolomics, and nuclear magnetic resonance) have been tested to find an embryo evaluation technique superior to morphological evaluation. While many of these research tools can accurately determine embryo quality and viability, most are invasive, expensive, labor-intensive, technically complex, and time-consuming, making them impractical for in-field embryo evaluation. Employing complex methods like RNA sequencing, SNP chips, mass spectrometry, and multiphoton microscopy at thousands of embryo production and collection facilities is unrealistic, no matter how accurate they may be. Therefore, future research should focus on innovating field-friendly, simple benchtop tests using existing findings, particularly from omics-based research methodologies. Time-lapse monitoring and artificial intelligence-based automated image analysis also potentially provide accurate embryo evaluation. However, further research is necessary to develop economically feasible options for in-field applications. Our recent work has examined possible applications of nuclear magnetic resonance (NMR) imaging, label-free microscopy, particularly holographic microscopy techniques like gradient light interference microscopy (GLIM), spatial light interference microscopy (SLIM), and multiphoton holographic microscopy in IVF labs. The ideal embryo evaluation tool should be accurate, objective, non-invasive, affordable, and simple enough for widespread adoption by embryo production and collection facilities worldwide. Under current circumstances, it is doubtful that transcriptomics, proteomics, metabolomics, GLIM, SLIM, NMR, multiphoton holographic microscopy, and similar techniques can be directly used for in-field embryo evaluation. However, biomarkers identified by these methodologies could be used for in-field embryo evaluation by devising simple, affordable benchtop techniques. Further investigation on time-lapse microscopy (TLM) and AI-based automated image processing may make these methods more affordable and potentially adoptable by the masses. There is great potential for these methodologies to become widely used, provided they can be made more economically viable. In conclusion, the next generation of microscopy capable of providing objective markers for gamete and embryo quality is on the horizon.

The Application of Magnetic Resonance Imaging in the Early and Accurate Diagnosis of Hip Joint Avascular Necrosis.

Introduction Avascular necrosis (AVN) is characterized by the death (necrosis) of cellular bone components in the subchondral bone or epiphysis due to a lack of or an interruption of the blood supply. In routine practice, AVN is most frequently encountered in the femoral head. In this study, we aim to evaluate the application of magnetic resonance imaging (MRI) in the early and accurate diagnosis of hip joint AVN. Materials and methods This was a retrospective, cross-sectional study conducted in the Department of Radiodiagnosis of Dr. D. Y. Patil tertiary care hospital, Pimpri, Pune, India. We studied 30 patients with complaints of pain and associated limping who underwent primary radiograph analysis of the hip joint, followed by MRI. Results We assessed 30 patients (45 hip joints) using plain radiography and MRI. Of the 45 hips, we could diagnose AVN in 28 hips (62.2%) using plain radiography, but we could not diagnose it in 17 hips (37.8%), whereas we were able to diagnose AVN in all hips (100%) using MRI. Forty percent of the patients (n = 12) were on steroids, 26.7%(n = 8) were chronic alcoholics, and 16.7% (n = 5) were idiopathic. The other less common causes were a history of trauma or fracture of the neck of the femur (n = 3) and sickle cell disease (n = 2).Of the 45 hips of the 30 patients studied, 15 patients had bilateral disease affecting a total of 30 hips (66.7%), and 15 patients had unilateral disease affecting a total of 15 hips (33.4%). Of the 30 hips (bilateral disease), five (13.3%) contralateral hips were clinically occult and were incidentally diagnosed with AVN. Conclusion The assessment of AVN based solely on plain radiography can miss vital information in stages II and III (Ficat and Arlet classification). Due to its multiplanar capability, superior spatial resolution, and better tissue characterization, MRI is very sensitive and able to detect femoral head AVN early and promptly in cases that are radiograph-negative or otherwise clinically unsuspected.

Hypertrophic cardiomyopathy – contribution of magnetic resonance imaging

Hypertrophic cardiomyopathy (HCM) is one of the most common form of cardiomyopathies. It is characterized by primary hypertrophy, disorganization, and fibrosis of the myocardium. These morphological characteristics determine the applicability and significance of magnetic resonance imaging in the evaluation of these patients. Cardiac magnetic resonance helps the diagnostic process by identifying hypertrophic segments, which are less accessible by echocardiography ensures more precise measurements of wall thickness and differentiates HCM from other causes of left ventricular hypertrophy. The method allows for not only qualitative but also quantitive evaluation of focal and diffuse fibrosis which plays an important role in evaluation of patients&amp;rsquo; prognosis and follow up. The aim of this article is to review the role of cardiac magnetic resonance in the diagnosis of HCM, demonstrating different forms and their typical morphological features, as well as to demonstrate the role of the method in the differential diagnosis of myocardial hypertrophy.

Bibliometric analysis of global research trends in magnetic resonance imaging studies of substantia nigra in Parkinson's disease (2001-2024).

Parkinson's disease (PD) is a globally prevalent neurodegenerative disorder, primarily characterized by muscle rigidity, resting tremor, and bradykinesia. The incidence of PD is rapidly escalating worldwide. Numerous studies have been conducted on the application of magnetic resonance imaging (MRI) in investigating the substantia nigra (SN) in PD patients. However, to date, no bibliometric analysis has been performed on this specific research area. Therefore, this study aimed to provide a comprehensive analysis of the current status in MRI research on the SN in PD patients. MRI study records related to the SN in PD patients from 2001 to 2024 were searched by using the Web of Science Core Collection (WOSCC) database and then the CiteSpace and VOSviewer were used to conduct bibliometric analysis. Our analysis found that the number of published articles related studies on MRI of the SN in PD showed an overall upward trend over the past decade, in which Lehericy, Stephane, Du, Guangwei, and Huang, Xuemei are the top three authors with the most articles. Additionally, United States, China and Germany are the main contributors to MRI studies of SN in PD. And Shanghai Jiao Tong University, University of Florida and Seoul National University are the leading institutions in the field. Finally, the keyword analysis showed that the hotspots and trends of research in this field are mainly concentrated in quantitative susceptibility mapping, neuroimaging, and neuromelanin-sensitive MRI. These analysis identified the most influential authors, institutions, countries and research hotspots in the field of SN-MRI research in PD, which has reference significance for the research interest in this field and provides a new idea for PD prevention.

Quantifying brain development in the HEALthy Brain and Child Development (HBCD) Study: The magnetic resonance imaging and spectroscopy protocol

The HEALthy Brain and Child Development (HBCD) Study, a multi-site prospective longitudinal cohort study, will examine human brain, cognitive, behavioral, social, and emotional development beginning prenatally and planned through early childhood. The acquisition of multimodal magnetic resonance-based brain development data is central to the study’s core protocol. However, application of Magnetic Resonance Imaging (MRI) methods in this population is complicated by technical challenges and difficulties of imaging in early life. Overcoming these challenges requires an innovative and harmonized approach, combining age-appropriate acquisition protocols together with specialized pediatric neuroimaging strategies. The HBCD MRI Working Group aimed to establish a core acquisition protocol for all 27 HBCD Study recruitment sites to measure brain structure, function, microstructure, and metabolites. Acquisition parameters of individual modalities have been matched across MRI scanner platforms for harmonized acquisitions and state-of-the-art technologies are employed to enable faster and motion-robust imaging. Here, we provide an overview of the HBCD MRI protocol, including decisions of individual modalities and preliminary data. The result will be an unparalleled resource for examining early neurodevelopment which enables the larger scientific community to assess normative trajectories from birth through childhood and to examine the genetic, biological, and environmental factors that help shape the developing brain.

Recent trends in AI applications for pelvic MRI: a comprehensive review.

Magnetic resonance imaging (MRI) is an essential tool for evaluating pelvic disorders affecting the prostate, bladder, uterus, ovaries, and/or rectum. Since the diagnostic pathway of pelvic MRI can involve various complex procedures depending on the affected organ, the Reporting and Data System (RADS) is used to standardize image acquisition and interpretation. Artificial intelligence (AI), which encompasses machine learning and deep learning algorithms, has been integrated into both pelvic MRI and the RADS, particularly for prostate MRI. This review outlines recent developments in the use of AI in various stages of the pelvic MRI diagnostic pathway, including image acquisition, image reconstruction, organ and lesion segmentation, lesion detection and classification, and risk stratification, with special emphasis on recent trends in multi-center studies, which can help to improve the generalizability of AI.

Coupled stack-up volume RF coils for low-field open MR imaging.

Low-field open magnetic resonance imaging (MRI) systems, typically operating at magnetic field strengths below 1 Tesla, has greatly expanded the accessibility of MRI technology to meet a wide range of patient needs. However, the inherent challenges of low-field MRI, such as limited signal-to-noise ratios and limited availability of dedicated radiofrequency (RF) coils, have prompted the need for innovative coil designs that can improve imaging quality and diagnostic capabilities. In response to these challenges, we introduce the coupled stack-up volume coil, a novel RF coil design that addresses the shortcomings of conventional birdcage in the context of low-field open MRI. The proposed coupled stack-up volume coil design utilizes a unique architecture that optimizes both transmit/receive efficiency and RF field homogeneity and offers the advantage of a simple design and construction, making it a practical and feasible solution for low-field MRI applications. This paper presents a comprehensive exploration of the theoretical framework, design considerations, and experimental validation of this innovative coil design. We demonstrate the superior performance of the coupled stack-up volume coil in achieving 47.7% higher transmit/receive efficiency and 68% more uniform magnetic field distribution compared to traditional birdcage coils in electromagnetic simulations. Bench tests results show that the B1 field efficiency of coupled stack-up volume coil is 57.3% higher compared with that of conventional birdcage coil. The proposed coupled stack-up volume coil outperforms the conventional birdcage coil in terms of B1 efficiency, imaging coverage, and low-frequency operation capability. This design provides a robust and simple solution to low-field MR RF coil design.

Reliability of task-based fMRI in the dorsal horn of the human spinal cord

Abstract The application of functional magnetic resonance imaging (fMRI) to the human spinal cord is still a relatively small field of research and faces many challenges. Here we aimed to probe the limitations of task-based spinal fMRI at 3T by investigating the reliability of spinal cord blood oxygen level dependent (BOLD) responses to repeated nociceptive stimulation across 2 consecutive days in 40 healthy volunteers. We assessed the test–retest reliability of subjective ratings, autonomic responses, and spinal cord BOLD responses to short heat-pain stimuli (1 s duration) using the intraclass correlation coefficient (ICC). At the group level, we observed robust autonomic responses as well as spatially specific spinal cord BOLD responses at the expected location, but no spatial overlap in BOLD response patterns across days. While autonomic indicators of pain processing showed good-to-excellent reliability, both β-estimates and z-scores of task-related BOLD responses showed poor reliability across days in the target region (gray matter of the ipsilateral dorsal horn). When taking into account the sensitivity of gradient-echo echo planar imaging (GE-EPI) to draining vein signals by including the venous plexus in the analysis, we observed BOLD responses with fair reliability across days. Taken together, these results demonstrate that heat-pain stimuli as short as 1 s are able to evoke a robust and spatially specific BOLD response, which is, however, strongly variable within participants across time, resulting in low reliability in the dorsal horn gray matter. Further improvements in data acquisition and analysis techniques are thus necessary before event-related spinal cord fMRI as used here can be reliably employed in longitudinal designs or clinical settings.

Beyond the Conventional Structural MRI: Clinical Application of Deep Learning Image Reconstruction and Synthetic MRI of the Brain.

Recent technological advancements have revolutionized routine brain magnetic resonance imaging (MRI) sequences, offering enhanced diagnostic capabilities in intracranial disease evaluation. This review explores 2 pivotal breakthrough areas: deep learning reconstruction (DLR) and quantitative MRI techniques beyond conventional structural imaging. DLR using deep neural networks facilitates accelerated imaging with improved signal-to-noise ratio and spatial resolution, enhancing image quality with short scan times. DLR focuses on supervised learning applied to clinical implementation and applications. Quantitative MRI techniques, exemplified by 2D multidynamic multiecho, 3D quantification using interleaved Look-Locker acquisition sequences with T2 preparation pulses, and magnetic resonance fingerprinting, enable precise calculation of brain-tissue parameters and further advance diagnostic accuracy and efficiency. Potential DLR instabilities and quantification and bias limitations will be discussed. This review underscores the synergistic potential of DLR and quantitative MRI, offering prospects for improved brain imaging beyond conventional methods.

Advancements and Challenges in Algebraic Techniques for Medical Imaging: A Comprehensive Review of MRI and CT Scan Applications in Nigeria

Medical imaging plays a crucial role in modern healthcare by providing essential diagnostic and treatment information. This review examines the advancements and challenges of algebraic techniques in enhancing Magnetic Resonance Imaging (MRI) and Computed Tomography (CT) scans in Nigeria. Algebraic methods, including Algebraic Reconstruction Techniques (ART), Compressed Sensing (CS), and Total Variation (TV) regularization, are integral in refining image reconstruction processes, reducing noise, and improving diagnostic accuracy. These techniques facilitate high-resolution imaging, artifact correction, and effective data fusion across different modalities. Despite the promising advancements, Nigeria faces several challenges, including high implementation costs, limited access to advanced imaging equipment, and a shortage of trained professionals. The economic barriers and disparities in technology access underscore the need for strategic investments, policy support, and collaborative initiatives to broaden the reach of these techniques. Successful case studies from institutions such as Lagos University Teaching Hospital and University College Hospital, Ibadan, highlight the tangible benefits of algebraic imaging techniques, including enhanced diagnostic clarity and reduced scan times. Training and education are essential for leveraging these advanced techniques, necessitating interdisciplinary programs and international collaborations. The integration of algebraic methods holds transformative potential for Nigeria's healthcare system, improving patient outcomes through early disease detection, precise treatment planning, and expanded access to advanced imaging services. Addressing the associated challenges through targeted efforts and continued innovation will further enhance diagnostic practices and healthcare delivery in Nigeria. Keywords: Algebraic Techniques, Medical Imaging, Magnetic Resonance Imaging (MRI), Computed Tomography (CT), Nigeria.

Subject-specific atlas for automatic brain tissue segmentation of neonatal magnetic resonance images

Developing advanced systems for 3D brain tissue segmentation from neonatal magnetic resonance (MR) images is vital for newborn structural analysis. However, automatic segmentation of neonatal brain tissues is challenging due to smaller head size and inverted T1/T2 tissue contrast compared to adults. In this work, a subject-specific atlas based technique is presented for segmentation of gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF) from neonatal MR images. It involves atlas selection, subject-specific atlas creation using random forest (RF) classifier, and brain tissue segmentation using the expectation maximization-Markov random field (EM-MRF) method. To increase the segmentation accuracy, different tissue intensity- and gradient-based features were used. Evaluation on 40 neonatal MR images (gestational age of 37–44 weeks) demonstrated an overall accuracy of 94.3% and an average Dice similarity coefficient (DSC) of 0.945 (GM), 0.947 (WM), and 0.912 (CSF). Compared to multi-atlas segmentation methods like SEGMA and EM-MRF with multiple atlases, our method improved accuracy by up to 4%, particularly in complex tissue regions. Our proposed method allows accurate brain tissue segmentation, a crucial step in brain magnetic resonance imaging (MRI) applications including brain surface reconstruction and realistic head model creation in neonates.

Pelvic congestion syndrome analysis through quantitative 2-dimensional phase-contrast magnetic resonance imaging: A promising vision from an observational cohort study.

To examine the application of quantitative 2-dimensional phase-contrast magnetic resonance imaging (2D PC-MRI) for treating patients with pelvic congestion syndrome (PCS). We conducted a retrospective cross-sectional analysis by using quantitative 2D PC-MRI data enrolled between April 2017 and Sep 2023. In addition, 32 healthy female controls (HCs) were included. Most patients with PCS presented with chronic pelvic pain and more than half had extra-pelvic venous symptoms (80/81, 98% and 45/81, 56%, respectively). Quantitative 2D PC-MRI analyzed the 81 patients with PCS, 239 patients without PCS, and 32 HCs. The patients with PCS had higher stroke volume (SV), absolute SV (ASV), and mean flux (MF) in the calf region (interstitial pixel shift) than did the HCs. In the left gonadal vein, the patients with PCS had higher SV, backward flow volume (BFV), ASV, and MF and lower forward flow volume (FFV), stroke distance (SD), and mean velocity (MV) than did the HCs. However, the patients with PCS had lower SV, FFV, MF, SD, and MV in the great saphenous veins. Quantitative 2D PC-MRI analysis revealed that the PCS group had higher SV, FFV, BFV, ASV, and MF in the calf region than did the non-PCS group. The variables that most strongly differentiated the patients with PCS from the HCs were SV in the great saphenous veins, SD in the great saphenous veins and left gonadal vein, and MV in the great saphenous veins and left gonadal vein. Caudal flow in the left gonadal vein was identified in half of the patients with PCS (39/81, 48.1%); 14 of them received embolization for left gonadal vein. In additional to providing an objective 3-dimensional morphology of the pelvic veins and extra-pelvic leaks, quantitative 2D PC-MRI analysis reveals distinct hemodynamic profiles between patients with PCS, those without PCS, and HCs, especially in the gonadal veins and regional perfusion of the calves.

Allysine-Targeted Molecular MRI Enables Early Prediction of Chemotherapy Response in Pancreatic Cancer.

Neoadjuvant therapy is routinely used in pancreatic ductal adenocarcinoma (PDAC), but not all tumors respond to this treatment. Current clinical imaging techniques are not able to precisely evaluate and predict the response to neoadjuvant therapies over several weeks. A strong fibrotic reaction is a hallmark of a positive response, and during fibrogenesis, allysine residues are formed on collagen proteins by the action of lysyl oxidases. Here, we report the application of an allysine-targeted molecular MRI probe, MnL3, to provide an early, noninvasive assessment of treatment response in PDAC. Allysine increased 2- to 3-fold after one dose of neoadjuvant therapy with FOLFIRINOX in sensitive human PDAC xenografts in mice. Molecular MRI with MnL3 could specifically detect and quantify fibrogenesis in PDAC xenografts. Comparing the MnL3 signal before and 3 days after one dose of FOLFIRINOX predicted subsequent treatment response. The MnL3 tumor signal increased by 70% from day 0 to day 3 in mice that responded to subsequent doses of FOLFIRINOX, whereas no signal increase was observed in FOLFIRINOX-resistant tumors. This study indicates the promise of allysine-targeted molecular MRI as a noninvasive tool to predict chemotherapy outcomes. Significance: Allysine-targeted molecular MRI can quantify fibrogenesis in pancreatic tumors and predict response to chemotherapy, which could guide rapid clinical management decisions by differentiating responders from nonresponders after treatment initiation.

Advanced magnetic resonance imaging in human placenta: insights into fetal growth restriction and congenital heart disease.

Placental function plays a crucial role in fetal development, as it serves as the primary interface for delivery of nutrients and oxygen from the mother to fetus. Magnetic resonance imaging (MRI) has significantly improved our ability to visualize and understand the placenta's complex structure and function. This review provides an up-to-date examination of the most common and novel placental MRI techniques. It will also discuss the clinical applications of MRI in diagnosing and monitoring placental insufficiency, as well as its implications for fetal growth restriction (FGR) and congenital heart disease (CHD). Ongoing research using multi-parametric MRI techniques aims to develop novel biomarkers and uncover the relationships between placental parameters and pre-onset diseased states, ultimately contributing to better maternal and fetal health outcomes, which is essential to better guide clinical judgement.