Soft Tissue Contrast Research Articles

Neck lumps: Early Detection with Dental Magnetic Resonance Imaging?

Cervical lymphadenopathy can indicate a range of diseases, including infections, inflammation, and neoplastic processes. Accurate diagnosis is crucial for identifying the underlying cause and determining appropriate treatment. Diagnostic procedures include clinical examination, ultrasound, fine needle aspiration, biopsy, and imaging techniques. While conventional imaging methods such as X-ray and computed tomography (CT) have proven useful, they exhibit limitations in sensitivity and specificity, especially for soft tissue structures. Magnetic resonance imaging (MRI) provides superior soft tissue contrast, offering additional critical information for differential diagnosis. This article presents a case study of a 29-year-old male with a cervical mass. Advanced dental MRI protocols, including DESS, SPACE-SPAIR, and SPACE-STIR sequences, have significantly enhanced the imaging capabilities of the den-tomaxillofacial region, enabling the generation of high-resolution images of both hard and soft tissues. Especially, MR OPGs have demonstrated the capacity to identify early signs of potential pathology. These protocols have the potential to enhance early detection, thereby con-tributing to accurate diagnosis and effective treatment planning.

Positron emission tomography-magnetic resonance imaging applications in pediatric musculoskeletal tumors.

The hybrid imaging positron emission tomography/magnetic resonance (PET/MR) is an important tool in the management of pediatric oncology patients, particularly in malignant musculoskeletal pathologies, because it combines the functional and metabolic information of tumor provided by PET with the high soft-tissue contrast and the functional information offered by magnetic resonance imaging (MRI). We performed an observational retrospective study that included pediatric patients diagnosed with primary bone or soft-tissue sarcomas in the Pediatric Hematology and Oncology Unit at the HM Montepríncipe University Hospital, Boadilla del Monte, Madrid (Spain) who underwent whole-body 18F-fluorodeoxyglucose (18F-FDG) PET/MRI as a staging study and for follow-up evaluation for treatment response from September 2017 to January 2023. This study explores the protocols, the practical application of the PET/MRI technique and our clinical experience at our center in the diagnosis and follow-up of primary bone tumors and soft-tissue sarcomas in children. Seventy-one 18F-PET/MR studies were performed on 39 patients. Most of them (55%) were initial extension studies and (45%) were follow-up studies. Most of the patients studied were male (74.4%) with a median age of 15 years. Of the 39 cases, 51% were primary bone tumors while 18% were Langerhans cell histiocytosis and 21% soft tissue tumors. Of the 71 studies, five showed metastases at the initial diagnosis, three presented lymph node involvement, one with local infiltration, and one with pulmonary metastasis. PET/MR has represented a significant advancement in the evaluation of pediatric malignant neoplasms, with specific applications in musculoskeletal tumors showing clear benefits over PET/CT. The primary advantage is the reduction in ionizing radiation doses and the assessment of soft tissues, making it an excellent option for malignant musculoskeletal pathologies in pediatric patients who often require long-term follow-up. It is particularly useful for early tumor detection and functional therapy monitoring in oncology. The development of new protocols is making studies increasingly faster and better tolerated, even without the need for anesthesia. PET/MRI has shown to increase diagnostic accuracy in primary bone and soft tissue tumors, as it allows for the comprehensive evaluation of their morpho-metabolic characteristics, locoregional, and distant involvement in a single study. It is also useful in surgical planning and post-treatment follow-up.

Feasibility of using toroidal transceivers for acquiring intraoperative MR images around deep brain stimulation electrodes

IntroductionMagnetic resonance imaging (MRI) provides excellent soft tissue contrast for visualizing of deep brain stimulation (DBS) targets, allowing validation of the electrode placement, and assessing complications such as microhemorrhage and edema. However, the presence of the electrodes can introduce challenges such as radiofrequency (RF) induced current artifacts and excessive heating of the electrode contacts. Additionally, extended procedure times are also considered a disadvantage when using MRI as an intraoperative imaging modality following DBS electrode placement. MethodWe propose a novel approach of using toroidal resonators to inductively couple the shaft of the electrode to the scanner's transmit-receive chain thereby utilizing it as a localized imaging antenna. The small extent of the field generated by the electrode antenna allows fast imaging with smaller field-of-views (FOVs) spanning only a few centimeters. Furthermore, we present a fast and accurate safety monitoring strategy that can be used to predict the temperature increase at the electrical contacts of the electrode. Results and DiscussionImaging with the toroidal transceiver yields a higher signal-to-noise ratio (SNR) efficiency in proximity to the electrodes. This approach reduced the RF induced current artifacts around the electrode which enhanced the visibility of the shaft and improved electrode localization. Moreover, the limited sensitivity around the electrode can be exploited to perform fast scans with small FOVs. The predicted heating around DBS contacts was in quantitative agreement with the experimental heating in swine studies with a normalized root-mean-square error (NRMSE) ≤ 0.09.

Grating-based phase-contrast computed tomography for breast tissue at an inverse compton source

The introduction of mammography screening programs has significantly reduced breast cancer mortality rates. Nevertheless, some lesions remain undetected, especially in dense breast tissue. Studies have shown that phase-contrast imaging can improve breast cancer diagnosis by increasing soft tissue contrast. Furthermore, grating-based phase-contrast imaging enables the simultaneous acquisition of absorption, phase-contrast, and scattering, so-called dark-field images. The latter allows the classification of microcalcifications. In addition, breast computed tomography (BCT) systems can identify and discriminate overlapping but clinically relevant structures. This study investigates the benefit of combining grating-based phase-contrast with BCT. We explore the potential of grating-based phase-contrast breast computed tomography (gbpc-BCT) with a breast phantom and a freshly dissected fibroadenoma. Improved image contrast could be achieved with radiation doses comparable to those used in clinical BCT.

Hybrid modality dual-energy imaging aggregating complementary advantages of kV-CT and MV-CBCT: concept proposal and clinical validation

Megavoltage cone-beam CT (MV-CBCT) is advantageous in metal artifact reduction during Image-Guided Radiotherapy (IGRT), although it is limited by poor soft tissue contrast. This study proposed and evaluated a novel hybrid modality dual-energy (DE) imaging method combining the complementary advantages of kV-CT and MV-CBCT.
Approach: The kV-CT and MV-CBCT images were acquired on a planning CT scanner and a Halcyon linear accelerator respectively. After rigid registration, images of basis materials were generated using the iterative decomposition method in the volumetric images. The decomposition accuracy was quantitatively evaluated on a Gammex 1472 phantom. The performance of contrast enhancement and metal artifact reduction in virtual monochromatic images were evaluated on both phantom and patient studies.
Main results: Using the proposed method, the mean percentage errors for RED and SPR were 0.90% and 0.81%, outperforming the clinical single-energy mapping method with mean errors of 1.28% and 1.07%, respectively. The contrasts of soft-tissue insets were enhanced by a factor of 2~3 at 40 keV compared to kV-CT. The standard deviation in the metal artifact area was reduced by ~67%, from 42 HU (kV-CT) to 14 HU (150 keV monochromatic). The head and neck patient test showed that the percent error of soft-tissue RED in the metal artifact area was reduced from 18.1% (HU-RED conversion) to less than 1.0% (the proposed method), which was equivalent to the maximum dosimetric difference of 28.7% based on the patient-specific plan.
Significance: Without hardware modification or extra imaging dose, the proposed hybrid modality method enabled kV-MV DE imaging, providing improved accuracy of quantitative analysis, soft-tissue contrast and metal artifact suppression for more accurate IGRT.&#xD.

Development of a nanometre scale X-ray speckle-based CT technique through the 3-D histological assessment of an acute respiratory distress syndrome model

The study of biological soft tissue structures at the micron scale details the function of healthy and pathological tissues, which is vital in the diagnosis and treatment of diseases. Speckle based X-ray phase contrast tomographic scans at a nanometer scale have the potential to thoroughly analyse such tissues in a quantitative and qualitative manner. Diamond light source, the UKs national synchrotron facility developed and refined a 1-D X-ray speckle-based imaging technique, referred to as Fly scan mode. This novel image acquisition technique was used to perform a rapid structural composition scan of rodent lung histology samples. The rodent samples were taken from healthy and Staphylococcus aureus induced acute respiratory distress syndrome models. The analysis and cross comparison of the fly scan method, absorption-based tomography and conventional histopathology H&E staining microscopy are discussed in this paper. This analysis and cross comparison outline the ways the speckle-based technique can be of benefit. These advantages include improved soft tissue contrast, 3-D volumetric rendering, segmentation of specific gross tissue structures, quantitative analysis of gross tissue volume. A further advantage is the analysis of cellular distribution throughout the volumetric rendering of the tissue sample. The study also details the current limitations of this technique and points to ways in which future work on this imaging modality may progress.

Modeling of artificial intelligence-based respiratory motion prediction in MRI-guided radiotherapy: a review.

The advancement of precision radiotherapy techniques, such as volumetric modulated arc therapy (VMAT), stereotactic body radiotherapy (SBRT), and particle therapy, highlights the importance of radiotherapy in the treatment of cancer, while also posing challenges for respiratory motion management in thoracic and abdominal tumors. MRI-guided radiotherapy (MRIgRT) stands out as state-of-art real-time respiratory motion management approach owing to the non-ionizing radiation nature and superior soft-tissue contrast characteristic of MR imaging. In clinical practice, MR imaging often operates at a frequency of 4Hz, resulting in approximately a 300 ms system latency of MRIgRT. This system latency decreases the accuracy of respiratory motion management in MRIgRT. Artificial intelligence (AI)-based respiratory motion prediction has recently emerged as a promising solution to address the system latency issues in MRIgRT, particularly for advanced contour prediction and volumetric prediction. However, implementing AI-based respiratory motion prediction faces several challenges including the collection of training datasets, the selection of prediction methods, and the formulation of complex contour and volumetric prediction problems. This review presents modeling approaches of AI-based respiratory motion prediction in MRIgRT, and provides recommendations for achieving consistent and generalizable results in this field.

7659 Iodinated Contrast Induced Thyrotoxicosis Leading to Takotsubu Cardiomyopathy

Abstract Disclosure: A. Jain: None. E. Naous: None. S. Sedrakyan: None. A.T. Sweeney: None. Background: Thyrotoxicosis may cause many cardiovascular manifestations including tachycardia, hypertension, atrial fibrillation and heart failure. Iatrogenic exposure to iodinated contrast media (ICM) precipitating iodine induced thyrotoxicosis (or the Jod-Basedow phenomenon) is often overlooked. Here, we describe a case of iodine induced thyrotoxicosis leading to takotsubu cardiomyopathy, following multiple exposures to ICM. Case Presentation: An 88-year-old male with a history of hypertension, dyslipidemia, chronic obstructive pulmonary disease, and an ED visit one month ago for hemoptysis for which a CT Angiography (CTA) of the chest was obtained (which excluded Pulmonary Embolism(PE)), presented with fever and shortness of breath. On physical examination his temperature was 100.3F, heart rate was 104bpm, blood pressure 130/62mmHg, respiratory rate was 20/min and saturation was 88% (room air). He was frail but his examination was otherwise unremarkable. Electrocardiogram (EKG) revealed sinus tachycardia. Chest CTA excluded PE. Transthoracic echocardiogram (TTE) showed an ejection fraction (EF) of 73% and no wall motion abnormalities. He was admitted to the hospital for a viral upper respiratory infection and was treated conservatively with bronchodilators. Odynophagia prompted a CT with contrast of the neck soft tissue, which was unrevealing. He was planned to be discharged the next day, but overnight developed severe abdominal pain, and atrial fibrillation with a rapid ventricular response (Troponin t was 191 ng/L (normal {nl}: <9 ng/L)). EKG showed new T-wave inversions in the anterolateral leads, raising a suspicion of myocardial ischemia. A repeated TTE revealed a new drop in EF from 73 to 41%, with new apical akinesis, suspicious for takotsubo cardiomyopathy. CT of the abdomen with contrast was unrevealing. Lab results showed a suppressed TSH of <0.01uIU/mL (nl: 0.34-5.60 uIU/mL), elevated FT4 of 13ng/dL (nl: 0.93-1.70 ng/dL), and TSI 4.97 IU/ L (nl: 0-0.55 IU/ L). Endocrinology was consulted. His thyroid examination was normal, and he had no eye findings. Neck ultrasound revealed a homogeneous thyroid gland without any nodules. His clinical course was consistent with the diagnosis of acute thyrotoxicosis precipitating takotsubu cardiomyopathy. He likely developed iodine induced thyrotoxicosis from multiple exposures to ICM, in a background of previously undiagnosed Graves’ disease. Discussion: Screening for thyroid disease is critical in patients with new onset tachyarrhythmias and stress cardiomyopathy. Iodine induced thyrotoxicosis typically presents after patients with underlying thyroid disease are exposed to iodinated contrast. Prior to ordering studies requiring ICM, it is important to thoroughly evaluate patients for possible pre-existing thyroid disease. Presentation: 6/2/2024

Static X-ray differential phase contrast imaging via bidirectional-misalignment grating

Grating-based X-ray differential phase contrast imaging (GB-DPCI) offers excellent imaging contrast for soft tissues. Limited by the phase stepping of gratings, the conventional GB-DPCI leads to a high radiation dose. This study presents a static GB-DPCI method employing an analyzer grating with a misaligned structure in both vertical and horizontal directions. A signal retrieval algorithm is developed for this method to permit the use of neighboring pixels on the detector to approximate multiple phase stepping positions, thereby obtaining the phase contrast signal in a single exposure. This study reduces high radiation doses and time-consumption caused by phase stepping. The presented method is validated with datasets from a laboratory X-ray tube and synchrotron radiation. Considering synchrotron results as example, minimal improvements in Feature Similarity Index Measure are 2.48%, 6.31%, and 7.06% for absorption, dark field, and phase contrasts, and in Information-Weight Structure Similarity Index Measure are 3.24%, 16.07%, and 8.61%.

A simulation study of MR-guided proton therapy system using iron-yoked superconducting open MRI: a conceptual study.

Radiotherapy platforms integrated with magnetic resonance imaging (MRI) have been significantly successful and widely used in X-ray therapy over the previous decade. MRI provides greater soft-tissue contrast than conventional X-ray techniques, which enables more precise radiotherapy with on-couch adaptive treatment planning and direct tracking of moving tumors. The integration of MRI into a proton beam irradiation system (PBS) is still in the research stage. However, this could be beneficial as proton therapy is more sensitive to anatomical changes and organ motion. In this simulation study, we considered the integration of PBS into the 0.3-T superconducting open MRI system. Our proposed design involves proton beams traversing a hole at the center of the iron yoke, which allows for a reduced fringe field in the irradiation nozzle while maintaining a large proton scan field of the current PBS. The shape of the bipolar MRI magnets was derived to achieve a large MRI field-of-view. To monitor the beam position and size accurately while maintaining a small beam size, the beam monitor installation was redesigned from the current system. The feasibility of this system was then demonstrated by the treatment plan quality, which showed that the magnetic field did not deteriorate the plan quality from that without the magnetic field for both a rectangular target and a prostate case. Although numerous challenges remain before the proposed simulation model can be implemented in a clinical setting, the presented conceptual design could assist in the initial design for the realization of the MR-guided proton therapy.

Image quality of virtual monochromatic and material density iodine images for evaluation of head and neck neoplasms using deep learning-based CT image reconstruction – A retrospective observational study

PurposeTo compare the quality of deep learning image reconstructed (DLIR) virtual monochromatic images (VMI) and material density (MD) iodine images from dual-energy computed tomography (DECT) for the evaluation of head and neck neoplasms with CT scans from a conventional single-energy protocol. MethodA total of 294 head and neck CT scans (98 VMIs operated at 60 keV, 102 MD iodine images, and 94 images from a 120 kVp single-energy CT (SECT) protocol) were retrospectively evaluated. VMIs and MD iodine images were generated using the Gemstone Spectral Imaging (GSI) mode using DLIR and metal artifact reduction (MAR) algorithms. SECT images were generated using adaptive statistical iterative reconstruction (ASIR-V). Images were scored by two independent readers on a 6-point Likert-type scale for overall image quality, vessel contrast, soft tissue contrast, noise texture, noise intensity, artifact reduction, and sharpness. ResultsSubjective overall image quality was rated as superior or excellent in 98 % of DLIR-based MD iodine images and VMIs, but only in 55 % of ASIR-V-based SECT images. For each individual quality criterion, image quality of VMIs and MD iodine images was rated as better than that of SECT images (p < 0.001 in each case). Noise texture and intensity were rated better in MD iodine images than in VMIs. ConclusionDECT using both DLIR and MAR for the generation of VMIs and MD iodine images resulted in higher subjective quality of oncologic head and neck images than ASIR-V-based SECT. Noise reduction and noise texture were best achieved with DLIR-based MD iodine images.

Comparing the Diagnostic Efficacy of 3D Ultrasound and MRI in the Classification of Müllerian Anomalies.

Müllerian anomalies significantly impact female reproductive health. This study aims to compare the diagnostic efficacy of three-dimensional ultrasound (3D-US) and magnetic resonance imaging (MRI) in detecting and classifying these anomalies. A retrospective analysis of 150 patients with Müllerian anomalies was conducted at Saveetha Medical College and Hospital from March 2018 to March 2024. MRI and 3D-US examinations were performed and analyzed independently by two radiologists. Anomalies were classified according to European Society of Human Reproduction and Embryology (ESHRE)/European Society for Gynaecological Endoscopy (ESGE) and American Society for Reproductive Medicine (ASRM) guidelines. The septate uterus was the most prevalent anomaly, observed in 53 patients (35.3%). MRI demonstrated superior diagnostic accuracy (AUC 0.92) compared to 3D-US (AUC 0.88). Significant associations were found between presenting symptoms and specific anomaly types (p < 0.05). Inter-rater reliability between the two radiologists, with respect to classification of anomalies, was high (Cohen's kappa 0.85). MRI's superior soft-tissue contrast and multiplanar capabilities make it the gold standard for evaluating complex uterine malformations. 3D-US offers valuable real-time imaging and is particularly effective in assessing septum characteristics. The combined use of MRI and 3D-US enhances diagnostic precision and facilitates tailored management strategies. Integrating MRI and 3D-US in clinical practice improves diagnostic accuracy and treatment planning for Müllerian anomalies, ultimately enhancing patient outcomes.

A Novel Framework for Multimodal Brain Tumor Detection with Scarce Labels.

Brain tumor detection has advanced significantly with the development of deep learning technology. Although multimodal data, such as Magnetic Resonance Imaging (MRI) and Computed Tomography (CT), has potential advantages in diagnostics, most existing studies rely solely on a single modality. This is because common fusion methods may lead to the loss of critical information when attempting multimodal fusion. Therefore, effectively integrating multimodal data has become a significant challenge. Additionally, medical image analysis requires large amounts of annotated data, and labeling images is a resourceintensive task that demands experienced professionals to spend a considerable amount of time. To address these challenges, this paper introduces a new unsupervised learning framework named Double-SimCLR. This framework builds on the foundation of contrastive learning and features a dual-branch structure, enabling direct and simultaneous processing of MRI and CT images for multimodal feature fusion. Given the "weak feature" characteristics of CT images (e.g., low soft tissue contrast and low resolution), we incorporated adaptive weight masking technology to enhance CT feature extraction. Moreover, we introduced a multimodal attention mechanism, which ensures that the model focuses on salient information, thereby elevating the precision and robustness of brain tumor detection. Even without substantial labeled data, experimental results demonstrate that Double-SimCLR achieves 93.458% accuracy, 92.463% precision, and a 93.058% F1-score, outperforming state-of-the-art (SOTA) models by 2.871%, 2.643%, and 3.098%, respectively.

Brain Tumor Detection Using Magnetic Resonance Imaging and Convolutional Neural Networks

Early and precise detection of brain tumors is critical for improving clinical outcomes and patient quality of life. This research focused on developing an image classifier using convolutional neural networks (CNN) to detect brain tumors in magnetic resonance imaging (MRI). Brain tumors are a significant cause of morbidity and mortality worldwide, with approximately 300,000 new cases diagnosed annually. Magnetic resonance imaging (MRI) offers excellent spatial resolution and soft tissue contrast, making it indispensable for identifying brain abnormalities. However, accurate interpretation of MRI scans remains challenging, due to human subjectivity and variability in tumor appearance. This study employed CNNs, which have demonstrated exceptional performance in medical image analysis, to address these challenges. Various CNN architectures were implemented and evaluated to optimize brain tumor detection. The best model achieved an accuracy of 97.5%, sensitivity of 99.2%, and binary accuracy of 98.2%, surpassing previous studies. These results underscore the potential of deep learning techniques in clinical applications, significantly enhancing diagnostic accuracy and reliability.

Pseudo‐CT synthesis in adaptive radiotherapy based on a stacked coarse‐to‐fine model: Combing diffusion process and spatial‐frequency convolutions

AbstractBackgroundCone beam computed tomography (CBCT) provides critical anatomical information for adaptive radiotherapy (ART), especially for tumors in the pelvic region that undergo significant deformation. However, CBCT suffers from inaccurate Hounsfield Unit (HU) values and lower soft tissue contrast. These issues affect the accuracy of pelvic treatment plans and implementation of the treatment, hence requiring correction.PurposeA novel stacked coarse‐to‐fine model combining Denoising Diffusion Probabilistic Model (DDPM) and spatial‐frequency domain convolution modules is proposed to enhance the imaging quality of CBCT images.MethodsThe enhancement of low‐quality CBCT images is divided into two stages. In the coarse stage, the improved DDPM with U‐ConvNeXt architecture is used to complete the denoising task of CBCT images. In the fine stage, the deep convolutional network model jointly constructed by fast Fourier and dilated convolution modules is used to further enhance the image quality in local details and global imaging. Finally, the accurate pseudo‐CT (pCT) images consistent with the size of the original data are obtained. Two hundred fifty paired CBCT‐CT images from cervical and rectal cancer, combined with 200 public dataset cases, were used collectively for training, validation, and testing.ResultsTo evaluate the anatomical consistency between pCT and real CT, we have used the mean(std) of structure similarity index measure (SSIM), peak signal to noise ratio (PSNR), and normalized cross‐correlation (NCC). The numerical results for the above three metrics comparing the pCT synthesized by the proposed model against real CT for cervical cancer cases were 87.14% (2.91%), 34.02 dB (1.35 dB), and 88.01% (1.82%), respectively. For rectal cancer cases, the corresponding results were 86.06% (2.70%), 33.50 dB (1.41 dB), and 87.44% (1.95%). The paired t‐test analysis between the proposed model and the comparative models (ResUnet, CycleGAN, DDPM, and DDIM) for these metrics revealed statistically significant differences (p &lt; 0.05). The visual results also showed that the anatomical structures between the real CT and the pCT synthesized by the proposed model were closer. For the dosimetric verification, mean absolute error of dosimetry (MAEdoes) values for the maximum dose (Dmax), the minimum dose (Dmin), and the mean dose (Dmean) in the planning target volume (PTV) were analyzed, with results presented as mean (lower quartile, upper quartile). The experimental results show that the values of the above three dosimetry indexes (Dmin, Dmax, and Dmean) for the pCT images synthesized by the proposed model were 0.90% (0.48%, 1.29%), 0.82% (0.47%, 1.17%), and 0.57% (0.44%, 0.67%). Compared with 10 cases of the original CBCT image by Mann–Whitney test (p &lt; 0.05), it also proved that pCT can significantly improve the accuracy of HU values for the dose calculation.ConclusionThe pCT synthesized by the proposed model outperforms the comparative models in numerical accuracy and visualization, promising for ART of pelvic cancers.

Photon-counting CT for forensic death investigations-a glance into the future of virtual autopsy.

This article explores the potential of photon-counting computed tomography (CT) in forensic medicine for a range of forensic applications. Photon-counting CT surpasses conventional CT in several key areas. It boasts superior spatial and contrast resolution, enhanced image quality at low x-ray energies, and spectral imaging capabilities that enable more precise material differentiation. These advantages translate to superior visualization of bone structures, foreign bodies, and soft tissues in postmortem examinations. The article discusses the technical principles of photon-counting CT detectors and highlights its potential applications in forensic imaging, including high-resolution virtual autopsies, pediatric forensic CT, trauma analysis, and bone density measurements. Furthermore, advancements in vascular imaging and soft tissue contrast promise to propel CT-based death investigations to an even more prominent role. The article concludes by emphasizing the immense potential of this new technology in forensic medicine and anthropology.

CRNN-Refined Spatiotemporal Transformer for Dynamic MRI reconstruction

Magnetic Resonance Imaging (MRI) plays a pivotal role in modern clinical practice, providing detailed anatomical visualization with exceptional spatial resolution and soft tissue contrast. Dynamic MRI, aiming to capture both spatial and temporal characteristics, faces challenges related to prolonged acquisition times and susceptibility to motion artifacts. Balancing spatial and temporal resolutions becomes crucial in real-world clinical scenarios. In the realm of dynamic MRI reconstruction, while Convolutional Recurrent Neural Networks (CRNNs) struggle with long-range dependencies, CRNNs require extensive iterations, impacting efficiency. Transformers, known for their effectiveness in high-dimensional imaging, are underexplored in dynamic MRI reconstruction. Additionally, prevailing algorithms fall short of achieving superior results in demanding generative reconstructions at high acceleration rates. This research proposes a novel approach for dynamic MRI reconstruction, named CRNN-Refined Spatiotemporal Transformer Network (CST-Net). The spatiotemporal Transformer initiates reconstruction, modeling temporal and spatial correlations, followed by refinement using the CRNN. This integration mitigates inaccuracies caused by damaged frames and reduces CRNN iterations, enhancing computational efficiency without compromising reconstruction quality. Our study compares the performance of the proposed CST-Net at 6 × and 12 × undersampling rates, showcasing its superiority over existing algorithms. Particularly, in challenging 25× generative reconstructions, the CST-Net outperforms current methods. The comparison includes experiments under both radial and Cartesian undersampling patterns. In conclusion, CST-Net successfully addresses the limitations inherent in existing generative reconstruction algorithms, thereby paving the way for further exploration and optimization of Transformer-based approaches in dynamic MRI reconstruction. Code and Datasets can be available: https://github.com/XWangBin/CST-Net.

Monitoring Blood-Brain Barrier Opening in Rats with a Preclinical Focused Ultrasound System.

The brain has a highly selective semipermeable blood barrier, termed the blood-brain barrier (BBB), which prevents the delivery of therapeutic macromolecular agents to the brain. The integration of MR-guided low-intensity pulsed focused ultrasound (FUS) with microbubble pre-injection is a promising technique for non-invasive and non-toxic BBB modulation. MRI can offer superior soft-tissue contrast and various quantitative assessments, such as vascular permeability, perfusion, and the spatial-temporal distribution of MRI contrast agents. Notably, contrast-enhanced MRI techniques with gadolinium-based MR contrast agents have been shown to be the gold standard for detecting BBB openings. This study outlines a comprehensive methodology involving MRI protocols and animal procedures for monitoring BBB opening in a rat model. The rat model provides the added benefit of jugular vein catheter utilization, which facilitates rapid medication administration. A stereotactic-guided preclinical FUS transducer facilitates the refinement and streamlining of animal procedures and MRI protocols. The resulting methods are characterized by reproducibility and simplicity, eliminating the need for specialized surgical expertise. This research endeavors to contribute to the optimization of preclinical procedures with rat models and encourage further investigation into the modulation of the BBB to enhance therapeutic interventions in neurological disorders.

Optimized gadolinium-DO3A loading in RAFT-polymerized copolymers for superior MR imaging of aging blood-brain barrier.

The development of gadolinium-based contrast agents (GBCAs) has been pivotal in advancing magnetic resonance imaging (MRI), offering enhanced soft tissue contrast without ionizing radiation exposure. Despite their widespread clinical use, the need for improved GBCAs has led to innovations in ligand chemistry and polymer science. We report a novel approach using methacrylate-functionalized DO3A ligands to synthesize a series of copolymers through direct reversible addition-fragmentation chain transfer (RAFT) polymerization. This technique enables precise control over the gadolinium content within the polymers, circumventing the need for subsequent conjugation and purification steps, and facilitates the addition of other components such as targeting ligands. The resulting copolymers were analysed for their relaxivity properties, indicating that specific gadolinium-DO3A loading contents between 12-30 mole percent yield optimal MRI contrast enhancement. Inductively coupled plasma (ICP) measurements corroborated these findings, revealing a non-linear relationship between gadolinium content and relaxivity. Optimized copolymers were synthesized with the claudin-1 targeting peptide, C1C2, to image BBB targeting in aged mice to show imaging utility. This study presents a promising pathway for the development of more efficient GBCA addition to copolymers for targeted drug delivery and bioimaging application.

Magnetic resonance imaging of the dromedary camel carpus

BackgroundThe dromedary camel (Camelus dromedarius) carpal joint presents multiple joints and constitutes several bones and soft tissues. Radiography and/or ultrasonography of the carpus are challenging due to structural superimposition. High-field magnetic resonance imaging (MRI) technique precludes superimposed tissues and offers high soft tissue contrast in multiple sequences and planes. Hence, understanding the normal MRI anatomy is crucial during clinical investigations. Magnetic resonance imaging is highly sensitive for investigation of soft tissues and articular cartilage; therefore, it is extensively used for outlining joint anatomy and evaluation of a wide range of musculoskeletal conditions. MRI images of a specific anatomical region acquired by using multiple sequences in various planes are necessary for a complete MRI examination. Given the dearth of information on the MRI features of the dromedary camel carpus, the current study demonstrates the MRI appearance of the clinically significant structures in the camel carpus in various sequences and planes using a high-field 1.5 Tesla superconducting magnet. For this purpose, twelve cadaveric forelimbs, obtained from 6 clinically sound lameness free adult dromedary camels, were examined.ResultsThe cortex and medulla of the radius, carpal bones and metacarpus were evaluated. Articular cartilage of the carpal joints was depicted and showed intermediate intensity. Carpal tendons expressed lower signal intensity in all pulse sequences. The collateral and inter-carpal ligaments showed mixed signal intensity.ConclusionsThe obtained data outlines the validation of MRI for investigation of the camel carpus and could set as a reference for interpretation in clinical patients.