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To determine the diagnostic accuracy and reproducibility of conventional MR imaging (MRI) of the shoulder in evaluating biceps pulley lesions using arthroscopy as the standard of reference. In a retrospective study, MR examinations of 68 patients with arthroscopically proven torn or intact biceps pulley were assessed for the presence of pulley lesions by three radiologists. The following criteria were evaluated: displacement of the long head of the biceps tendon (LHBT) relative to the subscapularis tendon (displacement sign), subluxation/dislocation of the LHBT, the integrity of the superior glenohumeral ligament (SGHL) and the coracohumeral ligament (CHL), lesions of the supraspinatus (SSP) and subscapularis (SSC) tendons adjacent to the rotator interval, presence of biceps tendinopathy and subacromial bursitis. There were 42 patients with pulley lesions in the study group. Conventional MR imaging showed an overall sensitivity of 95.2%, 88.1% and 92.9%, a specificity of 61.5%, 73.1%, and 80.8% and an accuracy of 82.4%, 82.4% and 88.2% in the diagnosis of pulley lesions. Interobserver agreement was substantial (multirater k = 0.75). Biceps tendinopathy (97.6%, 95.2%, 97.6%), defects of the SGHL (86.3%, 81.0%, 88.1%) and the displacement sign (88.1%, 81.0%, 85.7%) were the most sensitive diagnostic criteria. Subluxation/dislocation of the LHBT was insensitive (78.6%, 42.9%, 33.3%), but specific (69.2%, 100,0%, 96.2%). In the diagnosis of pulley lesions, conventional MR imaging is reproducible and shows high sensitivity and accuracy but moderate specificity. [ABSTRACT FROM AUTHOR]

Simple Summary: Differentiating atypical lipomatous tumors from lipomas on MR images is a challenging task due to similar imaging characteristics. Given these challenges, it would be highly beneficial to develop a reliable diagnostic tool, thereby minimizing the need for invasive diagnostic procedures. Therefore, the aim of this study was to develop and validate radiogenomic machine-learning models to predict the MDM2 gene amplification status in order to differentiate between ALTs and lipomas on preoperative MR images. The best machine-learning model was based on radiomic features from multiple MR sequences using a LASSO algorithm and showed a high discriminatory power to predict the MDM2 gene amplification. Due to the varying settings in which patients with lipomatous tumors present, this model may enhance the clinical diagnostic workup. Background: The aim of this study was to develop and validate radiogenomic models to predict the MDM2 gene amplification status and differentiate between ALTs and lipomas on preoperative MR images. Methods: MR images were obtained in 257 patients diagnosed with ALTs (n = 65) or lipomas (n = 192) using histology and the MDM2 gene analysis as a reference standard. The protocols included T2-, T1-, and fat-suppressed contrast-enhanced T1-weighted sequences. Additionally, 50 patients were obtained from a different hospital for external testing. Radiomic features were selected using mRMR. Using repeated nested cross-validation, the machine-learning models were trained on radiomic features and demographic information. For comparison, the external test set was evaluated by three radiology residents and one attending radiologist. Results: A LASSO classifier trained on radiomic features from all sequences performed best, with an AUC of 0.88, 70% sensitivity, 81% specificity, and 76% accuracy. In comparison, the radiology residents achieved 60–70% accuracy, 55–80% sensitivity, and 63–77% specificity, while the attending radiologist achieved 90% accuracy, 96% sensitivity, and 87% specificity. Conclusion: A radiogenomic model combining features from multiple MR sequences showed the best performance in predicting the MDM2 gene amplification status. The model showed a higher accuracy compared to the radiology residents, though lower compared to the attending radiologist. [ABSTRACT FROM AUTHOR]

Simple Summary: Since prostate MRI is increasingly applied and yet limited by long acquisition times, we prospectively investigated the performance of a novel reconstruction algorithm combining compressed sensing, parallel imaging and deep learning (C-SENSE AI) in patients with histologically proven prostate cancer. Highly accelerated T2w images were compared to clinical standard-of-reference T2w images. C-SENSE AI enabled a 58% acceleration in T2w imaging of the prostate while obtaining significantly better image quality and tumor detection. C-SENSE AI seems particularly interesting in view of the need for accelerated prostate MRI (e.g., in screening protocols) with preserved high image quality. Background: To assess the performance of prospectively accelerated and deep learning (DL) reconstructed T2-weighted (T2w) imaging in volunteers and patients with histologically proven prostate cancer (PCa). Methods: Prospectively undersampled T2w datasets were acquired with acceleration factors of 1.7 (reference), 3.4 and 4.8 in 10 healthy volunteers and 23 patients with histologically proven PCa. Image reconstructions using compressed SENSE (C-SENSE) and a combination of C-SENSE and DL-based artificial intelligence (C-SENSE AI) were analyzed. Qualitative image comparison was performed using a 6-point Likert scale (overall image quality, noise, motion artifacts, lesion detection, diagnostic certainty); the T2 and PI-RADS scores were compared between the two reconstructions. Additionally, quantitative image parameters were assessed (apparent SNR, apparent CNR, lesion size, line profiles). Results: All C-SENSE AI-reconstructed images received a significantly higher qualitative rating compared to the C-SENSE standard images. Analysis of the quantitative parameters supported this finding, with significantly higher aSNR and aCNR. The line profiles demonstrated a significantly steeper signal change at the border of the prostatic lesion and the adjacent normal tissue in the C-SENSE AI-reconstructed images, whereas the T2 and PI-RADS scores as well as the lesion size did not differ. Conclusion: In this prospective study, we demonstrated the clinical feasibility of a novel C-SENSE AI reconstruction enabling a 58% acceleration in T2w imaging of the prostate while obtaining significantly better image quality. [ABSTRACT FROM AUTHOR]

Purpose: UTE sequences typically acquire data during the ramping up of the gradient fields, which makes UTE imaging prone to eddy current and system delay effects. The purpose of this work was to use a simple gradient impulse response function (GIRF) measurement to estimate the real readout gradient waveform and to demonstrate that precise knowledge of the gradient waveform is important in the context of high‐resolution UTE musculoskeletal imaging. Methods: The GIRF was measured using the standard hardware of a 3 Tesla scanner and applied on 3D radial UTE data (TE: 0.14 ms). Experiments were performed on a phantom, in vivo on a healthy knee, and in vivo on patients with spine fractures. UTE images were reconstructed twice, first using the GIRF‐corrected gradient waveforms and second using nominal‐corrected waveforms, correcting for the low‐pass filter characteristic of the gradient chain. Results: Images reconstructed with the nominal‐corrected gradient waveforms exhibited blurring and showed edge artifacts. The blurring and the edge artifacts were reduced when the GIRF‐corrected gradient waveforms were used, as shown in single‐UTE phantom scans and in vivo dual‐UTE gradient‐echo scans in the knee. Further, the importance of the GIRF‐based correction was indicated in UTE images of the lumbar spine, where thin bone structures disappeared when the nominal correction was employed. Conclusion: The presented GIRF‐based trajectory correction method using standard scanner hardware can improve the quality of high‐resolution UTE musculoskeletal imaging. [ABSTRACT FROM AUTHOR]

Despite advances in prevention, risk assessment and treatment, coronary artery disease (CAD) remains the leading cause of morbidity and mortality in Western countries. The lion's share is due to acute coronary syndromes (ACS), which are predominantly triggered by plaque rupture or erosion and subsequent coronary thrombosis. As the majority of vulnerable plaques does not cause a significant stenosis, due to expansive remodeling, and are rather defined by their composition and biological activity, detection of vulnerable plaques with x-ray angiography has shown little success. Non-invasive vulnerable plaque detection by identifying biological features that have been associated with plaque progression, destabilization and rupture may therefore be more appropriate and may allow earlier detection, more aggressive treatment and monitoring of treatment response. MR molecular imaging with target specific molecular probes has shown great promise for the noninvasive in vivo visualization of biological processes at the molecular and cellular level in animals and humans. Compared to other imaging modalities; MRI can provide excellent spatial resolution; high soft tissue contrast and has the ability to simultaneously image anatomy; function as well as biological tissue composition and activity. [ABSTRACT FROM AUTHOR]

Abstract: Objective: Molecular magnetic resonance imaging (MRI) has emerged as a promising non-invasive modality to characterize atherosclerotic vessel wall changes on a morphological and molecular level. Intraplaque and endothelial fibrin has recently been recognized to play an important role in the progression of atherosclerosis. This study aimed to investigate the feasibility of intraplaque and endothelial fibrin detection using a fibrin-targeted contrast-agent, FTCA (EPIX Pharmaceuticals, Lexington, MA), in a mouse model of atherosclerosis. Methods: Male apolipoproteinE-knockout mice (ApoE−/−) were fed a high fat diet (HFD) for one to three months. MRI of the brachiocephalic artery was performed prior to and 90min after the administration of FTCA (n =8 per group). Contrast to noise ratios (CNR) and longitudinal relaxation rates (R1) of plaques were determined and compared to ex vivo fibrin density measurements on immunohistological sections stained with a fibrin-specific antibody and gadolinium concentrations measured by inductively coupled mass spectroscopy (ICP-MS). Results: Molecular MRI after FTCA administration demonstrated a significant increase (p <0.05) in contrast agent uptake in brachiocephalic artery plaques. In vivo CNR measurements were in good agreement with ex vivo fibrin density measurements on immunohistochemistry (y =2.4x +11.3, R 2 =0.82) and ICP-MS (y =0.95x +7.1, R 2 =0.70). Late stage atherosclerotic plaques displayed the strongest increase in CNR, R1, ex vivo fibrin staining and gadolinium concentration (p <0.05). Conclusion: This study demonstrated the feasibility of intraplaque and endothelial fibrin imaging using FTCA. Direct in vivo fibrin detection and quantification could be useful for characterization and staging of coronary and carotid atherosclerotic lesions, which may aid diagnosis and intervention. [Copyright &y& Elsevier]

Imaging studies of cardiovascular disease in small rodents have become a prerequisite in preclinical cardiovascular research. Transgenic and gene-knockout models of cardiovascular diseases enables the investigation of the influence of single genes or groups of genes on disease pathogenesis. In addition, experimental and genetically altered models provide valuable in vivo platforms to investigate the efficacy of novel drugs and contrast agents. Owing to the excellent soft tissue contrast, high spatial and temporal resolution, as well as the tomographic nature of MRI, anatomy and function can be assessed with unique accuracy and reproducibility. Furthermore, using novel targeted MRI contrast agents, molecular changes associated with cardiovascular disease can be investigated in the same imaging session. This review focuses on recent advances in hardware, imaging sequences and probe design. [ABSTRACT FROM AUTHOR]

This review summarizes the current status of molecular imaging of the extracellular matrix (ECM) in the context of atherosclerosis. Apart from cellular components, the ECM of the atherosclerotic plaque plays a relevant role during the initiation of atherosclerosis and its' subsequent progression. Important structural and signaling components of the ECM include elastin, collagen and fibrin. However, the ECM not only plays a structural role in the arterial wall but also interacts with different cell types and has important biological signaling functions. Molecular imaging of the ECM has emerged as a new diagnostic tool to characterize biological aspects of atherosclerotic plaques, which cannot be characterized by current clinically established imaging techniques, such as X-ray angiography. Different types of molecular probes can be detected in vivo by imaging modalities such as magnetic resonance imaging (MRI), positron emission tomography (PET) and single photon emission computed tomography (SPECT). The modality specific signaling component of the molecular probe provides information about its spatial location and local concentration. The successful introduction of molecular imaging into clinical practice and guidelines could open new pathways for an earlier detection of disease processes and a better understanding of the disease state on a biological level. Quantitative in vivo molecular parameters could also contribute to the development and evaluation of novel cardiovascular therapeutic interventions and the assessment of response to treatment. [ABSTRACT FROM AUTHOR]

Purpose: To evaluate the diagnostic performance of susceptibility-weighted magnetic resonance imaging (SWMR) for the differentiation of sclerotic and non-sclerotic Modic changes (MC) of the spine compared to computed tomography (CT) and radiographs.Materials and Methods: The Institutional Ethics-Review-Board approved this prospective study in advance. Written consent was obtained from all subjects. SWMR and standard T1/T2 MR of the cervical (n=21) and/or lumbar spine (n=34) were performed in 54 patients. 21 patients served as control. 18 patients were evaluated with CT; in all other patients radiographs were available. 67 Modic changes were identified on T1/T2 MR. On SWMR changes were classified as sclerotic and non-sclerotic based on signal intensity measurements. The sensitivity and specificity of SWMR and T1/T2 MR for differentiating between sclerotic and non-sclerotic Modic changes were determined with CT and radiographs as reference standard.Results: On SWMR, signal measurements between sclerotic and non-sclerotic Modic changes differed significantly (p<0.01). On T1- and T2-weighted MR no significant difference (p>0.05) was measured. On SWMR, a reliable differentiation between sclerotic and non-sclerotic Modic changes could be achieved, with a sensitivity of 100% and specificity of 95%. In contrast, the combination of T1-/T2-weighted MR yielded a significantly lower sensitivity to detect sclerosis (20%).Conclusion: SWMR allows a reliable detection of sclerosis in Modic changes with a higher accuracy compared to standard spine MR sequences, using radiographs and CT as reference standard. [ABSTRACT FROM AUTHOR]