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A high load of white matter lesions and enlarged basilar arteries have been shown in selected patients with Fabry disease, a disorder associated with an increased stroke risk. We studied a large cohort of patients with Fabry disease to differentially investigate white matter lesion load and cerebral artery diameters. We retrospectively analyzed cranial magnetic resonance imaging scans of 87 consecutive Fabry patients, 20 patients with ischemic stroke, and 36 controls. We determined the white matter lesion load applying the Fazekas score on fluid-attenuated inversion recovery sequences and measured the diameters of cerebral arteries on 3D-reconstructions of the time-of-flight-MR-angiography scans. Data of different Fabry patient subgroups (males – females; normal – impaired renal function) were compared with data of patients with stroke and controls. A history of stroke or transient ischemic attacks was present in 4/30 males (13%) and 5/57 (9%) females with Fabry disease, all in the anterior circulation. Only one man with Fabry disease showed confluent cerebral white matter lesions in the Fazekas score assessment (1%). Male Fabry patients had a larger basilar artery (p<0.01) and posterior cerebral artery diameter (p<0.05) compared to male controls. This was independent of disease severity as measured by renal function and did not lead to changes in arterial blood flow properties. A basilar artery diameter of >3.2 mm distinguished between men with Fabry disease and controls (sensitivity: 87%, specificity: 86%, p<0.001), but not from stroke patients. Enlarged arterial diameters of the posterior circulation are present only in men with Fabry disease independent of disease severity.
Utilizing 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography (PET)/computed tomography (CT), we performed this pilot study to evaluate the link between cytogenetic/genomic markers and imaging patterns in relapsed/refractory (RR) multiple myeloma (MM). We retrospectively analyzed data of 24 patients with RRMM who were treated at our institution between November 2018 and February 2020. At the last relapse/progression, patients had been treated with a median of three (range 1–10) lines of therapy. Six (25%) patients showed FDG avid extramedullary disease without adjacency to bone. We observed significantly higher maximum standardized uptake values (SUV\(_{max}\)) in patients harboring del(17p) compared with those without del(17p) (p = 0.025). Moreover, a high SUV\(_{max}\) of >15 indicated significantly shortened progression-free survival (PFS) (p = 0.01) and overall survival (OS) (p = 0.0002). One female patient exhibited biallelic TP53 alteration, i.e., deletion and mutation, in whom an extremely high SUV\(_{max}\) of 37.88 was observed. In summary, this pilot study suggested a link between del(17p)/TP53 alteration and high SUV\(_{max}\) on 18F-FDG PET/CT in RRMM patients. Further investigations are highly warranted at this point.
This study aimed to explore the correlation between imaging patterns and clinical features in patients with smoldering multiple myeloma (SMM) who simultaneously underwent 18F-FDG, 11C-Methionine, and 68Ga-Pentixafor positron emission tomography/computed tomography (PET/CT). We retrieved and analyzed clinical characteristics and PET imaging data of 10 patients with SMM. We found a significant correlation between bone marrow (BM) plasma cell (PC) infiltration and mean standardized uptake values (SUV\(_{mean}\)) of lumbar vertebrae L2-L4 on 11C-Methionine PET/CT scans (r = 0.676, p = 0.031) and 68Ga-Pentixafor PET/CT scans (r = 0.839, p = 0.002). However, there was no significant correlation between BM involvement and SUV\(_{mean}\) of lumbar vertebrae L2-L4 on 18F-FDG PET/CT scans (r = 0.558, p = 0.093). Similarly, mean target-to-background ratios (TBR\(_{mean}\)) of lumbar vertebrae L2-L4 also correlated with bone marrow plasma cell (BMPC) infiltration in 11C-Methionine PET/CT (r = 0.789, p = 0.007) and 68Ga-Pentixafor PET/CT (r = 0.724, p = 0.018) PET/CT. In contrast, we did not observe a significant correlation between BMPC infiltration rate and TBR\(_{mean}\) in 18F-FDG PET/CT (r = 0.355, p = 0.313). Additionally, on 11C-Methionine PET/CT scans, we found a significant correlation between BMPC infiltration and TBR\(_{max}\) of lumbar vertebrae L2-L4 (r = 0.642, p = 0.045). In conclusion, 11C-Methionine and 68Ga-Pentixafor PET/CT demonstrate higher sensitivity than 18F-FDG PET/CT in detecting BM involvement in SMM.
Functional magnetic resonance imaging (fMRI) has become a powerful and influential method to non-invasively study neuronal brain activity. For this purpose, the blood oxygenation level-dependent (BOLD) effect is most widely used. T2* weighted echo planar imaging (EPI) is BOLD sensitive and the prevailing fMRI acquisition technique. Here, we present an alternative to its standard Cartesian recordings, i.e. k-space density weighted EPI, which is expected to increase the signal-to-noise ratio in fMRI data. Based on in vitro and in vivo pilot measurements, we show that fMRI by k-space density weighted EPI is feasible and that this new acquisition technique in fact boosted spatial and temporal SNR as well as the detection of local fMRI activations. Spatial resolution, spatial response function and echo time were identical for density weighted and conventional Cartesian EPI. The signal-to-noise ratio gain of density weighting can improve activation detection and has the potential to further increase the sensitivity of fMRI investigations.
Background:
Clinical reasoning in Neurology is based on general associations which help to deduce the site of the lesion. However, even “golden principles” may occasionally be deceptive. Here, we describe the case of subacute flaccid tetraparesis due to motor cortical lesions. To our knowledge, this is the first report to include an impressive illustration of nearly symmetric motor cortical involvement of encephalitis on brain MRI.
Case presentation:
A 51 year old immunocompromized man developed a high-grade pure motor flaccid tetraparesis over few days. Based on clinical presentation, critical illness polyneuromyopathy was suspected. However, brain MRI revealed symmetrical hyperintensities strictly limited to the subcortical precentral gyrus. An encephalitis, possibly due to CMV infection, turned out to be the most likely cause.
Conclusion:
While recognition of basic clinical patterns is indispensable in neurological reasoning, awareness of central conditions mimicking peripheral nervous disease may be crucial to detect unsuspected, potentially treatable conditions.
Background. Missed or delayed detection of progressive neuronal damage after traumatic brain injury (TBI) may have negative impact on the outcome. We investigated whether routine follow-up CT is beneficial in sedated and mechanically ventilated trauma patients. Methods. The study design is a retrospective chart review. A routine follow-up cCT was performed 6 hours after the admission scan. We defined 2 groups of patients, group I: patients with equal or recurrent pathologies and group II: patients with new findings or progression of known pathologies. Results. A progression of intracranial injury was found in 63 patients (42%) and 18 patients (12%) had new findings in cCT 2 (group II). In group II a change in therapy was found in 44 out of 81 patients (54%). 55 patients with progression or new findings on the second cCT had no clinical signs of neurological deterioration. Of those 24 patients (44%) had therapeutic consequences due to the results of the follow-up cCT. Conclusion. We found new diagnosis or progression of intracranial pathology in 54% of the patients. In 54% of patients with new findings and progression of pathology, therapy was changed due to the results of follow-up cCT. In trauma patients who are sedated and ventilated for different reasons a routine follow-up CT is beneficial.
(1) Background: To evaluate radiomics features as well as a combined model with clinical parameters for predicting overall survival in patients with bladder cancer (BCa). (2) Methods: This retrospective study included 301 BCa patients who received radical cystectomy (RC) and pelvic lymphadenectomy. Radiomics features were extracted from the regions of the primary tumor and pelvic lymph nodes as well as the peritumoral regions in preoperative CT scans. Cross-validation was performed in the training cohort, and a Cox regression model with an elastic net penalty was trained using radiomics features and clinical parameters. The models were evaluated with the time-dependent area under the ROC curve (AUC), Brier score and calibration curves. (3) Results: The median follow-up time was 56 months (95% CI: 48–74 months). In the follow-up period from 1 to 7 years after RC, radiomics models achieved comparable predictive performance to validated clinical parameters with an integrated AUC of 0.771 (95% CI: 0.657–0.869) compared to an integrated AUC of 0.761 (95% CI: 0.617–0.874) for the prediction of overall survival (p = 0.98). A combined clinical and radiomics model stratified patients into high-risk and low-risk groups with significantly different overall survival (p < 0.001). (4) Conclusions: Radiomics features based on preoperative CT scans have prognostic value in predicting overall survival before RC. Therefore, radiomics may guide early clinical decision-making.
Objectives
Open-access cancer imaging datasets have become integral for evaluating novel AI approaches in radiology. However, their use in quantitative analysis with radiomics features presents unique challenges, such as incomplete documentation, low visibility, non-uniform data formats, data inhomogeneity, and complex preprocessing. These issues may cause problems with reproducibility and standardization in radiomics studies.
Methods
We systematically reviewed imaging datasets with public copyright licenses, published up to March 2023 across four large online cancer imaging archives. We included only datasets with tomographic images (CT, MRI, or PET), segmentations, and clinical annotations, specifically identifying those suitable for radiomics research. Reproducible preprocessing and feature extraction were performed for each dataset to enable their easy reuse.
Results
We discovered 29 datasets with corresponding segmentations and labels in the form of health outcomes, tumor pathology, staging, imaging-based scores, genetic markers, or repeated imaging. We compiled a repository encompassing 10,354 patients and 49,515 scans. Of the 29 datasets, 15 were licensed under Creative Commons licenses, allowing both non-commercial and commercial usage and redistribution, while others featured custom or restricted licenses. Studies spanned from the early 1990s to 2021, with the majority concluding after 2013. Seven different formats were used for the imaging data. Preprocessing and feature extraction were successfully performed for each dataset.
Conclusion
RadiomicsHub is a comprehensive public repository with radiomics features derived from a systematic review of public cancer imaging datasets. By converting all datasets to a standardized format and ensuring reproducible and traceable processing, RadiomicsHub addresses key reproducibility and standardization challenges in radiomics.
Critical relevance statement
This study critically addresses the challenges associated with locating, preprocessing, and extracting quantitative features from open-access datasets, to facilitate more robust and reliable evaluations of radiomics models.
Key points
- Through a systematic review, we identified 29 cancer imaging datasets suitable for radiomics research.
- A public repository with collection overview and radiomics features, encompassing 10,354 patients and 49,515 scans, was compiled.
- Most datasets can be shared, used, and built upon freely under a Creative Commons license.
- All 29 identified datasets have been converted into a common format to enable reproducible radiomics feature extraction.
Purpose
Machine learning based on radiomics features has seen huge success in a variety of clinical applications. However, the need for standardization and reproducibility has been increasingly recognized as a necessary step for future clinical translation. We developed a novel, intuitive open-source framework to facilitate all data analysis steps of a radiomics workflow in an easy and reproducible manner and evaluated it by reproducing classification results in eight available open-source datasets from different clinical entities.
Methods
The framework performs image preprocessing, feature extraction, feature selection, modeling, and model evaluation, and can automatically choose the optimal parameters for a given task. All analysis steps can be reproduced with a web application, which offers an interactive user interface and does not require programming skills. We evaluated our method in seven different clinical applications using eight public datasets: six datasets from the recently published WORC database, and two prostate MRI datasets—Prostate MRI and Ultrasound With Pathology and Coordinates of Tracked Biopsy (Prostate-UCLA) and PROSTATEx.
Results
In the analyzed datasets, AutoRadiomics successfully created and optimized models using radiomics features. For WORC datasets, we achieved AUCs ranging from 0.56 for lung melanoma metastases detection to 0.93 for liposarcoma detection and thereby managed to replicate the previously reported results. No significant overfitting between training and test sets was observed. For the prostate cancer detection task, results were better in the PROSTATEx dataset (AUC = 0.73 for prostate and 0.72 for lesion mask) than in the Prostate-UCLA dataset (AUC 0.61 for prostate and 0.65 for lesion mask), with external validation results varying from AUC = 0.51 to AUC = 0.77.
Conclusion
AutoRadiomics is a robust tool for radiomic studies, which can be used as a comprehensive solution, one of the analysis steps, or an exploratory tool. Its wide applicability was confirmed by the results obtained in the diverse analyzed datasets. The framework, as well as code for this analysis, are publicly available under https://github.com/pwoznicki/AutoRadiomics.
Two sons of a consanguineous marriage developed biventricular cardiomyopathy. One boy died of severe heart failure at the age of 6 years, the other was transplanted because of severe heart failure at the age of 10 years. In addition, focal palmoplantar keratoderma and woolly hair were apparent in both boys. As similar phenotypes have been described in Naxos disease and Carvajal syndrome, respectively, the genes for plakoglobin (JUP) and desmoplakin (DSP) were screened for mutations using direct genomic sequencing. A novel homozygous 2 bp deletion was identified in an alternatively spliced region of DSP. The deletion 5208_5209delAG led to a frameshift downstream of amino acid 1,736 with a premature truncation of the predominant cardiac isoform DSP-1. This novel homozygous truncating mutation in the isoform-1 specific region of the DSP C-terminus caused Carvajal syndrome comprising severe early-onset heart failure with features of non-compaction cardiomyopathy, woolly hair and an acantholytic form of palmoplantar keratoderma in our patient. Congenital hair abnormality and manifestation of the cutaneous phenotype in toddler age can help to identify children at risk for cardiac death.
Background
The effect of smoking on coronary vasomotion has been investigated in the past with various imaging techniques in both short- and long-term smokers. Additionally, coronary vasomotion has been shown to be normalized in long-term smokers by L-Arginine acting as a substrate for NO synthase, revealing the coronary endothelium as the major site of abnormal vasomotor response. Aim of the prospective cohort study was to investigate coronary vasomotion of young healthy short-term smokers via magnetic resonance cold pressor test with and without the administration of L-Arginine and compare obtained results with the ones from nonsmokers.
Methods
Myocardial blood flow (MBF) was quantified with first-pass perfusion MRI on a 1.5 T scanner in healthy short-term smokers (N = 10, age: 25.0 ± 2.8 years, 5.0 ± 2.9 pack years) and nonsmokers (N = 10, age: 34.3 ± 13.6) both at rest and during cold pressor test (CPT). Smokers underwent an additional examination after administration of L-Arginine within a median of 7 days of the naïve examination.
Results
MBF at rest turned out to be 0.77 ± 0.30 (smokers with no L-Arginine; mean ± standard deviation), 0.66 ± 0.21 (smokers L-Arginine) and 0.84 ± 0.08 (nonsmokers). Values under CPT were 1.21 ± 0.42 (smokers no L-Arginine), 1.09 ± 0.35 (smokers L-Arginine) and 1.63 ± 0.33 (nonsmokers). In all groups, MBF was significantly increased under CPT compared to the corresponding rest examination (p < 0.05 in all cases). Additionally, MBF under CPT was significantly different between the smokers and the nonsmokers (p = 0.002). MBF at rest was significantly different between the smokers when L-Arginine was given and the nonsmokers (p = 0.035).
Conclusion
Short-term smokers showed a reduced response to cold both with and without the administration of L-Arginine. However, absolute MBF values under CPT were lower compared to nonsmokers independently of L-Arginine administration.
Background
Functional lung MRI techniques are usually associated with time-consuming post-processing, where manual lung segmentation represents the most cumbersome part. The aim of this study was to investigate whether deep learning-based segmentation of lung images which were scanned by a fast UTE sequence exploiting the stack-of-spirals trajectory can provide sufficiently good accuracy for the calculation of functional parameters.
Methods
In this study, lung images were acquired in 20 patients suffering from cystic fibrosis (CF) and 33 healthy volunteers, by a fast UTE sequence with a stack-of-spirals trajectory and a minimum echo-time of 0.05 ms. A convolutional neural network was then trained for semantic lung segmentation using 17,713 2D coronal slices, each paired with a label obtained from manual segmentation. Subsequently, the network was applied to 4920 independent 2D test images and results were compared to a manual segmentation using the Sørensen–Dice similarity coefficient (DSC) and the Hausdorff distance (HD). Obtained lung volumes and fractional ventilation values calculated from both segmentations were compared using Pearson’s correlation coefficient and Bland Altman analysis.
To investigate generalizability to patients outside the CF collective, in particular to those exhibiting larger consolidations inside the lung, the network was additionally applied to UTE images from four patients with pneumonia and one with lung cancer.
Results
The overall DSC for lung tissue was 0.967 ± 0.076 (mean ± standard deviation) and HD was 4.1 ± 4.4 mm. Lung volumes derived from manual and deep learning based segmentations as well as values for fractional ventilation exhibited a high overall correlation (Pearson’s correlation coefficent = 0.99 and 1.00). For the additional cohort with unseen pathologies / consolidations, mean DSC was 0.930 ± 0.083, HD = 12.9 ± 16.2 mm and the mean difference in lung volume was 0.032 ± 0.048 L.
Conclusions
Deep learning-based image segmentation in stack-of-spirals based lung MRI allows for accurate estimation of lung volumes and fractional ventilation values and promises to replace the time-consuming step of manual image segmentation in the future.
Background
To increase the image quality of end-expiratory and end-inspiratory phases of retrospective respiratory self-gated 4D MRI data sets using non-rigid image registration for improved target delineation of moving tumors.
Methods
End-expiratory and end-inspiratory phases of volunteer and patient 4D MRI data sets are used as targets for non-rigid image registration of all other phases using two different registration schemes: In the first, all phases are registered directly (dir-Reg) while next neighbors are successively registered until the target is reached in the second (nn-Reg). Resulting data sets are quantitatively compared using diaphragm and tumor sharpness and the coefficient of variation of regions of interest in the lung, liver, and heart. Qualitative assessment of the patient data regarding noise level, tumor delineation, and overall image quality was performed by blinded reading based on a 4 point Likert scale.
Results
The median coefficient of variation was lower for both registration schemes compared to the target. Median dir-Reg coefficient of variation of all ROIs was 5.6% lower for expiration and 7.0% lower for inspiration compared with nn-Reg. Statistical significant differences between the two schemes were found in all comparisons. Median sharpness in inspiration is lower compared to expiration sharpness in all cases. Registered data sets were rated better compared to the targets in all categories. Over all categories, mean expiration scores were 2.92 +/- 0.18 for the target, 3.19 +/- 0.22 for nn-Reg and 3.56 +/- 0.14 for dir-Reg and mean inspiration scores 2.25 +/- 0.12 for the target, 2.72 +/- 215 0.04 for nn-Reg and 3.78 +/- 0.04 for dir-Reg.
Conclusions
In this work, end-expiratory and inspiratory phases of a 4D MRI data sets are used as targets for non-rigid image registration of all other phases. It is qualitatively and quantitatively shown that image quality of the targets can be significantly enhanced leading to improved target delineation of moving tumors.
Purpose
Image acquisition and subsequent manual analysis of cardiac cine MRI is time-consuming. The purpose of this study was to train and evaluate a 3D artificial neural network for semantic segmentation of radially undersampled cardiac MRI to accelerate both scan time and postprocessing.
Methods
A database of Cartesian short-axis MR images of the heart (148,500 images, 484 examinations) was assembled from an openly accessible database and radial undersampling was simulated. A 3D U-Net architecture was pretrained for segmentation of undersampled spatiotemporal cine MRI. Transfer learning was then performed using samples from a second database, comprising 108 non-Cartesian radial cine series of the midventricular myocardium to optimize the performance for authentic data. The performance was evaluated for different levels of undersampling by the Dice similarity coefficient (DSC) with respect to reference labels, as well as by deriving ventricular volumes and myocardial masses.
Results
Without transfer learning, the pretrained model performed moderately on true radial data [maximum number of projections tested, P = 196; DSC = 0.87 (left ventricle), DSC = 0.76 (myocardium), and DSC =0.64 (right ventricle)]. After transfer learning with authentic data, the predictions achieved human level even for high undersampling rates (P = 33, DSC = 0.95, 0.87, and 0.93) without significant difference compared with segmentations derived from fully sampled data.
Conclusion
A 3D U-Net architecture can be used for semantic segmentation of radially undersampled cine acquisitions, achieving a performance comparable with human experts in fully sampled data. This approach can jointly accelerate time-consuming cine image acquisition and cumbersome manual image analysis.
The introduction of new therapeutic agents has revolutionized the treatment of metastatic melanoma. The approval of adjuvant anti‐programmed death‐1 monotherapy with nivolumab or pembrolizumab, and dabrafenib plus trametinib has recently set a new landmark in the treatment of stage III melanoma. Now, clinical trials have shown that immune checkpoint blockade can be performed in a neoadjuvant setting, an approach established as a standard therapeutic approach for other tumour entities such as breast cancer. Recent studies suggest that a pathological response achieved by neoadjuvant immunotherapy is associated with long‐term tumour control and that short neoadjuvant application of checkpoint inhibitors may be superior to adjuvant therapy. Most recently, neoadjuvant ipilimumab plus nivolumab in stage III melanoma was reported. With two courses of dose‐optimized ipilimumab (1 mg kg−1) combined with nivolumab (3 mg kg−1), pathological responses were observed in 77% of patients, while only 20% of patients experienced grade 3 or 4 adverse events. However, the neoadjuvant trials employing combined immune checkpoint blockade conducted so far have excluded patients with in transit metastases, a common finding in stage III melanoma. Here we report four patients with in transit metastases or an advanced primary tumour who have been treated with neoadjuvant ipilimumab plus nivolumab according to the OpACIN‐neo trial scheme (arm B). All patients achieved radiological disease control and a pathological response. None of the patients has relapsed so far.
Background
Hypophosphatasia (HPP) is a rare, inherited metabolic disorder caused by loss-of-function mutations in the ALPL gene that encodes the tissue-nonspecific alkaline phosphatase TNAP (ORPHA 436). Its clinical presentation is highly heterogeneous with a remarkably wide-ranging severity. HPP affects patients of all ages. In children HPP-related musculoskeletal symptoms may mimic rheumatologic conditions and diagnosis is often difficult and delayed. To improve the understanding of HPP in children and in order to shorten the diagnostic time span in the future we studied the natural history of the disease in our large cohort of pediatric patients. This single centre retrospective chart review included longitudinal data from 50 patients with HPP diagnosed and followed at the University Children's Hospital Wuerzburg, Germany over the last 25 years.
Results
The cohort comprises 4 (8%) perinatal, 17 (34%) infantile and 29 (58%) childhood onset HPP patients. Two patients were deceased at the time of data collection. Diagnosis was based on available characteristic clinical symptoms (in 88%), low alkaline phosphatase (AP) activity (in 96%), accumulating substrates of AP (in 58%) and X-ray findings (in 48%). Genetic analysis was performed in 48 patients (31 compound heterozygous, 15 heterozygous, 2 homozygous mutations per patient), allowing investigations on genotype-phenotype correlations. Based on anamnestic data, median age at first clinical symptoms was 3.5 months (min. 0, max. 107), while median time to diagnosis was 13 months (min. 0, max. 103). Common symptoms included: impairment of motor skills (78%), impairment of mineralization (72%), premature loss of teeth (64%), musculoskeletal pain and craniosynostosis (each 64%) and failure to thrive (62%). Up to now 20 patients started medical treatment with Asfotase alfa.
Conclusions
Reported findings support the clinical perception of HPP being a chronic multi-systemic disease with often delayed diagnosis. Our natural history information provides detailed insights into the prevalence of different symptoms, which can help to improve and shorten diagnostics and thereby lead to an optimised medical care, especially with promising therapeutic options such as enzyme-replacement-therapy with Asfotase alfa in mind.
Magnetic Particle Imaging (MPI) is a promising new tomographic modality for fast as well as three-dimensional visualization of magnetic material. For anatomical or structural information an additional imaging modality such as computed tomography (CT) is required. In this paper, the first hybrid MPI-CT scanner for multimodal imaging providing simultaneous data acquisition is presented.
Minimally invasive endovascular interventions have become an important tool for the treatment of cardiovascular diseases such as ischemic heart disease, peripheral artery disease, and stroke. X-ray fluoroscopy and digital subtraction angiography are used to precisely guide these procedures, but they are associated with radiation exposure for patients and clinical staff. Magnetic Particle Imaging (MPI) is an emerging imaging technology using time-varying magnetic fields combined with magnetic nanoparticle tracers for fast and highly sensitive imaging. In recent years, basic experiments have shown that MPI has great potential for cardiovascular applications. However, commercially available MPI scanners were too large and expensive and had a small field of view (FOV) designed for rodents, which limited further translational research. The first human-sized MPI scanner designed specifically for brain imaging showed promising results but had limitations in gradient strength, acquisition time and portability. Here, we present a portable interventional MPI (iMPI) system dedicated for real-time endovascular interventions free of ionizing radiation. It uses a novel field generator approach with a very large FOV and an application-oriented open design enabling hybrid approaches with conventional X-ray-based angiography. The feasibility of a real-time iMPI-guided percutaneous transluminal angioplasty (PTA) is shown in a realistic dynamic human-sized leg model.
Background:
Contrast-enhanced cardiovascular magnetic resonance angiography (CE-CMRA) is the established imaging modality for patients with Marfan syndrome requiring life-long annual aortic imaging before and after aortic root replacement. Contrast-free CMRA techniques avoiding side-effects of contrast media are highly desirable for serial imaging but have not been evaluated in the postoperative setup of Marfan patients. The purpose of this study was to assess the feasibility of non-contrast balanced steady-state free precession (bSSFP) magnetic resonance imaging for aortic monitoring of postoperative patients with Marfan syndrome.
Methods:
Sixty-four adult Marfan patients after aortic root replacement were prospectively included. Fourteen patients (22%) had a residual aortic dissection after surgical treatment of type A dissection. bSSFP imaging and CE-CMRA were performed at 1.5 Tesla. Two radiologists evaluated the images regarding image quality (1 = poor, 4 = excellent), artifacts (1 = severe, 4 = none) and aortic pathologies. Readers measured the aortic diameters at defined levels in both techniques. Statistics included observer agreement for image scoring and diameter measurements and ROC analyses for comparison of the diagnostic performance of bSSFP and CE-CMRA.
Results:
Both readers observed no significant differences in image quality between bSSFP and CE-CMRA and found a median image quality score of 4 for both techniques (all p > .05). No significant differences were found regarding the frequency of image artifacts in both sequences (all p > .05). Sensitivity and specificity for detection of aortic dissections was 100% for both readers and techniques. Compared to bSSFP imaging, CE-CMRA resulted in higher diameters (mean bias, 0.9 mm; p < .05). The inter-observer biases of diameter measurements were not significantly different (all p > .05), except for the distal graft anastomosis (p = .001). Using both techniques, the readers correctly identified a graft suture dehiscence with aneurysm formation requiring surgery.
Conclusion:
Unenhanced bSSFP CMR imaging allows for riskless aortic monitoring with high diagnostic accuracy in Marfan patients after aortic root surgery.
Acute ischemic cardiac injury predisposes one to cognitive impairment, dementia, and depression. Pathophysiologically, recent positron emission tomography data suggest astroglial activation after experimental myocardial infarction (MI). We analyzed peripheral surrogate markers of glial (and neuronal) damage serially within 12 months after the first ST-elevation MI (STEMI). Serum levels of glial fibrillary acidic protein (GFAP) and neurofilament light chain (NfL) were quantified using ultra-sensitive molecular immunoassays. Sufficient biomaterial was available from 45 STEMI patients (aged 28 to 78 years, median 56 years, 11% female). The median (quartiles) of GFAP was 63.8 (47.0, 89.9) pg/mL and of NfL 10.6 (7.2, 14.8) pg/mL at study entry 0–4 days after STEMI. GFAP after STEMI increased in the first 3 months, with a median change of +7.8 (0.4, 19.4) pg/mL (p = 0.007). It remained elevated without further relevant increases after 6 months (+11.7 (0.6, 23.5) pg/mL; p = 0.015), and 12 months (+10.3 (1.5, 22.7) pg/mL; p = 0.010) compared to the baseline. Larger relative infarction size was associated with a higher increase in GFAP (ρ = 0.41; p = 0.009). In contrast, NfL remained unaltered in the course of one year. Our findings support the idea of central nervous system involvement after MI, with GFAP as a potential peripheral biomarker of chronic glial damage as one pathophysiologic pathway.