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Purpose
The AMADEUS (Area Measurement And DEpth and Underlying Structures) scoring and grading system has been proposed for the MRI based evaluation of untreated focal chondral defects around the knee. The clinical practicability, its correlation with arthroscopically assessed grading systems (ICRS – International Cartilage Repair Society) and thereby its clinical value in terms of decision making and guiding prognosis was yet to determine.
Methods
From 2008 to 2019 a total of 89 individuals were indicated for high tibial valgus osteotomy (HTO) due to tibial varus deformity and concomitant chondral defects of the medial compartment of the knee. All patients received a preoperative MRI (1.5 Tesla or 3.0 Tesla) and pre-osteotomy diagnostic arthroscopy. Chondral defects of the medial compartment were scored and graded with the MRI based AMADEUS by three independent raters and compared to arthroscopic defect grading by the ICRS system. Interrater and intrarater reliability as well as correlation analysis with the ICRS classification system were assessed.
Results
Intraclass correlation coefficients for the various subscores of the AMADEUS showed an overall good to excellent interrater agreement (min: 0.26, max: 0.80). Intrarater agreement turned out to be substantially inferior (min: 0.08, max: 0.53). Spearman correlation revealed an overall moderate correlative association of the AMADEUS subscores with the ICRS classification system, apart from the defect area subscore. Sensitivity of the AMADEUS to accurately identify defect severity according to the ICRS was 0.7 (0.69 for 3.0 Tesla MRI, 0.67 for 1.5 Tesla MRI). The mean AMADEUS grade was 2.60 ± 0.81 and the mean ICRS score 2.90 ± 0.63.
Conclusions
Overall, the AMADEUS with all its subscores shows moderate correlation with the arthroscopic chondral grading system according to ICRS. This suggests that chondral defect grading by means of the MRI based AMADEUS is well capable of influencing and guiding treatment decisions. Interrater reliability shows overall good agreement.
Objective
Growing interest in measuring the cochlear duct length (CDL) has emerged, since it can influence the selection of cochlear implant electrodes. Currently the measurements are performed with ionized radiation imaging. Only a few studies have explored CDL measurements in magnetic resonance imaging (MRI). Therefore, the presented study aims to fill this gap by estimating CDL in MRI and comparing it with multislice computed tomography (CT).
Study Design
Retrospective data analyses of 42 cochleae.
Setting
Tertiary care medical center.
Methods
Diameter (A value) and width (B value) of the cochlea were measured in HOROS software. The CDL and the 2-turn length were determined by the elliptic circular approximation (ECA). In addition, the CDL, the 2-turn length, and the angular length were determined via HOROS software by the multiplanar reconstruction (MPR) method.
Results
CDL values were significantly shorter in MRI by MPR (d = 1.38 mm, P < .001) but not by ECA. Similar 2-turn length measurements were significantly lower in MRI by MPR (d = 1.67 mm) and ECA (d = 1.19 mm, both P < .001). In contrast, angular length was significantly higher in MRI (d = 26.79°, P < .001). When the values were set in relation to the frequencies of the cochlea, no clinically relevant differences were estimated (58 Hz at 28-mm CDL).
Conclusion
In the presented study, CDL was investigated in CT and MRI by using different approaches. Since no clinically relevant differences were found, diagnostics with radiation may be omitted prior to cochlear implantation; thus, a concept of radiation-free cochlear implantation could be established.
Background
The Goutallier Classification is a semi quantitative classification system to determine the amount of fatty degeneration in rotator cuff muscles. Although initially proposed for axial computer tomography scans it is currently applied to magnet-resonance-imaging-scans. The role for its clinical use is controversial, as the reliability of the classification has been shown to be inconsistent. The purpose of this study was to compare the semi quantitative MRI-based Goutallier Classification applied by 5 different raters to experimental MR spectroscopic quantitative fat measurement in order to determine the correlation between this classification system and the true extent of fatty degeneration shown by spectroscopy.
Methods
MRI-scans of 42 patients with rotator cuff tears were examined by 5 shoulder surgeons and were graduated according to the MRI-based Goutallier Classification proposed by Fuchs et al. Additionally the fat/water ratio was measured with MR spectroscopy using the experimental SPLASH technique. The semi quantitative grading according to the Goutallier Classification was statistically correlated with the quantitative measured fat/water ratio using Spearman’s rank correlation.
Results
Statistical analysis of the data revealed only fair correlation of the Goutallier Classification system and the quantitative fat/water ratio with R = 0.35 (p < 0.05). By dichotomizing the scale the correlation was 0.72. The interobserver and intraobserver reliabilities were substantial with R = 0.62 and R = 0.74 (p < 0.01).
Conclusion
The correlation between the semi quantitative MRI based Goutallier Classification system and MR spectroscopic fat measurement is weak. As an adequate estimation of fatty degeneration based on standard MRI may not be possible, quantitative methods need to be considered in order to increase diagnostic safety and thus provide patients with ideal care in regard to the amount of fatty degeneration. Spectroscopic MR measurement may increase the accuracy of the Goutallier classification and thus improve the prediction of clinical results after rotator cuff repair. However, these techniques are currently only available in an experimental setting.
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.
AimIn PET imaging, the different types of radiotracers and accumulations, as well as the diversity of disease patterns, make the analysis of molecular imaging data acquired in vivo challenging. Here, we evaluate and validate a semi-automated MRI template-based data analysis tool that allows preclinical PET images to be aligned to a self-created PET template. Based on the user-defined volume-of-interest (VOI), image data can then be evaluated using three different semi-quantitative parameters: normalized activity, standardized uptake value, and uptake ratio.
Materials and MethodsThe nuclear medicine Data Processing Analysis tool (NU_DPA) was implemented in Matlab. Testing and validation of the tool was performed using two types of radiotracers in different kinds of stroke-related brain diseases in rat models. The radiotracers used are 2-[\(^{18}\)F]fluoro-2-deoxyglucose ([\(^{18}\)F]FDG), a metabol\(^{68}\)Ga]Ga-Fucoidan, a target-selective radioligand specifically binding to p-selectin. After manual image import, the NU_DPA tool automatically creates an averaged PET template out of the acquired PET images, to which all PET images are then aligned onto. The added MRI template-based information, resized to the lower PET resolution, defines the VOI and also allows a precise subdivision of the VOI into individual sub-regions. The aligned PET images can then be evaluated semi-quantitatively for all regions defined in the MRI atlas. In addition, a statistical analysis and evaluation of the semi-quantitative parameters can then be performed in the NU_DPA tool.
ResultsUsing ischemic stroke data in Wistar rats as an example, the statistical analysis of the tool should be demonstrated. In this [\(^{18}\)F]FDG-PET experiment, three different experimental states were compared: healthy control state, ischemic stroke without electrical stimulation, ischemic stroke with electrical stimulation. Thereby, statistical data evaluation using the NU_DPA tool showed that the glucose metabolism in a photothrombotic lesion can be influenced by electrical stimulation.
ConclusionOur NU_DPA tool allows a very flexible data evaluation of small animal PET data in vivo including statistical data evaluation. Using the radiotracers [\(^{18}\)F]FDG and [\(^{68}\)Ga]Ga-Fucoidan, it was shown that the semi-automatic MRI-template based data analysis of the NU_DPA tool is potentially suitable for both metabolic radiotracers as well as target-selective radiotracers.
Direct cooling of the catheter tip increases safety for CMR-guided electrophysiological procedures
(2012)
Background: One of the safety concerns when performing electrophysiological (EP) procedures under magnetic resonance (MR) guidance is the risk of passive tissue heating due to the EP catheter being exposed to the radiofrequency (RF) field of the RF transmitting body coil. Ablation procedures that use catheters with irrigated tips are well established therapeutic options for the treatment of cardiac arrhythmias and when used in a modified mode might offer an additional system for suppressing passive catheter heating.
Methods: A two-step approach was chosen. Firstly, tests on passive catheter heating were performed in a 1.5 T Avanto system (Siemens Healthcare Sector, Erlangen, Germany) using a ASTM Phantom in order to determine a possible maximum temperature rise. Secondly, a phantom was designed for simulation of the interface between blood and the vascular wall. The MR-RF induced temperature rise was simulated by catheter tip heating via a standard ablation generator. Power levels from 1 to 6 W were selected. Ablation duration was 120 s with no tip irrigation during the first 60 s and irrigation at rates from 2 ml/min to 35 ml/min for the remaining 60 s (Biotronik Qiona Pump, Berlin, Germany). The temperature was measured with fluoroscopic sensors (Luxtron, Santa Barbara, CA, USA) at a distance of 0 mm, 2 mm, 4 mm, and 6 mm from the catheter tip. Results: A maximum temperature rise of 22.4 degrees C at the catheter tip was documented in the MR scanner. This temperature rise is equivalent to the heating effect of an ablator's power output of 6 W at a contact force of the weight of 90 g (0.883 N). The catheter tip irrigation was able to limit the temperature rise to less than 2 degrees C for the majority of examined power levels, and for all examined power levels the residual temperature rise was less than 8 degrees C.
Conclusion: Up to a maximum of 22.4 degrees C, the temperature rise at the tissue surface can be entirely suppressed by using the catheter's own irrigation system. The irrigated tip system can be used to increase MR safety of EP catheters by suppressing the effects of unwanted passive catheter heating due to RF exposure from the MR scanner.
Background
Human cerebral small vessel disease (CSVD) has distinct histopathologic and imaging findings in its advanced stages. In spontaneously hypertensive stroke-prone rats (SHRSP), a well-established animal model of CSVD, we recently demonstrated that cerebral microangiopathy is initiated by early microvascular dysfunction leading to the breakdown of the blood–brain barrier and an activated coagulatory state resulting in capillary and arteriolar erythrocyte accumulations (stases). In the present study, we investigated whether initial microvascular dysfunction and other stages of the pathologic CSVD cascade can be detected by serial magnetic resonance imaging (MRI).
Findings
Fourteen SHRSP and three control (Wistar) rats (aged 26–44 weeks) were investigated biweekly by 3.0 Tesla (3 T) MRI. After perfusion, brains were stained with hematoxylin–eosin and histology was correlated with MRI data. Three SHRSP developed terminal CSVD stages including cortical, hippocampal, and striatal infarcts and macrohemorrhages, which could be detected consistently by MRI. Corresponding histology showed small vessel thromboses and increased numbers of small perivascular bleeds in the infarcted areas. However, 3 T MRI failed to visualize intravascular erythrocyte accumulations, even in those brain regions with the highest densities of affected vessels and the largest vessels affected by stases, as well as failing to detect small perivascular bleeds.
Conclusion
Serial MRI at a field strength of 3 T failed to detect the initial microvascular dysfunction and subsequent small perivascular bleeds in SHRSP; only terminal stages of cerebral microangiopathy were reliably detected. Further investigations at higher magnetic field strengths (7 T) using blood- and flow-sensitive sequences are currently underway.
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.
Even as medical data sets become more publicly accessible, most are restricted to specific medical conditions. Thus, data collection for machine learning approaches remains challenging, and synthetic data augmentation, such as generative adversarial networks (GAN), may overcome this hurdle. In the present quality control study, deep convolutional GAN (DCGAN)-based human brain magnetic resonance (MR) images were validated by blinded radiologists. In total, 96 T1-weighted brain images from 30 healthy individuals and 33 patients with cerebrovascular accident were included. A training data set was generated from the T1-weighted images and DCGAN was applied to generate additional artificial brain images. The likelihood that images were DCGAN-created versus acquired was evaluated by 5 radiologists (2 neuroradiologists [NRs], vs 3 non-neuroradiologists [NNRs]) in a binary fashion to identify real vs created images. Images were selected randomly from the data set (variation of created images, 40%-60%). None of the investigated images was rated as unknown. Of the created images, the NRs rated 45% and 71% as real magnetic resonance imaging images (NNRs, 24%, 40%, and 44%). In contradistinction, 44% and 70% of the real images were rated as generated images by NRs (NNRs, 10%, 17%, and 27%). The accuracy for the NRs was 0.55 and 0.30 (NNRs, 0.83, 0.72, and 0.64). DCGAN-created brain MR images are similar enough to acquired MR images so as to be indistinguishable in some cases. Such an artificial intelligence algorithm may contribute to synthetic data augmentation for "data-hungry" technologies, such as supervised machine learning approaches, in various clinical applications.
Background:
The amount of fatty degeneration (FD) has major impact on the clinical result and cuff integrity after rotator cuff repair. A quantitative analysis with magnet resonance imaging (MRI) spectroscopy was employed to analyze possible correlation of FD with tendon retraction, tendon thickness and patients’ characteristics in full thickness supraspinatus tears.
Methods:
Forty-two patients with full-thickness supraspinatus tears underwent shoulder MRI including an experimental spectroscopic sequence allowing quantification of the fat fraction in the supraspinatus muscle belly. The amount of fatty degeneration was correlated with tendon retraction, tendon thickness, patients’ age, gender, smoker status, symptom duration and body mass index (BMI). Patients were divided in to three groups of retraction (A) 0-10 mm (n=), (B) 11-20 mm (n=) and (C) < 21 mm (n=) and the means of FD for each group were calculated.
Results:
Tendon retraction (R = 0.6) and symptom duration (R = 0.6) correlated positively, whereas tendon thickness correlated negatively (R = − 0.6) with the amount of FD. The fat fraction increased significantly with tendon retraction: Group (A) showed a mean fat mount of 3.7% (±4%), group (B) of 16.7% (±8.2%) and group (C) of 37.5% (±19%). BMI, age and smoker-status only showed weak to moderate correlation with the amount of FD in this cohort.
Conclusion:
MRI spectroscopy revealed significantly higher amount of fat with increasing grade of retraction, symptom duration and decreased tendon thickness. Thus, these parameters may indirectly be associated with the severity of tendon disease.