Computed tomography (CT) and magnetic resonance imaging (MRI) can quantify muscle mass and quality. However, it is still unclear if CT and MRI derived measurements can be used interchangeable. In ...this prospective study, fifty consecutive participants of a cancer screening program underwent same day low-dose chest CT and MRI. Cross-sectional areas (CSA) of the paraspinal skeletal muscles were obtained. CT and MRI muscle fat infiltration (MFI) were assessed by mean radiodensity in Hounsfield units (HU) and proton density fat fraction (MRI
), respectively. CSA and MFI were highly correlated between CT and MRI (CSA: r = 0.93, P < 0.001; MFI: r = - 0.90, P < 0.001). Mean CSA was higher in CT compared to MRI (46.6cm
versus 43.0cm
; P = 0.05) without significance. Based on MRI
, a linear regression model was established to directly estimate skeletal muscle fat content from CT. Bland-Altman plots showed a difference between measurements of - 0.5 cm
to 7.6 cm
and - 4.2% to 2.4% regarding measurements of CSA and MFI, respectively. In conclusion, the provided results indicate interchangeability of CT and MRI derived imaging biomarkers of skeletal muscle quantity and quality. Comparable to MRI
, skeletal muscle fat content can be quantified from CT, which might have an impact of analyses in larger cohort studies, particularly in sarcopenia patients.
Objectives
To compare systematically quantitative MRI, MR spectroscopy (MRS), and different histological methods for liver fat quantification in order to identify possible incongruities.
Methods
...Fifty-nine consecutive patients with liver disorders were examined on a 3 T MRI system. Quantitative MRI was performed using a dual- and a six-echo variant of the modified Dixon (mDixon) sequence, calculating proton density fat fraction (PDFF) maps, in addition to single-voxel MRS. Histological fat quantification included estimation of the percentage of hepatocytes containing fat vesicles as well as semi-automatic quantification (qHisto) using tissue quantification software.
Results
In 33 of 59 patients, the hepatic fat fraction was >5 % as determined by MRS (maximum 45 %, mean 17 %). Dual-echo mDixon yielded systematically lower PDFF values than six-echo mDixon (mean difference 1.0 %;
P
< 0.001). Six-echo mDixon correlated excellently with MRS, qHisto, and the estimated percentage of hepatocytes containing fat vesicles (R = 0.984, 0.967, 0.941, respectively, all
P
< 0.001). Mean values obtained by the estimated percentage of hepatocytes containing fat were higher by a factor of 2.5 in comparison to qHisto. Six-echo mDixon and MRS showed the best agreement with values obtained by qHisto.
Conclusions
Six-echo mDixon, MRS, and qHisto provide the most robust and congruent results and are therefore most appropriate for reliable quantification of liver fat.
Key Points
•
Six-echo mDixon correlates excellently with MRS, qHisto, and the estimated percentage of fat-containing hepatocytes
.
•
Six-echo mDixon, MRS, and qHisto provide the most robust and congruent results
.
•
Dual-echo mDixon yields systematically lower PDFF values than six-echo mDixon
.
•
The percentage of fat-containing hepatocytes is 2.5-fold higher than fat fraction determined by qHisto
.
• Performance characteristics and systematic differences of the various methods should be considered
.
Although CT and MRI are standard procedures in cirrhosis diagnosis, differentiation of etiology based on imaging is not established. This proof-of-concept study explores the potential of deep ...learning (DL) to support imaging-based differentiation of the etiology of liver cirrhosis. This retrospective, monocentric study included 465 patients with confirmed diagnosis of (a) alcoholic (n = 221) and (b) other-than-alcoholic (n = 244) cirrhosis. Standard T2-weighted single-slice images at the caudate lobe level were randomly split for training with fivefold cross-validation (85%) and testing (15%), balanced for (a) and (b). After automated upstream liver segmentation, two different ImageNet pre-trained convolutional neural network (CNN) architectures (ResNet50, DenseNet121) were evaluated for classification of alcohol-related versus non-alcohol-related cirrhosis. The highest classification performance on test data was observed for ResNet50 with unfrozen pre-trained parameters, yielding an area under the receiver operating characteristic curve of 0.82 (95% confidence interval (CI) 0.71-0.91) and an accuracy of 0.75 (95% CI 0.64-0.85). An ensemble of both models did not lead to significant improvement in classification performance. This proof-of-principle study shows that deep-learning classifiers have the potential to aid in discriminating liver cirrhosis etiology based on standard MRI.
Abstract The amino-acid N-acetyl-aspartate (NAA) is located in neurons and the concentration of NAA correlates with neuronal mitochondrial function. The signal of NAA, as measured with proton ...magnetic resonance spectroscopy (1H-MRS), is considered to reflect both, neuronal density and integrity of neuronal mitochondria. A reduction of the NAA concentrations has been found in several psychiatric disorders. Newer studies report reversal of decreased NAA concentration with treatment. The objective of this review is to summarize the literature on NAA changes in association with psychopharmacological treatment in psychiatric disorders (affective disorders, obsessive-compulsive disorder, schizophrenia and dementia). The majority of studies identified increased NAA concentrations in response to treatment, while a smaller number of studies did not find this effect. The NAA increase seems to be neither specific for a certain disorder nor for a specific intervention. This suggests that the reduction of NAA may represent an altered functional (metabolic) state of neurons common to different psychiatric disorders and the increase after treatment to indicate functional restoration as one general effect of interventions.
Quantitative Cardiovascular Magnetic Resonance (CMR) techniques have gained high interest in CMR research. Myocardial T2 mapping is thought to be helpful in diagnosis of acute myocardial conditions ...associated with myocardial edema. In this study we aimed to establish a technique for myocardial T2 mapping based on gradient-spin-echo (GraSE) imaging.
The local ethics committee approved this prospective study. Written informed consent was obtained from all subjects prior to CMR. A modified GraSE sequence allowing for myocardial T2 mapping in a single breath-hold per slice using ECG-triggered acquisition of a black blood multi-echo series was developed at 1.5 Tesla. Myocardial T2 relaxation time (T2-RT) was determined by maximum likelihood estimation from magnitude phased-array multi-echo data. Four GraSE sequence variants with varying number of acquired echoes and resolution were evaluated in-vitro and in 20 healthy volunteers. Inter-study reproducibility was assessed in a subset of five volunteers. The sequence with the best overall performance was further evaluated by assessment of intra- and inter-observer agreement in all volunteers, and then implemented into the clinical CMR protocol of five patients with acute myocardial injury (myocarditis, takotsubo cardiomyopathy and myocardial infarction).
In-vitro studies revealed the need for well defined sequence settings to obtain accurate T2-RT measurements with GraSE. An optimized 6-echo GraSE sequence yielded an excellent agreement with the gold standard Carr-Purcell-Meiboom-Gill sequence. Global myocardial T2 relaxation times in healthy volunteers was 52.2 ± 2.0 ms (mean ± standard deviation). Mean difference between repeated examinations (n = 5) was -0.02 ms with 95% limits of agreement (LoA) of -4.7; 4.7 ms. Intra-reader and inter-reader agreement was excellent with mean differences of -0.1 ms, 95% LoA = -1.3; 1.2 ms and 0.1 ms, 95% LoA = -1.5; 1.6 ms, respectively (n = 20). In patients with acute myocardial injury global myocardial T2-RTs were prolonged (mean: 61.3 ± 6.7 ms).
Using an optimized GraSE sequence CMR allows for robust, reliable, fast myocardial T2 mapping and quantitative tissue characterization. Clinically, the GraSE-based T2-mapping has the potential to complement qualitative CMR in patients with acute myocardial injuries.
To explore the feasibility of CT-derived myocardial strain measurement in patients with advanced cardiac valve disease and to compare it to strain measurements derived from transthoracic ...echocardiography (TTE). 43 consecutive patients with advanced cardiac valve disease and clinically indicated retrospectively gated cardiac CTs were retrospectively analyzed. The longitudinal, circumferential as well as radial systolic strain were determined in all patients utilizing a commercially available CT strain software. In 36/43 (84%) patients, CT-derived longitudinal strain was compared to speckle-tracking TTE. Pearson's correlation coefficients as well as Bland-Altman analysis were used to compare the CT-derived strain measurements to TTE. The intra- and inter-reader-reliability of the CT-derived strain measurements were assessed by intra-class correlation coefficients (ICCs). Strain measurements were feasible in all patients. CT-derived global longitudinal strain (GLS) correlated moderately with TTE-derived GLS (r = 0.6, p < 0.001). A moderate correlation between CT-derived GLS and CT-derived left ventricular ejection fraction was found (LVEF, r = - 0.66, p = 0.036). Bland-Altman analysis showed a systematic underestimation of myocardial strain by cardiac CT compared to TTE (mean difference: - 5.8%, 95% limit of agreement between - 13.3 and 1.8%). Strain measurements showed an excellent intra- and inter-reader-reliability with an intra-reader ICC of 1.0 and an inter-reader ICC of 0.99 for GLS measurements. CT-derived myocardial strain measurements are feasible in patients with advanced cardiac valve disease. They are highly reproducible and correlate with established parameters of strain measurements. Our results encourage the implementation of CT-derived strain measurement into clinical routine.
Parkinson's disease (PD) affects more than six million people, but reliable MRI biomarkers with which to diagnose patients have not been established. Magnetic resonance fingerprinting (MRF) is a ...recent quantitative technique that can provide relaxometric maps from a single sequence. The purpose of this study is to assess the potential of MRF to identify PD in patients and their disease severity, as well as to evaluate comfort during MRF. Twenty‐five PD patients and 25 matching controls underwent 3 T MRI, including an axial 2D spoiled gradient echo MRF sequence. T1 and T2 maps were generated by voxel‐wise matching the measured MRF signal to a precomputed dictionary. All participants also received standard inversion recovery T1 and multi‐echo T2 mapping. An ROI‐based analysis of relaxation times was performed. Differences between patients and controls as well as techniques were determined by logistic regression, Spearman correlation and t‐test. Patients were asked to estimate the subjective comfort of the MRF sequence. Both MRF‐based T1 and T2 mapping discriminated patients from controls: T1 relaxation times differed most in cortical grey matter (PD 1337 ± 38 vs. control 1386 ± 37 ms; mean ± SD; P = .0001) and, in combination with normal‐appearing white matter, enabled correct discrimination in 85.7% of cases (sensitivity 83.3%; specificity 88.0%; receiver‐operating characteristic ROC) area under the curve AUC 0.87), while for T2 mapping the left putamen was the strongest classifier (40.54 ± 6.28 vs. 34.17 ± 4.96 ms; P = .0001), enabling differentiation of groups in 84.0% of all cases (sensitivity 80.0%; specificity 88.0%; ROC AUC 0.87). Relaxation time differences were not associated with disease severity. Standard mapping techniques generated significantly different relaxation time values and identified other structures as different between groups other than MRF. Twenty‐three out of 25 PD patients preferred the MRF examination instead of a standard MRI. MRF‐based mapping can identify PD patients with good comfort but needs further assessment regarding disease severity identification and its potential for comparability with standard mapping technique results.
Magnetic resonance fingerprinting (MRF)‐based T1 and T2 mapping can help identify Parkinson's disease patients based on regional relaxation time, but differs from standard mapping results. Disease severity could not be associated with relaxation times. T1 relaxation times differed most in cortical grey matter rather than in the basal ganglia.
This study investigated the impact of different ROI placement and analysis methods on the diagnostic performance of simplified IVIM-DWI for differentiating liver lesions. 1.5/3.0-T DWI data from a ...respiratory-gated MRI sequence (b = 0, 50, 250, 800 s/mm
) were analyzed in patients with malignant (n = 74/54) and benign (n = 35/19) lesions. Apparent diffusion coefficient ADC = ADC(0,800) and IVIM parameters D
' = ADC(50,800), D
' = ADC(250,800), f
' = f(0,50,800), f
' = f(0,250,800), and D*' = D*(0,50,250,800) were calculated voxel-wise. For each lesion, a representative 2D-ROI, a 3D-ROI whole lesion, and a 3D-ROI from "good" slices were placed, including and excluding centrally deviating areas (CDA) if present, and analyzed with various histogram metrics. The diagnostic performance of 2D- and 3D-ROIs was not significantly different; e.g. AUC (ADC/D
'/f
') were 0.958/0.902/0.622 for 2D- and 0.942/0.892/0.712 for whole lesion 3D-ROIs excluding CDA at 1.5 T (p > 0.05). For 2D- and 3D-ROIs, AUC (ADC/D
'/D
') were significantly higher, when CDA were excluded. With CDA included, AUC (ADC/D
'/D
'/f
'/D*') improved when low percentiles were used instead of averages, and was then comparable to the results of average ROI analysis excluding CDA. For lesion differentiation the use of a representative 2D-ROI is sufficient. CDA should be excluded from ROIs by hand or automatically using low percentiles of diffusion coefficients.
To determine value of transarterial radioembolization (TARE) for palliative treatment of unresectable liver-dominant breast metastases (LdBM) and to determine prognostic parameters.
Records of ...patients undergoing TARE for progressing LdBM between June 2006 and March 2015 were retrospectively reviewed; 44 female patients (mean age 56.1 y; range, 34.9-85.3 y) underwent 69 TAREs (56 resin-based, 13 glass-based). Of 44 patients, 42 had bilobar disease. Mean administered activity was 1.35 GBq ± 0.71. Median clinical and imaging follow-up times were 121 days (range, 26-870 d; n = 42 patients) and 93 days (range, 26-2,037 d; n = 38 patients). Clinical and biochemical toxicities, imaging response (according to Response Evaluation Criteria In Solid Tumors), time to progression, and overall survival (OS) were evaluated. Data were analyzed with stratification according to clinical and procedural parameters.
Toxicities included 1 cholecystitis (grade 2) and 1 duodenal ulceration (grade 3); no grade ≥ 4 clinical toxicities were noted. Objective response rate (complete + partial response) was 28.9% (11/38); disease control rate (response + stable disease) was 71.1% (27/38). Median time to progression of treated liver lobe was 101 days (range, 30-2,037 d). During follow-up, 34/42 patients died (median OS after first TARE: 184 d range 29-2,331 d). On multivariate analysis, baseline Eastern Cooperative Oncology Group (ECOG) status of 0 (P < .0001, hazard ratio HR = 0.146) and low baseline γ-glutamyltransferase (GGT) levels (P = .0146, HR = 0.999) were predictors of longer OS.
TARE can successfully delay progression of therapy-refractory LdBM with low complication rate. Nonelevated baseline ECOG status and low GGT levels were identified as prognostic factors.
Background
High-intensity focused ultrasound (HIFU) is used for the treatment of symptomatic leiomyomas. We aim to automate uterine volumetry for tracking changes after therapy with a 3D deep ...learning approach.
Methods
A 3D nnU-Net model in the default setting and in a modified version including convolutional block attention modules (CBAMs) was developed on 3D T2-weighted MRI scans. Uterine segmentation was performed in 44 patients with routine pelvic MRI (standard group) and 56 patients with uterine fibroids undergoing ultrasound-guided HIFU therapy (HIFU group). Here, preHIFU scans (
n
= 56), postHIFU imaging maximum one day after HIFU (
n
= 54), and the last available follow-up examination (
n
= 53, days after HIFU: 420 ± 377) were included. The training was performed on 80% of the data with fivefold cross-validation. The remaining data were used as a hold-out test set. Ground truth was generated by a board-certified radiologist and a radiology resident. For the assessment of inter-reader agreement, all preHIFU examinations were segmented independently by both.
Results
High segmentation performance was already observed for the default 3D nnU-Net (mean Dice score = 0.95 ± 0.05) on the validation sets. Since the CBAM nnU-Net showed no significant benefit, the less complex default model was applied to the hold-out test set, which resulted in accurate uterus segmentation (Dice scores: standard group 0.92 ± 0.07; HIFU group 0.96 ± 0.02), which was comparable to the agreement between the two readers.
Conclusions
This study presents a method for automatic uterus segmentation which allows a fast and consistent assessment of uterine volume. Therefore, this method could be used in the clinical setting for objective assessment of therapeutic response to HIFU therapy.
Key points
Deep learning methods enable accurate segmentation of the uterus in T2-weighted MRI.
Automatic uterine volumetry is possible in patients with and without leiomyomas.
Automated volumetry enables an objective assessment of response to high-intensity focused ultrasound therapy.
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