Evaluation of response in patients with hepatocellular carcinoma treated with intratumoral dendritic cell vaccination using intravoxel incoherent motion (IVIM) MRI and histogram analysis.

BACKGROUND: Immunotherapy of hepatocellular carcinoma (HCC) is an emerging method with promising results. Immunotherapy can have an antitumor effect without affecting tumor size, calling for functional imaging methods for response evaluation. PURPOSE: To evaluate the response to intratumoral injections with the immune primer ilixadencel in HCCs with diffusion-weighted magnetic resonance imaging (DW-MRI) using intravoxel incoherent motion (IVIM) and histogram analysis. MATERIAL AND METHODS: A total of 17 patients with advanced HCC were treated with intratumoral injections with ilixadencel on three occasions 2-5 weeks apart. The patients were examined with IVIM before each injection as well as approximately three months after the first injection. RESULTS: The 10th percentile of perfusion-related parameter D* decreased significantly after the first and second intratumoral injections of ilixadencel compared to baseline (P < 0.05). There was a non-significant trend of lower median region of interest f (perfusion fraction) before injection 2 compared to baseline (P = 0.07). There were significant correlations between the 10th percentile and median of D at baseline and change in tumor size after three months (r = 0.79, P < 0.01 and r = 0.72, P < 0.05, respectively). CONCLUSION: DW-MRI with IVIM and histogram analysis revealed significant reductions of D* early after treatment as well as an association between D at baseline and smaller tumor growth at three months. The lower percentiles (10th and 50th) were found more important. Further research is needed to confirm our preliminary findings of reduced perfusion after ilixadencel vaccinations, suggesting a treatment effect on HCC.

Head and neck cancer patient positioning using synthetic CT data in MRI-only radiation therapy.

PURPOSE: The accuracy and precision of patient positioning is crucial in radiotherapy; however, there are no publications available using synthetic computed tomography (sCT) that evaluate rotations in head and neck (H&N) patients positioning or the effect of translation and rotation combined. The aim of this work was to evaluate the differences between using sCT with the CT for 2D- and 3D-patient positioning in a magnetic resonance imaging (MRI)-only workflow. METHODS: This study included 14 H&N cancer patients, with generated sCT data (MRI Planner v2.2) and the CT deformably registered to the MRI. Patient positioning was evaluated by comparing sCT against CT data: 3D cone beam CT (CBCT) was registered to the deformed CT (dCT) and sCT in six degrees of freedom (DoF) with a rigid auto-registration algorithm and bone threshold, and 2D deformed digital reconstructed radiographs (dDRR) and synthetic DRRs (sDRR) were manually registered to orthogonal projections in five DoF by six blinded observers. The difference in displacement in all DoF were calculated for dCT and sCT, as well as for dDRR and sDRR. The interobserver variation was evaluated by separate application of the paired dDRR and sDRR registration matrices to the original coordinates of the planning target volume (PTV) structures and calculation of the Euclidean distance between the corresponding points. The Dice similarity coefficient (DSC) was calculated between dDRR/sDRR-registered PTVs. RESULTS: The mean difference in patient positioning using CBCT was <0.7 mm and <0.3° and using orthogonal projections <0.4 mm and <0.2° in all directions. The maximum Euclidean distance was 5.1 mm, the corresponding mean (1SD) Euclidean distance and mean DSC were 3.5 ± 0.7 mm and 0.93, respectively. CONCLUSIONS: This study shows that the sCT-based patient positioning gives a comparable result with that based on CT images, allowing sCT to replace CT as reference for patient treatment positioning.

VERDICT MRI for radiation treatment response assessment in neuroendocrine tumors.

Noninvasive methods to study changes in tumor microstructure enable early assessment of treatment response and thus facilitate personalized treatment. The aim of this study was to evaluate the diffusion MRI model, Vascular, Extracellular and Restricted Diffusion for Cytometry in Tumors (VERDICT), for early response assessment to external radiation treatment and to compare the results with those of more studied sets of parameters derived from diffusion-weighted MRI data. Mice xenografted with human small intestine tumors were treated with external radiation treatment, and diffusion MRI experiments were performed on the day before and up to 2 weeks after treatment. The diffusion models VERDICT, ADC, IVIM, and DKI were fitted to MRI data, and the treatment response of each tumor was calculated based on pretreatment tumor growth and post-treatment tumor volume regression. Linear regression and correlation analysis were used to evaluate each model and their respective parameters for explaining the treatment response. VERDICT analysis showed significant changes from day -1 to day 3 for the intracellular and extracellular volume fraction, as well as the cell radius index (p < 0.05; Wilcoxon signed-rank test). The strongest correlation between the diffusion model parameters and the tumor treatment response was seen for the ADC, kurtosis-corrected diffusion coefficient, and intracellular volume fraction on day 3 (τ = 0.47, 0.52, and -0.49, respectively, p < 0.05; Kendall rank correlation coefficient). Of all the tested models, VERDICT held the strongest explanatory value for the tumor treatment response on day 3 (R2  = 0.75, p < 0.01; linear regression). In conclusion, VERDICT has potential for early assessment of external radiation treatment and may provide further insights into the underlying biological effects of radiation on tumor tissue. In addition, the results suggest that the time window for assessment of treatment response using dMRI may be narrow.

Altered Structural Covariance of Insula, Cerebellum and Prefrontal Cortex Is Associated with Somatic Symptom Levels in Irritable Bowel Syndrome (IBS).

Somatization, defined as the presence of multiple somatic symptoms, frequently occurs in irritable bowel syndrome (IBS) and may constitute the clinical manifestation of a neurobiological sensitization process. Brain imaging data was acquired with T1 weighted 3 tesla MRI, and gray matter morphometry were analyzed using FreeSurfer. We investigated differences in networks of structural covariance, based on graph analysis, between regional gray matter volumes in IBS-related brain regions between IBS patients with high and low somatization levels, and compared them to healthy controls (HCs). When comparing IBS low somatization (N = 31), IBS high somatization (N = 35), and HCs (N = 31), we found: (1) higher centrality and neighbourhood connectivity of prefrontal cortex subregions in IBS high somatization compared to healthy controls; (2) higher centrality of left cerebellum in IBS low somatization compared to both IBS high somatization and healthy controls; (3) higher centrality of the anterior insula in healthy controls compared to both IBS groups, and in IBS low compared to IBS high somatization. The altered structural covariance of prefrontal cortex and anterior insula in IBS high somatization implicates that prefrontal processes may be more important than insular in the neurobiological sensitization process associated with IBS high somatization.

Neurochemical properties measured by 1H magnetic resonance spectroscopy may predict cognitive behaviour therapy outcome in paediatric OCD: a pilot study.

To identify neurochemical factors measured pre-treatment that may predict cognitive behavioural treatment (CBT) outcome, aiming at understanding possible causes of poor CBT response. 1H magnetic resonance spectroscopy was used before treatment with CBT in treatment naïve 11-18 year-old patients with moderate-severe OCD. Diagnoses and assessment of OCD severity were based on semi-structured interviews. Linear mixed effects models were used to analyse the association between metabolite level and treatment outcome. Worse CBT outcome was associated with higher concentration of glutamine and glutamate combined (Glx) in middle cingulate cortex (MCC) (F = + 3.35, p = 0.004) and of N-acetylaspartate and N-acetylaspartylglutamate combined (tNAA) (F = + 2.59, p = 0.019). Also, we noted a tendency towards higher thalamic Glx concentration (F = + 1.91, p = 0.077) to be associated with worse CBT outcome. In general, the findings of the current pilot study are compatible with the hypothesis of an overweight of excitatory to inhibitory factors in brain circuits driving goal-directed behaviours (GDB). Higher MCC Glx and tNAA may be involved in the selection of GDB. A more detailed understanding of how these brain areas function in health and illness is needed.

Synthetic computed tomography data allows for accurate absorbed dose calculations in a magnetic resonance imaging only workflow for head and neck radiotherapy.

BACKGROUND AND PURPOSE: Few studies on magnetic resonance imaging (MRI) only head and neck radiation treatment planning exist, and none using a generally available software. The aim of this study was to evaluate the accuracy of absorbed dose for head and neck synthetic computed tomography data (sCT) generated by a commercial convolutional neural network-based algorithm. MATERIALS AND METHODS: For 44 head and neck cancer patients, sCT were generated and the geometry was validated against computed tomography data (CT). The clinical CT based treatment plan was transferred to the sCT and recalculated without re-optimization, and differences in relative absorbed dose were determined for dose-volume-histogram (DVH) parameters and the 3D volume. RESULTS: For overall body, the results of the geometric validation were (Mean ± 1sd): Mean error -5 ± 10 HU, mean absolute error 67 ± 14 HU, Dice similarity coefficient 0.98 ± 0.05, and Hausdorff distance difference 4.2 ± 1.7 mm. Water equivalent depth difference for region Th1-C7, mid mandible and mid nose were -0.3 ± 3.4, 1.1 ± 2.0 and 0.7 ± 3.8 mm respectively. The maximum mean deviation in absorbed dose for all DVH parameters was 0.30% (0.12 Gy). The absorbed doses were considered equivalent (p-value < 0.001) and the mean 3D gamma passing rate was 99.4 (range: 95.7-99.9%). CONCLUSIONS: The convolutional neural network-based algorithm generates sCT which allows for accurate absorbed dose calculations for MRI-only head and neck radiation treatment planning. The sCT allows for statistically equivalent absorbed dose calculations compared to CT based radiotherapy.

Simulated basis sets for semi-LASER: the impact of including shaped RF pulses and magnetic field gradients.

OBJECTIVE: To study the need for inclusion of shaped RF pulses and magnetic field gradients in simulations of basis sets for the analysis of proton MR spectra of single voxels of the brain acquired with a semi-LASER pulse sequence. MATERIALS AND METHODS: MRS basis sets where simulated at different echo times with hard RF pulses as well as with shaped RF pulses without or with magnetic field gradients included. The influence on metabolite concentration quantification was assessed using both phantom and in vivo measurements. For comparison, simulations and measurements were performed with the PRESS pulse sequence. RESULTS: The effect of including gradients in the simulations was smaller for semi-LASER than for PRESS, however, still noticeable. The difference was larger for strongly coupled metabolites and at longer echo times. Metabolite quantification using semi-LASER was thereby less dependent on the inclusion of gradients than PRESS, which was seen in both phantom and in vivo measurements. DISCUSSION: The inclusion of the shaped RF pulses and magnetic field gradients in the simulation of basis sets for semi-LASER is only important for strongly coupled metabolites. If computational time is a limiting factor, simple simulations with hard RF pulses can provide almost as accurate metabolite quantification as those that include the chemical-shift related displacement.

Association between pain sensitivity and gray matter properties in the sensorimotor network in women with irritable bowel syndrome.

BACKGROUND: Enhanced perception of visceral stimuli is an important feature of Irritable Bowel Syndrome (IBS), but it is not known whether visceral sensitivity is associated with regional structural brain properties in IBS. METHODS: Structural brain magnetic resonance imaging data from 216 women with IBS and 138 healthy women were parcellated with FreeSurfer to define regional gray matter morphometry (volume, cortical thickness, surface area and mean curvature) in the sensorimotor network. General linear models were used to detect group differences between IBS and health. In a second set of 48 female IBS patients, pain threshold, pain intensity ratings during rectal balloon distension, and reported levels of abdominal pain and bloating were correlated with brain regions that showed differences between IBS and health in the first data set. KEY RESULTS: Several statistically significant differences between IBS patients and healthy controls were found, mainly higher gray matter volume and cortical thickness in primary somatosensory cortex, secondary somatosensory cortex, and subcortical regions, and lesser gray matter volume, surface area and cortical thickness in posterior insula and superior frontal gyrus. Pain intensity ratings during rectal distension were associated with left primary somatosensory cortical thickness, and pain threshold was associated with right nucleus accumbens volume. CONCLUSIONS AND INFERENCES: Regional gray matter differences in sensorimotor network are associated with visceral sensitivity and may represent neuroplastic changes in female IBS patients.

Resting state functional connectivity of the pain matrix and default mode network in irritable bowel syndrome: a graph theoretical analysis.

Irritable bowel syndrome (IBS) is a functional disorder of brain-gut interactions. Differential brain responses to rectal distention between IBS and healthy controls (HCs) have been demonstrated, particularly in the pain matrix and the default mode network. This study aims to compare resting-state functional properties of these networks between IBS patients and HCs using graph analysis in two independent cohorts. We used a weighted graph analysis of the adjacency matrix based on partial correlations between time series in the different regions in each subject to determine subject specific graph measures. These graph measures were normalized by values obtained in equivalent random networks. We did not find any significant differences between IBS patients and controls in global normalized graph measures, hubs, or modularity structure of the pain matrix and the DMN in any of our two independent cohorts. Furthermore, we did not find consistent associations between these global network measures and IBS symptom severity or GI-specific anxiety but we found a significant difference in the relationship between measures of psychological distress (anxiety and/or depressive symptoms) and normalized characteristic path length. The responses of these networks to visceral stimulation rather than their organisation at rest may be primarily disturbed in IBS.

Adipose tissue morphology, imaging and metabolomics predicting cardiometabolic risk and family history of type 2 diabetes in non-obese men.

We evaluated the importance of body composition, amount of subcutaneous and visceral fat, liver and heart ectopic fat, adipose tissue distribution and cell size as predictors of cardio-metabolic risk in 53 non-obese male individuals. Known family history of type 2 diabetes was identified in 25 individuals. The participants also underwent extensive phenotyping together with measuring different biomarkers and non-targeted serum metabolomics. We used ensemble learning and other machine learning approaches to identify predictors with considerable relative importance and their intricate interactions. Visceral fat and age were strong individual predictors of ectopic fat accumulation in liver and heart along with markers of lipid oxidation and reduced glucose tolerance. Subcutaneous adipose cell size was the strongest individual predictor of whole-body insulin sensitivity and also a marker of visceral and ectopic fat accumulation. The metabolite 3-MOB along with related branched-chain amino acids demonstrated strong predictability for family history of type 2 diabetes.

An AARS variant as the likely cause of Swedish type hereditary diffuse leukoencephalopathy with spheroids.

Swedish type Hereditary Diffuse Leukoencephalopathy with Spheroids (HDLS-S) is a severe adult-onset leukoencephalopathy with the histopathological hallmark of neuraxonal degeneration with spheroids, described in a large family with a dominant inheritance pattern. The initial stage of the disease is dominated by frontal lobe symptoms that develop into a rapidly advancing encephalopathy with pyramidal, deep sensory, extrapyramidal and optic tract symptoms. Median survival is less than 10 years. Recently, pathogenic mutations in CSF1R were reported in a clinically and histologically similar leukoencephalopathy segregating in several families. Still, the cause of HDLS-S remained elusive since its initial description in 1984, with no CSF1R mutations identified in the family. Here we update the original findings associated with HDLS-S after a systematic and recent assessment of several family members. We also report the results from exome sequencing analyses indicating the p.Cys152Phe variant in the alanyl tRNA synthetase (AARS) gene as the probable cause of this disease. The variant affects an amino acid located in the aminoacylation domain of the protein and does not cause differences in splicing or expression in the brain. Brain pathology in one case after 10 years of disease duration showed the end stage of the disease to be characterized by widespread liquefaction of the white matter leaving only some macrophages and glial cells behind the centrifugally progressing front. These results point to AARS as a candidate gene for rapidly progressing adult-onset CSF1R-negative leukoencephalopathies.

Optimization of b-value schemes for estimation of the diffusion coefficient and the perfusion fraction with segmented intravoxel incoherent motion model fitting.

PURPOSE: Intravoxel incoherent motion (IVIM) modeling for estimation of the diffusion coefficient (D) and perfusion fraction (f) is increasingly popular, but no consensus on standard protocols exists. This study provides a framework for optimization of b-value schemes for reduced estimation uncertainty of D and f from segmented model fitting. THEORY: Analytical expressions for uncertainties of D and f from segmented model fitting were derived as Cramer-Rao lower bounds (CRLBs). METHODS: Optimized b-value schemes were obtained for 3 to 12 acquisitions and in the limit of infinitely many acquisitions through constrained minimization of the CRLBs, with b-values constrained to be 0 or 200 to 800 s/mm2 . The optimized b-value scheme with eight acquisitions was compared with b-values linearly distributed in the allowed range using simulations and in vivo liver data from seven healthy volunteers. RESULTS: All optimized b-value schemes contained exactly three unique b-values regardless of the total number of acquisitions (0, 200, and 800 s/mm2 ) with repeated acquisitions distributed approximately as 1:2:2. Compared with linearly distributed b-values, the variability of estimates of D and f was reduced by approximately 30% as seen both in simulations and in repeated in vivo measurements. CONCLUSION: The uncertainty of IVIM D and f estimates can be reduced by the use of optimized b-value schemes.

Data-driven identification of tumor subregions based on intravoxel incoherent motion reveals association with proliferative activity.

PURPOSE: Intravoxel incoherent motion (IVIM) analysis gives information on tissue diffusion and perfusion and may thus have a potential for e.g. tumor tissue characterization. This work aims to study if clustering based on IVIM parameter maps can identify tumor subregions, and to assess the relevance of obtained subregions by histological analysis. METHODS: Fourteen mice with human neuroendocrine tumors were examined with diffusion-weighted imaging to obtain IVIM parameter maps. Gaussian mixture models with IVIM maps from all tumors as input were used to partition voxels into k clusters, where k = 2 was chosen for further analysis based on goodness of fit. Clustering was performed with and without the perfusion-related IVIM parameter D* , and with and without including spatial information. The validity of the clustering was assessed by comparison with corresponding histologically stained tumor sections. A Ki-67-based index quantifying the degree of tumor proliferation was considered appropriate for the comparison based on the obtained cluster characteristics. RESULTS: The clustering resulted in one class with low diffusion and high perfusion and another with slightly higher diffusion and low perfusion. Strong agreement was found between tumor subregions identified by clustering and subregions identified by histological analysis, both regarding size and spatial agreement. Neither D* nor spatial information had substantial effects on the clustering results. CONCLUSIONS: The results of this study show that IVIM parameter maps can be used to identify tumor subregions using a data-driven framework based on Gaussian mixture models. In the studied tumor model, the obtained subregions showed agreement with proliferative activity.

Evidence for an association of gut microbial Clostridia with brain functional connectivity and gastrointestinal sensorimotor function in patients with irritable bowel syndrome, based on tripartite network analysis.

BACKGROUND AND AIMS: Evidence from preclinical and clinical studies suggests that interactions among the brain, gut, and microbiota may affect the pathophysiology of irritable bowel syndrome (IBS). As disruptions in central and peripheral serotonergic signaling pathways have been found in patients with IBS, we explored the hypothesis that the abundance of serotonin-modulating microbes of the order Clostridiales is associated with functional connectivity of somatosensory brain regions and gastrointestinal (GI) sensorimotor function. METHODS: We performed a prospective study of 65 patients with IBS and 21 healthy individuals (controls) recruited from 2011 through 2013 at a secondary/tertiary care outpatient clinic in Sweden. Study participants underwent functional brain imaging, rectal balloon distension, a nutrient and lactulose challenge test, and assessment of oroanal transit time within a month. They also submitted stool samples, which were analyzed by 16S ribosomal RNA gene sequencing. A tripartite network analysis based on graph theory was used to investigate the interactions among bacteria in the order Clostridiales, connectivity of brain regions in the somatosensory network, and GI sensorimotor function. RESULTS: We found associations between GI sensorimotor function and gut microbes in stool samples from controls, but not in samples from IBS patients. The largest differences between controls and patients with IBS were observed in the Lachnospiraceae incertae sedis, Clostridium XIVa, and Coprococcus subnetworks. We found connectivity of subcortical (thalamus, caudate, and putamen) and cortical (primary and secondary somatosensory cortices) regions to be involved in mediating interactions among these networks. CONCLUSIONS: In a comparison of patients with IBS and controls, we observed disruptions in the interactions between the brain, gut, and gut microbial metabolites in patients with IBS-these involve mainly subcortical but also cortical regions of brain. These disruptions may contribute to altered perception of pain in patients with IBS and may be mediated by microbial modulation of the gut serotonergic system.

Multiparametric MR for non-invasive evaluation of tumour tissue histological characteristics after radionuclide therapy.

Early non-invasive tumour therapy response assessment requires methods sensitive to biological and physiological tumour characteristics. The aim of this study was to find and evaluate magnetic resonance imaging (MRI) derived tumour tissue parameters that correlate with histological parameters and that reflect effects of radionuclide therapy. Mice bearing a subcutaneous human small-intestine neuroendocrine tumour were i.v. injected with 177 Lu-octreotate. MRI was performed (7 T Bruker Biospec) on different post-therapy intervals (1 and 13 days) using T2-weighted imaging, mapping of T2* and T1 relaxation time constants, as well as diffusion and dynamic contrast enhancement (DCE-MRI) techniques. After MRI, animals were killed and tumours excised. Four differently stained histological sections of the most central imaged tumour plane were digitized, and segmentation techniques were used to produce maps reflecting fibrotic and vascular density, apoptosis, and proliferation. Histological maps were aligned with MRI-derived parametric maps using landmark-based registration. Correlations and predictive power were evaluated using linear mixed-effects models and cross-validation, respectively. Several MR parameters showed statistically significant correlations with histological parameters. In particular, three DCE-MRI-derived parameters reflecting capillary function additionally showed high predictive power regarding apoptosis (2/3) and proliferation (1/3). T1 could be used to predict vascular density, and perfusion fraction derived from diffusion MRI could predict fibrotic density, although with lower predictive power. This work demonstrates the potential to use multiparametric MRI to retrieve important information on the tumour microenvironment after radiotherapy. The non-invasiveness of the method also allows longitudinal tumour tissue characterization. Further investigation is warranted to evaluate the parameters highlighted in this study longitudinally, in larger studies, and with additional histological methods.

Comparison of methods for estimation of the intravoxel incoherent motion (IVIM) diffusion coefficient (D) and perfusion fraction (f).

OBJECTIVE: Intravoxel incoherent motion (IVIM) shows great potential in many applications, e.g., tumor tissue characterization. To reduce image-quality demands, various IVIM analysis approaches restricted to the diffusion coefficient (D) and the perfusion fraction (f) are increasingly being employed. In this work, the impact of estimation approach for D and f is studied. MATERIALS AND METHODS: Four approaches for estimating D and f were studied: segmented IVIM fitting, least-squares fitting of a simplified IVIM model (sIVIM), and Bayesian fitting of the sIVIM model using marginal posterior modes or posterior means. The estimation approaches were evaluated in terms of bias and variability as well as ability for differentiation between tumor and healthy liver tissue using simulated and in vivo data. RESULTS: All estimation approaches had similar variability and ability for differentiation and negligible bias, except for the Bayesian posterior mean of f, which was substantially biased. Combined use of D and f improved tumor-to-liver tissue differentiation compared with using D or f separately. DISCUSSION: The similar performance between estimation approaches renders the segmented one preferable due to lower numerical complexity and shorter computational time. Superior tissue differentiation when combining D and f suggests complementary biologically relevant information.

Identification of Potential MR-Derived Biomarkers for Tumor Tissue Response to 177Lu-Octreotate Therapy in an Animal Model of Small Intestine Neuroendocrine Tumor.

Magnetic resonance (MR) methods enable noninvasive, regional tumor therapy response assessment, but associations between MR parameters, underlying biology, and therapeutic effects must be investigated. The aim of this study was to investigate response assessment efficacy and biological associations of MR parameters in a neuroendocrine tumor (NET) model subjected to radionuclide treatment. Twenty-one mice with NETs received 177Lu-octreotate at day 0. MR experiments (day -1, 1, 3, 8, and 13) included T2-weighted, dynamic contrast-enhanced (DCE) and diffusion-weighted imaging (DWI) and relaxation measurements (T1/T2*). Tumor tissue was analyzed using proteomics. MR-derived parameters were evaluated for each examination day and for different radial distances from the tumor center. Response assessment efficacy and biological associations were evaluated using feature selection and protein expression correlations, respectively. Reduced tumor growth rate or shrinkage was observed until day 8, followed by reestablished growth in most tumors. The most important MR parameter for response prediction was DCE-MRI-derived pretreatment signal enhancement ratio (SER) at 40% to 60% radial distance, where it correlated significantly also with centrally sampled protein CCD89 (association: DNA damage and repair, proliferation, cell cycle arrest). The second most important was changed diffusion (D) between day -1 and day 3, at 60% to 80% radial distance, where it correlated significantly also with peripherally sampled protein CATA (association: oxidative stress, proliferation, cell cycle arrest, apoptotic cell death). Important information regarding tumor biology in response to radionuclide therapy is reflected in several MR parameters, SER and D in particular. The spatial and temporal information provided by MR methods increases the sensitivity for tumor therapy response.

Radioembolization Versus Bland Embolization for Hepatic Metastases from Small Intestinal Neuroendocrine Tumors: Short-Term Results of a Randomized Clinical Trial.

BACKGROUND: Radioembolization (RE) with intra-arterial administration of 90Y microspheres is a promising technique for the treatment of liver metastases from small intestinal neuroendocrine tumors (SI-NET) not amenable to surgery or local ablation. However, studies comparing RE to other loco-regional therapies are lacking. The aim of this randomized study was to compare the therapeutic response and safety after RE and bland hepatic arterial embolization (HAE), and to investigate early therapy-induced changes with diffusion-weighted MRI (DWI-MRI). METHODS: Eleven patients were included in a prospective randomized controlled pilot study, six assigned to RE and five to HAE. Response according to RECIST 1.1 using MRI or CT at 3 and 6 months post-treatment was recorded as well as changes in DWI-MRI parameters after 1 month. Data on biochemical tumor response, toxicity, and side effects were also collected. RESULTS: Three months after treatment, all patients in the HAE group showed partial response according to RECIST while none in the RE group did (p = 0.0022). After 6 months, the response rates were 4/5 (80%) and 2/6 (33%) in the HAE and RE groups, respectively (NS). DWI-MRI metrics could not predict RECIST response, but lower pretreatment ADC(120-800) and larger ADC(0-800) increase at 1 month were related to larger decrease in tumor diameter when all tumors were counted. CONCLUSION: HAE resulted in significantly higher RECIST response after 3 months, but no difference compared to RE remained after 6 months. These preliminary findings indicate that HAE remains a safe option for the treatment of liver metastases from SI-NET, and further studies are needed to establish the role of RE and the predictive value of MR-DWI.

Impact of prior distributions and central tendency measures on Bayesian intravoxel incoherent motion model fitting.

PURPOSE: Bayesian model fitting has been proposed as a robust alternative for intravoxel incoherent motion (IVIM) model-fitting parameter estimation. However, consensus regarding choice of prior distribution and posterior distribution central tendency measure is needed. The aim of this study was to compare the quality of IVIM parameter estimates produced by different prior distributions and central tendency measures, and to gain knowledge about the effect of these choices. METHODS: Three prior distributions (uniform, reciprocal, and lognormal) and two measures of central tendency (mean and mode) found in the literature were studied using simulations and in vivo data from a tumor mouse model. RESULTS: Simulations showed that the uniform and lognormal priors were superior to the reciprocal prior, especially for the parameters D and f and clinically relevant SNR levels. The choice of central tendency measure had less effect on the results, but had some effects on estimation bias. Results based on simulations and in vivo data agreed well, indicating high validity of the simulations. CONCLUSIONS: Choice of prior distribution and central tendency measure affects the results of Bayesian IVIM parameter estimates. This must be considered when comparing results from different studies. The best overall quality of IVIM parameter estimates was obtained using the lognormal prior. Magn Reson Med 79:1674-1683, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

The influence of cardiac triggering time and an optimization strategy for improved cardiac MR spectroscopy.

PURPOSE: To study how cardiac motion affects the spectral quality in cardiac MR spectroscopy and to establish an optimization strategy for the cardiac triggering time for improved quality and success rate of cardiac MRS. METHOD: Water spectra were acquired while the cardiac triggering time was varied over the cardiac cycle, and five different spectral quality parameters were studied (frequency, phase, linewidth, amplitude and noise). Furthermore, three different optimization strategies for the cardiac triggering time were tested, and finally, a comparison was made between water suppressed lipid spectra acquired in systole and diastole. RESULTS: The cardiac triggering time had a high impact on the spectral quality, especially on the mean signal amplitude and the standard deviation of the signal amplitude, phase and linewidth. Generally, the highest spectral quality was observed for spectra acquired in mid to end systole, at approximately 23% of the cardiac cycle. The exact optimal triggering time differed between subjects and needed to be individually optimized. To optimize the triggering time with our proposed MRS-method gave in average 13% higher signal than when the triggering time was determined through imaging. Lipid spectra acquired in systole demonstrated higher quality with improved SNR compared with acquisitions made in diastole. CONCLUSION: This study shows that the spectral quality in cardiac MRS is strongly dependent on the cardiac triggering time, and that the spectral quality as well as the repeatability between acquisitions is greatly improved when the cardiac triggering time is individually optimized in mid to end systole using MRS.