An open source software for analysis of dynamic contrast enhanced magnetic resonance images: UMMPerfusion revisited

Background: Perfusion imaging has become an important image based tool to derive the physiological information in various applications, like tumor diagnostics and therapy, stroke, (cardio-) vascular diseases, or functional assessment of organs. However, even after 20 years of intense research in this field, perfusion imaging still remains a research tool without a broad clinical usage. One problem is the lack of standardization in technical aspects which have to be considered for successful quantitative evaluation; the second problem is a lack of tools that allow a direct integration into the diagnostic workflow in radiology. Results: Five compartment models, namely, a one compartment model (1CP), a two compartment exchange (2CXM), a two compartment uptake model (2CUM), a two compartment filtration model (2FM) and eventually the extended Toft’s model (ETM) were implemented as plugin for the DICOM workstation OsiriX. Moreover, the plugin has a clean graphical user interface and provides means for quality management during the perfusion data analysis. Based on reference test data, the implementation was validated against a reference implementation. No differences were found in the calculated parameters. Conclusion: We developed open source software to analyse DCE-MRI perfusion data. The software is designed as plugin for the DICOM Workstation OsiriX. It features a clean GUI and provides a simple workflow for data analysis while it could also be seen as a toolbox providing an implementation of several recent compartment models to be applied in research tasks. Integration into the infrastructure of a radiology department is given via OsiriX. Results can be saved automatically and reports generated automatically during data analysis ensure certain quality control

Validation of a computational fluid dynamics model of drug delivery and interstitial fluid pressure in ovarian cancer xenografts

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Special issue on magnetic resonance imaging biomarkers of renal disease

No abstract available

Dynamic Contrast-Enhanced Magnetic Resonance Imaging Suggests Normal Perfusion in Normal-Appearing White Matter in Multiple Sclerosis

Objectives: Multiple sclerosis (MS) is a chronic, inflammatory disease of the central nervous system and has been associated with reduced perfusion in normal-appearing white matter (NAWM). The magnitude of this hypoperfusion is unclear. The present study aims to quantify NAWM perfusion with dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) in patients with relapsing-remitting (RR) MS and in a control group. Materials and Methods: The statistical power of a DCE-MRI acquisition to reveal hypoperfusion in MS was estimated using a Monte Carlo simulation: synthetic tissue curves with a contrast-to-noise ratio of 8 were generated for MS patients and control group using perfusion values reported in previous studies. A compartment-uptake model was fitted to these curves, yielding estimates of cerebral blood flow (CBF), cerebral blood volume (CBV), and permeability-surface area product (PS). This was repeated 1000 times. Mean and standard deviation of the resulting distributions were used to calculate the statistical power of a DCE-MRI study to detect perfusion differences between 16 control subjects and 24 MS subjects. In an institutional review board-approved study, patients with RR-MS (n = 24;mean age, 36 years;17 women, mean Enhanced Disability Status Scale score, 3.25) and patients without history or symptoms of neurological disorder (n = 16;mean age, 49 years;9 women) underwent a DCE-MRI examination with a previously established MRI protocol (3D SPGR sequence;2.1 seconds temporal resolution;44 slices;spatial resolution, 1.7 x 1.7 x 3 mm). Regions were defined manually in the middle cerebral artery;in the frontal, periventricular, and occipital NAWM;in the pons;and in the thalamus, and CBF, CBV, and PS were quantified using a compartment-uptake model. Parameter differences between MS and control groups were evaluated using a mixed linear model with subjects as random effect and controlling for age and sex. A P value of less than 0.05 was considered to indicate statistical significance. Results: For all but one of previously reported effect sizes, the simulation study estimated a statistical power of 80% to 100% to detect reduced CBF in MS. In the patient study, mean (standard deviation) CBF in NAWM was 11.0 (15.1) and 10.4 (8.2) mL/100 mL per minute in the MS and control groups, respectively. Mean CBV in NAWM was 0.50 (0.45) mL/100 mL in the MS group and 0.48 (0.28) mL/100 mL in the control group. Mean values of PS in NAWM were 0.002 mL (0.027)/100 mL per minute in the control group and -0.001 (0.015) mL/100 mL per minute in the MS patients. Differences between patient groups were not statistically significant for CBF, CBV, mean transit time, and PS (P = 0.44, P = 0.20, P = 0.78, P = 0.66, respectively). In both groups, the influence of age on any parameter was nonsignificant. Cerebral blood flow and CBV in the thalamus and pons were significantly higher than in NAWM regions (P 0.25) in all evaluated regions. Conclusions: Despite high statistical power, we could not confirm previous reports of NAWM hypoperfusion in MS. This indicates that, at least in our patient cohort, potential hypoperfusion is much less pronounced than reported in previous studies

Alterations in anatomic and functional imaging parameters with repeated FDG PET-CT and MRI during radiotherapy for head and neck cancer: a pilot study

Background: The use of imaging to implement on-treatment adaptation of radiotherapy is a promising paradigm but current data on imaging changes during radiotherapy is limited. This is a hypothesis-generating pilot study to examine the changes on multi-modality anatomic and functional imaging during (chemo)radiotherapy treatment for head and neck squamous cell carcinoma (HNSCC). Methods: Eight patients with locally advanced HNSCC underwent imaging including computed tomography (CT), Fluorine-18 fluorodeoxyglucose (FDG) positron emission tomography (PET)-CT and magnetic resonance imaging (MRI) (including diffusion weighted (DW) and dynamic contrast enhanced (DCE)) at baseline and during (chemo)radiotherapy treatment (after fractions 11 and 21). Regions of interest (ROI) were drawn around the primary tumour at baseline and during treatment. Imaging parameters included gross tumour volume (GTV) assessment, SUVmax, mean ADC value and DCE-MRI parameters including Plasma Flow (PF). On treatment changes and correlations between these parameters were analysed using a Wilcoxon rank sum test and Pearson’s linear correlation coefficient respectively. A p-value <0.05 was considered statistically significant. Results: Statistically significant reductions in GTV-CT, GTV-MRI and GTV-DW were observed between all imaging timepoints during radiotherapy. Changes in GTV-PET during radiotherapy were heterogeneous and non-significant. Significant changes in SUVmax, mean ADC value, Plasma Flow and Plasma Volume were observed between the baseline and the fraction 11 timepoint, whilst only changes in SUVmax between baseline and the fraction 21 timepoint were statistically significant. Significant correlations were observed between multiple imaging parameters, both anatomical and functional; 20 correlations between baseline to the fraction 11 timepoint; 12 correlations between baseline and the fraction 21 timepoints; and 4 correlations between the fraction 11 and fraction 21 timepoints. Conclusions: Multi-modality imaging during radiotherapy treatment demonstrates early changes (by fraction 11) in both anatomic and functional imaging parameters. All functional imaging modalities are potentially complementary and should be considered in combination to provide multi-parametric tumour assessment, to guide potential treatment adaptation strategies. Trial Registration: ISRCTN Registry: ISRCTN34165059. Registered 2nd February 2015