29 research outputs found

    Contrast-agent-based perfusion MRI code repository and testing framework: ISMRM Open Science Initiative for Perfusion Imaging (OSIPI)

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    Purpose Software has a substantial impact on quantitative perfusion MRI values. The lack of generally accepted implementations, code sharing and transparent testing reduces reproducibility, hindering the use of perfusion MRI in clinical trials. To address these issues, the ISMRM Open Science Initiative for Perfusion Imaging (OSIPI) aimed to establish a community-led, centralized repository for sharing open-source code for processing contrast-based perfusion imaging, incorporating an open-source testing framework. Methods A repository was established on the OSIPI GitHub website. Python was chosen as the target software language. Calls for code contributions were made to OSIPI members, the ISMRM Perfusion Study Group, and publicly via OSIPI websites. An automated unit-testing framework was implemented to evaluate the output of code contributions, including visual representation of the results. Results The repository hosts 86 implementations of perfusion processing steps contributed by 12 individuals or teams. These cover all core aspects of DCE- and DSC-MRI processing, including multiple implementations of the same functionality. Tests were developed for 52 implementations, covering five analysis steps. For T1 mapping, signal-to-concentration conversion and population AIF functions, different implementations resulted in near-identical output values. For the five pharmacokinetic models tested (Tofts, extended Tofts-Kety, Patlak, two-compartment exchange, and two-compartment uptake), differences in output parameters were observed between contributions. Conclusions The OSIPI DCE-DSC code repository represents a novel community-led model for code sharing and testing. The repository facilitates the re-use of existing code and the benchmarking of new code, promoting enhanced reproducibility in quantitative perfusion imaging

    Are epilepsy-relalated fMRI components dependent on the presence of interictal epileptic discharges in scalp EEG?

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    Spatial independent component analysis (ICA) is increasingly being used to extract resting-state networks from fMRI data. Previous studies showed that ICA also reveals independent components (ICs) related to the seizure onset zone. However, it is currently unknown how these epileptic ICs depend on the presence of interictal epileptic discharges (IEDs) in the EEG. The goal of this study was to explore the relation between ICs obtained from fMRI epochs during the occurrence of IEDs in the EEG and those without IEDs. fMRI data sets with co-registered EEG were retrospectively selected of patients from whom the location of the epileptogenic zone was confirmed by outcome of surgery (n = 8). The fMRI data were split into two epochs: one with IEDs visible in scalp EEG and one without. Spatial ICA was applied to the fMRI data of each part separately. The maps of all resulting components were compared to the resection area and the EEG-fMRI correlation pattern by computing a spatial correlation coefficient to detect the epilepsy-related component. For all patients, except one, there was a remarkable resemblance between the epilepsy-related components selected during epochs with IEDs and those without IEDs. These findings suggest that epilepsy-related ICs are not dependent on the presence of IEDs in scalp EEG. Since these epileptic ICs showed partial overlap with resting-state networks of healthy volunteers (n = 10), our study supports the need for new ways to classify epileptic ICs

    Locally advanced rectal cancer: 3D diffusion-prepared stimulated-echo turbo spin-echo versus 2D diffusion-weighted echo-planar imaging

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    Background: Diffusion-weighted imaging (DWI) has shown great value in rectal cancer imaging. However, traditional DWI with echo-planar imaging (DW-EPI) often suffers from geometrical distortions. We applied a three-dimensional diffusion-prepared stimulated-echo turbo spin-echo sequence (DPsti-TSE), allowing geometrically undistorted rectal DWI. We compared DPsti-TSE with DW-EPI for locally advanced rectal cancer DWI. Methods: For 33 prior-to-treatment patients, DWI images of the rectum were acquired with DPsti-TSE and DW-EPI at 3 T using b-values of 200 and 1000 s/mm2. Two radiologists conducted a blinded scoring of the images considering nine aspects of image quality and anatomical quality. Tumour apparent diffusion coefficient (ADC) and distortions were compared quantitatively. Results: DPsti-TSE scored significantly better than DW-EPI in rectum distortion (p = 0.005) and signal pileup (p = 0.001). DPsti-TSE had better tumour Dice similarity coefficient compared to DW-EPI (0.84 versus 0.80, p = 0.010). Tumour ADC values were higher for DPsti-TSE compared to DW-EPI (1.47 versus 0.86 × 10-3 mm2/s, p < 0.001). Radiologists scored DPsti-TSE significantly lower than DW-EPI on aspects of overall image quality (p = 0.001), sharpness (p < 0.001), quality of fat suppression (p < 0.001), tumour visibility (p = 0.009), tumour conspicuity (p = 0.010) and rectum wall visibility (p = 0.005). Conclusions: DPsti-TSE provided geometrically less distorted rectal cancer diffusion-weighted images. However, the image quality of DW-EPI over DPsti-TSE was referred on the basis of several image quality criteria. A significant bias in tumour ADC values from DPsti-TSE was present. Further improvements of DPsti-TSE are needed until it can replace DW-EPI

    Improved repeatability of dynamic contrast-enhanced MRI using the complex MRI signal to derive arterial input functions: a test-retest study in prostate cancer patients

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    PURPOSE: The arterial input function (AIF) is a major source of uncertainty in tracer kinetic (TK) analysis of dynamic contrast-enhanced (DCE)-MRI data. The aim of this study was to investigate the repeatability of AIFs extracted from the complex signal and of the resulting TK parameters in prostate cancer patients. METHODS: Twenty-two patients with biopsy-proven prostate cancer underwent a 3T MRI exam twice. DCE-MRI data were acquired with a 3D spoiled gradient echo sequence. AIFs were extracted from the magnitude of the signal (AIFMAGN ), phase (AIFPHASE ), and complex signal (AIFCOMPLEX ). The Tofts model was applied to extract Ktrans , kep and ve . Repeatability of AIF curve characteristics and TK parameters was assessed with the within-subject coefficient of variation (wCV). RESULTS: The wCV for peak height and full width at half maximum for AIFCOMPLEX (7% and 8%) indicated an improved repeatability compared to AIFMAGN (12% and 12%) and AIFPHASE (12% and 7%). This translated in lower wCV values for Ktrans (11%) with AIFCOMPLEX in comparison to AIFMAGN (24%) and AIFPHASE (15%). For kep , the wCV was 16% with AIFMAGN , 13% with AIFPHASE , and 13% with AIFCOMPLEX . CONCLUSION: Repeatability of AIFPHASE and AIFCOMPLEX is higher than for AIFMAGN , resulting in a better repeatability of TK parameters. Thus, use of either AIFPHASE or AIFCOMPLEX improves the robustness of quantitative analysis of DCE-MRI in prostate cancer.status: publishe
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