Publications by authors named "Dirk H J Poot"

39 Publications

Association Between T Relaxation Times Derived From Ultrashort Echo Time MRI and Symptoms During Exercise Therapy for Patellar Tendinopathy: A Large Prospective Study.

J Magn Reson Imaging 2021 May 30. Epub 2021 May 30.

Department of Radiology & Nuclear Medicine, Erasmus MC University Medical Center, Rotterdam, The Netherlands.

Background: Exercise therapy is considered preferential treatment for patellar tendinopathy (PT). However, there is conflicting evidence for structural patellar tendon adaptation in response to exercise therapy and its association with symptoms is weak.

Purpose: To assess the association between 1) T relaxation times and symptom severity; 2) baseline T and clinical outcome; and 3) longitudinal T changes and clinical outcome in athletes with PT performing exercise therapy.

Study Type: Randomized controlled clinical trial.

Subjects: Seventy-six athletes (18-35 years) with clinically diagnosed and ultrasound-confirmed PT.

Field Strength/sequence: 3D gradient echo sequence (3.0 T).

Assessment: Patients were enrolled in a randomized trial of progressive tendon-loading exercises (PTLE) versus eccentric exercise therapy (EET). Symptoms were assessed using the Victorian Institute of Sports Assessment (VISA-P) questionnaire. 3D-Ultrashort echo time (UTE)-MRI was acquired at baseline, 12 and 24 weeks. Voxel-wise T relaxation times were quantified using mono-exponential and bi-exponential models. T analysis was performed in three patellar tendon tissue compartments representing: aligned collagen, degenerative tissue, and interface.

Statistical Tests: Adjusted general linear, mixed-linear models, and generalized estimating equations.

Results: We included 76 patients with PT (58 men, mean age 24 ± 4 years); 38 in the PTLE-group and 38 in the EET-group, of which 57 subjects remained eligible for analysis. T relaxation times were significantly associated with VISA-P in degenerative and interface tissues of the patellar tendon. No association was found between baseline T and VISA-P after 24 weeks (P > 0.29). The estimated mean T in degenerative tissue decreased from 14 msec (95%CI: 12-16) at baseline to 13 msec (95%CI: 11-15) at 12 weeks and to 13 msec (95%CI: 10-15) at 24 weeks. The significant decrease in T from baseline to 24 weeks was associated with improved clinical outcome.

Data Conclusion: Tissue-specific T relaxation times, identified with 3D-UTE-MRI, decreased significantly in athletes with patellar tendinopathy performing exercise therapy and this decrease was associated with improved clinical outcome.

Evidence Level: 1 TECHNICAL EFFICACY: Stage 4.
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http://dx.doi.org/10.1002/jmri.27751DOI Listing
May 2021

T mapping of healthy knee cartilage: multicenter multivendor reproducibility.

Quant Imaging Med Surg 2021 Apr;11(4):1247-1255

Department of Radiology & Nuclear Medicine, Erasmus MC University Medical Center Rotterdam, The Netherlands.

Background: T mapping is increasingly used to quantify cartilage degeneration in knee osteoarthritis (OA), yet reproducibility studies in a multicenter setting are limited. The purpose of this study was to determine the longitudinal reproducibility and multicenter variation of cartilage T mapping, using various MRI equipment and acquisition protocols.

Methods: In this prospective multicenter study, four traveling, healthy human subjects underwent T mapping twice at five different centers with a 6-month-interval. Centers had various MRI scanners, field strengths, and T mapping acquisition protocols. Mean T values were calculated in six cartilage regions of interest (ROIs) as well as an average value per patient. A phantom was scanned once at each center. To evaluate longitudinal reproducibility, intraclass correlation coefficients (ICC), root-mean-square coefficient of variation (RMS-CV), and a Bland-Altman plot were used. To assess the variation of and phantom T values across centers, ANOVA was performed.

Results: ICCs of the T mapping measurements per ROI and the ROI's combined ranged from 0.73 to 0.91, indicating good to excellent longitudinal reproducibility. RMS-CVs ranged from 1.1% to 1.5% (per ROI) and 0.6% to 1.6% (ROIs combined) across the centers. A Bland-Altman plot did not reveal a systematic error. Evident, but consistent, discrepancies in T values were observed across centers, both and in the phantom.

Conclusions: The results of this study suggest that T mapping can be used to longitudinal assess cartilage degeneration in multicenter studies. Given the differences in absolute cartilage T values across centers, absolute T values derived from various centers in multicenter multivendor trials should not be pooled.
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http://dx.doi.org/10.21037/qims-20-674DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7930682PMC
April 2021

APIR4EMC: Autocalibrated parallel imaging reconstruction for extended multi-contrast imaging.

Magn Reson Imaging 2021 05 14;78:80-89. Epub 2021 Feb 14.

Department of Medical Informatics, Erasmus MC, Rotterdam, the Netherlands; Department of Radiology and Nuclear Medicine, Erasmus MC, Rotterdam, the Netherlands.

Purpose: To improve image quality of multi-contrast imaging with the proposed Autocalibrated Parallel Imaging Reconstruction for Extended Multi-Contrast Imaging (APIR4EMC).

Methods: APIR4EMC reconstructs multi-contrast images in an autocalibrated parallel imaging reconstruction framework by adding contrasts as virtual coils. Compensation of signal evolution along the echo train of different contrasts is performed to improve signal prediction for missing samples. As a proof of concept, we performed prospectively accelerated phantom and in-vivo brain acquisitions with T1, T1-fat saturated (Fatsat), T2, PD, and FLAIR contrasts. The k-space sampling patterns of these acquisitions were jointly optimized. Images were jointly reconstructed with the proposed APIR4EMC method as well as individually with GRAPPA. Root mean square error (RMSE) to fully sampled reference images and g-factor maps were computed for both methods in the phantom experiment. Visual evaluation was performed in the in-vivo experiment.

Results: Compared to GRAPPA, APIR4EMC reduced artifacts and improved SNR of the reconstructed images in the phantom acquisitions. Quantitatively, APIR4EMC substantially reduced noise amplification (g-factor) as well as RMSE compared to GRAPPA. Signal evolution compensation reduced artifacts. In the in-vivo experiments, 1 mm isotropic 3D images with contrasts of T1, T1-Fatsat, T2, PD, and FLAIR were acquired in as little as 7.5 min with the acceleration factor of 9. Reconstruction quality was consistent with the phantom results.

Conclusion: Compared to single contrast reconstruction with GRAPPA, APIR4EMC reduces artifacts and noise amplification in accelerated multi-contrast imaging.
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http://dx.doi.org/10.1016/j.mri.2021.02.002DOI Listing
May 2021

Quantitative volume and dynamic contrast-enhanced MRI derived perfusion of the infrapatellar fat pad in patellofemoral pain.

Quant Imaging Med Surg 2021 Jan;11(1):133-142

Department of Radiology & Nuclear Medicine, Erasmus MC, Rotterdam, The Netherlands.

Background: Patellofemoral pain (PFP) is a common knee condition and possible precursor of knee osteoarthritis (OA). Inflammation, leading to an increased perfusion, or increased volume of the infrapatellar fat pad (IPFP) may induce knee pain. The aim of the study was to compare quantitative dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) parameters, as imaging biomarkers of inflammation, and volume of the IPFP between patients with PFP and controls and between patients with and without IPFP edema or joint effusion.

Methods: Patients with PFP and healthy controls were included and underwent non-fat suppressed 3D fast-spoiled gradient-echo (FSPGR) and DCE-MRI. Image registration was applied to correct for motion. The IPFP was delineated on FSPGR using Horos software. Volume was calculated and quantitative perfusion parameters were extracted by fitting extended Tofts' pharmacokinetic model. Differences in volume and DCE-MRI parameters between patients and controls were tested by linear regression analyses. IPFP edema and effusion were analyzed identically.

Results: Forty-three controls and 35 PFP patients were included. Mean IPFP volume was 26.04 (4.18) mL in control subjects and 27.52 (5.37) mL in patients. Median K was 0.017 (0.016) min in control subjects and 0.016 (0.020) min in patients. None of the differences in volume and perfusion parameters were statistically significant. Knees with effusion showed a higher perfusion of the IPFP compared to knees without effusion in patients only.

Conclusions: The IPFP has been implicated as source of knee pain, but higher DCE-MR blood perfusion, an imaging biomarker of inflammation, and larger volume are not associated with PFP. Patient's knees with effusion showed a higher perfusion, pointing towards inflammation.
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http://dx.doi.org/10.21037/qims-20-441DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7719925PMC
January 2021

An optimal acquisition and post-processing pipeline for hybrid IVIM-DKI in head and neck.

Magn Reson Med 2021 02 31;85(2):777-789. Epub 2020 Aug 31.

Department of Radiology and Nuclear Medicine, Erasmus MC, Rotterdam, The Netherlands.

Purpose: To optimize the diffusion-weighting b values and postprocessing pipeline for hybrid intravoxel incoherent motion diffusion kurtosis imaging in the head and neck region.

Methods: Optimized diffusion-weighting b value sets ranging between 5 and 30 b values were constructed by optimizing the Cramér-Rao lower bound of the hybrid intravoxel incoherent motion diffusion kurtosis imaging model. With this model, the perfusion fraction, pseudodiffusion coefficient, diffusion coefficient, and kurtosis were estimated. Sixteen volunteers were scanned with a reference b value set and 3 repeats of the optimized sets, of which 1 with volunteers swallowing on purpose. The effects of (1) b value optimization and number of b values, (2) registration type (none vs. intervolume vs. intra- and intervolume registration), and (3) manual swallowing artifact rejection on the parameter precision were assessed.

Results: The SD was higher in the reference set for perfusion fraction, diffusion coefficient, and kurtosis by a factor of 1.7, 1.5, and 2.3 compared to the optimized set, respectively. A smaller SD (factor 0.7) was seen in pseudodiffusion coefficient. The sets containing 15, 20, and 30 b values had comparable repeatability in all parameters, except pseudodiffusion coefficient, for which set size 30 was worse. Equal repeatability for the registration approaches was seen in all parameters of interest. Swallowing artifact rejection removed the bias when present.

Conclusion: To achieve optimal hybrid intravoxel incoherent motion diffusion kurtosis imaging in the head and neck region, b value optimization and swallowing artifact image rejection are beneficial. The optimized set of 15 b values yielded the optimal protocol efficiency, with a precision comparable to larger b value sets and a 50% reduction in scan time.
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http://dx.doi.org/10.1002/mrm.28461DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7693044PMC
February 2021

Tissue-Specific T * Biomarkers in Patellar Tendinopathy by Subregional Quantification Using 3D Ultrashort Echo Time MRI.

J Magn Reson Imaging 2020 08 28;52(2):420-430. Epub 2020 Feb 28.

Department of Radiology & Nuclear Medicine, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands.

Background: Quantitative MRI of patellar tendinopathy (PT) can be challenging due to spatial variation of T * relaxation times.

Purpose: 1) To compare T * quantification using a standard approach with analysis in specific tissue compartments of the patellar tendon. 2) To evaluate test-retest reliability of different methods for fitting ultrashort echo time (UTE)-relaxometry data.

Study Type: Prospective.

Subjects: Sixty-five athletes with PT.

Field Strength/sequence: 3D UTE scans covering the patellar tendon were acquired using a 3.0T scanner and a 16-channel surface coil.

Assessment: Voxelwise median T * was quantified with monoexponential, fractional-order, and biexponential fitting. We applied two methods for T * analysis: first, a standard approach by analyzing all voxels covering the proximal patellar tendon. Second, within subregions of the patellar tendon, by using thresholds on biexponential fitting parameter percentage short T * (0-30% for mostly long T *, 30-60% for mixed T *, and 60-100% for mostly short T *).

Statistical Tests: Average test-retest reliability was assessed in three athletes using coefficients-of-variation (CV) and coefficients-of-repeatability (CR).

Results: With standard image analysis, we found a median [interquartile range, IQR] monoexponential T * of 6.43 msec [4.32-8.55] and fractional order T * 4.39 msec [3.06-5.78]. The percentage of short T * components was 52.9% [35.5-69.6]. Subregional monoexponential T * was 13.78 msec [12.11-16.46], 7.65 msec [6.49-8.61], and 3.05 msec [2.52-3.60] and fractional order T * 11.82 msec [10.09-14.44], 5.14 msec [4.25-5.96], and 2.19 msec [1.82-2.64] for 0-30%, 30-60%, and 60-100% short T *, respectively. Biexponential component short T * was 1.693 msec [1.417-2.003] for tissue with mostly short T * and long T * of 15.79 msec [13.47-18.61] for mostly long T *. The average CR (CV) was 2 msec (15%), 2 msec (19%) and 10% (22%) for monoexponential, fractional order and percentage short T *, respectively.

Data Conclusion: Patellar tendinopathy is characterized by regional variability in binding states of water. Quantitative multicompartment T * analysis in PT can be facilitated using a voxel selection method based on using biexponential fitting parameters.

Level Of Evidence: 1 TECHNICAL EFFICACY STAGE: 1 J. Magn. Reson. Imaging 2020;52:420-430.
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http://dx.doi.org/10.1002/jmri.27108DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7496783PMC
August 2020

Quantitative DCE-MRI demonstrates increased blood perfusion in Hoffa's fat pad signal abnormalities in knee osteoarthritis, but not in patellofemoral pain.

Eur Radiol 2020 Jun 17;30(6):3401-3408. Epub 2020 Feb 17.

Department of Radiology & Nuclear Medicine, Erasmus University Medical Center Rotterdam, Rotterdam, The Netherlands.

Objective: Infrapatellar fat pad (IPFP) fat-suppressed T2 (T2) hyperintense regions on MRI are an important imaging feature of knee osteoarthritis (OA) and are thought to represent inflammation. These regions are also common in non-OA subjects, and may not always be linked to inflammation. Our aim was to evaluate quantitative blood perfusion parameters, as surrogate measure of inflammation, within T2-hyperintense regions in patients with OA, with patellofemoral pain (PFP) (supposed OA precursor), and control subjects.

Methods: Twenty-two knee OA patients, 35 PFP patients and 43 healthy controls were included and underwent MRI, comprising T2 and DCE-MRI sequences. T2-hyperintense IPFP regions were delineated and a reference region was drawn in adjacent IPFP tissue with normal signal intensity. After fitting the extended Tofts pharmacokinetic model, quantitative DCE-MRI perfusion parameters were compared between the two regions within subjects in each subgroup, using a paired Wilcoxon signed-rank test.

Results: T2-hyperintense IPFP regions were present in 16 of 22 (73%) OA patients, 13 of 35 (37%) PFP patients, and 14 of 43 (33%) controls. DCE-MRI perfusion parameters were significantly different between regions with and without a T2-hyperintense signal in OA patients, demonstrating higher Ktrans compared to normal IFPF tissue (0.039 min versus 0.025 min, p = 0.017) and higher Ve (0.157 versus 0.119, p = 0.010). For PFP patients and controls no significant differences were found.

Conclusions: IPFP T2-hyperintense regions are associated with higher perfusion in knee OA patients in contrast to identically appearing regions in PFP patients and controls, pointing towards an inflammatory pathogenesis in OA only.

Key Points: • Morphologically identical appearing T2-hyperintense infrapatellar fat pad regions show different perfusion in healthy subjects, subjects with patellofemoral pain, and subjects with knee osteoarthritis. • Elevated DCE-MRI perfusion parameters within T2-hyperintense infrapatellar fat pad regions in patients with osteoarthritis suggest an inflammatory pathogenesis in osteoarthritis, but not in patellofemoral pain and healthy subjects.
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http://dx.doi.org/10.1007/s00330-020-06671-6DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7248045PMC
June 2020

Predicting Global Cognitive Decline in the General Population Using the Disease State Index.

Front Aging Neurosci 2019 23;11:379. Epub 2020 Jan 23.

Department of Radiology and Nuclear Medicine, Erasmus MC University Medical Center Rotterdam, Rotterdam, Netherlands.

Background: Identifying persons at risk for cognitive decline may aid in early detection of persons at risk of dementia and to select those that would benefit most from therapeutic or preventive measures for dementia.

Objective: In this study we aimed to validate whether cognitive decline in the general population can be predicted with multivariate data using a previously proposed supervised classification method: Disease State Index (DSI).

Methods: We included 2,542 participants, non-demented and without mild cognitive impairment at baseline, from the population-based Rotterdam Study (mean age 60.9 ± 9.1 years). Participants with significant global cognitive decline were defined as the 5% of participants with the largest cognitive decline per year. We trained DSI to predict occurrence of significant global cognitive decline using a large variety of baseline features, including magnetic resonance imaging (MRI) features, cardiovascular risk factors, APOE-ε4 allele carriership, gait features, education, and baseline cognitive function as predictors. The prediction performance was assessed as area under the receiver operating characteristic curve (AUC), using 500 repetitions of 2-fold cross-validation experiments, in which (a randomly selected) half of the data was used for training and the other half for testing.

Results: A mean AUC (95% confidence interval) for DSI prediction was 0.78 (0.77-0.79) using only age as input feature. When using all available features, a mean AUC of 0.77 (0.75-0.78) was obtained. Without age, and with age-corrected features and feature selection on MRI features, a mean AUC of 0.70 (0.63-0.76) was obtained, showing the potential of other features besides age.

Conclusion: The best performance in the prediction of global cognitive decline in the general population by DSI was obtained using only age as input feature. Other features showed potential, but did not improve prediction. Future studies should evaluate whether the performance could be improved by new features, e.g., longitudinal features, and other prediction methods.
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http://dx.doi.org/10.3389/fnagi.2019.00379DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6989484PMC
January 2020

An Efficient Method for Multi-Parameter Mapping in Quantitative MRI Using B-Spline Interpolation.

IEEE Trans Med Imaging 2020 05 21;39(5):1681-1689. Epub 2019 Nov 21.

Quantitative MRI methods that estimate multiple physical parameters simultaneously often require the fitting of a computational complex signal model defined through the Bloch equations. Repeated Bloch simulations can be avoided by matching the measured signal with a precomputed signal dictionary on a discrete parameter grid (i.e. lookup table) as used in MR Fingerprinting. However, accurate estimation requires discretizing each parameter with a high resolution and consequently high computational and memory costs for dictionary generation, storage, and matching. Here, we reduce the required parameter resolution by approximating the signal between grid points through B-spline interpolation. The interpolant and its gradient are evaluated efficiently which enables a least-squares fitting method for parameter mapping. The resolution of each parameter was minimized while obtaining a user-specified interpolation accuracy. The method was evaluated by phantom and in-vivo experiments using fully-sampled and undersampled unbalanced (FISP) MR fingerprinting acquisitions. Bloch simulations incorporated relaxation effects (T,T) , proton density (PD ) , receiver phase ( φ ), transmit field inhomogeneity ( B ), and slice profile. Parameter maps were compared with those obtained from dictionary matching, where the parameter resolution was chosen to obtain similar signal (interpolation) accuracy. For both the phantom and the in-vivo acquisition, the proposed method approximated the parameter maps obtained through dictionary matching while reducing the parameter resolution in each dimension ( T,T,B ) by - on average - an order of magnitude. In effect, the applied dictionary was reduced from 1.47GB to 464KB . Furthermore, the proposed method was equally robust against undersampling artifacts as dictionary matching. Dictionary fitting with B-spline interpolation reduces the computational and memory costs of dictionary-based methods and is therefore a promising method for multi-parametric mapping.
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http://dx.doi.org/10.1109/TMI.2019.2954751DOI Listing
May 2020

Autocalibrated parallel imaging reconstruction with sampling pattern optimization for GRASE: APIR4GRASE.

Magn Reson Imaging 2020 02 23;66:141-151. Epub 2019 Aug 23.

Department of Medical Informatics, Erasmus MC, Rotterdam, the Netherlands; Department of Radiology and Nuclear Medicine, Erasmus MC, Rotterdam, the Netherlands.

Purpose: To reduce artifacts and scan time of GRASE imaging by selecting an optimal sampling pattern and jointly reconstructing gradient echo and spin echo images.

Methods: We jointly reconstruct images for the different echo types by considering these as additional virtual coil channels in the novel Autocalibrated Parallel Imaging Reconstruction with Sampling Pattern Optimization for GRASE (APIR4GRASE) method. Besides image reconstruction, we identify optimal sampling patterns for the acquisition. The selected optimal patterns were validated on phantom and in-vivo acquisitions. Comparison to the conventional GRASE without acceleration, and to the GRAPPA reconstruction with a single echo type was also performed.

Results: Using identified optimal sampling patterns, APIR4GRASE eliminated modulation artifacts in both phantom and in-vivo experiments; mean square error (MSE) was reduced by 78% and 94%, respectively, compared to the conventional GRASE with similar scan time. Both artifacts and g-factor were reduced compared to the GRAPPA reconstruction with a single echo type.

Conclusion: APIR4GRASE substantially improves the speed and quality of GRASE imaging over the state-of-the-art, and is able to reconstruct both spin echo and gradient echo images.
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http://dx.doi.org/10.1016/j.mri.2019.08.019DOI Listing
February 2020

Quantitative subchondral bone perfusion imaging in knee osteoarthritis using dynamic contrast enhanced MRI.

Semin Arthritis Rheum 2020 Apr 1;50(2):177-182. Epub 2019 Aug 1.

Department of Radiology & Nuclear Medicine, Erasmus MC, University Medical Center, Rotterdam, the Netherlands. Electronic address:

Objective: Subchondral bone changes, characterized by increased bone turnover and vascularity, are believed to stimulate progression and pain in knee osteoarthritis (OA). The objective of this study was to evaluate the bone perfusion in knee OA using quantitative dynamic contrast enhanced MRI (DCE-MRI).

Design: Unicompartmental knee OA patients were included and underwent 3 Tesla DCE-MRI and T2-weighted MRI. Quantitative DCE-MRI analysis of Ktrans and Kep, representing perfusion parameters, was performed to evaluate differences between the most and least affected knee compartment. First, DCE-MRI parameter differences between epimetaphyseal and subchondral bone in both femur and tibia were assessed. Second, DCE-MRI parameters in subchondral bone marrow lesions (BMLs) were compared to surrounding subchondral bone without BMLs.

Results: Twenty-three patients were analyzed. Median Ktrans and Kep in epimetaphyseal bone were significantly higher (p < 0.05) in the most affected (Ktrans: 0.014; Kep: 0.054 min) compared to least affected (Ktrans: 0.010; Kep: 0.016 min) compartment. For subchondral bone, DCE-MRI parameters were significantly higher (p < 0.05) in the most affected (Ktrans: 0.019; Kep: 0.091 min) compared to least affected (Ktrans: 0.014; Kep: 0.058 min) compartment as well. Subchondral BMLs detected on fat-saturated T2-weighted images were present in all patients. Median Ktrans (0.091 vs 0.000 min) and Kep (0.258 vs 0.000 min) were significantly higher within subchondral BMLs compared to surrounding subchondral bone without BMLs (p < 0.001).

Conclusions: Increased perfusion parameters in epimetaphyseal bone, subchondral bone and BMLs are observed in unicompartmental knee OA. BMLs likely account for most of the effect of the higher bone perfusion in knee OA.
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http://dx.doi.org/10.1016/j.semarthrit.2019.07.013DOI Listing
April 2020

Groupwise image registration based on a total correlation dissimilarity measure for quantitative MRI and dynamic imaging data.

Sci Rep 2018 08 30;8(1):13112. Epub 2018 Aug 30.

Biomedical Imaging Group Rotterdam, Departments of Radiology and Medical Informatics, Erasmus MC - University Medical Centre Rotterdam, Rotterdam, The Netherlands.

The most widespread technique used to register sets of medical images consists of selecting one image as fixed reference, to which all remaining images are successively registered. This pairwise scheme requires one optimization procedure per pair of images to register. Pairwise mutual information is a common dissimilarity measure applied to a large variety of datasets. Alternative methods, called groupwise registrations, have been presented to register two or more images in a single optimization procedure, without the need of a reference image. Given the success of mutual information in pairwise registration, we adapt one of its multivariate versions, called total correlation, in a groupwise context. We justify the choice of total correlation among other multivariate versions of mutual information, and provide full implementation details. The resulting total correlation measure is remarkably close to measures previously proposed by Huizinga et al. based on principal component analysis. Our experiments, performed on five quantitative imaging datasets and on a dynamic CT imaging dataset, show that total correlation yields registration results that are comparable to Huizinga's methods. Total correlation has the advantage of being theoretically justified, while the measures of Huizinga et al. were designed empirically. Additionally, total correlation offers an alternative to pairwise mutual information on quantitative imaging datasets.
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http://dx.doi.org/10.1038/s41598-018-31474-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6117310PMC
August 2018

Groupwise Multichannel Image Registration.

IEEE J Biomed Health Inform 2019 05 6;23(3):1171-1180. Epub 2018 Jun 6.

Multichannel image registration is an important challenge in medical image analysis. Multichannel images result from modalities such as dual-energy CT or multispectral microscopy. Besides, multichannel feature images can be derived from acquired images, for instance, by applying multiscale feature banks to the original images to register. Multichannel registration techniques have been proposed, but most of them are applicable to only two multichannel images at a time. In the present study, we propose to formulate multichannel registration as a groupwise image registration problem. In this way, we derive a method that allows the registration of two or more multichannel images in a fully symmetric manner (i.e., all images play the same role in the registration procedure), and therefore, has transitive consistency by definition. The method that we introduce is applicable to any number of multichannel images, any number of channels per image, and it allows to take into account correlation between any pair of images and not just corresponding channels. In addition, it is fully modular in terms of dissimilarity measure, transformation model, regularisation method, and optimisation strategy. For two multimodal datasets, we computed feature images from the initially acquired images, and applied the proposed registration technique to the newly created sets of multichannel images. MIND descriptors were used as feature images, and we chose total correlation as groupwise dissimilarity measure. Results show that groupwise multichannel image registration is a competitive alternative to the pairwise multichannel scheme, in terms of registration accuracy and insensitivity towards registration reference spaces.
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http://dx.doi.org/10.1109/JBHI.2018.2844361DOI Listing
May 2019

Blood perfusion of patellar bone measured by dynamic contrast-enhanced MRI in patients with patellofemoral pain: A case-control study.

J Magn Reson Imaging 2018 11 7;48(5):1344-1350. Epub 2018 May 7.

Department of Radiology & Nuclear Medicine, Erasmus MC, University Medical Center, Rotterdam, The Netherlands.

Background: Altered perfusion might play an important role in the pathophysiology of patellofemoral pain (PFP), a common knee complaint with unclear pathophysiology.

Purpose: To investigate differences in dynamic contrast-enhanced (DCE)-MRI perfusion parameters between patients with PFP and healthy control subjects.

Population/subjects/phantom/specimen/animal Model: Thirty-five adult patients with PFP and 44 healthy adult control subjects.

Field Strength/sequence: 3T DCE-MRI consisting of a sagittal, anterior-posterior, frequency-encoded, fat-suppressed 3D spoiled gradient-echo sequence with intravenous contrast administration.

Assessment: Patellar bone volumes of interest (VOIs) were delineated by a blinded observer. Quantitative perfusion parameters (k and k ) were calculated from motion-compensated DCE-MRI data by fitting Tofts' model. Weighted mean and unweighted median values of k and k were computed within the patellar bone VOIs.

Statistical Tests: Differences in patellar bone perfusion parameters were compared between groups by linear regression analyses, adjusted for confounders.

Results: Mean differences of weighted mean and unweighted median were 0.0039 (95% confidence interval [CI] -0.0013; 0.0091) and 0.0052 (95% CI -0.0078; 0.018) for k , and 0.046 (95% CI -0.021; 0.11) and 0.069 (95% CI -0.017; 0.15) for k , respectively. All perfusion parameters were not significantly different between groups (P-values: 0.32; 0.47 for k , and 0.24; 0.15) for k . However, a significant difference in variance between populations was observed for k (P-value 0.007).

Data Conclusion: Higher patellar bone perfusion parameters were found in patients with PFP when compared to healthy control subjects, but these differences were not statistically significant. This result, and the observed significant difference in k variance, warrant further research.

Level Of Evidence: 1 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2018;47:1344-1350.
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http://dx.doi.org/10.1002/jmri.26174DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6221059PMC
November 2018

K-space trajectories in 3D-GRASE sequence for high resolution structural imaging.

Magn Reson Imaging 2018 05 8;48:10-19. Epub 2017 Dec 8.

Department of Radiology and Nuclear Medicine, Erasmus Medical Center, Rotterdam, The Netherlands.

Purpose: To propose and evaluate new k-space trajectories for 3D-GRASE to improve scan time over 3D-FSE/TSE for high resolution structural imaging.

Methods: Five different Cartesian k-space trajectories were developed and evaluated. They combine ideas of existing k-space trajectories for 3D-GRASE and 3D-FSE/TSE. T2 and T2* are linearly or radially modulated in k-space to achieve the desired contrast while including the autocalibration region needed for the parallel imaging reconstruction technique. Phase modulation among echoes was corrected in reconstruction to remove remaining artefacts. Simulation and in-vivo experiments on a 3T scanner were conducted to evaluate the performance of the different k-space trajectories.

Results: Two of the proposed k-space trajectories for high resolution structural imaging with 3D-GRASE obtained images comparable to 3D-FSE with lower specific absorption rate (PD/T2: 41%/75%) and shorter acquisition time (PD/T2: 27%/20%).

Conclusions: 3D-GRASE image quality strongly depends on the k-space trajectory. With an optimal trajectory, 3D-GRASE may be preferable over 3D-FSE/TSE for structural high-resolution MRI.
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http://dx.doi.org/10.1016/j.mri.2017.12.003DOI Listing
May 2018

Dynamic contrast-enhanced MRI of the patellar bone: How to quantify perfusion.

J Magn Reson Imaging 2018 03 14;47(3):848-858. Epub 2017 Jul 14.

Biomedical Imaging Group Rotterdam, Departments of Medical Informatics & Radiology, Erasmus MC, Rotterdam, The Netherlands.

Purpose: To identify the optimal combination of pharmacokinetic model and arterial input function (AIF) for quantitative analysis of blood perfusion in the patellar bone using dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI).

Materials And Methods: This method design study used a random subset of five control subjects from an Institutional Review Board (IRB)-approved case-control study into patellofemoral pain, scanned on a 3T MR system with a contrast-enhanced time-resolved imaging of contrast kinetics (TRICKS) sequence. We systematically investigated the reproducibility of pharmacokinetic parameters for all combinations of Orton and Parker AIF models with Tofts, Extended Tofts (ETofts), and Brix pharmacokinetic models. Furthermore, we evaluated if the AIF should use literature parameters, be subject-specific, or group-specific. Model selection was based on the goodness-of-fit and the coefficient of variation of the pharmacokinetic parameters inside the patella. This extends previous studies that were not focused on the patella and did not evaluate as many combinations of arterial and pharmacokinetic models.

Results: The vascular component in the ETofts model could not reliably be recovered (coefficient of variation [CV] of v >50%) and the Brix model parameters showed high variability of up to 20% for k across good AIF models. Compared to group-specific AIF, the subject-specific AIF's mostly had higher residual. The best reproducibility and goodness-of-fit were obtained by combining Tofts' pharmacokinetic model with the group-specific Parker AIF.

Conclusion: We identified several good combinations of pharmacokinetic models and AIF for quantitative analysis of perfusion in the patellar bone. The recommended combination is Tofts pharmacokinetic model combined with a group-specific Parker AIF model.

Level Of Evidence: 2 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2018;47:848-858.
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http://dx.doi.org/10.1002/jmri.25817DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5836942PMC
March 2018

Diffusion MRI microstructure models with in vivo human brain Connectome data: results from a multi-group comparison.

NMR Biomed 2017 Sep 23;30(9). Epub 2017 Jun 23.

Centre for Medical Image Computing, Department of Computer Science, University College London, UK.

A large number of mathematical models have been proposed to describe the measured signal in diffusion-weighted (DW) magnetic resonance imaging (MRI). However, model comparison to date focuses only on specific subclasses, e.g. compartment models or signal models, and little or no information is available in the literature on how performance varies among the different types of models. To address this deficiency, we organized the 'White Matter Modeling Challenge' during the International Symposium on Biomedical Imaging (ISBI) 2015 conference. This competition aimed to compare a range of different kinds of models in their ability to explain a large range of measurable in vivo DW human brain data. Specifically, we assessed the ability of models to predict the DW signal accurately for new diffusion gradients and b values. We did not evaluate the accuracy of estimated model parameters, as a ground truth is hard to obtain. We used the Connectome scanner at the Massachusetts General Hospital, using gradient strengths of up to 300 mT/m and a broad set of diffusion times. We focused on assessing the DW signal prediction in two regions: the genu in the corpus callosum, where the fibres are relatively straight and parallel, and the fornix, where the configuration of fibres is more complex. The challenge participants had access to three-quarters of the dataset and their models were ranked on their ability to predict the remaining unseen quarter of the data. The challenge provided a unique opportunity for a quantitative comparison of diverse methods from multiple groups worldwide. The comparison of the challenge entries reveals interesting trends that could potentially influence the next generation of diffusion-based quantitative MRI techniques. The first is that signal models do not necessarily outperform tissue models; in fact, of those tested, tissue models rank highest on average. The second is that assuming a non-Gaussian (rather than purely Gaussian) noise model provides little improvement in prediction of unseen data, although it is possible that this may still have a beneficial effect on estimated parameter values. The third is that preprocessing the training data, here by omitting signal outliers, and using signal-predicting strategies, such as bootstrapping or cross-validation, could benefit the model fitting. The analysis in this study provides a benchmark for other models and the data remain available to build up a more complete comparison in the future.
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http://dx.doi.org/10.1002/nbm.3734DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5563694PMC
September 2017

Classification of hemodynamically significant stenoses from dynamic CT perfusion and CTA myocardial territories.

Med Phys 2017 Apr 22;44(4):1347-1358. Epub 2017 Mar 22.

Department of Imaging Physics, TU Delft, 2628CJ, Delft, The Netherlands.

Purpose: Myocardial blood flow (MBF) obtained by dynamic CT perfusion (CTP) has been recently introduced to assess hemodynamic significance of coronary stenosis in coronary artery disease. The diagnostic performance of dynamic CTP MBF is limited due to subjective interpretation of MBF maps and MBF variations caused by physiological, methodological, and technical issues. In this paper, we introduce a novel method to quantify the hypoperfused volume (HPV) in myocardial territories derived from CT angiography (CTA) to overcome the limitations of current dynamic CTP MBF analysis methods.

Methods: The diagnostic performance of HPV in classifying significant stenoses was evaluated on 22 patients (57 vessels) that underwent CTA, CTP and invasive fractional flow reserve (FFR). FFR was used as the standard of reference to determine stenosis significance. The diagnostic performance was compared to that of the mean MBF computed in regions manually annotated by an expert (MA-MBF). HPV was derived by thresholding the MBF in myocardial territories constructed from CTA by locating the closest artery. Diagnostic performance was evaluated using leave-one-case out cross-validation. Inter-observer reproducibility was assessed by performing annotations of coronary seeds (HPV) and manual regions (MA-MBF) with two users. In addition, the influence of different parameter settings on the diagnostic performance of HPV was assessed.

Results: Leave-one-case out cross-validation showed that HPV has an accuracy of 72% (58-83%) with sensitivity of 72% (47-90%) and specificity of 72% (58-83%). The accuracy of MA-MBF was 70% (57-82%) with a sensitivity of 50% (26-74%) and a specificity of 79% (64-91%). The Spearman correlation and the kappa statistic was (ρ = 0.94, κ = 0.86) for HPV and (ρ = 0.72, κ = 0.82) for MA-MBF. The influence of parameter settings on HPV based diagnostic performance was not significant.

Conclusions: The proposed HPV accurately classifies hemodynamically significant stenoses with a level of accuracy comparable to the mean MBF in regions annotated by an expert. HPV improves inter-observer reproducibility as compared to MA-MBF by providing a more objective criterion to associate the stenotic coronary with the supplied myocardial territory.
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http://dx.doi.org/10.1002/mp.12126DOI Listing
April 2017

Reliable Dual Tensor Model Estimation in Single and Crossing Fibers Based on Jeffreys Prior.

PLoS One 2016 19;11(10):e0164336. Epub 2016 Oct 19.

Quantitative Imaging Group, Department of Imaging Physics, Delft University of Technology, 2628CJ Delft, The Netherlands.

Purpose: This paper presents and studies a framework for reliable modeling of diffusion MRI using a data-acquisition adaptive prior.

Methods: Automated relevance determination estimates the mean of the posterior distribution of a rank-2 dual tensor model exploiting Jeffreys prior (JARD). This data-acquisition prior is based on the Fisher information matrix and enables the assessment whether two tensors are mandatory to describe the data. The method is compared to Maximum Likelihood Estimation (MLE) of the dual tensor model and to FSL's ball-and-stick approach.

Results: Monte Carlo experiments demonstrated that JARD's volume fractions correlated well with the ground truth for single and crossing fiber configurations. In single fiber configurations JARD automatically reduced the volume fraction of one compartment to (almost) zero. The variance in fractional anisotropy (FA) of the main tensor component was thereby reduced compared to MLE. JARD and MLE gave a comparable outcome in data simulating crossing fibers. On brain data, JARD yielded a smaller spread in FA along the corpus callosum compared to MLE. Tract-based spatial statistics demonstrated a higher sensitivity in detecting age-related white matter atrophy using JARD compared to both MLE and the ball-and-stick approach.

Conclusions: The proposed framework offers accurate and precise estimation of diffusion properties in single and dual fiber regions.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0164336PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5070879PMC
June 2017

Stochastic optimization with randomized smoothing for image registration.

Med Image Anal 2017 01 6;35:146-158. Epub 2016 Jul 6.

Biomedical Imaging Group Rotterdam, Departments of Radiology and Medical Informatics, Erasmus MC, Rotterdam, The Netherlands.

Image registration is typically formulated as an optimization process, which aims to find the optimal transformation parameters of a given transformation model by minimizing a cost function. Local minima may exist in the optimization landscape, which could hamper the optimization process. To eliminate local minima, smoothing the cost function would be desirable. In this paper, we investigate the use of a randomized smoothing (RS) technique for stochastic gradient descent (SGD) optimization, to effectively smooth the cost function. In this approach, Gaussian noise is added to the transformation parameters prior to computing the cost function gradient in each iteration of the SGD optimizer. The approach is suitable for both rigid and nonrigid registrations. Experiments on synthetic images, cell images, public CT lung data, and public MR brain data demonstrate the effectiveness of the novel RS technique in terms of registration accuracy and robustness.
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http://dx.doi.org/10.1016/j.media.2016.07.003DOI Listing
January 2017

Super-resolution T estimation: Quantitative high resolution T mapping from a set of low resolution T -weighted images with different slice orientations.

Magn Reson Med 2017 05 1;77(5):1818-1830. Epub 2016 Jul 1.

iMinds-Vision Lab, Department of Physics, University of Antwerp, Antwerp, Belgium.

Purpose: Quantitative T mapping is a magnetic resonance imaging technique that estimates the spin-lattice relaxation time of tissues. Even though T mapping has a broad range of potential applications, it is not routinely used in clinical practice as accurate and precise high resolution T mapping requires infeasibly long acquisition times.

Method: To improve the trade-off between the acquisition time, signal-to-noise ratio and spatial resolution, we acquire a set of low resolution T -weighted images and directly estimate a high resolution T map by means of super-resolution reconstruction.

Results: Simulation and in vivo experiments show an increased spatial resolution of the T map, while preserving a high signal-to-noise ratio and short scan time. Moreover, the proposed method outperforms conventional estimation in terms of root-mean-square error.

Conclusion: Super resolution T estimation enables resolution enhancement in T mapping with the use of standard (inversion recovery) T acquisition sequences. Magn Reson Med 77:1818-1830, 2017. © 2016 International Society for Magnetic Resonance in Medicine.
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http://dx.doi.org/10.1002/mrm.26262DOI Listing
May 2017

Estimation of diffusion properties in three-way fiber crossings without overfitting.

Phys Med Biol 2015 Dec 12;60(23):9123-44. Epub 2015 Nov 12.

Quantitative Imaging Group, Department of Imaging Physics, Delft University of Technology, The Netherlands. Department of Radiology, Academic Medical Center, Amsterdam, The Netherlands.

Diffusion-weighted magnetic resonance imaging permits assessment of the structural integrity of the brain's white matter. This requires unbiased and precise quantification of diffusion properties. We aim to estimate such properties in simple and complex fiber geometries up to three-way fiber crossings using rank-2 tensor model selection. A maximum a-posteriori (MAP) estimator is employed to determine the parameters of a constrained triple tensor model. A prior is imposed on the parameters to avoid the degeneracy of the model estimation. This prior maximizes the divergence between the three tensor's principal orientations. A new model selection approach quantifies the extent to which the candidate models are appropriate, i.e. a single-, dual- or triple-tensor model. The model selection precludes overfitting to the data. It is based on the goodness of fit and information complexity measured by the total Kullback-Leibler divergence (ICOMP-TKLD). The proposed framework is compared to maximum likelihood estimation on phantom data of three-way fiber crossings. It is also compared to the ball-and-stick approach from the FMRIB Software Library (FSL) on experimental data. The spread in the estimated parameters reduces significantly due to the prior. The fractional anisotropy (FA) could be precisely estimated with MAP down to an angle of approximately 40° between the three fibers. Furthermore, volume fractions between 0.2 and 0.8 could be reliably estimated. The configurations inferred by our method corresponded to the anticipated neuro-anatomy both in single fibers and in three-way fiber crossings. The main difference with FSL was in single fiber regions. Here, ICOMP-TKLD predominantly inferred a single fiber configuration, as preferred, whereas FSL mostly selected dual or triple order ball-and-stick models. The prior of our MAP estimator enhances the precision of the parameter estimation, without introducing a bias. Additionally, our model selection effectively balances the trade-off between the goodness of fit and information complexity. The proposed framework can enhance the sensitivity of statistical analysis of diffusion tensor MRI.
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http://dx.doi.org/10.1088/0031-9155/60/23/9123DOI Listing
December 2015

Three-dimensional quantitative T1 and T2 mapping of the carotid artery: Sequence design and in vivo feasibility.

Magn Reson Med 2016 Mar 28;75(3):1008-17. Epub 2015 Apr 28.

Department of Radiology, Academic Medical Center, Amsterdam, the Netherlands.

Purpose: A novel three-dimensional (3D) T1 and T2 mapping protocol for the carotid artery is presented.

Methods: A 3D black-blood imaging sequence was adapted allowing carotid T1 and T2 mapping using multiple flip angles and echo time (TE) preparation times. B1 mapping was performed to correct for spatially varying deviations from the nominal flip angle. The protocol was optimized using simulations and phantom experiments. In vivo scans were performed on six healthy volunteers in two sessions, and in a patient with advanced atherosclerosis. Compensation for patient motion was achieved by 3D registration of the inter/intrasession scans. Subsequently, T1 and T2 maps were obtained by maximum likelihood estimation.

Results: Simulations and phantom experiments showed that the bias in T1 and T2 estimation was < 10% within the range of physiological values. In vivo T1 and T2 values for carotid vessel wall were 844 ± 96 and 39 ± 5 ms, with good repeatability across scans. Patient data revealed altered T1 and T2 values in regions of atherosclerotic plaque.

Conclusion: The 3D T1 and T2 mapping of the carotid artery is feasible using variable flip angle and variable TE preparation acquisitions. We foresee application of this technique for plaque characterization and monitoring plaque progression in atherosclerotic patients.
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http://dx.doi.org/10.1002/mrm.25634DOI Listing
March 2016

Super-resolution reconstruction of diffusion parameters from diffusion-weighted images with different slice orientations.

Magn Reson Med 2016 Jan 22;75(1):181-95. Epub 2015 Jan 22.

iMinds-Vision Lab, Department of Physics, University of Antwerp, Antwerp, Belgium.

Purpose: Diffusion MRI is hampered by long acquisition times, low spatial resolution, and a low signal-to-noise ratio. Recently, methods have been proposed to improve the trade-off between spatial resolution, signal-to-noise ratio, and acquisition time of diffusion-weighted images via super-resolution reconstruction (SRR) techniques. However, during the reconstruction, these SRR methods neglect the q-space relation between the different diffusion-weighted images.

Method: An SRR method that includes a diffusion model and directly reconstructs high resolution diffusion parameters from a set of low resolution diffusion-weighted images was proposed. Our method allows an arbitrary combination of diffusion gradient directions and slice orientations for the low resolution diffusion-weighted images, optimally samples the q- and k-space, and performs motion correction with b-matrix rotation.

Results: Experiments with synthetic data and in vivo human brain data show an increase of spatial resolution of the diffusion parameters, while preserving a high signal-to-noise ratio and low scan time. Moreover, the proposed SRR method outperforms the previous methods in terms of the root-mean-square error.

Conclusion: The proposed SRR method substantially increases the spatial resolution of MRI that can be obtained in a clinically feasible scan time.
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http://dx.doi.org/10.1002/mrm.25597DOI Listing
January 2016

Detecting statistically significant differences in quantitative MRI experiments, applied to diffusion tensor imaging.

IEEE Trans Med Imaging 2015 May 18;34(5):1164-76. Epub 2014 Dec 18.

In this work we present a framework for reliably detecting significant differences in quantitative magnetic resonance imaging and evaluate it with diffusion tensor imaging (DTI) experiments. As part of this framework we propose a new spatially regularized maximum likelihood estimator that simultaneously estimates the quantitative parameters and the spatially-smoothly-varying noise level from the acquisitions. The noise level estimation method does not require repeated acquisitions. We show that the amount of regularization in this method can be set a priori to achieve a desired coefficient of variation of the estimated noise level. The noise level estimate allows the construction of a Cramér-Rao-lower-bound based test statistic that reliably assesses the significance of differences between voxels within a scan or across different scans. We show that the regularized noise level estimate improves upon existing methods and results in a substantially increased precision of the uncertainty estimates of the DTI parameters. It enables correct specification of the null distribution of the test statistic and with it the test statistic obtains the highest sensitivity and specificity. The source code of the estimation framework, test statistic and experiment scripts are made available to the community.
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http://dx.doi.org/10.1109/TMI.2014.2380830DOI Listing
May 2015

Influence of image registration on apparent diffusion coefficient images computed from free-breathing diffusion MR images of the abdomen.

J Magn Reson Imaging 2015 Aug 19;42(2):315-30. Epub 2014 Nov 19.

Biomedical Imaging Group Rotterdam, Departments of Medical Informatics and Radiology, Erasmus MC - University Medical Center Rotterdam, the Netherlands.

Background: To evaluate the influence of image registration on apparent diffusion coefficient (ADC) images obtained from abdominal free-breathing diffusion-weighted MR images (DW-MRIs).

Methods: A comprehensive pipeline based on automatic three-dimensional nonrigid image registrations is developed to compensate for misalignments in DW-MRI datasets obtained from five healthy subjects scanned twice. Motion is corrected both within each image and between images in a time series. ADC distributions are compared with and without registration in two abdominal volumes of interest (VOIs). The effects of interpolations and Gaussian blurring as alternative strategies to reduce motion artifacts are also investigated.

Results: Among the four considered scenarios (no processing, interpolation, blurring and registration), registration yields the best alignment scores. Median ADCs vary according to the chosen scenario: for the considered datasets, ADCs obtained without processing are 30% higher than with registration. Registration improves voxelwise reproducibility at least by a factor of 2 and decreases uncertainty (Fréchet-Cramér-Rao lower bound). Registration provides similar improvements in reproducibility and uncertainty as acquiring four times more data.

Conclusion: Patient motion during image acquisition leads to misaligned DW-MRIs and inaccurate ADCs, which can be addressed using automatic registration.
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http://dx.doi.org/10.1002/jmri.24792DOI Listing
August 2015

Interactive local super-resolution reconstruction of whole-body MRI mouse data: a pilot study with applications to bone and kidney metastases.

PLoS One 2014 29;9(9):e108730. Epub 2014 Sep 29.

Department of Radiology, Leiden University Medical Center, Leiden, the Netherlands; Department of Intelligent Systems, Delft University of Technology, Delft, the Netherlands.

In small animal imaging studies, when the locations of the micro-structures of interest are unknown a priori, there is a simultaneous need for full-body coverage and high resolution. In MRI, additional requirements to image contrast and acquisition time will often make it impossible to acquire such images directly. Recently, a resolution enhancing post-processing technique called super-resolution reconstruction (SRR) has been demonstrated to improve visualization and localization of micro-structures in small animal MRI by combining multiple low-resolution acquisitions. However, when the field-of-view is large relative to the desired voxel size, solving the SRR problem becomes very expensive, in terms of both memory requirements and computation time. In this paper we introduce a novel local approach to SRR that aims to overcome the computational problems and allow researchers to efficiently explore both global and local characteristics in whole-body small animal MRI. The method integrates state-of-the-art image processing techniques from the areas of articulated atlas-based segmentation, planar reformation, and SRR. A proof-of-concept is provided with two case studies involving CT, BLI, and MRI data of bone and kidney tumors in a mouse model. We show that local SRR-MRI is a computationally efficient complementary imaging modality for the precise characterization of tumor metastases, and that the method provides a feasible high-resolution alternative to conventional MRI.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0108730PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4181866PMC
September 2015

Super-resolution reconstruction of late gadolinium-enhanced MRI for improved myocardial scar assessment.

J Magn Reson Imaging 2015 Jul 19;42(1):160-7. Epub 2014 Sep 19.

Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands.

Purpose: To develop and validate a method for improving image resolution of late gadolinium-enhanced (LGE) magnetic resonance imaging (MRI) for accurate assessment of myocardial scar.

Materials And Methods: In a cohort of 37 postinfarction patients, LGE was performed prior to ventricular tachycardia catheter ablation therapy at 1.5T. A super-resolution reconstruction (SRR) technique was applied to the three anisotropic views: short-axis (SA), two-chamber, and four-chamber, to reconstruct a single isotropic volume. For compensation of the interscan heart motion, a joint localized gradient-correlation-based scheme was developed. Scar was identified as either core or gray zone in both the SRR and original SA volumes, and evaluated based on the clinically established bipolar voltage range of the in vivo electroanatomical voltage mapping (EAVM).

Results: Compared to the SA volume, the SRR method resulted in significantly (P < 0.05) reduced myocardial scar gray zone sizes (10.5 ± 8.8 g vs. 9.2 ± 8.1 g) and improved agreement of the bipolar voltage range of scar gray zone (0.99 ± 0.65 mV vs. 1.46 ± 1.15 mV).

Conclusion: We propose an SRR method to automatically reconstruct a high-quality isotropic LGE volume from three orthogonal views. Analysis of the in vivo EAVM demonstrated improved myocardial scar assessment from the SRR volume compared with the SA LGE alone.
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http://dx.doi.org/10.1002/jmri.24759DOI Listing
July 2015

Three-dimensional inversion recovery manganese-enhanced MRI of mouse brain using super-resolution reconstruction to visualize nuclei involved in higher brain function.

NMR Biomed 2014 Jul 10;27(7):749-59. Epub 2014 May 10.

C. J. Gorter Center for High Field MRI, Department of Radiology, Leiden University Medical Center, Leiden, the Netherlands.

The visualization of activity in mouse brain using inversion recovery spin echo (IR-SE) manganese-enhanced MRI (MEMRI) provides unique contrast, but suffers from poor resolution in the slice-encoding direction. Super-resolution reconstruction (SRR) is a resolution-enhancing post-processing technique in which multiple low-resolution slice stacks are combined into a single volume of high isotropic resolution using computational methods. In this study, we investigated, first, whether SRR can improve the three-dimensional resolution of IR-SE MEMRI in the slice selection direction, whilst maintaining or improving the contrast-to-noise ratio of the two-dimensional slice stacks. Second, the contrast-to-noise ratio of SRR IR-SE MEMRI was compared with a conventional three-dimensional gradient echo (GE) acquisition. Quantitative experiments were performed on a phantom containing compartments of various manganese concentrations. The results showed that, with comparable scan times, the signal-to-noise ratio of three-dimensional GE acquisition is higher than that of SRR IR-SE MEMRI. However, the contrast-to-noise ratio between different compartments can be superior with SRR IR-SE MEMRI, depending on the chosen inversion time. In vivo experiments were performed in mice receiving manganese using an implanted osmotic pump. The results showed that SRR works well as a resolution-enhancing technique in IR-SE MEMRI experiments. In addition, the SRR image also shows a number of brain structures that are more clearly discernible from the surrounding tissues than in three-dimensional GE acquisition, including a number of nuclei with specific higher brain functions, such as memory, stress, anxiety and reward behavior.
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http://dx.doi.org/10.1002/nbm.3108DOI Listing
July 2014

Improved myocardial scar characterization by super-resolution reconstruction in late gadolinium enhanced MRI.

Med Image Comput Comput Assist Interv 2013 ;16(Pt 3):147-54

Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands.

Image resolution is an important factor for accurate myocardial scar assessment from late gadolinium enhanced (LGE) MR. It has been shown that the conventionally used short-axis (SA) LGE acquisition with anisotropic resolution may overestimate the scar size due to partial volume effect, undermining the prognostic and diagnostic accuracy of LGE MRI in critical clinical applications. In this work, we present a method for combining three complementary anisotropic orthogonal LGE sequences of the heart region into a single isotropic volume. Our algorithm is based on the super-resolution reconstruction technique and employs joint localized gradient-correlation-based technique for compensation of breathing motion. The proposed method was validated on the gold standard electroanatomical voltage mapping (EAVM) data of 15 post-infarction patients. The reconstructed myocardial scar image demonstrated improved agreement with the EAVM compared to the conventional SA image, especially at the clinically significant gray zone region.
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http://dx.doi.org/10.1007/978-3-642-40760-4_19DOI Listing
February 2014
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