PCA-based groupwise image registration for quantitative MRI

Huizinga, Wyke; Poot, Dirk H. J.; Guyader, Jean-Marie; Klaassen, Remy; Coolen, Bram F.; Kranenburg, Matthijs van; Geuns, Robert Jan M. van; Uitterdijk, André; Polfliet, Mathias; Vandemeulebroucke, Jef; Leemans, Alexander; Niessen, Wiro J.; Klein, Stefan

doi:10.1016/j.media.2015.12.004

Cited by 125 publications

(176 citation statements)

References 36 publications

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“…The groupwise registration method assumes that the intensity changes due to contrast can be described as a low dimensional signal model without prior knowledge of this model (Hamy et al [2014], Melbourne et al [2007], Huizinga et al [2016]). The method separates the intensity changes due to contrast from motion and registers all images simultaneously to a common space by minimizing a cost function based on PCA.…”

Section: Groupwise Registrationmentioning

confidence: 99%

“…In order to maximize the highest eigenvalues, and impose more alignment in the DCE-MRI series, this cost function is minimized (Huizinga et al [2016]). …”

Section: Groupwise Registrationmentioning

confidence: 99%

“…A potential downside is that pharmacokinetic modelling requires a high temporal resolution (Henderson et al [1998]). Another possible disadvantage is that a model could be corrupted by noise, or acquisition artefacts, leading to inappropriate model fits and thus misregistration (Melbourne et al [2007], Huizinga et al [2016]). Some registration methods apply data reduction techniques, such as principle component analysis (PCA) or independent component analysis (ICA), to separate motion from contrast induced intensity changes.…”

Section: Introductionmentioning

confidence: 99%

“…A true groupwise registration method would apply the cost function on the 4D image and aligns the images without the use of a reference image. Such a method is proposed by Huizinga et al [2016] and this PCA-based method will be validated on a clinical data set with a low temporal resolution (16 time points in 5 minutes).…”

Section: Introductionmentioning

confidence: 99%

“…In this study, clinical data sets were used to compare a conventional pairwise registration approach, using MI as metric, with the PCA-based groupwise registration method (Huizinga et al [2016]). The two methods were compared based on quantitative evaluation methods as well as on the visual quality of the subtraction images, providing a good evaluation for clinical application.…”

Section: Introductionmentioning

confidence: 99%

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Evaluation of motion correction for clinical dynamic contrast enhanced MRI of the liver

et al. 2017

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Abstract. Motion correction of 4D dynamic contrast enhanced MRI (DCE-MRI) series is required for diagnostic evaluation of liver lesions. The registration, however, is a challenging task, owing to rapid changes in image appearance. In this study, two different registration approaches are compared; a conventional pairwise method applying mutual information as metric and a groupwise method applying a principal component analysis based metric, introduced by Huizinga et al. [2016]. The pairwise method transforms the individual 3D images one by one to a reference image, whereas the groupwise registration method computes the metric on all the images simultaneously, exploiting the temporal information, and transforms all 3D images to a common space. The performance of the two registration methods was evaluated using 70 clinical 4D DCE-MRI series with the focus on the liver. The evaluation was based on the smoothness of the time intensity curves in lesions, lesion volume change after deformation and the smoothness of spatial deformation. Furthermore, the visual quality of subtraction images (pre-contrast image subtracted from the post contrast images) before and after registration was rated by two observers. Both registration methods improved the alignment of the DCE-MRI images in comparison to the non-corrected series. Furthermore, the groupwise method achieved better temporal alignment with smoother spatial deformations than the pairwise method. The quality of the subtraction images was graded satisfactory in 32% of the cases without registration and in 77% and 80% of the cases after pairwise and groupwise registration, respectively. In conclusion, the groupwise registration method outperforms the pairwise registration method and achieves clinically satisfying results. Registration leads to improved subtraction images.

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Section: Groupwise Registrationmentioning

confidence: 99%

“…In order to maximize the highest eigenvalues, and impose more alignment in the DCE-MRI series, this cost function is minimized (Huizinga et al [2016]). …”

Section: Groupwise Registrationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Evaluation of motion correction for clinical dynamic contrast enhanced MRI of the liver

et al. 2017

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Dual‐input tracer kinetic modeling of dynamic contrast‐enhanced MRI in thoracic malignancies

Lee

Rimner

Deasy

et al. 2019

J Applied Clin Med Phys

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Pulmonary perfusion with dynamic contrast‐enhanced (DCE‐) MRI is typically assessed using a single‐input tracer kinetic model. Preliminary studies based on perfusion CT are indicating that dual‐input perfusion modeling of lung tumors may be clinically valuable as lung tumors have a dual blood supply from the pulmonary and aortic system. This study aimed to investigate the feasibility of fitting dual‐input tracer kinetic models to DCE‐MRI datasets of thoracic malignancies, including malignant pleural mesothelioma (MPM) and nonsmall cell lung cancer (NSCLC), by comparing them to single‐input (pulmonary or systemic arterial input) tracer kinetic models for the voxel‐level analysis within the tumor with respect to goodness‐of‐fit statistics. Fifteen patients (five MPM, ten NSCLC) underwent DCE‐MRI prior to radiotherapy. DCE‐MRI data were analyzed using five different single‐ or dual‐input tracer kinetic models: Tofts‐Kety (TK), extended TK (ETK), two compartment exchange (2CX), adiabatic approximation to the tissue homogeneity (AATH) and distributed parameter (DP) models. The pulmonary blood flow (BF), blood volume (BV), mean transit time (MTT), permeability‐surface area product (PS), fractional interstitial volume (v I), and volume transfer constant (K Trans) were calculated for both single‐ and dual‐input models. The pulmonary arterial flow fraction (γ), pulmonary arterial blood flow (BFPA) and systemic arterial blood flow (BFA) were additionally calculated for only dual‐input models. The competing models were ranked and their Akaike weights were calculated for each voxel according to corrected Akaike information criterion (cAIC). The optimal model was chosen based on the lowest cAIC value. In both types of tumors, all five dual‐input models yielded lower cAIC values than their corresponding single‐input models. The 2CX model was the best‐fitted model and most optimal in describing tracer kinetic behavior to assess microvascular properties in both MPM and NSCLC. The dual‐input 2CX‐model‐derived BFA was the most significant parameter in differentiating adenocarcinoma from squamous cell carcinoma histology for NSCLC patients.

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Lower cerebral blood flow predicts cognitive decline in patients with vascular cognitive impairment

Dinther

Hooghiemstra

Bron

et al. 2023

Alzheimer's & Dementia

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INTRODUCTIONChronic cerebral hypoperfusion is one of the assumed pathophysiological mechanisms underlying vascular cognitive impairment (VCI). We investigated the association between baseline cerebral blood flow (CBF) and cognitive decline after 2 years in patients with VCI and reference participants.METHODSOne hundred eighty‐one participants (mean age 66.3 ± 7.4 years, 43.6% women) underwent arterial spin labeling (ASL) magnetic resonance imaging (MRI) and neuropsychological assessment at baseline and at 2‐year follow‐up. We determined the association between baseline global and lobar CBF and cognitive decline with multivariable regression analysis.RESULTSLower global CBF at baseline was associated with more global cognitive decline in VCI and reference participants. This association was most profound in the domain of attention/psychomotor speed. Lower temporal and frontal CBF at baseline were associated with more cognitive decline in memory.DISCUSSIONOur study supports the role of hypoperfusion in the pathophysiological and clinical progression of VCI.Highlights Impaired cerebral blood flow (CBF) at baseline is associated with faster cognitive decline in VCI and normal aging. Our results suggest that low CBF precedes and contributes to the development of vascular cognitive impairment. CBF determined by ASL might be used as a biomarker to monitor disease progression or treatment responses in VCI.

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PCA-based groupwise image registration for quantitative MRI

Cited by 125 publications

References 36 publications

Evaluation of motion correction for clinical dynamic contrast enhanced MRI of the liver

Evaluation of motion correction for clinical dynamic contrast enhanced MRI of the liver

Dual‐input tracer kinetic modeling of dynamic contrast‐enhanced MRI in thoracic malignancies

Lower cerebral blood flow predicts cognitive decline in patients with vascular cognitive impairment

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