Effects of Acquisition Parameter Modifications and Field Strength on the Reproducibility of Brain Perfusion Measurements Using Arterial Spin-Labeling

Baas, Koen P.A.; Petr, Jan; Kuijer, Joost P.A.; Nederveen, Aart J.; Mutsaerts, Henk‐Jan; Ven, K.C.C. van de

doi:10.3174/ajnr.a6856

Cited by 11 publications

(13 citation statements)

References 32 publications

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“…To improve both model prediction accuracy, generalisability, and repeatability, future efforts could be aimed at increasing the sample size by including multiple (longitudinal) cohorts. Although measurement reproducibility of ASL MRI is high (Baas et al, 2021 ; Mutsaerts et al, 2015 ), care should be taken when combining multiple cohorts differing in MRI vendor or ASL sequence parameters in order to maintain high reproducibility in brain age prediction.…”

Section: Discussionmentioning

confidence: 99%

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The value of arterial spin labelling perfusion MRI in brain age prediction

Dijsselhof

Barboure

Stritt

et al. 2023

Human Brain Mapping

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Current structural MRI‐based brain age estimates and their difference from chronological age—the brain age gap (BAG)—are limited to late‐stage pathological brain‐tissue changes. The addition of physiological MRI features may detect early‐stage pathological brain alterations and improve brain age prediction. This study investigated the optimal combination of structural and physiological arterial spin labelling (ASL) image features and algorithms. Healthy participants (n = 341, age 59.7 ± 14.8 years) were scanned at baseline and after 1.7 ± 0.5 years follow‐up (n = 248, mean age 62.4 ± 13.3 years). From 3 T MRI, structural (T1w and FLAIR) volumetric ROI and physiological (ASL) cerebral blood flow (CBF) and spatial coefficient of variation ROI features were constructed. Multiple combinations of features and machine learning algorithms were evaluated using the Mean Absolute Error (MAE). From the best model, longitudinal BAG repeatability and feature importance were assessed. The ElasticNetCV algorithm using T1w + FLAIR+ASL performed best (MAE = 5.0 ± 0.3 years), and better compared with using T1w + FLAIR (MAE = 6.0 ± 0.4 years, p < .01). The three most important features were, in descending order, GM CBF, GM/ICV, and WM CBF. Average baseline and follow‐up BAGs were similar (−1.5 ± 6.3 and − 1.1 ± 6.4 years respectively, ICC = 0.85, 95% CI: 0.8–0.9, p = .16). The addition of ASL features to structural brain age, combined with the ElasticNetCV algorithm, improved brain age prediction the most, and performed best in a cross‐sectional and repeatability comparison. These findings encourage future studies to explore the value of ASL in brain age in various pathologies.

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Section: Discussionmentioning

confidence: 99%

“…Although measurement reproducibility of ASL MRI is high (Baas et al, 2021;Mutsaerts et al, 2015), care should be taken when combining multiple cohorts differing in MRI vendor or ASL sequence parameters in order to maintain high reproducibility in brain age prediction.…”

Section: Limitations and Future Directionsmentioning

confidence: 99%

The value of arterial spin labelling perfusion MRI in brain age prediction

Dijsselhof

Barboure

Stritt

et al. 2023

Human Brain Mapping

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“…However, the consensus paper did not take tumor studies into key account, nor does it discuss peculiarities of tumor ASL imaging, which may influence the optimal application of ASL in tumor imaging under the recommended conditions. Several studies have assessed the test-retest repeatability of ASL CBF measurements, including the recommended single-delay pCASL implementation ( 114 , 115 ) but also more complex protocols ( 116 , 117 ). A reproducibility study has been performed for ASL CBF measurements obtained with commercial implementations of ASL across from major MRI vendors ( 118 ).…”

Section: Resultsmentioning

confidence: 99%

High-Grade Glioma Treatment Response Monitoring Biomarkers: A Position Statement on the Evidence Supporting the Use of Advanced MRI Techniques in the Clinic, and the Latest Bench-to-Bedside Developments. Part 1: Perfusion and Diffusion Techniques

et al. 2022

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ObjectiveSummarize evidence for use of advanced MRI techniques as monitoring biomarkers in the clinic, and highlight the latest bench-to-bedside developments.MethodsExperts in advanced MRI techniques applied to high-grade glioma treatment response assessment convened through a European framework. Current evidence regarding the potential for monitoring biomarkers in adult high-grade glioma is reviewed, and individual modalities of perfusion, permeability, and microstructure imaging are discussed (in Part 1 of two). In Part 2, we discuss modalities related to metabolism and/or chemical composition, appraise the clinic readiness of the individual modalities, and consider post-processing methodologies involving the combination of MRI approaches (multiparametric imaging) or machine learning (radiomics).ResultsHigh-grade glioma vasculature exhibits increased perfusion, blood volume, and permeability compared with normal brain tissue. Measures of cerebral blood volume derived from dynamic susceptibility contrast-enhanced MRI have consistently provided information about brain tumor growth and response to treatment; it is the most clinically validated advanced technique. Clinical studies have proven the potential of dynamic contrast-enhanced MRI for distinguishing post-treatment related effects from recurrence, but the optimal acquisition protocol, mode of analysis, parameter of highest diagnostic value, and optimal cut-off points remain to be established. Arterial spin labeling techniques do not require the injection of a contrast agent, and repeated measurements of cerebral blood flow can be performed. The absence of potential gadolinium deposition effects allows widespread use in pediatric patients and those with impaired renal function. More data are necessary to establish clinical validity as monitoring biomarkers. Diffusion-weighted imaging, apparent diffusion coefficient analysis, diffusion tensor or kurtosis imaging, intravoxel incoherent motion, and other microstructural modeling approaches also allow treatment response assessment; more robust data are required to validate these alone or when applied to post-processing methodologies.ConclusionConsiderable progress has been made in the development of these monitoring biomarkers. Many techniques are in their infancy, whereas others have generated a larger body of evidence for clinical application.

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“…99m Tc-HMPAO SPECT repeatability of absolute flow on rescan was 15.0 ± 1.5% [ 58 ]. Very good repeatability of CBV, K trans , and CBF, respectively, was reported for DSC (3–11%) [ 59 ], DCE (7.7%) [ 60 ] and ASL (6.6–14.8%) [ 30 ]. These, however, greatly depend on the used parameters, sequence implementation, or models used for quantification and can vary substantially between studies [ 61 , 62 ].…”

Section: Resultsmentioning

confidence: 99%

“…ASL perfusion MRI addresses most of these issues as it is non-invasive using magnetically labeled blood as an endogenous tracer. ASL is fully quantitative with accuracy and reproducibility [30] comparable to 15 O-H 2 O-PET [31]. One disadvantage of ASL is its limited SNR and low sensitivity in regions with low CBF such as the white matter.…”

Section: Perfusion Imagingmentioning

confidence: 99%

A systematic review on the use of quantitative imaging to detect cancer therapy adverse effects in normal-appearing brain tissue

Petr

Hogeboom

Nikulin

et al. 2021

Magn Reson Mater Phy

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Cancer therapy for both central nervous system (CNS) and non-CNS tumors has been previously associated with transient and long-term cognitive deterioration, commonly referred to as ‘chemo fog’. This therapy-related damage to otherwise normal-appearing brain tissue is reported using post-mortem neuropathological analysis. Although the literature on monitoring therapy effects on structural magnetic resonance imaging (MRI) is well established, such macroscopic structural changes appear relatively late and irreversible. Early quantitative MRI biomarkers of therapy-induced damage would potentially permit taking these treatment side effects into account, paving the way towards a more personalized treatment planning.This systematic review (PROSPERO number 224196) provides an overview of quantitative tomographic imaging methods, potentially identifying the adverse side effects of cancer therapy in normal-appearing brain tissue. Seventy studies were obtained from the MEDLINE and Web of Science databases. Studies reporting changes in normal-appearing brain tissue using MRI, PET, or SPECT quantitative biomarkers, related to radio-, chemo-, immuno-, or hormone therapy for any kind of solid, cystic, or liquid tumor were included. The main findings of the reviewed studies were summarized, providing also the risk of bias of each study assessed using a modified QUADAS-2 tool. For each imaging method, this review provides the methodological background, and the benefits and shortcomings of each method from the imaging perspective. Finally, a set of recommendations is proposed to support future research.

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Effects of Acquisition Parameter Modifications and Field Strength on the Reproducibility of Brain Perfusion Measurements Using Arterial Spin-Labeling

Cited by 11 publications

References 32 publications

The value of arterial spin labelling perfusion MRI in brain age prediction

The value of arterial spin labelling perfusion MRI in brain age prediction

High-Grade Glioma Treatment Response Monitoring Biomarkers: A Position Statement on the Evidence Supporting the Use of Advanced MRI Techniques in the Clinic, and the Latest Bench-to-Bedside Developments. Part 1: Perfusion and Diffusion Techniques

A systematic review on the use of quantitative imaging to detect cancer therapy adverse effects in normal-appearing brain tissue

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