Pulseq‐CEST: Towards multi‐site multi‐vendor compatibility and reproducibility of CEST experiments using an open‐source sequence standard

Herz, K; Mueller, Sebastian; Perlman, Or; Zaitsev, Maxim; Knutsson, Linda; Sun, Phillip Zhe; Zhou, Jinyuan; Zijl, Peter van; Heinecke, Kerstin; Schuenke, Patrick; Farrar, Christian T.; Schmidt, Manuel; Dörfler, Arnd; Scheffler, Klaus; Zaiß, Moritz

doi:10.1002/mrm.28825

Cited by 41 publications

(57 citation statements)

References 53 publications

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“…In particular, an elevated semi‐solid volume fraction was observed for the subcortical WM (19.80% ± 0.50%) compared to the GM (12.77% ± 0.75%), allowing a clear identification of the corpus callosum and white matter fiber tracts. The obtained values were in good agreement with previous literature reports 51,52 . The semi‐solid chemical exchange rate was faster in the GM (56.54 ± 3.1 Hz) compared to WM (43.87 ± 2.36 Hz), in agreement with the literature 24,52,53 …”

Section: Resultssupporting

confidence: 92%

An end‐to‐end AI‐based framework for automated discovery of rapid CEST/MT MRI acquisition protocols and molecular parameter quantification (AutoCEST)

Perlman

Zhu

Zaiß

et al. 2022

Magnetic Resonance in Med

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To develop an automated machine-learning-based method for the discovery of rapid and quantitative chemical exchange saturation transfer (CEST) MR fingerprinting acquisition and reconstruction protocols.Methods: An MR physics-governed AI system was trained to generate optimized acquisition schedules and the corresponding quantitative reconstruction neural network. The system (termed AutoCEST) is composed of a CEST saturation block, a spin dynamics module, and a deep reconstruction network, all differentiable and jointly connected. The method was validated using a variety of chemical exchange phantoms and in vivo mouse brains at 9.4T. Results:The acquisition times for AutoCEST optimized schedules ranged from 35 to 71 s, with a quantitative image reconstruction time of only 29 ms. The resulting exchangeable proton concentration maps for the phantoms were in good agreement with the known solute concentrations for AutoCEST sequences (mean absolute error = 2.42 mM; Pearson's r = 0.992, p < 0.0001), but not for an unoptimized sequence (mean absolute error = 65.19 mM; Pearson's r = − 0.161, p = 0.522). Similarly, improved exchange rate agreement was observed between AutoCEST and quantification of exchange using saturation power (QUESP) methods (mean absolute error: 35.8 Hz, Pearson's r = 0.971, p < 0.0001) compared to an unoptimized schedule and QUESP (mean absolute error = 58.2 Hz; Pearson's r = 0.959, p < 0.0001). The AutoCEST in vivo mouse brain semisolid proton volume fractions were lower in the cortex (12.77% ± 0.75%) compared to the white matter (19.80% ± 0.50%), as expected.

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Section: Resultssupporting

confidence: 92%

An end‐to‐end AI‐based framework for automated discovery of rapid CEST/MT MRI acquisition protocols and molecular parameter quantification (AutoCEST)

Perlman

Zhu

Zaiß

et al. 2022

Magnetic Resonance in Med

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“…To develop the application of CEST MRI for differentiation of treatment effects and tumor progression, a consensus from all relevant stakeholders regarding image acquisition and analysis is required to enable multicenter and multi-vendor trials. This is an area of active research, where a working group of international CEST experts is working toward an open source consensus CEST acquisition and analysis protocol ( 71 ).…”

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 2: Spectroscopy, Chemical Exchange Saturation, Multiparametric Imaging, and Radiomics

et al. 2022

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ObjectiveTo summarize evidence for use of advanced MRI techniques as monitoring biomarkers in the clinic, and to highlight the latest bench-to-bedside developments.MethodsThe current evidence regarding the potential for monitoring biomarkers was reviewed and individual modalities of metabolism and/or chemical composition imaging discussed. Perfusion, permeability, and microstructure imaging were similarly analyzed in Part 1 of this two-part review article and are valuable reading as background to this article. We appraise the clinic readiness of all the individual modalities and consider methodologies involving machine learning (radiomics) and the combination of MRI approaches (multiparametric imaging).ResultsThe biochemical composition of high-grade gliomas is markedly different from healthy brain tissue. Magnetic resonance spectroscopy allows the simultaneous acquisition of an array of metabolic alterations, with choline-based ratios appearing to be consistently discriminatory in treatment response assessment, although challenges remain despite this being a mature technique. Promising directions relate to ultra-high field strengths, 2-hydroxyglutarate analysis, and the use of non-proton nuclei. Labile protons on endogenous proteins can be selectively targeted with chemical exchange saturation transfer to give high resolution images. The body of evidence for clinical application of amide proton transfer imaging has been building for a decade, but more evidence is required to confirm chemical exchange saturation transfer use as a monitoring biomarker. Multiparametric methodologies, including the incorporation of nuclear medicine techniques, combine probes measuring different tumor properties. Although potentially synergistic, the limitations of each individual modality also can be compounded, particularly in the absence of standardization. Machine learning requires large datasets with high-quality annotation; there is currently low-level evidence for monitoring biomarker clinical application.ConclusionAdvanced MRI techniques show huge promise in treatment response assessment. The clinical readiness analysis highlights that most monitoring biomarkers require standardized international consensus guidelines, with more facilitation regarding technique implementation and reporting in the clinic.

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“…Therefore, newer imaging approaches have been proposed such as the AREX (apparent exchange-dependent relaxation) method [ 39 , 40 ]. Recently, the so called ‘Pulseq-CEST project’ has been launched for sharing current sequence parameters and for developing an open-source sequence standard [ 41 ].…”

Section: Discussionmentioning

confidence: 99%

The Value of APTw CEST MRI in Routine Clinical Assessment of Human Brain Tumor Patients at 3T

et al. 2022

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Background. With fast-growing evidence in literature for clinical applications of chemical exchange saturation transfer (CEST) magnetic resonance imaging (MRI), this prospective study aimed at applying amide proton transfer-weighted (APTw) CEST imaging in a clinical setting to assess its diagnostic potential in differentiation of intracranial tumors at 3 tesla (T). Methods. Using the asymmetry magnetization transfer ratio (MTRasym) analysis, CEST signals were quantitatively investigated in the tumor areas and in a similar sized region of the normal-appearing white matter (NAWM) on the contralateral hemisphere of 27 patients with intracranial tumors. Area under curve (AUC) analyses were used and results were compared to perfusion-weighted imaging (PWI). Results. Using APTw CEST, contrast-enhancing tumor areas showed significantly higher APTw CEST metrics than contralateral NAWM (AUC = 0.82; p < 0.01). In subgroup analyses of each tumor entity vs. NAWM, statistically significant effects were yielded for glioblastomas (AUC = 0.96; p < 0.01) and for meningiomas (AUC = 1.0; p < 0.01) but not for lymphomas as well as metastases (p > 0.05). PWI showed results comparable to APTw CEST in glioblastoma (p < 0.01). Conclusions. This prospective study confirmed the high diagnostic potential of APTw CEST imaging in a routine clinical setting to differentiate brain tumors.

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Pulseq‐CEST: Towards multi‐site multi‐vendor compatibility and reproducibility of CEST experiments using an open‐source sequence standard

Abstract: This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Cited by 41 publications

References 53 publications

An end‐to‐end AI‐based framework for automated discovery of rapid CEST/MT MRI acquisition protocols and molecular parameter quantification (AutoCEST)

An end‐to‐end AI‐based framework for automated discovery of rapid CEST/MT MRI acquisition protocols and molecular parameter quantification (AutoCEST)

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 2: Spectroscopy, Chemical Exchange Saturation, Multiparametric Imaging, and Radiomics

The Value of APTw CEST MRI in Routine Clinical Assessment of Human Brain Tumor Patients at 3T

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