Evaluation of contributors to amide proton transfer<scp>–</scp>weighted imaging and nuclear Overhauser enhancement<scp>–</scp>weighted imaging contrast in tumors at a high magnetic field

Cui, Jing; Zhao, Yu; Sun, Casey; Xu, Junzhong; Zu, Zhongliang

doi:10.1002/mrm.29675

Cited by 7 publications

(7 citation statements)

References 65 publications

(136 reference statements)

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“…More detailed statistical data can be found in the supporting information Tables S6 and S7. It was observed that while no significant difference was observed in APT between tumors and normal tissues for all denoising methods except the DCAE in APT imaging, there was a significant difference in NOE(-3.5), consistent with previous findings (15,(55)(56)(57).…”

Section: Comparison With State-of-the-art Methods Via Animal Experimentssupporting

confidence: 89%

“…The DCAE-CEST model was trained using simulated CEST signals, the parameters for which were derived from literature reviews (6,56,(58)(59)(60)(61)(62)(63)(64)(65) or based on our prior knowledge and experiences. Nonetheless, accurately quantifying the underlying CEST parameters remains a challenging task, primarily due to the difficulty to accurately isolate each CEST pool.…”

Section: Discussionmentioning

confidence: 99%

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A Denoising Convolutional Autoencoder for SNR Enhancement in Chemical Exchange Saturation Transfer imaging: (DCAE-CEST)

Kurmi,

Viswanathan,

2024

Preprint

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PurposeTo develop a SNR enhancement method for chemical exchange saturation transfer (CEST) imaging using a denoising convolutional autoencoder (DCAE), and compare its performance with state-of-the-art denoising methods.MethodThe DCAE-CEST model encompasses an encoder and a decoder network. The encoder learns features from the input CEST Z-spectrum via a series of 1D convolutions, nonlinearity applications and pooling. Subsequently, the decoder reconstructs an output denoised Z-spectrum using a series of up-sampling and convolution layers. The DCAE-CEST model underwent multistage training in an environment constrained by Kullback–Leibler divergence, while ensuring data adaptability through context learning using Principal Component Analysis processed Z-spectrum as a reference. The model was trained using simulated Z-spectra, and its performance was evaluated using both simulated data and in-vivo data from an animal tumor model. Maps of amide proton transfer (APT) and nuclear Overhauser enhancement (NOE) effects were quantified using the multiple-pool Lorentzian fit, along with an apparent exchange-dependent relaxation metric.ResultsIn digital phantom experiments, the DCAE-CEST method exhibited superior performance, surpassing existing denoising techniques, as indicated by the peak SNR and Structural Similarity Index. Additionally, in vivo data further confirms the effectiveness of the DCAE-CEST in denoising the APT and NOE maps when compared to other methods. While no significant difference was observed in APT between tumors and normal tissues, there was a significant difference in NOE, consistent with previous findings.ConclusionThe DCAE-CEST can learn the most important features of the CEST Z-spectrum and provide the most effective denoising solution compared to other methods.

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Section: Comparison With State-of-the-art Methods Via Animal Experimentssupporting

confidence: 89%

Section: Discussionmentioning

confidence: 99%

A Denoising Convolutional Autoencoder for SNR Enhancement in Chemical Exchange Saturation Transfer imaging: (DCAE-CEST)

Kurmi,

Viswanathan,

2024

Preprint

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“…However, estimating APT k sw remains challenging due to the overlapping contributions 53,54 and the different exchange and relaxation rate selectivity of different quantification methods 55 . Consequently, diverse k sw values using different fitting models and quantification methods have been reported 54–59 . The current study may suggest higher k sw values for the APT effect isolated by the DSP‐CEST method.…”

Section: Discussionmentioning

confidence: 78%

“…55 Consequently, diverse k sw values using different fitting models and quantification methods have been reported. [54][55][56][57][58][59] The current study may suggest higher k sw values for the APT effect isolated by the DSP-CEST method. Similarly, no significant difference was found in the NOE (−3.5 ppm), which differs from the multiple-pool Lorentzian fitted NOE (−3.5 ppm) effect as shown in both Figure 8 and the previous report.…”

Section: F I G U R Ementioning

confidence: 83%

Specific and rapid guanidinium CEST imaging using double saturation power and QUASS analysis in a rodent model of global ischemia

Zhou,

Ji,

Zhao

et al. 2023

Magnetic Resonance in Med

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PurposeGuanidinium CEST is sensitive to metabolic changes and pH variation in ischemia, and it can offer advantages over conventional pH‐sensitive amide proton transfer (APT) imaging by providing hyperintense contrast in stroke lesions. However, quantifying guanidinium CEST is challenging due to multiple overlapping components and a close frequency offset from water. This study aims to evaluate the applicability of a new rapid and model‐free CEST quantification method using double saturation power, termed DSP‐CEST, for isolating the guanidinium CEST effect from confounding factors in ischemia. To further reduce acquisition time, the DSP‐CEST was combined with a quasi‐steady state (QUASS) CEST technique to process non‐steady‐state CEST signals.MethodsThe specificity and accuracy of the DSP‐CEST method in quantifying the guanidinium CEST effect were assessed by comparing simulated CEST signals with/without the contribution from confounding factors. The feasibility of this method for quantifying guanidinium CEST was evaluated in a rat model of global ischemia induced by cardiac arrest and compared to a conventional multiple‐pool Lorentzian fit method.ResultsThe DSP‐CEST method was successful in removing all confounding components and quantifying the guanidinium CEST signal increase in ischemia. This suggests that the DSP‐CEST has the potential to provide hyperintense contrast in stroke lesions. Additionally, the DSP‐CEST was shown to be a rapid method that does not require the acquisition of the entire or a portion of the CEST Z‐spectrum that is required in conventional model‐based fitting approaches.ConclusionThis study highlights the potential of DSP‐CEST as a valuable tool for rapid and specific detection of viable tissues.

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“…Our findings indicate that their influences to the variation of CESRT signal in tumors cannot be ignored, and the "shine through" effect from MT to the CEST ratio is more significant at higher saturation powers. 41 Consequently, it is crucial to use the AREX metric to mitigate the influences from the variation in T 1 weighting and MT effect when evaluating the relative contributions from amide, amine and guanidine proton transfer effects to the APTw contrast in specific pathologies.…”

Section: Discussionmentioning

confidence: 99%

Evaluation of the molecular origin of amide proton transfer–weighted imaging

Sun,

Zhao,

2023

Magnetic Resonance in Med

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PurposeTo evaluate the assumption in amide proton transfer weighted (APTw) imaging that the APT dominates over the relayed nuclear Overhauser enhancement (rNOE) and other CEST effects such as those from amines/guanidines, thereby providing imaging of mobile proteins/peptides.MethodsWe introduced two auxiliary asymmetric analysis metrics that can vary the relative contributions from amine/guanidinium CEST and other effects. By comparing these metrics with the conventional asymmetric analysis metric on healthy rat brains, we can approximately assess the contribution from amines/guanidines to APTw and determine whether the APT dominates over the rNOE effect. To further investigate the molecular origin of APTw, we used samples of dialyzed tissue homogenates to eliminate small metabolites and supernatants of homogenates to separate lipids from other components.ResultsWhen the APTw signal is positive using high saturation amplitudes (e.g., 2–3 μT), the contributions from amines/guanidines are significant and cannot be ignored. The APTw signal from the dialyzed homogenates and the controls has negligible changes, indicating that it primarily originates from macromolecules rather than small metabolites. Additionally, the APTw signals with low saturation amplitudes (e.g., 1 μT) were negative in tissue homogenates but positive in their supernatants, suggesting that proteins contribute positively to APTw signals, whereas lipids contribute negatively to it.ConclusionThe positive APTw signal using high saturation amplitudes could have significant contributions from soluble proteins through CEST, including amide/amine/guanidine proton transfer effects. In contrast, the negative APTw signal using low saturation amplitudes has significant contribution from lipids through rNOE.

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Evaluation of contributors to amide proton transfer–weighted imaging and nuclear Overhauser enhancement–weighted imaging contrast in tumors at a high magnetic field

Cited by 7 publications

References 65 publications

A Denoising Convolutional Autoencoder for SNR Enhancement in Chemical Exchange Saturation Transfer imaging: (DCAE-CEST)

A Denoising Convolutional Autoencoder for SNR Enhancement in Chemical Exchange Saturation Transfer imaging: (DCAE-CEST)

Specific and rapid guanidinium CEST imaging using double saturation power and QUASS analysis in a rodent model of global ischemia

Evaluation of the molecular origin of amide proton transfer–weighted imaging

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