Assessment of ischemic penumbra in patients with hyperacute stroke using amide proton transfer (APT) chemical exchange saturation transfer (CEST) MRI

Machine learning-based multi-pool Voigt fitting of CEST, rNOE, and MTC in Z-spectra

PURPOSE

Four-pool Voigt (FPV) machine learning (ML)-based fitting for Z-spectra was developed to reduce fitting times for clinical feasibility in terms of on-scanner analysis and to promote larger cohort studies. The approach was compared to four-pool Lorentzian (FPL)-ML-based modeling to empirically verify the advantage of Voigt models for Z-spectra.

METHODS

Voigt and Lorentzian models were fitted to human 3 T Z-spectral data using least squares (LS) to generate training data for the corresponding ML versions. Gradient boosting decision trees were trained, resulting in one Voigt and one Lorentzian ML model. Modeling accuracy was tested, and the fitting times of the ML models and LS versions were evaluated. The goodness of fits of Voigt and Lorentzian ML models were compared.

RESULTS

The training time for each ML model (Voigt and Lorentzian) was less than 1 min, and the modeling accuracy compared to the corresponding LS versions was excellent, as indicated by a nonsignificant difference between the parameters obtained by LS and corresponding ML versions. The average fitting time was 20 μs/spectrum for both ML models compared to 0.27 and 0.82 s/spectrum for LS with FPL and FPV, respectively. The goodness of fits of FPV-ML and FPL-ML differed significantly (p < 0.005), with FPV-ML showing an improvement for all tested data.

CONCLUSION

Gradient boosting decision trees fitting of multi-pool Z-spectra significantly reduces fitting times compared to traditional LS approaches, allowing fast data processing while upholding fitting quality. Along with the short training times, this makes the method suitable for clinical settings and for large cohort research applications. The FPV-ML approach provides a significant improvement of goodness of fit compared to FPL-ML.

Asymmetry analysis of nuclear Overhauser enhancement effect at -1.6 ppm in ischemic stroke

BACKGROUND

The nuclear Overhauser enhancement (NOE)-mediated saturation transfer effect at -1.6 ppm, termed NOE(-1.6 ppm), has demonstrated potential for detecting ischemic stroke. However, the quantification of the NOE(-1.6 ppm) effect usually relies on a multiple-pool Lorentzian fit method, which necessitates a time-consuming acquisition of the entire chemical exchange saturation transfer (CEST) Z-spectrum with high-frequency resolution, thus hindering its clinical applications.

PURPOSE

This study aims to assess the feasibility of employing asymmetry analysis, a rapid CEST data acquisition and analysis method, for quantifying the NOE(-1.6 ppm) effect in an animal model of ischemic stroke.

METHODS

We examined potential contaminations from guanidinium/amine CEST, NOE(-3.5 ppm), and asymmetric magnetization transfer (MT) effects, which could reduce the specificity of the asymmetry analysis of NOE(-1.6 ppm). First, a Lorentzian difference (LD) analysis was used to mitigate direct water saturation and MT effects, providing separate estimations of the contributions from the guanidinium/amine CEST and NOE effects. Then, the asymmetry analysis of the LD fitted spectrum was compared with the asymmetry analysis of the raw CEST Z-spectrum to evaluate the contribution of the asymmetric MT effect at -1.6 ppm.

RESULTS

Results show that the variations of the LD quantified NOE(-1.6 ppm) in stroke lesions are much greater than that of the CEST signals at +1.6 ppm and NOE(-3.5 ppm), suggesting that NOE(-1.6 ppm) has a dominating contribution to the asymmetry analysis at -1.6 ppm compared with the guanidinium/amine CEST and NOE(-3.5 ppm) in ischemic stroke. The NOE(-1.6 ppm) variations in the asymmetry analysis of the raw CEST Z-spectrum are close to those in the asymmetry analysis of the LD fitted spectrum, revealing that the NOE(-1.6 ppm) dominates over the asymmetric MT effects.

CONCLUSION

Our study demonstrates that the asymmetry analysis can quantify the NOE(-1.6 ppm) contrast in ischemic stroke with high specificity, thus presenting a viable alternative for rapid mapping of ischemic stroke.

Validation of qMT and CEST MRI as Biomarkers of Response to Treatment After Lumbar Spinal Cord Injury in Rats

The progression and repair of a traumatically injured spinal cord (SCI) involves multifactored processes. Noninvasive, mechanism-informative objective biomarkers could greatly facilitate the translation of findings from preclinical animal models to patient applications. We aimed to develop and validate multiparametric chemical exchange saturation transfer (CEST) and quantitative magnetization transfer (qMT) magnetic resonance imaging (MRI) biomarkers for assessing SCI severity, demyelination, and neuroinflammation, as well as the response to neuroprotective drug treatment riluzole. Changes in CEST and qMT MRI metrics before and after a moderate contusion injury at the L1 level of the lumbar spinal cord were compared between two groups of rats that received either the riluzole or a vehicle treatment over 8 weeks. The specificity of these MRI biomarkers was validated by postmortem immunohistology. The functional relevance of these biomarkers was evaluated by correlation with hindlimb sensorimotor and pain behavior. The pool size ratio (PSR) maps from qMT acquisitions of the SCI region in riluzole-treated rats showed increased white matter macromolecular content compared to the HBC vehicle-treated group, suggesting increased myelin levels and possible remyelination of the injured spinal cord. CEST APT pool (3.5 ppm) amplitude decreased at the region rostral to the injury in riluzole-treated rats compared to the vehicle group, indicating potentially reduced neuroinflammatory activity. MRI metrics correlated temporally with behavioral measures of injury severity and recovery. Histological analysis spatially validated MRI-revealed myelination and neuroinflammation status and confirmed differences between the drug and vehicle treatment groups. Quantitative MRI is well suited for monitoring and quantifying the efficacy of pharmacological treatments in preclinical spinal cord injury models. Multiparametric MRI changes in white matter myelination (qMT PSR) and neuroinflammation (CEST APT) in the injured spinal cord were related to injury severity, behavioral deficits, and recovery progression over time. Both imaging metrics captured enhanced recovery from the neuroprotective drug riluzole, supporting the practical utility of these MRI biomarkers.

Multiparametric Chemical Exchange Saturation Transfer MRI Detects Metabolic Changes in Mild Cognitive Impairment Cases at 3.0 Tesla

This study aimed to assess the potential of multiparametric chemical exchange saturation transfer magnetic resonance imaging (CEST MRI) for MCI detection. Twenty-eight patients with MCI and 31 age- and gender-matched normal controls (NCs) were enrolled. CEST MRI was performed with a gradient and spin-echo sequence on a 3T scanner. Multi-parametric CEST parameters were analyzed, such as amide CEST, amine CEST, amine and amide concentration independent assay (AACID), magnetization transfer ratio yielding rex (MTRrex-amide), and downfield rNOE suppressed apparent exchange-dependent relaxation amide proton (DNS-AREX-amide). Statistical analyses of CEST parameters were performed to evaluate group differences, their correlations with Montreal cognitive assessment (MoCA) score, and diagnostic performance for MCI. Compared with NC group, amide CEST as well as MTRrex-amide decreased in the left hippocampus and amine CEST as well as AACID increased in the right hippocampus in the MCI group; In both hippocampi, the DNS-AREX-amide were significantly lower in the MCI group versus the NC group (all P < 0.05). Amine CEST in the right hippocampus was negatively correlated with MoCA score (r = - 0.457, p = 0.017); DNS-AREX-amide in the bilateral hippocampus was positively correlated with MoCA score (left: r = 0.449, P = 0.019; right: AUC = 0.529, P = 0.05). DNS-AREX-amide in the bilateral hippocampus have a good ability to identify MCI (left: AUC = 0.756, P < 0.01; right: AUC = 0.762, P < 0.01). CEST MRI provides a potential imaging diagnostic strategy for MCI, which may promote early detection of MCI and provide novel insights into the pathological progress toward AD.

Assessment of myelination development in neonatal rats using chemical exchange saturation transfer (CEST) 7-T MRI

Myelination is a crucial process in the nervous system. This study aimed to evaluate the progression of myelin sheath development in different brain regions of neonatal rats at distinct developmental stages using Chemical Exchange Saturation Transfer (CEST) 7-T MRI. Male SD rats of different ages (3 days, 1 week, 2 weeks, 3 weeks, 1 month, 2 months) were selected for the study. Advanced in vivo MRI experiments were conducted using a 7-T MRI scanner. Custom MatLab scripts were employed to generate MR images and process the data. Myelin staining was used to assess myelin distribution in various brain regions. Statistical analysis was performed using repeated measures multivariate analysis of variance (MANOVA) and Spearman's rank correlation. The progression of myelination was significantly different in different brain regions (F(5, 30) = 3.34, P < 0.05), with the corpus callosum showing an accelerated rate of myelination. Within the first month alone, there was an increase of 46.1% in myelination (t(35) = 2.29, P < 0.05). The hypothalamus and internal capsule exhibited a more gradual yet consistent increase in myelination over the two-month period, with increases of 47.1% (t(35) = 2.27, P < 0.05) and 39.8% (t(35) = 2.59, P < 0.05), respectively. A substantial positive correlation was found between the MRI-based and histological measurements of myelination (r = 0.31, P < 0.05). This study demonstrates the potential of CEST 7-T MRI as a non-invasive tool for assessing myelination progression and provides insights into the differential myelination rates across various brain regions during early development.

Nonlinear parameter estimation with physics-constrained spectral-spatial priors for highly accelerated chemical exchange saturation transfer MRI

Objective.To develop a nonlinear, model-based parameter estimation method directly from incomplete measurements ink - wspace for robust spectral analysis in highly accelerated chemical exchange saturation transfer (CEST) magnetic resonance imaging (MRI).Approach. A CEST-specific, separable nonlinear model, which describes spectral decomposition using multi-pool Lorentzian functions (conventional magnetization transfer (MT), direct saturation of water signals (DS), amide, amine, and nuclear Overhauser effect) derived from the steady-state Bloch McConnel equation, is incorporated into a measurement model in CEST MRI. Furthermore, signal drop in saturation transfer experiments is formulated by an additional, separable nonlinear spectral prior indicating that the symmetric z-spectra synthesized using conventional MT and DS always remain higher or equal to the whole z-spectra with all pools. Given the above considerations, linear and nonlinear parameters in the proposed method are estimated in an alternating fashion directly from highly incomplete measurements ink - wspace by solving a constrained optimization problem with the physics-constrained spectral priors while imposing additional sparsity priors on spatial parameter maps.Main results.Compared with conventional methods, the proposed method yields clearer delineation of tumor-specific CEST maps without apparent artifact and noise.Significance.We successfully demonstrated the feasibility of the proposed method for CEST MRI with highly incomplete measurements thus enabling high-resolution whole brain CEST MRI in clinically reasonable imaging time.

Amide proton transfer MRI at 9.4 T for differentiating tissue acidosis in a rodent model of ischemic stroke

PURPOSE

Differentiating ischemic brain damage is critical for decision making in acute stroke treatment for better outcomes. We examined the sensitivity of amide proton transfer (APT) MRI, a pH-weighted imaging technique, to achieve this differentiation.

METHODS

In a rat stroke model, the ischemic core, oligemia, and the infarct-growth region (IGR) were identified by tracking the progression of the lesions. APT MRI signals were measured alongside ADC, T1, and T2 maps to evaluate their sensitivity in distinguishing ischemic tissues. Additionally, stroke under hyperglycemic conditions was studied.

RESULTS

The APT signal in the IGR decreased by about 10% shortly after stroke onset, and further decreased to 35% at 5 h, indicating a progression from mild to severe acidosis as the lesion evolved into infarction. Although ADC, T1, and T2 contrasts can only detect significant differences between the IGR and oligemia for a portion of the stroke duration, APT contrast consistently differentiates between them at all time points. However, the contrast to variation ratio at 1 h is only about 20% of the contrast to variation ratio between the core and normal tissues, indicating limited sensitivity. In the ischemic core, the APT signal decreases to about 45% and 33% of normal tissue level at 1 h for the normoglycemic and hyperglycemic groups, respectively, confirming more severe acidosis under hyperglycemia.

CONCLUSION

The sensitivity of APT MRI is high in detecting severe acidosis of the ischemic core but is much lower in detecting mild acidosis, which may affect the accuracy of differentiation between the IGR and oligemia.

Quantitative separation of CEST effect by Rex-line-fit analysis of Z-spectra

The process of chemical exchange saturation transfer (CEST) is quantified by evaluating a Z-spectra, where CEST signal quantification and Z-spectra fitting have been widely used to distinguish the contributions from multiple origins. Based on the exchange-dependent relaxation rate in the rotating frame (Rex), this paper introduces an additional pathway to quantitative separation of CEST effect. The proposed Rex-line-fit method is solved by a multi-pool model and presents the advantage of only being dependent of the specific parameters (solute concentration, solute-water exchange rate, solute transverse relaxation, and irradiation power). Herein we show that both solute-water exchange rate and solute concentration monotonously vary with Rex for Amide, Guanidino, NOE and MT, which has the potential to assist in solving quantitative separation of CEST effect. Furthermore, we achieve Rex imaging of Amide, Guanidino, NOE and MT, which may provide direct insight into the dependency of measurable CEST effects on underlying parameters such as the exchange rate and solute concentration, as well as the solute transverse relaxation.

Deep-learning-based super-resolution for accelerating chemical exchange saturation transfer MRI

Chemical exchange saturation transfer (CEST) MRI is a molecular imaging tool that provides physiological information about tissues, making it an invaluable tool for disease diagnosis and guided treatment. Its clinical application requires the acquisition of high-resolution images capable of accurately identifying subtle regional changes in vivo, while simultaneously maintaining a high level of spectral resolution. However, the acquisition of such high-resolution images is time consuming, presenting a challenge for practical implementation in clinical settings. Among several techniques that have been explored to reduce the acquisition time in MRI, deep-learning-based super-resolution (DLSR) is a promising approach to address this problem due to its adaptability to any acquisition sequence and hardware. However, its translation to CEST MRI has been hindered by the lack of the large CEST datasets required for network development. Thus, we aim to develop a DLSR method, named DLSR-CEST, to reduce the acquisition time for CEST MRI by reconstructing high-resolution images from fast low-resolution acquisitions. This is achieved by first pretraining the DLSR-CEST on human brain T1w and T2w images to initialize the weights of the network and then training the network on very small human and mouse brain CEST datasets to fine-tune the weights. Using the trained DLSR-CEST network, the reconstructed CEST source images exhibited improved spatial resolution in both peak signal-to-noise ratio and structural similarity index measure metrics at all downsampling factors (2-8). Moreover, amide CEST and relayed nuclear Overhauser effect maps extrapolated from the DLSR-CEST source images exhibited high spatial resolution and low normalized root mean square error, indicating a negligible loss in Z-spectrum information. Therefore, our DLSR-CEST demonstrated a robust reconstruction of high-resolution CEST source images from fast low-resolution acquisitions, thereby improving the spatial resolution and preserving most Z-spectrum information.

Multimodal imaging evaluation of early neurological deterioration following acute ischemic stroke

Background

Early neurologic deterioration occurs in up to one-third of patients with acute ischemic stroke (IS), often leading to poor functional outcomes. At present, few studies have applied amide proton transfer (APT) imaging to the evaluation of early neurological deterioration (END). This study analyzed the value of computed tomography perfusion (CTP) combined with multimodal magnetic resonance imaging (MRI) in patients with acute IS with END.

Methods

This retrospective study included patients with acute IS who were admitted to the neurology inpatient department in a tertiary hospital from October 2021 to June 2023. Patients with acute IS underwent CTP within 24 hours of stroke onset and MRI [arterial spin labeling (ASL), susceptibility-weighted imaging (SWI), and APT] within 7 days. END was defined as an elevation of ≥2 points on the National Institute of Health Stroke Scale (NIHSS) within 7 days of stroke onset. Univariable and multivariable analyses were used to compare clinical and imaging biomarkers in patients with acute IS with and without END. The performance of potential biomarkers in distinguishing between the two groups was evaluated using receiver operating characteristic (ROC) curve analysis.

Results

Among the 70 patients with acute IS, 20 (29%) had END. After conducting univariable analysis, variables were selected for entry into a binary logistic regression analysis based on our univariable analysis results, previous research findings, clinical experience, and methodological standards. The results indicated that relative cerebral blood volume (CBV) on CTP, relative cerebral blood flow (CBF) on ASL, and relative signal intensity on amide proton transfer-weighted (APTw) imaging were independent risk factors for END. The areas under the ROC curves for these risk factors were 0.710 [95% confidence interval (CI): 0.559-0.861, P=0.006], 0.839 (95% CI: 0.744-0.933, P<0.001), and 0.804 (95% CI: 0.676-0.932, P<0.001), respectively. The combined area under the curve (AUC), sensitivity, and specificity of the four indices (0.941, 100%, and 78%, respectively) were higher than those of the four indices alone.

Conclusions

CTP combined with multi-modal MRI better evaluated hemodynamics, tissue metabolism, and other relevant patient information, providing an objective basis for the clinical assessment of patients with acute IS with END and facilitating the development of accurate and personalized treatment plans.

Amide proton transfer-weighted imaging with a short acquisition time based on a self B0 correction using the turbo spin echo-Dixon method: A phantom study

PURPOSE

Conventional amide proton transfer (APT)-weighted imaging requires a chemical exchange saturation transfer (CEST) sequence with multiple saturation frequency offsets and a B0 correction sequence, plus a long acquisition time that can be reduced by applying the conventional method using CEST images with seven radiation pulses (i.e., the seven-points method). For a further reduction of acquisition times, we propose fast two-dimensional (2D) APT-weighted imaging based on a self B0 correction using the turbo spin echo (TSE)-Dixon method. We conducted a phantom study to investigate the accuracy of TSE-Dixon APT-weighted imaging.

METHODS

We prepared two types of phantoms with six samples for a concentrationdependent evaluation and a pH-dependent evaluation. APT-weighted images were acquired by the conventional, seven-points, and TSE-Dixon methods. Linear regression analyses assessed the dependence between each method's APT signal intensities (SIs) and the concentration or pH. We performed a one-way analysis of variance with Tukey's honestly significant difference post hoc test to compare the APT SIs among the three methods. The agreement of the APT SIs between the conventional and seven-points or TSE-Dixon methods was assessed by a Bland- Altman plot analysis.

RESULTS

The APT SIs of all three acquisition methods showed positive concentration dependence and pH dependence. No significant differences were observed in the APT SIs between the conventional and TSE-Dixon methods at each concentration. The Bland-Altman plot analyses showed that the APT SIs measured with the seven-points method resulted in 0.42% bias and narrow 95% limits of agreement (LOA) (0.93%-0.09%) compared to the conventional method. The APT SIs measured using the TSE-Dixon method showed 0.14% bias and similar 95% LOA (-0.33% to 0.61%) compared with the seven-points method. The APT SIs of all three methods showed positive pH dependence. At each pH, no significant differences in the APT SIs were observed among the methods. Bland-Altman plot analyses showed that the APT SIs measured with the seven-points method resulted in low bias (0.03%) and narrow 95% LOA (-0.30% to 0.36%) compared to the conventional method. The APT SIs measured by the TSE-Dixon method showed slightly larger bias (0.29%) and similar 95% LOA (from -0.15% to 0.72%) compared to those measured by the seven-points method.

CONCLUSION

These results demonstrated that our proposed method has the same concentration dependence and pH dependence as the conventional method and the seven-points method. We thus expect that APT-weighted imaging with less influence of motion can be obtained in clinical examinations.

Metabolic Imaging of Acute Ischemic Stroke (PET, 1Hydrogen Spectroscopy, 17Oxygen Imaging, 23Sodium MRI, pH Imaging)

Acute stroke imaging plays a vital and time-sensitive role in therapeutic decision-making. Current clinical workflows widely use computed tomography (CT) and magnetic resonance (MR) techniques including CT and MR perfusion to estimate the volume of ischemic penumbra at risk for infarction without acute intervention. The use of imaging techniques aimed toward evaluating the metabolic derangements underlying a developing infarct may provide additional information for differentiating the penumbra from benign oligemia and infarct core. The authors review several modalities of metabolic imaging including PET, hydrogen and oxygen spectroscopy, sodium MRI, and pH-weighted MRI.

Spatiotemporal Dynamics of Neuroinflammation Relate to Behavioral Recovery in Rats with Spinal Cord Injury

PURPOSE

The degree and dynamic progression of neuroinflammation after traumatic spinal cord injuries (SCI) are crucial determinants of the severity of injury and potential for recovery. We used Positron Emission Tomography (PET) to monitor neuroinflammation longitudinally, correlating it with Chemical Exchange Saturation Transfer (CEST) Magnetic Resonance Imaging (MRI) and behavior in contusion-injured rats. These studies help validate CEST metrics and confirm how imaging may be used to evaluate the efficacy of therapies and understand their mechanisms of action.

PROCEDURES

12 SCI and 4 sham surgery rats were subjected to CEST MRI and PET-Translocator Protein (TSPO) scans for 8 weeks following injury. Z-spectra from the SCI were analyzed using a 5-Lorentzian pool model for fitting. Weekly motor and somatosensory behavior were correlated with imaging metrics, which were validated through post-mortem histological and immuo-staining using ionized calcium-binding adaptor protein-1 (iba-1, microglia) and glial fibrillary acidic protein (GFAP, astrocytes).

RESULTS

PET-TSPO showed widespread inflammation and post-mortem histology confirmed the presence of activated microglia. Changes in CEST and nuclear Overhauser Effect (NOE) peaks at 3.5 ppm and -1.6 ppm respectively were largest within the first week after injury and more pronounced in rostral versus caudal segments. These temporal indices of neuroinflammation corresponded to the recovery of locomotor behaviors and somatic sensation in rats with moderate contusion injury. The results confirm that CEST MRI metrics are sensitive indices of states of neuroinflammation within injured spinal cords.

CONCLUSIONS

The detection of dynamic spatiotemporal features of neuroinflammation progression underscores the importance of considering their timings and locations for neuroprotective and anti-inflammatory therapies. The availability of noninvasive MRI indices of neuroinflammation may facilitate clinical trials aimed at treatments that promote recovery after SCI.

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

PURPOSE

Guanidinium 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.

METHODS

The 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.

RESULTS

The 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.

CONCLUSION

This study highlights the potential of DSP-CEST as a valuable tool for rapid and specific detection of viable tissues.

Dual contrast CEST MRI for pH-weighted imaging in stroke

PURPOSE

pH enhanced (pHenh ) CEST imaging combines the pH sensitivity from amide and guanidino signals, but the saturation parameters have not been optimized. We propose pHdual as a variant of pHenh that suppresses background signal variations, while enhancing pH sensitivity and potential for imaging ischemic brain injury of stroke.

METHODS

Simulation and in vivo rodent stroke experiments of pHenh MRI were performed with varied RF saturation powers for both amide and guanidino protons to optimize the contrast between lesion/normal tissues, while simultaneously minimizing signal variations across different types of normal tissues. In acute stroke, contrast and volume ratio measured by pHdual imaging were compared with an amide-CEST approach, and perfusion and diffusion MRI.

RESULTS

Simulation experiments indicated that amide and guanidino CEST signals exhibit unique sensitivities across different pH ranges, with pHenh producing greater sensitivity over a broader pH regime. The pHenh data of rodent stroke brain demonstrated that the lesion/normal tissue contrast was maximized for an RF saturation power pair of 0.5 μT at 2.0 ppm and 1.0 μT at 3.6 ppm, whereas an optimal contrast-to-variation ratio (CVR) was obtained with a 0.7 μT saturation at 2.0 ppm and 0.8 μT at 3.6 ppm. In acute stroke, CVR optimized pHenh (i.e., pHdual ) achieved a higher sensitivity than the three-point amide-CEST approach, and distinct patterns of lesion tissue compared to diffusion and perfusion MRI.

CONCLUSION

pHdual MRI improves the sensitivity of pH-weighted imaging and will be a valuable tool for assessing tissue viability in stroke.

3D CEST MRI with an unevenly segmented RF irradiation scheme: A feasibility study in brain tumor imaging

PURPOSE

To integrate 3D CEST EPI with an unevenly segmented RF irradiation module and preliminarily demonstrate it in the clinical setting.

METHODS

A CEST MRI with unevenly segmented RF saturation was implemented, including a long primary RF saturation to induce the steady-state CEST effect, maintained with repetitive short secondary RF irradiation between readouts. This configuration reduces relaxation-induced blur artifacts during acquisition, allowing fast 3D spatial coverage. Numerical simulations were performed to select parameters such as flip angle (FA), short RF saturation duration (Ts2), and the number of readout segments. The sequence was validated experimentally with data from a phantom, healthy volunteers, and a brain tumor patient.

RESULTS

Based on the numerical simulation and l-carnosine gel phantom experiment, FA, Ts2, and the number of segments were set to 20°, 0.3 s, and the range from 4 to 8, respectively. The proposed method minimized signal modulation in the human brain images in the kz direction during the acquisition and provided the blur artifacts-free CEST contrast over the whole volume. Additionally, the CEST contrast in the tumor tissue region is higher than in the contralateral normal tissue region.

CONCLUSIONS

It is feasible to implement a highly accelerated 3D EPI CEST imaging with unevenly segmented RF irradiation.

Investigation of relayed nuclear Overhauser enhancement effect at -1.6 ppm in an ischemic stroke model

BACKGROUND

When an ischemic stroke happens, it triggers a complex signalling cascade that may eventually lead to neuronal cell death if no reperfusion. Recently, the relayed nuclear Overhauser enhancement effect at -1.6 ppm [NOE(-1.6 ppm)] has been postulated may allow for a more in-depth analysis of the ischemic injury. This study assessed the potential utility of NOE(-1.6 ppm) in an ischemic stroke model.

METHODS

Diffusion-weighted imaging, perfusion-weighted imaging, and chemical exchange saturation transfer (CEST) magnetic resonance imaging (MRI) data were acquired from five rats that underwent scans at 9.4 T after middle cerebral artery occlusion.

RESULTS

The apparent diffusion coefficient (ADC), cerebral blood flow (CBF), and apparent exchange-dependent relaxations (AREX) at 3.5 ppm and NOE(-1.6 ppm) were quantified. AREX(3.5 ppm) and NOE(-1.6 ppm) were found to be hypointense and exhibited different signal patterns within the ischemic tissue. The NOE(-1.6 ppm) deficit areas were equal to or larger than the ADC deficit areas, but smaller than the AREX(3.5 ppm) deficit areas. This suggested that NOE(-1.6 ppm) might further delineate the acidotic tissue estimated using AREX(3.5 ppm). Since NOE(-1.6 ppm) is closely related to membrane phospholipids, NOE(-1.6 ppm) potentially highlighted at-risk tissue affected by lipid peroxidation and membrane damage. Altogether, the ADC/NOE(-1.6 ppm)/AREX(3.5 ppm)/CBF mismatches revealed four zones of increasing sizes within the ischemic tissue, potentially reflecting different pathophysiological information.

CONCLUSIONS

Using CEST coupled with ADC and CBF, the ischemic tissue may thus potentially be separated into four zones to better understand the pathophysiology after stroke and improve ischemic tissue fate definition. Further verification of the potential utility of NOE(-1.6 ppm) may therefore lead to a more precise diagnosis.

Comparison of model-free Lorentzian and spinlock model-based fittings in quantitative CEST imaging of acute stroke

PURPOSE

CEST MRI detects complex tissue changes following acute stroke. Our study aimed to test if spinlock model-based fitting of the quasi-steady-state (QUASS)-reconstructed equilibrium CEST MRI improves the determination of multi-pool signal changes over the commonly-used model-free Lorentzian fitting in acute stroke.

THEORY AND METHODS

Multiple three-pool CEST Z-spectra were simulated using Bloch-McConnell equations for a range of T1 , relaxation delay, and saturation times. The multi-pool CEST signals were solved from the simulated Z-spectra to test the accuracy of routine Lorentzian (model-free) and spinlock (model-based) fittings without and with QUASS reconstruction. In addition, multiparametric MRI scans were obtained in rat models of acute stroke, including relaxation, diffusion, and CEST Z-spectrum. Finally, we compared model-free and model-based per-pixel CEST quantification in vivo.

RESULTS

The spinlock model-based fitting of QUASS CEST MRI provided a nearly T1 -independent determination of multi-pool CEST signals, advantageous over the fittings of apparent CEST MRI (model-free and model-based). In vivo data also demonstrated that the spinlock model-based QUASS fitting captured significantly different changes in semisolid magnetization transfer (-0.9 ± 0.8 vs. 0.3 ± 0.8%), amide (-1.1 ± 0.4 vs. -0.5 ± 0.2%), and guanidyl (1.0 ± 0.4 vs. 0.7 ± 0.3%) signals over the model-free Lorentzian analysis.

CONCLUSION

Our study demonstrated that spinlock model-based fitting of QUASS CEST MRI improved the determination of the underlying tissue changes following acute stroke, promising further clinical translation of quantitative CEST imaging.

Noninvasive Characterization of Metabolic Changes in Ischemic Stroke Using Z-spectrum-fitted Multiparametric Chemical Exchange Saturation Transfer-weighted Magnetic Resonance Imaging

OBJECTIVE

This study aimed to noninvasively characterize the metabolic alterations in ischemic brain tissues using Z-spectrum-fitted multiparametric chemical exchange saturation transfer-weighted magnetic resonance imaging (CEST-MRI).

METHODS

Three sets of Z-spectrum data with saturation power (B1) values of 1.5, 2.5, and 3.5 µT, respectively, were acquired from 17 patients with ischemic stroke. Multiple contrasts contributing to the Z-spectrum, including fitted amide proton transfer (APTfitted), +2 ppm peak (CEST@2ppm), concomitantly fitted APTfitted and CEST@2ppm (APT&CEST@2ppm), semisolid magnetization transfer contrast (MT), aliphatic nuclear Overhauser effect (NOE), and direct saturation of water (DSW), were fitted with 4 and 5 Lorentzian functions, respectively. The CEST metrics were compared between ischemic lesions and contralateral normal white matter (CNWM), and the correlation between the CEST metrics and the apparent diffusion coefficient (ADC) was assessed. The differences in the Z-spectrum metrics under varied B1 values were also investigated.

RESULTS

Ischemic lesions showed increased APTfitted, CEST@2ppm, APT&CEST@2ppm, NOE, and DSW as well as decreased MT. APT&CEST@2ppm, MT, and DSW showed a significant correlation with ADC [APT&CEST@2ppm at the 3 B1 values: R=0.584/0.467/0.551; MT at the 3 B1 values: R=-0.717/-0.695/-0.762 (4-parameter fitting), R=-0.734/-0.711/-0.785 (5-parameter fitting); DSW of 4-/5-parameter fitting: R=0.794/0.811 (2.5 µT), R=0.800/0.790 (3.5 µT)]. However, the asymmetric analysis of amide proton transfer (APTasym) could not differentiate the lesions from CNWM and showed no correlation with ADC. Furthermore, the Z-spectrum contrasts varied with B1.

CONCLUSION

The Z-spectrum-fitted multiparametric CEST-MRI can comprehensively detect metabolic alterations in ischemic brain tissues.

Effect of Saturation Pulse Duration and Power on pH-weighted Amide Proton Transfer Imaging: A Phantom Study

PURPOSE

Amide proton transfer (APT) imaging may detect changes in tissues' pH based on the chemical exchange saturation transfer (CEST) phenomenon, and thus it may be useful for identifying the penumbra in ischemic stroke patients. We investigated the effect of saturation pulse duration and power on the APT effect in phantoms with different pH values.

METHODS

Five samples were prepared from a 1:10 solution of egg-white albumin in phosphate-buffered saline at pH 6.53-7.65. The APT signal intensity (SI) was defined as asymmetry of the magnetization transfer ratio at 3.5 ppm. We measured the APT SIs in the egg-white albumin samples of different pH values with saturation pulse durations of 0.5, 1.0, 2.0, and 3.0 sec and saturation pulse powers of 0.5, 1.5, and 2.5 μT. The relative change in the APT SI in relation to the saturation duration and power at different pH values was defined as follows: (APT SI each saturation pulse - APT SI shortest or weakest pulse)/APT SIshortest or weakest pulse. The dependence of the APT SI on pH and the relative change in the APT SI were calculated as the slope of the linear regression.

RESULTS

The lower the pH, the larger the relative change in the APT SI, due to the change in saturation pulse duration and power. The APT SI was highly correlated with the pH at all saturation pulse durations and powers.

CONCLUSION

The influence of saturation duration and power on the APT effect was greater at lower pH than higher pH. The combination of saturation pulse ≥ 1.0 s and power ≥ 1.5 μT was useful for the sensitive detection of changes in APT effects in the egg-white albumin samples with different pH values.

Amide proton transfer-weighted MRI features of acute ischemic stroke subtypes

Stroke is a highly heterogeneous disorder with distinct subtypes, and the stroke subtype influences the outcome. Amide proton transfer-weighted (APTW) MRI has been demonstrated to be promising in stroke patients, but the image characteristics of stroke subtypes have not been sufficiently investigated. The purpose of this study was to investigate the APTW MRI features of different subtypes of acute ischemic stroke (AIS). Ninety-two AIS patients presenting within 96 h of symptom onset were enrolled and examined with a 3.0-T MRI system. Patients were grouped into four subtypes: lacunar circulation infarcts (LACI, n = 33); total anterior circulation infarcts (TACI, n = 9); partial anterior circulation infarcts (PACI, n = 28); and posterior circulation infarcts (POCI, n = 22). APTW values in the lesion (APTWlesion ) and the contralateral normal-appearing region (APTWcontral ) were measured. The change in APTW values between the acute ischemic lesion and the contralateral normal-appearing region (APTWles-con ) was calculated. A two-sample t-test, one-way ANOVA, and the Chi-square method were used. There were significant differences between APTWlesion and APTWcontral in the three categories of nonlacunar strokes (TACI, PACI, and POCI, all p < 0.01), but not for lacunar strokes (LACI, p = 0.080). TACI patients had the lowest APTWlesion and APTWles-con in all groups (p < 0.05). In the POCI group, patients with supratentorial infarcts showed significant differences between APTWlesion and APTWcontral (p = 0.001), while the differences were not significant for infratentorial infarcts (p = 0.135). Our results suggest that the APT effect was heterogeneous in different stroke subtypes, and that APTW MRI gave an excellent performence in depicting nonlacunar AIS in supratentorial locations.

Biogenic Imaging Contrast Agents

Imaging contrast agents are widely investigated in preclinical and clinical studies, among which biogenic imaging contrast agents (BICAs) are developing rapidly and playing an increasingly important role in biomedical research ranging from subcellular level to individual level. The unique properties of BICAs, including expression by cells as reporters and specific genetic modification, facilitate various in vitro and in vivo studies, such as quantification of gene expression, observation of protein interactions, visualization of cellular proliferation, monitoring of metabolism, and detection of dysfunctions. Furthermore, in human body, BICAs are remarkably helpful for disease diagnosis when the dysregulation of these agents occurs and can be detected through imaging techniques. There are various BICAs matched with a set of imaging techniques, including fluorescent proteins for fluorescence imaging, gas vesicles for ultrasound imaging, and ferritin for magnetic resonance imaging. In addition, bimodal and multimodal imaging can be realized through combining the functions of different BICAs, which helps overcome the limitations of monomodal imaging. In this review, the focus is on the properties, mechanisms, applications, and future directions of BICAs.

CEST 2022 - Fast WASABI post-processing: Access to rapid B0 and B1 correction in clinical routine for CEST MRI

CEST MRI methods, such as APT and NOE imaging reveal biomarkers with significant diagnostic potential due to their ability to access molecular tissue information. Regardless of the technique used, CEST MRI data are affected by static magnetic B₀ and radiofrequency B₁ field inhomogeneities that degrade their contrast. For this reason, the correction of B₀ field-induced artefacts is essential, whereas accounting for B₁ field inhomogeneities have shown significant improvements in image readability. In a previous work, an MRI protocol called WASABI was presented, which can map simultaneously B₀ and B₁ field inhomogeneities, while maintaining the same sequence and readout types as used for CEST MRI. Despite the highly satisfactory quality of B₀ and B₁ maps computed from the WASABI data, the post-processing method is based on an exhaustive search of a four-parameter space and an additional four-parameter non-linear model fitting step. This leads to long post-processing times that are prohibitive in clinical practice. This work provides a new method for fast post-processing of WASABI data with outstanding acceleration of the parameter estimation procedure and without compromising its stability. The resulting computational acceleration makes the WASABI technique suitable for clinical use. The stability of the method is demonstrated on phantom data and clinical 3 Tesla in vivo data.

Frequency importance analysis for chemical exchange saturation transfer magnetic resonance imaging using permuted random forest

Chemical exchange saturation transfer magnetic resonance imaging (CEST MRI) is a promising molecular imaging tool that allows sensitive detection of endogenous metabolic changes. However, because the CEST spectrum does not display a clear peak like MR spectroscopy, its signal interpretation is challenging, especially under 3-T field strength or with a large saturation B₁ . Herein, as an alternative to conventional Z-spectral fitting approaches, a permuted random forest (PRF) method is developed to determine featured saturation frequencies for lesion identification, so-called CEST frequency importance analysis. Briefly, voxels in the CEST dataset were labeled as lesion and control according to multicontrast MR images. Then, by considering each voxel's saturation signal series as a sample, a permutation importance algorithm was employed to rank the contribution of saturation frequency offsets in the differentiation of lesion and normal tissue. Simulations demonstrated that PRF could correctly determine the frequency offsets (3.5 or -3.5 ppm) for classifying two groups of Z-spectra, under a range of B₀ , B₁ conditions and sample sizes. For ischemic rat brains, PRF only displayed high feature importance around amide frequency at 2 h postischemia, reflecting that the pH changes occurred at an early stage. By contrast, the data acquired at 24 h postischemia exhibited high feature importance at multiple frequencies (amide, water, and lipids), which suggested the complex tissue changes that occur during the later stages. Finally, PRF was assessed using 3-T CEST data from four brain tumor patients. By defining the tumor region on amide proton transfer-weighted images, PRF analysis identified different CEST frequency importance for two types of tumors (glioblastoma and metastatic tumor) (p < 0.05, with each image slice as a subject). In conclusion, the PRF method was able to rank and interpret the contribution of all acquired saturation offsets to lesion identification; this may facilitate CEST analysis in clinical applications, and open up new doors for comprehensive CEST analysis tools other than model-based approaches.

Discrimination between progressive penumbra and benign oligemia of the diffusion-perfusion mismatch region by amide proton transfer-weighted imaging

PURPOSE

Amide proton transfer-weighted (APTw) imaging was an effective tool to reveal the tissue acidosis of acute ischemic stroke. This study aimed to evaluate the ability of APTw MRI to distinguish progressive penumbra and benign oligemia in the diffusion-perfusion mismatch region.

MATERIALS AND METHODS

38 acute cerebral infarction patients who underwent a comprehensive MRI examination, including diffusion-weighted imaging (DWI), perfusion-weighted imaging (PWI), APT imaging, and a follow-up scan in one week were recruited. There were 12 DWI/PWI match cases. The DWI/PWI mismatch patients were divided into 10 progressive cases and 16 stable cases according to the lesion size on the follow-up DWI image compared to the admission scan. Three ROIs: infarction lesion, peripheral, and contralateral normal regions were measured on each subject's MTRasym map. The Friedman test was used to compare the changes of MTRasym among three different regions within each group. The Kruskal-Wallis ANOVA test was used to compare them among the same region of different groups. The correlation between the MTRasym of the peripheral region and the lesion enlargement was analyzed by the Spearman test.

RESULTS

The MTRasym at the infarction lesion of all three groups showed significant decrease to the contralateral normal tissue. In the progressive mismatch group, the MTRasym at the peripheral region within the DWI/PWI mismatch showed a significant difference with the contralateral normal region and no difference with the infarct core. Whereas both the MTRasym at the peripheral region of the stable mismatch and match groups had no significant difference with the contralateral side, but the differences were significant from those of the central core. When comparing the peripheral region of three groups, the MTRasym of the progressive mismatch group showed a significant decrease to that of the stable mismatch and match groups. The MTRasym of the peripheral region showed a negative correlation with lesion enlargement.

CONCLUSION

APTw imaging is promising to stratify the heterogeneous PWI/DWI mismatch region and benefit the clinical treatment.

Amide proton transfer imaging in stroke

Amide proton transfer (APT) imaging, a variant of chemical exchange saturation transfer MRI, has shown promise in detecting ischemic tissue acidosis following impaired aerobic metabolism in animal models and in human stroke patients due to the sensitivity of the amide proton exchange rate to changes in pH within the physiological range. Recent studies have demonstrated the possibility of using APT-MRI to detect acidosis of the ischemic penumbra, enabling the assessment of stroke severity and risk of progression, monitoring of treatment progress, and prognostication of clinical outcome. This paper reviews current APT imaging methods actively used in ischemic stroke research and explores the clinical aspects of ischemic stroke and future applications for these methods.

Numerical fitting of Extrapolated semisolid Magnetization transfer Reference signals: Improved detection of ischemic stroke

PURPOSE

To propose a novel Numerical fitting method of the Extrapolated semisolid Magnetization transfer Reference (NEMR) signal for quantifying the CEST effect.

THEORY AND METHODS

Modified two-pool Bloch-McConnell equations were used to numerically fit the magnetization transfer (MT) and direct water saturation (DS) signals at far off-resonance frequencies, which was subsequently extrapolated into the frequency range of amide proton transfer (APT) and nuclear Overhauser enhancement (NOE) pools. Then the subtraction of the fitted two-pool z-spectrum and the experimentally acquired z-spectrum yielded APT^# and NOE^# signals mostly free of MT and DS contamination. Several strategies were used to accelerate the NEMR fitting. Furthermore, the proposed NEMR method was compared with the conventional extrapolated semisolid magnetization transfer reference (EMR) and magnetization transfer ratio asymmetry (MTR_asym ) methods in simulations and stroke patients.

RESULTS

The combination of RF downsampling, MT lineshape look-up table, and conversion of MATLAB code to C code accelerated the NEMR fitting by over 2700-fold. Monte-Carlo simulations showed that NEMR had higher accuracy than EMR and eliminated the requirement of the steady-state condition. In ischemic stroke patients, the NEMR maps at 1 μT removed hypointense artifacts seen on EMR and MTR_asym images, and better depicted stroke lesions than EMR. For NEMR, NOE^# yielded significantly (p < 0.05) stronger signal contrast between stroke and normal tissues than APT^# at 1 μT.

CONCLUSION

The proposed NEMR method is suitable for arbitrary saturation settings and can remove MT and DS contamination from the CEST signal for improved detection of ischemic stroke.

Imaging of Suspected Stroke in Children, From the AJR Special Series on Emergency Radiology

Pediatric stroke encompasses different causes, clinical presentations, and associated conditions across ages. Although it is relatively uncommon, pediatric stroke presents with poor short- and long-term outcomes in many cases. Because of a wide range of overlapping presenting symptoms between pediatric stroke and other more common conditions, such as migraine and seizures, stroke diagnosis can be challenging or delayed in children. When combined with a comprehensive medical history and physical examination, neuroimaging plays a crucial role in diagnosing stroke and differentiating stroke mimics. This review highlights the current neuroimaging workup for diagnosing pediatric stroke in the emergency department, describes advantages and disadvantages of different imaging modalities, highlights disorders that predispose children to infarct or hemorrhage, and presents an overview of stroke mimics. Key differences in the initial approach to suspected stroke between children and adults are also discussed.

Chemical exchange saturation transfer (CEST) magnetic resonance imaging (MRI) quantification of transient ischemia using a combination method of 5-pool Lorentzian fitting and inverse Z-spectrum analysis

Background

Chemical exchange saturation transfer (CEST) is a promising method for the detection of biochemical alterations in cancers and neurological diseases. However, the sensitivity of the currently existing quantitative method for detecting ischemia needs further improvement.

Methods

To further improve the quantification of the CEST signal and enhance the CEST detection for ischemia, we used a quantitative analysis method that combines an inverse Z-spectrum analysis and a 5-pool Lorentzian fitting. Specifically, a 5-pool Lorentzian simulation was conducted with the following brain tissue parameters: water, amide (3.5 ppm), amine (2.2 ppm), magnetization transfer (MT), and nuclear Overhauser enhancement (NOE; -3.5 ppm). The parameters were first calculated offline and stored as the initial value of the Z-spectrum fitting. Then, the measured Z-spectrum with the peak value set to 0 was fitted via the stored initial value, which yielded the reference Z-spectrum. Finally, the difference between the inverse of the Z-spectrum and the inverse of the reference Z-spectrum was used as the CEST definite spectrum.

Results

The simulation results demonstrated that the Z-spectra of the rat brain were well simulated by a 5-pool Lorentzian fitting. Further, the proposed method detected a larger difference than did either the saturation transfer difference or the 5-pool Lorentzian fitting, as demonstrated by simulations. According to the results of the cerebral ischemia rat model, the proposed method provided the highest contrast-to-noise ratio (CNR) between the contralateral and the ipsilateral striatum under various acquisition conditions. The results indicated that the difference of fitted amplitudes generated with a 5-pool Lorentzian fitting in amide at 3.5 ppm (6.04%±0.39%; 6.86%±0.39%) was decreased in a stroke lesion compared to the contralateral normal tissue. Moreover, the difference of the residual of inversed Z-spectra in which 5-pool Lorentzian fitting was used to calculate the reference Z-spectra ( M T R R e x 5 L ) amplitudes in amide at 3.5 ppm (13.83%±2.20%, 15.69%±1.99%) was reduced in a stroke lesion compared to the contralateral normal tissue.

Conclusions

M T R R e x 5 L is predominantly pH-sensitive and is suitable for detecting tissue acidosis following an acute stroke.

Demonstration of pH imaging in acute stroke with endogenous ratiometric chemical exchange saturation transfer magnetic resonance imaging at 2 ppm

pH change is often considered a hallmark of metabolic disruption in diseases such as ischemic stroke and cancer. Chemical exchange saturation transfer (CEST) MRI, particularly amide proton transfer (APT), has emerged as a noninvasive pH imaging approach. However, there are changes in multipool CEST effects besides APT MRI. Our study investigated radiofrequency (RF) amplitude-based ratiometric CEST pH imaging in acute stroke. Briefly, adult male Wistar rats underwent CEST MRI under two RF saturation (B₁ ) levels of 0.75 and 1.5 μT following middle cerebral artery occlusion. Magnetization transfer (MT), direct water saturation, CEST at 2 ppm (CEST@2 ppm), amine (2.75 ppm), and APT (3.5 ppm) effects were resolved with the multipool Lorentzian fitting approach. The ratiometric analysis was measured in the ischemic lesion and the contralateral normal area, which was also correlated with pH-specific MT and the relaxation normalized APT (MRAPT) index. MT, amine CEST effect, and their respective ratiometric indices did not show significant changes in ischemic regions (p > 0.05), as expected. Whereas APT decreased in the ischemic lesion for B₁ of 1.5 μT (p < 0.01), the correlation between the amide ratio with MRAPT index was moderate (r = 0.52, p = 0.02). By comparison, the ischemic tissue showed a significantly increased CEST@2 ppm for both saturation levels from the contralateral normal area (p ≤ 0.01). Importantly, the CEST@2 ppm ratio decreased in the ischemic lesion (p < 0.01), which highly correlated with the MRAPT index (r = 0.93, p < 0.001). To summarize, our study demonstrated the feasibility of endogenous CEST@2 ppm ratiometric imaging of pH upon acute stroke, promising to detect pH changes in metabolic diseases.

High-field ex vivo and in vivo two-dimensional nuclear magnetic resonance spectroscopy in murine brain: Resolving and exploring the molecular environment

The structural and chemical complexities within the brain pose a challenge that few noninvasive techniques can tackle with the dexterity of nuclear magnetic resonance (NMR) spectroscopy. Still, even with the advent of ultrahigh fields and of cryogenically cooled coils for in vivo research, the superposition of metabolic resonances arising from the brain remains a challenge. The present study explores the potential to tackle this milieu using a combination of two-dimensional (2D) NMR techniques, implemented on murine brains in vivo at 15.2 T and ex vivo at 14.1 T. While both experiments were affected by substantial inhomogeneous broadenings conveying distinct elongated lineshapes to the cross-peaks, the ability of increased fields to resolve off-diagonal resonances was clear. A comparison between the corresponding conventional and double quantum-filtered correlated spectroscopy traces enabled an improved assignment of in vivo resonances on the basis of more sensitive ex vivo 2D acquisitions, foremost on the basis of homonuclear cross-relaxation-driven correlations for peaks resonating downfield from water, and of heteronuclear correlations at natural abundance for the upfield protons. With the aid of such 2D correlations approximately 29 metabolites could be resolved and identified. This enhanced resolution was used to explore features related to the metabolites' diffusivities, their exposure to water, and their facility to undergo magnetization transfers to amide/amine/hydroxyl resonances. Cross-peaks from main murine brain biomolecules, including choline, creatine, γ-aminobutyric acid, N-acetyl aspartate, glutamine, and glutamate, showed enhancements in several of these various features, opening interesting vistas about metabolite compartmentalization as viewed by these 2D NMR experiments.

Reassembled saturation transfer (REST) MR images at 2 B1 values for in vivo exchange-dependent imaging of amide and nuclear Overhauser enhancement

PURPOSE

Design an efficient CEST scheme for exchange-dependent images with high contrast-to-noise ratio.

THEORY

Reassembled saturation transfer (REST) signals were defined as Δ $$ \Delta $$ r.Z = r.Z_ref - r.Z_CEST and the reassembled exchange-dependen magnetization transfer ratio r.MTR_Rex  = r.1/Z_ref - r.1/Z_CEST , utilizing the averages over loosely sampled reference frequency offsets as Z_ref and over densely sampled target offsets as Z_CEST . Using r.MTR_Rex measured under 2 B_1,sat values, exchange rate could be estimated.

METHODS

The REST approach was optimized and assessed quantitatively by simulations for various exchange rates, pool concentration, and water T₁ . In vivo evaluation was performed on ischemic rat brains at 7 Tesla and human brains at 3 Tesla, in comparison with conventional asymmetrical analysis, Lorentzian difference (LD), an MTR_{Rex_} LD.

RESULTS

For a broad choice of Δ ω ref $$ \Delta {\omega}_{ref} $$ ranges and numbers, Δr.Z and r.MTR_Rex exhibited comparable quantification features with conventional LD and MTR_Rex _LD, respectively, when B_1,sat  ≤ 1 μT. The subtraction of 2 REST values under distinct B_1,sat values showed linear relationships with exchange rate and obtained immunity to field inhomogeneity and variation in MT and water T₁ . For both rat and human studies, REST images exhibited similar contrast distribution to MTR_Rex _LD, with superiority in contrast-to-noise ratio and acquisition efficiency. Compared with MTR_Rex _LD, 2-B_1,sat subtraction REST images displayed better resistance to B₁ inhomogeneity, with more specific enhanced regions. They also showed higher signals for amide than for nuclear Overhauser enhancement effect in human brain, presumably reflecting the higher increment from faster-exchanging species as B_1,sat increased.

CONCLUSION

Featuring high contrast-to-noise ratio efficiency, REST could be a practical exchange-dependent approach readily applicable to either retrospective Z-spectra analysis or perspective 6-offset acquisition.

Predicting a Favorable (mRS 0-2) or Unfavorable (mRS 3-6) Stroke Outcome by Arterial Spin Labeling and Amide Proton Transfer Imaging in Post-Thrombolysis Stroke Patients

(1) Background: The objective of this study was to determine whether arterial spin labeling (ASL), amide proton transfer (APT), or their combination could distinguish between patients with a low and high modified Rankin Scale (mRS) and forecast the effectiveness of the therapy; (2) Methods: Fifty-eight patients with subacute phase ischemic stroke were included in this study. Based on cerebral blood flow (CBF) and asymmetry magnetic transfer ratio (MTRasym) images, histogram analysis was performed on the ischemic area to acquire imaging biomarkers, and the contralateral area was used as a control. Imaging biomarkers were compared between the low (mRS 0-2) and high (mRS 3-6) mRS score groups using the Mann-Whitney U test. Receiver operating characteristic (ROC) curve analysis was used to evaluate the performance of the potential biomarkers in differentiating between the two groups; (3) Results: The rAPT 50th had an area under the ROC curve (AUC) of 0.728, with a sensitivity of 91.67% and a specificity of 61.76% for differentiating between patients with low and high mRS scores. Moreover, the AUC, sensitivity, and specificity of the rASL max were 0.926, 100%, and 82.4%, respectively. Combining the parameters with logistic regression could further improve the performance in predicting prognosis, leading to an AUC of 0.968, a sensitivity of 100%, and a specificity of 91.2%; (4) Conclusions: The combination of APT and ASL may be a potential imaging biomarker to reflect the effectiveness of thrombolytic therapy for stroke patients, assisting in guiding treatment approaches and identifying high-risk patients such as those with severe disability, paralysis, and cognitive impairment.

In vivo pH mapping with omega plot-based quantitative chemical exchange saturation transfer MRI

PURPOSE

Chemical exchange saturation transfer (CEST) MRI is promising for detecting dilute metabolites and microenvironment properties, which has been increasingly adopted in imaging disorders such as acute stroke and cancer. However, in vivo CEST MRI quantification remains challenging because routine asymmetry analysis (MTRasym ) or Lorentzian decoupling measures a combined effect of the labile proton concentration and its exchange rate. Therefore, our study aimed to quantify amide proton concentration and exchange rate independently in a cardiac arrest-induced global ischemia rat model.

METHODS

The amide proton CEST (APT) effect was decoupled from tissue water, macromolecular magnetization transfer, nuclear Overhauser enhancement, guanidinium, and amine protons using the image downsampling expedited adaptive least-squares (IDEAL) fitting algorithm on Z-spectra obtained under multiple RF saturation power levels, before and after global ischemia. Omega plot analysis was applied to determine amide proton concentration and exchange rate simultaneously.

RESULTS

Global ischemia induces a significant APT signal drop from intact tissue. Using the modified omega plot analysis, we found that the amide proton exchange rate decreased from 29.6 ± 5.6 to 12.1 ± 1.3 s-1 (P < 0.001), whereas the amide proton concentration showed little change (0.241 ± 0.035% vs. 0.202 ± 0.034%, P = 0.074) following global ischemia.

CONCLUSION

Our study determined the labile proton concentration and exchange rate underlying the in vivo APT MRI. The significant change in the exchange rate, but not the concentration of amide proton demonstrated that the pH effect dominates the APT contrast during tissue ischemia.

Amide proton transfer MRI differentiates between progressive multifocal leukoencephalopathy and malignant brain tumors: a pilot study

BACKGROUND

Progressive multifocal leukoencephalopathy (PML) is a demyelinating disease of the central nerve system caused by the John Cunningham virus. On MRI, PML may sometimes appear similar to primary central nervous system lymphoma (PCNSL) and glioblastoma multiforme (GBM). The purpose of this pilot study was to evaluate the potential of amide proton transfer (APT) imaging for differentiating PML from PCNSL and GBM.

METHODS

Patients with PML (n = 4; two men; mean age 52.3 ± 6.1 years), PCNSL (n = 7; four women; mean age 74.4 ± 5.8 years), or GBM (n = 11; 6 men; mean age 65.0 ± 15.2 years) who underwent APT-CEST MRI between January 2021 and September 2022 were retrospectively evaluated. Magnetization transfer ratio asymmetry (MTR_asym) values were measured on APT imaging using a region of interest within the lesion. Receiver operating characteristics curve analysis was used to determine diagnostic cutoffs for MTR_asym.

RESULTS

The mean MTR_asym values were 0.005 ± 0.005 in the PML group, 0.025 ± 0.005 in the PCNSL group, and 0.025 ± 0.009 in the GBM group. There were significant differences in MTR_asym between PML and PCNSL (P = 0.023), and between PML and GBM (P = 0.015). For differentiating PML from PCNSL, an MTR_asym threshold of 0.0165 gave diagnostic sensitivity, specificity, positive predictive value, and negative predictive value of 100% (all). For differentiating PML from GBM, an MTR_asym threshold of 0.015 gave diagnostic sensitivity, specificity, positive predictive value, and negative predictive value of 100%, 90.9%, 80.0%, and 100%, respectively.

CONCLUSION

MTR_asym values obtained from APT imaging allowed patients with PML to be clearly discriminated from patients with PCNSL or GBM.

Quasi-steady-state amide proton transfer (QUASS APT) MRI enhances pH-weighted imaging of acute stroke

PURPOSE

Chemical exchange saturation transfer (CEST) imaging measurement depends not only on the labile proton concentration and pH-dependent exchange rate but also on experimental conditions, including the relaxation delay and radiofrequency (RF) saturation time. Our study aimed to extend a quasi-steady-state (QUASS) solution to a modified multi-slice CEST MRI sequence and test if it provides enhanced pH imaging after acute stroke.

METHODS

Our study derived the QUASS solution for a modified multislice CEST MRI sequence with an unevenly segmented RF saturation between image readout and signal averaging. Numerical simulation was performed to test if the generalized QUASS solution corrects the impact of insufficiently long relaxation delay, primary and secondary saturation times, and multi-slice readout. In addition, multiparametric MRI scans were obtained after middle cerebral artery occlusion, including relaxation and CEST Z-spectrum, to evaluate the performance of QUASS CEST MRI in a rodent acute stroke model. We also performed Lorentzian fitting to isolate multi-pool CEST contributions.

RESULTS

The QUASS analysis enhanced pH-weighted magnetization transfer asymmetry contrast over the routine apparent CEST measurements in both contralateral normal (-3.46% ± 0.62% (apparent) vs. -3.67% ± 0.66% (QUASS), P < 0.05) and ischemic tissue (-5.53% ± 0.68% (apparent) vs. -5.94% ± 0.73% (QUASS), P < 0.05). Lorentzian fitting also showed significant differences between routine and QUASS analysis of ischemia-induced changes in magnetization transfer, amide, amine, guanidyl CEST, and nuclear Overhauser enhancement (-1.6 parts per million) effects.

CONCLUSION

Our study demonstrated that generalized QUASS analysis enhanced pH MRI contrast and improved quantification of the underlying CEST contrast mechanism, promising for further in vivo applications.

Toward In Vivo MRI of the Tissue Proton Exchange Rate in Humans

Quantification of proton exchange rate (kex) is a challenge in MR studies. Current techniques either have low resolutions or are dependent on the estimation of parameters that are not measurable. The Omega plot method, on the other hand, provides a direct way for determining kex independent of the agent concentration. However, it cannot be used for in vivo studies without some modification due to the contributions from the water signal. In vivo tissue proton exchange rate (kex) MRI, based on the direct saturation (DS) removed Omega plot, quantifies the weighted average of kex of the endogenous tissue metabolites. This technique has been successfully employed for imaging the variation in the kex of ex vivo phantoms, as well as in vivo human brains in healthy subjects, and stroke or multiple sclerosis (MS) patients. In this paper, we present a brief review of the methods used for kex imaging with a focus on the development of in vivo kex MRI technique based on the DS-removed Omega plot. We then review the recent clinical studies utilizing this technique for better characterizing brain lesions. We also outline technical challenges for the presented technique and discuss its prospects for detecting tissue microenvironmental changes under oxidative stress.

Chemical Exchange Saturation Transfer for Pancreatic Ductal Adenocarcinoma Evaluation

OBJECTIVES

The aims of the study are to evaluate the feasibility of using pH-sensitive magnetic resonance imaging, chemical exchange saturation transfer (CEST) in pancreatic imaging and to differentiate pancreatic ductal adenocarcinoma (PDAC) with the nontumor pancreas (upstream and downstream) and normal control pancreas.

METHODS

Sixteen CEST images with PDAC and 12 CEST images with normal volunteers were acquired and magnetization transfer ratio with asymmetric analysis were measured in areas of PDAC, upstream, downstream, and normal control pancreas. One-way analysis of variance and receiver operating characteristic curve were used to differentiate tumor from nontumor pancreas.

RESULTS

Areas with PDAC showed higher signal intensity than upstream and downstream on CEST images. The mean (standard deviation) values of magnetization transfer ratio with asymmetric analysis were 0.015 (0.034), -0.044 (0.030), -0.019 (0.027), and -0.037 (0.031), respectively, in PDAC area, upstream, downstream, and nontumor area in patient group and -0.008 (0.024) in normal pancreas. Significant differences were found between PDAC and upstream ( P < 0.001), between upstream and normal pancreas ( P = 0.04). Area under curve is 0.857 in differentiating PDAC with nontumor pancreas.

CONCLUSIONS

pH-sensitive CEST MRI is feasible in pancreatic imaging and can be used to differentiate PDAC from nontumor pancreas. This provides a novel metabolic imaging method in PDAC.

Brain pH Measurement Using AACID CEST MRI Incorporating the 2 ppm Amine Resonance

Many pathological conditions lead to altered intracellular pH (pH_i) disrupting normal cellular functions. The chemical exchange saturation transfer (CEST) method, known as Amine and Amide Concentration Independent Detection (AACID), can produce image contrast that is predominantly dependent on tissue intracellular pH_i. The AACID value is linearly related to the ratio of the 3.5 ppm amide CEST effect and the 2.75 ppm amine CEST effect in the physiological range. However, the amine CEST effect at 2 ppm is often more clearly defined in vivo, and may provide greater sensitivity to pH changes. The purpose of the current study was to compare AACID measurement precision utilizing the 2.0 and 2.75 ppm amine CEST effects. We hypothesized that the 2.0 ppm amine CEST resonance would produce measurements with greater sensitivity to pH changes. In the current study, we compare the range of the AACID values obtained in 24 mice with brain tumors and in normal tissue using the 2 ppm and 2.75 ppm amine resonances. All CEST data were acquired on a 9.4T MRI scanner. The AACID measurement range increased by 39% when using the 2 ppm amine resonance compared to the 2.75 ppm resonance, with decreased measurement variability across the brain. These data indicate that in vivo pH measurements made using AACID CEST can be enhanced by incorporating the 2 ppm amine resonance. This approach should be considered for pH measurements made over short intervals when no changes are expected in the concentration of metabolites that contribute to the 2 ppm amine resonance.

Deep learning-based classification of preclinical breast cancer tumor models using chemical exchange saturation transfer magnetic resonance imaging

Chemical exchange saturation transfer (CEST) magnetic resonance imaging has shown promise for classifying tumors based on their aggressiveness, but CEST contrast is complicated by multiple signal sources and thus prolonged acquisition times are often required to extract the signal of interest. We investigated whether deep learning could help identify pertinent Z-spectral features for distinguishing tumor aggressiveness as well as the possibility of acquiring only the pertinent spectral regions for more efficient CEST acquisition. Human breast cancer cells, MDA-MB-231 and MCF-7, were used to establish bi-lateral tumor xenografts in mice to represent higher and lower aggressive tumors, respectively. A convolutional neural network (CNN)-based classification model, trained on simulated data, utilized Z-spectral features as input to predict labels of different tissue types, including MDA-MB-231, MCF-7, and muscle tissue. Saliency maps reported the influence of Z-spectral regions on classifying tissue types. The model was robust to noise with an accuracy of more than 91.5% for low and moderate noise levels in simulated testing data (SD of noise less than 2.0%). For in vivo CEST data acquired with a saturation pulse amplitude of 2.0 μT, the model had a superior ability to delineate tissue types compared with Lorentzian difference (LD) and magnetization transfer ratio asymmetry (MTRasym ) analysis, classifying tissues to the correct types with a mean accuracy of 85.7%, sensitivity of 81.1%, and specificity of 94.0%. The model's performance did not improve substantially when using data acquired at multiple saturation pulse amplitudes or when adding LD or MTRasym spectral features, and did not change when using saliency map-based partial or downsampled Z-spectra. This study demonstrates the potential of CNN-based classification to distinguish between different tumor types and muscle tissue, and speed up CEST acquisition protocols.

Consistent depiction of the acidic ischemic lesion with APT MRI-Dual RF power evaluation of pH-sensitive image in acute stroke

PURPOSE

Amide proton transfer-weighted (APTw) MRI provides a non-invasive pH-sensitive image, complementing perfusion and diffusion imaging for refined stratification of ischemic tissue. Although the commonly used magnetization transfer (MT) asymmetry (MTR_asym ) calculation reasonably corrects the direct RF saturation effect, it is susceptible to the concomitant semisolid macromolecular MT contribution. Therefore, this study aimed to compare the performance of MTR_asym and magnetization transfer and relaxation-normalized APT (MRAPT) analyses under 2 representative experimental conditions.

METHODS

Multiparametric MRI scans were performed in a rodent model of acute stroke, including relaxation, diffusion, and Z spectral images under 2 representative RF levels of 0.75 and 1.5 µT. Both MTR_asym and MRAPT values in the ischemic diffusion lesion and the contralateral normal areas were compared using correlation and Bland-Altman tests. In addition, the acidic lesion volumes were compared.

RESULTS

MRAPT measurements from the diffusion lesion under the 2 conditions were highly correlated (R² = 0.97) versus MTR_asym measures (R² = 0.58). The pH lesion sizes determined from MRAPT analysis were in good agreement (178 ± 43 mm³ vs. 186 ± 55 mm³ for B₁ of 0.75 and 1.5 µT, respectively).

CONCLUSIONS

The study demonstrated that MRAPT analysis could be generalized to moderately different RF amplitudes, providing a more consistent depiction of acidic lesions than the MTR_asym analysis.

A Fully Convolutional Network (FCN) based Automated Ischemic Stroke Segment Method using Chemical Exchange Saturation Transfer Imaging

BACKGROUND

Chemical exchange saturation transfer (CEST) MRI is a promising imaging modality in ischemic stroke detection for its sensitivity in sensing post-ischemic pH alteration. However, the accurate segmentation of pH-altered regions remains difficult due to the complicated sources in water signal changes of CEST MRI. Meanwhile, manual localization and quantification of stroke lesions are laborious and time-consuming, which cannot meet the urgent need for timely therapeutic interventions.

PURPOSE

The goal of this study was to develop an automatic lesion segmentation approach of ischemic region based on CEST MR images. A novel segmentation framework based on fully convolutional neural network was investigated for our task.

METHODS

Z-spectra from 10 rats were manually labeled as ground truth and split into two datasets, where the training dataset including 3 rats was used to generate a segmentation model, and the remaining rats were used as test datasets to evaluate the model's performance. Then a 1-D fully convolutional neural network equipped with bottleneck structures was set up, and a Grad-CAM approach was used to produce a coarse localization map, which can reflect the relevancy to the 'ischemia' class of each pixel.

RESULTS

As compared with the ground truth, the proposed network model achieved satisfying segmentation results with high values of evaluation metrics including specificity (SPE), sensitivity (SEN), accuracy (ACC), and Dice similarity coefficient (DSC), especially in some intractable situations where conventional MRI modalities and CEST quantitative method failed to distinguish between ischemic and normal tissues, and the model with augmentation was robust to input perturbations. The Grad-CAM maps performed clear tissue change distributions and interpreted the segmentations, and showed a strong correlation with the quantitative method, gave extended thinking to the function of networks.

CONCLUSIONS

The proposed method can segment ischemia region from CEST images, with the Grad-CAM maps give access to interpretative information about the segmentations, which demonstrates great potential in clinical routines. This article is protected by copyright. All rights reserved.

Advanced Imaging Techniques for Differentiating Pseudoprogression and Tumor Recurrence After Immunotherapy for Glioblastoma

Glioblastoma (GBM) is the most common malignant tumor of the central nervous system with poor prognosis. Although the field of immunotherapy in glioma is developing rapidly, glioblastoma is still prone to recurrence under strong immune intervention. The major challenges in the process of immunotherapy are evaluating the curative effect, accurately distinguishing between treatment-related reactions and tumor recurrence, and providing guidance for clinical decision-making. Since the conventional magnetic resonance imaging (MRI) is usually difficult to distinguish between pseudoprogression and the true tumor progression, many studies have used various advanced imaging techniques to evaluate treatment-related responses. Meanwhile, criteria for efficacy evaluation of immunotherapy are constantly updated and improved. A standard imaging scheme to evaluate immunotherapeutic response will benefit patients finally. This review mainly summarizes the application status and future trend of several advanced imaging techniques in evaluating the efficacy of GBM immunotherapy.

A Brief History and Future Prospects of CEST MRI in Clinical Non-Brain Tumor Imaging

Chemical exchange saturation transfer (CEST) MRI is a promising molecular imaging tool which allows the specific detection of metabolites that contain exchangeable amide, amine, and hydroxyl protons. Decades of development have progressed CEST imaging from an initial concept to a clinical imaging tool that is used to assess tumor metabolism. The first translation efforts involved brain imaging, but this has now progressed to imaging other body tissues. In this review, we summarize studies using CEST MRI to image a range of tumor types, including breast cancer, pelvic tumors, digestive tumors, and lung cancer. Approximately two thirds of the published studies involved breast or pelvic tumors which are sites that are less affected by body motion. Most studies conclude that CEST shows good potential for the differentiation of malignant from benign lesions with a number of reports now extending to compare different histological classifications along with the effects of anti-cancer treatments. Despite CEST being a unique 'label-free' approach with a higher sensitivity than MR spectroscopy, there are still some obstacles for implementing its clinical use. Future research is now focused on overcoming these challenges. Vigorous ongoing development and further clinical trials are expected to see CEST technology become more widely implemented as a mainstream imaging technology.

Deep neural network based CEST and AREX processing: Application in imaging a model of Alzheimer's disease at 3 T

PURPOSE

To optimize and apply deep neural network based CEST (deepCEST) and apparent exchange dependent-relaxation (deepAREX) for imaging the mouse brain with Alzheimer's disease (AD) at 3T MRI.

METHODS

CEST and T₁ data of central and anterior brain slices of 10 AD mice and 10 age-matched wild type (WT) mice were acquired at a 3T animal MRI scanner. The networks of deepCEST/deepAREX were optimized and trained on the WT data. The CEST/AREX contrasts of AD and WT mice predicted by the networks were analyzed and further validated by immunohistochemistry.

RESULTS

After optimization and training on CEST data of WT mice, deepCEST/deepAREX could rapidly (~1 s) generate precise CEST and AREX results for unseen CEST data of AD mice, indicating the accuracy and generalization of the networks. Significant lower amide weighted (3.5 ppm) signal related to amyloid β-peptide (Aβ) plaque depositions, which was validated by immunohistochemistry results, was detected in both central and anterior brain slices of AD mice compared to WT mice. Decreased magnetization transfer (MT) signal was also found in AD mice especially in the anterior slice.

CONCLUSION

DeepCEST/deepAREX could rapidly generate accurate CEST/AREX contrasts in animal study. The well-optimized deepCEST/deepAREX have potential for AD differentiation at 3T MRI.

Demonstration of fast multi-slice quasi-steady-state chemical exchange saturation transfer (QUASS CEST) human brain imaging at 3T

PURPOSE

To combine multi-slice chemical exchange saturation transfer (CEST) imaging with quasi-steady-state (QUASS) processing and demonstrate the feasibility of fast QUASS CEST MRI at 3T.

METHODS

Fast multi-slice echo planar imaging (EPI) CEST imaging was developed with concatenated slice acquisition after single radiofrequency irradiation. The multi-slice CEST signal evolution was described by the spin-lock relaxation during saturation duration (T_s ) and longitudinal relaxation during the relaxation delay time (T_d ) and post-label delay (PLD), from which the QUASS CEST was generalized to fast multi-slice acquisition. In addition, numerical simulations, phantom, and normal human subjects scans were performed to compare the conventional apparent and QUASS CEST measurements with different T_s , T_d, and PLD.

RESULTS

The numerical simulation showed that the apparent CEST effect strongly depends on T_s , T_d , and PLD, while the QUASS CEST algorithm minimizes such dependences. In the L-carnosine gel phantom, the proposed QUASS CEST effects (2.68 ± 0.12% [mean ± SD]) were higher than the apparent CEST effects (1.85 ± 0.26%, p < 5e-4). In the human brain imaging, Bland-Altman analysis bias of the proposed QUASS CEST effects was much smaller than the PLD-corrected apparent CEST effects (0.03% vs. -0.54%), indicating the proposed fast multi-slice CEST imaging is robust and accurate.

CONCLUSIONS

The QUASS processing enables fast multi-slice CEST imaging with minimal loss in the measurement of the CEST effect.

Imaging Acute Stroke: From One-Size-Fit-All to Biomarkers

In acute stroke management, time window has been rigidly used as a guide for decades and the reperfusion treatment is only available in the first few limited hours. Recently, imaging-based selection of patients has successfully expanded the treatment window out to 16 and even 24 h in the DEFUSE 3 and DAWN trials, respectively. Recent guidelines recommend the use of imaging techniques to guide therapeutic decision-making and expanded eligibility in acute ischemic stroke. A tissue window is proposed to replace the time window and serve as the surrogate marker for potentially salvageable tissue. This article reviews the evolution of time window, addresses the advantage of a tissue window in precision medicine for ischemic stroke, and discusses both the established and emerging techniques of neuroimaging and their roles in defining a tissue window. We also emphasize the metabolic imaging and molecular imaging of brain pathophysiology, and highlight its potential in patient selection and treatment response prediction in ischemic stroke.

Clinical translation of amide proton transfer (APT) MRI for ischemic stroke: a systematic review (2003-2020)

Amide proton transfer (APT) magnetic resonance imaging (MRI) is a pH-sensitive imaging technique that can potentially complement existing clinical imaging protocol for the assessment of ischemic stroke. This review aims to summarize the developments in the clinical research of APT imaging of ischemic stroke after 17 years of progress since its first preclinical study in 2003. Three electronic databases: PubMed, Scopus, and Cochrane Library were systematically searched for articles reporting clinical studies on APT imaging of ischemic stroke. Only articles in English published between 2003 to 2020 that involved patients presenting ischemic stroke-like symptoms that underwent APT MRI were included. Of 1,093 articles screened, 14 articles met the inclusion criteria with a total of 282 patients that had been scanned using APT imaging. Generally, the clinical studies agreed APT effect to be hypointense in ischemic tissue compared to healthy tissue, allowing for the detection of ischemic stroke. Other uses of APT imaging have also been investigated in the studies, including penumbra identification, predicting long term clinical outcome, and serving as a biomarker for supportive treatment monitoring. The published results demonstrated the potential of APT imaging in these applications, but further investigations and larger trials are needed for conclusive evidence. Future studies are recommended to report the result of asymmetry analysis at 3.5 ppm along with the findings of the study to reduce this contribution to the heterogeneity of experimental methods observed and to facilitate effective comparison of results between studies and centers. In addition, it is important to focus on the development of fast 3D imaging for full volumetric ischemic tissue assessment for clinical translation.

Identification of Tumor-Specific MRI Biomarkers Using Machine Learning (ML)

The identification of reliable and non-invasive oncology biomarkers remains a main priority in healthcare. There are only a few biomarkers that have been approved as diagnostic for cancer. The most frequently used cancer biomarkers are derived from either biological materials or imaging data. Most cancer biomarkers suffer from a lack of high specificity. However, the latest advancements in machine learning (ML) and artificial intelligence (AI) have enabled the identification of highly predictive, disease-specific biomarkers. Such biomarkers can be used to diagnose cancer patients, to predict cancer prognosis, or even to predict treatment efficacy. Herein, we provide a summary of the current status of developing and applying Magnetic resonance imaging (MRI) biomarkers in cancer care. We focus on all aspects of MRI biomarkers, starting from MRI data collection, preprocessing and machine learning methods, and ending with summarizing the types of existing biomarkers and their clinical applications in different cancer types.