Evaluating the Role of Amide Proton Transfer (APT)-Weighted Contrast, Optimized for Normalization and Region of Interest Selection, in Differentiation of Neoplastic and Infective Mass Lesions on 3T MRI

Amide proton transfer weighted contrast has diagnostic capacity in detecting diabetic foot: an MRI-based case-control study

Objective

To evaluate the role of foot muscle amide proton transfer weighted (APTw) contrast and tissue rest perfusion in quantifying diabetic foot (DF) infection and its correlation with blood parameters.

Materials and methods

With approval from an ethical review board, this study included 40 diabetes mellitus (DM) patients with DF and 31 DM patients without DF or other lower extremity arterial disease. All subjects underwent MRI, which included foot sagittal APTw and coronal arterial spin labeling (ASL) imaging. The normalized MTRasym (3.5 ppm) and the ratio of blood flow (rBF) in rest status of the affected side lesions to the non-affected contralateral side were determined. The inter-group differences of these variables were evaluated. Furthermore, the association between normalized MTRasym (3.5 ppm), rBF, and blood parameters [fasting blood glucose (FBG), glycosylated hemoglobin content, C-reactive protein, neutrophil percentage, and white blood cell count] was explored. Using an ROC curve, the diagnostic capacity of normalized MTRasym (3.5 ppm), BF, and blood biochemical markers in differentiating with or without DF in DM was assessed.

Results

In the DF group, MTRasym (3.5 ppm) and BF in lesion and normalized MTRasym (3.5 ppm) were higher than those in the control group (p < 0.05). In addition, correlations were identified between normalized MTRasym (3.5 ppm) and blood parameters, such as C-reactive protein, glycosylated hemoglobin content, FBG, neutrophil ratio, and white blood cell (p < 0.001). Meanwhile, association between BF in lesion and blood parameters, such as C-reactive protein, neutrophil percentage, and FBG (p < 0.01). AUC of normalized MTRasym (3.5 ppm) in identifying with/without DF in patients with DM is 0.986 (95% CI, 0.918-1.00) with the sensitivity of 97.22% and the specificity of 100%.

Conclusion

Normalized MTRasym (3.5 ppm) and the BF in lesion may be treated as a safer and more convenient new indicator to evaluate the tissue infection without using a contrast agent, which may be useful in monitoring and preoperatively assessing DF patients with renal insufficiency.

3D Amide Proton Transfer Weighted Brain Tumor Imaging With Compressed SENSE: Effects of Different Acceleration Factors

Objectives

The aim of the current study was to evaluate the performance of compressed SENSE (CS) for 3D amide proton transfer weighted (APTw) brain tumor imaging with different acceleration factors (AFs), and the results were compared with those of conventional SENSE.

Methods

Approximately 51 patients with brain tumor (22 males, 49.95 ± 10.52 years) with meningiomas (n = 16), metastases (n = 12), or gliomas (n = 23) were enrolled. All the patients received 3D APTw imaging scans on a 3.0 T scanner with acceleration by CS (AFs: CS2, CS3, CS4, and CS5) and SENSE (AF: S1.6). Two readers independently and subjectively evaluated the APTw images relative to image quality and measured confidence concerning image blur, distortion, motion, and ghosting artifacts, lesion recognition, and contour delineation with a 5-point Likert scale. Mean amide proton transfer (APT) values of brain tumors (APT_tumor), the contralateral normal-appearing white matter (APT_CNAWM), and the peritumoral edema area (if present, APT_edema) and the tumor volume (V_APT) were measured for objective evaluation and determination of the optimal AF. The Ki67 labeling index was also measured by using standard immunohistochemical staining procedures in samples from patients with gliomas, and the correlation between tumor APT values and the Ki67 index was analyzed.

Results

The image quality of AF = CS5 was significantly lower than that of other groups. V_APT showed significant differences among the six sequences in meningiomas (p = 0.048) and gliomas (p = 0.023). The pairwise comparison showed that the V_APT values of meningiomas measured from images by CS5 were significantly lower, and gliomas were significantly larger than those by SENSE1.6 and other CS accelerations, (p < 0.05). APT_tumor (p = 0.191) showed no significant difference among the three types of tumors. The APT_tumor values of gliomas measured by APTw images with the SENSE factor of 1.6 and the CS factor of 2, 3, and 4 (except for CS5) were all positively correlated with Ki67.

Conclusion

Compressed SENSE could be successfully extended to accelerated 3D APTw imaging of brain tumors without compromising image quality using the AF of 4.

Differentiation of fibroadenomas versus malignant breast tumors utilizing three-dimensional amide proton transfer weighted magnetic resonance imaging

OBJECTIVE

To explore the value of amide proton transfer-weighted (APTw) magnetic resonance imaging (MRI) for differential diagnosis of fibroadenomas and malignant breast tumors.

MATERIALS AND METHODS

This prospective study enrolled 56 patients with suspected breast tumors and performed APTw imaging. Based on the histopathology results, patients were divided into group 1 with malignant breast tumors (n = 41) and group 2 with fibroadenomas (n = 15). The measured image parameters (APTw value, ADC value, type of Time of Intensity Curve, maximum tumor diameter in image) and the maximal diameter of the tumors measured from surgical resection were compared between the two groups, and the diagnostic performance based on these parameters was quantified with ROC curve. Spearman's correlation coefficient was used to analyze the association between APTw or ADC values and ER, PR, HER2, and Ki-67 expressions.

RESULTS

The intraclass correlation coefficients (ICC = 0.87 and 0.91) indicated a good inter-observer agreement of the measured APTw values. APTw values of malignant lesions were significantly higher than those of fibroadenomas (3.21 ± 1.04% vs 1.50 ± 0.54%, p < 0.001). Area under the curve (AUC) obtained from APTw imaging, DWI, DCE, APTw imaging+DWI, APTw imaging+DWI, and APTw imaging+DWI + DCE was 0.959, 0.897, 0.976, 0.997, and 1 respectively. The APTw value showed a negative correlation with ER expression (r = -0.357).

CONCLUSION

APTw imaging yielded similar diagnosis performance in discriminating fibroadenomas and malignant breast tumors when compared to the DCE and better than DWI imaging, and provided supplement information on tumor cell activity to DWI images. The APTw value showed correlations with some prognostic factors for breast cancer.

CryptoCEST: A promising tool for spatially resolved identification of fungal brain lesions and their differentiation from brain tumors with MRI

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The fungal disaccharide trehalose generates a concentration-dependent CEST MRI contrast.

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CEST MRI can detect endogenous trehalose in Cryptococcus neoformans and C. gattii cells.

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This enables spatially resolved identification of fungal lesions in the mouse brain.

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The CryptoCEST contrast can differentiate cryptococcal brain lesions from gliomas.

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CryptoCEST holds potential for non-invasive differential diagnosis of cryptococcomas.

Infectious brain lesions caused by the pathogenic fungi Cryptococcus neoformans and C. gattii, also referred to as cryptococcomas, could be diagnosed incorrectly as cystic brain tumors if only based on conventional magnetic resonance (MR) images. Previous MR spectroscopy (MRS) studies showed high local concentrations of the fungal disaccharide trehalose in cryptococcomas. The aim of this study was to detect and localize fungal brain lesions caused by Cryptococcus species based on Chemical Exchange Saturation Transfer (CEST) MR imaging of endogenous trehalose, and hereby to distinguish cryptococcomas from gliomas. In phantoms, trehalose and cryptococcal cells generated a concentration-dependent CEST contrast in the 0.2 – 2 ppm chemical shift range, similar to glucose, but approximately twice as strong. In vivo single voxel MRS of a murine cryptococcoma model confirmed the presence of trehalose in cryptococcomas, but mainly for lesions that were large enough compared to the size of the MRS voxel. With CEST MRI, combining the more specific CEST signal at 0.7 ppm with the higher signal-to-noise ratio signal at 4 ppm in the CryptoCEST contrast enabled localization and distinction of cryptococcomas from the normal brain and from gliomas, even for lesions smaller than 1 mm³. Thanks to the high endogenous concentration of the fungal biomarker trehalose in cryptococcal cells, the CryptoCEST contrast allowed identification of cryptococcomas with high spatial resolution and differentiation from gliomas in mice. Furthermore, the CryptoCEST contrast was tested to follow up antifungal treatment of cryptococcomas. Translation of this non-invasive method to the clinic holds potential for improving the differential diagnosis and follow-up of cryptococcal infections in the brain.

Amide proton transfer imaging for differentiation of tuberculomas from high-grade gliomas: Preliminary experience

PURPOSE

Tuberculomas can occasionally masquerade as high-grade gliomas (HGG). Evidence from magnetisation transfer (MT) imaging suggests that there is lower protein content in the tuberculoma microenvironment. Building on the principles of chemical exchange saturation transfer and MT, amide proton transfer (APT) imaging generates tissue contrast as a function of the mobile amide protons in tissue's native peptides and intracellular proteins. This study aimed to further the understanding of tuberculomas using APT and to compare it with HGG.

METHOD

Twenty-two patients (n = 8 tuberculoma; n = 14 HGG) were included in the study. APT was a 3D turbo spin-echo Dixon sequence with inbuilt B₀ correction. A two-second, 2 μT saturation pulse alternating over transmit channels was applied at ±3.5 ppm around water resonance. The APT-weighted image (APTw) was computed as the MT ratio asymmetry (MTR_asym) at 3.5 ppm. Mean MTR_asym values in regions of interest (areas = 9 mm²; positioned in component with homogeneous enhancement/least apparent diffusion coefficient) were used for the analysis.

RESULTS

MTR_asym values of tuberculomas (n = 14; 8 cases) ranged from 1.34% to 3.11% (M = 2.32 ± 0.50). HGG (n = 17;14 cases) showed MTR_asym ranging from 2.40% to 5.70% (M = 4.32 ± 0.84). The inter-group difference in MTR_asym was statistically significant (p < 0.001). APTw images in tuberculomas were notable for high MTR_asym values in the perilesional oedematous-appearing parenchyma (compared to contralateral white matter; p < 0.001).

CONCLUSION

Tuberculomas demonstrate lower MTR_asym ratios compared to HGG, reflective of a relative paucity of mobile amide protons in the ambient microenvironment. Elevated MTR_asym values in perilesional parenchyma in tuberculomas are a unique observation that may be a clue to the inflammatory milieu.

Effect of offset-frequency step size and interpolation methods on chemical exchange saturation transfer MRI computation in human brain

Chemical exchange saturation transfer (CEST) MRI is a non-invasive molecular imaging technique with potential applications in pre-clinical and clinical studies. Applications of amide proton transfer-weighted (APT-w), glutamate-weighted (Glu-w) and creatine-weighted (Cr-w) CEST, among others, have been reported. In general, CEST data are acquired at multiple offset-frequencies. In reported studies, different offset-frequency step sizes and interpolation methods have been used during B₀ inhomogeneity correction of data. The objective of the current study was to evaluate the effects of different step sizes and interpolation methods on CEST value computation. In the current study, simulation (Glu-w, Cr-w and APT-w) and experimental data from the brain were used. Experimental CEST data (Glu-w) were acquired from human volunteers at 7 T and brain tumor patients (APT-w) at 3 T. During B₀ inhomogeneity correction, different interpolation methods (polynomial [degree-1, 2 and 3], cubic-Hermite, cubic-spline and smoothing-spline) were compared. CEST values were computed using asymmetry analysis. The effects of different step sizes and interpolation methods were evaluated using coefficient of variation (CV), normalized mean square error (nMSE) and coefficient of correlation parameters. Additionally, an optimum interpolation method for APT-w values was selected based upon fitting accuracy, T-test, receiver operating characteristic analysis, and its diagnostic performance in differentiating low-grade and high-grade tumors. CV and nMSE increase with an increase in step size irrespective of the interpolation method (except for cubic-Hermite and cubic-spline). The nMSE of Cr-w and Glu-w CEST values were least for polynomial (degree-2 and 3). The quality of Glu-w CEST maps became coarse with the increase in step size. There was a significant difference (P < .05) between low-grade and high-grade tumors using polynomial interpolation (degree-1, 2 and 3); however, linear interpolation outperforms other methods for APT-w data, providing the highest sensitivity and specificity. In conclusion, depending upon the saturation parameters and field strength, optimization of step size and interpolation should be carried out for different CEST metabolites/molecules. Glu-w, Cr-w and APT-w CEST data should be acquired with a step size of between 0.2 and 0.3 ppm. For B₀ inhomogeneity correction, polynomial (degree-2) should be used for Glu-w and Cr-w CEST data at 7 T and linear interpolation should be used for APT-w data at 3 T for a limited frequency range.

The role of APT imaging in gliomas grading: A systematic review and meta-analysis

PURPOSE

Gliomas are diagnosed and staged by conventional MRI. Although non-conventional sequences such as perfusion-weighted MRI may differentiate low-grade from high-grade gliomas, they are not reliable enough yet. The latter is of paramount importance for patient management. In this regard, we aim to evaluate the role of Amide Proton Transfer (APT) imaging in grading gliomas as a non-invasive tool to provide reliable differentiation across tumour grades.

METHODS

A systematic search of PubMed, Medline and Embase was conducted to identify relevant publications between 01/01/2008 and 15/09/2020. Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) was used to assess studies' quality. A random-effects model standardized mean difference meta-analysis was performed to assess APT's ability to differentiate low-grade gliomas (LGGs) from high-grade gliomas (HGGs), WHO 2-4 grades, wild-type from mutated isocitrate dehydrogenase (IDH) gliomas, methylated from unmethylated O6-methylguanine-DNA methyltransferase (MGMT) gliomas. Area under the curve (AUC) of the Receiver Operating Characteristic (ROC) meta-analysis was employed to assess the diagnostic performance of APT.

RESULTS

23 manuscripts met the inclusion criteria and reported the use of APT to differentiate glioma grades with histopathology as reference standard. APT-weighted signal intensity can differentiate LGGs from HGGs with an estimated size effect of (-1.61 standard deviations (SDs), p < 0.0001), grade 2 from grade 3 (-1.83 SDs, p = 0.005), grade 2 from grade 4 (-2.34 SDs, p < 0.0001) and IDH wild-type from IDH mutated (0.94 SDs, p = 0.003) gliomas. The combined AUC of 0.84 highlights the good diagnostic performance of APT-weighted imaging in differentiating LGGs from HGGs.

CONCLUSIONS

APT imaging is an exciting prospect in differentiating LGGs from HGGs and with potential to predict the histopathological grade. However, more studies are required to optimize and improve its reliability.

Advanced multimodality MR imaging of a cerebral nocardiosis abscess in an immunocompetent patient with a focus on Amide Proton Transfer weighted imaging

Cerebral nocardiosis abscess is a very rare entity in an immunocompetent patient. In this case report multiparametric and multimodality MR imaging characteristics of a pyogenic brain abscess caused by Nocardia Farcinica are discussed with a specific focus on amide proton transfer weighted imaging as a modern non-invasive, molecular MR imaging method which detects endogenous mobile protein and peptide concentration and tissue pH changes in pathologic brain lesions. The imaging characteristics are reviewed and discussed in respect to possible differential diagnoses, especially malignant tumorous lesions.

A Novel Intelligent System for Brain Tumor Diagnosis Based on a Composite Neutrosophic-Slantlet Transform Domain for Statistical Texture Feature Extraction

Discrete wavelet transform (DWT) is often implemented by an iterative filter bank; hence, a lake of optimization of a discrete time basis is observed with respect to time localization for a constant number of zero moments. This paper discusses and presents an improved form of DWT for feature extraction, called Slantlet transform (SLT) along with neutrosophy, a generalization of fuzzy logic, which is a relatively new logic. Thus, a novel composite NS-SLT model has been suggested as a source to derive statistical texture features that used to identify the malignancy of brain tumor. The MR images in the neutrosophic domain are defined using three membership sets, true (T), false (F), and indeterminate (I); then, SLT was applied to each membership set. Three statistical measurement-based methods are used to extract texture features from images of brain MRI. One-way ANOVA has been applied as a method of reducing the number of extracted features for the classifiers; then, the extracted features are subsequently provided to the four neural network classification techniques, Support Vector Machine Neural Network (SVM-NN), Decision Tree Neural Network (DT-NN), K-Nearest Neighbor Neural Network (KNN-NN), and Naive Bayes Neural Networks (NB-NN), to predict the type of the brain tumor. Meanwhile, the performance of the proposed model is assessed by calculating average accuracy, precision, sensitivity, specificity, and Area Under the Curve (AUC) of the Receiver Operating Characteristic (ROC) curve. The experimental results demonstrate that the proposed approach is quite accurate and efficient for diagnosing brain tumors when the Gray Level Run Length Matrix (GLRLM) features derived from the composite NS-SLT technique is used.

Amide Proton Transfer-Weighted (APTw) Imaging of Intracranial Infection in Children: Initial Experience and Comparison with Gadolinium-Enhanced T1-Weighted Imaging

Purpose

To evaluate the performance of amide proton transfer-weighted (APTw) imaging against the reference standard of gadolinium-enhanced T1-weighted imaging (Gd-T1w) in children with intracranial infection.

Materials and Methods

Twenty-eight pediatric patients (15 males and 13 females; age range 1-163 months) with intracranial infection were recruited in this study. 2D APTw imaging and conventional MR sequences were conducted using a 3 T MRI scanner. Kappa (κ) statistics and the McNemar test were performed to determine whether the hyperintensity on APTw was related to the enhancement on Gd-T1w. The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of APTw imaging to predict lesion enhancement were calculated.

Result

In twelve patients with brain abscesses, the enhancing rim of the abscesses on the Gd-T1w images was consistently hyperintense on the APTw images. In eight patients with viral encephalitis, three showed slight spotted gadolinium enhancement, while the APTw image also showed a slight spotted high signal. Five of these patients showed no enhancement on Gd-T1w and isointensity on the APTw image. In eleven patients with meningitis, increased APTw signal intensities were clearly visible in gadolinium-enhancing meninges. Sixty infectious lesions (71%) showed enhancement on Gd-T1w images. The sensitivity and specificity of APTw were 93.3% (56/60) and 91.7% (22/24). APTw demonstrated excellent agreement (κ = 0.83) with Gd-T1w, with no significant difference (P = 0.69) in detection of infectious lesions.

Conclusions

These initial data show that APTw MRI is a noninvasive technique for the detection and characterization of intracranial infectious lesions. APTw MRI enabled similar detection of infectious lesions to Gd-T1w and may provide an injection-free means of evaluation of intracranial infection.

Evaluating the feasibility of creatine-weighted CEST MRI in human brain at 7 T using a Z-spectral fitting approach

The current study aims to evaluate the feasibility of creatine (Cr) chemical exchange saturation transfer (CEST)-weighted MRI at 7 T in the human brain by optimizing the saturation pulse parameters and computing contrast using a Z-spectral fitting approach. The Cr-weighted (Cr-w) CEST contrast was computed from phantoms data. Simulations were carried out to obtain the optimum saturation parameters for Cr-w CEST with lower contribution from other brain metabolites. CEST-w images were acquired from the brains of four human subjects at different saturation parameters. The Cr-w CEST contrast was computed using both asymmetry analysis and Z-spectra fitting approaches (models 1 and 2, respectively) based on Lorentzian functions. For broad magnetization transfer (MT) effect, Gaussian and Super-Lorentzian line shapes were also evaluated. In the phantom study, the Cr-w CEST contrast showed a linear dependence on concentration in physiological range and a nonlinear dependence on saturation parameters. The in vivo Cr-w CEST map generated using asymmetry analysis from the brain represents mixed contrast with contribution from other metabolites as well and relayed nuclear Overhauser effect (rNOE). Simulations provided an estimate for the optimum range of saturation parameters to be used for acquiring brain CEST data. The optimum saturation parameters for Cr-w CEST to be used for brain data were around B_1rms  = 1.45 μT and duration = 2 seconds. The Z-spectral fitting approach enabled computation of individual components. This also resulted in mitigating the contribution from MT and rNOE to Cr-w CEST contrast, which is a major source of underestimation in asymmetry analysis. The proposed modified z-spectra fitting approach (model 2) is more stable to noise compared with model 1. Cr-w CEST contrast obtained using fitting was 6.98 ± 0.31% in gray matter and 5.45 ± 0.16% in white matter. Optimal saturation parameters reduced the contribution from other CEST effects to Cr-w CEST contrast, and the proposed Z-spectral fitting approach enabled computation of individual components in Z-spectra of the brain. Therefore, it is feasible to compute Cr-w CEST contrast with a lower contribution from other CEST and rNOE.