Amide Proton Transfer-weighted Imaging Research Articles

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

PurposeAmide 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 methods38 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. ResultsThe 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. ConclusionAPTw imaging is promising to stratify the heterogeneous PWI/DWI mismatch region and benefit the clinical treatment.

Three-Dimensional Gradient-Echo-Based Amide Proton Transfer-Weighted Imaging of Brain Tumors: Comparison With Two-Dimensional Spin-Echo-Based Amide Proton Transfer-Weighted Imaging.

Although amide proton transfer-weighted (APTw) imaging is reported by 2-dimensional (2D) spin-echo-based sequencing, 3-dimensional (3D) APTw imaging can be obtained by gradient-echo-based sequencing. The purpose of this study was to compare the efficacy of APTw imaging between 2D and 3D imaging in patients with various brain tumors. A total of 49 patients who had undergone 53 examinations [5 low-grade gliomas (LGG), 16 high-grade gliomas (HGG), 6 malignant lymphomas, 4 metastases, and 22 meningiomas] underwent APTw imaging using 2D and 3D sequences. The magnetization transfer ratio asymmetry (MTR asym ) was assessed by means of region of interest measurements. Pearson correlation was performed to determine the relationship between MTR asym for the 2 methods, and Student's t test to compare MTR asym for LGG and HGG. The diagnostic accuracy to differentiate HGG from LGG of the 2 methods was compared by means of the McNemar test. Three-dimensional APTw imaging showed a significant correlation with 2D APTw imaging ( r = 0.79, P < 0.0001). The limits of agreement between the 2 methods were -0.021 ± 1.42%. The MTR asym of HGG (2D: 1.97 ± 0.96, 3D: 2.11 ± 0.95) was significantly higher than those of LGG (2D: 0.46 ± 0.89%, P < 0.01; 3D: 0.15 ± 1.09%, P < 0.001). The diagnostic performance of the 2 methods to differentiate HGG from LGG was not significantly different ( P = 1). The potential capability of 3D APTw imaging is equal to or greater than that of 2D APTw imaging and is considered at least as valuable in patients with brain tumors.

Three-Dimensional Amide Proton Transfer-Weighted Imaging for Differentiating between Glioblastoma, IDH-Wildtype and Primary Central Nervous System Lymphoma.

Distinguishing primary central nervous system lymphoma (PCNSL) from glioblastoma, isocitrate dehydrogenase (IDH)-wildtype is sometimes hard. Because the role of operation on them varies, accurate preoperative diagnosis is crucial. In this study, we evaluated whether a specific kind of chemical exchange saturation transfer imaging, i.e., amide proton transfer-weighted (APTw) imaging, was useful to distinguish PCNSL from glioblastoma, IDH-wildtype. A total of 14 PCNSL and 27 glioblastoma, IDH-wildtype cases were evaluated. There was no significant difference in the mean APTw signal values between the two groups. However, the percentile values from the 1st percentile to the 20th percentile APTw signals and the width1-100 APTw signals significantly differed. The highest area under the curve was 0.796, which was obtained from the width1-100 APTw signal values. The sensitivity and specificity values were 64.3% and 88.9%, respectively. APTw imaging was useful to distinguish PCNSL from glioblastoma, IDH-wildtype. To avoid unnecessary aggressive surgical resection, APTw imaging is recommended for cases in which PCNSL is one of the differential diagnoses.

Whole-tumor amide proton transfer-weighted imaging histogram analysis to predict pathological extramural venous invasion in rectal adenocarcinoma: a preliminary study.

To evaluate amide proton transfer-weighted (APTw)-derived whole-tumor histogram analysis parameters in predicting pathological extramural venous invasion (pEMVI) positive status of rectal adenocarcinoma (RA). Preoperative MR including APTw imaging of 125 patients with RA (mean 61.4 ± 11.6years) were retrospectively analyzed. Two radiologists reviewed each case's EMVI status based on the MR-based modified 5-point scale system with conventional MR images. The APTw histogram parameters of primary tumors were obtained automatically using whole-tumor volume histogram analysis. The independent risk factors markedly correlated with pEMVI-positive status were assessed using univariate and multivariate logistic regression analyses. Diagnosis performance was assessed by receiver operating characteristic curve (ROC) analysis. The AUCs were compared using the Delong method. Univariate analysis demonstrated that MR-tumor (T) stage, MR-lymph node (N) stage, APTw-10%, APTw-90%, interquartile range, APTw-minimum, APTw-maximum, APTw-mean, APTw-median, entropy, kurtosis, mean absolute deviation (MAD), and robust MAD were significantly related to pEMVI-positive status (all p < 0.05). Multivariate analysis demonstrated that MR-T stage (OR = 4.864, p = 0.018), MR-N stage (OR = 4.967, p = 0.029), interquartile range (OR = 0.892, p = 0.037), APT-minimum (OR = 1.046, p = 0.031), entropy (OR = 11.604, p = 0.006), and kurtosis (OR = 1.505, p = 0.007) were the independent risk factors enabling prediction of pEMVI-positive status. The AUCs for diagnostic ability of conventional MRI assessment, the APTw histogram model, and the combined model (including APTw histogram and clinical variables) were 0.785, 0.853, and 0.918, respectively. The combined model outperformed the APTw histogram model (p = 0.013) and the conventional MRI assessment (p = 0.006). Whole-tumor histogram analysis of APTw images combined with clinical factors showed better diagnosis efficiency in predicting EMVI involvement in RA. • Rectal adenocarcinomas with pEMVI-positive status are typically associated with higher APTw-SI values. • APTw-minimum, interquartile range, entropy, kurtosis, MR-T stage, and MR-N stage are the independent risk factors for EMVI involvement. • The best prediction for EMVI involvement was obtained with a combined model of APTw histogram and clinical variables (area under the curve, 0.918).

APTw combined with mDixon-Quant imaging to distinguish the differentiation degree of cervical squamous carcinoma.

To investigate the value of amide proton transfer weighted (APTw) imaging combined with modified Dixon fat quantification (mDixon-Quant) imaging in determining the degree of differentiation of cervical squamous carcinoma (CSC) against histopathologic. Magnetic resonance imaging (MRI) data were collected from 52 CSC patients. According to histopathologic results, patients were divided into the poorly differentiated group (37 cases) and the well/moderately differentiated group (15 cases). The APTw value by APTw imaging and the fat fraction (FF) and transverse relaxation rate values by mDixon-Quant were independently measured by two radiologists. Intra-class correlation coefficients (ICCs) were used to test the consistency of APTw, FF, and values measured by the two observers. The Mann-Whitney U test was used to analyze the difference in each parameter between the two groups. Logistic regression analysis was used to assess the association between the degree of differentiation on histopathology and imaging parameters by APTw and mDixon Quant. The ROC curve was used to evaluate the diagnostic efficacy of various parameters and their combination in distinguishing the degree of CSC differentiation on histopathology. The DeLong test was used to access the differences among the area under the ROC curves (AUCs). The Pearson correlation coefficient was used to evaluate the correlation between APTw and mDixon-Quant imaging parameters. The APTw means were 2.95 ± 0.78% and 2.05 (1.85, 2.65)% in the poorly and well/moderately differentiated groups, respectively. The values were 26.62 (21.99, 33.31)/s and 22.93 ± 6.09/s in the poorly and well/moderately differentiated groups, respectively (P < 0.05). The AUCs of APTw, , and their combination were 0.762, 0.686, and 0.843, respectively. The Delong test suggested statistical significance between and the combination of APTw and . values showed a significant correlation with APTw values in the poorly differentiated group. APTw combined with mDixon-Quant can be used to efficiently distinguish the differention degrees of CSC diagnosed on histopathology.

Generalization of quasi-steady-state reconstruction to CEST MRI with two-tiered RF saturation and gradient-echo readout-Synergistic nuclear Overhauser enhancement contribution to brain tumor amide proton transfer-weighted MRI.

While amide proton transfer-weighted (APTw) MRI has been adopted in tumor imaging, there are concurrent APT, magnetization transfer, and nuclear Overhauser enhancement changes. Also, the APTw image is confounded by relaxation changes, particularly when the relaxation delay and saturation time are not sufficiently long. Our study aimed to extend a quasi-steady-state (QUASS) solution to determine the contribution of the multipool CEST signals to the observed tumor APTw contrast. Our study derived the QUASS solution for a multislice CEST-MRI sequence with an interleaved RF saturation and gradient-echo readout between signal averaging. Multiparametric MRI scans were obtained in rat brain tumor models, including T1 , T2 , diffusion, and CEST scans. Finally, we performed spinlock model-based multipool fitting to determine multiple concurrent CEST signal changes in the tumor. The QUASS APTw MRI showed small but significant differences in normal and tumor tissues and their contrast from the acquired asymmetry calculation. The spinlock model-based fitting showed significant differences in semisolid magnetization transfer, amide, and nuclear Overhauser enhancement effects between the apparent and QUASS CEST MRI. In addition, we determined that the tumor APTw contrast is due to synergistic APT increase (+3.5ppm) and NOE decrease (-3.5ppm), with their relative contribution being about one third and two thirds under a moderate B1 of 0.75 μT at 4.7 T. Our study generalized QUASS analysis to gradient-echo image readout and quantified the underlying tumor CEST signal changes, providing an improved elucidation of the commonly used APTw MRI.

Amide Proton Transfer-Weighted Imaging Detects Hippocampal Proteostasis Disturbance Induced by Sleep Deprivation at 7.0 T MRI.

Sleep deprivation leads to hippocampal injury. Proteostasis disturbance is an important mechanism linking sleep deprivation and hippocampal injury. However, identifying noninvasive imaging biomarkers for hippocampal proteostasis disturbance remains challenging. Amide proton transfer-weighted (APTw) imaging is a chemical exchange saturation transfer technique based on the amide protons in proteins and peptides. We aimed to explore the ability of APTw imaging in detecting sleep deprivation-induced hippocampal proteostasis disturbance and its biological significance, as well as its biological basis. In vitro, the feasibility of APTw imaging in detecting changes of the protein state was evaluated, demonstrating that APTw imaging can detect alterations in the protein concentration, conformation, and aggregation state. In vivo, the hippocampal APTw signal declined with increased sleep deprivation time and was significantly lower in sleep-deprived rats than that in normal rats. This signal was positively correlated with the number of surviving neurons counted in Nissl staining and negatively correlated with the expression of glucose-regulated protein 78 evaluated in immunohistochemistry. Differentially expressed proteins in proteostasis network pathways were identified in the hippocampi of normal rats and sleep-deprived rats via mass spectrometry proteomics analysis, providing the biological basis for the change of the hippocampal APTw signal in sleep-deprived rats. These findings demonstrate that APTw imaging can detect hippocampal proteostasis disturbance induced by sleep deprivation and reflect the extent of neuronal injury and endoplasmic reticulum stress.

Preoperative MR radiomics based on high-resolution T2-weighted images and amide proton transfer-weighted imaging for predicting lymph node metastasis in rectal adenocarcinoma.

Lymph node (LN) metastasis is an important prognostic factor in rectal cancer (RC). However, accurate identification of LN metastasis can be challenged for radiologists. The aim of our study was to assess the utility of MRI radiomics based on T2-weighted images (T2WI) and amide proton transfer-weighted(APTw) images for predicting LN metastasis in RC preoperatively. A total of 125 patients with pathologically confirmed rectal adenocarcinoma (RA) from January 2019 to June 2021 who underwent preoperative MR were enrolled in this retrospective study. Radiomics features were extracted from high-resolutionT2WI and APTw images of primary tumor. The most relevant radiomics and clinical features were selected using correlation and multivariate logistic analysis. Radiomics models were built using five machine learning algorithms including support vector machine (SVM), logical regression (LR), k- nearest neighbor (KNN), naive bayes (NB), and random forest (RF). The best algorithm was selected for further establish the clinical- radiomics model. The receiver operating characteristic curve (ROC) analysis was used to assess the performance of radiomics and clinical-radiomics model for predicting LN metastasis. The LR classifier had the best prediction performance, with AUCs of 0.983 (95% CI 0.957-1.000), 0.864 (95% CI 0.729-0.972), 0.851 (95% CI 0.713-0.940) on the training set, validation, and test sets, respectively. In terms of prediction, the clinical-radiomics combined model outperformed the radiomics model. The AUCs of the clinical-radiomics combined model in the validation and test sets were 0.900 (95% CI 0.785-0.986), and 0.929 (95% CI 0.721-0.943), respectively. The radiomics model based on high-resolution T2WI and APTw images can predict LN metastasis accurately in patients with RA.

Three-dimensional amide proton transfer-weighted and intravoxel incoherent motion imaging for predicting bone metastasis in patients with prostate cancer: A pilot study

PurposeTo explore the value of 3-dimensional amide proton transfer-weighted (APTw) and intravoxel incoherent motion (IVIM) imaging in predicting bone metastasis (BM) of prostate cancer (PCa) in addition to routine diffusion-weighted imaging (DWI). MethodsThe clinical and imaging data of 39 PCa patients who were pathologically confirmed in our hospital from March 2019 to February 2022 were retrospectively analyzed, and they were divided into BM-negative (27 patients) and BM-positive (12 patients) groups. MR examination included APTw, DWI and IVIM imaging. The IVIM data was fitted by single-exponential IVIM model (IVIMmono) and double-exponential IVIM model (IVIMbi), respectively. The APTw, ADC, IVIMmono (Dmono, D*mono, and fmono), and IVIMbi (Dbi, D*bi, and fbi) parameters were independently measured by two radiologists. The synthetic minority oversampling technique (SMOTE) was conducted to balance the minority group. Mann-Whitney U test or Student's t-test was used to compare above values between the BM-negative and BM-positive groups. The diagnostic performance was evaluated with receiver operating characteristic (ROC) analysis of each parameter and their combination. The Delong test was used for ROC curve comparison.The relationship between APTw and IVIM was explored through Spearman's rank correlation analysis. ResultsThe APTw and D*mono values were higher, and the ADC, fmono, and fbi values were lower in the BM-positive group than in the BM-negative group (all P < 0.05). Among the individual parameters, the AUC of fmono was the highest (AUC = 0.865), and AUC (fmono) was significantly higher than AUC (fbi), AUC (D*mono), and AUC (ADC) (all P < 0.05). The AUC (IVIMmono) was higher than the AUC (IVIMbi) (P = 0.0068). The combination of APTw and IVIMmono further improved diagnostic capability, and the AUC of APTw+IVIMmono was significantly higher than those of APTw and DWI (all P < 0.05). No correlation was found between IVIM-derived parameters and APTw value. ConclusionBoth 3D APTw and IVIM imaging could predict BM of PCa. IVIM showed better performance than APTw and DWI, and the single-exponential IVIM model was superior to the double-exponential IVIM model. The combination of APTw and IVIM could further improve diagnostic performance.

Identification of ovarian endometriotic cysts in cystic lesions of the ovary by amide proton transfer-weighted imaging and R2∗ mapping

To investigate the value of amide proton transfer weighted (APTw) imaging and R2∗ mapping of cystic fluid in differentiating ovarian endometriotic cysts (OE) from other ovarian cystic (OOC) lesions. A total of 42 patients who underwent 3 T pelvic magnetic resonance imaging (MRI) were enrolled. Nineteen lesions were OE and 27 lesions were OOC. The APTw imaging and R2∗ values of the cystic fluid were measured and compared between the two groups using the independent sample t-test or Mann-Whitney U-test. Receiver operating characteristic (ROC) curves were used to evaluate the diagnostic efficacy of different parameters. The area under ROC curves (AUCs) was compared using the Delong test. Spearman's correlation analysis was used to assess the correlation between APTw imaging and R2∗ values. APTw imaging values of OE were lower, while R2∗ values were higher in OE than those in OOC (p=0.001 and<0.001). The AUCs of APTw imaging and R2∗ values to identify OE from OOC were 0.910 and 0.975. The AUC increased to 0.990 when combining APTw imaging and R2∗ values, yet without a significant difference to the APTw imaging or R2∗ value alone (p=0.229 and 0.082, respectively). APTw imaging values were negatively correlated with R2∗ values (r=-0.522, p<0.001). Both APTw imaging and R2∗ values of OE are significantly different from other ovarian cystic lesions. APTw imaging combined with R2∗ values show excellent diagnostic efficacy to differentiate between OE and OOC.

Amide proton transfer-weighted magnetic resonance imaging for the diagnosis of symptomatic chronic intracranial artery stenosis: a feasibility study.

Hemodynamic changes after intracranial artery stenosis (ICAS) or occlusion are important causes of metabolic alterations in tissue. This study aimed to explore the feasibility of using amide proton transfer-weighted (APTw) magnetic resonance imaging (MRI) to diagnose patients with symptomatic chronic ICAS based on pH variations caused by metabolite damage. Sixty-seven patients with clinically confirmed unilateral anterior circulation ICAS (≥70% arterial narrowing) and 20 healthy volunteers were recruited for the study. Each patient underwent an MRI examination including a T2 fluid-attenuated inversion recovery (T2-FLAIR) sequence, spin-echo echo-planar diffusion-weighted imaging (DWI), three-dimensional pseudo-continuous arterial spin labeling (pcASL), and an APTw sequence. Areas with abnormal perfusion and APTw effects were defined as perfusion/pH matched areas; areas with abnormal perfusion but normal APTw effects were defined as perfusion/pH unmatched areas; the contralateral mirror areas were defined as the normal areas. Regions of interest (ROIs) were selected within these three areas, and the corresponding apparent diffusion coefficient (ADC), cerebral blood flow (CBF), and magnetization transfer ratio asymmetry (MTRasym) were measured. High intraclass correlation coefficient (ICC) values (0.78≤ ICCs ≤0.97; P<0.05) were observed between the two radiologists who independently performed the data analysis. Significant differences were found in CBF and MTRasym between the perfusion/pH matched, perfusion/pH unmatched, and normal areas [F(2,64)=288.5, 163.5; both P<0.05], but the ADC values were comparable between the three [F(2,64)=2.11; P>0.05]. Spearman correlation analysis revealed no significant correlation between changes in MTRasym and CBF (P>0.05). Finally, APTw showed a robust performance in diagnosing symptomatic chronic ICAS, with an area under the receiver operating characteristic curve (ROC) of 0.953 (sensitivity 97.01%; specificity 85.07%; cut-off value 1.005%). The present study has demonstrated that metabolic alterations are present in patients with symptomatic chronic ICAS. Our findings illustrate that APTw imaging could potentially serve as an effective method to provide a robust clinical diagnosis for patients with symptomatic chronic ICAS.

Radiomics analysis of amide proton transfer-weighted and structural MR images for treatment response assessment in malignant gliomas.

The purpose of this study was to evaluate the value of amide proton transfer-weighted (APTw) MRI radiomic features for the differentiation of tumor recurrence from treatment effect in malignant gliomas. Eighty-six patients who had suspected tumor recurrence after completion of chemoradiation or radiotherapy, and who had APTw-MRI data acquired at 3 T, were retrospectively analyzed. Using a fluid-attenuated inversion recovery (FLAIR) image-based mask, radiomics analysis was applied to the processed APTw and structural MR images. A chi-square automatic interaction detector decision tree was used for classification analysis. Models with and without APTw features were built using the same strategy. Tenfold cross-validation was applied to obtain the overall classification performance of each model. Sixty patients were confirmed as having tumor recurrence, and the remainder were confirmed as having treatment effect, at median time points of 190 and 171 days after therapy, respectively. There were 525 radiomic features extracted from each of the processed APTw and structural MR images. Based on these, the APTw-based model yielded the highest accuracy (86.0%) for the differentiation of tumor recurrence from treatment effect, compared with 74.4%, 76.7%, 83.7%, and 76.7% for T1 w, T2 w, FLAIR, and Gd-T1 w, respectively. Model classification accuracy was 82.6% when using the combined structural MR images (T1 w, T2 w, FLAIR, Gd-T1 w), and increased to 89.5% when using these structural plus APTw images. The corresponding sensitivity and specificity were 85.0% and 76.9% for the combination of structural MR images, and 85.0% and 100% after adding APTw image features. Adding APTw-based radiomic features increased MRI accuracy in the assessment of the treatment response in post-treatment malignant gliomas.

Sensitivity and specificity of amide proton transfer-weighted imaging for assessing programmed death-ligand 1 status in non-small cell lung cancer: a comparative study with intravoxel incoherent motion and 18F-FDG PET.

BackgroundNoninvasive assessment of programmed death-ligand 1 (PD-L1) expression status in non-small cell lung cancer (NSCLC) is necessary. This study arm to investigate the value of 2-[18F]-fluoro-2-deoxy-D-glucose positron emission tomography (18F-FDG PET), diffusion-weighted imaging (DWI), intravoxel incoherent motion (IVIM), and amide proton transfer-weighted imaging (APTWI) in the assessment of PD-L1 status in NSCLC.MethodsThis is a prospective diagnostic study. A total of 76 patients with NSCLC underwent chest 18F-FDG PET/magnetic resonance imaging (MRI). Parameters maximum standardized uptake value (SUVmax), quantitate the metabolic tumor volume (MTV), total lesion glycolysis (TLG), apparent diffusion coefficient (ADC), diffusion coefficient (D), pseudo diffusion coefficient (D*), and perfusion fraction (f), and magnetization transfer ratio asymmetry at 3.5 ppm [MTRasym (3.5 ppm)] from 18F-FDG PET, DWI, IVIM, and APTWI, respectively, were compared. The optimal combination of parameters was investigated using logistic regression models and evaluated by area under the receiver operating characteristic (ROC) curve (AUC). The bootstrap with 1,000 samples was used for model validation.ResultsSUVmax, MTV, TLG, and MTRasym (3.5 ppm) were higher and D and f were lower in PD-L1 positive NSCLC than in PD-L1 negative NSCLC (all P<0.05). Logistic analysis showed that the combination of MTRasym (3.5 ppm), D, and SUVmax had the strongest predictive value for the differentiation of PD-L1 positive and PD-L1 negative NSCLC [AUC, 0.946; 95% confidence interval (CI): 0.869–0.985; sensitivity, 85.29%; specificity, 91.67%; P all <0.001]. The verification model showed the combination of MTRasym (3.5 ppm), D, and SUVmax had the strongest predictive value, and its ROC curve and calibration curve showed good accuracy (AUC, 0.919, 95% CI: 0.891–0.937) and consistency.ConclusionsMulti-parametric 18F-FDG PET/MRI is beneficial for the non-invasive assessment of PD-L1 status in NSCLC patients, and the combination of SUVmax, D, and MTRasym (3.5 ppm) may serve as a prognostic biomarker to guide immunotherapy.

3D Amide Proton Transfer-Weighted Imaging for Grading Glioma and Correlating IDH Mutation Status: Added Value to 3D Pseudocontinuous Arterial Spin Labelling Perfusion.

The goal of this study was to evaluate the diagnostic performance of 3D amide proton transfer-weighted (3D-APTW) imaging and 3D pseudocontinuous arterial spin labelling (3D-pCASL) alone and in combination in grading gliomas (low-grade glioma (LGG) vs. high-grade glioma (HGG)) and correlating isocitrate dehydrogenase (IDH) mutation status. Preoperatively, 81 patients with pathologically confirmed gliomas underwent 3.0-T magnetic resonance imaging (MRI) examinations. The APTW, relative APTW (rAPTW), cerebral blood flow (CBF), and relative CBF (rCBF) values were calculated to evaluate the solid components of the tumours. The MRI parameters were compared in the classification of gliomas by independent- and paired-samples t tests. A receiver operating characteristic (ROC) curve was constructed, and the area under the ROC curve (AUC) was calculated to assess the diagnostic performance of each parameter and the combination of the rAPTW and rCBF values. Patients with HGG showed significantly higher APTW, rAPTW, CBF, and rCBF values than those with LGG (all p < 0.001). In the ROC curve analysis, the AUC of rAPTW was the highest at 0.90. By adding the rAPTW signal to the rCBF values, the diagnostic ability of the combined parameters improved from 0.90 to 0.96. The rAPTW value yielded the highest AUC (0.92) in correlating the IDH mutation status, and the diagnostic ability improved to 0.96 by adding it to the rCBF value. 3D-APTW imaging combined with 3D-pCASL imaging may be used to aid assessment of grading glioma and IDH mutation status.

Amide Proton Transfer-Weighted Magnetic Resonance Imaging for Detecting Severity and Predicting Outcome after Traumatic Brain Injury in Rats.

After traumatic brain injury (TBI), early assessment of secondary injury severity is critically important for estimating prognosis and treatment stratification. Currently, secondary injury severity is difficult to estimate. The objective of this study was to investigate the capacity of non-invasive amide proton transfer-weighted (APTw) magnetic resonance imaging (MRI) techniques to assess TBI injury in different brain regions and predict long-term neurobehavior outcomes. Fifty-five male and female rats were subjected to a controlled cortical impact with one of three different impactor depths to produce different degrees of TBI. Multi-parameter MRI data were acquired on a 4.7-Tesla scanner at 1 h, 1 day, and 3 days. Immunofluorescence staining was used to detect activated microglia at 3 days, and neurobehavioral tests were performed to assess long-term outcomes after 28 days. The APTw signal in the injury core at 1 day correlated with deficits in sensorimotor function, the sucrose preference test (a test for anhedonia), and spatial memory function on the Barnes maze. The APTw signal in the perilesion ipsilateral cortex gradually increased after TBI, and the value at 3 days correlated with microglia density at 3 days and with spatial memory decline and anhedonia at 28 days. The correlation between APTw and activated microglia was also observed in the ipsilateral thalamus, and its correlation to memory deficit and depression was evident in other ipsilateral sites. These results suggest that APTw imaging can be used for detecting secondary injury and as a potential predictor of long-term outcomes from TBI.

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

ObjectivesThe 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.MethodsApproximately 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 (APTtumor), the contralateral normal-appearing white matter (APTCNAWM), and the peritumoral edema area (if present, APTedema) and the tumor volume (VAPT) 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.ResultsThe image quality of AF = CS5 was significantly lower than that of other groups. VAPT showed significant differences among the six sequences in meningiomas (p = 0.048) and gliomas (p = 0.023). The pairwise comparison showed that the VAPT 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). APTtumor (p = 0.191) showed no significant difference among the three types of tumors. The APTtumor 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.ConclusionCompressed SENSE could be successfully extended to accelerated 3D APTw imaging of brain tumors without compromising image quality using the AF of 4.

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 -3.5ppm) 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 2h 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.

Review and consensus recommendations on clinical APT-weighted imaging approaches at 3T: Application to brain tumors.

Amide proton transfer‐weighted (APTw) MR imaging shows promise as a biomarker of brain tumor status. Currently used APTw MRI pulse sequences and protocols vary substantially among different institutes, and there are no agreed‐on standards in the imaging community. Therefore, the results acquired from different research centers are difficult to compare, which hampers uniform clinical application and interpretation. This paper reviews current clinical APTw imaging approaches and provides a rationale for optimized APTw brain tumor imaging at 3 T, including specific recommendations for pulse sequences, acquisition protocols, and data processing methods. We expect that these consensus recommendations will become the first broadly accepted guidelines for APTw imaging of brain tumors on 3 T MRI systems from different vendors. This will allow more medical centers to use the same or comparable APTw MRI techniques for the detection, characterization, and monitoring of brain tumors, enabling multi‐center trials in larger patient cohorts and, ultimately, routine clinical use.

Amide Proton Transfer Could Provide More Accurate Lesion Characterization in the Transition Zone of the Prostate.

There is an overlap comparing transition zone prostate cancer (TZ PCa) and benign prostatic hyperplasia (BPH) on T2-weighted imaging (T2WI) and diffusion-weighted imaging (DWI), creating additional challenges for assessment of TZ tumors on MRI. To evaluate whether amide proton transfer-weighted (APTw) imaging provides new diagnostic ideas for TZ PCa. Prospective. A total of 51 TZ PCa patients (age, 49-89), 44 stromal BPH (age, 57-92), and 45 glandular BPH patients (age, 56-92). A 3 T; T2WI turbo spin echo (TSE), quantitative T2*-weighted imaging, DWI echo planar imaging, 3D APTw TSE. Differences in APTw, apparent diffusion coefficient (ADC), and T2* among three lesions were compared by one-way analysis of variance (ANOVA). Regions of interest were drawn by two radiologists (X.Q.Z. and X.Y.Q., with 21 and 15 years of experience, respectively). Multivariable logistic regression analyses; ANOVA with post hoc testing; receiver operator characteristic curve analysis; Delong test. Significance level: P < 0.05. APTw among TZ PCa, stromal BPH, and glandular BPH (3.48% ± 0.83% vs. 2.76% ± 0.49% vs. 2.72% ± 0.45%, respectively) were significantly different except between stromal BPH and glandular BPH (P >0.99). Significant differences were found in ADC (TZ PCa 0.76 ± 0.16 × 10-3 mm2 /sec vs. stromal BPH 0.91 ± 0.14 × 10-3 mm2 /sec vs. glandular BPH 1.08 ± 0.18 × 10-3 mm2 /sec) among three lesions. APTw (OR=12.18, 11.80, respectively) and 1/ADC (OR=703.87, 181.11, respectively) were independent predictors of TZ PCa from BPH and stromal BPH. The combination of APTw and ADC had better diagnostic performance in the identification of TZ PCa from BPH and stromal BPH. APTw imaging has the potential to be of added value to ADC in differentiating TZ PCa from BPH and stromal BPH. 2 TECHNICAL EFFICACY: Stage 2.

Evaluation of Amide Proton Transfer-Weighted Imaging for Risk Factors in Stage I Endometrial Cancer: A Comparison With Diffusion-Weighted Imaging and Diffusion Kurtosis Imaging.

BackgroundEndometrial cancer (EC) is one of the most common gynecologic malignancies in clinical practice. This study aimed to compare the value of diffusion-weighted imaging (DWI), diffusion kurtosis imaging (DKI), and amide proton transfer-weighted imaging (APTWI) in the assessment of risk stratification factors for stage I EC including histological subtype, grade, stage, and lymphovascular space invasion (LVSI).MethodsA total of 72 patients with stage I EC underwent pelvic MRI. The apparent diffusion coefficient (ADC), mean diffusivity (MD), mean kurtosis (MK), and magnetization transfer ratio asymmetry (MTRasym at 3.5 ppm) were calculated and compared in risk groups with the Mann–Whitney U test or independent samples t-test. Spearman’s rank correlation was applied to depict the correlation of each parameter with risk stratification. The diagnostic efficacy was evaluated with receiver operating characteristic (ROC) curve analysis and compared using the DeLong test. A multivariate logistic regression was conducted to explore the optimal model for risk prediction.ResultsThere were significantly greater MTRasym (3.5 ppm) and MK and significantly lower ADC and MD in the non-adenocarcinoma, stage IB, LVSI-positive, high-grade, and non-low-risk groups (all p < 0.05). The MK and MTRasym (3.5 ppm) were moderately positively correlated with risk stratification as assessed by the European Society for Medical Oncology (EMSO) clinical practice guidelines (r = 0.640 and 0.502, respectively), while ADC and MD were mildly negatively correlated with risk stratification (r = −0.358 and −0.438, respectively). MTRasym (3.5 ppm), MD, and MK were identified as independent risk predictors in stage I EC, and optimal predictive performance was obtained with their combinations (AUC = 0.906, sensitivity = 70.97%, specificity = 92.68%). The results of the validation model were consistent with the above results, and the calibration curve showed good accuracy and consistency.ConclusionsAlthough similar performance was obtained with each individual parameter of APTWI, DWI, and DKI for the noninvasive assessment of aggressive behavior in stage I EC, the combination of MD, MK, and MTRasym (3.5 ppm) provided improved predictive power for non-low-risk stage I EC and may serve as a superior imaging marker.