Amide Proton Transfer Imaging Research Articles

Advanced Imaging in the Diagnosis and Response Assessment of High-Grade Glioma: AJR Expert Panel Narrative Review.

This AJR Expert Panel Narrative explores the current status of advanced MRI and PET techniques for the post-therapeutic response assessment of high-grade adult-type gliomas, focusing on ongoing clinical controversies in current practice. Discussed techniques that complement conventional MRI and aid the differentiation of recurrent tumor from post-treatment effects include DWI and diffusion tensor imaging; perfusion MRI techniques including dynamic susceptibility contrast (DSC), dynamic contrast-enhanced MRI, and arterial spin labeling; MR spectroscopy including assessment of 2-hydroxyglutarate (2HG) concentration; glucose- and amino acid (AA)-based PET; and amide proton transfer imaging. Updated criteria for Response Assessment in Neuro-Oncology are presented. Given the abundant supporting clinical evidence, the panel supports a recommendation that routine response assessment after HGG treatment should include perfusion MRI, particularly given the development of a consensus recommended DSC-MRI protocol. Although published studies support 2HG MRS and AA PET, these techniques' widespread adoption will likely require increased availability (for 2HG MRS) or increased insurance funding in the United States (for AA PET). The article concludes with a series of consensus opinions from the author panel, centered on the clinical integration of the advanced imaging techniques into posttreatment surveillance protocols.

Amide proton transfer imaging has added value for predicting extraprostatic extension in prostate cancer patients.

Prostate cancer invades the capsule is a key factor in selecting appropriate treatment methods. Accurate preoperative prediction of extraprostatic extension (EPE) can help achieve precise selection of treatment plans. The aim of this study is to verify the diagnostic efficacy of tumor size, length of capsular contact (LCC), apparent diffusion coefficient (ADC), and Amide proton transfer (APT) value in predicting EPE. Additionally, the study aims to investigate the potential additional value of APT for predicting EPE. This study include 47 tumor organ confined patients (age, 64.16 ± 9.18) and 50 EPE patients (age, 61.51 ± 8.82). The difference of tumor size, LCC, ADC and APT value between groups were compared. Binary logistic regression was used to screen the EPE predictors. The receiver operator characteristic curve analysis was performed to assess the diagnostic performance of variables for predicting EPE. The diagnostic efficacy of combined models (model I: ADC+LCC+tumor size; model II: APT+LCC+tumor size; and model III: APT +ADC+LCC+tumor size) were also analyzed. APT, ADC, tumor size and the LCC were independent predictors of EPE. The area under the curve (AUC) of APT, ADC, tumor size and the LCC were 0.752, 0.665, 0.700 and 0.756, respectively. The AUC of model I, model II, and model III were 0.803, 0.845 and 0.869, respectively. The cutoff value of APT, ADC, tumor size and the LCC were 3.65%, 0.97×10-3mm2/s, 17.30mm and 10.78mm, respectively. The sensitivity/specificity of APT, ADC, tumor size and the LCC were 76%/89.4.0%, 80%/59.6%, 54%/78.9%, 72%/66%, respectively. The sensitivity/specificity of model I, Model II and Model III were 74%/72.3%, 82%/72.5% and 84%/80.9%, respectively. Amide proton transfer imaging has added value for predicting EPE. The combination model of APT balanced the sensitivity and specificity.

B1 Power Modification for Amide Proton Transfer Imaging in Parotid Glands: A Strategy for Image Quality Accommodation and Evaluation of Tumor Detection Feasibility.

In the application of APTw protocols for evaluating tumors and parotid glands, inhomogeneity and hyperintensity artifacts have remained an obstacle. This study aimed to improve APTw imaging quality and evaluate the feasibility of difference B1 values to detect parotid tumors. A total of 31 patients received three APTw sequences to acquire 32 lesions and 30 parotid glands (one patient had lesions on both sides). Patients received T2WI and 3D turbo-spin-echo (TSE) APTw imaging on a 3.0 T scanner for three sequences (B1 = 2 μT, 1 μT, and 0.7 μT in APTw 1, 2, and 3, respectively). APTw image quality was evaluated using four-point Likert scales in terms of integrity and hyperintensity artifacts. Image quality was compared between the three sequences. An evaluable group and a trustable group were obtained for APTmean value comparison. Tumors in both APT2 and APT3 had fewer hyperintensity artifacts than in APT1. With B1 values decreasing, tumors had less integrity in APTw imaging. APTmean values of tumors were higher than parotid glands in traditional APT1 sequence though not significant, while the APTmean subtraction value was significantly different. Applying a lower B1 value could remove hyperintensity but could also compromise its integrity. Combing different APTw sequences might increase the feasibility of tumor detection.

Abstract WMP61: Assessment of Carotid Artery Plaques With Chemical Exchange Saturation Transfer Imaging

Background: Assessing carotid artery plaques in stenosis is crucial for treatment strategies and safety. Chemical exchange saturation transfer (CEST)-MRI, particularly Amide proton transfer (APT) imaging, shows promise in molecular imaging. This study explores the correlation between APT imaging and histopathological findings of carotid artery plaques in 34 consecutive patients who had carotid endarterectomy. We investigated the utility of CEST-MRI as a preoperative plaque diagnostic tool. Methods: APT imaging evaluated plaques prior to the procedures. APT signal values were derived from concentration maps. Plaques were categorized into Group A (APT signal values ≥ 1.90 E-04) and Group B (APT signal values < 1.90 E-04). Postoperative histopathological assessments were conducted on the excised plaques. Histology slides were categorized following AHA’s classification, distinguishing type VI lesions with intraplaque hemorrhage from non-type VI lesions. Results: Type VI lesions accounted for 64.7% (22 cases), while non-type VI lesions were 35.3% (12 cases). Type VI group showed significantly higher mean APT signal values (2.72 ± 1.96 E-04) compared to non-type VI group (0.70 ± 0.59 E-04) (p < 0.001). Pathologically, Group A had a significantly higher proportion of Type VI lesions (100%) than Group B (45%) (p < 0.01). Symptomatic patients or patients with worsening stenosis rates were significantly higher in Group A (75%) than Group B (36%) (p < 0.01). Conclusion: Elevated APT signals were observed in unstable plaques with intraplaque hemorrhage and in plaques of symptomatic or progressive stenosis patients. CEST-MRI evaluation is valuable for assessing plaque characteristics and activity.

The Value of Amide Proton Transfer MRI in the Diagnosis of Malignant and Benign Urinary Bladder Lesions: Comparison With Diffusion-Weighted Imaging.

Conventional magnetic resonance imaging (MRI) has certain limitations in distinguishing between malignant and benign urinary bladder (UB) lesions. Amide proton transfer (APT) imaging may provide more diagnostic information than diffusion-weighted imaging (DWI) to distinguish between malignant and benign UB. To investigate the potential of APT imaging in the diagnosis of malignant and benign UB lesions and to compare its diagnostic efficacy with that of conventional DWI. Prospective. Eighty patients with UB lesions. A 3.0 T/turbo spin echo (TSE) T1-weighted and T2-weighted imaging, single-shot echo planar DWI, and three-dimensional TSE APT imaging. Patients underwent radical cystectomy or transurethral resection of the bladder lesions within 2 weeks after CT urography and MRI examination. APT signal intensity in UB lesions was quantified by the asymmetric magnetization transfer ratio (MTRasym ). MTRasym and apparent diffusion coefficient (ADC) values were measured and compared between malignant and benign UB lesions. Kolmogorov-Smirnov test, Student's t test or Mann-Whitney U test, Spearman rank correlation coefficient, area under the receiver operating characteristic (ROC) curve (AUC), Delong test, and intraclass correlation coefficient (ICC). The significance threshold was set at P < 0.05. Thirty-two patients had pathologically confirmed benign UB lesions, including 2 bladder leiomyomas, 1 submucosal amyloidosis, 1 inflammatory myofibroblastic tumor, and 28 inflammatory lesions, and 48 patients had pathologically confirmed urothelial carcinoma. Urothelial carcinomas showed significantly higher MTRasym values (1.53% [0.74%] vs. 0.85% [0.23%]) and significantly lower ADC values (1.24 ± 0.34 × 10-3  mm2 /s vs. 1.43 ± 0.22 × 10-3  mm2 /s) than benign UB lesions. The MTRasym value (AUC = 0.928) was significantly better in differentiating urothelial carcinoma from benign UB lesions than the ADC value (AUC = 0.722). APT imaging may have value in discriminating malignant from benign UB lesions and has better diagnostic performance than DWI. 3 TECHNICAL EFFICACY: Stage 2.

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

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

Machine learning-based amide proton transfer imaging using partially synthetic training data.

Machine learning (ML) has been increasingly used to quantify CEST effect. ML models are typically trained using either measured data or fully simulated data. However, training with measured data often lacks sufficient training data, whereas training with fully simulated data may introduce bias because of limited simulations pools. This study introduces a new platform that combines simulated and measured components to generate partially synthetic CEST data, and to evaluate its feasibility for training ML models to predict amide proton transfer (APT) effect. Partially synthetic CEST signals were created using an inverse summation of APT effects from simulations and the other components from measurements. Training data were generated by varying APT simulation parameters and applying scaling factors to adjust the measured components, achieving a balance between simulation flexibility and fidelity. First, tissue-mimicking CEST signals along with ground truth information were created using multiple-pool model simulations to validate this method. Second, an ML model was trained individually on partially synthetic data, in vivo data, and fully simulated data, to predict APT effect in rat brains bearing 9 L tumors. Experiments on tissue-mimicking data suggest that the ML method using the partially synthetic data is accurate in predicting APT. In vivo experiments suggest that our method provides more accurate and robust prediction than the training using in vivo data and fully synthetic data. Partially synthetic CEST data can address the challenges in conventional ML methods.

Arterial Spin Labeling and Amide Proton Transfer Imaging can Differentiate Glioblastoma from Brain Metastasis: A Systematic Review and Meta-Analysis

Currently, arterial spin labeling (ASL) and amide proton transfer (APT) imaging have shown potential for distinguishing glioblastoma from brain metastases. Thus, a meta-analysis was conducted to investigate this further. An extensive and comprehensive search was conducted in 6 English and Chinese databases according to predefined inclusion and exclusion criteria, encompassing data up to July 2023. Data from eligible literature were extracted, and bivariate models were employed to calculate pooled sensitivities, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), and area under the curve (AUC) of the summary receiver operating characteristic curve. The meta-analysis included 11 articles. For ASL, the pooled sensitivity was 0.77 (95% confidence interval [CI], 0.63-0.87), and the pooled specificity was 0.87 (95% CI, 0.77-0.93). The pooled PLR was 5.89 (95% CI, 2.97-11.69), the pooled NLR was 0.26 (95% CI, 0.15-0.47), the pooled DOR was 22.33 (95% CI, 6.89-72.34), and AUC was 0.90 (95% CI, 0.87-0.92). For APT imaging, the pooled sensitivity was 0.78 (95% CI, 0.70-0.85), and the pooled specificity was 0.86 (95% CI, 0.77-0.92). The pooled PLR was 5.51 (95% CI, 3.24-9.37), the pooled NLR was 0.25 (95% CI, 0.17-0.37), the pooled DOR was 21.99 (95% CI, 10.28-47.03), and the AUC was 0.90 (95% CI, 0.87-0.92). This meta-analysis suggest that both ASL and APT imaging exhibit high accuracy in distinguishing between glioblastoma and brain metastasis.

Added-value of 3D amide proton transfer MRI in assessing prognostic factors of cervical cancer: a comparative study with multiple model diffusion-weighted imaging.

Amide proton transfer (APT) imaging has been gradually applied to cervical cancer, yet the relationships between APT and multiple model diffusion-weighted imaging (DWI) have yet to be investigated. This study attempted to evaluate the added value of 3-dimensional (3D) APT imaging to multiple model DWI for assessing prognostic factors of cervical cancer. This prospective diagnostic study was conducted in The First Affiliated Hospital of Zhengzhou University. A total of 88 consecutive patients with cervical cancer underwent APT imaging and DWI with 11 b-values (0-2,000 s/mm2). The apparent diffusion coefficient (ADC), pure molecular diffusion (D), perfusion fraction (f), pseudo-diffusion (D*), mean kurtosis (MK), and mean diffusivity (MD) were calculated based on mono-exponential, bi-exponential, and kurtosis models. The mean, minimum, and maximum values of APT signal intensity (APT SI) and DWI-derived metrics were compared based on tumor stages, subtypes, grades, and lymphovascular space invasion status by Student's t-test or Mann-Whitney U test. Receiver operating characteristic (ROC) curve analysis was used to evaluate the diagnostic performance of the parameters. APT SImax, APT SImin, MKmean, and MKmax showed significant differences between adenocarcinoma (AC) and squamous cell carcinoma (SCC) (all P<0.05). APT SImean, APT SImax, and MKmax were higher and ADCmin, Dmean, Dmin, and MDmin were lower in the high-grade tumor than in low-grade tumor (all P<0.05). For distinguishing lymphovascular space invasion, only MKmean showed significant difference (P=0.010). APT SImax [odds ratio (OR) =2.347, P=0.029], APT SImin (OR =0.352; P=0.024), and MKmean (OR =6.523; P=0.001) were the independent predictors for tumor subtype, and APT SImax (OR =2.885; P=0.044), MDmin (OR =0.155, P=0.012) were the independent predictors for histological grade of cervical cancer. When APT SImin and APT SImax was combined with MKmean and MKmax, the diagnostic performance was significantly improved for differentiating AC and AC [area under the curve (AUC): 0.908, sensitivity: 87.5%; specificity: 83.3%; P<0.001]. The combination of APT SImean, APT SImax, ADCmin, MKmax, and MDmin demonstrated the highest diagnostic performance for predicting tumor grade (AUC: 0.903, sensitivity: 78.6%; specificity: 88.9%; P<0.001). Addition of APT to DWI may improve the ability to noninvasively predict poor prognostic factors of cervical cancer.

CEST and nuclear Overhauser enhancement imaging withdeep learning-extrapolated semisolid magnetization transfer reference: Scan-rescan reproducibility andreliability studies.

To develop a novel MR physics-driven, deep-learning, extrapolated semisolid magnetization transfer reference (DeepEMR) framework to provide fast, reliable magnetization transfer contrast (MTC) and CEST signal estimations, and to determine the reproducibility and reliability of the estimates from the DeepEMR. A neural network was designed to predict a direct water saturation and MTC-dominated signal at a certain CEST frequency offset using a few high-frequency offset features in the Z-spectrum. The accuracy, scan-rescan reproducibility, and reliability of MTC, CEST, and relayed nuclear Overhauser enhancement (rNOE) signals estimated from the DeepEMR were evaluated on numerical phantoms and in heathy volunteers at 3 T. In addition, we applied the DeepEMR method to brain tumor patients and compared tissue contrast with other CEST calculation metrics. The DeepEMR method demonstrated a high degree of accuracy in the estimation of reference MTC signals at ±3.5 ppm for APT and rNOE imaging, and computational efficiency (˜190-fold) compared with a conventional fitting approach. In addition, the DeepEMR method achieved high reproducibility and reliability (intraclass correlation coefficient = 0.97, intersubject coefficient of variation = 3.5%, and intrasubject coefficient of variation = 1.3%) of the estimation of MTC signals at ±3.5 ppm. In tumor patients, DeepEMR-based amide proton transfer images provided higher tumor contrast than a conventional MT ratio asymmetry image, particularly at higher B1 strengths (>1.5 μT), with a distinct delineation of the tumor core from normal tissue or peritumoral edema. The DeepEMR approach is feasible for measuring clean APT and rNOE effects in longitudinal and cross-sectional studies with low scan-rescan variability.

Amide proton transfer imaging in rats after heatstroke.

Metabolic acidosis is the most common acid-base change following heatstroke. This study aimed to evaluate the internal environment changes caused by heatstroke using amide proton transfer (APT) imaging. Nineteen male Sprague-Dawley rats were randomly divided into the control group (CTRL, n  = 7) and the heatstroke group (HS, n  = 12). All the rats underwent a 7.0-T MRI, which included T2-weighted imaging (T2WI) and APT imaging. Subsequently, the surviving HS group rats repeated the same magnetic resonance scanning after 25 days and were designated as the follow-up group (FU, n  = 7). APT values were measured in the hippocampus, thalamus, and corpus callosum. The APT values of the three groups were statistically analyzed and found in the hippocampus (CTRL vs. HS, P  = 0.011; CTRL vs. FU, P  = 0.078; HS vs. FU, P  = 0.484; η ² = 0.276), left thalamus (CTRL vs. HS, P  = 0.004; CTRL vs. FU, P  = 0.014; HS vs. FU, P  = 0.822; η ² = 0.331), right thalamus (CTRL vs. HS, P  = 0.003; CTRL vs. FU, P  = 0.015; HS vs. FU P  = 0.769; η ² = 0.336), and corpus callosum (CTRL vs. HS, P  < 0.001; CTRL vs. FU, P  = 0.005; HS vs. FU, P  = 0.523; η ² = 0.437). APT imaging can be a viable and practical tool for diagnosing heatstroke and monitoring its progression.

Role of amide proton transfer imaging in maximizing tumor resection in malignant glioma: a possibility to take the place of 11C-methionine positron emission tomography.

Amide proton transfer (APT) imaging has been proposed as a technique to assess tumor metabolism. However, the relationship between APT imaging and other quantitative modalities including positron emission tomography (PET) has not been investigated in detail. This study aimed to evaluate the clinical usefulness of APT imaging in determining the metabolic status of malignant glioma and to compare findings with those from 11C-methionine (Met)-PET. This research analyzed APT imaging data from 20 consecutive patients with malignant glioma treated between January 2022 and July 2023. Patients underwent tumor resection and correlations between tumor activity and intensity of APT signal were investigated. We also compared 11C-Met-PET and APT imaging for the same regions of the perifocal tumor invasion area. Clear, diagnostic APT images were obtained from all 20 cases. Mean APT intensity (APTmean) was significantly higher in the glioblastoma (GBM), IDH wild type group (27.2 ± 12.8%) than in other gliomas (6.0 ± 4.7%; p < 0.001). The cut-off APTmean to optimally distinguish between GBM and other malignant gliomas was 12.8%, offering 100% sensitivity and 83.3% specificity. These values for APTmean broadly matched the tumor-to-contralateral normal brain tissue ratio from 11C-Met-PET analysis (r = 0.66). The APT signal was also observed in the gadolinium non-contrast region on T1-weighted imaging, appearing to reflect the surrounding tumor-infiltrated area. APT imaging can be used to evaluate the area of tumor invasion, similar to 11C-Met-PET. APT imaging revealed low invasiveness in patients and was useful in preoperative planning for tumor resection, facilitating maximum tumor resection including the tumor invasive area.

Post-Surgical Depositions of Blood Products Are No Major Confounder for the Diagnostic and Prognostic Performance of CEST MRI in Patients with Glioma.

Amide proton transfer (APT) and semi-solid magnetization transfer (ssMT) imaging can predict clinical outcomes in patients with glioma. However, the treatment of brain tumors is accompanied by the deposition of blood products within the tumor area in most cases. For this reason, the objective was to assess whether the diagnostic interpretation of the APT and ssMT is affected by methemoglobin (mHb) and hemosiderin (Hs) depositions at the first follow-up MRI 4 to 6 weeks after the completion of radiotherapy. A total of 34 participants underwent APT and ssMT imaging by applying reconstruction methods described by Zhou et al. (APTwasym), Goerke et al. (MTRRexAPT and MTRRexMT) and Mehrabian et al. (MTconst). Contrast-enhancing tumor (CE), whole tumor (WT), mHb and Hs were segmented on contrast-enhanced T1wCE, T2w-FLAIR, T1w and T2*w images. ROC-analysis, Kaplan-Meier analysis and the log rank test were used to test for the association of mean contrast values with therapy response and overall survival (OS) before (WT and CE) and after correcting tumor volumes for mHb and Hs (CEC and WTC). CEC showed higher associations of the MTRRexMT with therapy response (CE: AUC = 0.677, p = 0.081; CEC: AUC = 0.705, p = 0.044) and of the APTwasym with OS (CE: HR = 2.634, p = 0.040; CEC: HR = 2.240, p = 0.095). In contrast, WTC showed a lower association of the APTwasym with survival (WT: HR = 2.304, p = 0.0849; WTC: HR = 2.990, p = 0.020). Overall, a sophisticated correction for blood products did not substantially influence the clinical performance of APT and ssMT imaging in patients with glioma early after radiotherapy.

Research Progress on Amide Proton Transfer Imaging in Preoperative and Postoperative Glioma Assessment.

Amide proton transfer (APT) imaging is a technique that reflects the level of amide proton transport of hydrogen ions in water to peptides and proteins within the tumour by using magnetic resonance imaging without contrast administration. This technique can more accurately reflect the protein level, pH value, and other relevant information within the tumour. Currently, APT is widely used in glioma research. In this paper, we briefly describe the research progress on this technique.

CEST 2022-three-dimensional amide proton transfer (APT) imaging can identify the changes of cerebral cortex in Parkinson's disease

PurposeAmide proton transfer (APT) imaging has shown its diagnostic and predictive superiority in Parkinson's disease (PD) in our previous studies using 2D APT imaging based on deep nuclei. We hypothesized that the pathophysiological abnormality of PD will change the APT-related parameters in the cerebral cortex, and the signal changes can contribute to accurate diagnosis of PD. Methods34 patients with idiopathic Parkinson's disease (IPD) and 29 age- and sex-matched normal controls (NC) were enrolled in this prospective study. 3D-APT imaging and 3D-T1WI was performed in our participants. A volume-based morphometry algorithm was used and get automated cortical segmentations. Quantitative parameter maps of APT-related metrics were calculated by using SPM and MATLAB. The unpaired Student's t-test or Mann-Whitney U test was used for comparison of these values between IPD and NC groups. The associations between APT-related metrics and clinical assessments were investigated by Spearman correlation analysis. The receiver-operating characteristic (ROC) analysis was used to assess the diagnostic performances. The binary logistic regression model was used to combine the imaging parameters. ResultsThere wasn't any correlations between cortical APT-related signals and clinical assessment, including the H&Y scale, the disease duration, the UPDRS III scores and the MMSE scores. The MTRasym, CESTRnr and MTRRex had significantly higher values (p <0.001, corrected by Bonferroni methods) in the IPD group than NC groups in the region of bilateral and total temporal grey matter. The single parameters achieved the best diagnostic performance among all APT-related metrics was MTRRex on the right temporal grey matter, with an area under the ROC curve (AUC) of 0.865. The combined parameters achieved the highest diagnostic performance (AUC: 0.932). Conclusions3D-APT imaging could identify the changes of the cerebral cortex in Parkinson's disease. The cortical changes of APT-related parameters could potentially serve as imaging biomarkers to aid in the non-invasive diagnosis of PD.

Application of amide proton transfer imaging to pretreatment risk stratification of childhood neuroblastoma: comparison with neuron-specific enolase.

The diagnosis and treatment of childhood neuroblastoma (NB) varies with different risk groups, thus requiring accurate preoperative risk assessment. This study aimed to verify the feasibility of amide proton transfer (APT) imaging in risk stratification of abdominal NB in children, and compare it with the serum neuron-specific enolase (NSE). This prospective study enrolled 86 consecutive pediatric volunteers with suspected NB, and all subjects underwent abdominal APT imaging on a 3T magnetic resonance imaging scanner. A 4-pool Lorentzian fitting model was used to mitigate motion artifacts and separate the APT signal from the contaminating ones. The APT values were measured from tumor regions delineated by two experienced radiologists. The one-way analysis of variance, independent-sample t-test, Mann-Whitney U-test, and receiver operating characteristic analysis were performed to evaluate and compare the risk stratification performance of the APT value and serum NSE index-a routine biomarker of NB in clinics. Thirty-four cases (mean age, 38.6±32.4 months; 5 very-low-risk, 5 low-risk, 8 intermediate-risk and 16 high-risk ones) were included in the final analysis. The APT values were significantly higher in high-risk NB (5.80%±1.27%) than in the non-high-risk group (3.88%±1.01%) composed of the other three risk groups (P<0.001). However, there was no significant difference (P=0.18) in NSE levels between the high-risk (93.05±97.14 ng/mL) and non-high-risk groups (41.45±30.99 ng/mL). The associated area under the curve (AUC) of the APT parameter (AUC =0.89) in differentiating high-risk NB from non-high-risk NB was significantly higher (P=0.03) than that of NSE (AUC =0.64). As an emerging non-invasive magnetic resonance imaging technique, APT imaging has a promising prospect for distinguishing high-risk NB from non-high-risk NB in routine clinical applications.

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

The purpose is to evaluate the relative contribution from confounding factors (T1 weighting and magnetization transfer) to the CEST ratio (CESTR)-quantified amide proton transfer (APT) and nuclear Overhauser enhancement (NOE) (-3.5) in tumors as well as whether the CESTR can reflect the distribution of the solute concentration (fs ). We first provided a signal model that shows the separate dependence of CESTR on these confounding factors and the clean CEST/NOE effects quantified by an apparent exchange-dependent relaxation (AREX) method. We then measured the change in these effects in the 9-L tumor model in rats, through which we calculated the relative contribution of each confounding factor. fs was also fitted, and its correlations with the CESTR and AREX were assessed to evaluate their capabilities to reflect fs . The CESTR-quantified APT shows "positive" contrast in tumors, which arises primarily from R1w at low powers and both R1w and magnetization transfer at high powers. CESTR-quantified NOE (-3.5) shows no or weak contrast in tumors, which is due to the cancelation of R1w and NOE (-3.5), which have opposite contributions. CESTR-quantified APT has a stronger correlation with APT fs than AREX-quantified APT. CESTR-quantified NOE (-3.5) has a weaker correlation with NOE (-3.5) fs than AREX-quantified NOE (-3.5). CESTR reflects a combined effect of T1 weighting and CEST/NOE. Both factors depend on fs , which contributes positively to the dependence of CESTR on fs in APT imaging and enhances its correlation with fs . In contrast, these factors have opposite contributions to its dependence on fs in NOE (-3.5) imaging, thereby weakening the correlation.

Amide Proton Transfer–Chemical Exchange Saturation Transfer Imaging of Intracranial Brain Tumors and Tumor-Like Lesions: Our Experience and a Review

Chemical exchange saturation transfer (CEST) is a molecular magnetic resonance imaging (MRI) method that can generate image contrast based on the proton exchange between labeled protons in solutes and free, bulk water protons. Amide proton transfer (APT) imaging is the most frequently reported amide-proton-based CEST technique. It generates image contrast by reflecting the associations of mobile proteins and peptides resonating at 3.5 ppm downfield from water. Although the origin of the APT signal intensity in tumors is unclear, previous studies have suggested that the APT signal intensity is increased in brain tumors due to the increased mobile protein concentrations in malignant cells in association with an increased cellularity. High-grade tumors, which demonstrate a higher proliferation than low-grade tumors, have higher densities and numbers of cells (and higher concentrations of intracellular proteins and peptides) than low-grade tumors. APT-CEST imaging studies suggest that the APT-CEST signal intensity can be used to help differentiate between benign and malignant tumors and high-grade gliomas and low-grade gliomas as well as estimate the nature of lesions. In this review, we summarize the current applications and findings of the APT-CEST imaging of various brain tumors and tumor-like lesions. We report that APT-CEST imaging can provide additional information on intracranial brain tumors and tumor-like lesions compared to the information provided by conventional MRI methods, and that it can help indicate the nature of lesions, differentiate between benign and malignant lesions, and determine therapeutic effects. Future research could initiate or improve the lesion-specific clinical applicability of APT-CEST imaging for meningioma embolization, lipoma, leukoencephalopathy, tuberous sclerosis complex, progressive multifocal leukoencephalopathy, and hippocampal sclerosis.

Amide proton transfer (APT) imaging of breast cancers and its correlation with biological status

PurposeTo assess the usefulness of amide proton transfer (APT) imaging to predict the biological status of breast cancers. MethodSixty-six patients (age range 31–85 years, mean 58.9 years) with histopathologically proven invasive ductal carcinomas of 2 cm or larger in diameter were included in this study. 3D APT weighted imaging was conducted on a 3 T scanner. Mean APT signal intensity (SI) was analyzed in relation to biological subtypes, Ki-67 labeling index, and nuclear grades (NGs). ResultsThe triple-negative (TN) cancers (n = 10; 2.75 ± 0.42%) showed significantly higher APT SI than the luminal type cancers (n = 48; 1.74 ± 0.83) and HER2 cancers (n = 8; 1.83 ± 0.21) (P = 0.0007, 0.03). APT SI had weakly positive correlation with the Ki-67 labeling index (r = 0.38, P = 0.002). The mean APT SIs were significantly higher for high-Ki-67 (>30%) (n = 31; 2.25 ± 0.70) than low-Ki-67 (≤30%) cancers (n = 35; 1.60 ± 0.79) (P = 0.0007). There was no significant difference in the APT SIs between NG 1–2 (n = 31; 1.71 ± 0.84) and NG 3 (n = 35; 2.08 ± 0.76%) cancers (P = 0.06). ConclusionsTN and high-Ki-67 breast cancers showed high APT SIs. APT imaging can help to predict the biological status of breast cancers.

Comparison and combination of amide proton transfer magnetic resonance imaging and the apparent diffusion coefficient in differentiating the grades of prostate cancer.

More effective risk stratification of prostate cancer (PCa) than that possible with current methods can reduce undertreatment and guard against overtreatment. The aim of this study is to validate the differences and combined effects of amide proton transfer (APT) imaging and apparent diffusion coefficient (ADC) in discriminating the PCa grade group (GG) ≤2 from GG ≥3 PCa. This is an ongoing prospective study conducted in the radiology department of Nanxishan Hospital of Guangxi Zhuang Autonomous Region. Patients pathologically diagnosed with PCa were enrolled consecutively according to the eligibility criteria. A total of 180 patients (age range, 42-92 years) were included in this study. Using histopathology as the reference standard, we placed 71 cases in GG ≤2 (mean age 67.03±8.696 years) and 109 cases in GG ≥3 (age 69.60±9.638 years). Magnetic resonance imaging (MRI) parameters, including APT and ADC values, were analyzed using an independent samples t-test and binary logistic regression analysis stratified with GG. Receiver operating characteristic curve was used to analyze the diagnostic performance for different parameters distinguishing GG ≤2 and GG ≥3. APT [odds ratio (OR) for the transitional zone (TZ) PCa: 3.20, 95% CI: 1.14-8.98, P=0.02; OR for the peripheral zone (PZ) PCa: 86.32, 95% CI: 13.24-562.88, P=0.003] and ADC values (OR for TZ PCa: 89.79; 95% CI: 2.85-2,827.99, P=0.01; OR for PZ PCa: 39.92; 95% CI: 3.22-494.18, P=0.004) were independent predictors that differentiated the GG of patients. The sensitivity and specificity of the APT values were 61.1% and 81.0%, respectively, while the sensitivity and specificity of the ADC values were 83.3% and 61.9%, respectively. The optimal cutoff value of APT was 3.35% and which of ADC was 1.25×10-3 mm2/s in TZ origin PCa. At the optimal cutoff values of 3.31% (APT) and 0.79×10-3 mm2/s (ADC) in PZ PCa, the sensitivity and specificity of the APT values were 74.0% and 83.6%, respectively, while the sensitivity and specificity of the ADC values were 94.0% and 53.4%, respectively. The area under the curve of the combination of APT and ADC was significantly higher than either of APT or ADC alone in Delong test (TZ: P=0.002 and P=0.020; PZ: P=0.033 and P<0.001). APT and ADC have complementary effects on the sensitivity and specificity for identifying different PCa GGs. A combination model of APT and ADC could improve the diagnostic efficacy of PCa differentiation.