Amide Proton Transfer Imaging Research Articles

Effects of amide proton transfer imaging in diagnosis, grading and prognosis prediction of cervical cancer: a systematic review and meta-analysis

PurposeTo assess the effectiveness of Amide Proton Transfer (APT) imaging in predicting the histopathological characteristics of cervical cancer. MethodsA comprehensive literature search was conducted across multiple databases, covering studies until December 27, 2023. The meta-analysis was performed using Stata 15 and Review Manager 5.4 software. Key metrics analyzed included pooled sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), and summary receiver operating characteristic (sROC) curves. The analysis focused on differentiating cervical cancer types, squamous carcinoma differentiation, and lymph node involvement. Meta-regression was employed to investigate heterogeneity. ResultsThirteen studies involving 868 patients were included in the meta-analysis. For differentiating adenocarcinoma from squamous carcinoma, the pooled sensitivity was 0.82 (95%CI: 0.71-0.90), specificity was 0.65 (95%CI: 0.48-0.79), and DOR was 9 (95%CI: 1.6-3.5). When distinguishing poorly differentiated from moderately/well-differentiated squamous carcinoma, the sensitivity was 0.74 (95%CI: 0.66-0.81), specificity was 0.83 (95%CI: 0.75-0.89), and DOR was 14 (95%CI: 8-23). For identifying lymph node involvement, the sensitivity was 0.87 (95%CI: 0.78-0.92), specificity was 0.66 (95%CI: 0.59-0.73), and DOR was 13 (95%CI: 7-26). No publication bias was detected. ConclusionsAPT imaging demonstrates high sensitivity and specificity in distinguishing between cervical cancer types, grading squamous carcinoma, and detecting lymph node involvement. It can be considered a reliable technique for predicting the pathological features of cervical cancer in clinical practice.

Amide proton transfer MRI may reflect effective reperfusion and predict functional outcomes in patients with ischemic stroke.

Perfusion imaging is useful to assess tissue recovery in patients with acute ischemic stroke (AIS); however, it cannot reflect tissue metabolism. We postulated that amide proton transfer (APT) imaging can characterize the tissue status after reperfusion therapy, thus providing prognostic value for 90-day functional outcomes. We included 63 patients with AIS and large-vessel occlusion (LVO). The APT signals, including APT# and NOE# (nuclear Overhauser enhancement) were quantified. Ischemic lesions observed on APT# and diffusion-weighted imaging (DWI) were classified according to their mismatch patterns (APT# < DWI; APT# ≥ DWI). Predictors of 90-day good outcomes (modified Rankin scale score 0-2) were evaluated. Patients with successful reperfusion exhibited higher APT#, smaller percentage change of APT#, and a greater likelihood of presenting APT# < DWI compared to those with poor reperfusion (all P < 0.05). The APT# (odds ratio [OR] = 11.48, P = 0.046) and a mismatch pattern of APT# < DWI (OR = 7.41, P = 0.020) independently predicted good outcomes besides the clinical parameters. A mismatch pattern of APT# ≥ DWI was a significant marker of poor outcomes despite successful reperfusion (P = 0.002). Our study provides preliminary evidence that APT may reveal tissue recovery after reperfusion and predict good outcomes at 90 days in patients with AIS and LVO.

Enhancing amide proton transfer imaging in ischemic stroke using a machine learning approach with partially synthetic data.

Amide proton transfer (APT) imaging, a technique sensitive to tissue pH, holds promise in the diagnosis of ischemic stroke. Achieving accurate and rapid APT imaging is crucial for this application. However, conventional APT quantification methods either lack accuracy or are time-consuming. Machine learning (ML) has recently been recognized as a potential solution to improve APT quantification. In this paper, we applied an ML model trained on a new type of partially synthetic data, along with an optimization approach utilizing recursive feature elimination, to predict APT imaging in an animal stroke model. This partially synthetic datum is not a simple blend of measured and simulated chemical exchange saturation transfer (CEST) signals. Rather, it integrates the underlying components including all CEST, direct water saturation, and magnetization transfer effects partly derived from measurements and simulations to reconstruct the CEST signals using an inverse summation relationship. Training with partially synthetic data requires less in vivo data compared to training entirely with fully synthetic or in vivo data, making it a more practical approach. Since this type of data closely resembles real tissue, it leads to more accurate predictions than ML models trained on fully synthetic data. Results indicate that an ML model trained on this partially synthetic data can successfully predict the APT effect with enhanced accuracy, providing significant contrast between stroke lesions and normal tissues, thus clearly delineating lesions. In contrast, conventional quantification methods such as the asymmetric analysis method, three-point method, and multiple-pool model Lorentzian fit showed inadequate accuracy in quantifying the APT effect. Moreover, ML methods trained using in vivo data and fully synthetic data exhibited poor predictive performance due to insufficient training data and inaccurate simulation pool settings or parameter ranges, respectively. Following optimization, only 13 frequency offsets were selected from the initial 69, resulting in significantly reduced scan time.

The value of amide proton transfer imaging in assessing brain damage in patients with obstructive sleep apnea

ObjectiveTo investigate the application value of amide proton transfer (APT) magnetic resonance imaging in evaluating brain damage in patients with obstructive sleep apnea (OSA). Materials and methods49 OSA patients and 25 healthy individuals matched for age and sex were included as case and control groups. All study participants underwent conventional 3D T1WI and APT imaging of the head. The APT values were measured in each of the brain regions of interest (ROI). To compare the differences in APT values of each brain region between the case and control groups, to compare the differences in the efficacy of APT values of each brain region in diagnosing OSA, and to investigate the correlation between APT values of each brain region and Apnea Hypopnea Index (AHI) and minimum blood oxygen saturation. ResultsCompared to the control group, patients with OSA had elevated APT values in several brain regions (P < 0.05), and the diagnostic efficacy of the combined diagnosis of OSA by multiple brain regions is better than that by each brain region alone.Left frontal APT values were positively correlated with AHI in the case group (r = 0.33, P = 0.020).In the case group, the APT values of bilateral frontal lobe, parietal lobe, occipital lobe, left temporal lobe, right thalamus, left internal capsule, left lenticular nucleus, right cerebellar hemisphere and splenium of corpus callosum were negatively correlated with the minimum blood oxygen saturation, and the APT values for each of the above ROIs were positively correlated. ConclusionAPT imaging has a certain value in evaluating brain damage in OSA patients, which may provide a new objective imaging basis for the clinical diagnosis of OSA.

Advanced imaging techniques and non-invasive biomarkers in pediatric brain tumors: state of the art.

In the pediatric age group, brain neoplasms are the second most common tumor category after leukemia, with an annual incidence of 6.13 per 100,000. Conventional MRI sequences, complemented by CT whenever necessary, are fundamental for the initial diagnosis and surgical planning as well as for post-operative evaluations, assessment of response to treatment, and surveillance; however, they have limitations, especially concerning histopathologic or biomolecular phenotyping and grading. In recent years, several advanced MRI sequences, including diffusion-weighted imaging, diffusion tensor imaging, arterial spin labelling (ASL) perfusion, and MR spectroscopy, have emerged as a powerful aid to diagnosis as well as prognostication; furthermore, other techniques such as diffusion kurtosis, amide proton transfer imaging, and MR elastography are being translated from the research environment to clinical practice. Molecular imaging, especially PET with amino-acid tracers, complement MRI in several aspects, including biopsy targeting and outcome prediction. Finally, radiomics with radiogenomics are opening entirely new perspectives for a quantitative approach aiming at identifying biomarkers that can be used for personalized, precision management strategies.

The value of predicting neoadjuvant chemotherapy early efficacy in nasopharyngeal carcinoma based on amide proton transfer imaging and diffusion weighted imaging.

Early detection of nasopharyngeal carcinoma (NPC) patients who are not sensitive to neoadjuvant chemotherapy (NAC) can guard against overtreatment. This study aimed to evaluate the effectiveness of amide proton transfer (APT) imaging and diffusion-weighted imaging (DWI) in predicting the early response to NAC in patients with NPC. This prospective study enrolled fifty patients with biopsy-confirmed NPC from September 2021 to May 2023. Magnetic resonance imaging (MRI) including APT and DWI, was performed before NAC. After NAC, patients were divided into complete response (CR), partial response (PR), and stable disease (SD) and progressive disease (PD) groups based on the Response Evaluation Criteria in Solid Tumours Version 1.1. The Kruskal-Wallis H test was used for statistical analysis. The differences in APT and apparent diffusion coefficient (ADC) values among the different efficacy groups were compared, the receiver operating characteristic (ROC) curve was drawn for statistically significant parameters, and the area under the curve (AUC) was calculated. Fifty patients (mean age: 47±14 years; 42 males and 8 females) were included in the final analysis (11 were in the CR group, 30 in the PR group, 9 in the SD group, and 0 in the PD group). The ADC values showed no significant differences among the different treatment response groups. The SD group showed significantly lower APTmax (P=0.025), APTskewness (P=0.025) and APT90% (P=0.001) values than the CR and PR groups. Setting APT90% =3.10% as the cut-off value, optimal diagnostic performance (AUC: 0.831; sensitivity: 0.778; specificity: 0.878) was obtained in predicting the SD group. APT imaging can predict the early tumour response to NAC in patients with NPC. APT imaging may be superior to DWI in predicting tumour response.

Amide proton transfer and apparent diffusion coefficient analysis reveal susceptibility of brain regions to neonatal hypoxic-ischemic encephalopathy

PurposeTo identify brain regions affected by Hypoxic-Ischemic Encephalopathy (HIE) in neonates using Amide Proton Transfer (APT) imaging and Apparent Diffusion Coefficient (ADC). Materials and methodsTwenty neonates were divided into HIE and control groups. All neonates were undergoing MRI, including APT and DWI. Imaging analysis was performed using SPM12. The independent-samples t-test was used to analyze the difference in APTw values and ADC values between the mild HIE neonates and the control group. The receiver operating characteristic (ROC) curves were established to assess the diagnostic values of APTw and ADC values in different brain regions for HIE. Pearson's correlation analysis was used to analyze the correlation between APTw values and ADC values for each region. ResultsAPTw values were significantly higher in 26 regions of the HIE group. ADC values were lower in the right anterior temporal lobe and higher in bilateral Subthalamic nucleus in HIE. The APTw values of 22 regions showed very high area under the curve (AUC), whereas the AUC of ADC values in right anterior temporal lobe and right subthalamic nucleus were both 0.802. Notably, the right anterior temporal lobe exhibited significant differences in both APTw and ADC values between the HIE and control groups, additionally, APTw value was significant positive correlated with ADC values in right anterior temporal lobe. ConclusionAPTw and ADC are effective in detecting HIE, with APTw being more sensitive. The right anterior temporal lobe is particularly affected by HIE, with significant changes in APTw and ADC values and a positive correlation between them. This suggests that temporal lobe damage may be critical in the long-term neurological consequences of HIE.

Characterization of carotid plaques using chemical exchange saturation transfer imaging.

The preoperative assessment of carotid plaques is necessary to render revascularization safe and effective. The aim of this study is to evaluate the usefulness of chemical exchange saturation transfer (CEST)-MRI, particularly amide proton transfer (APT) imaging as a preoperative carotid plaque diagnostic tool. We recorded the APT signal intensity on concentration maps of 34 patients scheduled for carotid endarterectomy. Plaques were categorized into group A (APT signal intensity ≥ 1.90 E-04; n = 12) and group B (APT signal intensity < 1.90 E-04; n = 22). Excised plaques were subjected to histopathological assessment and, using the classification promulgated by the American Heart Association, they were classified as intraplaque hemorrhage-positive [type VI-positive (tVI+)] and -negative [no intraplaque hemorrhage (tVI-)]. Of the 34 patients, 22 (64.7%) harbored tVI+- and 12 (35.3%) had tVI- plaques. The median APT signals were significantly higher in tVI+- than tIVI- patients (2.43 E-04 (IQR = 0.98-4.00 E-04) vs 0.54 E-04 (IQR = 0.14-1.09 E-04), p < .001). Histopathologically, the number of patients with tVI+ plaques was significantly greater in group A (100%, n = 12) than group B (45%, n = 22) (p < .01). The number of symptomatic patients or asymptomatic patients with worsening stenosis was also significantly greater in group A than group B (75% vs 36%, p < .01). In unstable plaques with intraplaque hemorrhage and in patients with symptoms or progressive stenosis, the ATP signals were significantly elevated. CEST-MRI studies has the potential for the preoperative assessment of the plaques' characteristics.

The value of amide proton transfer imaging combined with serum CA125 levels in predicting lymph vascular invasion in cervical cancer before surgery.

Preoperative prediction of lymphovascular space invasion (LVSI) is crucial for improving the prognosis of patients with cervical cancer. To evaluate the value of preoperative amide proton transfer (APT) imaging combined with serum CA125 levels for predicting LVSI in cervical cancer. This retrospective study included 80 patients with cervical cancer who underwent preoperative magnetic resonance imaging, including APT imaging. Serum CA125 levels were measured using a fully automated immunoassay analyzer and chemiluminescence method. The presence of LVSI was determined based on the pathological results after surgery. Among the 40 patients who met the requirements, 29 had postoperative pathological confirmation of LVSI, while 11 did not. The areas under the receiver operating characteristic curves (AUC) of preoperative APT and CA125 levels predicting LVSI were 0.889 and 0.687, respectively. When the APT value was 2.9%, the corresponding Youden index was the highest (0.702), with a sensitivity of 79.3% and specificity of 90.9%. When the critical value of the preoperative serum CA15 level was 25.3 u/mL, the corresponding Youden index was the highest (0.508), with a sensitivity of 69.0% and a specificity of 81.8%. The sensitivity and specificity of preoperative APT imaging combined with serum CA125 in predicting LVSI were 82.7% and 100%, respectively, with a Youden's index of 0.828 and an AUC of 0.923. The combination of preoperative APT imaging and serum CA125 levels is valuable for predicting LVSI in cervical cancer. Diagnostic efficacy is highest when the APT value is >2.9% and the serum CA125 level is >25.3 u/mL.

Multimodal imaging evaluation of early neurological deterioration following acute ischemic stroke.

Early neurologic deterioration occurs in up to one-third of patients with acute ischemic stroke (IS), often leading to poor functional outcomes. At present, few studies have applied amide proton transfer (APT) imaging to the evaluation of early neurological deterioration (END). This study analyzed the value of computed tomography perfusion (CTP) combined with multimodal magnetic resonance imaging (MRI) in patients with acute IS with END. This retrospective study included patients with acute IS who were admitted to the neurology inpatient department in a tertiary hospital from October 2021 to June 2023. Patients with acute IS underwent CTP within 24 hours of stroke onset and MRI [arterial spin labeling (ASL), susceptibility-weighted imaging (SWI), and APT] within 7 days. END was defined as an elevation of ≥2 points on the National Institute of Health Stroke Scale (NIHSS) within 7 days of stroke onset. Univariable and multivariable analyses were used to compare clinical and imaging biomarkers in patients with acute IS with and without END. The performance of potential biomarkers in distinguishing between the two groups was evaluated using receiver operating characteristic (ROC) curve analysis. Among the 70 patients with acute IS, 20 (29%) had END. After conducting univariable analysis, variables were selected for entry into a binary logistic regression analysis based on our univariable analysis results, previous research findings, clinical experience, and methodological standards. The results indicated that relative cerebral blood volume (CBV) on CTP, relative cerebral blood flow (CBF) on ASL, and relative signal intensity on amide proton transfer-weighted (APTw) imaging were independent risk factors for END. The areas under the ROC curves for these risk factors were 0.710 [95% confidence interval (CI): 0.559-0.861, P=0.006], 0.839 (95% CI: 0.744-0.933, P<0.001), and 0.804 (95% CI: 0.676-0.932, P<0.001), respectively. The combined area under the curve (AUC), sensitivity, and specificity of the four indices (0.941, 100%, and 78%, respectively) were higher than those of the four indices alone. CTP combined with multi-modal MRI better evaluated hemodynamics, tissue metabolism, and other relevant patient information, providing an objective basis for the clinical assessment of patients with acute IS with END and facilitating the development of accurate and personalized treatment plans.

B1 inhomogeneity corrected CEST MRI based on direct saturation removed omega plot model at 5T.

CEST can image macromolecules/compounds via detecting chemical exchange between labile protons and bulk water. B1 field inhomogeneity impairs CEST quantification. Conventional B1 inhomogeneity correction methods depend on interpolation algorithms, B1 choices, acquisition number or calibration curves, making reliable correction challenging. This study proposed a novel B1 inhomogeneity correction method based on a direct saturation (DS) removed omega plot model. Four healthy volunteers underwent B1 field mapping and CEST imaging under four nominal B1 levels of 0.75, 1.0, 1.5, and 2.0 μT at 5T. DS was resolved using a multi-pool Lorentzian model and removed from respective Z spectrum. Residual spectral signals were used to construct the omega plot as a linear function of 1/ , from which corrected signals at nominal B1 levels were calculated. Routine asymmetry analysis was conducted to quantify amide proton transfer (APT) effect. Its distribution across white matter was compared before and after B1 inhomogeneity correction and also with the conventional interpolation approach. B1 inhomogeneity yielded conspicuous artifact on APT images. Such artifact was mitigated by the proposed method. Homogeneous APT maps were shown with SD consistently smaller than that before B1 inhomogeneity correction and the interpolation method. Moreover, B1 inhomogeneity correction from two and four CEST acquisitions yielded similar results, superior over the interpolation method that derived inconsistent APT contrasts among different B1 choices. The proposed method enables reliable B1 inhomogeneity correction from at least two CEST acquisitions, providing an effective way to improve quantitative CEST MRI.

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 &lt; 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 &lt; 0.001). Pathologically, Group A had a significantly higher proportion of Type VI lesions (100%) than Group B (45%) (p &lt; 0.01). Symptomatic patients or patients with worsening stenosis rates were significantly higher in Group A (75%) than Group B (36%) (p &lt; 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.