Accelerated CEST imaging through deep learning quantification from reduced frequency offsets.

PURPOSE: To shorten CEST acquisition time by leveraging Z-spectrum undersampling combined with deep learning for CEST map construction from undersampled Z-spectra. METHODS: Fisher information gain analysis identified optimal frequency offsets (termed "Fisher offsets") for the multi-pool fitting model, maximizing information gain for the amplitude and the FWHM parameters. These offsets guided initial subsampling levels. A U-NET, trained on undersampled brain CEST images from 18 volunteers, produced CEST maps at 3 T with varied undersampling levels. Feasibility was first tested using retrospective undersampling at three levels, followed by prospective in vivo undersampling (15 of 53 offsets), reducing scan time significantly. Additionally, glioblastoma grade IV pathology was simulated to evaluate network performance in patient-like cases. RESULTS: Traditional multi-pool models failed to quantify CEST maps from undersampled images (structural similarity index [SSIM] <0.2, peak SNR <20, Pearson r <0.1). Conversely, U-NET fitting successfully addressed undersampled data challenges. The study suggests CEST scan time reduction is feasible by undersampling 15, 25, or 35 of 53 Z-spectrum offsets. Prospective undersampling cut scan time by 3.5 times, with a maximum mean squared error of 4.4e-4, r = 0.82, and SSIM = 0.84, compared to the ground truth. The network also reliably predicted CEST values for simulated glioblastoma pathology. CONCLUSION: The U-NET architecture effectively quantifies CEST maps from undersampled Z-spectra at various undersampling levels.

Using amide proton transfer-weighted magnetic resonance imaging (MRI) in peritumor tissue to predict parametrial infiltration of cervical cancer: a case-control study.

Background: Parametrial infiltration (PMI) is an important indicator for staging and treatment of cervical cancer (CC). The potential of amide proton transfer-weighted (APTw) parameters of peritumor tissue in predicting PMI is still uncertain. This study aims to explore whether the APTw parameters of peritumor tissue can improve diagnostic value of diffusion-weighted imaging (DWI) in magnetic resonance imaging (MRI). Methods: Eighty-one patients with pathologic analysis-confirmed CC were enrolled in this retrospective study. All patients underwent APTw MRI and DWI. The APTw values of tumor (APTw-t), APTw values in peritumor tissues (APTw-p) and apparent diffusion coefficient (ADC) values were independently reviewed by two radiologists to map the regions of interest and measure the corresponding values. Receiver operating characteristic curves were generated to evaluate the diagnostic performance of these quantitative parameters. Results: The study patients were divided into the PMI group (n=22) and non-PMI group (n=59). The APTw-t and APTw-p values (%) of PMI group were higher than those of the non-PMI group [3.71 (interquartile range, IQR, 3.60-3.98) and 2.75 (IQR, 2.68-2.77) vs. 3.33 (IQR, 3.24-3.60) and 1.98 (IQR, 1.82-2.36); P<0.001]. The ADC values of PMI group were lower than those of non-PMI group [0.88 (IQR, 0.83-0.94) ×10-3 vs. 0.95 (IQR, 0.88-1.04)×10-3 mm2/sec; P<0.001]. The area under the curve (AUC) of APTw-t, APTw-p and ADC value for PMI diagnosis were 0.810, 0.831 and 0.806 respectively. In addition, the AUC value (0.918) of APTw-p + ADC was optimal, with a sensitivity and specificity of 91.20% and 87.20% respectively. Conclusions: APTw in peritumor tissues, combined with ADC value can be used to efficiently distinguish PMI of CC.

Amide proton transfer-weighted and arterial spin labeling imaging may improve differentiation between high-grade glioma recurrence and radiation-induced brain injury.

Rationale and objectives: The management of tumor recurrence (TR) and radiation-induced brain injury (RIBI) poses significant challenges, necessitating the development of effective differentiation strategies. In this study, we investigated the potential of amide proton transfer-weighted (APTw) and arterial spin labeling (ASL) imaging for discriminating between TR and RIBI in patients with high-grade glioma (HGG). Methods: A total of 64 HGG patients receiving standard treatment were enrolled in this study. The patients were categorized based on secondary pathology or MRI follow-up results, and the demographic characteristics of each group were presented. The APTw, rAPTw, cerebral blood flow (CBF) and rCBF values were quantified. The differences in various parameters between TR and RIBI were assessed using the independent-samples t-test. The discriminative performance of these MRI parameters in distinguishing between the two conditions was assessed using receiver operating characteristic (ROC) curve analysis. Additionally, the Delong test was employed to further evaluate their discriminatory ability. Results: The APTw and CBF values of TR were significantly higher compared to RIBI (P < 0.05). APTw MRI demonstrated superior diagnostic efficiency in distinguishing TR from RIBI (area under the curve [AUC]: 0.864; sensitivity: 75.0 %; specificity: 81.8 %) when compared to ASL imaging. The combined utilization of APTw and CBF value further enhanced the AUC to 0.922. The Delong test demonstrated that the combination of APTw and ASL exhibited superior performance in the identification of TR and RIBI, compared to ASL alone (P = 0.048). Conclusion: APTw exhibited superior diagnostic efficacy compared to ASL in the evaluation of TR and RIBI. Furthermore, the combination of APTw and ASL exhibits greater discriminatory capability and diagnostic performance.

Feasibility of Amide Proton Transfer-Weighted Imaging at 3T for Renal Masses: A Preliminary Study.

BACKGROUND: To investigate the optimal B1,rms value of renal amide proton transfer-weighted (APTw) images and the reproducibility of this value, and to explore the utility of APT imaging of renal masses and kidney tissues. METHODS: APTw images with different B1,rms values were repeatedly recorded in 15 healthy volunteers to determine the optimal value. Two 4-point Likert scales (poor [1] to excellent [4]) were used to evaluate contour clarity and artifacts in masses and normal tissues. The APTw values of masses and normal tissues were then compared in evaluable images (contour clarity score > 1, artifacts score > 1). The APTw of malignant masses, normal tissues, and benign masses were calculated and compared with the Mann-Whitney U test. RESULTS: The optimal scanning parameter of B1,rms was 2 µT, and the APTw images had good agreement in the volunteers. Our study of APTw imaging examined 70 renal masses (13 benign, 57 malignant) and 49 normal kidneys (including those from 15 healthy volunteers). The mean APTw value for renal malignant masses (2.28(1.55)) was different from that for benign masses (0.91(1.30)) (P<0.001), renal cortex (1.30 (1.25)) (P<0.001), renal medulla (1.64 (1.33)) (P<0.05), and renal pelvis (5.49 (2.65)) (P<0.001). CONCLUSION: These preliminary data demonstrate that APTw imaging of the kidneys has potential use as an imaging biomarker for the differentiation of normal tissues, malignant masses, and benign masses.

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

Objective: To evaluate the role of foot muscle amide proton transfer weighted (APTw) contrast and tissue rest perfusion in quantifying diabetic foot (DF) infection and its correlation with blood parameters. Materials and methods: With approval from an ethical review board, this study included 40 diabetes mellitus (DM) patients with DF and 31 DM patients without DF or other lower extremity arterial disease. All subjects underwent MRI, which included foot sagittal APTw and coronal arterial spin labeling (ASL) imaging. The normalized MTRasym (3.5 ppm) and the ratio of blood flow (rBF) in rest status of the affected side lesions to the non-affected contralateral side were determined. The inter-group differences of these variables were evaluated. Furthermore, the association between normalized MTRasym (3.5 ppm), rBF, and blood parameters [fasting blood glucose (FBG), glycosylated hemoglobin content, C-reactive protein, neutrophil percentage, and white blood cell count] was explored. Using an ROC curve, the diagnostic capacity of normalized MTRasym (3.5 ppm), BF, and blood biochemical markers in differentiating with or without DF in DM was assessed. Results: In the DF group, MTRasym (3.5 ppm) and BF in lesion and normalized MTRasym (3.5 ppm) were higher than those in the control group (p < 0.05). In addition, correlations were identified between normalized MTRasym (3.5 ppm) and blood parameters, such as C-reactive protein, glycosylated hemoglobin content, FBG, neutrophil ratio, and white blood cell (p < 0.001). Meanwhile, association between BF in lesion and blood parameters, such as C-reactive protein, neutrophil percentage, and FBG (p < 0.01). AUC of normalized MTRasym (3.5 ppm) in identifying with/without DF in patients with DM is 0.986 (95% CI, 0.918-1.00) with the sensitivity of 97.22% and the specificity of 100%. Conclusion: Normalized MTRasym (3.5 ppm) and the BF in lesion may be treated as a safer and more convenient new indicator to evaluate the tissue infection without using a contrast agent, which may be useful in monitoring and preoperatively assessing DF patients with renal insufficiency.

Quasi-steady-state (QUASS) reconstruction enhances T1 normalization in apparent exchange-dependent relaxation (AREX) analysis: A reevaluation of T1 correction in quantitative CEST MRI of rodent brain tumor models.

PURPOSE: The apparent exchange-dependent relaxation (AREX) analysis has been proposed as an effective means to correct T1 contribution in CEST quantification. However, it has been recognized that AREX T1 correction is not straightforward if CEST scans are not performed under the equilibrium condition. Our study aimed to test if quasi-steady-state (QUASS) reconstruction could boost the accuracy of the AREX metric under common non-equilibrium scan conditions. THEORY AND METHODS: Numerical simulation and in vivo scans were performed to assess the AREX metric accuracy. The CEST signal was simulated under different relaxation delays, RF saturation amplitudes, and durations. The AREX was evaluated as a function of the bulk water T1 and labile proton concentration using the multiple linear regression model. AREX MRI was also assessed in brain tumor rodent models, with both apparent CEST scans and QUASS reconstruction. RESULTS: Simulation showed that the AREX calculation from apparent CEST scans, under non-equilibrium conditions, had significant dependence on labile proton fraction ratio, RF saturation time, and T1. In comparison, QUASS-boosted AREX depended on the labile proton fraction ratio without significant dependence on T1 and RF saturation time. Whereas the apparent (2.7 ± 0.8%) and QUASS MTR asymmetry (2.8 ± 0.8%) contrast between normal and tumor regions of interest (ROIs) were significant, the difference was small. In comparison, AREX contrast between normal and tumor ROIs calculated from the apparent CEST scan and QUASS reconstruction was 3.8 ± 1.1%/s and 4.4 ± 1.2%/s, respectively, statistically different from each other. CONCLUSIONS: AREX analysis benefits from the QUASS-reconstructed equilibrium CEST effect for improved T1 correction and quantitative CEST analysis.

T1 Mapping and Amide Proton Transfer Weighted Imaging for Predicting Lymph Node Metastasis in Patients with Rectal Cancer.

BACKGROUND: Accurate preoperative judgment of lymph node (LN) metastasis is a critical step in creating a treatment strategy and evaluating prognosis in rectal cancer (RC) patients. OBJECTIVE: This study aimed to explore the value of T1 mapping and amide proton transfer weighted (APTw) imaging in predicting LN metastasis in patients with rectal cancer. METHODS: In a retrospective study, twenty-three patients with pathologically confirmed rectal adenocarcinoma who underwent MRI and surgery from August 2019 to August 2021 were selected. Then, 3.0T/MR sequences included conventional sequences (T1WI, T2WI, and DWI), APTw imaging, and T1 mapping. Patients were divided into LN metastasis (group A) and non-LN metastasis groups (group B). The intra-group correlation coefficient (ICC) was used to test the inter-observer consistency. Mann-Whitney U test was used to compare the differences between the two groups. Spearman correlation analysis was performed to evaluate the correlation between T1 and APT values. Logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the differential performance of each parameter and their combination. The difference between AUCs was compared using the DeLong test. RESULTS: The APT value in patients with LN metastasis was significantly higher than in those without LN metastasis group (P=0.020). Also, similar results were observed for the T1 values (P=0.001). The area under the ROC curve of the APT value in the prediction of LN metastasis was 0.794; when the cutoff value was 1.73%, the sensitivity and specificity were 71.4% and 88.9%, respectively. The area under the ROC curve of the T1 value was 0.913; when the cutoff value was 1367.36 ms, the sensitivity and specificity were 78.6% and 100.0%, respectively. The area under the ROC curve of T1+APT was 0.929, with a sensitivity of 78.6% and specificity of 100.0%. CONCLUSION: APT and T1 values show great diagnostic efficiency in predicting LN metastasis in rectal cancer.

Image quality assessment and feasibility of three-dimensional amide proton transfer-weighted imaging for hepatocellular carcinoma.

Background: With the continuous innovation of magnetic resonance imaging (MRI) hardware and software technology, amide proton transfer-weighted (APTw) imaging has been applied in liver cancer. However, to our knowledge, no study has evaluated the feasibility of a three-dimensional amide proton transfer-weighted (3D-APTw) imaging sequence for hepatocellular carcinoma (HCC). This study thus aimed to conduct an image quality assessment of 3D-APTw for HCC and to explore its feasibility. Methods: 3D-APTw MRI examinations were completed in 134 patients with clinically suspected HCC. According to the uniformity of APTw signal in the liver and within the lesion and the proportion of artifact and missing signal regions, APTw images were subjectively scored using a 5-point scale. The scanning success rate of liver APTw imaging was calculated as the ratio of the number of cases with a quality assurance measurement of more than 3 to the total number of HCC cases. The intra- and interobserver quality assurance measurements for APTw images were compared via the Kappa consistency test. Within the HCC cases with a minimum image quality threshold of 3 points, the APT values of HCC and the liver parenchyma, signal-to-noise ratio of APT-weighted images (SNRAPTw), and contrast-to-noise ratio of HCC (CNRHCC) were measured by two observers. The intra- and interobserver agreement was assessed using the intraclass correlation coefficient (ICC). The differences in APT values between HCC and liver parenchyma was determined using the Mann-Whitney test. Results: Sixty-six HCC cases with a quality assurance measurement of APTw imaging were included in the final analysis, and the calculated success rate was 70.21% (66/94). The subjective APT image quality scores of the two observers were consistent (3.66±1.18, 3.50±1.19, and 3.68±1.18), and no intergroup or intragroup statistical differences were found (P=0.594, and P=0.091), but the consistency of inter- and intraobserver was not as satisfactory (κ=0.594 and κ=0.580). The APT values in HCC lesion were significantly higher than those in liver parenchyma (2.73%±0.91% vs. 1.62%±0.55%; P<0.001). The APT values in HCC showed favorable intra- and interobserver consistency between the two observers (ICC =0.808 and ICC =0.853); the APT values in liver parenchyma, SNRAPTw, and CNRHCC values had moderate intraobserver consistency (ICC =0.578, ICC =0.568, and ICC =0.508) and interobserver consistency (ICC =0.599, ICC =0.199, and ICC =0.650). The coefficients of variation of the APTw values in the HCC lesion and in liver parenchyma were 33.4% and 34.4%, respectively. The SNRAPTw and CNRHCC were 30.75±18.74 and 3.56±3.19, with a coefficient of variation of 60.9% and 74.9%, respectively. Conclusions: Liver 3D-APTw imaging was preliminarily demonstrated to be clinically feasible for evaluating HCC.

Fluid suppression in amide proton transfer-weighted (APTw) CEST imaging: New theoretical insights and clinical benefits.

PURPOSE: Amide proton transfer-weighted (APTw) MRI at 3T provides a unique contrast for brain tumor imaging. However, APTw imaging suffers from hyperintensities in liquid compartments such as cystic or necrotic structures and provides a distorted APTw signal intensity. Recently, it has been shown that heuristically motivated fluid suppression can remove such artifacts and significantly improve the readability of APTw imaging. THEORY AND METHODS: In this work, we show that the fluid suppression can actually be understood by the known concept of spillover dilution, which itself can be derived from the Bloch-McConnell equations in comparison to the heuristic approach. Therefore, we derive a novel post-processing formula that efficiently removes fluid artifact, and explains previous approaches. We demonstrate the utility of this APTw assessment in silico, in vitro, and in vivo in brain tumor patients acquired at MR scanners from different vendors. RESULTS: Our results show a reduction of the CEST signals from fluid environments while keeping the APTw-CEST signal intensity almost unchanged for semi-solid tissue structures such as the contralateral normal appearing white matter. This further allows us to use the same color bar settings as for conventional APTw imaging. CONCLUSION: Fluid suppression has considerable value in improving the readability of APTw maps in the neuro-oncological field. In this work, we derive a novel post-processing formula from the underlying Bloch-McConnell equations that efficiently removes fluid artifact, and explains previous approaches which justify the derivation of this metric from a theoretical point of view, to reassure the scientific and medical field about its use.

Amide proton transfer-weighted MRI for renal tumors: Comparison with diffusion-weighted imaging.

OBJECTIVE: To investigate the potential of amide proton transfer-weighted (APTw) MRI in identifying benign and malignant renal tumors and to evaluate whether APTw MRI can add diagnostic value to diffusion-weighted imaging (DWI). MATERIALS AND METHODS: Participants with renal tumor underwent preoperative multiparametric MRI, including APTw MRI and DWI. The APTw and apparent diffusion coefficient (ADC) of malignant tumors and benign tumors were calculated independently by two radiologists and compared. The value of the mean APTw and the mean ADC for differentiating malignant and benign tumors was evaluated by receiver operating characteristic analysis. RESULTS: In total, 65 participants (mean age, 59 years ±14; 41 men) were evaluated: 54 with malignant and 11 with benign renal tumors. Malignant renal tumors showed higher mean APTw values [2.03% (1.63) vs 1.00% (1.60); P < 0.01] and lower mean ADC values (1.22 × 10-3 mm2/s ± 0.37 vs 1.51 × 10-3 mm2/s ± 0.37; P < 0.05) than benign renal tumors. The area under the receiver operating characteristic curve (AUC) of APTw, ADC and the combination of them for the identification of benign and malignant renal tumors was 0.78(95% CI: 0.66, 0.87; P < 0.001),0.70(95% CI: 0.54, 0.86; P < 0.05) and 0.79 (95% CI: 0.67, 0.88; P < 0.001). The optimal cutoff value for mean APTw was 2.14% (sensitivity, 74%; specificity, 73%). There was no difference between these three parameters for differentiating malignant from benign renal tumors (P > 0.05). CONCLUSION: The APTw MRI has the potential use as an imaging biomarker for renal malignant and benign tumors.

Combining amide proton transfer-weighted and arterial spin labeling imaging to differentiate solitary brain metastases from glioblastomas.

PURPOSE: To evaluate the clinical utility of amide proton transfer-weighted imaging (APTw) and arterial spin labeling (ASL) in differentiating solitary brain metastases (SBMs) from glioblastomas (GBMs). METHODS: Forty-eight patients diagnosed with brain tumors were enrolled. All patients underwent conventional MRI, APTw, and ASL scans on a 3.0 T MRI system. The mean APTw value and mean cerebral blood flow (CBF) value were measured. The differences in various parameters between GBMs and SBMs were assessed using the independent-samples t-test. The quantitative performance of these MRI parameters in distinguishing between GBMs and SBMs was evaluated using receiver operating characteristic (ROC) curve analysis. RESULTS: GBMs exhibited significantly higher APTw and CBF values in peritumoral regions compared with SBMs (P < 0.05). There was no significant difference between SBMs and GBMs in tumor cores. APTw MRI had a higher diagnostic efficiency in differentiating SBMs from GBMs (area under the curve [AUC]: 0.864; 75.0% sensitivity and 81.8% specificity). Combined use of APTw and CBF value increased the AUC to 0.927. CONCLUSION: APTw may be superior to ASL for distinguishing between SBMs and GBMs. Combination of APTw and ASL showed better discrimination and a superior diagnostic performance.

Snapshot CEST++: Advancing rapid whole-brain APTw-CEST MRI at 3 T.

APTw CEST MRI suffers from long preparation times and consequently long acquisition times (~5 min). Recently, a consensus on the preparation module for clinical APTw CEST at 3 T was found in the community, and we present a fast whole-brain APTw CEST MRI sequence following this consensus preparation of pulsed RF irradiation of 2 s duration at 90% RF duty-cycle and a B1,rms of 2 µT. After optimization of the snapshot CEST approach for APTw imaging regarding flip angle, voxel size and frequency offset sampling, we extend it by undersampled GRE acquisition and compressed sensing reconstruction. This allows 2 mm isotropic whole-brain APTw imaging for clinical research at 3 T below 2 min. With this sequence, a fast snapshot APTw imaging method is now available for larger clinical studies of 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.

Applications of chemical exchange saturation transfer magnetic resonance imaging in identifying genetic markers in gliomas.

Chemical exchange saturation transfer (CEST) imaging is an important molecular magnetic resonance imaging technique that can image numerous low-concentration biomolecules with water-exchangeable protons (such as cellular proteins) and tissue pH. CEST, or more specially amide proton transfer-weighted imaging, has been widely used for the detection, diagnosis, and response assessment of brain tumors, and its feasibility in identifying molecular markers in gliomas has also been explored in recent years. In this paper, after briefing on the basic principles and quantification methods of CEST imaging, we review its early applications in identifying isocitrate dehydrogenase mutation status, MGMT methylation status, 1p/19q deletion status, and H3K27M mutation status in gliomas. Finally, we discuss the limitations or weaknesses in these studies.

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

Background: 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. Methods: 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. Results: 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%). Conclusions: 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.

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.

The Value of APTw CEST MRI in Routine Clinical Assessment of Human Brain Tumor Patients at 3T.

BACKGROUND: With fast-growing evidence in literature for clinical applications of chemical exchange saturation transfer (CEST) magnetic resonance imaging (MRI), this prospective study aimed at applying amide proton transfer-weighted (APTw) CEST imaging in a clinical setting to assess its diagnostic potential in differentiation of intracranial tumors at 3 tesla (T). METHODS: Using the asymmetry magnetization transfer ratio (MTRasym) analysis, CEST signals were quantitatively investigated in the tumor areas and in a similar sized region of the normal-appearing white matter (NAWM) on the contralateral hemisphere of 27 patients with intracranial tumors. Area under curve (AUC) analyses were used and results were compared to perfusion-weighted imaging (PWI). RESULTS: Using APTw CEST, contrast-enhancing tumor areas showed significantly higher APTw CEST metrics than contralateral NAWM (AUC = 0.82; p < 0.01). In subgroup analyses of each tumor entity vs. NAWM, statistically significant effects were yielded for glioblastomas (AUC = 0.96; p < 0.01) and for meningiomas (AUC = 1.0; p < 0.01) but not for lymphomas as well as metastases (p > 0.05). PWI showed results comparable to APTw CEST in glioblastoma (p < 0.01). CONCLUSIONS: This prospective study confirmed the high diagnostic potential of APTw CEST imaging in a routine clinical setting to differentiate brain tumors.

A Comparative Study of Amide Proton Transfer Weighted Imaging and Intravoxel Incoherent Motion MRI Techniques Versus (18) F-FDG PET to Distinguish Solitary Pulmonary Lesions and Their Subtypes.

BACKGROUND: Amide proton transfer weighted imaging (APTw), intravoxel incoherent motion (IVIM), and positron emission tomography (PET) imaging all have the potential to characterize solitary pulmonary lesions (SPLs). PURPOSE: To compare APTw and IVIM with PET imaging for distinguishing between benign and malignant SPLs and their subtypes. STUDY TYPE: Prospective. POPULATION: Ninety-five patients, 78 with malignant SPLs (including 48 with adenocarcinoma [AC] and 17 with squamous cell carcinoma [SCC]), and 17 with benign SPLs. FIELD STRENGTH/SEQUENCE: Fast spin-echo (FSE) T2WI, FSE APTw and echo-planar imaging IVIM, MR-base attenuation correction (MRAC), and PET imaging on a 3-T whole-body PET/MR system. ASSESSMENT: The magnetization transfer ratio asymmetry (MTRasym) at 3.5 ppm, diffusion coefficient (D), pseudo diffusion coefficient (D*), perfusion fraction (f), and the maximum standardized uptake value (SUVmax) were analyzed. STATISTICAL TESTS: Individual sample t-test, Delong test, Pearson's correlation analysis, and area under the receiver operating characteristic curve (AUC). P < 0.05 indicated statistical significance. RESULTS: The MTRasym and SUVmax were significantly higher, and D was significantly lower in the malignant group (3.3 ± 2.6 [%], 7.8 ± 5, and 1.2 ± 0.3 [×10-3 mm2 /second]) compared to the benign group (-0.3 ± 1.6 [%], 3.1 ± 3.8, and 1.6 ± 0.3 [×10-3 mm2 /second]). The MTRasym and D were significantly lower, and SUVmax was significantly higher in the SCC group (0.8 ± 1.0 [%], 1.0 ± 0.2 [×10-3 mm2 /second] than in the AC group (4.1 ± 2.6 [%], 1.3 ± 0.3 [×10-3 mm2 /second], 6.7 ± 4.6). Besides, the combination (AUC = 0.964) of these three methods showed higher diagnostic efficacy than any individual method (AUC = 0.917, 0.851, 0.82, respectively) in identifying malignant and benign SPLs. However, APTw showed better diagnostic efficacy than the combination of three methods or PET imaging alone in distinguishing SCC and AC groups (AUC = 0.934, 0.781, 0.725, respectively). DATA CONCLUSION: APTw, IVIM, and PET imaging are all effective methods to distinguish benign and malignant SPLs and their subtypes. APTw is potentially more capable than PET imaging of distinguishing lung SCC from AC. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY: Stage 2.

Fully automated analysis combining [18F]-FET-PET and multiparametric MRI including DSC perfusion and APTw imaging: a promising tool for objective evaluation of glioma progression.

PURPOSE: To evaluate diagnostic accuracy of fully automated analysis of multimodal imaging data using [18F]-FET-PET and MRI (including amide proton transfer-weighted (APTw) imaging and dynamic-susceptibility-contrast (DSC) perfusion) in differentiation of tumor progression from treatment-related changes in patients with glioma. MATERIAL AND METHODS: At suspected tumor progression, MRI and [18F]-FET-PET data as part of a retrospective analysis of an observational cohort of 66 patients/74 scans (51 glioblastoma and 23 lower-grade-glioma, 8 patients included at two different time points) were automatically segmented into necrosis, FLAIR-hyperintense, and contrast-enhancing areas using an ensemble of deep learning algorithms. In parallel, previous MR exam was processed in a similar way to subtract preexisting tumor areas and focus on progressive tumor only. Within these progressive areas, intensity statistics were automatically extracted from [18F]-FET-PET, APTw, and DSC-derived cerebral-blood-volume (CBV) maps and used to train a Random Forest classifier with threefold cross-validation. To evaluate contribution of the imaging modalities to the classifier's performance, impurity-based importance measures were collected. Classifier performance was compared with radiology reports and interdisciplinary tumor board assessments. RESULTS: In 57/74 cases (77%), tumor progression was confirmed histopathologically (39 cases) or via follow-up imaging (18 cases), while remaining 17 cases were diagnosed as treatment-related changes. The classification accuracy of the Random Forest classifier was 0.86, 95% CI 0.77-0.93 (sensitivity 0.91, 95% CI 0.81-0.97; specificity 0.71, 95% CI 0.44-0.9), significantly above the no-information rate of 0.77 (p = 0.03), and higher compared to an accuracy of 0.82 for MRI (95% CI 0.72-0.9), 0.81 for [18F]-FET-PET (95% CI 0.7-0.89), and 0.81 for expert consensus (95% CI 0.7-0.89), although these differences were not statistically significant (p > 0.1 for all comparisons, McNemar test). [18F]-FET-PET hot-spot volume was single-most important variable, with relevant contribution from all imaging modalities. CONCLUSION: Automated, joint image analysis of [18F]-FET-PET and advanced MR imaging techniques APTw and DSC perfusion is a promising tool for objective response assessment in gliomas.

Imaging glioma biology: spatial comparison of amino acid PET, amide proton transfer, and perfusion-weighted MRI in newly diagnosed gliomas.

PURPOSE: Imaging glioma biology holds great promise to unravel the complex nature of these tumors. Besides well-established imaging techniques such O-(2-[18F]fluoroethyl)-L-tyrosine (FET)-PET and dynamic susceptibility contrast (DSC) perfusion imaging, amide proton transfer-weighted (APTw) imaging has emerged as a promising novel MR technique. In this study, we aimed to better understand the relation between these imaging biomarkers and how well they capture cellularity and vascularity in newly diagnosed gliomas. METHODS: Preoperative MRI and FET-PET data of 46 patients (31 glioblastoma and 15 lower-grade glioma) were segmented into contrast-enhancing and FLAIR-hyperintense areas. Using established cutoffs, we calculated hot-spot volumes (HSV) and their spatial overlap. We further investigated APTw and CBV values in FET-HSV. In a subset of 10 glioblastoma patients, we compared cellularity and vascularization in 34 stereotactically targeted biopsies with imaging. RESULTS: In glioblastomas, the largest HSV was found for APTw, followed by PET and CBV (p < 0.05). In lower-grade gliomas, APTw-HSV was clearly lower than in glioblastomas. The spatial overlap of HSV was highest between APTw and FET in both tumor entities and regions. APTw correlated significantly with cellularity, similar to FET, while the association with vascularity was more pronounced in CBV and FET. CONCLUSIONS: We found a relevant spatial overlap in glioblastomas between hotspots of APTw and FET both in contrast-enhancing and FLAIR-hyperintense tumor. As suggested by earlier studies, APTw was lower in lower-grade gliomas compared with glioblastomas. APTw meaningfully contributes to biological imaging of gliomas.