Purpose To assess amide proton transfer‐weighted (APTW) imaging features in patients with malignant gliomas after chemoradiation and the diagnostic performance of APT imaging for distinguishing true progression from pseudoprogression. Materials and Methods After approval by the Institutional Review Board, 32 patients with clinically suspected tumor progression in the first 3 months after chemoradiation were enrolled and scanned at 3T. Longitudinal routine magnetic resonance imaging (MRI) changes and medical records were assessed to confirm true progression versus pseudoprogression. True progression was defined as lesions progressing on serial imaging over 6 months, and pseudoprogression was defined as lesions stabilizing or regressing without intervention. The APTW mean and APTW max signals were obtained from three to five regions of interests for each patient and compared between the true progression and pseudoprogression groups. The diagnostic performance was assessed with receiver operating characteristic curve analysis. Results The true progression was associated with APTW hyperintensity (APTW mean = 2.75% ± 0.42%), while pseudoprogression was associated with APTW isointensity to mild hyperintensity (APTW mean = 1.56% ± 0.42%). The APTW signal intensities were significantly higher in the true progression group ( n = 20) than in the pseudoprogression group ( P < 0.001; n = 12). The cutoff APTW mean and APTW max intensity values to distinguish between true progression and pseudoprogression were 2.42% (with a sensitivity of 85.0% and a specificity of 100%) and 2.54% (with a sensitivity of 95.0% and a specificity of 91.7%), respectively. Conclusion The APTW‐MRI signal is a valuable imaging biomarker for distinguishing pseudoprogression from true progression in glioma patients. J. Magn. Reson. Imaging 2016;44:456–462.
Purpose To develop prospectively accelerated 3D CEST imaging using compressed sensing (CS), combined with a saturation scheme based on time‐interleaved parallel transmission. Methods A variable density pseudo‐random sampling pattern with a centric elliptical k‐space ordering was used for CS acceleration in 3D. Retrospective CS studies were performed with CEST phantoms to test the reconstruction scheme. Prospectively CS‐accelerated 3D‐CEST images were acquired in 10 healthy volunteers and 6 brain tumor patients with an acceleration factor (R CS ) of 4 and compared with conventional SENSE reconstructed images. Amide proton transfer weighted (APTw) signals under varied RF saturation powers were compared with varied acceleration factors. Results The APTw signals obtained from the CS with acceleration factor of 4 were well‐preserved as compared with the reference image (SENSE R = 2) both in retrospective phantom and prospective healthy volunteer studies. In the patient study, the APTw signals were significantly higher in the tumor region (gadolinium [Gd]‐enhancing tumor core) than in the normal tissue ( p < .001). There was no significant APTw difference between the CS‐accelerated images and the reference image. The scan time of CS‐accelerated 3D APTw imaging was dramatically reduced to 2:10 minutes (in‐plane spatial resolution of 1.8 1.8 mm 2 ; 15 slices with 4‐mm slice thickness) as compared with SENSE (4:07 minutes). Conclusion Compressed sensing acceleration was successfully extended to 3D‐CEST imaging without compromising CEST image quality and quantification. The CS‐based CEST imaging can easily be integrated into clinical protocols and would be beneficial for a wide range of applications.
Water saturation shift referencing (WASSR) Z-spectra can be used to correct shifts due to B0-field inhomogeneities, for magnetic susceptibility mapping and analysis of relaxation effects. The spectra follow a Lorentzian shape with discrete values. Hence, a Lorentzian fit to retrieve the shape parameters (amplitude A, line width LW and frequency shift ΔfH2O ) simplifies analysis. Conventionally, the least-squares (LS) method is used for such fitting despite being time consuming and sensitive to the unavoidable noise in vivo. We propose a deep learning-based Lorentzian-fitting neural network (LoFNet) that demonstrated improved robustness against noise and sampling density in combination with reduced time consumption.
Recent experiments suggest that T 1 relaxation in the rotating frame ( T 1ρ ) is sensitive to metabolism and can detect localized activity-dependent changes in the human visual cortex. Current functional magnetic resonance imaging (fMRI) methods have poor temporal resolution due to delays in the hemodynamic response resulting from neurovascular coupling. Because T 1ρ is sensitive to factors that can be derived from tissue metabolism, such as pH and glucose concentration via proton exchange, we hypothesized that activity-evoked T 1ρ changes in visual cortex may occur before the hemodynamic response measured by blood oxygenation level-dependent (BOLD) and arterial spin labeling (ASL) contrast. To test this hypothesis, functional imaging was performed using BOLD, and ASL in human participants viewing an expanding ring stimulus. We calculated eccentricity phase maps across the occipital cortex for each functional signal and compared the temporal dynamics of T 1ρ versus BOLD and ASL. The results suggest that T 1ρ changes precede changes in the two blood flow-dependent measures. These observations indicate that T 1ρ detects a signal distinct from traditional fMRI contrast methods. In addition, these findings support previous evidence that T 1ρ is sensitive to factors other than blood flow, volume, or oxygenation. Furthermore, they suggest that tissue metabolism may be driving activity-evoked T 1ρ changes.
Abstract Purpose To develop and evaluate a physics‐driven, saturation contrast‐aware, deep‐learning‐based framework for motion artifact correction in CEST MRI. Methods A neural network was designed to correct motion artifacts directly from a Z‐spectrum frequency (Ω) domain rather than an image spatial domain. Motion artifacts were simulated by modeling 3D rigid‐body motion and readout‐related motion during k‐space sampling. A saturation‐contrast‐specific loss function was added to preserve amide proton transfer (APT) contrast, as well as enforce image alignment between motion‐corrected and ground‐truth images. The proposed neural network was evaluated on simulation data and demonstrated in healthy volunteers and brain tumor patients. Results The experimental results showed the effectiveness of motion artifact correction in the Z‐spectrum frequency domain (MOCO Ω ) compared to in the image spatial domain. In addition, a temporal convolution applied to a dynamic saturation image series was able to leverage motion artifacts to improve reconstruction results as a denoising process. The MOCO Ω outperformed existing techniques for motion correction in terms of image quality and computational efficiency. At 3 T, human experiments showed that the root mean squared error (RMSE) of APT images decreased from 4.7% to 2.1% at 1 μT and from 6.2% to 3.5% at 1.5 μT in case of “moderate” motion and from 8.7% to 2.8% at 1 μT and from 12.7% to 4.5% at 1.5 μT in case of “severe” motion, after motion artifact correction. Conclusion The MOCO Ω could effectively correct motion artifacts in CEST MRI without compromising saturation transfer contrast.
Quantitative CT perfusion (CTP) thresholds for assessing the extent of ischemia in patients with acute ischemic stroke (AIS) have been established; relative cerebral blood flow (rCBF) <30% is typically used for estimating estimated ischemic core volume and Tmax (time to maximum) >6 seconds for critical hypoperfused volume in AIS patients with large vessel occlusion (LVO). In this study, we aimed to identify the optimal threshold values for patients presenting with AIS secondary to distal medium vessel occlusions (DMVOs).In this retrospective study, consecutive AIS patients with anterior circulation DMVO who underwent pretreatment CTP and follow-up MRI/CT were included. The CTP data were processed by RAPID (iSchemaView, Menlo Park, CA) to generate estimated ischemic core volumes using rCBF <20%, <30%, <34%, and <38% and critical hypoperfused volumes using Tmax (seconds) >4, >6, >8, and >10. Final infarct volumes (FIVs) were obtained from follow-up MRI/CT within 5 days of symptom onset. Diagnostic performance between CTP thresholds and FIV was assessed in the successfully and unsuccessfully recanalized groups.Fifty-five patients met our inclusion criteria (32 female [58.2%], 68.0 ± 12.1 years old [mean ± SD]). Recanalization was attempted with intravenous tissue-type plasminogen activator and mechanical thrombectomy in 27.7% and 38.1% of patients, respectively. Twenty-five patients (45.4%) were successfully recanalized. In the successfully recanalized patients, no CTP threshold significantly outperformed what is used in LVO setting (rCBF < 30%). All rCBF CTP thresholds demonstrated fair diagnostic performances for predicting FIV. In unsuccessfully recanalized patients, all Tmax CTP thresholds strongly predicted FIV with relative superiority of Tmax >10 seconds (area under the receiver operating characteristic curve = .875, p = .001).In AIS patients with DMVOs, longer Tmax delays than Tmax > 6 seconds, most notably, Tmax > 10 seconds, best predict FIV in unsuccessfully recanalized patients. No CTP threshold reliably predicts FIV in the successfully recanalized group nor significantly outperformed rCBF < 30%.
'/%3e%3cuse xlink:href='%23a' transform='rotate(23.036 .093 25.536)'/%3e%3cuse xlink:href='%23a' transform='rotate(45.87 1.273 16.18)'/%3e%3cuse xlink:href='%23a' transform='rotate(69.945 .996 12.078)'/%3e%3cuse xlink:href='%23a' transform='rotate(20.66 -19.689 31.932)'/%3e%3c/svg%3e)