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Abstract Background We aimed to determine the capabilities of compressed sensing (CS) and deep learning reconstruction (DLR) with those of conventional parallel imaging (PI) for improving image quality while reducing examination time on female pelvic 1.5-T magnetic resonance imaging (MRI). Methods Fifty-two consecutive female patients with various pelvic diseases underwent MRI with T1- and T2-weighted sequences using CS and PI. All CS data was reconstructed with and without DLR. Signal-to-noise ratio (SNR) of muscle and contrast-to-noise ratio (CNR) between fat tissue and iliac muscle on T1-weighted images (T1WI) and between myometrium and straight muscle on T2-weighted images (T2WI) were determined through region-of-interest measurements. Overall image quality (OIQ) and diagnostic confidence level (DCL) were evaluated on 5-point scales. SNRs and CNRs were compared using Tukey’s test, and qualitative indexes using the Wilcoxon signed-rank test. Results SNRs of T1WI and T2WI obtained using CS with DLR were higher than those using CS without DLR or conventional PI (p

PURPOSEDeep learning reconstruction (DLR) to improve imaging quality has already been introduced, but no studies have evaluated the effect of DLR on diffusion-weighted imaging (DWI) or intravoxel incoherent motion (IVIM) in in vitro or in vivo studies. The purpose of this study was to determine the effect of DLR for magnetic resonance imaging (MRI) in terms of image quality improvement, apparent diffusion coefficient (ADC) assessment, and IVIM index evaluation on DWI through in vitro and in vivo studies.METHODSFor the in vitro study, a phantom recommended by the Quantitative Imaging Biomarkers Alliance was scanned and reconstructed with and without DLR, and 15 patients with brain tumors with normal-appearing gray and white matter examined using IVIM and reconstructed with and without DLR were included in the in vivo study. The ADCs of all phantoms for DWI with and without DLR, as well as the coefficient of variation percentage (CV%), and ADCs and IVIM indexes for each participant, were evaluated based on DWI with and without DLR by means of region-of-interest measurements. For the in vitro study, using the mean ADCs for all phantoms, a t-test was adopted to compare DWI with and without DLR. For the in vivo study, a Wilcoxon signed-rank test was used to compare the CV% between the two types of DWI. In addition, the Wilcoxon signed-rank test was used to compare the ADC, true diffusion coefficient (D), pseudodiffusion coefficient (D*), and percentage of water molecules in micro perfusion within 1 voxel (f) with and without DLR; the limits of agreement of each parameter were determined through a Bland–Altman analysis.RESULTSThe in vitro study identified no significant differences between the ADC values for DWI with and without DLR (P > 0.05), and the CV% was significantly different for DWI with and without DLR (P < 0.05) when b values ≥250 s/mm2 were used. The in vivo study revealed that D* and f with and without DLR were significantly different (P < 0.001). The limits of agreement of the ADC, D, and D* values for DWI with and without DLR were determined as 0.00 ± 0.51 × 10-3, 0.00 ± 0.06 × 10-3, and 1.13 ± 4.04 × 10-3 mm2/s, respectively. The limits of agreement of the f values for DWI with and without DLR were determined as −0.01 ± 0.07.CONCLUSIONDeep learning reconstruction for MRI has the potential to significantly improve DWI quality at higher b values. It has some effect on D* and f values in the IVIM index evaluation, but ADC and D values are less affected by DLR.

Purpose: Although there is no lymphatic system in the central nervous system (CNS), there seems to be a mechanism to remove macro molecules from the brain. Cerebrospinal fluid (CSF) and interstitial fluid (ISF) are thought to be parts of this pathway, but the details are not known. In this study, MR signal of the extracellular water was decomposed into components with distinct T2's, to obtain some information about distribution of waste material in the brain. Methods: Images were acquired using a Curr, Purcell, Meiboom, Gill (CPMG) imaging sequence. In order to reduce T1 contamination and the signal oscillation, hard pulses were used as refocusing pulses. The signal was then decomposed into many T2 components using non-negative least squares (NNLS) in pixel-by-pixel basis. Finally, a color map was generated by assigning different color for each T2 component, then adding them together. Results: From the multi-echo images, it was possible to decompose the decaying signal into separate T2 components. By adjusting the color table to create the color map, it is possible to visualize the extracellular water distribution, as well as their T2 values. Several observation points include: (1) CSF inside ventricles has very long T2 (~2 s), and seems to be relatively homogeneous, (2) subarachnoid CSF also have long T2, but there are short T2 component at the brain surface, at the surface of dura, at the blood vessels in the subarachnoid space, etc., (3) in the brain parenchyma, short T2 components (longer than intracellular component but shorter than CSF) exists along the white matter, in the choroid plexus, etc. These can be considered as distribution of macromolecules (waste materials) in the brain. Conclusion: From T2 component analysis it is possible to obtain some insight into pathways for the transport of large molecules in the CNS, where no lymphatic system is present. [ABSTRACT FROM AUTHOR]

Purpose: To directly compare the utility for therapeutic outcome prediction of dynamic first-pass contrast- enhanced (CE)-perfusion area-detector computed tomography (ADCT), MR imaging assessed with the same mathematical method and 2-[fluorine-18]-fluoro-2-deoxy-d-glucose- positron emission tomography combined with CT (PET/CT) for non-small cell lung cancer (NSCLC) patients treated with chemoradiotherapy. Materials and Methods: Forty-three consecutive stage IIIB NSCLC patients, consisting of 25 males (mean age ± standard deviation: 66.6 ± 8.7 years) and 18 females (66.4 ± 8.2 years) underwent PET/CT, dynamic CE-perfusion ADCT and MR imaging, chemoradiotherapy, and follow-up examination. In each patient, total, pulmonary arterial, and systemic arterial perfusions were calculated from both perfusion data and SUVmax on PET/CT, assessed for each targeted lesion, and averaged to determine final values. Receiver operating characteristics analyses were performed to compare the utility for distinguishing responders from non-responders using Response Evaluation Criteria in Solid Tumor (RECIST) 1.1 criteria. Overall survival (OS) assessed with each index were compared between two groups by means of the Kaplan-Meier method followed by the log-rank test. Results: Area under the curve (Az) for total perfusion on ADCT was significantly larger than that of pulmonary arterial perfusion (P < 0.05). Az of total perfusion on MR imaging was significantly larger than that of pulmonary arterial perfusion (P < 0.05). Mean OS of responder and non-responder groups were significantly different for total and systemic arterial (P < 0.05) perfusion. Conclusion: Dynamic first-pass CE-perfusion ADCT and MR imaging as well as PET/CT are useful for early prediction of treatment response by NSCLC patients treated with chemoradiotherapy. [ABSTRACT FROM AUTHOR]

Background Magnetic resonance imaging (MRI) cardiac gated phase contrast (PC) cine techniques have non-invasively shown the effect of the cardiac pulse on cerebrospinal fluid (CSF) movement. Echo planar imaging (EPI) has shown CSF movement as influenced by both cardiac pulsation and respiration. Previously, it has not been possible to visualize CSF movement in response to respiration non-invasively. The present study was undertaken to do so. Methods The effect of respiration on CSF movement was investigated using a non-contrast timespatial labeling inversion pulse (Time-SLIP) with balanced steady-state free precession (bSSFP) readout. CSF movement was observed in the intracranial compartment in response to respirations in ten normal volunteers. To elucidate the respiration effect, the acquisition was triggered at the beginning of deep inhalation, deep exhalation and breath holding. Results By employing this respiration-induced spin labeling bSSFP cine method, we were able to visualize CSF movement induced by respiratory excursions. CSF moved cephalad (16.4 ± 7.7 mm) during deep inhalation and caudad (11.6 ± 3.0 mm) during deep exhalation in the prepontine cisternal area. Small but rapid cephalad (3.0 ± 0.4 mm) and caudad (3.0 ± 0.5 mm) movement was observed in the same region during breath holding and is thought to reflect cardiac pulsations. Conclusions The Time-SLIP bSSFP cine technique allows for non-invasive visualization of CSF movement associated with respiration to a degree not previously reported. [ABSTRACT FROM AUTHOR]