Two-stage deep learning for accelerated 3D time-of-flight MRA without matched training data.

OBJECTIVES The aim of this study was to compare the image quality of low-kV protocols with optimized automatic tube voltage selection (ATVS) settings to reduce either radiation dose or contrast medium (CM) with that of a reference protocol for computed tomography angiography (CTA) of the thoracoabdominal aorta. MATERIALS AND METHODS In this institutional review board-approved, single-center, prospective randomized controlled trial, 126 patients receiving CTA of the aorta were allocated to one of three computed tomography protocols: (A) reference protocol at 120 kVp and standard weight-adapted CM dose; (B) protocol at 90 kVp, reduced radiation and standard CM dose; and (C) protocol at 90 kVp, standard radiation and reduced CM dose. All three protocols were performed on a third-generation dual-source computed tomography scanner using the semimode of the ATVS system. The image-task-dependent optimization settings of the ATVS (slider level) were adjusted to level 11 (high-contrast task) for protocols A and B and level 3 (low-contrast task) for protocol C. Radiation dose parameters were assessed. The contrast-to-noise ratios (CNRs) of protocols B and C were tested for noninferiority compared with A. Subjective image quality was assessed using a 5-point Likert scale. RESULTS Size-specific dose estimate was 34.3% lower for protocol B compared with A (P < 0.0001). Contrast medium was 20.2% lower for protocol C compared with A (P < 0.0001). Mean CNR in B and C was noninferior to protocol A (CNR of 30.2 ± 7, 33.4 ± 6.7, and 30.5 ± 8.9 for protocols A, B, and C, respectively). There was no significant difference in overall subjective image quality among protocols (4.09 ± 0.21, 4.03 ± 0.19, and 4.08 ± 0.17 for protocols A, B, and C, respectively; P = 0.4). CONCLUSIONS The slider settings of an ATVS system can be adjusted to optimize either radiation dose or CM at noninferior image quality in low-kV CTA of the aorta. This optimization could be used to extend future ATVS algorithms to take clinical risk factors like kidney function of individual patients into account.

Computed Tomography Angiography of the Aorta-Optimization of Automatic Tube Voltage Selection Settings to Reduce Radiation Dose or Contrast Medium in a Prospective Randomized Trial

BACKGROUND AND PURPOSE: The clinical practice of three-dimensional TOF-MRA, despite its capability in brain artery assessment, has been hampered by the relatively long scan time, while recent developments in fast imaging techniques with random undersampling has shed light on an improved balance between image quality and imaging speed. Our aim was to evaluate the effectiveness of TOF-MRA accelerated by compressed sensitivity encoding and to identify the optimal acceleration factors for routine clinical use. MATERIALS AND METHODS: One hundred subjects, enrolled at 5 centers, underwent 8 brain TOF-MRA sequences: 5 sequences using compressed sensitivity encoding with acceleration factors of 2, 4, 6, 8, and 10 (CS2, CS4, CS6, CS8, and CS10), 2 using sensitivity encoding with factors of 2 and 4 (SF2 and SF4), and 1 without acceleration as a reference sequence (RS). Five large arteries, 6 medium arteries, and 6 small arteries were evaluated quantitatively (reconstructed signal intensity, structural similarity, contrast ratio) and qualitatively (scores on arteries, artifacts, overall image quality, and diagnostic confidence for aneurysm and stenosis). Comparisons were performed among the 8 sequences. RESULTS: The quantitative measurements showed that the reconstructed signal intensities of the assessed arteries and the structural similarity consistently decreased as the compressed sensitivity encoding acceleration factor increased, and no significant difference was found for the contrast ratios in pair-wise comparisons among SF2, CS2, and CS4. Qualitative evaluations showed no significant difference in pair-wise comparisons among RS, SF2, and CS2 (P > .05). The visualization of all the assessed arteries was acceptable for CS2 and CS4, while 2 small arteries in images of CS6 were not reliably displayed, and the visualization of large arteries was acceptable in images of CS8 and CS10. CONCLUSIONS: CS4 is recommended for routine brain TOF-MRA with balanced image quality and acquisition time; CS6, for examinations when small arteries are not evaluated; and CS10, for fast visualization of large arteries.

http://www.ajnr.org/content/ajnr/42/7/1208.full.pdf

Acceleration of Brain TOF-MRA with Compressed Sensitivity Encoding: A Multicenter Clinical Study

Time-of-flight magnetic resonance angiography (TOF-MRA) is one of the most widely used non-contrast MR imaging methods to visualize blood vessels, but due to the 3-D volume acquisition highly accelerated acquisition is necessary. Accordingly, high quality reconstruction from undersampled TOF-MRA is an important research topic for deep learning. However, most existing deep learning works require matched reference data for supervised training, which are often difficult to obtain. By extending the recent theoretical understanding of cycleGAN from the optimal transport theory, here we propose a novel two-stage unsupervised deep learning approach, which is composed of the multi-coil reconstruction network along the coronal plane followed by a multi-planar refinement network along the axial plane. Specifically, the first network is trained in the square-root of sum of squares (SSoS) domain to achieve high quality parallel image reconstruction, whereas the second refinement network is designed to efficiently learn the characteristics of highly-activated blood flow using double-headed max-pool discriminator. Extensive experiments demonstrate that the proposed learning process without matched reference exceeds performance of state-of-the-art compressed sensing (CS)-based method and provides comparable or even better results than supervised learning approaches.

Two-Stage Deep Learning for Accelerated 3D Time-of-Flight MRA without Matched Training Data

Compressed Sensing MRI: Technique and Clinical Applications

BACKGROUND Compressed sensing (CS) has been widely used to improve the speed of MRI, but the feasibility of application in 3D intracranial MR angiography (MRA) needs to be evaluated in clinical practice. PURPOSE To evaluate the clinical feasibility of CS-MRA in comparison with conventional 3D-MRA (Con-MRA). STUDY TYPE Retrospective. SUBJECTS Forty-nine consecutive patients with suspected intracranial arterial disease. FIELD STRENGTH/SEQUENCE 3T MRI. 3D time-of-flight (TOF) MRA using a CS algorithm and conventional 3D TOF MRA scan. ASSESSMENT Three radiologists (4, 11, and 12 years of experience in neuroradiology) independently assessed the image quality, vascular lesions, and variations of intracranial arteries of both CS-MRA and Con-MRA, respectively. STATISTICAL TESTS The Kendall W test was performed to assess the interobserver agreement of image quality and intracranial arterial stenosis. A nonparametric test (Wilcoxon test) was used for comparison of the image quality and definition of the external carotid artery (ECA). Weighted kappa analysis was performed for the interstudy agreement of intracranial arterial stenosis. The aneurysm, decreased branches, congenital hypoplasia, absence, and variant branching of intracranial arteries were observed and evaluated for interobserver agreement and interstudy agreement by kappa analysis. Paired-t-tests for signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were conducted. RESULTS Image quality is better for CS-MRA compared with Con-MRA with significance (Z = -3.710 to -2.673, with P < 0.01). The interstudy agreement of lesion and variation of intracranial arteries assessment for each observer was excellent. The SNR and CNR were significantly higher in CS-MRA compared with Con-MRA (P < 0.001). The definition of ECA of CS-MRA was significantly better (Z = -4.9, P < 0.001). DATA CONCLUSION CS-MRA showed significantly higher image quality with less blur, comparable image diagnostic performance of intracranial arteries, and better display of ECA than Con-MRA. LEVEL OF EVIDENCE 3 Technical Efficacy Stage: 2 J. Magn. Reson. Imaging 2019;50:1843-1851.

Clinical feasibility study of 3D intracranial magnetic resonance angiography using compressed sensing.

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Clinical feasibility study of 3D intracranial magnetic resonance angiography using compressed sensing.