lesion conspicuity
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Author(s):  
Elisabeth Sartoretti ◽  
Sabine Sartoretti-Schefer ◽  
Luuk van Smoorenburg ◽  
Barbara Eichenberger ◽  
Árpád Schwenk ◽  
...  

Objectives: To compare a novel 3D spiral gradient echo (GRE) sequence with a conventional 2D cartesian turbo spin echo (TSE) sequence for sagittal contrast-enhanced (CE) fat-suppressed (FS) T1 weighted (T1W) spine MRI. Methods: In this inter-individual comparison study, 128 patients prospectively underwent sagittal CE FS T1W spine MRI with either a 2D cartesian TSE (“TSE”, 285 s, 64 patients) or a 3D spiral GRE sequence (“Spiral”, 93 s, 64 patients). Between both groups, patients were matched in terms of anatomical region (cervical/thoracic/lumbar spine and sacrum). Three readers used 4-point Likert scales to assess images qualitatively in terms of overall image quality, presence of artifacts, spinal cord visualization, lesion conspicuity and quality of fat suppression. Results: Spiral achieved a 67.4% scan time reduction compared to TSE. Interreader agreement was high (alpha=0.868-1). Overall image quality (4;[3,4] vs 3;[3,4], p<0.001 – p=0.002 for all readers), presence of artifacts (4;[3,4] vs 3;[3,4] p=0.027 – p=0.046 for all readers), spinal cord visualization (4;[4,4] vs 4;[3,4], p<0.001 for all readers), lesion conspicuity (4;[4,4] vs 4;[4,4], p=0.016 for all readers) and quality of fat suppression (4;[4,4] vs 4;[4,4], p=0.027 – p=0.033 for all readers), were all deemed significantly improved by all three readers on Spiral images as compared to TSE images Conclusion: We demonstrate the feasibility of a novel 3D spiral GRE sequence for improved and rapid sagittal CE FS T1W spine MRI. Advances in knowledge: A 3D spiral GRE sequence allows for improved sagittal CE FS T1W spine MRI at very short scan times.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jae Won Choi ◽  
Yeon Jin Cho ◽  
Ji Young Ha ◽  
Seul Bi Lee ◽  
Seunghyun Lee ◽  
...  

AbstractThis study aimed to evaluate a deep learning model for generating synthetic contrast-enhanced CT (sCECT) from non-contrast chest CT (NCCT). A deep learning model was applied to generate sCECT from NCCT. We collected three separate data sets, the development set (n = 25) for model training and tuning, test set 1 (n = 25) for technical evaluation, and test set 2 (n = 12) for clinical utility evaluation. In test set 1, image similarity metrics were calculated. In test set 2, the lesion contrast-to-noise ratio of the mediastinal lymph nodes was measured, and an observer study was conducted to compare lesion conspicuity. Comparisons were performed using the paired t-test or Wilcoxon signed-rank test. In test set 1, sCECT showed a lower mean absolute error (41.72 vs 48.74; P < .001), higher peak signal-to-noise ratio (17.44 vs 15.97; P < .001), higher multiscale structural similarity index measurement (0.84 vs 0.81; P < .001), and lower learned perceptual image patch similarity metric (0.14 vs 0.15; P < .001) than NCCT. In test set 2, the contrast-to-noise ratio of the mediastinal lymph nodes was higher in the sCECT group than in the NCCT group (6.15 ± 5.18 vs 0.74 ± 0.69; P < .001). The observer study showed for all reviewers higher lesion conspicuity in NCCT with sCECT than in NCCT alone (P ≤ .001). Synthetic CECT generated from NCCT improves the depiction of mediastinal lymph nodes.


2021 ◽  
Author(s):  
Kurt Schilling ◽  
Shreyas Fadnavis ◽  
Joshua Batson ◽  
Mereze Visagie ◽  
Anna J.E. Combes ◽  
...  

Quantitative diffusion MRI (dMRI) is a promising technique for evaluating the spinal cord in health and disease. However, low signal-to-noise ratio (SNR) can impede interpretation and quantification of these images. The purpose of this study is to evaluate a denoising approach, Patch2Self, to improve the quality, reliability, and accuracy of quantitative diffusion MRI of the spinal cord. Patch2Self is a self-supervised learning-based denoising method that leverages statistical independence of noise to suppress signal components strictly originating from random fluctuations. We conduct three experiments to validate the denoising performance of Patch2Self on clinical-quality, single-shell dMRI acquisitions with a small number of gradient directions: 1) inter-session scan-rescan in healthy volunteers to evaluate enhancements in image contrast and model fitting; 2) repeated intra-session scans in a healthy volunteer to compare signal averaging to Patch2Self; and 3) assessment of spinal cord lesion conspicuity in a multiple sclerosis group. We find that Patch2Self improves intra-cord contrast, signal modeling, SNR, and lesion conspicuity within the spinal cord. This denoising approach holds promise for facilitating reliable diffusion measurements in the spinal cord to investigate biological and pathological processes.


2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Li Zhao ◽  
Meng Liang ◽  
Pu-yeh Wu ◽  
Yang Yang ◽  
Hongmei Zhang ◽  
...  

Abstract Purpose To compare the imaging quality, T stage and extramural venous invasion (EMVI) evaluation between the conventional and synthetic T2-weighted imaging (T2WI), and to investigate the role of quantitative values obtained from synthetic magnetic resonance imaging (MRI) for assessing nodal staging in rectal cancer (RC). Methods Ninety-four patients with pathologically proven RC who underwent rectal MRI examinations including synthetic MRI were retrospectively recruited. The image quality of conventional and synthetic T2WI was compared regarding signal-to-noise ratio (SNR), contrast-to-noise (CNR), sharpness of the lesion edge, lesion conspicuity, absence of motion artifacts, and overall image quality. The accuracy of T stage and EMVI evaluation on conventional and synthetic T2WI were compared using the Mc-Nemar test. The quantitative T1, T2, and PD values were used to predict the nodal staging of MRI-evaluated node-negative RC. Results There were no statistically significant differences between conventional and synthetic T2WI in SNR, CNR, overall image quality, lesion conspicuity, and absence of motion artifacts (p = 0.058–0.978). There were no significant differences in the diagnostic accuracy of T stage and EMVI between conventional and synthetic T2WI from two observers (p = 0.375 and 0.625 for T stage; p = 0.625 and 0.219 for EMVI). The T2 value showed good diagnostic performance for predicting the nodal staging of RC with the area under the receiver operating characteristic, sensitivity, specificity, and accuracy of 0.854, 90.0%, 71.4%, and 80.3%, respectively. Conclusions Synthetic MRI may facilitate preoperative staging and EMVI evaluation of RC by providing synthetic T2WI and quantitative maps in one acquisition.


Cancers ◽  
2021 ◽  
Vol 13 (14) ◽  
pp. 3593
Author(s):  
Sebastian Gassenmaier ◽  
Saif Afat ◽  
Marcel Dominik Nickel ◽  
Mahmoud Mostapha ◽  
Judith Herrmann ◽  
...  

Multiparametric MRI (mpMRI) of the prostate has become the standard of care in prostate cancer evaluation. Recently, deep learning image reconstruction (DLR) methods have been introduced with promising results regarding scan acceleration. Therefore, the aim of this study was to investigate the impact of deep learning image reconstruction (DLR) in a shortened acquisition process of T2-weighted TSE imaging, regarding the image quality and diagnostic confidence, as well as PI-RADS and T2 scoring, as compared to standard T2 TSE imaging. Sixty patients undergoing 3T mpMRI for the evaluation of prostate cancer were prospectively enrolled in this institutional review board-approved study between October 2020 and March 2021. After the acquisition of standard T2 TSE imaging (T2S), the novel T2 TSE sequence with DLR (T2DLR) was applied in three planes. Overall, the acquisition time for T2S resulted in 10:21 min versus 3:50 min for T2DLR. The image evaluation was performed by two radiologists independently using a Likert scale ranging from 1–4 (4 best) applying the following criteria: noise levels, artifacts, overall image quality, diagnostic confidence, and lesion conspicuity. Additionally, T2 and PI-RADS scoring were performed. The mean patient age was 69 ± 9 years (range, 49–85 years). The noise levels and the extent of the artifacts were evaluated to be significantly improved in T2DLR versus T2S by both readers (p < 0.05). Overall image quality was also evaluated to be superior in T2DLR versus T2S in all three acquisition planes (p = 0.005–<0.001). Both readers evaluated the item lesion conspicuity to be superior in T2DLR with a median of 4 versus a median of 3 in T2S (p = 0.001 and <0.001, respectively). T2-weighted TSE imaging of the prostate in three planes with an acquisition time reduction of more than 60% including DLR is feasible with a significant improvement of image quality.


2021 ◽  
Vol 75 ◽  
pp. 90-96
Author(s):  
Catherine S. Giess ◽  
Sughra Raza ◽  
Christine M. Denison ◽  
Eren D. Yeh ◽  
Eva C. Gombos ◽  
...  

2021 ◽  
Vol 94 (1121) ◽  
pp. 20200869
Author(s):  
Thomas Sartoretti ◽  
Elisabeth Sartoretti ◽  
Michael Wyss ◽  
Manoj Mannil ◽  
Luuk van Smoorenburg ◽  
...  

Objectives: Diffusion-weighted imaging (DWI) plays a crucial role in the diagnosis of ischemic stroke. We assessed the value of computed and acquired high b-value DWI in comparison with conventional b = 1000 s mm−2 DWI for ischemic stroke at 3T. Methods: We included 36 patients with acute ischemic stroke who presented with diffusion abnormalities on DWI performed within 24 h of symptom onset. B-values of 0, 500, 1000 and 2000 s mm−2 were acquired. Synthetic images with b-values of 1000, 1500, 2000 and 2500 s mm−2 were computed. Two readers compared synthetic (syn) and acquired (acq) b = 2000 s mm−2 images with acquired b = 1000 s mm−2 images in terms of lesion detection rate, image quality, presence of uncertain hyperintensities and lesion conspicuity. Readers also selected their preferred b-value. Contrast ratio (CR) measurements were performed. Non-parametrical statistical tests and weighted Cohens’ κ tests were computed. Results: Syn1000 and syn1500 matched acq1000 images in terms of lesion detection rate, image quality and presence of uncertain hyperintensities but presented with significantly improved lesion conspicuity (p < 0.01) and were frequently selected as preferred b-values. Acq2000 images exhibited a similar lesion detection rate and improved lesion conspicuity (p < 0.01) but worse image quality (p < 0.01) than acq1000 images. Syn2000 and syn2500 images performed significantly worse (p < 0.01) than acq1000 images in most or all categories. CR significantly increased with increasing b-values. Conclusion: Synthetic images at b = 1000 and 1500 s mm−2 and acquired DWI images at b = 2000 s mm−2 may be of clinical value due to improved lesion conspicuity. Advances in knowledge: Synthetic b-values enable improved lesion conspicuity for DWI of ischemic stroke.


2021 ◽  
Author(s):  
Xiuli Sui ◽  
Hui Tan ◽  
Haojun Yu ◽  
Yiqiu Zhang ◽  
Pengcheng Hu ◽  
...  

Abstract PURPOSE To explorer the optimal reconstruction parameters in oncologic 18 F-FDG total-body PET/CT studies with ultra-low activity injection. METHODS A total of 204 reconstructed PET images of 34 patients with a total of 58 lesions were analyzed by two experienced nuclear medicine physicians. Images were reconstructed with ordered subset expectation maximization (OSEM) algorithm (2 and 3 iterations) including time-of-flight (TOF) and point spread function (PSF) corrections and regularization ordered subset expectation maximization (ROSEM) (b-values of 0.3, 0.4, 0.5, and 0.6). General image quality was assessed using the five-point method including overall image quality, image clarity, noise, and lesion conspicuity. Image noise, signal-to-noise ratio, lesion size, SUVmax, SUVpeak and T/N were quantitatively analyzed by the third reader who did not participate in subjective image assessment. RESULTS In objective image quality indicators, noise decreased and a continuous increase of SNR with incremental β-values (0.3,0.4, 0.5 and 0.6) compared with OSEM3. In subjective image quality, OSEM2, ROSEM0.5 and ROSEM0.6 scored higher (all P<0.001) in overall image quality, image contrast and noise. The scores of ROSEM reconstructions were all higher in lesion conspicuity compared with OSEM3 (all P<0.001). In lesion detectability, SUVmax, SUVpeak and T/N increase with β value of ROSEM increase. Compared with OSEM3, there was a negative correlation between lesion size and the percentage increase of SUVpeak in OSEM2 and ROSEM reconstructions (all P<0.01). CONCLUSION In clinical practice, we recommended OSEM reconstruction with 3 iterations with a relatively short reconstruction time and we recommend ROSEM algorithm with b of 0.5 when reconstruction time is not considered.


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