T2-weighted Turbo Spin-echo Sequences Research Articles

Relationship between the intravascular enhancement sign on three-dimensional T1-weighted turbo spin echo and intraluminal thrombus in middle cerebral artery atherosclerosis

PurposeTo investigate the association between the intravascular enhancement sign (IVES) and intraluminal thrombus (ILT) detected by high-resolution magnetic resonance vessel wall imaging (HR-VWI) in patients with middle cerebral artery (MCA) atherosclerosis. MethodThe data of patients who underwent HR-VWI between May 2021 and May 2023, including clinical information, the number of IVES vessels, stenosis degree, ILT, plaque features on 3D T1-weighted turbo spin echo sequences, and signal intensity ratio (SIR) on 3D time-of-flight magnetic resonance angiography, were retrospectively analyzed. Correlation and logistic regression analyses were performed. ResultsA total of 194 MCA plaques were identified in 132 patients (103 [53 %] on the left). Atherosclerosis with, relative to without, ILT was associated with a higher incidence of ischemic events, higher plaque enhancement and stenosis degrees, more vessels with IVES, and lower remodeling ratio, lumen area, wall area, total vessel area, and SIR. Multivariate logistic regression analysis showed significant and independent associations of the number of IVES vessels (OR = 1.089; 95 % CI [1.013–1.170]; P = 0.020) and SIR (OR = 0.007; 95 % CI [0.0004–0.124]; P < 0.001) with ILT. The number of vessels with the IVES (AUC = 0.81, 95 % CI [0.75–0.87]; P < 0.001) and SIR (AUC = 0.88, 95 % CI [0.82–0.94]; P < 0.001) sufficiently diagnosed ILT, and the AUC of the combination of the IVES and SIR was 0.89 (95 % CI [0.84–0.94]; P < 0.001). ConclusionThe number of IVES vessels and SIR are independent risk factors for ILT. They may provide new monitoring targets for stroke prevention in patients with atherosclerotic stenosis.

Added Value of [18F]PSMA-1007 PET/CT and PET/MRI in Patients With Biochemically Recurrent Prostate Cancer: Impact on Detection Rates and Clinical Management.

Prostate-specific membrane antigen (PSMA) positron emission tomography (PET) can change management in a large fraction of patients with biochemically recurrent prostate cancer (BCR). To investigate the added value of PET to MRI and CT for this patient group, and to explore whether the choice of the PET paired modality (PET/MRI vs. PET/CT) impacts detection rates and clinical management. Retrospective. 41 patients with BCR (median age [range]: 68 [55-78]). 3T, including T1-weighted gradient echo (GRE), T2-weighted turbo spin echo (TSE) and dynamic contrast-enhanced GRE sequences, diffusion-weighted echo-planar imaging, and a T1-weighted TSE spine sequence. In addition to MRI, [18F]PSMA-1007 PET and low-dose CT were acquired on the same day. Images were reported using a five-point Likert scale by two teams each consisting of a radiologist and a nuclear medicine physician. The radiologist performed a reading using CT and MRI data and a joint reading between radiologist and nuclear medicine physician was performed using MRI, CT, and PET from either PET/MRI or PET/CT. Findings were presented to an oncologist to create intended treatment plans. Intrareader and interreader agreement analysis was performed. McNemar test, Cohen's κ, and intraclass correlation coefficients. A P-value <0.05 was considered significant. 7 patients had positive findings on MRI and CT, 22 patients on joint reading with PET/CT, and 18 patients joint reading with PET/MRI. For overall positivity, interreader agreement was poor for MR and CT (κ = 0.36) and almost perfect with addition of PET (PET/CT κ = 0.85, PET/MRI κ = 0.85). The addition of PET from PET/CT and PET/MRI changed intended treatment in 20 and 18 patients, respectively. Between joint readings, intended treatment was different for eight patients. The addition of [18F]PSMA-1007 PET/MRI or PET/CT to MRI and CT may increase detection rates, could reduce interreader variability, and may change intended treatment in half of patients with BCR. 3 TECHNICAL EFFICACY: Stage 3.

Comparison between postcontrast thin-slice T1-weighted 2D spin echo and 3D T1-weighted SPACE sequences in the detection of brain metastases at 1.5 and 3 T

ObjectivesAccurate detection of metastatic brain lesions (MBL) is critical due to advances in radiosurgery. We compared the results of three readers in detecting MBL using T1-weighted 2D spin echo (SE) and sampling perfection with application-optimized contrasts using different flip angle evolution (SPACE) sequences with whole-brain coverage at both 1.5 T and 3 T.MethodsFifty-six patients evaluated for MBL were included and underwent a standard protocol (1.5 T, n = 37; 3 T, n = 19), including postcontrast T1-weighted SE and SPACE. The rating was performed by three raters in two sessions > six weeks apart. The true number of MBL was determined using all available imaging including follow-up. Intraclass correlations for intra-rater and inter-rater agreement were calculated. Signal intensity ratios (SIR; enhancing lesion, white matter) were determined on a subset of 46 MBL > 4 mm. A paired t-test was used to evaluate postcontrast sequence order and SIR. Reader accuracy was evaluated by the coefficient of determination.ResultsA total of 135 MBL were identified (mean/subject 2.41, SD 6.4). The intra-rater agreement was excellent for all 3 raters (ICC = 0.97–0.992), as was the inter-rater agreement (ICC = 0.995 SE, 0.99 SPACE). Subjective qualitative ratings were lower for SE images; however, signal intensity ratios were higher in SE sequences. Accuracy was high in all readers for both SE (R2 0.95–0.96) and SPACE (R2 0.91–0.96) sequences.ConclusionsAlthough SE sequences are superior to gradient echo sequences in the detection of small MBL, they have long acquisition times and frequent artifacts. We show that T1-weighted SPACE is not inferior to standard thin-slice SE sequences in the detection of MBL at both imaging fields.Critical relevance statementOur results show the suitability of 3D T1-weighted turbo spin echo (TSE) sequences (SPACE, CUBE, VISTA) in the detection of brain metastases at both 1.5 T and 3 T.Key points• Accurate detection of brain metastases is critical due to advances in radiosurgery.• T1-weighted SE sequences are superior to gradient echo in detecting small metastases.• T1-weighted 3D-TSE sequences may achieve high resolution and relative insensitivity to artifacts.• T1-weighted 3D-TSE sequences have been recommended in imaging brain metastases at 3 T.• We found T1-weighted 3D-TSE equivalent to thin-slice SE at 1.5 T and 3 T.Graphical

Lax Uterosacral Ligament and Urge Urinary Incontinence: MRI Findings in Symptomatic Patients Versus Healthy Volunteers

Introduction and hypothesisThe objective was to explore the association between urge urinary incontinence (UUI) and lax uterosacral ligaments (USL) using MRI.MethodsSixty-seven female participants were recruited prospectively: 41 continent volunteers (control group) and 26 patients with UUI. Static proton density- and T2-weighted turbo spin echo sequences of MR images were used. A radiologist employed a standardized grid system to record structural observations of the USLs on sequentially numbered axial MR images and then applied a four-point grading scale to assess ligament visibility. MR images were interpreted by a radiologist and a urologist, and then validated by an expert radiologist.ResultsThe comparison between the mean length of uterosacral ligaments in the control and UUI groups was highly statistically significant (p < 0.001). The mean length of the right USL was 38 ± 11 mm, and the left USL was 35 ± 12 mm in the UUI group. In the control group, the mean length of the USL was 22 ± 9 mm on the right side and 18 ± 9 mm on the left side, along their craniocaudal extent. The highest inter-observer agreement was on the level of origin and insertion (image numbers), whereas the lowest agreement was on the anatomical site of origin and insertion of the USL in both the control and UUI groups.ConclusionsThe average length of USLs in patients with UUI is significantly longer than that in healthy continent women, indicating laxity. Our findings support the relationship between the laxity of the USL and UUI symptoms and have therapeutic implications.

Sorting lung tumor volumes from 4D-MRI data using an automatic tumor-based signal reduces stitching artifacts.

To investigate whether a novel signal derived from tumor motion allows more precise sorting of 4D-magnetic resonance (4D-MR) image data than do signals based on normal anatomy, reducing levels of stitching artifacts within sorted lung tumor volumes. (4D-MRI) scans were collected for 10 lung cancer patients using a 2D T2-weighted single-shot turbo spin echo sequence, obtaining 25 repeat frames per image slice. For each slice, a tumor-motion signal was generated using the first principal component of movement in the tumor neighborhood (TumorPC1). Signals were also generated from displacements of the diaphragm (DIA) and upper and lower chest wall (UCW/LCW) and from slice body area changes (BA). Pearson r coefficients of correlations between observed tumor movement and respiratory signals were determined. TumorPC1, DIA, and UCW signals were used to compile image stacks showing each patient's tumor volume in a respiratory phase. Unsorted image stacks were also built for comparison. For each image stack, the presence of stitching artifacts was assessed by measuring the roughness of the compiled tumor surface according to a roughness metric (Rg). Statistical differences in weighted means of Rg between any two signals were determined using an exact permutation test. The TumorPC1 signal was most strongly correlated with superior-inferior tumor motion, and had significantly higher Pearson r values (median 0.86) than those determined for correlations of UCW, LCW, and BA with superior-inferior tumor motion (p<0.05). Weighted means of ratios of Rg values in TumorPC1 image stacks to those in unsorted, UCW, and DIA stacks were 0.67, 0.69, and 0.71, all significantly favoring TumorPC1 (p=0.02-0.05). For other pairs of signals, weighted mean ratios did not differ significantly from one. Tumor volumes were smoother in 3D image stacks compiled using the first principal component of tumor motion than in stacks compiled with signals based on normal anatomy.

7 T Lesion-Attenuated Magnetization-Prepared Gradient Echo Acquisition for Detection of Posterior Fossa Demyelinating Lesions in Multiple Sclerosis.

Detection of infratentorial demyelinating lesions in multiple sclerosis (MS) presents a challenge in magnetic resonance imaging (MRI), a difficulty that is further heightened in 7 T MRI. This study aimed to assess the efficacy of a novel MRI approach, lesion-attenuated magnetization-prepared gradient echo acquisition (LAMA), for detecting demyelinating lesions within the posterior fossa and upper cervical spine on 7 T MRI and contrast its performance with conventional double-inversion recovery (DIR) and T2-weighted turbo spin echo sequences. We conducted a retrospective cross-sectional study in 42 patients with a confirmed diagnosis of MS. All patients had 7 T MRI that incorporated LAMA, 3D DIR, and 2D T2-weighted turbo spin echo sequences. Three readers assessed lesion count in the brainstem, cerebellum, and upper cervical spinal cord using both DIR and T2-weighted images in one session. In a separate session, LAMA was analyzed alone. Contrast-to-noise ratio was also compared between LAMA and the conventional sequences. Lesion counts between methods were assessed using nonparametric Wilcoxon signed rank test. Interrater agreement in lesion detection was estimated by intraclass correlation coefficients. LAMA identified a significantly greater number of lesions than DIR + T2 (mean 6.4 vs 3.0; P < 0.001). LAMA also exhibited better interrater agreement (intraclass correlation coefficient [95% confidence interval], 0.75 [0.41-0.88] vs 0.61 [0.35-0.78]). The contrast-to-noise ratio for LAMA (3.7 ± 0.9) significantly exceeded that of DIR (1.94 ± 0.7) and T2 (1.2 ± 0.7) (all P's < 0.001). In cases with no lesions detected using DIR + T2, at least 1 lesion was identified in 83.3% with LAMA. Across all analyzed brain regions, LAMA consistently detected more lesions than DIR + T2. LAMA significantly improves the detection of infratentorial demyelinating lesions in MS patients compared with traditional methods. Integrating LAMA with standard magnetization-prepared 2 rapid acquisition gradient echo acquisition provides a valuable tool for accurately characterizing the extent of MS disease.

Prediction of diabetes insipidus occurrence after endoscopic endonasal removal of sellar lesions using MRI-based radiomics and machine learning.

Pituitary adenomas and craniopharyngiomas are the most common lesions of the sellar region. These tumors are responsible for invasion or compression of crucial neurovascular structures. The involvement of the pituitary stalk warrants high rates of both pre- and post- operative diabetes insipidus. The aim of our study was to assess the accuracy of machine learning analysis from preoperative MRI of pituitary adenomas and craniopharyngiomas for the prediction of DI occurrence. All patients underwent MRI exams either on a 1.5- or 3-T MR scanner from two Institutions, including coronal T2-weighted (T2-w) and contrast-enhanced T1-weighted (CE T1-w) Turbo Spin Echo sequences. Feature selection was carried out as a multi-step process, with a threshold of 0.75 to identify robust features. Further feature selection steps included filtering based on feature variance (threshold >0.01) and pairwise correlation (threshold <0.80). A Bayesian Network model was trained with 10-fold cross validation employing SMOTE to balance classes exclusively within the training folds. Thirty patients were included in this study. In total 2394 features were extracted and 1791 (75%) resulted stable after ICC analysis. The number of variant features was 1351 and of non-colinear features was 125. Finally, 10 features were selected by oneR ranking. The Bayesian Network model showed an accuracy of 63% with a precision of 77% for DI prediction (0.68 area under the precision-recall curve). We assessed the accuracy of machine learning analysis of texture-derived parameters from preoperative MRI of pituitary adenomas and craniopharyngiomas for the prediction of DI occurrence.

Comparison of standard T2-weighted turbo spin echo and volumetric interpolated breath-hold examination magnetic resonance imaging sequences in the assessment of articular process dysplasia in Pug dogs with thoracolumbar myelopathy.

A retrospective study to compare the classification, as normal, hypoplastic or aplastic, of thoracic (T10-T13) caudal articular process (CAP) morphology in Pug dogs with a thoracolumbar myelopathy as normal, hypoplastic or aplastic, between T2 weighted Turbo Spin Echo (T2W-TSE), in sagittal and transverse planes, and Volumetric Interpolated Breath-hold Examination (VIBE) Magnetic Resonance Imaging (MRI) sequences, in comparison to Computed Tomography (CT). We hypothesized a stronger agreement for VIBE in comparison to T2W-TSE. Diagnostic accuracy of T2W-TSE was inferior to VIBE for aplastic (60%, 95% CI 0.561-0.639 vs. 78%, 95%CI 0.744-0.815) hypoplastic (44%, 95%CI 0.427-0.452 vs. 62.5%, 95%CI 0.595-0.655) and normal CAP (70%, 95%CI 0.655-0.744 vs. 87%, 95%CI 0.848-0.892). Superior accuracy of classification using VIBE vs. T2W-TSE sequences using the McNemar Chi squared test was significant for aplastic (p = 0.0002) and normal CAP (p = 0.004). VIBE sequences had a sensitivity of 96% and specificity of 75% to detect CAP abnormality and with T2W-TSE imaging sensitivity 81% and specificity of 75%. Three-dimensionally reconstructable VIBE sequences were significantly more accurate than traditional T2W-TSE MRI sequences in classifying CAP morphology, which should reduce the need for CT for pre-operative assessment.

Deep Learning Super-Resolution Reconstruction for Fast and Motion-Robust T2-weighted Prostate MRI.

Background Deep learning (DL) reconstructions can enhance image quality while decreasing MRI acquisition time. However, DL reconstruction methods combined with compressed sensing for prostate MRI have not been well studied. Purpose To use an industry-developed DL algorithm to reconstruct low-resolution T2-weighted turbo spin-echo (TSE) prostate MRI scans and compare these with standard sequences. Materials and Methods In this prospective study, participants with suspected prostate cancer underwent prostate MRI with a Cartesian standard-resolution T2-weighted TSE sequence (T2C) and non-Cartesian standard-resolution T2-weighted TSE sequence (T2NC) between August and November 2022. Additionally, a low-resolution Cartesian DL-reconstructed T2-weighted TSE sequence (T2DL) with compressed sensing DL denoising and resolution upscaling reconstruction was acquired. Image sharpness was assessed qualitatively by two readers using a five-point Likert scale (from 1 = nondiagnostic to 5 = excellent) and quantitatively by calculating edge rise distance. The Friedman test and one-way analysis of variance with post hoc Bonferroni and Tukey tests, respectively, were used for group comparisons. Prostate Imaging Reporting and Data System (PI-RADS) score agreement between sequences was compared by using Cohen κ. Results This study included 109 male participants (mean age, 68 years ± 8 [SD]). Acquisition time of T2DL was 36% and 29% lower compared with that of T2C and T2NC (mean duration, 164 seconds ± 20 vs 257 seconds ± 32 and 230 seconds ± 28; P < .001 for both). T2DL showed improved image sharpness compared with standard sequences using both qualitative (median score, 5 [IQR, 4-5] vs 4 [IQR, 3-4] for T2C and 4 [IQR, 3-4] for T2NC; P < .001 for both) and quantitative (mean edge rise distance, 0.75 mm ± 0.39 vs 1.15 mm ± 0.68 for T2C and 0.98 mm ± 0.65 for T2NC; P < .001 and P = .01) methods. PI-RADS score agreement between T2NC and T2DL was excellent (κ range, 0.92-0.94 [95% CI: 0.87, 0.98]). Conclusion DL reconstruction of low-resolution T2-weighted TSE sequences enabled accelerated acquisition times and improved image quality compared with standard acquisitions while showing excellent agreement with conventional sequences for PI-RADS ratings. Clinical trial registration no. NCT05820113 © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Turkbey in this issue.

Problem Solving MRI to Reduce False-Positive Biopsy Related to Breast US: Conductivity vs. DWI vs. Abbreviated Contrast-Enhanced MRI.

While breast ultrasound (US) is a useful tool for diagnosing breast masses, it can entail false-positive biopsy results because of some overlapping features between benign and malignant breast masses and subjective interpretation. To evaluate the performance of conductivity imaging for reducing false-positive biopsy results related to breast US, as compared to diffusion-weighted imaging (DWI) and abbreviated MRI consisting of one pre- and one post-contrast T1-weighted imaging. Prospective. Seventy-nine women (median age, 44 years) with 86 Breast Imaging Reporting and Data System (BI-RADS) category 4 masses as detected by breast US. 3-T, T2-weighted turbo spin echo sequence, DWI, and abbreviated contrast-enhanced MRI (T1-weighted gradient echo sequence). US-guided biopsy (reference standard) was obtained on the same day as MRI. The maximum and mean conductivity parameters from whole and single regions of interest (ROIs) were measured. Apparent diffusion coefficient (ADC) values were obtained from an area with the lowest signal within a lesion on the ADC map. The performance of conductivity, ADC, and abbreviated MRI for reducing false-positive biopsies was evaluated using the following criteria: lowest conductivity and highest ADC values among malignant breast lesions and BI-RADS categories 2 or 3 on abbreviated MRI. One conductivity parameter with the maximum area under the curve (AUC) from receiver operating characteristics was selected. A P-value <0.05 was considered statistically significant. US-guided biopsy revealed 65 benign lesions and 21 malignant lesions. The mean conductivity parameter of the single ROI method was selected (AUC = 0.74). Considering conductivity (≤0.10 S/m), ADC (≥1.60 × 10-3 mm2 /sec), and BI-RADS categories 2 or 3 reduced false-positive biopsies by 23% (15 of 65), 38% (25 of 65), and 43% (28 of 65), respectively, without missing malignant lesions. Conductivity imaging may show lower performance than DWI and abbreviated MRI in reducing unnecessary biopsies. 2 TECHNICAL EFFICACY: Stage 2.

Geometric Reliability of Super-Resolution Reconstructed Images from Clinical Fetal MRI in the Second Trimester

Fetal Magnetic Resonance Imaging (MRI) is an important noninvasive diagnostic tool to characterize the central nervous system (CNS) development, significantly contributing to pregnancy management. In clinical practice, fetal MRI of the brain includes the acquisition of fast anatomical sequences over different planes on which several biometric measurements are manually extracted. Recently, modern toolkits use the acquired two-dimensional (2D) images to reconstruct a Super-Resolution (SR) isotropic volume of the brain, enabling three-dimensional (3D) analysis of the fetal CNS.We analyzed 17 fetal MR exams performed in the second trimester, including orthogonal T2-weighted (T2w) Turbo Spin Echo (TSE) and balanced Fast Field Echo (b-FFE) sequences. For each subject and type of sequence, three distinct high-resolution volumes were reconstructed via NiftyMIC, MIALSRTK, and SVRTK toolkits. Fifteen biometric measurements were assessed both on the acquired 2D images and SR reconstructed volumes, and compared using Passing-Bablok regression, Bland-Altman plot analysis, and statistical tests.Results indicate that NiftyMIC and MIALSRTK provide reliable SR reconstructed volumes, suitable for biometric assessments. NiftyMIC also improves the operator intraclass correlation coefficient on the quantitative biometric measures with respect to the acquired 2D images. In addition, TSE sequences lead to more robust fetal brain reconstructions against intensity artifacts compared to b-FFE sequences, despite the latter exhibiting more defined anatomical details.Our findings strengthen the adoption of automatic toolkits for fetal brain reconstructions to perform biometry evaluations of fetal brain development over common clinical MR at an early pregnancy stage.

Evaluation of distal tibial epiphysis and calcaneal epiphysis according to the Vieth method in 3.0T magnetic resonance images: a pilot study.

In forensic medicine practice, age estimation-both in living and deceased individuals-can be requested due to legal requirements. Radiologic methods, such as X-rays, for the estimation of bone age have been discussed, and ethical concerns have been raised. Given these factors, radiologic methods that reduce radiation exposure have gained importance and have become one of the research topics in forensic medicine. In this study, the MR images of the ankles of patients aged between 8 and 25years, obtained with a 3.0T MR scanner, were evaluated retrospectively according to the staging method defined by Vieth et al. In the study, the ankle MR images of 201 cases (83 females and 118 males) with sagittal T1-weighted turbo spin echo and T2-weighted short tau inversion recovery sequences were evaluated independently by two observers. According to the results of our study, the intra- and inter-observer agreements are at a very good level for both the distal tibial and calcaneal epiphyses. All the cases detected as stages 2, 3, and 4 in both sexes for both the distal tibial and the calcaneal epiphyses have been determined to be under the age of 18years. According to the data obtained from our study, we consider that stage 5 for males and stage 6 for both sexes in the distal tibial epiphysis and stage 6 for males in the calcaneal epiphysis can be used to estimate the age of 15years. As far as we know, our study is the first to evaluate ankle MR images with the method defined by Vieth et al. Further studies should be conducted to evaluate the validity of the procedure.

LSW-Net: Lightweight Deep Neural Network Based on Small-World properties for Spine MR Image Segmentation.

Segmenting spinal tissues from MR images is important for automatic image analysis. Deep neural network-based segmentation methods are efficient, yet have high computational costs. To design a lightweight model based on small-world properties (LSW-Net) to segment spinal MR images, suitable for low-computing-power embedded devices. Retrospective. A total of 386 subjects (2948 images) from two independent sources. Dataset I: 214 subjects/779 images, all for disk degeneration screening, 147 had disk degeneration, 52 had herniated disc. Dataset II: 172 subjects/2169 images, 142 patients with vertebral degeneration, 163 patients with disc degeneration. 70% images in each dataset for training, 20% for validation, and 10% for testing. T1- and T2-weighted turbo spin echo sequences at 3 T. Segmentation performance of LSW-Net was compared with four mainstream (including U-net and U-net++) and five lightweight models using five radiologists' manual segmentations (vertebrae, disks, spinal fluid) as reference standard. LSW-Net was also deployed on NVIDIA Jetson nano to compare the pixels number in segmented vertebrae and disks. All models were evaluated with accuracy, precision, Dice similarity coefficient (DSC), and area under the receiver operating characteristic (AUC). Pixel numbers segmented by LSW-Net on the embedded device were compared with manual segmentation using paired t-tests, with P < 0.05 indicating significance. LSW-Net had 98.5% fewer parameters than U-net but achieved similar accuracy in both datasets (dataset I: DSC 0.84 vs. 0.87, AUC 0.92 vs. 0.94; dataset II: DSC 0.82 vs. 0.82, AUC 0.88 vs. 0.88). LSW-Net showed no significant differences in pixel numbers for vertebrae (dataset I: 5893.49 vs. 5752.61, P = 0.21; dataset II: 5073.42 vs. 5137.12, P = 0.56) and disks (dataset I: 1513.07 vs. 1535.69, P = 0.42; dataset II: 1049.74 vs. 1087.88, P = 0.24) segmentation on an embedded device compared to manual segmentation. Proposed LSW-Net achieves high accuracy with fewer parameters than U-net and can be deployed on embedded device, facilitating wider application. 2. 1.

Modulation transfer function measurement of three-dimensional T1-weighted turbo spin echo sequence with low refocusing flip angles using single-plate method

This study aimed to demonstrate the usefulness of modulation transfer function (MTF) measurements using the single-plate method to evaluate changes in resolution properties that are dependent on three parameters: echo train length (ETL), low refocusing flip angle (RFA), and start-up echo in three-dimensional T1-weighted turbo spin echoes (TSE) with a low RFA and to optimize these parameters. Although the MTFs were slightly degraded with an RFA of 120°, they were considerably degraded with an RFA of ≤ 90°. On the other hand, the MTF of low RFA was greatly improved by setting the start-up echo, allowing setting a long ETL. The single-plate method provided a clear and easy evaluation of the resolution properties of low RFA TSE. Furthermore, this method allows us to visualize changes in the signal intensity of each echo in k-space, depending on the sequence variation. These results suggest that the MTF measurement using the single-plate method is useful for evaluating the resolution properties of TSE sequences and optimizing the measured parameters.

Using Machine Learning Methods to Assess Lymphovascular Invasion and Survival in Breast Cancer: Performance of Combining Preoperative Clinical and MRI Characteristics.

Preoperative assessment of lymphovascular invasion (LVI) in invasive breast cancer (IBC) is of high clinical relevance for treatment decision-making and prognosis. To investigate the associations of preoperative clinical and magnetic resonance imaging (MRI) characteristics with LVI and disease-free survival (DFS) by using machine learning methods in patients with IBC. Retrospective. Five hundred and seventy-five women (range: 24-79 years) with IBC who underwent preoperative MRI examinations at two hospitals, divided into the training (N=386) and validation datasets (N=189). Axial fat-suppressed T2-weighted turbo spin-echo sequence and dynamic contrast-enhanced with fat-suppressed T1-weighted three-dimensional gradient echo imaging. MRI characteristics (clinical T stage, breast edema score, MRI axillary lymph node status, multicentricity or multifocality, enhancement pattern, adjacent vessel sign, and increased ipsilateral vascularity) were reviewed independently by three radiologists. Logistic regression (LR), eXtreme Gradient Boosting (XGBoost), k-Nearest Neighbor (KNN), and Support Vector Machine (SVM) algorithms were used to establish the models by combing preoperative clinical and MRI characteristics for assessing LVI status in the training dataset, and the methods were further applied in the validation dataset. The LVI score was calculated using the best-performing of the four models to analyze the association with DFS. Chi-squared tests, variance inflation factors, receiver operating characteristics (ROC), Kaplan-Meier curve, log-rank, Cox regression, and intraclass correlation coefficient were performed. The area under the ROC curve (AUC) and hazard ratios (HR) were calculated. A P-value <0.05 was considered statistically significant. The model established by the XGBoost algorithm had better performance than LR, SVM, and KNN models, achieving an AUC of 0.832 (95% confidence interval [CI]: 0.789, 0.876) in the training dataset and 0.838 (95% CI: 0.775, 0.901) in the validation dataset. The LVI score established by the XGBoost model was an independent indicator of DFS (adjusted HR: 2.66, 95% CI: 1.22-5.80). The XGBoost model based on preoperative clinical and MRI characteristics may help to investigate the LVI status and survival in patients with IBC. 3 TECHNICAL EFFICACY: Stage 2.

Prostatic urinary tract visualization with super-resolution deep learning models.

In urethra-sparing radiation therapy, prostatic urinary tract visualization is important in decreasing the urinary side effect. A methodology has been developed to visualize the prostatic urinary tract using post-urination magnetic resonance imaging (PU-MRI) without a urethral catheter. This study investigated whether the combination of PU-MRI and super-resolution (SR) deep learning models improves the visibility of the prostatic urinary tract. We enrolled 30 patients who had previously undergone real-time-image-gated spot scanning proton therapy by insertion of fiducial markers. PU-MRI was performed using a non-contrast high-resolution two-dimensional T2-weighted turbo spin-echo imaging sequence. Four different SR deep learning models were used: the enhanced deep SR network (EDSR), widely activated SR network (WDSR), SR generative adversarial network (SRGAN), and residual dense network (RDN). The complex wavelet structural similarity index measure (CW-SSIM) was used to quantitatively assess the performance of the proposed SR images compared to PU-MRI. Two radiation oncologists used a 1-to-5 scale to subjectively evaluate the visibility of the prostatic urinary tract. Cohen's weighted kappa (k) was used as a measure of agreement of inter-operator reliability. The mean CW-SSIM in EDSR, WDSR, SRGAN, and RDN was 99.86%, 99.89%, 99.30%, and 99.67%, respectively. The mean prostatic urinary tract visibility scores of the radiation oncologists were 3.70 and 3.53 for PU-MRI (k = 0.93), 3.67 and 2.70 for EDSR (k = 0.89), 3.70 and 2.73 for WDSR (k = 0.88), 3.67 and 2.73 for SRGAN (k = 0.88), and 4.37 and 3.73 for RDN (k = 0.93), respectively. The results suggest that SR images using RDN are similar to the original images, and the SR deep learning models subjectively improve the visibility of the prostatic urinary tract.

An unsupervised deep learning-based image translation method for retrospective motion correction of high resolution kidney MRI

A primary challenge for in vivo kidney magnetic resonance imaging (MRI) is the presence of different types of involuntary physiological motion, affecting the diagnostic utility of acquired images due to severe motion artifacts. Existing prospective and retrospective motion correction methods remain ineffective when dealing with complex large amplitude nonrigid motion artifacts. Here, we introduce an unsupervised deep learning-based image to image translation method between motion-affected and motion-free image domains, for correction of rigid-body, respiratory and nonrigid motion artifacts in vivo kidney MRI.High resolution (i.e., 156 × 156 × 370 μm) ex vivo 3 Tesla MRI scans of 13 porcine kidneys (because of their anatomical homology to human kidney) were conducted using a 3D T2-weighted turbo spin echo sequence. Rigid-body, respiratory and nonrigid motion-affected images were then simulated using the magnitude-only ex vivo motion-free image set. Each 2D coronal slice of motion-affected and motion-free image volume was then divided into patches of 128 × 128 for training the model. We proposed to add normalised cross-correlation loss to cycle consistency generative adversarial network structure (NCC-CycleGAN), to enforce edge alignment between motion-corrected and motion-free image domains.Our NCC-CycleGAN motion correction model demonstrated high performance with an in-tissue structural similarity index measure of 0.77 ± 0.08, peak signal-to-noise ratio of 26.67 ± 3.44 and learned perceptual image patch similarity of 0.173 ± 0.05 between the reconstructed motion-corrected and ground truth motion-free images. This corresponds to a significant respective average improvement of 34%, 23% and 39% (p < 0.05; paired t-test) for the three metrics to correct the three different types of simulated motion artifacts.We demonstrated the feasibility of developing an unsupervised deep learning-based method for efficient automated retrospective kidney MRI motion correction, while preserving microscopic tissue structures in high resolution imaging.

Comparison of a deep learning-accelerated T2-weighted turbo spin echo sequence and its conventional counterpart for female pelvic MRI: reduced acquisition times and improved image quality

ObjectivesTo investigate the feasibility of a deep learning-accelerated T2-weighted turbo spin echo (TSE) sequence (T2DL) applied to female pelvic MRI, using standard T2-weighted TSE (T2S) as reference.MethodsIn total, 24 volunteers and 48 consecutive patients with benign uterine diseases were enrolled. Patients in the menstrual phase were excluded. T2S and T2DL sequences in three planes were performed for each participant. Quantitative image evaluation was conducted by calculating the signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR). Image geometric distortion was evaluated by measuring the diameters in all three directions of the uterus and lesions. Qualitative image evaluation including overall image quality, artifacts, boundary sharpness of the uterine zonal layers, and lesion conspicuity were assessed by three radiologists using a 5-point Likert scale, with 5 indicating the best quality. Comparative analyses were conducted for the two sequences.ResultsT2DL resulted in a 62.7% timing reduction (1:54 min for T2DL and 5:06 min for T2S in axial, sagittal, and coronal imaging, respectively). Compared to T2S, T2DL had significantly higher SNR (p ≤ 0.001) and CNR (p ≤ 0.007), and without geometric distortion (p = 0.925–0.981). Inter-observer agreement regarding qualitative evaluation was excellent (Kendall’s W > 0.75). T2DL provided superior image quality (all p < 0.001), boundary sharpness of the uterine zonal layers (all p < 0.001), lesion conspicuity (p = 0.002, p < 0.001, and p = 0.021), and fewer artifacts (all p < 0.001) in sagittal, axial, and coronal imaging.ConclusionsCompared with standard TSE, deep learning-accelerated T2-weighted TSE is feasible to reduce acquisition time of female pelvic MRI with significant improvement of image quality.

Simultaneous Multislice Accelerated TSE for Improved Spatiotemporal Resolution and Diagnostic Accuracy in Magnetic Resonance Neurography: A Feasibility Study.

This study aims to evaluate the utility of simultaneous multislice (SMS) acceleration for routine magnetic resonance neurography (MRN) at 3 T. Patients with multiple sclerosis underwent MRN of the sciatic nerve consisting of a standard fat-saturated T2-weighted turbo spin echo (TSE) sequence using integrated parallel acquisition technique (PAT2) acceleration and 2 T2 TSE sequences using a combination of PAT-SMS acceleration (1) to reduce scan time (PAT2-SMS2; SMS-TSE FAST ) and (2) for time neutral increase of in-plane resolution (PAT1-SMS2; SMS-TSE HR ). Acquisition times were 5:29 minutes for the standard T2 TSE, 3:12 minutes for the SMS-TSE FAST , and 5:24 minutes for the SMS-TSE HR . Six qualitative imaging parameters were analyzed by 2 blinded readers using a 5-point Likert scale and T2 nerve lesions were quantified, respectively. Qualitative and quantitative image parameters were compared, and both interrater and intrarater reproducibility were statistically assessed. In addition, signal-to-noise ratio/contrast-to-noise ratio (CNR) was obtained in healthy controls using the exact same imaging protocol. A total of 15 patients with MS (mean age ± standard deviation, 38.1 ± 11 years) and 10 healthy controls (mean age, 29.1 ± 7 years) were enrolled in this study. CNR analysis was highly reliable (intraclass correlation coefficient, 0.755-0.948) and revealed a significant CNR decrease for the sciatic nerve for both SMS protocols compared with standard T2 TSE (SMS-TSE FAST /SMS-TSE HR , -39%/-55%; P ≤ 0.01). Intrarater and interrater reliability of qualitative image review was good to excellent (κ: 0.672-0.971/0.617-0.883). Compared with the standard T2 TSE sequence, both SMS methods were shown to be superior in reducing pulsatile flow artifacts ( P < 0.01). Ratings for muscle border sharpness, detailed muscle structures, nerve border sharpness, and nerve fascicular structure did not differ significantly between the standard T2 TSE and the SMS-TSE FAST ( P > 0.05) and were significantly better for the SMS-TSE HR than for standard T2 TSE ( P < 0.001). Muscle signal homogeneity was mildly inferior for both SMS-TSE FAST ( P > 0.05) and SMS-TSE HR ( P < 0.001). A significantly higher number of T2 nerve lesions were detected by SMS-TSE HR ( P ≤ 0.01) compared with the standard T2 TSE and SMS-TSE FAST , whereas no significant difference was observed between the standard T2 TSE and SMS-TSE FAST . Implementation of SMS offers either to substantially reduce acquisition time by over 40% without significantly impeding image quality compared with the standard T2 TSE or to increase in-plane resolution for a high-resolution approach and improved depiction of T2 nerve lesions while keeping acquisition times constant. This addresses the specific needs of MRN by providing different imaging approaches for 2D clinical MRN.

Risk Factors for Cerebrovascular Events in Moyamoya Angiopathy Using 4D Flow MRI: A Pilot Study.

Little is known about internal carotid artery (ICA) hemodynamics in patients with moyamoya angiopathy (MMA) and its role in cerebrovascular events. To characterize ICA hemodynamics in MMA patients by 4D flow MRI and investigate its relationship with cerebrovascular events. Prospective. Seventy MMA patients (50 years old ± 9, 30 males). Time-resolved three-directional velocity encoded fast field echo sequence (4D flow) MRI, T1-weighted fast field echo sequence, T2 weighted turbo spin echo sequence, diffusion weighted echo planar imaging; T2-weighted fluid-attenuated inversion recovery turbo spin echo sequence, susceptibility weighted fast field echo sequence, and time-of-flight MR angiography fast field echo sequence at 3.0T. ICA hemodynamics (maximum and average velocity [Vmax , Vavg ], average blood flow [Flowavg ], and wall shear stress) were analyzed based on 4D flow data. Cerebral infarction, defined as the occurrence of events, in 124 brain hemispheres was determined according to clinical symptoms and conventional brain MR imaging. The independent-samples T test was used to evaluate differences in ICA hemodynamics between infarcted and non-infarcted hemispheres. Binary logistic regression was performed to investigate the relationship between ICA hemodynamics and events. A P value < 0.05 was considered statistically significant. Sixty-one infarcted hemispheres (eight hemispheres with acute ischemic damage, 30 with chronic ischemic damage, and 23 with chronic hemorrhagic damage) had cerebrovascular events and 63 non-infarcted hemispheres did not. The hemodynamic parameters in the infarcted hemispheres (Vmax : P < 0.001; Vavg : P=0.003; and Flowavg : P=0.004) were significantly lower than those in the non-infarcted hemispheres. However, Vmax (P=0.052), Vavg (P=0.107), and Flowavg (P=0.074) were not significantly different among hemispheres with acute ischemic lesions, chronic ischemic lesions and chronic hemorrhagic lesions. Vmax (odds ratio 3.033, 95% CI: 1.075-8.562) was independently associated with cerebrovascular events. Vmax maybe a higher risk factor of cerebrovascular events in MMA patients. 2 TECHNICAL EFFICACY STAGE: 3.