Fast Spin Echo Research Articles

Prospective evaluation of in vivo and phantom repeatability and reproducibility of diffusion-weighted MRI sequences on 1.5 T MRI-linear accelerator (MR-Linac) and MR simulator devices for head and neck cancers

IntroductionDiffusion-weighted imaging (DWI) on MRI-linear accelerator (MR-linac) systems can potentially be used for monitoring treatment response and adaptive radiotherapy in head and neck cancers (HNC) but requires extensive validation. We performed technical validation to compare six total DWI sequences on an MR-linac and MR simulator (MR sim) in patients, volunteers, and phantoms. MethodsTen human papillomavirus-positive oropharyngeal cancer patients and ten healthy volunteers underwent DWI on a 1.5 T MR-linac with three DWI sequences: echo planar imaging (EPI), split acquisition of fast spin echo signals (SPLICE), and turbo spin echo (TSE). Volunteers were also imaged on a 1.5 T MR sim with three sequences: EPI, BLADE (vendor tradename), and readout segmentation of long variable echo trains (RESOLVE). Participants underwent two scan sessions per device and two repeats of each sequence per session. Repeatability and reproducibility within-subject coefficient of variation (wCV) of mean ADC were calculated for tumors and lymph nodes (patients) and parotid glands (volunteers). ADC bias, repeatability/reproducibility metrics, SNR, and geometric distortion were quantified using a phantom. ResultsIn vivo repeatability/reproducibility wCV for parotids were 5.41%/6.72%, 3.83%/8.80%, 5.66%/10.03%, 3.44%/5.70%, 5.04%/5.66%, 4.23%/7.36% for EPIMR-linac, SPLICE, TSE, EPIMR sim, BLADE, RESOLVE. Repeatability/reproducibility wCV for EPIMR-linac, SPLICE, TSE were 9.64%/10.28%, 7.84%/8.96%, 7.60%/11.68% for tumors and 7.80%/9.95%, 7.23%/8.48%, 10.82%/10.44% for nodes. All sequences except TSE had phantom ADC biases within ± 0.1x10-3 mm2/s for most vials (EPIMR-linac, SPLICE, and BLADE had 2, 3, and 1 vials out of 13 with larger biases, respectively). SNR of b = 0 images was 87.3, 180.5, 161.3, 171.0, 171.9, 130.2 for EPIMR-linac, SPLICE, TSE, EPIMR sim, BLADE, RESOLVE. ConclusionMR-linac DWI sequences demonstrated near-comparable performance to MR sim sequences and warrant further clinical validation for treatment response assessment in HNC.

Detecting Double Expression Status in Primary Central Nervous System Lymphoma Using Multiparametric MRI Based Machine Learning.

Double expression lymphoma (DEL) is a subtype of primary central nervous system lymphoma (PCNSL) that often has a poor prognosis. Currently, there are limited noninvasive ways to detect protein expression. To detect DEL in PCNSL using multiparametric MRI-based machine learning. Retrospective. Forty PCNSL patients were enrolled in the study among whom 17 were DEL (9 males and 8 females, 61.29 ± 14.14 years) and 23 were non-DEL (14 males and 9 females, 55.57 ± 14.16 years) with 59 lesions (28 DEL and 31 non-DEL). ADC map derived from DWI (b = 0/1000 s/mm2 ), fast spin echo T2WI, T2FLAIR, and contrast-enhanced T1 weighted imaging (T1CE) were collected at 3.0 T. Two raters manually segmented lesions by ITK-SNAP on ADC, T2WI, T2FLAIR and T1CE. A total of 2234 radiomics features from the tumor segmentation area were extracted. The t-test was conducted to filter the features, and elastic net regression algorithm combined with recursive feature elimination was used to calculate the essential features. Finally, 12 groups with combinations of different sequences were fitted to 6 classifiers, and the optimal models were selected. Continuous variables were assessed by the t-test, while categorical variables were assessed by the non-parametric test. Interclass correlation coefficient tested variables' consistency. Sensitivity, specificity, accuracy F1-score, and area under the curve (AUC) were used to evaluate model performance. DEL status could be identified to varying degrees with 72 models based on radiomics, and model performance could be improved by combining different sequences and classifiers. Both SVMlinear and logistic regression (LR) combined with four sequence group had similar largest AUCmean (0.92 ± 0.09 vs. 0.92 ± 0.05), and SVMlinear was considered as the optimal model in this study since the F1-score of SVMlinear (0.88) was higher than that of LR (0.83). Multiparametric MRI-based machine learning is promising in DEL detection. 4 TECHNICAL EFFICACY STAGE: 2.

Deep learning HASTE sequence compared with T2-weighted BLADE sequence for liver MRI at 3 Tesla: a qualitative and quantitative prospective study.

To qualitatively and quantitatively compare a single breath-hold fast half-Fourier single-shot turbo spin echo sequence with deep learning reconstruction (DL HASTE) with T2-weighted BLADE sequence for liver MRI at 3T. From December 2020 to January 2021, patients with liver MRI were prospectively included. For qualitative analysis, sequence quality, presence of artifacts, conspicuity, and presumed nature of the smallest lesion were assessed using the chi-squared and McNemar tests. For quantitative analysis, number of liver lesions, size of the smallest lesion, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) in both sequences were assessed using the paired Wilcoxon signed-rank test. Intraclass correlation coefficients (ICCs) and kappa coefficients were used to assess agreement between the two readers. One hundred and twelve patients were evaluated. Overall image quality (p = .006), artifacts (p < .001), and conspicuity of the smallest lesion (p = .001) were significantly better for the DL HASTE sequence than for the T2-weighted BLADE sequence. Significantly more liver lesions were detected with the DL HASTE sequence (356 lesions) than with the T2-weighted BLADE sequence (320 lesions; p < .001). CNR was significantly higher for the DL HASTE sequence (p < .001). SNR was higher for the T2-weighted BLADE sequence (p < .001). Interreader agreement was moderate to excellent depending on the sequence. Of the 41 supernumerary lesions visible only on the DL HASTE sequence, 38 (93%) were true-positives. The DL HASTE sequence can be used to improve image quality and contrast and reduces artifacts, allowing the detection of more liver lesions than with the T2-weighted BLADE sequence. The DL HASTE sequence is superior to the T2-weighted BLADE sequence for the detection of focal liver lesions and can be used in daily practice as a standard sequence. • The half-Fourier acquisition single-shot turbo spin echo sequence with deep learning reconstruction (DL HASTE sequence) has better overall image quality, reduced artifacts (particularly motion artifacts), and improved contrast, allowing the detection of more liver lesions than with the T2-weighted BLADE sequence. • The acquisition time of the DL HASTE sequence is at least eight times faster (21s) than that of the T2-weighted BLADE sequence (3-5min). • The DL HASTE sequence could replace the conventional T2-weighted BLADE sequence to meet the growing indication for hepatic MRI in clinical practice, given its diagnostic and time-saving performance.

Diagnostic performance of deep learning–based reconstruction algorithm in 3D MR neurography

ObjectiveThe study aims to evaluate the diagnostic performance of deep learning–based reconstruction method (DLRecon) in 3D MR neurography for assessment of the brachial and lumbosacral plexus.Materials and methodsThirty-five exams (18 brachial and 17 lumbosacral plexus) of 34 patients undergoing routine clinical MR neurography at 1.5 T were retrospectively included (mean age: 49 ± 12 years, 15 female). Coronal 3D T2-weighted short tau inversion recovery fast spin echo with variable flip angle sequences covering plexial nerves on both sides were obtained as part of the standard protocol. In addition to standard-of-care (SOC) reconstruction, k-space was reconstructed with a 3D DLRecon algorithm.Two blinded readers evaluated images for image quality and diagnostic confidence in assessing nerves, muscles, and pathology using a 4-point scale. Additionally, signal-to-noise ratio (SNR) and contrast-to-noise ratios (CNR) between nerve, muscle, and fat were measured.For comparison of visual scoring result non-parametric paired sample Wilcoxon signed-rank testing and for quantitative analysis paired sample Student’s t-testing was performed.ResultsDLRecon scored significantly higher than SOC in all categories of image quality (p < 0.05) and diagnostic confidence (p < 0.05), including conspicuity of nerve branches and pathology. With regard to artifacts there was no significant difference between the reconstruction methods.Quantitatively, DLRecon achieved significantly higher CNR and SNR than SOC (p < 0.05).ConclusionDLRecon enhanced overall image quality, leading to improved conspicuity of nerve branches and pathology, and allowing for increased diagnostic confidence in evaluation of the brachial and lumbosacral plexus.

MRI Assessment of Brain Frailty and Clinical Outcome in Patients With Acute Posterior Perforating Artery Infarction.

Global brain health has gained increasing attention recently. Imaging markers of brain frailty have been related to functional outcomes in previous studies on anterior circulation; however, little data are available on imaging markers and posterior circulation. To investigate the impact of brain frailty on functional outcomes in patients with acute perforating artery infarction (PAI) of the posterior circulation. Prospective. One hundred patients (60.78 ± 9.51 years, 72% men) with acute posterior circulation PAI (determined by diffusion-weighted magnetic resonance imaging (MRI)/time-of-flight MR angiography). T1- and T2-weighted fast spin echo, T2-weighted fluid-attenuated inversion recovery, diffusion-weighted echo planar, gradient echo (susceptibility-weight imaging), and 3D time-of-flight MR angiography sequences at 3.0 T. Periventricular and deep white matter hyperintensities (WMH), enlarged perivascular spaces (EPVS) in the basal ganglia and centrum semiovale area, lacunes, cerebral microbleeds (CMB), and total brain frailty score by calculating the above imaging characters were rated visually by three radiologists with 9, 10, and 11 years of experience and one neuroradiologist with 12. Infarction volume was assessed using baseline diffusion-weighted imaging (DWI) data obtained within 24 hours of symptom onset. A modified Rankin Scale (mRS) score >1 on day 90 defined an adverse functional outcome. Associations between the imaging markers of brain frailty and functional outcomes were assessed. Fisher's exact test, Mann-Whitney U test, and multivariable binary logistic regression. A P value <0.05 was considered statistically significant. Adverse prognoses (mRS > 1) were observed in 34 (34%) patients. Infarction volume, periventricular WMH, deep WMH, basal ganglia EPVS, CMB, and the brain frailty score were significantly associated with adverse functional outcomes. An increased brain frailty score was significantly associated with unfavorable mRS score on day 90 (odds ratio 1.773, 95% confidence interval 1.237-2.541). Advanced MRI imaging markers of brain frailty, individually or combined as a total brain frailty score, were associated with worse functional outcomes after acute posterior circulation PAI. 3 TECHNICAL EFFICACY: Stage 3.

A Deep Learning Pipeline Using Prior Knowledge for Automatic Evaluation of Placenta Accreta Spectrum Disorders With MRI.

The diagnosis of prenatal placenta accreta spectrum (PAS) with magnetic resonance imaging (MRI) is highly dependent on radiologists' experience. A deep learning (DL) method using the prior knowledge that PAS-related signs are generally found along the utero-placental borderline (UPB) may help radiologists, especially those with less experience, to mitigate this issue. To develop a DL tool for antenatal diagnosis of PAS using T2-weighted MR images. Retrospective. Five hundred and forty pregnant women with clinically suspected PAS disorders from two institutions, divided into training (409), internal test (103), and external test (28) datasets. Sagittal T2-weighted fast spin echo sequence at 1.5 T and 3 T. An nnU-Net was trained for placenta segmentation. The UPB straightening approach was used to extract the utero-placental boundary region. The UPB image was then fed into DenseNet-PAS for PAS diagnosis. DenseNet-PP learnt placental position information to improve the PAS diagnosis performance. Three radiologists with 8, 10, and 12 years of experience independently evaluated the images. Two radiologists marked the placenta tissue. Histopathological findings were the reference standard. Area under the curve (AUC) was used to evaluate the classification. Dice coefficient evaluated the segmentation between radiologists and the model performance. The Mann-Whitney U-test or the chi-squared test assessed the significance of differences. Decision curve analysis was used to determine clinical effectiveness. DeLong's test was used to compare AUCs. Of the 540 patients, 170 had PAS disorders confirmed by histopathology. The DL model using UPB images and placental position yielded the highest AUC of 0.860 and 0.897 in internal test and external test cohorts, respectively, significantly exceeding the performance of three radiologists (internal test AUC, 0.737-0.770). By extracting the UPB image, this fully automatic DL pipeline achieved high accuracy and may assist radiologists in PAS diagnosis using MRI. 3 TECHNICAL EFFICACY: Stage 2.

Brain-Tumor Interface-Based MRI Radiomics Models to Determine EGFR Mutation, Response to EGFR-TKI and T790M Resistance Mutation in Non-Small Cell Lung Carcinoma Brain Metastasis.

Preoperative assessment of epidermal growth factor receptor (EGFR) status, response to EGFR-tyrosine kinase inhibitors (TKI) and development of T790M mutation in non-small cell lung carcinoma (NSCLC) patients with brain metastases (BM) is important for clinical decision-making, while previous studies were only based on the whole BM. To investigate values of brain-to-tumor interface (BTI) for determining the EGFR mutation, response to EGFR-TKI and T790M mutation. Retrospective. Two hundred thirty patients from Hospital 1 (primary cohort) and 80 patients from Hospital 2 (external validation cohort) with BM and histological diagnosis of primary NSCLC, and with known EGFR status (biopsy) and T790M mutation status (gene sequencing). Contrast-enhanced T1-weighted (T1CE) and T2-weighted (T2W) fast spin echo sequences at 3.0T MRI. Treatment response to EGFR-TKI therapy was determined by the Response Evaluation Criteria in Solid Tumors. Radiomics features were extracted from the 4 mm thickness BTI and selected by least shrinkage and selection operator regression. The selected BTI features and volume of peritumoral edema (VPE) were combined to construct models using logistic regression. The performance of each radiomics model was evaluated using the area under the receiver operating characteristic (ROC) curve (AUC). A total of 7, 3, and 3 features were strongly associated with the EGFR mutation status, response to EGFR-TKI and T790M mutation status, respectively. The developed models combining BTI features and VPE can improve the performance than those based on BTI features alone, generating AUCs of 0.814, 0.730, and 0.774 for determining the EGFR mutation, response to EGFR-TKI and T790M mutation, respectively, in the external validation cohort. BTI features and VPE were associated with the EGFR mutation status, response to EGFR-TKI and T790M mutation status in NSCLC patients with BM. 3 Technical Efficacy: Stage 2.

Evaluation of 3D stack-of-spiral turbo FLASH acquisitions for pseudo-continuous and velocity-selective ASL-derived brain perfusion mapping.

The most-used 3D acquisitions for ASL are gradient and spin echo (GRASE)- and stack-of-spiral (SOS)-based fast spin echo, which require multiple shots. Alternatively, turbo FLASH (TFL) allows longer echo trains, and SOS-TFL has the potential to reduce the number of shots to even single-shot, thus improving the temporal resolution. Here we compare the performance of 3D SOS-TFL and 3D GRASE for ASL at 3T. The 3D SOS-TFL readout was optimized with respect to fat suppression and excitation flip angles for pseudo-continuous ASL- and velocity-selective (VS)ASL-derived cerebral blood flow (CBF) mapping as well as for VSASL-derived cerebral blood volume (CBV) mapping. Results were compared with 3D GRASE readout on healthy volunteers in terms of perfusion quantification and temporal SNR (tSNR) efficiency. CBF and CBV mapping derived from 3D SOS-TFL-based ASL was demonstrated on one stroke patient, and the potential for single-shot acquisitions was exemplified. SOS-TFL with a 15° flip angle resulted in adequate tSNR efficiency with negligible image blurring. Selective water excitation was necessary to eliminate fat-induced artifacts. For pseudo-continuous ASL- and VSASL-based CBF and CBV mapping, compared to the employed four-shot 3D GRASE with an acceleration factor of 2, the fully sampled 3D SOS-TFL delivered comparable performance (with a similar scan time) using three shots, which could be further undersampled to achieve single-shot acquisition with higher tSNR efficiency. SOS-TFL had reduced CSF contamination for VSASL-CBF. 3D SOS-TFL acquisition was found to be a viable substitute for 3D GRASE for ASL with sufficient tSNR efficiency, minimal relaxation-induced blurring, reduced CSF contamination, and the potential of single-shot, especially for VSASL.

High-Resolution Single-Shot Fast Spin-Echo MR Imaging with Deep Learning Reconstruction Algorithm Can Improve Repeatability and Reproducibility of Follicle Counting.

To investigate the diagnostic performance of high-resolution single-shot fast spin-echo (SSFSE) imaging with deep learning (DL) reconstruction algorithm on follicle counting and compare it with original SSFSE images and conventional fast spin-echo (FSE) images. This study included 20 participants (40 ovaries) with clinically confirmed polycystic ovary syndrome (PCOS) who underwent high-resolution ovary MRI, including three-plane T2-weighted FSE sequences and slice-matched T2-weighted SSFSE sequences. A DL reconstruction algorithm was applied to the SSFSE sequences to generate SSFSE-DL images, and the original SSFSE images were also saved. Subjective evaluations such as the blurring artifacts, subjective noise, and clarity of the follicles on the SSFSE-DL, SSFSE, and conventional FSE images were independently conducted by two observers. Intra-class correlation coefficients and Bland-Altman plots were used to present the repeatability and reproducibility of the follicle number per ovary (FNPO) based on the three types of images. SSFSE-DL images showed less blurring artifact, subjective noise, and better clarity of the follicles than SSFSE and FSE (p < 0.05). For the repeatability of the FNPO, SSFSE-DL showed the highest intra-observer (ICC = 0.930; 95% CI: 0.878-0.962) and inter-observer (ICC = 0.914; 95% CI: 0.843-0.953) agreements. The inter-observer 95% limits of agreement (LOA) for SSFSE-DL, SSFSE, and FSE ranged from -3.7 to 4.5, -4.4 to 7.0, and -7.1 to 7.6, respectively. The intra-observer 95% LOA for SSFSE-DL, SSFSE, and FSE ranged from -3.5 to 4.0, -5.1 to 6.1, and -5.7 to 4.2, respectively. The absolute values of intra-observer and inter-observer differences for SSFSE-DL were significantly lower than those for SSFSE and FSE (p < 0.05). Compared with the original SSFSE images and the conventional FSE images, high-resolution SSFSE images with DL reconstruction algorithm can better display follicles, thus improving FNPO assessment.

Latent signal models: Learning compact representations of signal evolution for improved time‐resolved, multi‐contrast MRI

To improve time-resolved reconstructions by training auto-encoders to learn compact representations of Bloch-simulated signal evolution and inserting the decoder into the forward model. Building on model-based nonlinear and linear subspace techniques, we train auto-encoders on dictionaries of simulated signal evolution to learn compact, nonlinear, latent representations. The proposed latent signal model framework inserts the decoder portion of the auto-encoder into the forward model and directly reconstructs the latent representation. Latent signal models essentially serve as a proxy for fast and feasible differentiation through the Bloch equations used to simulate signal. This work performs experiments in the context of T2 -shuffling, gradient echo EPTI, and MPRAGE-shuffling. We compare how efficiently auto-encoders represent signal evolution in comparison to linear subspaces. Simulation and in vivo experiments then evaluate if reducing degrees of freedom by incorporating our proxy for the Bloch equations, the decoder portion of the auto-encoder, into the forward model improves reconstructions in comparison to subspace constraints. An auto-encoder with 1 real latent variable represents single-tissue fast spin echo, EPTI, and MPRAGE signal evolution to within 0.15% normalized RMS error, enabling reconstruction problems with 3 degrees of freedom per voxel (real latent variable + complex scaling) in comparison to linear models with 4-8 degrees of freedom per voxel. In simulated/in vivo T2 -shuffling and in vivo EPTI experiments, the proposed framework achieves consistent quantitative normalized RMS error improvement over linear approaches. From qualitative evaluation, the proposed approach yields images with reduced blurring and noise amplification in MPRAGE-shuffling experiments. Directly solving for nonlinear latent representations of signal evolution improves time-resolved MRI reconstructions.

MR-orthopantomography in operative dentistry and oral and maxillofacial surgery: a proof of concept study

This prospective study aimed to present, compare, and evaluate the suitability of five different magnetic resonance imaging (MRI) protocols (3D double-echo steady-state (DESS), 3D fast spin echo short-tau inversion recovery (SPACE-STIR), 3D fast spin echo spectral attenuated inversion recovery (SPACE-SPAIR), volumetric interpolated breath-hold examination (T1-VIBE-Dixon), and ultrashort echo time (UTE)) and for orthopantomogram (OPG)-like MRI reconstructions using a novel mandibular coil. Three readers assessed MR-OPGs of 21 volunteers regarding technical image quality (4, excellent; 0, severely reduced), susceptibility to artifacts (3, absence; 0, massive), and visualization of anatomical structures in the oral cavity and surrounding skeletal structures (4, fine details visible; 0, no structures visible). Average image quality was good (3.29 ± 0.83) for all MRI protocols, with UTE providing the best image quality (3.52 ± 0.62) and no to minor artifacts (2.56 ± 0.6). Full diagnostic interpretability of the osseous structures is best in VIBE-Dixon and UTE MR-OPGs. DESS provided excellent visualization of the finest details of the nervous tissue (3.95 ± 0.22). Intra-reader and inter-reader agreement between the readers was good to excellent for all protocols (ICCs 0.812–0.957). MR-OPGs provide indication-specific accurate imaging of the oral cavity and could contribute to the early detection of pathologies, staging, and radiological follow-up of oral and maxillofacial diseases.

Reducing Gadolinium Exposure in Patients Undergoing Monitoring for Meningiomas.

Background Due to the non-malignant and slow-growing nature of many meningiomas, surveillance with serial magnetic resonance imaging (MRI) serves as an acceptable management plan. However, repeated imaging with gold-standard contrast-based studies may lead to contrast-associated adverse effects. Non-gadolinium T2 sequences may serve as a suitable alternative without the risk of adverse effects of contrast. Thus, this study sought to investigate the agreement between post-contrast T1 and non-gadolinium T2 MRI sequences in the measurement of meningioma growth. Methodology The Virginia Commonwealth University School of Medicine (VCU SOM) brain tumor database was used to create a cohort of meningioma patients and determine the number of patients who had T1 post-contrast imaging accompanied by readily measurable imaging from either T2 fast spin echo (FSE) or T2 fluid-attenuated inversion recovery (FLAIR) sequences. Measurements of the largest axial and perpendicular diameters of each tumor were conducted by two independent observers using T1 post-contrast, T2 FSE, and T2 FLAIR imaging series.Lin's concordance correlation coefficient (CCC) was calculated to assess inter-rater reliability between observers and agreement between measurements of tumor diameter among the different imaging sequences. Results In total, 33 patients (average age = 72.1 ± 12.9 years, 90% female) with meningiomas were extracted from our database, with 22 (66.7%) undergoing T1 post-contrast imaging accompanied with readily measurable imaging from T2 FSE and/or T2 FLAIR sequences. The inter-rater reliability between the measurements of T1 axial and perpendicular diameters was 0.96 (95% confidence interval (CI) = 0.92-0.98) and 0.92 (95% CI = 0.83-0.97), respectively. The inter-rater reliability between the measurements of T2 axial perpendicular diameters was 0.93 (95% = CI 0.92-0.97) and 0.89 (95% CI = 0.74-0.95), respectively. The agreements between the measurement of T1 and T2 FSE axial diameter by each observer were 0.97 (95% CI = 0.93-0.98) and 0.92 (95% CI = 0.81-0.97). The agreements between the measurements of T1 and T2 FSE perpendicular diameter measurements by each observer were 0.98 (95% CI = 0.95-0.99) and 0.88 (95% CI = 0.73-0.95). Conclusions Two-thirds of our patients had meningiomas that were readily measurable on either T2 FSE or T2 FLAIR sequences. Additionally, there was excellent inter-rater reliability between the observers in our study as well as an agreement between individual measurements of T1 post-contrast and T2 FSE tumor diameters. These findings suggest that T2 FSE may serve as a safe and similarly effective surveillance method for the long-term management of meningioma patients.

The Impact of Fatty Infiltration on MRI Segmentation of Lower Limb Muscles in Neuromuscular Diseases: A Comparative Study of Deep Learning Approaches.

Deep learning methods have been shown to be useful for segmentation of lower limb muscle MRIs of healthy subjects but, have not been sufficiently evaluated on neuromuscular disease (NDM) patients. Evaluate the influence of fat infiltration on convolutional neural network (CNN) segmentation of MRIs from NMD patients. Retrospective study. Data were collected from a hospital database of 67 patients with NMDs and 14 controls (age: 53 ± 17 years, sex: 48 M, 33 F). Ten individual muscles were segmented from the thigh and six from the calf (20 slices, 200 cm section). A 1.5 T. Sequences: 2D T1 -weighted fast spin echo. Fat fraction (FF): three-point Dixon 3D GRE, magnetization transfer ratio (MTR): 3D MT-prepared GRE, T2: 2D multispin-echo sequence. U-Net 2D, U-Net 3D, TransUNet, and HRNet were trained to segment thigh and leg muscles (101/11 and 95/11 training/validation images, 10-fold cross-validation). Automatic and manual segmentations were compared based on geometric criteria (Dice coefficient [DSC], outlier rate, absence rate) and reliability of measured MRI quantities (FF, MTR, T2, volume). Bland-Altman plots were chosen to describe agreement between manual vs. automatic estimated FF, MTR, T2 and volume. Comparisons were made between muscle populations with an FF greater than 20% (G20+) and lower than 20% (G20-). The CNNs achieved equivalent results, yet only HRNet recognized every muscle in the database, with a DSC of 0.91 ± 0.08, and measurement biases reaching -0.32% ± 0.92% for FF, 0.19 ± 0.77 for MTR, -0.55 ± 1.95 msec for T2, and - 0.38 ± 3.67 cm3 for volume. The performances of HRNet, between G20- and G20+ decreased significantly. HRNet was the most appropriate network, as it did not omit any muscle. The accuracy obtained shows that CNNs could provide fully automated methods for studying NMDs. However, the accuracy of the methods may be degraded on the most infiltrated muscles (>20%). 4. Stage 1.

High-efficiency 3D black-blood thoracic aorta imaging with patch-based low-rank tensor reconstruction.

Three-dimensional (3D) black-blood (BB) vessel wall imaging is a promising noninvasive imaging technique for assessing thoracic aortic diseases. We aimed to develop and evaluate a fast thoracic aorta vessel wall imaging method with patch-based low-rank tensor (Pt-LRT) reconstruction using the 3D-modulated variable flip angle fast-spin echo (vFA-FSE) sequence. The Pt-LRT technique adopts a low-rank tensor image model with regularization to explore the local low-rankness and nonlocal redundancies of the images to assess the thoracic aorta vessel wall. It uses high-order tensors to capture correlations between data in multiple dimensions and reconstructs images from highly undersampled data. For this study, 12 healthy participants and 2 patients with thoracic aortic diseases were evaluated at 3T magnetic resonance (MR). The reconstruction results were compared to the traditional generalized autocalibrating partially parallel acquisitions (GRAPPA) and ℓ1-SPIRiT reconstruction to assess the feasibility of the proposed framework. Quantitative analyses of the vessel wall thickness (VWT), internal diameter (ID), lumen area (LA), and contrast-to-noise ratio (CNR) between the lumen and vessel wall were performed on all healthy participants. Results demonstrated no significant differences between the GRAPPA and the proposed Pt-LRT in VWT, ID, or LA of the aorta (P<0.05). A higher mean CNR was attained with 3D patch-based low-rank tensor reconstruction than with ℓ1-SPIRiT reconstruction (49.4±10.8 vs. 38.9±8.2). The proposed 3D BB thoracic aorta vessel wall imaging method can reduce the scan time and produce an image quality that is in good agreement with the conventional GRAPPA acquisition, which takes approximately more than 8 min. This study also shows that the proposed Pt-LRT method substantially improves the visualization and sharpness of the vessel wall and the definition of the tissue boundary compared to the imaging obtained with ℓ1-SPIRiT.

Development and Validation of a Combined MRI Radiomics, Imaging and Clinical Parameter-Based Machine Learning Model for Identifying Idiopathic Central Precocious Puberty in Girls.

Idiopathic central precocious puberty (ICPP) impairs child development, without early intervention. The current reference standard, the gonadotropin-releasing hormone stimulation test, is invasive which may hinder diagnosis and intervention. To develop a model for accurate diagnosis of ICPP, by integrating pituitary MRI, carpal bone age, gonadal ultrasound, and basic clinical data. Retrospective. A total of 492 girls with PP (185 with ICPP and 307 peripheral precocious puberty [PPP]) were randomly divided by reference standard into training (75%) and internal validation (25%) data. Fifty-one subjects (16 with ICPP, 35 with PPP) provided by another hospital as external validation. T1-weighted (spin echo [SE], fast SE, cube) and T2-weighted (fast SE-fat suppression) imaging at 3.0 T or 1.5 T. Radiomics features were extracted from pituitary MRI after manual segmentation. Carpal bone age, ovarian, follicle and uterine volumes and endometrium presence were assessed from radiographs and gonadal ultrasound. Four machine learning methods were developed: a pituitary MRI radiomics model, an integrated image model (with pituitary MRI, gonadal ultrasound and bone age), a basic clinical model (with age and sex hormone data), and an integrated multimodal model combining all features. Intraclass correlation coefficients were used to assess consistency of segmentation. Receiver operating characteristic (ROC) curves and the Delong tests were used to assess and compare the diagnostic performance of models. P < 0.05 was considered statistically significant. The area under of the ROC curve (AUC) of the pituitary MRI radiomics model, integrated image model, basic clinical model, and integrated multimodal model in the training data was 0.668, 0.809, 0.792, and 0.860. The integrated multimodal model had higher diagnostic efficacy (AUC of 0.862 and 0.866 for internal and external validation). The integrated multimodal model may have potential as an alternative clinical approach to diagnose ICPP. 3. Stage 2.

Comparison between 2D FSE T2-weighted Dixon MRI and contrast-enhanced 2D FSE and 3D FSPGR T1-weighted Dixon MRI to quantify inflammation in hands of patients with early rheumatoid arthritis

PurposeThe purpose of this study was to compare two-dimensional (2D) T2-weighted, contrast-enhanced 2D T1-weighted and contrast-enhanced three-dimensional (3D) T1-weighted Dixon MRI sequences to assess disease activity using the RAMRIS scoring system in hands of patients with early rheumatoid arthritis. Materials and methodsTwenty-five patients (19 women, 6 men; mean age 51.4 years ± 12.7 years [SD], age range: 28–70 years) with rheumatoid arthritis prospectively underwent MRI examination of both hands at 1.5 T using 2D fast spin-echo (FSE) T2-weighted, contrast-enhanced 2D FSE T1-weighted and contrast-enhanced 3D fast spoiled gradient echo (FSPGR) T1-weighted Dixon sequences. Three radiologists independently assessed disease activity according to RAMRIS using Dixon water-only and fat-only images. Intraclass correlation coefficients (ICC) were calculated to assess inter-technique and interobserver agreements. ResultsAgreement to assess total RAMRIS score was very good between the MRI protocols (mean ICC ranging from 0.81 to 0.93) and between readers (mean ICC ranging from 0.91 to 0.94). Mean total RAMRIS scores of the three readers were significantly greater with contrast-enhanced 3D FSPGR T1-weighted (42.73 ± 29.39) than with contrast-enhanced 2D FSE T1-weighted (35.81 ± 25.48) and 2D FSE T2-weighted (32.20 ± 25.06) Dixon sequences. Conclusion2D FSE T2-weighted, contrast-enhanced 2D FSE T1-weighted Dixon and contrast-enhanced 3D FSPGR T1-weighted Dixon protocols are reproducible alternatives for the RAMRIS scoring in hands of patients with early rheumatoid arthritis. Coupling contrast-enhanced 3D FSPGR T1-weighted and 2D FSE T2-weighted sequences might be the most efficient option to completely assess the rheumatoid arthritis -related synovial and bone changes with the Dixon method.

Chemical Exchange Saturation Transfer MRI: Capability for Predicting Therapeutic Effect of Chemoradiotherapy on Non-Small Cell Lung Cancer Patients.

Amide proton transfer (APT) weighted chemical exchange saturation transfer CEST (APTw/CEST) magnetic resonance imaging (MRI) has been suggested as having the potential for assessing the therapeutic effect of brain tumors or rectal cancer. Moreover, diffusion-weighted imaging (DWI) and positron emission tomography fused with computed tomography by means of 2-[fluorine-18]-fluoro-2-deoxy-D-glucose (FDG-PET/CT) have been suggested as useful in same setting. To compare the capability of APTw/CEST imaging, DWI, and FDG-PET/CT for predicting therapeutic effect of chemoradiotherapy (CRT) on stage III non-small cell lung cancer (NSCLC) patients. Prospective. Eighty-four consecutive patients with Stage III NSCLC, 45 men (age range, 62-75 years; mean age, 71 years) and 39 women (age range, 57-75 years; mean age, 70 years). All patients were then divided into two groups (Response Evaluation Criteria in Solid Tumors [RECIST] responders, consisting of the complete response and partial response groups, and RECIST non-responders, consisting of the stable disease and progressive disease groups). 3 T, echo planar imaging or fast advanced spin-echo (FASE) sequences for DWI and 2D half Fourier FASE sequences with magnetization transfer pulses for CEST imaging. Magnetization transfer ratio asymmetry (MTRasym ) at 3.5 ppm, apparent diffusion coefficient (ADC), and maximum standard uptake value (SUVmax, ) on PET/CT were assessed by means of region of interest (ROI) measurements at primary tumor. Kaplan-Meier method followed by log-rank test and Cox proportional hazards regression analysis with multivariate analysis. A P value <0.05 was considered statistically significant. Progression-free survival (PFS) and overall survival (OS) had significant difference between two groups. MTRasym at 3.5 ppm (hazard ratio [HR] = 0.70) and SUVmax (HR = 1.41) were identified as significant predictors for PFS. Tumor staging (HR = 0.57) was also significant predictors for OS. APTw/CEST imaging showed potential performance as DWI and FDG-PET/CT for predicting the therapeutic effect of CRT on stage III NSCLC patients. 2 TECHNICAL EFFICACY: Stage 1.

Comparative physiological, morphological, histological, and AQP2 immunohistochemical analysis of the Arabian camels (Camelus dromedarius) and oxen kidney: Effects of adaptation to arid environments

Compared to other mammals, Arabian camels are ideal models for exploring the structural adaptations that enable camels to survive in arid environments. Thus, this study aimed to explore how evolutionary adaptation to arid conditions modifies the characteristics of the kidneys in Arabian camels (Camelus dromedarius) compared to oxen. Urine samples were physically and chemically analyzed. Harvested kidneys were subjected to topographical and fast spin echo magnetic resonance (FSE-MR) imaging. Histology, histomorphometry, and Aquaporin-2 (AQP2) expression by immunohistochemistry were also performed. Here, in dromedaries, sodium and potassium values in the urine were much higher (p=0.001, for both), whereas chloride was much lower (p=0.004) than the values of oxen. Compared with oxen, the level of the hormone aldosterone in serum was significantly lower (p=0.002), whereas creatinine and urea were significantly higher (p=0.005 and p=0.001, respectively). Uric acid in dromedaries and oxen did not differ significantly (p=0.349). Like sodium levels (p=0.001) in dromedary serum, chloride was also much higher (p=0.002) than in oxen. The average value of potassium was much lower (p=0.009) than that of oxen. Morphologically, anatomical and FSE MRI studies revealed that minor and major calyces were not found in dromedary kidneys. The renal pelvis was not found in oxen, and the major calyx was directly connected to the ureter. The dromedary kidney contained a wider medullary portion as well as increased diameters for renal corpuscles (RCs), proximal convoluted tubules (PCTs), and collecting tubules (CTs, p&amp;lt;0.05) compared with the oxen. We also noted that AQP2 was significantly expressed in dromedary nephron components, except for RCs, compared with oxen as shown by immunohistochemistry. Overall, these data strongly suggest that the dromedary has a greater ability to adapt to harsh desert conditions in terms of producing highly concentrated urine than oxen.

Carotid Artery Thrombus in Antiphospholipid Antibody Syndrome.

HomeRadiologyRecently Published PreviousNext Reviews and CommentaryFree AccessImages in RadiologyCarotid Artery Thrombus in Antiphospholipid Antibody SyndromeZongli Han, Hui Qi Zongli Han, Hui Qi Author AffiliationsFrom the Department of Neurosurgery, Peking University Shenzhen Hospital, 1120 Lianhua Rd, Shenzhen 518036, PR China.Address correspondence to H.Q. (email: [email protected]).Zongli HanHui Qi Published Online:Mar 14 2023https://doi.org/10.1148/radiol.221836MoreSectionsPDF ToolsImage ViewerAdd to favoritesCiteTrack CitationsPermissionsReprints ShareShare onFacebookTwitterLinked In A 23-year-old previously healthy woman presented with sudden-onset right-sided hemiparesis and paresthesia. Brain MRI scan demonstrated acute left frontal lobe embolic infarcts. High-spatial-resolution vessel wall MRI scan revealed an isointense peripherally enhancing lesion in the left common carotid artery with resultant severe luminal narrowing, compatible with an intraluminal thrombus (Figure, A–C). Contrast-enhanced US image confirmed free-floating thrombus with proximal attachment to the vessel wall (Figure, D). Endarterectomy was performed, and an organized thrombus was confirmed with pathologic process. Antibody serology tests were positive for anticardiolipin immunoglobulin G, β-2 glycoprotein immunoglobulin G, and lupus anticoagulants. The diagnosis of antiphospholipid antibody syndrome was established according to the Miyakis criteria (1,2). The patient was treated with warfarin and showed no signs of clinical or radiologic relapse at 1-year follow-up.Images in a 23-year-old woman with sudden-onset right-sided hemiparesis and paresthesia. (A–C) T1-weighted three-dimensional isotropic variable flip-angle fast spin echo MRI scans with black-blood technique with a 3-T clinical scanner (uMR 780; United Imaging Healthcare) show vessel walls. (A) Axial and (B) coronal T1-weighted images without contrast material show an intraluminal T1 isointense lesion within the left common carotid artery with resultant severe luminal narrowing (arrows). (C) Coronal contrast-enhanced T1-weighted image shows peripheral linear contrast enhancement of the thrombus (arrow). (D) Contrast-enhanced US image demonstrates a free-floating thrombus with microbubbles between the thrombus and the carotid vessel (*) with proximal attachment to the vessel wall (arrowhead).Download as PowerPointOpen in Image Viewer Antiphospholipid antibody syndrome is an autoimmune disease characterized by recurrent arterial or venous thrombosis, pathologic pregnancy, and positive antiphospholipid antibodies (3). Neurologic manifestations, especially cerebral ischemia, are frequently present; however, presentation with carotid thrombus is uncommon (4).Disclosures of conflicts of interest: Z.H. No relevant relationships. H.Q. No relevant relationships.AcknowledgmentsThe authors thank Hui Zhang from the Department of Radiology, who helped with the interpretation of the high-resolution MRI. They also thank Liya Wei from the Department of Ultrasound, who helped with the interpretation of the contrast-enhanced US image.

Serial Cardiac MRI for Quantification of the Dynamics of Anthracycline-Induced Subclinical Myocardial Injury.

Anthracyclines are known to be associated with chemotherapy-induced cardiotoxicity. Limited data focus on dynamic myocardial injury during the course of chemotherapy in patients with breast cancer. To investigate the variation of tissue characterization and myocardial deformation derived by cardiac MRI during anthracycline chemotherapy. Prospective. Fifty-eight female breast cancer patients (mean age: 52.82 ± 2.61 years) were enrolled. A 3.0-T, cardiac MRI including cine balanced steady-state free precession, a modified Looker-Locker inversion recovery (MOLLI), and a fast spin echo (FSE) T2-weighted sequences were performed. Cardiac MRI was performed baseline and after two, four, and six cycles of chemotherapy. Assessment of global longitudinal strain (GLS), global circumstance strain (GCS), global radial strain (GRS), and strain rate (GLS-s, GCS-s, GRS-s) and T1, T2 and T2* were accomplished by CVI42. The anthracycline dose and risk factors were also collected before each cardiac MRI. Analysis of variance (ANOVA) for repeated measures was used to compare the changes in LVEF cardiac function, strain and T1/T2/T2* parameters over time. Pearson correlation analyses were performed to estimate the potential associations between differences in myocardial characteristics (∆) and the chemotherapy cycle. A P value <0.05 was considered statistically significant. LVEF was not significantly different from pretreatment MRI regarding each cycle of chemotherapy (P=0.54). Compared with baseline, patients had significantly lower GLS (-15.85% ± 0.83%, -14.50% ± 0.88%, -12.34% ± 1.01% vs. -18.82% ± 0.92%) and GLS-s (-0.71% ± 0.07%, -0.65% ± 0.05%, -0.64% ± 0.04% vs. -0.95 ± 0.06%) and increased T2 values (57.21 ± 4.27 msec, 58.60 ± 3.93 msec, 58.10 ± 3.17 msec vs. 43.88 ± 3.28 msec) at two, four and six cycles of chemotherapy treatment. ∆GLS and ∆GLS-s were significantly associated with the chemotherapy cycle (correlation coefficients for GLS=0.75, GLS-s=0.75). Cardiac MRI can precisely detect the dynamic changes of anthracycline-induced subclinical myocardial injury that is represented as a gradually decrease in GLS and GLS-s. These parameters may provide new insight for monitoring risk and therapy in patients with breast cancer. 2. Stage 1.