Turbo Spin-echo Magnetic Resonance Imaging Research Articles

Significance of three-dimensional turbo spin-echo magnetic resonance imaging with semiquantitative assessment of knee osteoarthritis: correlation to two-dimensional routine magnetic resonance imaging

Abstract Background As one of the most prevalent chronic degenerative diseases, knee osteoarthritis (KOA) is associated with the progressive degradation of articular cartilage, meniscus, synovium, ligaments, bone, muscles, and tendons. Knee osteoarthritis affects the quality of life and can cause chronic disability worldwide. Magnetic resonance imaging (MRI) is a crucial imaging modality for the morphological assessment of cartilage and all other joint tissues involved in osteoarthritis. The objective of this study was to evaluate the effectiveness of the three-dimensional (3D) turbo spin-echo (TSE) MRI and to compare its relevance to two-dimensional (2D) routine MRI in adding additional information and in the early detection of KOA. Results Total agreement between the two techniques ranged between 82.7% (cartilage degeneration), 91.4% (osteophytes), 98.3% for bone marrow edema and periarticular cyst up to 100% of other several features regarding meniscal injury and ligamentous tear. Conclusions When compared to standard 2D TSE MRI, 3D TSE MRI demonstrates substantial to almost complete agreement and high accuracy for semiquantitative assessment of knee osteoarthritis (OA). 3D TSE MRI also takes less time, which is important for large OA studies and can be used for the detection of early knee joint changes.

Deep Learning-Enhanced Accelerated 2D TSE and 3D Superresolution Dixon TSE for Rapid Comprehensive Knee Joint Assessment.

The aim of this study was to evaluate the use of a multicontrast deep learning (DL)-reconstructed 4-fold accelerated 2-dimensional (2D) turbo spin echo (TSE) protocol and the feasibility of 3-dimensional (3D) superresolution reconstruction (SRR) of DL-enhanced 6-fold accelerated 2D Dixon TSE magnetic resonance imaging (MRI) for comprehensive knee joint assessment, by comparing image quality and diagnostic performance with a conventional 2-fold accelerated 2D TSE knee MRI protocol. This prospective, ethics-approved study included 19 symptomatic adult subjects who underwent knee MRI on a clinical 3 T scanner. Every subject was scanned with 3 DL-enhanced acquisition protocols in a single session: a clinical standard 2-fold in-plane parallel imaging (PI) accelerated 2D TSE-based protocol (5 sequences, 11 minutes 23 seconds) that served as a reference, a DL-reconstructed 4-fold accelerated 2D TSE protocol combining 2-fold PI and 2-fold simultaneous multislice acceleration (5 sequences, 6 minutes 24 seconds), and a 3D SRR protocol based on DL-enhanced 6-fold accelerated (ie, 3-fold PI and 2-fold simultaneous multislice) 2D Dixon TSE MRI (6 anisotropic 2D Dixon TSE acquisitions rotated around the phase-encoding axis, 6 minutes 24 seconds). This resulted in a total of 228 knee MRI scans comprising 21,204 images. Three readers evaluated all pseudonymized and randomized images in terms of image quality using a 5-point Likert scale. Two of the readers (musculoskeletal radiologists) additionally evaluated anatomical visibility and diagnostic confidence to assess normal and pathological knee structures with a 5-point Likert scale. They recorded the presence and location of internal knee derangements, including cartilage defects, meniscal tears, tears of ligaments, tendons and muscles, and bone injuries. The statistical analysis included nonparametric Friedman tests, and interreader and intrareader agreement assessment using the weighted Fleiss-Cohen kappa (κ) statistic. P values of less than 0.05 were considered statistically significant. The evaluated DL-enhanced 4-fold accelerated 2D TSE protocol provided very similar image quality and anatomical visibility to the standard 2D TSE protocol, whereas the 3D SRR Dixon TSE protocol scored less in terms of overall image quality due to reduced edge sharpness and the presence of artifacts (P < 0.001). Subjective signal-to-noise ratio, contrast resolution, fluid brightness, and fat suppression were good to excellent for all protocols. For 1 reader, the Dixon method of the 3D SRR protocol provided significantly better fat suppression than the spectral fat saturation applied in the standard 2D TSE protocol (P < 0.05). The visualization of knee structures with 3D SRR Dixon TSE was very similar to the standard protocol, except for cartilage, tendons, and bone, which were affected by the presence of reconstruction and aliasing artifacts (P < 0.001). The diagnostic confidence of both readers was high for all protocols and all knee structures, except for cartilage and tendons. The standard 2D TSE protocol showed a significantly higher diagnostic confidence for assessing tendons than 3D SRR Dixon TSE MRI (P < 0.01). The interreader and intrareader agreement for the assessment of internal knee derangements using any of the 3 protocols was substantial to almost perfect (κ = 0.67-1.00). For cartilage, the interreader agreement was substantial for DL-enhanced accelerated 2D TSE (κ = 0.79) and almost perfect for standard 2D TSE (κ = 0.98) and 3D SRR Dixon TSE (κ = 0.87). For menisci, the interreader agreement was substantial for 3D SRR Dixon TSE (κ = 0.70-0.80) and substantial to almost perfect for standard 2D TSE (κ = 0.80-0.99) and DL-enhanced 2D TSE (κ = 0.87-1.00). Moreover, the total acquisition time was reduced by 44% when using the DL-enhanced accelerated 2D TSE or 3D SRR Dixon TSE protocol instead of the conventional 2D TSE protocol. The presented DL-enhanced 4-fold accelerated 2D TSE protocol provides image quality and diagnostic performance similar to the standard 2D protocol. Moreover, the 3D SRR of DL-enhanced 6-fold accelerated 2D Dixon TSE MRI is feasible for multicontrast 3D knee MRI as its diagnostic performance is comparable to standard 2-fold accelerated 2D knee MRI. However, reconstruction and aliasing artifacts need to be further addressed to guarantee a more reliable visualization and assessment of cartilage, tendons, and bone. Both the 2D and 3D SRR DL-enhanced protocols enable a 44% faster examination compared with conventional 2-fold accelerated routine 2D TSE knee MRI and thus open new paths for more efficient clinical 2D and 3D knee MRI.

Comparison of the Image Quality of Turbo Spin Echo and Echo-Planar Diffusion-Weighted Imaging of the Head and Neck Region.

Magnetic resonance imaging (MRI) of the head and neck region is notably challenging due to the complex anatomy and the critical need for high-resolution imaging to accurately diagnose various pathologies. The two prominent MRI techniques used in this context are turbo spin echo (TSE) and echo-planar diffusion-weighted imaging (EP-DWI). TSE is recognized for providing high-resolution anatomical images, whereas EP-DWI offers functional imaging that highlights the diffusion of water molecules, essential for detecting early pathological changes. This study aims to compare the image quality of TSE and EP-DWI in the head and neck region to assess their diagnostic efficacy and clinical utility. This retrospective study was conducted at Saveetha Medical College and Hospital over six months. A total of 100 patients (50 males and 50 females, aged 18-65 years) with various head and neck pathologies were included. Patients underwent both TSE and EP-DWI sequences using a Philips MULTIVA 1.5 T scanner. Image quality was assessed based on signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), artifact presence, and lesion detection. Two experienced radiologists independently reviewed the images, with inter-observer agreement calculated using Cohen's kappa coefficient. The mean SNR for TSE was significantly higher than EP-DWI (45.2 vs. 28.7, p<0.01), indicating superior image clarity and detail in TSE images. TSE demonstrated a higher mean CNR compared to EP-DWI (25.4 vs. 15.8, p<0.01), suggesting better differentiation between different tissue types and pathologies. Artifacts were more frequent in EP-DWI images (45% vs. 15%), with motion artifacts being the most common. TSE detected more lesions (120 vs. 95), with more precise delineation of lesions. The inter-observer agreement was excellent for both TSE and EP-DWI, with kappa values of 0.85 and 0.80, respectively. TSE MRI provides superior image quality compared to EP-DWI for evaluating the head and neck region. The enhanced SNR and CNR in TSE images result in clearer and more detailed visualizations of anatomical structures and pathological changes, with fewer artifacts. While EP-DWI is valuable for functional imaging, its role should be complementary to TSE. The study suggests that TSE should be the preferred modality for detailed anatomical assessment in the head and neck region. Further studies with larger sample sizes and advanced imaging techniques may provide additional insights into optimizing MRI protocols for head and neck imaging.

Comparison between T2 Turbo Inversion Recovery Magnitude and T2 Frequency Selective Fat Saturation Turbo Spin Echo MRI Sequences in Detection of Perianal Fistula

Fat suppression magnetic resonance imaging (MRI) sequences are routinely included in the MRI protocol for patients with perianal fistula to improve the visibility of the abnormal tracts and abscesses against the background of hypo-signal intensity on the image. The objective of this study is to compare the turbo inversion recovery magnitude (TIRM) and frequency selective fat saturation turbo spin echo (FSTSE) MRI sequences in detecting perianal fistulas in terms of time and clarity. The MRI protocol included a coronal T2 turbo inversion recovery magnitude sequence, a T2 fat saturation turbo spin echo, and T2 turbo inversion recovery magnitude sequences in the axial plane. The evaluation of sequence image quality involved calculating the signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR). Additionally three radiologists assessed the best image using a questionnaire designed to align with the study’s objectives. The T2 TIRM sequence was found to have the highest number of ticked images. The inter-rater kappa agreement showed fair agreement (k = 0.370) between the raters. However, the SNR and CNR values for the T2 FSTSE were higher than those of the T2 TIRM sequence, with a p-value less than 0.001. There is a significant difference in the meantime in that the T2 TIRM sequence has less time than the T2 FSTSE with a p-value &lt; 0.001. Due to its uniform fat suppression in the MR image and shorter acquisition time, the turbo inversion recovery magnitude sequence exhibited superior performance compared to the T2 frequency-selective turbo spin echo sequence.

Daily heart rate variability biofeedback training decreases locus coeruleus MRI contrast in younger adults in a randomized clinical trial

As an arousal hub region in the brain, the locus coeruleus (LC) has bidirectional connections with the autonomic nervous system. Magnetic resonance imaging (MRI)-based measures of LC structural integrity have been linked to cognition and arousal, but less is known about factors that influence LC structure and function across time. Here, we tested the effects of heart rate variability (HRV) biofeedback, an intervention targeting the autonomic nervous system, on LC MRI contrast and sympathetic activity. Younger and older participants completed daily HRV biofeedback training for five weeks. Those assigned to an experimental condition performed biofeedback involving slow, paced breathing designed to increase heart rate oscillations, whereas those assigned to a control condition performed biofeedback to decrease heart rate oscillations. At the pre- and post-training timepoints, LC contrast was assessed using turbo spin echo MRI scans, and RNA sequencing was used to assess cAMP-responsive element binding protein (CREB)-regulated gene expression in circulating blood cells, an index of sympathetic nervous system signaling. We found that left LC contrast decreased in younger participants in the experimental group, and across younger participants, decreases in left LC contrast were related to the extent to which participants increased their heart rate oscillations during training. Furthermore, decreases in left LC contrast were associated with decreased expression of CREB-associated gene transcripts. On the contrary, there were no effects of biofeedback on LC contrast among older participants in the experimental group. These findings provide novel evidence that in younger adults, HRV biofeedback involving slow, paced breathing can decrease both LC contrast and sympathetic nervous system signaling.

Magnetic resonance imaging for assessment of the quadriceps tendon cross-sectional area as an adjunctive diagnostic parameter in patients with patellofemoral pain syndrome.

In this study, we aimed to provide a more valuable diagnostic parameter and more equivocal assessment of the diagnostic potential of patellofemoral pain syndrome (PFPS) by comparing the quadriceps tendon cross-sectional area (QTCSA) with the quadriceps tendon thickness (QTT), a traditional measure of quadriceps tendon hypertrophy. Between March 2014 and August 2020, a total of 30 patients with PFPS (16 males, 14 females; mean age, 30.4±11.2 years; range, 16 to 49 years) and 30 healthy individuals (19 males, 11 females; mean age: 30.8±13.8 years; range, 17 to 62 years) who underwent knee magnetic resonance imaging (MRI) were retrospectively analyzed. T1-weighted turbo spin-echo transverse MRI scans were obtained. The QTCSA was measured on the axial angled phases of the images by drawing outlines, and the QTT was measured at the most hypertrophied quadriceps tendon. The mean QTT and QTCSA in the patients with PFPS (6.33±0.80 mm and 155.77±36.60 mm2, respectively) were significantly higher than those in the control group (5.77±0.36 mm and 111.90±24.10 mm2, respectively; p<0.001, for both). The receiver operating characteristic curve was used to confirm the sensitivities and specificities for both the QTT and QTCSA as predictors of PFPS. The optimal diagnostic cut-off value for QTT was 5.98 mm, with a sensitivity of 66.7%, a specificity of 70.0%, and an area under the curve (AUC) of 0.75 (range, 0.62 to 0.88). The optimal diagnostic cut-off value for QTCSA was 121.04 mm2, with a sensitivity of 73.3%, a specificity of 70.0%, and an AUC of 0.83 (range, 0.74 to 0.93). Based on our study results, the QTCSA seems to be a more reliable diagnostic indicator for PFPS than QTT.

Lung Nodule Detection With Modern Low-Field MRI (0.55 T) in Comparison to CT.

The aim of this study was to evaluate the accuracy of modern low-field magnetic resonance imaging (MRI) for lung nodule detection and to correlate nodule size measurement with computed tomography (CT) as reference. Between November 2020 and July 2021, a prospective clinical trial using low-field MRI at 0.55 T was performed in patients with known pulmonary nodules from a single academic medical center. Every patient underwent MRI and CT imaging on the same day. The primary aim was to evaluate the detection accuracy of pulmonary nodules using MRI with transversal periodically rotated overlapping parallel lines with enhanced reconstruction in combination with coronal half-Fourier acquired single-shot turbo spin-echo MRI sequences. The secondary outcome was the correlation of the mean lung nodule diameter with CT as reference according to the Lung Imaging Reporting and Data System. Nonparametric Mann-Whitney U test, Spearman rank correlation coefficient, and Bland-Altman analysis were applied to analyze the results. A total of 46 participants (mean age ± SD, 66 ± 11 years; 26 women) were included. In a blinded analysis of 964 lung nodules, the detection accuracy was 100% for those ≥6 mm (126/126), 80% (159/200) for those ≥4-<6 mm, and 23% (147/638) for those <4 mm in MRI compared with reference CT. Spearman correlation coefficient of MRI and CT size measurement was r = 0.87 ( P < 0.001), and the mean difference was 0.16 ± 0.9 mm. Modern low-field MRI shows excellent accuracy in lesion detection for lung nodules ≥6 mm and a very strong correlation with CT imaging for size measurement, but could not compete with CT in the detection of small nodules.

Headache frequency and neck pain are associated with trapezius muscle T2 in tension-type headache among young adults

BackgroundTension-type headache (TTH) is the most prevalent primary headache disorder. Neck pain is commonly associated with primary headaches and the trigemino-cervical complex (TCC) refers to the convergence of trigeminal and cervical afferents onto neurons of the brainstem, thus conceptualizes the emergence of headache in relation to neck pain. However, no objective biomarkers exist for the myofascial involvement in primary headaches. This study aimed to investigate the involvement of the trapezius muscles in primary headache disorders by quantitative magnetic resonance imaging (MRI), and to explore associations between muscle T2 values and headache frequency and neck pain.MethodsThis cohort study prospectively enrolled fifty participants (41 females, age range 20–31 years): 16 subjects with TTH only (TTH-), 12 with mixed-type TTH plus migraine (TTH+), and 22 healthy controls (HC). The participants completed fat-suppressed T2‐prepared three-dimensional turbo spin-echo MRI, a headache diary (over 30 days prior to MRI), manual palpation (two weeks before MRI), and evaluation of neck pain (on the day of MRI). The bilateral trapezius muscles were manually segmented, followed by muscle T2 extraction. Associations between muscle T2 and the presence of neck pain as well as the number of days with headache (considering the 30 days prior to imaging using the headache calendar) were analyzed using regression models (adjusting for age, sex, and body mass index).ResultsThe TTH+ group demonstrated the highest muscle T2 values (right side: 31.4 ± 1.2 ms, left side: 31.4 ± 0.8 ms) as compared to the TTH- group or HC group (p < 0.001). Muscle T2 was significantly associated with the number of headache days (β-coefficient: 2.04, p = 0.04) and the presence of neck pain (odds ratio: 2.26, p = 0.04). With muscle T2 as the predictor, the area under the curve for differentiating between HC and the TTH+ group was 0.82.ConclusionsIncreased T2 of trapezius muscles may represent an objective imaging biomarker for myofascial involvement in primary headache disorders, which could help to improve patient phenotyping and therapy evaluation. Pathophysiologically, the increased muscle T2 values could be interpreted as a surrogate of neurogenic inflammation and peripheral sensitization within myofascial tissues.

Prediction model for knee osteoarthritis using magnetic resonance–based radiomic features from the infrapatellar fat pad: data from the osteoarthritis initiative

The infrapatellar fat pad (IPFP) plays an important role in the incidence of knee osteoarthritis (OA). Magnetic resonance (MR) signal heterogeneity of the IPFP is related to pathologic changes. In this study, we aimed to investigate whether the IPFP radiomic features have predictive value for incident radiographic knee OA (iROA) 1 year prior to iROA diagnosis. Data used in this work were obtained from the osteoarthritis initiative (OAI). In this study, iROA was defined as a knee with a baseline Kellgren-Lawrence grade (KLG) of 0 or 1 that further progressed to KLG ≥2 during the follow-up visit. Intermediate-weighted turbo spin-echo knee MR images at the time of iROA diagnosis and 1 year prior were obtained. Five clinical characteristics-age, sex, body mass index, knee injury history, and knee surgery history-were obtained. A total of 604 knees were selected and matched (302 cases and 302 controls). A U-Net segmentation model was independently trained to automatically segment the IPFP. The prediction models were established in the training set (60%). Three main models were generated using (I) clinical characteristics; (II) radiomic features; (III) combined (clinical plus radiomic) features. Model performance was evaluated in an independent testing set (remaining 40%) using the area under the curve (AUC). Two secondary models were also generated using Hoffa-synovitis scores and clinical characteristics. The comparison between the automated and manual segmentations of the IPFP achieved a Dice coefficient of 0.900 (95% CI: 0.891-0.908), which was comparable to that of experienced radiologists. The radiomic features model and the combined model yielded superior AUCs of 0.700 (95% CI: 0.630-0.763) and 0.702 (95% CI: 0.635-0.763), respectively. The DeLong test found no statistically significant difference between the receiver operating curves of the radiomic and combined models (P=0.831); however, both models outperformed the clinical model (P=0.014 and 0.004, respectively). Our results demonstrated that radiomic features of the IPFP are predictive of iROA 1 year prior to the diagnosis, suggesting that IPFP radiomic features can serve as an early quantitative prediction biomarker of iROA.

Associations between locus coeruleus MRI contrast and physiological responses to acute stress in younger and older adults

Acute stress activates the brain’s locus coeruleus (LC)-noradrenaline system. Recent studies indicate that a magnetic resonance imaging (MRI)-based measure of LC structure is associated with better cognitive outcomes in later life. Yet despite the LC’s documented role in promoting physiological arousal during acute stress, no studies have examined whether MRI-assessed LC structure is related to arousal responses to acute stress. In this study, 102 younger and 51 older adults completed an acute stress induction task while we assessed multiple measures of physiological arousal (heart rate, breathing rate, systolic and diastolic blood pressure, sympathetic tone, and heart rate variability, HRV). We used turbo spin echo MRI scans to quantify LC MRI contrast as a measure of LC structure. We applied univariate and multivariate approaches to assess how LC MRI contrast was associated with arousal at rest and during acute stress reactivity and recovery. In older participants, having higher caudal LC MRI contrast was associated with greater stress-related increases in systolic blood pressure and decreases in HRV, as well as lower HRV during recovery from acute stress. These results suggest that having higher caudal LC MRI contrast in older adulthood is associated with more pronounced physiological responses to acute stress. Further work is needed to confirm these patterns in larger samples of older adults.

Evaluation of Occluded Distal Vessels with Variable Flip-Angle 3-Dimensional Turbo Spin-Echo Magnetic Resonance Imaging Before Acute Mechanical Thrombectomy

The aim of this study was to evaluate the course of occluded distal vessels before mechanical thrombectomy (MT) for acute large vessel occlusion (LVO) with non-contrast magnetic resonance imaging (MRI). The variable flip-angle three-dimensional turbo spin-echo (VRFA-3D-TSE) method was used to evaluate the course of occluded distal vessels quickly and clearly in acute LVO cases before MT. Patients with acute LVO who were indicated for MT between April 2021 and March 2022 were examined by the VRFA-3D-TSE method to evaluate the distal course of occluded vessels. We included internal carotid artery (ICA) occlusion, M1 occlusion of the middle cerebral artery, and basilar artery (BA) occlusion. Preoperative images were compared to the angiographic findings after recanalization or with follow-up magnetic resonance angiography, and the results were assessed by 2 endovascular treatment specialists as excellent, good, or poor imaging. MT was performed in a total of 27 patients. There were 17 patients with intracranial occlusion of the ICA, M1, and BA. Occlusion was found in the intracranial ICA in 6 patients, the M1 in 7, and the BA in 4. VRFA-3D-TSE MRI was performed in all patients, and the imaging was rated (by the 2assessors) as excellent in 12 of 17 and 14 of 17 cases, good in 5 of 17 and 3 of 17 cases, and poor in 0 of 17 cases. In patients with acute LVO, VRFA-3D-TSE MRI enabled rapid and good depiction of the course of occluded distal vessels before MT without the use of contrast medium.

Three-dimensional turbo spin-echo (TSE) MRI assessment of indirect acute muscle injuries in athletes: comparison with two-dimensional TSE MRI.

To evaluate three-dimensional (3D) turbo spin-echo (TSE) magnetic resonance imaging (MRI) for the assessment of acute muscle injuries in elite athletes in comparison with two-dimensional (2D) MRI. Elite athletes with clinically suspected acute muscle injury of the thigh who underwent both 2D and 3D MRI protocols on the same day were retrospectively included. Two musculoskeletal radiologists independently assessed 2D and 3D MRIs, with both techniques evaluated separately 1-month apart. Muscle injuries were evaluated using the BAMIC and the INSEP classifications. A second assessment of injuries was performed by each reader 2 months after the initial readings. Agreement was determined using weighted kappa statistics. The level of diagnostic confidence in classifying injuries was also assessed for both MRI protocols. A total of 40 athletes were included. Intra-reader agreement when comparing injury grades from 2D vs. 3D for both INSEP and BAMIC classifications was almost perfect for both readers and ranged between 0.84 and 0.98. Inter-reader agreement was substantial to almost perfect and ranged from 0.78 to 0.93 for the 2D protocol, and from 0.78 to 0.95 for the 3D protocol. Intra-reader agreement for each MRI protocol separately was almost perfect to perfect for both readers and ranged between 0.84 and 1.00. Diagnostic confidence for grading injuries improved for both readers when using the 3D protocol. Compared to 2D MRI, 3D TSE MRI is a reliable technique for acute muscular injury assessment, providing faster acquisition times and improving the diagnostic confidence. • Compared to 2D MRI, 3D TSE MRI is a reliable technique for the assessment of acute muscular injuries. • 3D TSE MRI has the advantage of faster total acquisition times, thinner sections, and multiplanar reconstruction, improving the confidence for structural assessment including connective tissue involvement.

A Multi-Task Deep Learning Method for Detection of Meniscal Tears in MRI Data from the Osteoarthritis Initiative Database.

We present a novel and computationally efficient method for the detection of meniscal tears in Magnetic Resonance Imaging (MRI) data. Our method is based on a Convolutional Neural Network (CNN) that operates on complete 3D MRI scans. Our approach detects the presence of meniscal tears in three anatomical sub-regions (anterior horn, body, posterior horn) for both the Medial Meniscus (MM) and the Lateral Meniscus (LM) individually. For optimal performance of our method, we investigate how to preprocess the MRI data and how to train the CNN such that only relevant information within a Region of Interest (RoI) of the data volume is taken into account for meniscal tear detection. We propose meniscal tear detection combined with a bounding box regressor in a multi-task deep learning framework to let the CNN implicitly consider the corresponding RoIs of the menisci. We evaluate the accuracy of our CNN-based meniscal tear detection approach on 2,399 Double Echo Steady-State (DESS) MRI scans from the Osteoarthritis Initiative database. In addition, to show that our method is capable of generalizing to other MRI sequences, we also adapt our model to Intermediate-Weighted Turbo Spin-Echo (IW TSE) MRI scans. To judge the quality of our approaches, Receiver Operating Characteristic (ROC) curves and Area Under the Curve (AUC) values are evaluated for both MRI sequences. For the detection of tears in DESS MRI, our method reaches AUC values of 0.94, 0.93, 0.93 (anterior horn, body, posterior horn) in MM and 0.96, 0.94, 0.91 in LM. For the detection of tears in IW TSE MRI data, our method yields AUC values of 0.84, 0.88, 0.86 in MM and 0.95, 0.91, 0.90 in LM. In conclusion, the presented method achieves high accuracy for detecting meniscal tears in both DESS and IW TSE MRI data. Furthermore, our method can be easily trained and applied to other MRI sequences.

Technical note: Unexpected external markers artifact in 3D k-space based parallel imaging turbo spin-echo magnetic resonance imaging.

MRI for radiotherapy planning requires spatial referencing using immobilization devices and markers. Clinical images of a difficult-to-interpret artifact are presented, resembling a metastasis, which occurs when combining CAIPIRINHA k-space-based parallel imaging (PI), 3D distortion correction, and external markers. A 3D variable flip angle Turbo Spin Echo sequence was used on a 1.5T and 3T MRI using flexible and head and neck coils. Two types of markers were tested: Liquimark LM1 and Spee-D-Mark. A silicone oil phantom was used that represents low signal intensity, such as gray matter. 3D Fourier transforms were also used to show the issue's origin. The markers can appear in an unexpected region of a patient, not in the same original or reconstructed slice nor in a rectilinear direction in a slice, especially when using CAIPIRINHA acceleration with 3D distortion correction. The probability of occurrence was respectively 13% and 80% for distances of <=2mm and >2mm between marker and patient, for example when using thermoplastic masks. Clinical cases are shown where this semi-randomly occurring artifact appears post contrast only, and thus can be interpreted as metastases. The artifact did not appear when using compressed sensing acceleration. Markers used for radiotherapy MRI application can introduce additional artifacts that can be interpreted as metastases. However, other high signal intensity structures on the surface of a patient, such as the ear, can lead to an equivalent error.

T2-weighted turbo spin-echo magnetic resonance imaging of canine brain anatomy at 1.5T, 3T, and 7T field strengths.

Post-mortem T2 weighted images of canine heads were acquired at 1.5T, 3T, and 7T. This study aimed to (1) identify anatomical structures of the canine brain using an ultra-high-field magnetic resonance imaging (MRI) (7T) to help to facilitate their localization on high field MRI images (3T and 1.5T), where these structures may appear less well defined and delineated and (2) evaluate the visibility of canine brain anatomical structures on 1.5T, 3T, and 7T MRI images for optimizing clinical utility. Our hypothesis was that the provided subjective image quality comparison at different field strengths may offer a general baseline for canine brain anatomy and may help clinicians evaluate MRI options better. Six canine heads were examined with 1.5T, 3T, and 7T MRI scanners. T2-weighted images were acquired in three orthogonal planes at each field strength using a turbo spin-echo sequence. Fifty neuroanatomic structures were identified and evaluated on the 7T MR images; subsequently, those were found on the 3T and 45 out of the 50 structures were detected on the 1.5T imaging. The structures that were not able to be identified on the 1.5T imaging included the septum pellucidum, oculomotor nucleus, substantia nigra, claustrum, and thalamic nucleus griseus. Images acquired at 7T were subjective of higher spatial and contrast resolution. However, the ultra-high-field images were prone to artifacts at the interface between tissues of different magnetic properties. In conclusion, 3T MR imaging appears to be the best comprise for evaluating canine brain anatomy on MRI with fewer imaging artifacts.

Quantitative Muscle MRI in Patients with Neuromuscular Diseases-Association of Muscle Proton Density Fat Fraction with Semi-Quantitative Grading of Fatty Infiltration and Muscle Strength at the Thigh Region.

(1) Background and Purpose: The skeletal muscles of patients suffering from neuromuscular diseases (NMD) are affected by atrophy, hypertrophy, fatty infiltration, and edematous changes. Magnetic resonance imaging (MRI) is an important tool for diagnosis and monitoring. Concerning fatty infiltration, T1-weighted or T2-weighted DIXON turbo spin echo (TSE) sequences enable a qualitative assessment of muscle involvement. To achieve higher comparability, semi-quantitative grading scales, such as the four-point Mercuri scale, are commonly applied. However, the evaluation remains investigator-dependent. Therefore, effort is being invested to develop quantitative MRI techniques for determination of imaging markers such as the proton density fat fraction (PDFF). The present work aims to assess the diagnostic value of PDFF in correlation to Mercuri grading and clinically determined muscle strength in patients with myotonic dystrophy type 2 (DM2), limb girdle muscular dystrophy type 2A (LGMD2A), and adult Pompe disease. (2) Methods: T2-weighted two-dimensional (2D) DIXON TSE and chemical shift encoding-based water-fat MRI were acquired in 13 patients (DM2: n = 5; LGMD2A: n = 5; Pompe disease: n = 3). Nine different thigh muscles were rated in all patients according to the Mercuri grading and segmented to extract PDFF values. Muscle strength was assessed according to the British Medical Research Council (BMRC) scale. For correlation analyses between Mercuri grading, muscle strength, and PDFF, the Spearman correlation coefficient (rs) was computed. (3) Results: Mean PDFF values ranged from 7% to 37% in adults with Pompe disease and DM2 and up to 79% in LGMD2A patients. In all three groups, a strong correlation of the Mercuri grading and PDFF values was observed for almost all muscles (rs > 0.70, p < 0.05). PDFF values correlated significantly to muscle strength for muscle groups responsible for knee flexion (rs = −0.80, p < 0.01). (4) Conclusion: In the small, investigated patient cohort, PDFF offers similar diagnostic precision as the clinically established Mercuri grading. Based on these preliminary data, PDFF could be further considered as an MRI-based biomarker in the assessment of fatty infiltration of muscle tissue in NMD. Further studies with larger patient cohorts are needed to advance PDFF as an MRI-based biomarker in NMD, with advantages such as its greater dynamic range, enabling the assessment of subtler changes, the amplified objectivity, and the potential of direct correlation to muscle function for selected muscles.

3D MRI: Technical Considerations and Practical Integration.

One of the main advantages of three-dimensional (3D) magnetic resonance imaging (MRI) is the possibility of isotropic voxels and reconstructed planar cuts through the volumetric data set in any orientation with multiplanar reformation software through real-time evaluation. For example, reformats by the radiologist during reporting allows exploitation of the full potential of isotropic 3D volumetric acquisition or through standardized retrospective reformats of thicker predefined slices of an isotropic volumetric data set by technologists. The main challenges for integrating 3D fast spin echo (FSE) and turbo spin-echo (TSE) MRI in clinical practice are a long acquisition time and some artifacts, whereas for integrating 3D gradient-recalled echo protocols, the main challenges are lower signal-to-noise ratios (SNRs) and the inability to produce intermediate, and T2-weighted contrast. The implementation of bidirectional parallel imaging acquisition and random undersampling acceleration strategies of 3D TSE pulse sequences substantially shortens the examination time with only minor SNR reductions. This article provides an overview of general technical considerations of 3D FSE and TSE sequences in musculoskeletal MRI. It also describes how these sequences achieve efficient data acquisition and reviews the main advantages and challenges for their introduction to clinical practice.

Deep cross-modality (MR-CT) educed distillation learning for cone beam CT lung tumor segmentation.

Despite the widespread availability of in-treatment room cone beam computed tomography (CBCT) imaging, due to the lack of reliable segmentation methods, CBCT is only used for gross set up corrections in lung radiotherapies. Accurate and reliable auto-segmentation tools could potentiate volumetric response assessment and geometry-guided adaptive radiation therapies. Therefore, we developed a new deep learning CBCT lung tumor segmentation method. The key idea of our approach called cross-modality educed distillation (CMEDL) is to use magnetic resonance imaging (MRI) to guide a CBCT segmentation network training to extract more informative features during training. We accomplish this by training an end-to-end network comprised of unpaired domain adaptation (UDA) and cross-domain segmentation distillation networks (SDNs) using unpaired CBCT and MRI datasets. UDA approach uses CBCT and MRI that are not aligned and may arise from different sets of patients. The UDA network synthesizes pseudo MRI from CBCT images. The SDN consists of teacher MRI and student CBCT segmentation networks. Feature distillation regularizes the student network to extract CBCT features that match the statistical distribution of MRI features extracted by the teacher network and obtain better differentiation of tumor from background. The UDA network was implemented with a cycleGAN improved with contextual losses separately on Unet and dense fully convolutional segmentation networks (DenseFCN). Performance comparisons were done against CBCT only using 2D and 3D networks. We also compared against an alternative framework that used UDA with MR segmentation network, whereby segmentation was done on the synthesized pseudo MRI representation. All networks were trained with 216 weekly CBCTs and 82 T2-weighted turbo spin echo MRI acquired from different patient cohorts. Validation was done on 20 weekly CBCTs from patients not used in training. Independent testing was done on 38 weekly CBCTs from patients not used in training or validation. Segmentation accuracy was measured using surface Dice similarity coefficient (SDSC) and Hausdroff distance at 95th percentile (HD95) metrics. The CMEDL approach significantly improved (p < 0.001) the accuracy of both Unet (SDSC of 0.83±0.08; HD95 of 7.69±7.86mm) and DenseFCN (SDSC of 0.75±0.13; HD95 of 11.42±9.87mm) over CBCT only 2DUnet (SDSC of 0.69±0.11; HD95 of 21.70±16.34mm), 3D Unet (SDSC of 0.72±0.20; HD95 15.01±12.98mm), and DenseFCN (SDSC of 0.66±0.15; HD95 of 22.15±17.19mm) networks. The alternate framework using UDA with the MRI network was also more accurate than the CBCT only methods but less accurate the CMEDL approach. Our results demonstrate feasibility of the introduced CMEDL approach to produce reasonably accurate lung cancer segmentation from CBCT images. Further validation on larger datasets is necessary for clinical translation.

Image quality improvement of single-shot turbo spin-echo magnetic resonance imaging of female pelvis using a convolutional neural network.

We have developed a deep learning-based approach to improve image quality of single-shot turbo spin-echo (SSTSE) images of female pelvis. We aimed to compare the deep learning-based single-shot turbo spin-echo (DL-SSTSE) images of female pelvis with turbo spin-echo (TSE) and conventional SSTSE images in terms of image quality.One hundred five and 21 subjects were used as training and test sets, respectively. We performed 6-fold cross validation. In the training process, low-quality images were generated from TSE images as input. TSE images were used as ground truth images. In the test process, the trained convolutional neural network was applied to SSTSE images. The output images were denoted as DL-SSTSE images. Apart from DL-SSTSE images, classical filtering methods were adopted to SSTSE images. Generated images were denoted as F-SSTSE images. Contrast ratio (CR) of gluteal fat and myometrium and signal-to-noise ratio (SNR) of gluteal fat were measured for all images. Two radiologists graded these images using a 5-point scale and evaluated the image quality with regard to overall image quality, contrast, noise, motion artifact, boundary sharpness of layers in the uterus, and the conspicuity of the ovaries. CRs, SNRs, and image quality scores were compared using the Steel-Dwass multiple comparison tests.CRs and SNRs were significantly higher in DL-SSTSE, F-SSTSE, and TSE images than in SSTSE images. Scores with regard to overall image quality, contrast, noise, and boundary sharpness of layers in the uterus were significantly higher on DL-SSTSE and TSE images than on SSTSE images. There were no significant differences in the CRs, SNRs, and respective scores between DL-SSTSE and TSE images. The score with regard to motion artifacts was significantly higher on DL-SSTSE, F-SSTSE, and SSTSE images than on TSE images. The score with regard to the conspicuity of ovaries was significantly higher on DL-SSTSE images than on F-SSTSE, SSTSE, and TSE images (P < .001).DL-SSTSE images showed higher image quality as compared with SSTSE images. In comparison with conventional TSE images, DL-SSTSE images had acceptable image quality while keeping the advantage of the motion artifact-robustness and acquisition time efficiency in SSTSE imaging.

Efficient segmentation of lumbar intervertebral disc from MR images

Segmentation of spine Magnetic Resonance Images (MRIs) has become an indispensable process in the diagnosis of lumbar disc degeneration, causing low back pain. Over the last decade of years, computer-directed diagnosis of disease, as well as computer-guided spine surgery, is based on the two-dimensional (2D) analysis of mid-sagittal slice of MRI. This work proposes an automatic strategy to extract the 3D segmentation of the normal disc as well as degenerated lumbar intervertebral discs (IVDs) from T2-weighted Turbo Spin Echo MRI of the spine using Connected Component (CC) analysis algorithm and statistical shape analysis. The challenges faced by the IVD segmentation includes (i) partial volume effects (ii) intensity inhomogeneity (iii) grey level overlap of different soft tissues. The proposed method first pre-processes the dataset and enables it for the application of the CC algorithm. The CC (subsets of pixels of the disc) of the spine MRI is extracted and apply statistical shape analysis for the refinement of the segmentation results to detect IVDs. Experimental results of the proposed method show a robust segmentation, accomplishing the dice similarity index of 92.4% and thus achieving a low error rate. Other performance measures such as Precision, Accuracy, JaccardIdx, JaccardDist, Global Consistency Error, Variation of Information, etc were also evaluated. The algorithm is evaluated quantitatively using adequate experiments on a dataset of 15 MRI scans, of different scenarios such as healthy and degenerate disc and this proposed method is verified as a promising accurate method for the automatic segmentation of IVD.