TSE Images Research Articles

Imaging features and management of tuberculomas: a review of cases and literature.

To describe the imaging features of patients presenting with soft tissue masses and a provisional diagnosis of soft tissue tumours, for whom biopsy confirmed the presence of necrotising granulomata consistent with tuberculoma. A review of the histopathology database for patients who had a diagnosis of necrotising granulomata in nonspinal sites. Patients with bone and joint-based pathology were excluded. Patient age, sex, lesion location, and relevant history were recorded, as were the radiographic, magnetic resonance imaging (MRI), and US findings. Four males and three females were included, with a mean age of 45.7 years (range 20-71 years). Radiographs showed soft tissue calcification in two cases. On MRI, three lesions were mildly hyperintense on T1W TSE images, and a 'penumbra sign' was seen in six cases. T2W FSE and fat suppressed PDW FSE/STIR sequences demonstrated mixed fluid/solid signal intensity in all cases. All patients showed peri-lesional oedema, while postcontrast studies in two patients showed rim enhancement and heterogeneous enhancement, respectively. On US, one lesion appeared mainly solid, and six were predominantly fluid. US-guided needle biopsy established the diagnosis of necrotising granulomatous infection in all cases. Soft tissue tuberculomas can present as soft tissue masses mimicking sarcomas. However, the presence of a 'penumbra sign' on T1W TSE sequences and peri-lesional oedema should raise the possibility of infection. Biopsy specimens should therefore be sent for both histopathology and microbiology culture and sensitivity.

Improved MR Detection of Optic Nerve Demyelination With MP2RAGE-FLAWS Compared With T2-Weighted Fat-Saturated Sequences.

Nonenhanced T1-w sequences such as magnetization-prepared 2 rapid acquisition gradient echo (MP2RAGE) and derived fluid and white matter suppression (FLAWS) have demonstrated high performance for detecting brain parenchymal and cervical spine demyelinating lesions in multiple sclerosis. However, their potential for identifying optic nerve (ON) demyelination remains unexplored. The aim of this study was to evaluate the performance of compressed sensing-accelerated (CS) MP2RAGE-FLAWS imaging for detection of ON demyelination lesions compared with T2-w fat-saturated (FS) TSE imaging in a clinical setting. We conducted a retrospective study of magnetic resonance scans acquired on patients with central nervous system demyelinating disorders between January and December 2022. Inclusion criteria were the acquisition in the same session of a brain CS-MP2RAGE-FLAWS imaging and a combination of axial + coronal T2-w FS orbital sequences. A 4-step radiological analysis-including blinded and consensus readings-assessed ON lesion detection. The reference standard was the final reading session of radiologists using the entire patient file. Sensitivities and specificities of both sequences were computed and compared using McNemar χ2 tests. Thirty-nine patients (mean age: 43 ± 14 years; 25 women) were analyzed, including 34 with multiple sclerosis, 2 with MOGAD (myelin oligodendrocyte glycoprotein antibody-associated disease), 1 with NMOSD (neuromyelitis optica spectrum disorder), and 2 with indeterminate demyelinating disease. Among the 78 ONs analyzed, 64 lesions were detected with CS-MP2RAGE-FLAWS as opposed to 37 with 2D T2-w FS imaging, corresponding to a total of 41 and 27 affected nerves, respectively. CS-MP2RAGE-FLAWS exhibited higher sensitivity for overall detection of ON lesions compared with 2D T2-w FS imaging (97.5% vs 67.5%, P = 0.001) without reducing the specificity. Improved lesion detectability with CS-MP2RAGE-FLAWS was significant compared with 2D T2-w FS in intraorbital and intracanalicular segments (respectively, 92.3% vs 50% and 96.3% vs 66.7%; P < 0.05). There was no difference in sensitivity (P = 0.69) or specificity (P = 0.99) regarding the intracranial segment analysis. CS-MP2RAGE-FLAWS sequence improves ON lesion detection compared with conventional 2D T2-w FS, especially in the intraorbital segment, while simultaneously providing whole-brain and cervical spinal cord imaging at no additional time cost.

SPINEPS—automatic whole spine segmentation of T2-weighted MR images using a two-phase approach to multi-class semantic and instance segmentation

Abstract Objectives Introducing SPINEPS, a deep learning method for semantic and instance segmentation of 14 spinal structures (ten vertebra substructures, intervertebral discs, spinal cord, spinal canal, and sacrum) in whole-body sagittal T2-weighted turbo spin echo images. Material and methods This local ethics committee-approved study utilized a public dataset (train/test 179/39 subjects, 137 female), a German National Cohort (NAKO) subset (train/test 1412/65 subjects, mean age 53, 694 female), and an in-house dataset (test 10 subjects, mean age 70, 5 female). SPINEPS is a semantic segmentation model, followed by a sliding window approach utilizing a second model to create instance masks from the semantic ones. Segmentation evaluation metrics included the Dice score and average symmetrical surface distance (ASSD). Statistical significance was assessed using the Wilcoxon signed-rank test. Results On the public dataset, SPINEPS outperformed a nnUNet baseline on every structure and metric (e.g., an average over vertebra instances: dice 0.933 vs 0.911, p &lt; 0.001, ASSD 0.21 vs 0.435, p &lt; 0.001). SPINEPS trained on automated annotations of the NAKO achieves an average global Dice score of 0.918 on the combined NAKO and in-house test split. Adding the training data from the public dataset outperforms this (average instance-wise Dice score over the vertebra substructures 0.803 vs 0.778, average global Dice score 0.931 vs 0.918). Conclusion SPINEPS offers segmentation of 14 spinal structures in T2w sagittal images. It provides a semantic mask and an instance mask separating the vertebrae and intervertebral discs. This is the first publicly available algorithm to enable this segmentation. Key Points QuestionNo publicly available automatic approach can yield semantic and instance segmentation masks for the whole spine (including posterior elements) in T2-weighted sagittal TSE images. FindingsSegmenting semantically first and then instance-wise outperforms a baseline trained directly on instance segmentation. The developed model produces high-resolution MRI segmentations for the whole spine. Clinical relevanceThis study introduces an automatic approach to whole spine segmentation, including posterior elements, in arbitrary fields of view T2w sagittal MR images, enabling easy biomarker extraction, automatic localization of pathologies and degenerative diseases, and quantifying analyses as downstream research.

AI-accelerated T2-weighted TSE imaging of the rectum demonstrates excellent image quality with reduced acquisition time.

AI-accelerated T2-weighted TSE imaging of the rectum demonstrates excellent image quality with reduced acquisition time.

Deep learning reconstruction for turbo spin echo to prospectively accelerate ankle MRI: A multi-reader study

PurposeTo evaluate a deep learning reconstruction for turbo spin echo (DLR-TSE) sequence of ankle magnetic resonance imaging (MRI) in terms of acquisition time, image quality, and lesion detectability by comparing with conventional TSE. MethodsBetween March 2023 and May 2023, patients with an indication for ankle MRI were prospectively enrolled. Each patient underwent a conventional TSE protocol and a prospectively undersampled DLR-TSE protocol. Four experienced radiologists independently assessed image quality using a 5-point scale and reviewed structural abnormalities. Image quality assessment included overall image quality, differentiation of anatomic details, diagnostic confidence, artifacts, and noise. Interchangeability analysis was performed to evaluate the equivalence of DLR-TSE relative to conventional TSE for detection of structural pathologies. ResultsIn total, 56 patients were included (mean age, 32.6 ± 10.6 years; 35 men). The DLR-TSE (233 s) protocol enabled a 57.4 % reduction in total acquisition time, compared with the conventional TSE protocol (547 s). DLR-TSE images had superior overall image quality, fewer artifacts, and less noise (all P < 0.05), compared with conventional TSE images, according to mean ratings by the four readers. Differentiation of anatomic details, diagnostic confidence, and assessments of structural abnormalities showed no differences between the two techniques (P > 0.05). Furthermore, DLR-TSE demonstrated diagnostic equivalence with conventional TSE, based on interchangeability analysis involving all analyzed structural abnormalities. ConclusionDLR can prospectively accelerate conventional TSE to a level comparable with a 4-minute comprehensive examination of the ankle, while providing superior image quality and similar lesion detectability in clinical practice.

Radiomics Analysis of Multiparametric PET/MRI for N- and M-Staging in Patients with Primary Cervical Cancer.

The aim of this study was to investigate the potential of multiparametric 18F-FDG PET/MR imaging as a platform for radiomics analysis and machine learning algorithms based on primary cervical cancers to predict N- and M-stage in patients. A total of 30 patients with histopathological confirmation of primary and untreated cervical cancer were prospectively enrolled for a multiparametric 18F-FDG PET/MR examination, comprising a dedicated protocol for imaging of the female pelvis. The primary tumor in the uterine cervix was manually segmented on post-contrast T1-weighted images. Quantitative features were extracted from the segmented tumors using the Radiomic Image Processing Toolbox for the R software environment for statistical computing and graphics. 45 different image features were calculated from non-enhanced as well as post-contrast T1-weighted TSE images, T2-weighted TSE images, the ADC map, the parametric Ktrans, Kep, Ve and iAUC maps and PET images, respectively. Statistical analysis and modeling was performed using Python 3.5 and the scikit-learn software machine learning library for the Python programming language. Prediction of M-stage was superior when compared to N-stage. Prediction of M-stage using SVM with SVM-RFE as feature selection obtained the highest performance providing sensitivity of 91 % and specificity of 92 %. Using receiver operating characteristic (ROC) analysis of the pooled predictions, the area under the curve (AUC) was 0.97. Prediction of N-stage using RBF-SVM with MIFS as feature selection reached sensitivity of 83 %, specificity of 67 % and an AUC of 0.82. M- and N-stage can be predicted based on isolated radiomics analyses of the primary tumor in cervical cancers, thus serving as a template for noninvasive tumor phenotyping and patient stratification using high-dimensional feature vectors extracted from multiparametric PET/MRI data. · Radiomics analysis based on multiparametric PET/MRI enables prediction of the metastatic status of cervical cancers. · Prediction of M-stage is superior to N-stage. · Multiparametric PET/MRI displays a valuable platform forradiomics analyses .

Kiosk 3R-FC-01 - Interleaved Flow-sensitive Dephasing (iFSD) for Enhanced Blood Flow Suppression and Preserved t1-weighted Contrast and Overall Signals in 3D TSE Imaging

Kiosk 3R-FC-01 - Interleaved Flow-sensitive Dephasing (iFSD) for Enhanced Blood Flow Suppression and Preserved t1-weighted Contrast and Overall Signals in 3D TSE Imaging

Comparison of T2-Weighted 3D-Space and T2-Weighted 2D-TSE Sequences in Lumbar Spine Magnetic Resonance Imaging (MRI)

Background: Spine-related issues like low back pain have substantially increased in the past few decades across all age categories having various reasons. Objectives: To compare the image quality and diagnostic value of 3D space MRI sequence with 2D TSE MRI sequence in lumbar spine imaging. Methods: Fifty patients, irrespective of gender having age between 30-70 years, who presented with lower back pain were enrolled for the study. Lumbar spine imaging was done using 2D TSE and 3D space sequences and the subsequent images were evaluated by two senior consultant radiologists for qualitative analysis of visibility and pathologic indices of both sequences. Data was analyzed on SPSS 25.0. Statistical analysis was done using Cohen's kappa (k). Results: Female participants were 56% of total study population. Mean age of study participants found to be 53.62±10.76 years. Statistically significant difference (p-value =0.000) was noted for visibility score of all the lumbar spine components, when the 3D SPACE and 2D TSE images were compared with 3D-SPACE images found being superior in visibility. Inter- observer agreement for visibility of various regions of lumber spine was nearly perfect (k&gt; 0.8) and substantial (0.6 to 0.8) for 3D-SPACE, while substantial (0.8&lt;k&gt; 0.6) for 2D-TSE. Pathologic indexes had a significant level of inter-observer agreement (k &gt; 0.6). Inter-observer agreement for 3D sequence (k = 0.72) was greater than that for 2D-TSE sequence (k = 0.64). Conclusion: Images from 3D-SPACE sequences provide superior visibility over 2D-TSE and could be recommended as alternative imaging method for lumbar spine pathologies. Higher inter observer agreement illustrate that it may be included in routine sequences to make the better diagnosis for lumbar spine pathologies correctly.

Differentiation of Borderline Epithelial Ovarian Tumors from Benign and Malignant Epithelial Ovarian Tumors by MRI Scoring

The distinction between benign and borderline epithelial ovarian tumors is important because treatment and follow-up strategies differ We aimed to evaluate benign, borderline, and malignant epithelial ovarian tumors using MRI features and contributed to the preoperative evaluation. MRIs of 81 patients (20 bilateral), including 31 benign, 27 borderline, and 23 malignant, who had pelvic imaging between 2013-2020, were evaluated retrospectively. The evaluation was made blindly to the pathology result by two radiologists with MRI scoring and features that we determined. MRI evaluation was performed with T1 TSE, T2 TSE, fat-suppressed T2 TSE, and before and after contrast T1 fat-suppressed and non-fat-suppressed TSE images. The numbers and findings obtained in scoring were evaluated by Chi-Square, ordinal logistic regression, and 2 and 3 category ROC analysis. The total score varied between 7 and 24. Among the three groups, a significant difference was found in terms of T1, T2 signal intensity (p <0.01), size (p = 0.055), solid area (p <0.001), septa number (p <0.05), ovarian parenchyma (p = 0.001), ascites (p <0.001), peritoneal involvement (p <0.001), laterality (p <0.001), contrast enhancement pattern (p <0.001). On the other hand, no significant difference was found in terms of wall thickness, lymph node involvement and endometrial thickness (p> 0.05). Cut-off values were found as 11.5 and 18.5 in the 3-category ROC analysis performed for the score (VUS: 0.8109). Patients with a score below 11.5 were classified as benign, those between 11.5-18.5 as borderline, and those over 18.5 as malignant. The differentiation of borderline tumors from benign and malignant tumors by MRI scoring will contribute to the preoperative diagnosis.

Reliability of Cervical Neural Foramen Stenosis Grading Based on Axial Three-Dimensional Magnetic Resonance Images

Objective: To assess the reliability of cervical neural foramen stenosis (CNFS) grading by using three-dimensional (3D) T1W, 3D T2W, and twodimensional (2D) T2W images in axial plane. Materials and Methods: The authors enrolled 32 patients between December 2019 and February 2020 who underwent cervical spine magnetic resonance imaging (MRI) with clinical manifestations of cervical spondylosis. Two blinded radiologists interpreted the axial 3D T1W TSE, 3D T2W TSE, and 2D T2W TSE images using a 4-point visual scale for CNFS grading in all cervical levels. Intra-observer agreement of CNFS grading on the three imaging pulse sequences for each observer and inter-observer agreement between both observers were analyzed using intra-class correlation coefficient (ICC). Results: Three hundred eighty-four neural foramina were evaluated. The overall mean intra-observer agreement of CNFS grading was strong on the axial 3D T1W TSE, 3D T2W TSE, and 2D T2W TSE images for each observer with ICC values of 0.79 and 0.82. The overall mean inter-observer agreement for CNFS grading was strong on 3D T1W TSE, 3D T2W TSE, and 2D T2W TSE images with ICC values of 0.79, 0.79, and 0.86, respectively. Conclusion: Axial 3D T1W TSE, 3D T2W TSE, and 2D T2W TSE images exhibited comparable strong reliability in the grading of cervical neural foramen stenosis without the significant benefit of 3D over 2D technique. Keywords: Cervical spine; Neural foramen stenosis; MRI; Grading

High-Resolution 7T MR Imaging of the Trochlear Nerve.

The trochlear nerve has traditionally been difficult to identify on MR imaging. The advent of 7T MR imaging promises to greatly benefit visualization of small structures due to gains in the signal-to-noise ratio allowing improved spatial resolution. We investigated the utility of a clinically feasible ultra-high-resolution 7T MR imaging protocol for identification of the trochlear nerve, as well as assessment of normal trochlear nerve anatomy. Coronal high-resolution 2D T2-weighted TSE images used in a 7T epilepsy protocol of 50 subjects at our institution were reviewed by 2 independent radiologists for visualization of the trochlear nerve at the nerve origin and cisternal, tentorial, and cavernous segments. The frequency of nerve visibility within these segments and their anatomy were documented, and disagreements were resolved by joint review. Of the 100 nerves reviewed in 50 subjects, at least 2 segments of the trochlear nerve from the brainstem to the cavernous sinus were identified in 100% of cases. The origins from the brainstem and cisternal segment were visible in 65% and 93% of nerves, respectively. The trochlear nerve was identified at the trochlear groove in 100% of cases and in the posterior wall of the cavernous sinus in 74% of cases. Coronal high-resolution 2D TSE at 7T reliably identified the trochlear nerve throughout its course and is a promising tool for imaging patients with suspected trochlear nerve pathology.

Thin-Slice Prostate MRI Enabled by Deep Learning Image Reconstruction.

Thin-slice prostate MRI might be beneficial for prostate cancer diagnostics. However, prolongation of acquisition time is a major drawback of thin-slice imaging. Therefore, the purpose of this study was to investigate the impact of a thin-slice deep learning accelerated T2-weighted (w) TSE imaging sequence (T2DLR) of the prostate as compared to conventional T2w TSE imaging (T2S). Thirty patients were included in this prospective study at one university center after obtaining written informed consent. T2S (3 mm slice thickness) was acquired first in three orthogonal planes followed by thin-slice T2DLR (2 mm slice thickness) in axial plane. Acquisition time of axial conventional T2S was 4:12 min compared to 4:37 min for T2DLR. Imaging datasets were evaluated by two radiologists using a Likert-scale ranging from 1-4, with 4 being the best regarding the following parameters: sharpness, lesion detectability, artifacts, overall image quality, and diagnostic confidence. Furthermore, preference of T2S versus T2DLR was evaluated. The mean patient age was 68 ± 8 years. Sharpness of images and lesion detectability were rated better in T2DLR with a median of 4 versus a median of 3 in T2S (p < 0.001 for both readers). Image noise was evaluated to be significantly worse in T2DLR as compared to T2S (p < 0.001 and p = 0.021, respectively). Overall image quality was also evaluated to be superior in T2DLR versus T2S with a median of 4 versus 3 (p < 0.001 for both readers). Both readers chose T2DLR in 29 cases as their preference. Thin-slice T2DLR of the prostate provides a significant improvement of image quality without significant prolongation of acquisition time.

Comment on Gassenmaier et al. Accelerated T2-Weighted TSE Imaging of the Prostate Using Deep Learning Image Reconstruction: A Prospective Comparison with Standard T2-Weighted TSE Imaging. Cancers 2021, 13, 3593.

Magnetic resonance imaging (MRI) plays a central role in oncology without using ionizing radiation or radioactive markers [...].

High-Resolution 3D MRI With Deep Generative Networks via Novel Slice-Profile Transformation Super-Resolution.

High-resolution magnetic resonance imaging (MRI) sequences, such as 3D turbo or fast spin-echo (TSE/FSE) imaging, are clinically desirable but suffer from long scanning time-related blurring when reformatted into preferred orientations. Instead, multi-slice two-dimensional (2D) TSE imaging is commonly used because of its high in-plane resolution but is limited clinically by poor through-plane resolution due to elongated voxels and the inability to generate multi-planar reformations due to staircase artifacts. Therefore, multiple 2D TSE scans are acquired in various orthogonal imaging planes, increasing the overall MRI scan time. In this study, we propose a novel slice-profile transformation super-resolution (SPTSR) framework with deep generative learning for through-plane super-resolution (SR) of multi-slice 2D TSE imaging. The deep generative networks were trained by synthesized low-resolution training input via slice-profile downsampling (SP-DS), and the trained networks inferred on the slice profile convolved (SP-conv) testing input for 5.5x through-plane SR. The network output was further slice-profile deconvolved (SP-deconv) to achieve an isotropic super-resolution. Compared to SMORE SR method and the networks trained by conventional downsampling, our SPTSR framework demonstrated the best overall image quality from 50 testing cases, evaluated by two abdominal radiologists. The quantitative analysis cross-validated the expert reader study results. 3D simulation experiments confirmed the quantitative improvement of the proposed SPTSR and the effectiveness of the SP-deconv step, compared to 3D ground-truths. Ablation studies were conducted on the individual contributions of SP-DS and SP-conv, networks structure, training dataset size, and different slice profiles.

Poster 200: High Prevalence of Abnormal Imaging Findings in Clinically Asymptomatic Siblings Of JOCD Patients On 3T Knee MRI

Objectives:Endochondral ossification is a skeletal developmental process in children by which the embryonic cartilaginous model of bones undergoes gradual ossification over time until skeletal maturity is reached. Juvenile Osteochondritis Dissecans (JOCD) is a developmental disease characterized by focal areas of chondronecrosis within the epiphyseal cartilage and subsequent delay of the ossification front. JOCD lesions can become loose bodies and lead to premature Osteoarthritis. The etiology of JOCD is not yet well understood, however, there is mounting evidence of a genetic predisposition. Recently, positive familial history, including familial OCD and a genome-wide association study in humans identified genetic loci related to juvenile OCD. In this longitudinal pilot study, we examined siblings of JOCD patients utilizing clinical 3T MRI data to evaluate morphological integrity of the epiphyseal cartilage and the advancing ossification front in the distal femoral condyles in bilateral knees. We hypothesized that asymptomatic, clinically “silent” JOCD lesions could be detected in young siblings of patients affected by JOCD.Methods:In this longitudinal study, 44 MRI datasets from seven skeletally immature participants with no clinical symptoms (7 siblings of JOCD patients; 3 females; 12 bilateral knees; average age at first visit=8.7 years; range=6-10 years) were evaluated. This study was approved by the institutional review board and informed consent was obtained. All images were acquired at 3T MRI system with a 1Tx/15Rx knee coil. Sagittal PD-weighted TSE images without fat suppression (TR/TE = 3900/40 ms, resolution = 0.36x0.36 mm2, scanning time = 1min:49s) and with fat suppression (TR/TE = 3530/40 ms, resolution = 0.36x0.36 mm2, scanning time = 3min:46s) were acquired bilaterally at first visit and at multiple MRI follow-up studies ranging from 6-21 months. The images were reviewed by an experienced musculoskeletal radiologist using the following MRI criteria: (i) integrity of the ossification front; (ii) presence/absence of bone marrow edema; (iii) intact/disrupted secondary physis; and (iv) T2 hyperintensity in epiphyseal cartilage.Results:Five of seven participants (71%) met at least one of the MRI criteria defining a JOCD lesion. Six of the seven participants (86%) had an irregular ossification front at the distal aspect of the medial and/or lateral femoral epicondyles, focal areas of T2 hyperintensities in the epiphyseal cartilage, and a disrupted secondary physis. Of the 13 imaged knees, two knees (both lateral and medial epicondyle) from the same participant and two knees (only lateral epicondyle) had no abnormal MRI findings (= 6 normal epicondyles). Abnormal findings in the medial and lateral epicondyles of the remaining bilateral knees resolved over time in 11 epicondyles (Fig. 1), whereas in the remaining 9 epicondyles the abnormal findings persisted or progressed (Fig. 2).Conclusions:The most important finding of this pilot study is the high prevalence (6 out of 7, 86%) of morphological changes during skeletal development in this group of first-degree relatives of JOCD patients. Furthermore, 71% (5 out of 6) of participants met the imaging criteria for early JOCD lesions at least at one time point during the study without developing any clinical symptoms. There is mounting evidence of a genetic contribution to the etiology of JOCD. In the literature, so called ossification variants are considered morphological variants of bone shape with an overall prevalence of 12% and are believed to resolve naturally over time. While 55% of the epicondyles with abnormalities in the ossification front in our cohort resolved over time on MRI, during the course of this study – typically 8-21 months, the remaining 45% did not resolve or occurred at the last imaging time point with associated marrow edema and needed clinical surveillance. A high incidence of MRI abnormalities in the ossification front, epiphyseal cartilage and secondary physis in a clinically asymptomatic study group of first degree relatives of patients with JOCD supports the hypothesis a) that there is a strong genetic predisposition for this disease, b) clinically “silent” initial stages of the disease could be overlooked, challenging the common current understanding of normal physiologic “ossification variants”.Figure 1.Sagittal PD-weighted TSE w/o fat-suppression (FS) of the lateral femoral condyle in a 10-year-old boy. The follow-up studies demonstrate complete resolution of the irregular ossification front (arrowhead), absence of bone marrow edema.Figure 2.Sagittal PD-weighted TSE w/o fat-suppression (FS) of the lateral femoral condyle in a 10-year-old boy. The baseline study demonstrates a focal T2-hyperintense lesion (arrow) and a delayed ossification front with associated bone marrow edema (*) meeting the MR imaging criteria for an early JOCD lesion. The asymptomatic sibling was clinically surveilled and subsequent follow-up studies demonstrated resolution of the MR imaging findings.

3D CAIPIRINHA SPACE versus standard 2D TSE for routine knee MRI: a large-scale interchangeability study.

To perform a large-scale interchangeability study comparing 3D controlled aliasing in parallel imaging results in higher acceleration (CAIPIRINHA) sampling perfection with application optimized contrast using different flip angle evolutions (SPACE) TSE with standard 2D TSE for knee MRI. In this prospective study, 250 patients underwent 3 T knee MRI, including a multicontrast 3D CAIPIRINHA SPACE TSE (9:26 min) and a standard 2D TSE protocol (12:14 min). Thirty-three (13%) patients had previous anterior cruciate ligament and/or meniscus surgery. Two radiologists assessed MRIs for image quality and identified pathologies of menisci, ligaments, and cartilage by using a 4-point Likert scale according to the level of diagnostic confidence. Interchangeability of the protocols was tested under the same-reader scenario using a bootstrap percentile confidence interval. Interreader reliability and intermethod concordance were also evaluated. Despite higher image quality and diagnostic confidence for standard 2D TSE compared to 3D CAIPIRINHA SPACE TSE, the protocols were found interchangeable for diagnosing knee abnormalities, except for patellar (6.8% difference; 95% CI: 4.0, 9.6) and trochlear (3.6% difference; 95% CI: 0.8, 6.6) cartilage defects. The interreader reliability was substantial to almost perfect for 2D and 3D MRI (range κ, 0.785-1 and κ, 0.725-0.964, respectively). Intermethod concordance was almost perfect for all diagnoses (range κ, 0.817-0.986). Multicontrast 3D CAIPIRINHA SPACE TSE and standard 2D TSE protocols perform interchangeably for diagnosing knee abnormalities, except for patellofemoral cartilage defects. Despite the radiologist's preference for 2D TSE imaging, a pursuit towards time-saving 3D TSE knee MRI is justified for routine practice. • Multicontrast 3D CAIPIRINHA SPACE and standard 2D TSE protocols perform interchangeably for diagnosing knee abnormalities, except for patellofemoral cartilage defects. • Radiologists are more confident in diagnosing knee abnormalities on 2D TSE than on 3D CAIPIRINHA SPACE TSE MRI. • Despite the radiologist's preference for 2D TSE, a pursuit towards accelerated 3D TSE knee MRI is justified for routine practice.

Proximal Region of Carotid Atherosclerotic Plaque Shows More Intraplaque Hemorrhage: The Plaque at Risk Study.

Intraplaque hemorrhage contributes to lipid core enlargement and plaque progression, leading to plaque destabilization and stroke. The mechanisms that contribute to the development of intraplaque hemorrhage are not completely understood. A higher incidence of intraplaque hemorrhage and thin/ruptured fibrous cap (upstream of the maximum stenosis in patients with severe [≥70%] carotid stenosis) has been reported. We aimed to noninvasively study the distribution of intraplaque hemorrhage and a thin/ruptured fibrous cap in patients with mild-to-moderate carotid stenosis. Eighty-eight symptomatic patients with stroke (<70% carotid stenosis included in the Plaque at Risk study) demonstrated intraplaque hemorrhage on MR imaging in the carotid artery plaque ipsilateral to the side of TIA/stroke. The intraplaque hemorrhage area percentage was calculated. A thin/ruptured fibrous cap was scored by comparing pre- and postcontrast black-blood TSE images. Differences in mean intraplaque hemorrhage percentages between the proximal and distal regions were compared using a paired-samples t test. The McNemar test was used to reveal differences in proportions of a thin/ruptured fibrous cap. We found significantly larger areas of intraplaque hemorrhage in the proximal part of the plaque at 2, 4, and 6 mm from the maximal luminal narrowing, respectively: 14.4% versus 9.6% (P = .04), 14.7% versus 5.4% (P < .001), and 11.1% versus 2.2% (P = .001). Additionally, we found an increased proximal prevalence of a thin/ruptured fibrous cap on MR imaging at 2, 4, 6, and 8 mm from the MR imaging section with the maximal luminal narrowing, respectively: 33.7% versus 18.1%, P = .007; 36.1% versus 7.2%, P < .001; 33.7% versus 2.4%, P = .001; and 30.1% versus 3.6%, P = .022. We demonstrated that intraplaque hemorrhage and a thin/ruptured fibrous cap are more prevalent on the proximal side of the plaque compared with the distal side in patients with mild-to-moderate carotid stenosis.

Stability of Liver Radiomics across Different 3D ROI Sizes-An MRI In Vivo Study.

We aimed to evaluate the stability of radiomic features in the liver of healthy individuals across different three-dimensional regions of interest (3D ROI) sizes in T1-weighted (T1w) and T2-weighted (T2w) images from different MR scanners. We retrospectively included 66 examinations of patients without known diseases or pathological imaging findings acquired on three MRI scanners (3 Tesla I: 25 patients, 3 Tesla II: 19 patients, 1.5 Tesla: 22 patients). 3D ROIs of different diameters (10, 20, 30 mm) were drawn on T1w GRE and T2w TSE images into the liver parenchyma (segment V–VIII). We extracted 93 radiomic features from the different ROIs and tested features for significant differences with the Mann–Whitney-U (MWU)-test. The MWU-test revealed significant differences for most second- and higher-order features, indicating a systematic difference dependent on the ROI size. The features mean, median, root mean squared (RMS), 10th percentile, and 90th percentile were not significantly different. We also assessed feature robustness to ROI size variation with overall concordance correlation coefficients (OCCCs). OCCCs across the different ROI-sizes for mean, median, and RMS were excellent (>0.90) in both sequences on all three scanners. These features, therefore, seem robust to ROI-size variation and suitable for radiomic studies of liver MRI.

A deep learning method for predicting knee osteoarthritis radiographic progression from MRI

BackgroundThe identification of patients with knee osteoarthritis (OA) likely to progress rapidly in terms of structure is critical to facilitate the development of disease-modifying drugs.MethodsUsing 9280 knee magnetic resonance (MR) images (3268 patients) from the Osteoarthritis Initiative (OAI) database , we implemented a deep learning method to predict, from MR images and clinical variables including body mass index (BMI), further cartilage degradation measured by joint space narrowing at 12 months.ResultsUsing COR IW TSE images, our classification model achieved a ROC AUC score of 65%. On a similar task, trained radiologists obtained a ROC AUC score of 58.7% highlighting the difficulty of the classification task. Additional analyses conducted in parallel to predict pain grade evaluated by the WOMAC pain index achieved a ROC AUC score of 72%. Attention maps provided evidence for distinct specific areas as being relevant in those two predictive models, including the medial joint space for JSN progression and the intra-articular space for pain prediction.ConclusionsThis feasibility study demonstrates the interest of deep learning applied to OA, with a potential to support even trained radiologists in the challenging task of identifying patients with a high-risk of disease progression.

Delineation of Inner Annulus Fibrosus and Nucleus Pulposus on Routine T2-weighted MR Images.

Retrospective study of 150 IVDs. Assessment of costume algorithm ability to delineate the IAF and NP on routine T2 images. Central hyperintense region on T2-weighted MR images of normal lumbar IVDs represents a combination of IAF and NP. Ability to identify NP as distinct from IAF can help improve our understanding of IVD morphology in-vivo. Sagittal T2-weighted TSE MR images of 150 lumbar IVDs from 25 patients were analyzed. MR images were processed using a custom algorithm that markedly increased the signal intensity of structures with inherent signal intensity within 2 defined intensity thresholds. Signal intensity and contrast-to- noise ratio between outer annulus fibrosus, IAF, and NP were assessed at baseline and after processing. To assess consistency of underlying T2 differences, similar analysis was done on 108 discs from 18 patients in whom additional sagittal T2-weighted STIR images were available. Following image processing, apparent IAF and NP were rendered visible in 86% and 84.3% IVDs on T2-weighted TSE and STIR images respectively. While signal intensity of these 2 regions was inherently different (P< 0.001) before processing on TSE and STIR images, their visualization was facilitated by a significant increase (P<0.001) in contrast-to-noise ratio after processing. Nonvisualization of NP was associated with disc degeneration (P<0.001). Inherent differences exist in signal intensities of normal NP and IAF on T2-weighted MR images. Accentuating these differences using image postprocessing techniques can render these 2 structures visible.