Magnetic resonance imaging in the evaluation of cervical foraminal stenosis: comparison of 3D T2 SPACE with sagittal oblique 2D T2 TSE

Objective The oblique orientation of the cervical neural foramina challenges the implementation of a short MRI protocol with concurrent excellent visualization of the spine. While sagittal oblique T2-weighted sequences permit good evaluation of the cervical neuroforamina, all segments may not be equally well depicted on a single sequence and conspicuity of foraminal stenosis may be limited. 3D T2-weighted sequences can be reformatted in arbitrary planes, including the sagittal oblique. We set out to compare 3D T2w SPACE sequences with sagittal oblique reformations and sagittal oblique 2D T2w TSE sequences for the evaluation of cervical foraminal visibility and stenosis. Materials and methods Sixty consecutive patients who underwent MRI of the cervical spine with sagittal oblique 2D T2w TSE and 3D T2w SPACE sequences were included. Image homogeneity of the sequences was evaluated. Imaging sets were assessed for structure visibility and foraminal stenosis by two independent readers. Results of the sequences were compared by Wilcoxon matched-pairs tests. Interreader agreement was evaluated by weighted κ. Results Visibility of most structures was rated good to excellent on both sequences (mean visibility scores ≥ 4.5 of 5), though neuroforaminal contents were better seen on sagittal oblique T2w TSE (mean scores 4.1–4.6 vs. 3.1–4.1 on 3D T2w SPACE, p < 0.01). Stenosis grades were comparable between sequences (mean 1.1–2.6 of 4), with slightly higher values for 3D T2w SPACE at some levels (difference ≤ 0.3 points). Conclusion 3D T2w SPACE is comparable with sagittal oblique 2D T2w TSE in the evaluation of cervical neural foramina.

A case report of an extremely rare type of cardiac tumor: Primary Cardiac Angiofibroma

Cardiac angiofibroma is a very rare diagnosis when a patient develops an intracardiac mass. It is a primary benign cardiac tumor with a scarcity of information in the literature. This case report illustrates a 26-year-old man with a complaint of chronic chest tightness who was firstly diagnosed with right ventricle tumor by echocardiography then underwent cardiac MRI which confirmed the presence of a highly-vascular tumor with radiologically benign behavior. Then his tumor was excised, his postoperative course was uncomplicated and he was well within almost 2 months after discharge. Ultimately the histopathologic findings demonstrated vascular and stromal tissue in favor of angiofibroma and excluded the other diagnoses with IHC and trichrome staining. Angiofibroma is a benign, highly vascular tumor, mostly discovered in the nasopharynx. When it is found in the heart, CMR and pathology are pivotal to rule in its diagnosis. It is isointense in T1 weighted and hyperintense in T2 weighted sequences with intense enhancement following contrast injection. Its pathology contains an admixture of vasculatures with CD31 positive immunoreactivity for endothelial cells and fibrotic tissue with bluish coloration in trichrome staining. Eventually, its treatment includes merely surgical excision given its benign nature.

Qualitative Heterogeneous Signal Drop on Chemical Shift (CS) MR Imaging: Correlative Quantitative Analysis between CS Signal Intensity Index and Contrast Washout Parameters Using T1-Weighted Sequences

The aim of this study was to calculate MRI quantitative parameters extracted from chemical-shift (CS) and dynamic contrast-enhanced (DCE) T1-weighted (T1-WS) images of adrenal lesions (AL) with qualitative heterogeneous signal drop on CS T1-WS and compare them to those of AL with homogeneous or no signal drop on CS T1-WS. On 3 T MRI, 65 patients with a total of 72 AL were studied. CS images were qualitatively assessed for grouping AL as showing homogeneous (Group 1, n = 19), heterogeneous (Group 2, n = 23), and no (Group 3, n = 30) signal drop. Histopathology or follow-up data served as reference standard to classify AL. ROIs were drawn both on CS and DCE images to obtain adrenal CS signal intensity index (ASII), absolute (AWO), and relative washout (RWO) values. Quantitative parameters (QP) were compared with ANOVA analysis and post hoc Dunn’s test. The performance of QP to classify AL was assessed with receiver operating characteristic analysis. CS ASII values were significantly different among the three groups (p < 0.001) with median values of 71%, 53%, and 3%, respectively. AWO/RWO values were similar in Groups 1 (adenomas) and 2 (benign AL) but significantly (p < 0.001) lower in Group 3 (20 benign AL and 10 malignant AL). With cut-offs, respectively, of 60% (Group 1 vs. 2), 20% (Group 2 vs. 3), and 37% (Group 1 vs. 3), CS ASII showed areas under the curve of 0.85, 0.96, and 0.93 for the classification of AL, overall higher than AWO/RWO. In conclusion, AL with qualitative heterogeneous signal drop at CS represent benign AL with QP by DCE sequence similar to those of AL with homogeneous signal drop at CS, but different to those of AL with no signal drop at CS; ASII seems to be the only quantitative parameter able to differentiate AL among the three different groups.

Artificial intelligence-based automatic assessment of lower limb torsion on MRI

Abnormal torsion of the lower limbs may adversely affect joint health. This study developed and validated a deep learning-based method for automatic measurement of femoral and tibial torsion on MRI. Axial T2-weighted sequences acquired of the hips, knees, and ankles of 93 patients (mean age, 13 ± 5 years; 52 males) were included and allocated to training (n = 60), validation (n = 9), and test sets (n = 24). A U-net convolutional neural network was trained to segment both femur and tibia, identify osseous anatomic landmarks, define pertinent reference lines, and quantify femoral and tibial torsion. Manual measurements by two radiologists provided the reference standard. Inter-reader comparisons were performed using repeated-measures ANOVA, Pearson’s r, and the intraclass correlation coefficient (ICC). Mean Sørensen-Dice coefficients for segmentation accuracy ranged between 0.89 and 0.93 and erroneous segmentations were scarce. Ranges of torsion as measured by both readers and the algorithm on the same axial image were 15.8°–18.0° (femur) and 33.9°–35.2° (tibia). Correlation coefficients (ranges, .968 ≤ r ≤ .984 [femur]; .867 ≤ r ≤ .904 [tibia]) and ICCs (ranges, .963 ≤ ICC ≤ .974 [femur]; .867 ≤ ICC ≤ .894 [tibia]) indicated excellent inter-reader agreement. Algorithm-based analysis was faster than manual analysis (7 vs 207 vs 230 s, p < .001). In conclusion, fully automatic measurement of torsional alignment is accurate, reliable, and sufficiently fast for clinical workflows.

A case report of an extremely rare type of cardiac tumor: Primary Cardiac Angiofibroma

Cardiac angiofibroma is a very rare diagnosis when a patient develops an intracardiac mass. It is a primary benign cardiac tumor with a scarcity of information in the literature. This case report illustrates a 26-year-old man with a complaint of chronic chest tightness who was firstly diagnosed with right ventricle tumor by echocardiography then underwent cardiac MRI which confirmed the presence of a highly-vascular tumor with radiologically benign behavior. Then his tumor was excised, his postoperative course was uncomplicated and he was well within almost 2 months after discharge. Ultimately the histopathologic findings demonstrated vascular and stromal tissue in favor of angiofibroma and excluded the other diagnoses with IHC and trichrome staining. Angiofibroma is a benign, highly vascular tumor, mostly discovered in the nasopharynx. When it is found in the heart, CMR and pathology are pivotal to rule in its diagnosis. It is isointense in T1 weighted and hyperintense in T2 weighted sequences with intense enhancement following contrast injection. Its pathology contains an admixture of vasculatures with CD31 positive immunoreactivity for endothelial cells and fibrotic tissue with bluish coloration in trichrome staining. Eventually, its treatment includes merely surgical excision given its benign nature.

NIMG-10. OPTIMIZING IMAGE QUALITY FOR MAGNETIC RESONANCE SIMULATION IN SPINE STEREOTACTIC BODY RADIATION THERAPY

BACKGROUND Currently, the standard MRI sequence for SC imaging in SBRT has been axial 2D T2-weighted Turbo Spin Echo (TSE). Even though 3D T2-weighted sequences such as SPACE (Sampling Perfection with Application optimized Contrasts using different flip angle Evolution) image a whole volume simultaneously and thus offer better reconstruction, they have not been clinically implemented due to their long acquisition times. However, the application of Compressed Sensing (CS) methods on SPACE sequences, achieving clinically acceptable time. METHODS A 3D T2 CS SPACE was obtained and evaluated against the standard 2D TSE for spine SBRT based on a MagPhan RT quality assurance phantom and patients data, analysis was done using the phantom manufacturer software ImageOwl that calculates image distortions by comparing the known position of phantom features to their detected position in the image. RESULTS Results of phantom comparison between 3D T2 and 2D T2 indicate that although the 3D sequence had lower signal-to-noise ratio (SNR) than the 2D sequence, it presented less geometric distortions caused by gradient non-linearities, particularly in the anterior-posterior (A/P) and head-feet (H/F) directions. Distortions caused by chemical shift are in theory smaller for the 3D T2 CS SPACE, amounting to 0.85mm compared to 1.62mm with 2D T2. Between 2D versus 3D MRI defined SC data among 4 patients, average deviation of the centroid point cord contours was 0.08cm. The volume of the cord showed 1cc larger 3D volumes compared to 2D T2. Finally, the mean voxel count overlap coefficient and DICE coefficient was 0.92 and 0.87 respectively. CONCLUSIONS Since 3D MRI is under consideration to replace 2D MRI, it is important to compare SC contours from 3D to 2D MRI and assess their impact on treatment plans. Positive results would pave the path for larger subject cohort evaluation.

Walk Your Talk: Real-World Adherence to Guidelines on the Use of MRI in Multiple Sclerosis

(1) Although guidelines about the use of MRI sequences for Multiple Sclerosis (MS) diagnosis and follow-up are available, variability in acquisition protocols is not uncommon in everyday clinical practice. The aim of this study was to evaluate the real-world application of MS imaging guidelines in different settings to clarify the level of adherence to these guidelines. (2) Via an on-line anonymous survey, neuroradiologists (NR) were asked about MRI protocols and parameters routinely acquired when MS patients are evaluated in their center, both at diagnosis and follow-up. Furthermore, data about report content and personal opinions about emerging neuroimaging markers were also retrieved. (3) A total of 46 participants were included, mostly working in a hospital or university hospital (80.4%) and with more than 10 years of experience (47.9%). We found a relatively good adherence to the suggested MRI protocols regarding the use of T2-weighted sequences, although almost 10% of the participants routinely acquired 2D sequences with a slice thickness superior to 3 mm. On the other hand, a wider degree of heterogeneity was found regarding gadolinium administration, almost routinely performed at follow-up examination (87.0% of cases) in contrast with the current guidelines, as well as a low use of a standardized reporting system (17.4% of cases). (4) Although the MS community is getting closer to a standardization of MRI protocols, there is still a relatively wide heterogeneity among NR, with particular reference to contrast administration, which must be overcome to guarantee an adequate quality of patients’ care in MS.

Multi-view convolutional neural networks for automated ocular structure and tumor segmentation in retinoblastoma

In retinoblastoma, accurate segmentation of ocular structure and tumor tissue is important when working towards personalized treatment. This retrospective study serves to evaluate the performance of multi-view convolutional neural networks (MV-CNNs) for automated eye and tumor segmentation on MRI in retinoblastoma patients. Forty retinoblastoma and 20 healthy-eyes from 30 patients were included in a train/test (N = 29 retinoblastoma-, 17 healthy-eyes) and independent validation (N = 11 retinoblastoma-, 3 healthy-eyes) set. Imaging was done using 3.0 T Fast Imaging Employing Steady-state Acquisition (FIESTA), T2-weighted and contrast-enhanced T1-weighted sequences. Sclera, vitreous humour, lens, retinal detachment and tumor were manually delineated on FIESTA images to serve as a reference standard. Volumetric and spatial performance were assessed by calculating intra-class correlation (ICC) and dice similarity coefficient (DSC). Additionally, the effects of multi-scale, sequences and data augmentation were explored. Optimal performance was obtained by using a three-level pyramid MV-CNN with FIESTA, T2 and T1c sequences and data augmentation. Eye and tumor volumetric ICC were 0.997 and 0.996, respectively. Median [Interquartile range] DSC for eye, sclera, vitreous, lens, retinal detachment and tumor were 0.965 [0.950–0.975], 0.847 [0.782–0.893], 0.975 [0.930–0.986], 0.909 [0.847–0.951], 0.828 [0.458–0.962] and 0.914 [0.852–0.958], respectively. MV-CNN can be used to obtain accurate ocular structure and tumor segmentations in retinoblastoma.