Coronal T1-weighted Images Research Articles

Establishing Optic Nerve Diameter Threshold Sensitive and Specific for Optic Atrophy Diagnosis.

To determine apotential threshold optic nerve diameter (OND) that could reliably differentiate healthy nerves from those affected by optic atrophy (OA) and to determine correlations of OND in OA with retinal nerve fiber layer (RNFL) thickness, visual acuity (VA), and visual field mean deviation (VFMD). This was aretrospective case control study. Magnetic resonance (MR) images were reviewed from individuals with OA aged 18years or older with vision loss for more than 6months and an OA diagnosis established by aneuro-ophthalmologist. Individuals without OA who underwent MR imaging of the orbit for other purposes were also collected. OND was measured on coronal T2-weighted images in the midorbital section, 1cm posterior to the optic disc. Measurements of mean RNFL thickness, VA and VFMD were also collected. In this study 47 OA subjects (63% women, 78eyes) and 75 normal subjects (42.7% women, 127 eyes) were assessed. Healthy ONDs (mean 2.73 ± 0.24 mm) were significantly greater than OA nerve diameters (mean 1.94 ± 0.32 mm; P < 0.001). Athreshold OND of ≤2.3 mmhadasensitivity of 0.92 and aspecificity of 0.93 in predicting OA. Mean RNFL (r = 0.05, p = 0.68), VA (r = 0.17, p = 0.14), and VFMD (r = 0.18, p = 0.16) were not significantly associated with OND. ONDs are significantly reduced in patients with OA compared with healthy nerves. Athreshold OND of ≤2.3 mm is highly sensitive and specific for adiagnosis of OA. OND was not significantly correlated with RNFL thickness, VA, or VFMD.

Portable MRI to assess optic chiasm decompression after endoscopic endonasal resection of sellar and suprasellar lesions.

Low-field portable MRI (pMRI) is a recent technological advancement with potential for broad applications. Compared with conventional MRI, pMRI is less resource-intensive with regard to operational costs and scan time. The application of pMRI in neurosurgical oncology has not been previously described. The goal of this study was to demonstrate the efficacy of pMRI in assessing optic nerve decompression after endoscopic endonasal surgery for sellar and suprasellar pathologies. Patients who underwent endoscopic endonasal surgery for sellar and suprasellar lesions at a single institution and for whom pMRI and routine MRI were performed postoperatively were retrospectively reviewed to compare the two imaging systems. To assess the relative resolution of pMRI compared with MRI, the distance from the optic chiasm to the top of the third ventricle was measured, and the measurements were compared between paired equivalent slices on T2-weighted coronal images. The inter- and intrarater correlations were analyzed. Twelve patients were included in this study (10 with pituitary adenomas and 2 with craniopharyngiomas) with varying degrees of optic chiasm compression on preoperative imaging. Measurements were averaged across raters before calculating agreement between pMRI and MRI, which demonstrated significant interrater reliability (intraclass correlation coefficient [ICC] = 0.78, p < 0.01). Agreement between raters within the pMRI measurements was also significantly reliable (ICC = 0.93, p < 0.01). Finally, a linear mixed-effects model was specified to demonstrate that MRI measurement could be predicted using the pMRI measurement with the patient and rater set as random effects (pMRI β coefficient = 0.80, p < 0.01). The results of this study suggest that resolution of pMRI is comparable to that of conventional MRI in assessing the optic chiasm position in relation to the third ventricle. Portable MRI sufficiently demonstrates decompression of the optic chiasm after endoscopic endonasal surgery. It can be an alternative strategy in cases in which cost, scan-time considerations, or lack of intraoperative MRI availability may preclude the ability to assess adequate optic nerve decompression after endoscopic endonasal surgery for sellar and suprasellar lesions.

Pediatric craniopharyngiomas: magnetic resonance imaging assessment for hypothalamus-pituitary axis dysfunction and outcome prediction.

In adamantinomatous craniopharyngiomas, tumor topographical categories, cystic component volume, and magnetic resonance signal intensity may impact prognosis. To identify magnetic resonance imaging (MRI) variables associated with pituitary-hypothalamic axis dysfunction and predictive of outcome in children with cystic adamantinomatous craniopharyngiomas. We evaluated 40 preoperative MRIs of adamantinomatous craniopharyngiomas to classify tumor topography, volume, and signal intensity of the cystic components and peritumoral edema. Volumes and normalized signal intensity minimum values were extracted from coronal T2-weighted images (nT2min). Radiological variables were compared to pituitary-hypothalamic axis dysfunction-related clinical data and surgical outcomes. Adamantinomatous craniopharyngiomas were categorized into five topographic classes (12 patients, sellar-suprasellar; seven patients, pseudo-intraventricular; six patients, strict intraventricular; 14 patients, secondary intraventricular; one patient, not strict intraventricular). All cases exhibited a predominant (30 patients, 80%) or total (10 patients, 20%) cystic tumor component and displayed low nT2min percentage values compared to cerebrospinal fluid (42.3% [interquartile range 28.4-54.6%]). Significant associations between tumor topographic classes and pituitary dysfunction (P<0.001), andbetween peritumoral edema and hypothalamic dysfunction (P<0.001) were found. Considering extent of surgical removal and tumor relapse, volume of the cystic tumor component displayed a positive correlation (P=0.002; r=0.48; P=0.02; r=0.36), while nT2min intensity values exhibited a negative correlation (P=0.01; r= - 0.40; P=0.028; r= - 0.34). Severe hypothalamic-pituitary axis dysfunction is associated with tumors along the pituitary stalk and peritumoral edema. Tumor invasion of the third ventricle, tight adherence to the hypothalamus, larger volumes, and lower nT2min intensity of the tumor cystic component are independent predictors of extent ofadamantinomatous craniopharyngioma excision and recurrence.

Automatic Quantification of Normal Brain Gyrification Patterns and Changes in Fetuses with Polymicrogyria and Lissencephaly Based on MRI.

The current imaging assessment of fetal brain gyrification is performed qualitatively and subjectively using sonography and MR imaging. A few previous studies have suggested methods for quantification of fetal gyrification based on 3D reconstructed MR imaging, which requires unique data and is time-consuming. In this study, we aimed to develop an automatic pipeline for gyrification assessment based on routinely acquired fetal 2D MR imaging data, to quantify normal changes with gestation, and to measure differences in fetuses with lissencephaly and polymicrogyria compared with controls. We included coronal T2-weighted MR imaging data of 162 fetuses retrospectively collected from 2 clinical sites: 134 controls, 12 with lissencephaly, 13 with polymicrogyria, and 3 with suspected lissencephaly based on sonography, yet with normal MR imaging diagnoses. Following brain segmentation, 5 gyrification parameters were calculated separately for each hemisphere on the basis of the area and ratio between the contours of the cerebrum and its convex hull. Seven machine learning classifiers were evaluated to differentiate control fetuses and fetuses with lissencephaly or polymicrogyria. In control fetuses, all parameters changed significantly with gestational age (P < .05). Compared with controls, fetuses with lissencephaly showed significant reductions in all gyrification parameters (P ≤ .02). Similarly, significant reductions were detected for fetuses with polymicrogyria in several parameters (P ≤ .001). The 3 suspected fetuses showed normal gyrification values, supporting the MR imaging diagnosis. An XGBoost-linear algorithm achieved the best results for classification between fetuses with lissencephaly and control fetuses (n = 32), with an area under the curve of 0.90 and a recall of 0.83. Similarly, a random forest classifier showed the best performance for classification of fetuses with polymicrogyria and control fetuses (n = 33), with an area under the curve of 0.84 and a recall of 0.62. This study presents a pipeline for automatic quantification of fetal brain gyrification and provides normal developmental curves from a large cohort. Our method significantly differentiated fetuses with lissencephaly and polymicrogyria, demonstrating lower gyrification values. The method can aid radiologic assessment, highlight fetuses at risk, and may improve early identification of fetuses with cortical malformations.

Attenuation of gadolinium enhancement in pituitary gland on magnetic resonance imaging of patients with pediatric growth hormone deficiency

BackgroundAlthough it is generally thought that disturbance of perfusion in the anterior lobe of the pituitary gland leads to complete or partial hypopituitarism, the gadolinium (Gd) enhancement findings on Magnetic Resonance Imaging (MRI) of patients with growth hormone deficiency (GHD) remain unknown. The purpose of this study was to compare Gd enhancement of the pituitary gland on MRI of patients with GHD to that of healthy subjects.MethodsIn this retrospective study, we analyzed the data of 10 patients with clinically diagnosed GHD who underwent Gd-enhanced MRI of their pituitaries (age 8.3pm3.5 year, female 1, males 9), together with data of 5 patients with clinically normal growth hormone (GH) dynamics who also underwent Gd-enhanced pituitary MRI (age 6.2pm3.4 year, female 4, males 1). In each subject, a maximum-diameter region of interest (ROI) was drawn on the anterior pituitary gland of post Gd-enhanced coronal T1-weighted images, and the signal intensity ratio of the anterior pituitary gland to the white matter on the right temporal lobe of the same cross section was assessed.ResultsThe mean area of the ROI in the anterior pituitary gland and white matter of temporal lobe on the same cross section showed no significant differences between patients with GHD and those with normal GH (pituitary, 17.43 mm2pm8.24 vs. 21.08 mm2pm10.40, p = 1.00; white matter, 74.47mm2pm24.19 and 62.50 mm2pm17.90, p = 0.37), suggesting that the sizes of the pituitary glands were comparable. The ratios of Gd enhancement in the anterior pituitary gland showed significant differences between GHD and normal-GH subjects (pm0.716pm0.68pm0.26 vs.0.72pm0.16, p= 0.04).ConclusionsThese results suggested that the contrast effect on Gd-enhanced MRI is attenuated in the pituitary glands of patients with GHD compared to those with normal GH. These new clinical findings regarding Gd-enhanced MRI can assist the diagnosis of pediatric GHD.

Why Should Radiologists Evaluate MR Localizer Sequences?

This study aimed to assess the diagnostic accuracy of magnetic resonance (MR) localizer sequences in the detection of spinal incidental findings. MR localizer sequence findings from 384 patients were reviewed retrospectively. The images were evaluated by an experienced radiologist. T2-weighted diagnostic sagittal and coronal images included in the abdominal images were taken as references. Of the 384 patients, 170 were female and 214 were male. Pathology was detected in 63 of the patients. The findings were more common in male groups. These pathologies were spinal discopathy, metastases, hemangioma, angulation in the coccyx, and hemivertebra. Although often overlooked, MR localizer images enable diagnosing additional pathologies in the spine. These are unsuspected but can be critical for patient management, reducing patient morbidity and mortality.

Segmentation-Based Analysis of T2- and T1-Weighted Dynamic Magnetic Resonance Images Provides Adequate Observer Agreement in the Evaluation of Interstitial Lung Disease.

The aim of the study is to quantify observer agreement in the magnetic resonance imaging (MRI) classification of inflammatory or fibrotic interstitial lung disease (ILD). Our study is a preliminary analysis of a larger prospective cohort. The MRI images of 18 patients with ILD (13 females; mean age, 65 years) were acquired in a 1.5 T scanner and included axial fat-saturated T2-weighted (T2-WI, n = 18) and coronal fat-saturated T1-weighted images before and 1, 3, 5, and 10 minutes after gadolinium administration (n = 16). The MRI studies were evaluated with 2 different methods: a qualitative evaluation (visual assessment and measurement of few regions of interest; evaluations were performed independently by 5 radiologists and 3 times by 1 radiologist) and a segmentation-based analysis with software extraction of signal intensity values (evaluations were performed independently by 2 radiologists and twice by 1 radiologist). Interstitial lung disease was classified as inflammatory or fibrotic, based on previously described imaging criteria. Regarding the qualitative evaluation, intraobserver agreement was excellent (κ = 0.92, P < 0.05) for T2-WI and fair (κ = 0.29, P < 0.05) for T1 dynamic study, while interobserver agreement was moderate (κ = 0.56, P < 0.05) and poor (κ = 0.11, P = 0.18), respectively. In contrast, upon segmentation-based analysis, intraobserver and interobserver agreement were excellent for T2-WI (κ = 0.886, P < 0.001; κ = 1.00, P < 0.001; respectively); for T1-WI, intraobserver agreement was excellent (κ = 0.87, P < 0.05) and interobserver agreement was good (κ = 0.75, P < 0.05). Segmentation-based MRI analysis is more reproducible than a qualitative evaluation with visual assessment and measurement of few regions of interest.

Predicting visual recovery in pituitary adenoma patients post-endoscopic endonasal transsphenoidal surgery: Harnessing delta-radiomics of the optic chiasm from MRI

ObjectivesTo investigate whether morphological changes after surgery and delta-radiomics of the optic chiasm obtained from routine MRI could help predict postoperative visual recovery of pituitary adenoma patients.MethodsA total of 130 pituitary adenoma patients were retrospectively enrolled and divided into the recovery group (n = 87) and non-recovery group (n = 43) according to visual outcome 1 year after endoscopic endonasal transsphenoidal surgery. Morphological parameters of the optic chiasm were measured preoperatively and postoperatively, including chiasmal thickness, deformed angle, and suprasellar extension. Delta-radiomics of the optic chiasm were calculated based on features extracted from preoperative and postoperative coronal T2-weighted images, followed by machine learning modeling using least absolute shrinkage and selection operator wrapped with support vector machine through fivefold cross-validation in the development set. The delta-radiomic model was independently evaluated in the test set, and compared with the combined model that incorporated delta-radiomics, significant clinical and morphological parameters.ResultsPostoperative morphological changes of the optic chiasm could not significantly be used as predictors for the visual outcome. In contrast, the delta-radiomics model represented good performances in predicting visual recovery, with an AUC of 0.821 in the development set and 0.811 in the independent test set. Moreover, the combined model that incorporated age and delta-radiomics features of the optic chiasm achieved the highest AUC of 0.841 and 0.840 in the development set and independent test set, respectively.ConclusionsOur proposed machine learning models based on delta-radiomics of the optic chiasm can be used to predict postoperative visual recovery of pituitary adenoma patients.Clinical relevance statementOur delta-radiomics-based models from MRI enable accurate visual recovery predictions in pituitary adenoma patients who underwent endoscopic endonasal transsphenoidal surgery, facilitating better clinical decision-making and ultimately improving patient outcomes.Key Points• Prediction of the postoperative visual outcome for pituitary adenoma patients is important but challenging.• Delta-radiomics of the optic chiasm after surgical decompression represented better prognostic performances compared with its morphological changes.• The proposed machine learning models can serve as novel approaches to predict visual recovery for pituitary adenoma patients in clinical practice.

Comparison of vestibular schwannoma visualization between 0.55 T and 1.5 T MRI

ObjectivesVestibular schwannoma (VS) is the most common mass of the internal auditory canal (IAC) and is responsible for unilateral sensorineural hearing loss. Magnetic resonance imaging (MRI) at 1.5 T and 3 T is the standard of care for the evaluation of VS, and the feasibility of using modern low-field MRI for imaging of the IAC has not yet been elucidated. Hence, the purpose of this prospective study was to assess image quality and diagnostic performance of a modern 0.55 T MRI. Materials and MethodsFifty-six patients with known unilateral VS underwent routine MRI of the IAC at 1.5 T, followed immediately by 0.55 T MRI. Two radiologists independently evaluated the image quality, conspicuity of VS, diagnostic confidence, and image artifacts separately for isotropic T2-weighted SPACE images and for transversal and coronal T1-weighted fat-saturated contrast-enhanced images at 1.5 T and 0.55 T using 5-point Likert scales. In a second independent reading, both readers assessed lesion conspicuity and subjective diagnostic confidence in a direct comparison of 1.5 T and 0.55 T images. ResultsImage quality of transversal T1-weighted images (p = 0.13 and p = 0.16 for Reader 1 and Reader 2, respectively) and T2-weighted SPACE images (p = 0.39 and p = 0.58) were rated equally at 1.5 T and 0.55 T by both readers, whereas image quality of coronal T1-weighted images was superior at 1.5 T (p = 0.009 and p = 0.001). Analysis of the conspicuity of VS, diagnostic confidence, and image artifacts of all sequences revealed no significant differences between 1.5 T and 0.55 T. In the direct comparison of 1.5 T with 0.55 T images, there were no significant differences in lesion conspicuity or diagnostic confidence for any sequence (p = 0.60–0.73). ConclusionsModern low-field MRI at 0.55 T provided a sufficient diagnostic image quality and seems feasible for the evaluation of VS of the IAC.

Quantitative study of supraspinatus tendon injury grading based on synthetic magnetic resonance imaging

Objective: To investigate the diagnostic value of quantitative parameters of synthetic magnetic resonance imaging (SyMRI) in the grade of supraspinatus tendon injury. Methods: Ninety-seven patients with clinical definite of supraspinatus tendon injury from July 2021 to July 2022 in General Hospital of Ningxia Medical University were prospectively collected (case group), including 54 males and 43 females, with an age of 29 to 56 (37.4±9.6) years. According to the results of shoulder arthroscopy, the case group were divided into three subgroups included tendinopathy group (37 cases, grade Ⅱ), partial tear group (34 cases, grade Ⅲ) and complete tear group (26 cases, grade Ⅳ). During the same period, 28 normal rotator cuff volunteers without supraspinatus tendon injury were recruited (control group), including 16 males and 12 females, aged 23 to 49 (36.1±7.2) years, and marked as grade Ⅰ. All the subjects underwent MRI scan of articulatio humeri included T1-weighted imaging(T1WI) fast spin echo(FSE) sequences in axial view, T2-weighted imaging(T2WI) fat suppression(FS) sequences in axial view, T2WI FS sequences in oblique coronal view, proton density-weighted (PDW) imaging in oblique sagittal view and SyMRI in oblique coronal view. The supraspinatus tendon was divided into lateral, medial and middle subregions according to its shape in oblique coronal T2WI view, two radiologists measured the T1, T2 and PD values of the supraspinatus tendon. The interclass correlation coefficient (ICC) were used to compare the consistency between and within observers. One-way analysis of variance or Kruskal-Wallis H test were used to compare the differences of quantitative parameters in different grades, the multivariate logistic regression model was used to analyze the risk factors of supraspinatus tendon injury grade, and the receiver operating characteristic (ROC) curves and area under curve (AUC) was drawn and calculated to evaluate the diagnostic efficacy. The Spearman correlation was used to analyze the correlation between the quantitative values and grades of supraspinatus tendon injury. Results: The ICC values of T1, T2 and PD values for the three subregions of the supraspinatus tendon were greater than 0. 700. The differences of T1 values in the lateral subregion, T2 values in the lateral and middle subregions were statistically significant in the overall comparison across different grades (all P<0. 001).The differences of T1 values in the middle and medial subregions, T2 values in the medial subregion and PD values in the lateral, middle and medial subregions were not statistically significant in the overall comparison of different grades (all P>0. 05). Multiple logistic regression model analysis showed that T2 values in the lateral and middle subregions were related factors for the grade of supraspinatus tendon injury[ OR (95%CI):1.123 (1.037-1.216), 0.122 (1.151-1.197);all P<0.001 ]. The AUC of the T2 values in lateral subregion diagnosing grade Ⅰ vs grade Ⅳ, grade Ⅱ vs grade Ⅳ and grade Ⅲ vs grade Ⅳ were 0.891(95%CI: 0.801-0.981), 0.797(95%CI: 0.680-0.914), 0.723(95%CI: 0.594-0.853) (all P<0.001), and the AUC of the T2 values in middle subregion diagnosing grade Ⅰ vs Ⅳ, grade Ⅱ vs Ⅳ, grade Ⅱ vs Ⅲ, and grade Ⅰ vs Ⅲ were 0.946 (95%CI: 0.849-0.989), 0.886 (95%CI: 0.809-0.962), 0.746 (95%CI: 0.631-0.861), 0.843 (95%CI: 0.745-0.941)(all P<0.001). The T2 values in the lateral and middle subregions were positively correlated with the grade of supraspinatus tendon injury (r=0.542, 0.615; both P<0.001), while T1 values and T2 values in the medial subregions were not significantly correlated with the grade of supraspinatus tendon injury (both P>0.05). Conclusion: SyMRI has high clinical application value in the grading of supraspinatus tendon injury, especially T2 value can be used as an effective quantitative parameter for the grading of supraspinatus tendon injury.

MRI and Trouillas' grading system of pituitary tumors: the usefulness of T2 signal intensity volumetric values.

To classify pituitary macroadenomas according to the Trouillas' grading system; to compare this grading system with T2 values of volumetric signal intensity to determine T2 values able to predict the final grade. A total of 106 patients with macroadenomas were grouped according to the grading system score combining proliferation and invasiveness criteria of Trouillas' classification. Normalized volumetric signal intensity values were extracted from coronal T2-weighted images (nT2mean, nT2Max, nT2min) and were compared with the final grading score system. Thirty-three patients were in grade 1a (non-invasive, non-proliferative tumors), 17 patients in grade 1b (non-invasive, proliferative tumors), 36 patients in grade 2a (invasive, non-proliferative tumors), and 20 patients in grade 2b (invasive, proliferative tumors). No patient was in grade 3 (metastatic tumors). nT2Max and nT2min were the best quantitative values to discriminate invasive from non-invasive grades; in invasive grades, nT2Max intensity values were higher, and nT2min intensity values were lower than in non-invasive grades. Receiver operating characteristic analysis of nT2 values showed that nT2min values had a better diagnostic performance than nT2Max values because they allowed differentiating with a moderate accuracy invasive tumors (2a or 2b grades) from both non-invasive proliferative tumors (1b) and non-invasive-non proliferative tumors (1a) (2a vs 1b: AUCnT2min = 0.78, 2b vs 1b: AUCnT2min = 0.72, 2a vs 1a: AUCnT2min = 0.72, 2b vs 1a AUCnT2min = 0.69). Volumetric nT2Max and nT2min values of MRI might be practical and non-invasive markers for assessing tumor invasiveness although nT2 min signal intensity values have more effects in discriminating tumor's invasive behavior.

Rapidly Resolving Orbital Pseudotumor in Systemic Lupus Erythematosus

Rapidly Resolving Orbital Pseudotumor in Systemic Lupus Erythematosus

Abstract 5374: Why only focus on the tumor?: The crucial role of the extra-tumor environment to predict poor responders for locally advanced rectal cancer

Abstract Introduction As total neoadjuvant therapy for locally advanced rectal cancer (LARC) emerged, the possibility of skipping radiotherapy for poorly responsive patients arose. Machine-learning algorithms have focused on the radiopathologic features of tumor segmentation in order to predict responsiveness to radiotherapy. However, in addition to the tumor itself, there are several factors related to responsiveness, such as vasculature affecting hypoxia or MRI-detected extramural vascular invasion status. We aimed to predict poor responders using pretreatment rectal MRI images without segmentation and to identify which factors mainly contribute to the prediction algorithm. Methods Between Jan 1, 2000, and Dec 30, 2020, 689 consecutive patients were retrospectively included in two hospitals. Poor responders were defined by tumor regression grades (TRG) 2 and 3 that were determined through surgical resection. The ResNet-50 model was trained to predict poor responders from pretreatment rectal MRIs (T2-weighted axial, sagittal, and coronal images). We adopted a tenfold cross-validation for training and testing the model and used Gradient-weighted Class Activation Mapping (Grad-CAM) to highlight the important regions in the MRI scans that help predict poor responders. Results The number in each group of TRG was 108 (15.7%), 250 (36.3%), 265 (38.5%), and 66 (9.6%) for TRG0, TRG1, TRG2, and TRG3, respectively. There were 618 patients in the training cohort and 71 patients in the validation cohort. In the training and validation cohort, the accuracy for the prediction of poor responders was 85.6% (area under the curve (AUC) 0.856 [95% CI 0.761-0.950]) and 70.2% (AUC 0.703 [0.682-0.724]), although without segmentation. Our prediction model achieved a sensitivity of 0.724 (95% CI 0.700-0.748), a specificity of 0.684 (0.658-0.710), a positive predictive value of 0.697 (0.656-0.737), and a negative predictive value of 0.708 (0.666-0.751) in the validation cohort. Grad-CAM showed that the most important part of the accurately predicted images to contribute to the prediction was not the tumor (7/355, 1.9%) but the pelvic vasculature (353/355, 99.4%), including iliac vessels, femoral vessels, and presacral plexus, and followed by the mesorectum (38/355, 10.7%). Conclusion The pelvic vasculature contributes more to predicting poor responders to radiotherapy than the tumor itself. Therefore, when creating a prediction model for responsiveness to radiotherapy in LARC, this should be considered. Citation Format: Rumi Shin, Byunho Jo, Inyeop Jang, Cheong-Il Shin, Jin Sun Choi, Seung-Yong Jeong, Seung Chul Heo, Ji Won Park, Min Jung Kim, Tae Hyun Hwang. Why only focus on the tumor?: The crucial role of the extra-tumor environment to predict poor responders for locally advanced rectal cancer. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5374.

Application of quantitative T1, T2 and T2* mapping magnetic resonance imaging in cartilage degeneration of the shoulder joint

To investigate and compare the values of 3.0 T MRI T1, T2 and T2* mapping quantification techniques in evaluating cartilage degeneration of the shoulder joint. This study included 123 shoulder joints of 119 patients, which were scanned in 3.0 T MRI with axial Fat Suppression Proton Density Weighted Image (FS-PDWI), sagittal fat suppression T2 Weighted Image (FS-T2WI), coronal T1Weighted Image (T1WI), FS-PDWI, cartilage-specific T1, T2 and T2* mapping sequences. Basing on MRI images, the shoulder cartilage was classified into grades 0 1, 2, 3 and 4 according to the International Cartilage Regeneration & Joint Preservation Society (ICRS). The grading of shoulder cartilage was based on MRI images with ICRS as reference, and did not involve arthroscopy or histology.The T1, T2 and T2* relaxation values in the superior, middle and inferior bands of shoulder articular cartilage were measured at all grades, and the differences in various indicators between groups were analyzed and compared using a single-factor ANOVA test. The correlation between T1, T2 and T2* relaxation values and MRI-based grading was analyzed by SPSS software. There were 46 shoulder joints with MRI-based grade 0 in healthy control group (n = 46), while 49 and 28 shoulder joints with grade 1–2 (mild degeneration subgroup) and grade 3–4 (severe degeneration subgroup) in patient group (n = 73), accounting for 63.6% and 36.4%, respectively. The T1, T2 and T2* relaxation values of the superior, middle and inferior bands of shoulder articular cartilage were significantly and positively correlated with the MRI-based grading (P < 0.01). MRI-basedgrading of shoulder cartilage was markedly associated with age (r = 0.766, P < 0.01). With the aggravation of cartilage degeneration, T1, T2 and T2* relaxation values showed an upward trend (all P < 0.01), and T1, T2 and T2* mapping could distinguish cartilage degeneration at all levels (all P < 0.01). The T1, T2 and T2* relaxation values were significantly different between normal group and mild degeneration subgroup, normal group and severe degeneration subgroup, mild degeneration subgroup and severe degeneration subgroup (all P < 0.05). Quantitative T1, T2 and T2* mapping can quantify the degree of shoulder cartilage degeneration. All these MRI mapping quantification techniques can be used as critical supplementary sequences to assess shoulder cartilage degeneration, among which T2 mapping has the highest value.

The association between paraspinal muscle degeneration and osteoporotic vertebral compression fracture severity in postmenopausal women.

According to reports in the literature, osteoporotic vertebral compression fracture (OVCF) is associated with paraspinal muscle degeneration; however, the association between the severity of OVCF and paraspinal muscle degeneration is not clear. The purpose of this study was to investigate the association between paraspinal muscle degeneration and OVCF severity in postmenopausal women. Three hundred and seventy-six MRI images from 47 patients were collected and analyzed. Sagittal and axial coronal T2-weighted images were used to measure the fractured vertebra sagittal cross-sectional area (FSCSA), the adjacent normal vertebral body sagittal cross-sectional area (NSCSA), paraspinal muscle cross-sectional area (CSA), and the fat cross-sectional area (FCSA). The ratio of fractured vertebra compressed sagittal cross-sectional area (RCSA) and fatty infiltration ratio (FIR) was subsequently calculated. The formulas for RCSA and FIR calculations are as follows: RCSA = (NSCSA-FSCSA)/NSCSA; FIR = FCSA/CSA. RCSA and FIR represent the severity of OVCF and paraspinal muscle degeneration, respectively. The correlation between paraspinal muscle degeneration and OVCF severity was analyzed using the Pearson correlation, and multiple regression analysis was performed to explore related risk factors. OVCF severity was closely associated with paraspinal muscle degeneration (L3/4 FIR r= 0.704, P< 0.05; L4/5 FIR r= 0.578, P< 0.05; L5/S1 FIR r= 0.581, P< 0.05). Multiple regression analysis demonstrated that the risk factor for OVCF severity was L3/4 FIR (β= 0.421, P= 0.033). OVCF severity was associated with the FIR of paraspinal muscles, and L3/4 FIR was a predictive factor for OVCF severity in postmenopausal women.

Carotid Artery Thrombus in Antiphospholipid Antibody Syndrome.

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

Characterization of motion dependent magnetic field inhomogeneity for DWI in the kidneys

PurposeDiffusion-weighted imaging (DWI) of the abdomen has increased dramatically for both research and clinical purposes. Motion and static field inhomogeneity related challenges limit image quality of abdominopelvic imaging with the most conventional echo-planar imaging (EPI) pulse sequence. While reversed phase encoded imaging is increasingly used to facilitate distortion correction, it typically assumes one motion independent magnetic field distribution. In this study, we describe a more generalized workflow for the case of kidney DWI in which the field inhomogeneity at multiple respiratory phases is mapped and used to correct all images in a multi-contrast DWI series. MethodsIn this HIPAA-compliant and IRB-approved prospective study, 8 volunteers (6 M, ages 28–51) had abdominal imaging performed in a 3 T MRI system (MAGNETOM Prisma; Siemens Healthcare, Erlangen, Germany) with ECG gating. Coronal oblique T2-weighted HASTE images were collected for anatomical reference. Sagittal phase-contrast (PC) MRI images through the left renal artery were collected to determine systolic and diastolic phases. Cardiac triggered oblique coronal DWI were collected at 10 b-values between 0 and 800 s/mm2 and 12 directions. DWI series were distortion corrected using field maps generated by forward and reversed phase encoded b = 0 images collected over the full respiratory cycle and matched by respiratory phase. Morphologic accuracy, intraseries spatial variability, and diffusion tensor imaging (DTI) metrics mean diffusivity (MD) and fractional anisotropy (FA) were compared for results generated with no distortion correction, correction with only one respiratory bin, and correction with multiple respiratory bins across the breathing cycle. ResultsComputed field maps showed significant variation in static field with kidney laterality, region, and respiratory phase. Distortion corrected images showed significantly better registration to morphologic images than uncorrected images; for the left kidney, the multiple bin correction outperformed one bin correction. Line profile analysis showed significantly reduced spatial variation with multiple bins than one bin correction. DTI metrics were mostly similar between correction methods, with some differences observed in MD between uncorrected and corrected datasets. ConclusionsOur results indicate improved morphology of kidney DWI and derived parametric maps as well as reduced variability over the full image series using the motion-resolved distortion correction. This work highlights some morphologic and quantitative metric improvements can be obtained for kidney DWI when distortion correction is performed in a respiratory-resolved manner.

Shoulder MRI-based radiomics for diagnosis and severity staging assessment of surgically treated supraspinatus tendon tears.

To develop and validate MRI-based radiomics models capable of evaluating supraspinatus tendon tears within the shoulder joints by using arthroscopy as the reference standard. A total of 432 patients (332 in the training set and 100 in the external validation set) with intact supraspinatus tendon (n = 202) and supraspinatus tendon tear (n = 230, 130 full-thickness tears and 100 partial-thickness tears) were enrolled. Radiomics features were extracted from fat-saturated T2-weighted coronal images. Two radiomics signature models for detecting supraspinatus tendon abnormalities (tear or not), and stage lesion severity (full- or partial-thickness tear) and radiomics scores (Rad-score), were constructed and calculated using multivariate logistic regression analysis. The diagnostic performance of the two models was validated using ROC curves on the training and validation datasets. For the radiomics model of no tears or tears, thirteen features from MR images were used to build the radiomics signature with an AUC value of 0.98 in the training set, 0.97 in the internal validation set, and 0.98 in the external validation set. For the radiomics model of full- or partial-thickness tears, thirteen features from MR images were used to build the radiomics signature with an AUC value of 0.79 in the training set, 0.69 in the internal validation set, and 0.77 in the external validation set. The proposed radiomics models in this study can accurately rule out supraspinatus tendon tears and are capable of assessing the severity staging of tears with moderate accuracy based on shoulder MR images. • The radiomics model of no tears or tears achieved a high overall accuracy of 93.6%, sensitivity of 91.6%, and specificity of 95.2% for supraspinatus tendon tears. • The radiomics model of full- or partial-thickness tears displayed moderate performance with an accuracy of 76.4%, a sensitivity of 79.2%, and a specificity of 74.3% for supraspinatus tendon tears severity staging.

Deep learning for the ovarian lesion localization and discrimination between borderline and malignant ovarian tumors based on routine MR imaging

To establish a deep learning (DL) model in differentiating borderline ovarian tumor (BOT) from epithelial ovarian cancer (EOC) on conventional MR imaging. We retrospectively enrolled 201 patients of 102 pathologically proven BOTs and 99 EOCs at OB/GYN hospital Fudan University, between January 2015 and December 2017. All imaging data were reviewed on picture archiving and communication systems (PACS) server. Both T1-weighted imaging (T1WI) and T2-weighted imaging (T2WI) MR images were used for lesion area determination. We trained a U-net++ model with deep supervision to segment the lesion area on MR images. Then, the segmented regions were fed into a classification model based on DL network to categorize ovarian masses automatically. For ovarian lesion segmentation, the mean dice similarity coefficient (DSC) of the trained U-net++ model in the testing dataset achieved 0.73 pm 0.25, 0.76 pm 0.18, and 0.60 pm 0.24 in the sagittal T2WI, coronal T2WI, and axial T1WI images, respectively. The DL model by combined T2WI computerized network could differentiate BOT from EOC with a significantly higher AUC of 0.87, an accuracy of 83.7%, a sensitivity of 75.0% and a specificity of 87.5%. In comparison, the AUC yielded by radiologist was only 0.75, with an accuracy of 75.5%, a sensitivity of 96.0% and specificity of 54.2% (P < 0.001).The trained DL network model derived from routine MR imaging could help to distinguish BOT from EOC with a high accuracy, which was superior to radiologists’ assessment.

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.