Postcontrast Images Research Articles

Frequency of Anterior Inferior Cerebellar Artery Vascular Loops Using CISS Sequence on 3.0T MRI in the Otologic Symptomized Patients

Aim: To estimate the frequency of vascular loops in the anterior inferior cerebellar artery in the otologic symptomized patients using CISS sequence on 3.0 Tesla MRI” in Pakistani populations. Methodology: Cross sectional descriptive study was conducted in Armed Forces Institute of Radiology and Imaging, Military Hospital Rawalpindi from 12th April 2019 to 11th October 2019. One hundred patients of both genders between age of 20-60 years were presented with otologic symptoms i.e. tinnitus, dizziness and hearing loss (unilateral/bilateral) and advised MRI brain. Patients with any diagnosed arterial, venous and arterio-venous cause of otologic symptoms, severe claustrophobia and with internal cardiac pacemakers or any other metallic foreign body were excluded. Patients were undergone MRI brain on 3.0 Tesla. TIWS, T2WS and CISS sequences were taken along with post-contrast T1WS images. Results: There was 20 to 60 years of patients range of age having mean age of 38.38±12.05 years and majority of patients 65% between 20-40 years. There were 53(53%) males and 47(47%) females and having 1.2:1 ratio of male to female. Frequency of anterior inferior cerebellar artery vascular loops in the otologic symptomized patients using CISS sequence on 3.0 Tesla MRI was seen in 59(59%) patients. Conclusion: The frequency of anterior inferior cerebellar artery vascular loops in the otologic symptomized patients using CISS sequence on 3.0 Tesla MRI is very high. Keywords: Anterior inferior cerebellar artery vascular loops, Magnetic resonance imaging, Otologic symptoms

Patellar Tendon-Lateral Femoral Condyle Friction Syndrome: About 5 Cases

Objective: The objective is to illustrate the MR imaging findings occurring in the posterior inferolateral patellar tendon and the lateral femoral condyle in patients experiencing chronic anterior and/or lateral knee pain. Material and methods: A retrospective review of the MR images in (patients who presented with chronic anterior or lateral knee pain. In all patients, postcontrast images were available. Results: Sagittal and axial imaging planes best demonstrated the patellar tendon and its relationship with the lateral femoral condyle. In all the patients, there was obliteration of the fat planes and abnormal signal intensity in the lateral soft tissues of the inferior patellofemoral joint. Enhancement after administration of gadolinium was noted in all cases in which contrast was administered. One patient showed cystic changes in the soft tissues adjacent to the lateral femoral condyle in addition to fat plane obliteration. Abnormal patellar alignment was noted in one patient. Patellar tendon pathology was seen in one patient. Conclusion: When assessing anterior knee symptoms, MR imaging facilitates the identification of changes associated with patellar tendon-lateral femoral condyle friction syndrome, which should be differentiated from other causes of anterior or lateral knee pain.

Longitudinal enlargement of choroid plexus is associated with chronic lesion expansion and neurodegeneration in RRMS patients

Background and Objective: We explored dynamic changes in the choroid plexus (CP) in patients with relapsing-remitting multiple sclerosis (RRMS) and assessed its relationship with chronic lesion expansion and atrophy in various brain compartments. Methods: Fifty-seven RRMS patients were annually assessed for a minimum of 48 months with 3D FLAIR, pre- and post-contrast 3D T1 and diffusion-weighted magnetic resonance imaging (MRI). The CP was manually segmented at baseline and last follow-up. Results: The volume of CP significantly increased by 1.4% annually. However, the extent of CP enlargement varied considerably among individuals (ranging from −3.6 to 150.8 mm3 or −0.2% to 6.3%). The magnitude of CP enlargement significantly correlated with central (r = 0.70, p < 0.001) and total brain atrophy (r = −0.57, p < 0.001), white (r = −0.61, p < 0.001) and deep grey matter atrophy (r = −0.60, p < 0.001). Progressive CP enlargement was significantly associated with the volume and extent of chronic lesion expansion (r = 0.60, p < 0.001), but not with the number or volume of new lesions. Conclusion: This study provides evidence of progressive CP enlargement in patients with RRMS. Our findings also demonstrate that enlargement of the CP volume is linked to the expansion of chronic lesions and neurodegeneration of periventricular white and grey matter in RRMS patients.

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 .

Brain Tumor Imaging without Gadolinium-based Contrast Agents: Feasible or Fantasy?

Gadolinium-based contrast agents (GBCAs) form the cornerstone of current primary brain tumor MRI protocols at all stages of the patient journey. Though an imperfect measure of tumor grade, GBCAs are repeatedly used for diagnosis and monitoring. In practice, however, radiologists will encounter situations where GBCA injection is not needed or of doubtful benefit. Reducing GBCA administration could improve the patient burden of (repeated) imaging (especially in vulnerable patient groups, such as children), minimize risks of putative side effects, and benefit costs, logistics, and the environmental footprint. On the basis of the current literature, imaging strategies to reduce GBCA exposure for pediatric and adult patients with primary brain tumors will be reviewed. Early postoperative MRI and fixed-interval imaging of gliomas are examples of GBCA exposure with uncertain survival benefits. Half-dose GBCAs for gliomas and T2-weighted imaging alone for meningiomas are among options to reduce GBCA use. While most imaging guidelines recommend using GBCAs at all stages of diagnosis and treatment, non-contrast-enhanced sequences, such as the arterial spin labeling, have shown a great potential. Artificial intelligence methods to generate synthetic postcontrast images from decreased-dose or non-GBCA scans have shown promise to replace GBCA-dependent approaches. This review is focused on pediatric and adult gliomas and meningiomas. Special attention is paid to the quality and real-life applicability of the reviewed literature.

MR IMAGING AND EVALUATION OF THE PITUITARY STALK: SIZE, SHAPE, AND ENHANCEMENT PATTERN

Background: Knowing the normal imaging appearance of the pituitary stalk is essential for diagnosing pituitary infundibular lesions and a more accurate assessment of the stalk. Objective: We aimed to evaluate the normal pituitary stalk using high-resolution magnetic resonance imaging(MRI) at 1.5T. Materials and Methods: All images were obtained with a 1.5 T MR scanner using a dedicated pituitary MRI protocol. A total of 50 patients, with a gender distribution of 32 men and 18 women, were included in the study. Their ages ranged from 18 to 70 years, averaging 43 years. The diameter and length of the pituitary stalk were measured. The signal intensity and enhancement of the stalk were visually evaluated on pre- and post-contrast T1-weighted images. Results: The average anterior-posterior (AP) and transverse diameters of the pituitary stalk at the optic chiasm level were 3.19 ± 0.48 mm and 3.25 ± 0.46 mm, respectively. The average AP and transverse diameters of the pituitary stalk at the pituitary gland insertion were 1.93 ± 0.38 mm and 1.95 ± 0.40 mm, respectively. The length of the pituitary stalk was 6.35 ± 1.63 mm. Compared to the optic chiasm and neurohypophysis,the stalk demonstrated hypointensity on unenhancedMR images. The enhancement of the pituitary stalk is observed in all cases. Conclusions: The study pinpointed key MRI criteria for evaluating the normal pituitary stalks size, shape, and how it takes up contrast dye. These details act as a roadmap for spotting and understanding pituitary gland issues.

Magnetic resonance imaging subtraction vs. pre- and post-contrast 3D gradient recalled echo fat suppressed imaging for evaluation of the canine and feline brain.

Subtraction magnetic resonance imaging (MRI) has been reported to increase accuracy in the diagnosis of meningeal and inflammatory brain diseases in small animals. 3D T1W gradient recalled echo (GRE) techniques have been proposed as a suitable alternative to conventional spin echo sequences in imaging the canine brain. The aim of this study was to compare subtraction images and paired pre- and post-contrast 3D T1W GRE fat suppressed (FS) images in canine and feline MRI studies using clinical diagnosis as the gold standard. Paired pre- and post-contrast T1W 3D FS GRE images and individual subtraction images of 100 small animal patients were randomized and independently evaluated by 2 blinded observers. Diagnosis categories were "normal," "inflammatory," "neoplastic," and "other." Clinical diagnosis was made in the same categories and served as the gold standard. Image interpretation results were compared to the clinical diagnosis. Interobserver agreement was determined. Clinically, 41 studies were categorized as "normal," 18 as "inflammatory," 28 as "neoplastic," and 13 as "other." The agreement of the pre- and post-contrast GRE images with the gold standard was significantly higher than that of the subtraction images (k = 0.7491 vs. k = 0.5924; p = 0.0075). The largest sources of error were misinterpretation of "other" as "normal" and "normal" as "inflammatory." There was no significant difference between the two observers (p = 0.8820). Based on this study, subtraction images do not provide an advantage to paired pre- and post-contrast FS GRE images when evaluating the canine and feline brain.

Can Short Tau Inversion Recovery (STIR) Imaging Be Used as a Stand-Alone Sequence To Assess a Perianal Fistulous Tract on MRI? A Retrospective Cohort Study Comparing STIR and T1-Post Contrast Imaging.

Perianal fistulas demand precise preoperative assessment for optimal surgical outcomes. MRI, using Short Tau Inversion Recovery (STIR) and T1-post contrast sequences, plays a crucial role in this evaluation.This retrospective cohort study compared STIR imaging's diagnostic efficacy with T1-post contrast sequences in identifying perianal fistulous tracts. The study investigated whether STIR imaging could serve as the sole diagnostic sequence, simplifying clinical practice. In a tertiary care hospital, 100 patients underwent pelvic MRI for suspected perianal fistulas. Radiologists independently evaluated STIR and T1-post contrast sequences for internal openings, tract extent, distinction, abscess presence, and tract type. Sensitivity, specificity, area under the curve (AUC), and Cohen's kappa analysis were used for diagnostic assessment. STIR imaging showed notable sensitivity (79.8-97.9%) and specificity (100%) for identifying internal openings and tracts. Combined with T1-post contrast, diagnostic accuracy improved significantly, with near-perfect AUC values. Kappa values indicated moderate to substantial agreement between radiological assessments and clinical diagnosis. The combined sequences achieved 100% sensitivity and specificity for tract visualization. STIR imaging presents promise as a singular diagnostic tool for perianal fistulas, especially when combined with T1-post contrast sequences. While offering potential clinical diagnosis simplifications, further studies are warranted to validate its utility and ensure comprehensive diagnostic accuracy.

Prevalence of Scarpa's ganglion enhancement on high-resolution MRI imaging.

The vestibular ganglion, or Scarpa's ganglion, is a cluster of afferent vestibular neurons within the internal auditory canal (IAC). There is minimal literature describing enhancement of this region on magnetic resonance imaging (MRI) and its correlation to clinical symptoms. Here, we sought to find the prevalence of enhancement at Scarpa's ganglion, and determine whether such enhancement correlates with demographics or clinical symptoms. A retrospective review was performed of consecutive patients with an MRI of the IAC between 3/1/2021 and 5/20/2021. Two neuroradiologists independently reviewed for T1 and FLAIR enhancement of the Scarpa's ganglion on post-contrast fat-saturated T1 and post-contrast FLAIR images. Discrepancies were agreed upon by consensus. Clinical variables (hearing loss, vestibular symptoms, tinnitus, and MRI indication) were gathered from a retrospective chart review. Eighty-nine patients were included (51 female); the mean age was 58 (range 19-85). The most common MRI indication was hearing loss (n = 53). FLAIR enhancement was present on the right in 7 patients, on the left in 7 patients, and bilaterally in 6 patients. No enhancement was seen on post-contrast T1 images. There was no statistically significant correlation between consensus FLAIR on at least one side and age (p = .74), gender (p = .29), hearing loss (p = .32), hearing loss side (p = .39), type of hearing loss (p = .87), vestibular symptoms (p = .71), or tinnitus (p = .81). Enhancement is present in the minority of patients on post-contrast FLAIR images. If seen, it should be considered an uncommon but not unexpected finding with no clinical significance.

Tumefactive demyelinating lesions: a retrospective cohort study in Thailand

Tumefactive demyelinating lesions (TDL), characterized by large (≥ 2 cm) demyelinating lesions mimicking tumors, are a rare manifestation of the central nervous system inflammatory demyelinating diseases (CNS-IDD). Distinguishing TDL from other brain lesions can be challenging, often necessitating biopsy or advanced diagnostics. The natural history of TDL varies among races. This study aimed to assess demographics, clinical and radiological features, laboratory findings, management, and outcomes of Thai patients with TDL. We retrospectively reviewed records of twenty-six patients with TDL from the Multiple Sclerosis and Related Disorders registry from two tertiary medical centers. Among 1102 CNS-IDD patients, 26 (2.4%) had TDL. The median age at TDLs onset was 34.5 years (range 17–75); 69.2% were female. Over 70% manifested TDL as their initial CNS-IDD presentation. Common presenting symptoms included motor deficits, sensory disturbances, and cognitive problems. About two-fifths exhibited multiple lesions, most frequently in the frontoparietal region (46.2%). Half of the patients showed an incomplete ring on post-contrast T1-weighted imaging, with peripheral diffusion-weighted imaging restriction in twenty-one patients. T2-hypointense rims were present in thirteen (56.5%) patients. Brain biopsy was performed in 12 cases (46.1%). Serum aquaporin-4 immunoglobulin was positive in 16.7% of tested (4/24) cases. Serum myelin oligodendrocyte glycoprotein immunoglobulin was negative in all thirteen patients tested. Twenty patients (76.9%) received intravenous corticosteroids for TDL attacks. After the median follow-up period of 48 months (range 6–300), 23.1% experienced CNS-IDD relapses. Median Expanded Disability Status Scale at TDL diagnosis was 4.3 (range 0.0–9.5), and improved to 3.0 (range 0.0–10.0) at the last follow-up. This study suggested that TDL were rare among Thai CNS-IDD patients, frequently presenting as a monophasic condition with a favorable outcome.

Predictive Performance of Radiomic Features Extracted from Breast MR Imaging in Postoperative Upgrading of Ductal Carcinoma in Situ to Invasive Carcinoma.

To investigate the predictive performance of radiomic features extracted from breast MRI for upgrade of ductal carcinoma in situ (DCIS) to invasive carcinoma. This retrospective study included 71 women with DCIS lesions diagnosed preoperatively by biopsy. All women underwent breast dynamic contrast-enhanced (DCE) MRI of the breast, which included pre-contrast and five post-contrast phases continuously with a time resolution of 60s. Lesion segmentation was performed manually, and 144 radiomic features of the lesions were extracted from T2-weighted images (T2WI), pre-contrast T1-weighted images (T1WI), and post-contrast 1st, 2nd, and 5th phase subtraction images on DCE-MRI. Qualitative features of mammography, ultrasound, and MRI were also assessed. Clinicopathological features were evaluated using medical records. The least absolute shrinkage and selection operator (LASSO) algorithm was applied for features selection and model building. The predictive performance of postoperative upgrade to invasive carcinoma was assessed using the area under the receiver operating characteristic curve. Surgical specimens revealed 13 lesions (18.3%) that were upgraded to invasive carcinoma. Among clinicopathological and qualitative features, age was the only significant predictive variable. No significant radiomic features were observed on T2WI and post-contrast 2nd phase subtraction images on DCE-MRI. The area under the curves (AUCs) of the LASSO radiomics model integrated with age were 0.915 for pre-contrast T1WI, 0.862 for post-contrast 1st phase subtraction images, and 0.833 for post-contrast 5th phase subtraction images. The AUCs of the 200-times bootstrap internal validations were 0.885, 0.832, and 0.775. A radiomics approach using breast MRI may be a promising method for predicting the postoperative upgrade of DCIS. The present study showed that the radiomic features extracted from pre-contrast T1WI and post-contrast subtraction images in the very early phase of DCE-MRI were more predictable.

Enlarged Perivascular Space and Index for Diffusivity Along the Perivascular Space as Emerging Neuroimaging Biomarkers of Neurological Diseases.

The existence of lymphatic vessels or similar clearance systems in the central nervous system (CNS) that transport nutrients and remove cellular waste is a neuroscientific question of great significance. As the brain is the most metabolically active organ in the body, there is likely to be a potential correlation between its clearance system and the pathological state of the CNS. Until recently the successive discoveries of the glymphatic system and the meningeal lymphatics solved this puzzle. This article reviews the basic anatomy and physiology of the glymphatic system. Imaging techniques to visualize the function of the glymphatic system mainly including post-contrast imaging techniques, indirect lymphatic assessment by detecting increased perivascular space, and diffusion tensor image analysis along the perivascular space (DTI-ALPS) are discussed. The pathological link between glymphatic system dysfunction and neurological disorders is the key point, focusing on the enlarged perivascular space (EPVS) and the index of diffusivity along the perivascular space (ALPS index), which may represent the activity of the glymphatic system as possible clinical neuroimagingbiomarkers of neurological disorders. The pathological link between glymphatic system dysfunction and neurological disorders is the key point, focusing on the enlarged perivascular space (EPVS) and the index for of diffusivity along the perivascular space (ALPS index), which may represent the activity of the glymphatic system as possible clinical neuroimaging biomarkers of neurological disorders.

Prediction of locally advanced rectal cancer response to neoadjuvant chemoradiation therapy using volumetric multiparametric MRI-based radiomics.

To assess the role of pretreatment multiparametric (mp)MRI-based radiomic features in predicting pathologic complete response (pCR) of locally advanced rectal cancer (LARC) to neoadjuvant chemoradiation therapy (nCRT). This was a retrospective dual-center study including 98 patients (M/F 77/21, mean age 60years) with LARC who underwent pretreatment mpMRI followed by nCRT and total mesorectal excision or watch and wait. Fifty-eight patients from institution 1 constituted the training set and 40 from institution 2 the validation set. Manual segmentation using volumes of interest was performed on T1WI pre-/post-contrast, T2WI and diffusion-weighted imaging (DWI) sequences. Demographic information and serum carcinoembryonic antigen (CEA) levels were collected. Shape, 1st and 2nd order radiomic features were extracted and entered in models based on principal component analysis used to predict pCR. The best model was obtained using a k-fold cross-validation method on the training set, and AUC, sensitivity and specificity for prediction of pCR were calculated on the validation set. Stage distribution was T3 (n = 79) or T4 (n = 19). Overall, 16 (16.3%) patients achieved pCR. Demographics, MRI TNM stage, and CEA were not predictive of pCR (p range 0.59-0.96), while several radiomic models achieved high diagnostic performance for prediction of pCR (in the validation set), with AUCs ranging from 0.7 to 0.9, with the best model based on high b-value DWI demonstrating AUC of 0.9 [95% confidence intervals: 0.67, 1], sensitivity of 100% [100%, 100%], and specificity of 81% [66%, 96%]. Radiomic models obtained from pre-treatment MRI show good to excellent performance for the prediction of pCR in patients with LARC, superior to clinical parameters and CEA. A larger study is needed for confirmation of these results.

A semi-automatic segmentation method for meningioma developed using a variational approach model.

Meningioma is the commonest primary brain tumour. Volumetric post-contrast magnetic resonance imaging (MRI) is recognised as gold standard for delineation of meningioma volume but is hindered by manual processing times. We aimed to investigate the utility of a model-based variational approach in segmenting meningioma. A database of patients with a meningioma (2007-2015) was queried for patients with a contrast-enhanced volumetric MRI, who had consented to a research tissue biobank. Manual segmentation by a neuroradiologist was performed and results were compared to the mathematical model, using a battery of tests including the Sørensen-Dice coefficient (DICE) and JACCARD index. A publicly available meningioma dataset (708 segmented T1 contrast-enhanced slices) was also used to test the reliability of the model. 49 meningioma cases were included. The most common meningioma location was convexity (n = 15, 30.6%). The mathematical model segmented all but one incidental meningioma, which failed due to the lack of contrast uptake. The median meningioma volume by manual segmentation was 19.0cm3 (IQR 4.9-31.2). The median meningioma volume using the mathematical model was 16.9cm3 (IQR 4.6-28.34). The mean DICE score was 0.90 (SD = 0.04). The mean JACCARD index was 0.82 (SD = 0.07). For the publicly available dataset, the mean DICE and JACCARD scores were 0.90 (SD = 0.06) and 0.82 (SD = 0.10), respectively. Segmentation of meningioma volume using the proposed mathematical model was possible with accurate results. Application of this model on contrast-enhanced volumetric imaging may help reduce work burden on neuroradiologists with the increasing number in meningioma diagnoses.

Radiomics analysis for the prediction of locoregional recurrence of locally advanced oropharyngeal cancer and hypopharyngeal cancer.

By radiomic analysis of the postcontrast CT images, this study aimed to predict locoregional recurrence (LR) of locally advanced oropharyngeal cancer (OPC) and hypopharyngeal cancer (HPC). A total of 192 patients with stage III-IV OPC or HPC from two independent cohort were randomly split into a training cohort with 153 cases and a testing cohort with 39 cases. Only primary tumor mass was manually segmented. Radiomic features were extracted using PyRadiomics, and then the support vector machine was used to build the radiomic model with fivefold cross-validation process in the training data set. For each case, a radiomics score was generated to indicate the probability of LR. There were 94 patients with LR assigned in the progression group and 98 patients without LR assigned in the stable group. There was no significant difference of TNM staging, treatment strategies and common risk factors between these two groups. For the training data set, the radiomics model to predict LR showed 83.7% accuracy and 0.832 (95% CI 0.72, 0.87) area under the ROC curve (AUC). For the test data set, the accuracy and AUC slightly declined to 79.5% and 0.770 (95% CI 0.64, 0.80), respectively. The sensitivity/specificity of training and test data set for LR prediction were 77.6%/89.6%, and 66.7%/90.5%, respectively. The image-based radiomic approach could provide a reliable LR prediction model in locally advanced OPC and HPC. Early identification of those prone to post-treatment recurrence would be helpful for appropriate adjustments to treatment strategies and post-treatment surveillance.

Development of A Radiomic Model for MGMT Promoter Methylation Detection in Glioblastoma Using Conventional MRI.

The methylation of the O6-methylguanine-DNA methyltransferase (MGMT) promoter is a molecular marker associated with a better response to chemotherapy in patients with glioblastoma (GB). Standard pre-operative magnetic resonance imaging (MRI) analysis is not adequate to detect MGMT promoter methylation. This study aims to evaluate whether the radiomic features extracted from multiple tumor subregions using multiparametric MRI can predict MGMT promoter methylation status in GB patients. This retrospective single-institution study included a cohort of 277 GB patients whose 3D post-contrast T1-weighted images and 3D fluid-attenuated inversion recovery (FLAIR) images were acquired using two MRI scanners. Three separate regions of interest (ROIs) showing tumor enhancement, necrosis, and FLAIR hyperintensities were manually segmented for each patient. Two machine learning algorithms (support vector machine (SVM) and random forest) were built for MGMT promoter methylation prediction from a training cohort (196 patients) and tested on a separate validation cohort (81 patients), based on a set of automatically selected radiomic features, with and without demographic variables (i.e., patients' age and sex). In the training set, SVM based on the selected radiomic features of the three separate ROIs achieved the best performances, with an average of 83.0% (standard deviation: 5.7%) for accuracy and 0.894 (0.056) for the area under the curve (AUC) computed through cross-validation. In the test set, all classification performances dropped: the best was obtained by SVM based on the selected features extracted from the whole tumor lesion constructed by merging the three ROIs, with 64.2% (95% confidence interval: 52.8-74.6%) accuracy and 0.572 (0.439-0.705) for AUC. The performances did not change when the patients' age and sex were included with the radiomic features into the models. Our study confirms the presence of a subtle association between imaging characteristics and MGMT promoter methylation status. However, further verification of the strength of this association is needed, as the low diagnostic performance obtained in this validation cohort is not sufficiently robust to allow clinically meaningful predictions.

Findings of MRI, CT scan and ultrasound in Marion's disease in a young woman: a case report

BackgroundPrimary bladder neck obstruction (PBNO) is a rare condition of the lower urinary tract in young and middle-aged patients. PBNO is a urological condition affecting both sexes in which the bladder neck fails to open adequately during voiding, resulting in obstruction of urinary flow in the absence of anatomic obstruction, such as benign prostatic hypertrophy in men or genitourinary prolapse in women. PBNO may present voiding symptoms (decreased force of stream, hesitancy, intermittent stream, incomplete emptying) or irritative symptoms (frequency, urgency, urge incontinence, nocturia) or a combination of both.Case presentationA 31-year-old female without medical history presented to our department with a 4–5 months history of a sense of incomplete emptying bladder and suprapubic discomfort. In Abdominal and Pelvic CT images of her CT scan, evidence of homogenous concentric hypertrophy of the urethra with mild enhancement in the post-contrast image was seen. Also, pelvic MRI shows isointense on T1- weighted and isointense to mildly hyperintense on T2-weighted Images (to skeletal muscle signal) of the concentric hypertrophy muscular layer of the urethra. The post-contrast image demonstrates moderate enhancement in the hypertrophied urethra. A month later, while the patient had not received any treatment, a pelvic ultrasound showed concentric hypertrophy hypoechoic muscular layer of the urethra.DiscussionThe true prevalence of PBNO is unknown but Farrar et al. reported a 2% prevalence of primary bladder neck obstruction.In 1933, Marion described PBNO as caused by fibrous narrowing of the bladder neck and detrusor hyperplasia. Also, Marion described two types of disease (congenital and acquired) and treatment methods. In this study was shown isointense on T1-weighted and isointense to mildly hyperintense on T2-weighted Images of concentric hypertrophy muscular layer of urethra with moderate enhancement on the post-contrast image. A doughnut sign was also seen in our axial slices (particularly in T2-weighted images), so this sign seems to be a diagnostic finding in MRI. In our study, the diffusion sequence and ADC map showed no obvious restriction.ConclusionsAlthough PBNO has been described for decades, there is still a controversy about diagnosis and treatment. In patients suspected of PBNO, imaging methods, especially MRI, can help confirm the diagnosis or rule out other causes of bladder neck obstruction. In future studies, imaging modalities can be one of the diagnostic criteria for PBNO.

Breast Fibroglandular Tissue Segmentation for Automated BPE Quantification With Iterative Cycle-Consistent Semi-Supervised Learning.

Background Parenchymal Enhancement (BPE) quantification in Dynamic Contrast-Enhanced Magnetic Resonance Imaging (DCE-MRI) plays a pivotal role in clinical breast cancer diagnosis and prognosis. However, the emerging deep learning-based breast fibroglandular tissue segmentation, a crucial step in automated BPE quantification, often suffers from limited training samples with accurate annotations. To address this challenge, we propose a novel iterative cycle-consistent semi-supervised framework to leverage segmentation performance by using a large amount of paired pre-/post-contrast images without annotations. Specifically, we design the reconstruction network, cascaded with the segmentation network, to learn a mapping from the pre-contrast images and segmentation predictions to the post-contrast images. Thus, we can implicitly use the reconstruction task to explore the inter-relationship between these two-phase images, which in return guides the segmentation task. Moreover, the reconstructed post-contrast images across multiple auto-context modeling-based iterations can be viewed as new augmentations, facilitating cycle-consistent constraints across each segmentation output. Extensive experiments on two datasets with various data distributions show great segmentation and BPE quantification accuracy compared with other state-of-the-art semi-supervised methods. Importantly, our method achieves 11.80 times of quantification accuracy improvement along with 10 times faster, compared with clinical physicians, demonstrating its potential for automated BPE quantification. The code is available at https://github.com/ZhangJD-ong/Iterative-Cycle-consistent-Semi-supervised-Learning-for-fibroglandular-tissue-segmentation.

Cardiac Magnetic Resonance Imaging in COVID-19 Vaccine-Associated Myocarditis Compared With Classical Myocarditis

BackgroundStudies comparing COVID-19 vaccine-associated and classical myocarditis (CM) are lacking. ObjectivesThe purpose of this study was to compare cardiac magnetic resonance (CMR) imaging findings and short-term clinical outcomes in patients with messenger RNA COVID-19 postvaccination myocarditis (PVM) and CM. MethodsThis was a retrospective study of patients with myocarditis: 31 with PVM and 46 with CM. Patients underwent a CMR protocol scan including T1 and T2 sequences. Late gadolinium enhancement (LGE) was expressed as percentage of left ventricular myocardial mass and the extracellular volume was calculated based on precontrast and postcontrast T1 images. Clinical outcomes included heart failure hospitalizations and mortality. ResultsStudy patients were predominantly male (81% in PVM vs 89% in CM, P = 0.330). Patients with PVM had lower T1 values compared with CM (1,064.2 ± 67.0 ms vs 1,081.6 ± 41.9 ms, P = 0.032), although T2 and extracellular volume values were similar in both groups. Left ventricular ejection fraction and LGE were similar in both groups. The most frequent location of LGE was the basal inferolateral wall. PVM more commonly demonstrated a mid-wall LGE pattern while CM demonstrated a subepicardial LGE pattern. Compared with CM, patients with PVM were more likely to have a pericardial effusion (42% vs 17%, P = 0.018) and pericardial LGE (38% vs 13%, P = 0.009). During short-term follow-up (median 300 days for PVM, 319 days for CM), there were no deaths or heart failure hospitalizations in either group. ConclusionsOur study shows similar CMR imaging findings and short-term outcomes in PVM and CM, although PVM was associated with milder myocardial abnormalities and more frequent pericardial involvement.

A novel MRI feature, the cut green pepper sign, can help differentiate a suprasellar pilocytic astrocytoma from an adamantinomatous craniopharyngioma

ObjectiveThere are no specific magnetic resonance imaging (MRI) features that distinguish pilocytic astrocytoma (PA) from adamantinomatous craniopharyngioma (ACP). In this study we compared the frequency of a novel enhancement characteristic on MRI (called the cut green pepper sign) in PA and ACP.MethodsConsecutive patients with PA (n = 24) and ACP (n = 36) in the suprasellar region were included in the analysis. The cut green pepper sign was evaluated on post-contrast T1WI images independently by 2 neuroradiologists who were unaware of the pathologic diagnosis. The frequency of cut green pepper sign in PA and ACP was compared with Fisher’s exact test.ResultsThe cut green pepper sign was identified in 50% (12/24) of patients with PA, and 5.6% (2/36) with ACP. The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of the cut green pepper sign for diagnosing PA were 50%, 94.4%, 85.7% and 73.9%, respectively. There was a statistically significant difference in the age of patients with PA with and without the cut green pepper sign (12.3 ± 9.2 years vs. 5.5 ± 4.4 years, p = 0.035).ConclusionThe novel cut green pepper sign can help distinguish suprasellar PA from ACP on MRI.