Analysis of clinical factors and ultrasound features associated with COVID-19 vaccine-related axillary lymphadenopathy: A large group study.

PURPOSE: To investigate factors that distinguish COVID-19 vaccine-related axillary lymphadenopathy from malignancy or other etiologies. METHODS: From June 2021 to April 2022, 3859 consecutive female patients had breast and axillary ultrasound (US) at our institution. After exclusions, 592 patients were included in the study. We retrospectively reviewed clinical history and US features of enlarged axillary lymph nodes. Assessed clinical factors included age, vaccination type, dose and vaccination date, and ultrasound features included cortical thickness, shape, marginal irregularity, focal cortical thickening, fatty hilum, and number and anatomic location of enlarged lymph nodes. The seven US features were used to score the severity of lymphadenopathy. Binary logistic models and independent two-sample t-tests were used for statistical analysis. RESULTS: Among 592 patients (mean age 49.3 ± 10.3 years), 406(68.6%), 90(15.2%), 42(7.1), 4(0.7%) and 50(8.4%) patients received Pfizer, AstraZeneca, Moderna, Janssen and cross inoculation of more than one type, respectively. 185(31.3%), 376(63.5%) and 31(5.2%) patients received a first, second and third dose, respectively. The interval between vaccination and US was 30.9 ± 21.5 days. US showed axillary lymphadenopathy (LAP) in 113 patients (19.1%). Clinical factors associated with LAP were age younger than 50 years, mRNA vaccine, first dose and shorter interval(P < 0.05). US features associated with LAP were mean cortical thickness of 4.6 ± 1.63 mm, oval shape (70.8%), smooth margin (53.1%), focal cortical thickening (62.8%) and preserved fatty hilum (84.1%). Using our scoring method, the mean overall score for vaccine-related LAP was 2.45 ± 1.51 points. CONCLUSION: Awareness of influencing factors and sonographic features can help differentiate COVID-19 vaccine-related adenopathy from other etiologies.

Deep learning system for automated detection of posterior ligamentous complex injury in patients with thoracolumbar fracture on MRI.

This study aimed to develop a deep learning (DL) algorithm for automated detection and localization of posterior ligamentous complex (PLC) injury in patients with acute thoracolumbar (TL) fracture on magnetic resonance imaging (MRI) and evaluate its diagnostic performance. In this retrospective multicenter study, using midline sagittal T2-weighted image with fracture (± PLC injury), a training dataset and internal and external validation sets of 300, 100, and 100 patients, were constructed with equal numbers of injured and normal PLCs. The DL algorithm was developed through two steps (Attention U-net and Inception-ResNet-V2). We evaluate the diagnostic performance for PLC injury between the DL algorithm and radiologists with different levels of experience. The area under the curves (AUCs) generated by the DL algorithm were 0.928, 0.916 for internal and external validations, and by two radiologists for observer performance test were 0.930, 0.830, respectively. Although no significant difference was found in diagnosing PLC injury between the DL algorithm and radiologists, the DL algorithm exhibited a trend of higher AUC than the radiology trainee. Notably, the radiology trainee's diagnostic performance significantly improved with DL algorithm assistance. Therefore, the DL algorithm exhibited high diagnostic performance in detecting PLC injuries in acute TL fractures.

Changes in radiomic and radiologic features in meningiomas after radiation therapy.

OBJECTIVES: This study evaluated the radiologic and radiomic features extracted from magnetic resonance imaging (MRI) in meningioma after radiation therapy and investigated the impact of radiation therapy in treating meningioma based on routine brain MRI. METHODS: Observation (n = 100) and radiation therapy (n = 62) patients with meningioma who underwent MRI were randomly divided (7:3 ratio) into training (n = 118) and validation (n = 44) groups. Radiologic findings were analyzed. Radiomic features (filter types: original, square, logarithm, exponential, wavelet; feature types: first order, texture, shape) were extracted from the MRI. The most significant radiomic features were selected and applied to quantify the imaging phenotype using random forest machine learning algorithms. Area under the curve (AUC), sensitivity, and specificity for predicting both the training and validation sets were computed with multiple-hypothesis correction. RESULTS: The radiologic difference in the maximum area and diameter of meningiomas between two groups was statistically significant. The tumor decreased in the treatment group. A total of 241 series and 1691 radiomic features were extracted from the training set. In univariate analysis, 24 radiomic features were significantly different (P < 0.05) between both groups. Best subsets were one original, three first-order, and six wavelet-based features, with an AUC of 0.87, showing significant differences (P < 0.05) in multivariate analysis. When applying the model, AUC was 0.76 and 0.79 for the training and validation set, respectively. CONCLUSION: In meningioma cases, better size reduction can be expected after radiation treatment. The radiomic model using MRI showed significant changes in radiomic features after radiation treatment.

Erratum: Agreement and Reliability between Clinically Available Software Programs in Measuring Volumes and Normative Percentiles of Segmented Brain Regions.

This corrects the article on p. 959 in vol. 23, PMID: 36175000.

Cortical mean diffusivity is reliable in measuring brain abnormalities in drug-naïve essential tremor patients.

OBJECTIVE: Essential tremor (ET) is a common movement disorder, but the pathogenesis is poorly understood. Several associated brain areas were reported with inconsistent results due to heterogeneous populations. It is necessary to analyze a more homogeneous patient group. METHODS: We recruited 25 drug-naïve ET patients and 36 age- and sex-matched controls. All participants were right-handed. ET. ET was defined according to diagnostic criteria of the Consensus Statement of the Movement Disorder Society on Tremor. ET patients were divided into sporadic (SET) and familial ET (FET). We assessed tremor severity in ET. The cortical microstructural changes were compared between ET patients and controls using mean diffusivity (MD) of diffusion tensor imaging, and cortical thickness. The correlation of tremor severity with the cortical MD and thickness were respectively analyzed. RESULTS: MD values were increased in the insular, precuneus, medial orbitofrontal, posterior, and isthmus cingulate and temporo-occipital areas in ET. In comparison between SET and FET, MD values were higher in the superior and caudal middle frontal, postcentral, and temporo-occipital regions in FET. The cortical thickness of ET patients was more increased in the left lingual gyrus and lower in the right bankssts gyrus. We could not find any correlation of tremor severity with the MD values in ET patients. Still, there was a positive correlation with the cortical thickness of the frontal and parietal areas. CONCLUSIONS: Our results support the idea that ET is a disorder that disrupts widespread brain regions and indicates that cortical MD may be more sensitive to measure brain abnormalities than cortical thickness.

Agreement and Reliability between Clinically Available Software Programs in Measuring Volumes and Normative Percentiles of Segmented Brain Regions.

OBJECTIVE: To investigate the agreement and reliability of estimating the volumes and normative percentiles (N%) of segmented brain regions among NeuroQuant (NQ), DeepBrain (DB), and FreeSurfer (FS) software programs, focusing on the comparison between NQ and DB. MATERIALS AND METHODS: Three-dimensional T1-weighted images of 145 participants (48 healthy participants, 50 patients with mild cognitive impairment, and 47 patients with Alzheimer's disease) from a single medical center (SMC) dataset and 130 participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset were included in this retrospective study. All images were analyzed with DB, NQ, and FS software to obtain volume estimates and N% of various segmented brain regions. We used Bland-Altman analysis, repeated measures ANOVA, reproducibility coefficient, effect size, and intraclass correlation coefficient (ICC) to evaluate inter-method agreement and reliability. RESULTS: Among the three software programs, the Bland-Altman plot showed a substantial bias, the ICC showed a broad range of reliability (0.004-0.97), and repeated-measures ANOVA revealed significant mean volume differences in all brain regions. Similarly, the volume differences of the three software programs had large effect sizes in most regions (0.73-5.51). The effect size was largest in the pallidum in both datasets and smallest in the thalamus and cerebral white matter in the SMC and ADNI datasets, respectively. N% of NQ and DB showed an unacceptably broad Bland-Altman limit of agreement in all brain regions and a very wide range of ICC values (-0.142-0.844) in most brain regions. CONCLUSION: NQ and DB showed significant differences in the measured volume and N%, with limited agreement and reliability for most brain regions. Therefore, users should be aware of the lack of interchangeability between these software programs when they are applied in clinical practice.

A prospective multi-centre study of susceptibility map-weighted MRI for the diagnosis of neurodegenerative parkinsonism.

OBJECTIVES: This study aimed to compare susceptibility map-weighted imaging (SMwI) using various MRI machines (three vendors) with N-3-fluoropropyl-2-ß-carbomethoxy-3-ß-(4-iodophe nyl)nortropane (18F-FP-CIT) PET in the diagnosis of neurodegenerative parkinsonism in a multi-centre setting. METHODS: We prospectively recruited 257 subjects, including 157 patients with neurodegenerative parkinsonism, 54 patients with non-neurodegenerative parkinsonism, and 46 healthy subjects from 10 hospitals between November 2019 and October 2020. All participants underwent both SMwI and 18F-FP-CIT PET. SMwI was interpreted by two independent reviewers for the presence or absence of abnormalities in nigrosome 1, and discrepancies were resolved by consensus. 18F-FP-CIT PET was used as the reference standard. Inter-observer agreement was tested using Cohen's kappa coefficient. McNemar's test was used to test the agreement between the interpretations of SMwI and 18F-FP-CIT PET per participant and substantia nigra (SN). RESULTS: The inter-observer agreement was 0.924 and 0.942 per SN and participant, respectively. The diagnostic sensitivity of SMwI was 97.9% and 99.4% per SN and participant, respectively; its specificity was 95.9% and 95.2%, respectively, and its accuracy was 97.1% and 97.7%, respectively. There was no significant difference between the results of SMwI and 18F-FP-CIT PET (p > 0.05, for both SN and participant). CONCLUSIONS: This study demonstrated that the high diagnostic performance of SMwI was maintained in a multi-centre setting with various MRI scanners, suggesting the generalisability of SMwI for determining nigrostriatal degeneration in patients with parkinsonism. KEY POINTS: • Susceptibility map-weighted imaging helps clinicians to predict nigrostriatal degeneration. • The protocol for susceptibility map-weighted imaging can be standardised across MRI vendors. • Susceptibility map-weighted imaging showed diagnostic performance comparable to that of dopamine transporter PET in a multi-centre setting with various MRI scanners.

Acute to Subacute Spinal Cord Infarction Mimicking Acute Multiple Sclerosis: Usefulness of Diffusion-weighted MRI for Diagnosis.

BACKGROUND: Spinal Cord Infarction (SCI) is difficult to diagnose because of its rarity, unknown etiology, and unestablished diagnostic criteria. Additionally, the timeline of SCI has not been studied in detail, as few studies using Diffusion-Weighted Image (DWI) sequences of the spine of a small target population have been previously conducted. CASE STUDY: A 56-year-old male with underlying arrhythmia suddenly developed visual field defects on the right side, pain in the left upper extremity, and a tingling sensation in the left hand. Brain Magnetic resonance imaging (MRI) revealed acute to subacute stages of multifocal brain infarction. On additional cervical spinal MRI, it showed atypical MRI findings of SCI, considered late acute to early subacute phase, which were similar to those seen in the acute phase of multiple sclerosis (MS). Additional DWI revealed restricted diffusion. From these findings, it could be inferred that the patient's SCI occurred at the same time as the multifocal brain infarctions caused by atrial fibrillation. CONCLUSION: A DWI sequence of spine MRI could be helpful in the diagnosis of acute to subacute phase SCI and in differentiating with acute MS.

Application of T1 Map Information Based on Synthetic MRI for Dynamic Contrast-Enhanced Imaging: A Comparison Study with the Fixed Baseline T1 Value Method.

OBJECTIVE: For an accurate dynamic contrast-enhanced (DCE) MRI analysis, exact baseline T1 mapping is critical. The purpose of this study was to compare the pharmacokinetic parameters of DCE MRI using synthetic MRI with those using fixed baseline T1 values. MATERIALS AND METHODS: This retrospective study included 102 patients who underwent both DCE and synthetic brain MRI. Two methods were set for the baseline T1: one using the fixed value and the other using the T1 map from synthetic MRI. The volume transfer constant (Ktrans), volume of the vascular plasma space (vp), and the volume of the extravascular extracellular space (ve) were compared between the two methods. The interclass correlation coefficients and the Bland-Altman method were used to assess the reliability. RESULTS: In normal-appearing frontal white matter (WM), the mean values of Ktrans, ve, and vp were significantly higher in the fixed value method than in the T1 map method. In the normal-appearing occipital WM, the mean values of ve and vp were significantly higher in the fixed value method. In the putamen and head of the caudate nucleus, the mean values of Ktrans, ve, and vp were significantly lower in the fixed value method. In addition, the T1 map method showed comparable interobserver agreements with the fixed baseline T1 value method. CONCLUSION: The T1 map method using synthetic MRI may be useful for reflecting individual differences and reliable measurements in clinical applications of DCE MRI.

Prognostic Prediction Based on Dynamic Contrast-Enhanced MRI and Dynamic Susceptibility Contrast-Enhanced MRI Parameters from Non-Enhancing, T2-High-Signal-Intensity Lesions in Patients with Glioblastoma.

OBJECTIVE: Few attempts have been made to investigate the prognostic value of dynamic contrast-enhanced (DCE) MRI or dynamic susceptibility contrast (DSC) MRI of non-enhancing, T2-high-signal-intensity (T2-HSI) lesions of glioblastoma multiforme (GBM) in newly diagnosed patients. This study aimed to investigate the prognostic values of DCE MRI and DSC MRI parameters from non-enhancing, T2-HSI lesions of GBM. MATERIALS AND METHODS: A total of 76 patients with GBM who underwent preoperative DCE MRI and DSC MRI and standard treatment were retrospectively included. Six months after surgery, the patients were categorized into early progression (n = 15) and non-early progression (n = 61) groups. We extracted and analyzed the permeability and perfusion parameters of both modalities for the non-enhancing, T2-HSI lesions of the tumors. The optimal percentiles of the respective parameters obtained from cumulative histograms were determined using receiver operating characteristic (ROC) curve and univariable Cox regression analyses. The results were compared using multivariable Cox proportional hazards regression analysis of progression-free survival. RESULTS: The 95th percentile value (PV) of Ktrans, mean Ktrans, and median Ve were significant predictors of early progression as identified by the ROC curve analysis (area under the ROC curve [AUC] = 0.704, p = 0.005; AUC = 0.684, p = 0.021; and AUC = 0.670, p = 0.0325, respectively). Univariable Cox regression analysis of the above three parametric values showed that the 95th PV of Ktrans and the mean Ktrans were significant predictors of early progression (hazard ratio [HR] = 1.06, p = 0.009; HR = 1.25, p = 0.017, respectively). Multivariable Cox regression analysis, which also incorporated clinical parameters, revealed that the 95th PV of Ktrans was the sole significant independent predictor of early progression (HR = 1.062, p < 0.009). CONCLUSION: The 95th PV of Ktrans from the non-enhancing, T2-HSI lesions of GBM is a potential prognostic marker for disease progression.

Improvement of the Diagnostic Performance of Facial Neuritis Using Contrast-Enhanced 3D T1 Black-Blood Imaging: Comparison with Contrast-Enhanced 3D T1-Spoiled Gradient-Echo Imaging.

This study aims to investigate the diagnostic ability of the contrast-enhanced 3D T1 black-blood fast spin-echo (T1 BB-FSE) sequence compared with the contrast-enhanced 3D T1-spoiled gradient-echo (CE-GRE) sequence in patients with facial neuritis. Forty-five patients with facial neuritis who underwent temporal bone MR imaging, including T1 BB-FSE and CE-GRE imaging, were examined. Two reviewers independently assessed the T1 BB-FSE and CE-GRE images in terms of diagnostic performance, and qualitative (diagnostic confidence and visual asymmetric enhancement) and quantitative analysis (contrast-enhancing lesion extent of the canalicular segment of the affected facial nerve (LEC) and the affected side-to-normal signal intensity ratio (rSI)). The AUCs of each reviewer, and the sensitivity and accuracy of T1 BB-FSE were significantly superior to those of CE-GRE (p < 0.05). Regarding diagnostic confidence and visual asymmetric enhancement, T1 BB-FSE tended to be rated greater than CE-GRE (p < 0.05). Additionally, in quantitative analysis, LEC and rSI of the canalicular segment on T1 BB-FSE were larger than those on CE-GRE (p < 0.05). The T1 BB-FSE sequence was significantly superior to the CE-GRE sequence, with more conspicuous lesion visualization in terms of both qualitative and quantitative aspects in patients with facial neuritis.

Prevalence of brain MRI findings in children with nonacquired growth hormone deficiency: a systematic review and meta-analysis.

PURPOSE: To verify and integrate the prevalence and phenotype of abnormalities in the sellar region in patients with growth hormone deficiency (GHD) using MRI data. METHODS: We searched PubMed and EMBASE up to December 14, 2020. The inclusion criteria were as follows: (1) pediatric patients diagnosed with nonacquired GHD and (2) detailed data sufficient to assess the proportion of sellar and parasellar abnormalities on brain MRI scans. Finally, thirty-two studies with 39,060 children (mean or median age, 3.4-14.1 years) were included. The number and type of MRI findings from all included studies were pooled by two authors. The heterogeneity across studies was evaluated with the Q test or the inconsistency index (I2) statistic. Subgroup analyses were performed according to the type of GHD (isolated GHD [IGHD] vs. multiple pituitary hormone deficiency [MPHD]), MRI magnet, geographical region, and cutoff serum growth hormone (GH) level. RESULTS: The pooled proportion of sellar and parasellar abnormalities was 58.0% (95% CI, 47.1-68.6%; I2, 98.2%). The MPHD group showed a higher proportion of sellar and parasellar abnormalities and pituitary stalk interruption syndrome than the IGHD group (91.4% vs. 40.1%, P<0.001; 65.3% vs. 20.1%, P<0.001). The patients in studies with low peak GH levels on stimulation tests were more associated with severe MR abnormalities (cutoff GH ≤ 5 µg/l vs. cutoff GH = 10 µg/l; 72.8 % vs. 38.0%; P<0.001). CONCLUSION: The types and incidence of MRI abnormalities of the sellar region differ significantly between the IGHD and MPHD groups.

Comparison of Genetic Profiles and Prognosis of High-Grade Gliomas Using Quantitative and Qualitative MRI Features: A Focus on G3 Gliomas.

OBJECTIVE: To evaluate the association of MRI features with the major genomic profiles and prognosis of World Health Organization grade III (G3) gliomas compared with those of glioblastomas (GBMs). MATERIALS AND METHODS: We enrolled 76 G3 glioma and 155 GBM patients with pathologically confirmed disease who had pretreatment brain MRI and major genetic information of tumors. Qualitative and quantitative imaging features, including volumetrics and histogram parameters, such as normalized cerebral blood volume (nCBV), cerebral blood flow (nCBF), and apparent diffusion coefficient (nADC) were evaluated. The G3 gliomas were divided into three groups for the analysis: with this isocitrate dehydrogenase (IDH)-mutation, IDH mutation and a chromosome arm 1p/19q-codeleted (IDHmut1p/19qdel), IDH mutation, 1p/19q-nondeleted (IDHmut1p/19qnondel), and IDH wildtype (IDHwt). A prediction model for the genetic profiles of G3 gliomas was developed and validated on a separate cohort. Both the quantitative and qualitative imaging parameters and progression-free survival (PFS) of G3 gliomas were compared and survival analysis was performed. Moreover, the imaging parameters and PFS between IDHwt G3 gliomas and GBMs were compared. RESULTS: IDHmut G3 gliomas showed a larger volume (p = 0.017), lower nCBF (p = 0.048), and higher nADC (p = 0.007) than IDHwt. Between the IDHmut tumors, IDHmut1p/19qdel G3 gliomas had higher nCBV (p = 0.024) and lower nADC (p = 0.002) than IDHmut1p/19qnondel G3 gliomas. Moreover, IDHmut1p/19qdel tumors had the best prognosis and IDHwt tumors had the worst prognosis among G3 gliomas (p < 0.001). PFS was significantly associated with the 95th percentile values of nCBV and nCBF in G3 gliomas. There was no significant difference in neither PFS nor imaging features between IDHwt G3 gliomas and IDHwt GBMs. CONCLUSION: We found significant differences in MRI features, including volumetrics, CBV, and ADC, in G3 gliomas, according to IDH mutation and 1p/19q codeletion status, which can be utilized for the prediction of genomic profiles and the prognosis of G3 glioma patients. The MRI signatures and prognosis of IDHwt G3 gliomas tend to follow those of IDHwt GBMs.

Quantitative dynamic contrast-enhanced MR imaging shows widespread blood-brain barrier disruption in mild traumatic brain injury patients with post-concussion syndrome.

OBJECTIVES: To explore the utility of dynamic contrast-enhanced (DCE) MR imaging for quantitative analysis of blood-brain barrier disruption in mild traumatic brain injury (mTBI) patients with post-concussion syndrome (PCS). METHODS: Forty-four consecutive patients with PCS after mTBI and 32 controls were included in this retrospective study. Ktrans and ve from DCE MR imaging were analyzed at contrast-enhancing lesions, T2 hyperintense white matter (WM) lesions, normal-appearing white matter (NAWM), and predilection sites for diffuse axonal injury (LocationDAI). The Mann-Whitney U-test was performed to compare the parameters between mTBI patients and controls and the parameters were correlated with neuropsychological tests using Mann-Whitney U-test and Spearman rank correlation. RESULTS: The median ve of the T2 hyperintense WM lesions in mTBI patients (n=21) was higher than that of NAWM in controls (p=.027). Both median Ktrans and ve at NAWM were also significantly higher in mTBI patients than in controls (p=.023 and p=.029, respectively). In addition, mTBI patients had higher Ktrans and ve at LocationDAI than controls (p=.008 and p=.015, respectively). VLT (delayed recall) scores were significantly correlated with ve values at T2 hyperintense WM lesions (p=-0.767, p=.044). The median ve at LocationDAI was significantly higher in patients with atypical performance in the digit span test (forward) than in those with average or good performance (p=.043). CONCLUSIONS: mTBI patients with PCS had higher Ktrans and ve values than controls not only at T2 hyperintense WM lesions but also at NAWM and LocationDAI. BBB disruption may be implicated in development of PCS in mTBI patients. KEY POINTS: • mTBI patients with PCS had higher permeability than controls at T2 hyperintense WM lesions on DCE MR imaging. • mTBI patients with PCS had higher permeability than controls also at NAWM and predilection sites for DAI. • BBB disruption may be implicated in the development of PCS in mTBI patients.

PREDICTION OF NONDIAGNOSTIC RESULTS IN FINE-NEEDLE ASPIRATION OF THYROID NODULES: UTILITY OF ON-SITE GROSS VISUAL ASSESSMENT OF SPECIMENS FOR LIQUID-BASED CYTOLOGY.

OBJECTIVE: To explore a comprehensive approach for on-site gross visual assessments of liquid-based cytology (LBC) specimens of thyroid nodules and determine morphologic criteria that help predict nondiagnostic rates. METHODS: Two-hundred nodules from 165 patients who underwent fine-needle aspiration (FNA) at our hospital were included in this prospectively designed, retrospective analysis. Specimens were visually assessed on-site for three morphologic categories (specimen color, specimen volume, and particle count) using a 5-point grading. RESULTS: Twenty-two nodules (11%) showed nondiagnostic results. Regarding specimen color, nondiagnostic rates tended to be higher in grades 1 (75%) and 5 (100%) than in grades 2 (18%), 3 (8%), or 4 (17%), with a significant difference between grade 1 and grade 3 ( P = .003). For specimen volume, nondiagnostic results were significantly more common in grade 1 (33%) and 5 (33%) than in grades 3 (5%) or 4 (1%) ( P<.005). There was a significant negative correlation between the grading of the particle count and the nondiagnostic rate (Spearman ρ = -1.000; P<.001). The sensitivity and specificity in the prediction of nondiagnostic results were 77% and 76%, respectively, at the optimal cutoff value of 2 (grade 2 or lower). CONCLUSION: Particle count was an important morphologic criterion that helped predict nondiagnostic rates in LBC specimens of thyroid nodules, and the specimen color and volume were also useful adjuncts. In routine practice, on-site gross visual assessment followed by resampling (if necessary) may potentially help reduce the rates of nondiagnostic results, repeat FNAs, and the number of unnecessary needle passes. ABBREVIATIONS: FNA = fine-needle aspiration; LBC = liquid-based cytology; ROC = receiver operating characteristic; US = ultrasonography.

Radiogenomics correlation between MR imaging features and major genetic profiles in glioblastoma.

OBJECTIVES: To assess the association between MR imaging features and major genomic profiles in glioblastoma. METHODS: Qualitative and quantitative imaging features such as volumetrics and histogram analysis from normalised CBV (nCBV) and ADC (nADC) were evaluated based on both T2WI and CET1WI. The imaging parameters of different genetic profile groups were compared and regression analyses were used for identifying imaging-molecular associations. Progression-free survival (PFS) was analysed by a Kaplan-Meier test and Cox proportional hazards model. RESULTS: An IDH mutation was observed in 18/176 patients, and ATRX loss was positive in 17/158 of the IDH-wt cases. The IDH-mut group showed a larger volume on T2WI and a higher volume ratio between T2WI and CET1WI than the IDH-wt group (p < 0.05). In the IDH-mut group, higher mean nADC values were observed compared with the IDH-wt tumours (p < 0.05). Among the IDH-wt tumours, IDH-wt, ATRX-loss tumours revealed higher 5th percentile nADC values than the IDH-wt, ATRX-noloss tumours (p = 0.03). PFS was the longest in the IDH-mut group, followed by the IDH-wt, ATRX-loss groups and the IDH-wt, ATRX-noloss groups, consecutively (p < 0.05). We found significant associations of PFS with the genetic profiles and imaging parameters. CONCLUSION: Major genetic profiles of glioblastoma showed a significant association with MR imaging features, along with some genetic profiles, which are independent prognostic parameters for GBM. KEY POINTS: • Significant correlation exists between radiological parameters such as volumetric and ADC values and major genomic profiles such as IDH mutation and ATRX loss status • Radiological parameters such as the ADC value were feasible predictors of glioblastoma patients' prognosis • Imaging features can predict major genomic profiles of the tumours and the prognosis of glioblastoma patients.

Subarachnoid Hemorrhage Misdiagnosed as an Acute ST Elevation Myocardial Infarction.

Without significant coronary artery stenosis, ischemic electrocardiographic change including ST segment elevation, segmental wall motion abnormality and elevated serum cardiac-specific markers (creatine kinase-MB, Troponin-T) may develop after central nervous system injuries such as subarachnoid, intracranial or subdural hemorrhage. Misdiagnosing these patients as acute myocardial infarction may result in catastrophic outcomes. By reporting a case of a 55-year old female with subarachnoid hemorrhage mimicking acute ST elevation myocardial infarction, we hope to underline that careful attention of neurologic abnormality is critical in making better prognosis.