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International audience; The emergence of massively parallel yet affordable computing devices has been a game changer for research in the field of artificial intelligence (AI). In addition, dramatic investment from the web giants has fostered the development of a high-quality software stack. Going forward, the combination of faster computers with dedicated software libraries and the widespread availability of data has opened the door to more flexibility in the design of AI models. Radiomics is a process used to discover new imaging biomarkers that has multiple applications in radiology and can be used in conjunction with AI. AI can be used throughout the various processes of diagnostic imaging, including data acquisition, reconstruction, analysis and reporting. Today, the concept of "AI-augmented" radiologists is preferred to the theory of the replacement of radiologists by AI in many indications. Current evidence bolsters the assumption that AI-assisted radiologists work better and faster. Interventional radiology becomes a data-rich specialty where the entire procedure is fully recorded in a standardized DICOM format and accessible via standard picture archiving and communication systems. No other interventional specialty can bolster such readiness. In this setting, interventional radiology could lead the development of AI-powered applications in the broader interventional community. This article provides an update on the current status of radiomics and AI research, analyzes upcoming challenges and also discusses the main applications in AI in interventional radiology to help radiologists better understand and criticize articles reporting AI in medical imaging.

Brain imaging is essential for the diagnosis of acute stroke and vascular aphasia. Magnetic resonance imaging (MRI) is the modality of choice for the etiological diagnosis of aphasia, the assessment of its severity, and the prediction of recovery. Diffusion weighted imaging is used to detect, localize, and quantify the extension of the irreversibly injured brain tissue called ischemic core. Perfusion weighted imaging (from MRI or CT) is useful to assess the extension of hypoperfused but salvageable tissue called penumbra. Functional imaging (positron emission tomography (PET), functional MRI (fMRI)) may help predicting recovery and is useful for the understanding of language networks and individual variability. This chapter is meant to review the state of the art of morphological and functional imaging of vascular aphasia and to illustrate the MRI profiles of different aphasic syndromes.

Resume Introduction La baisse d’acuite visuelle est un motif de consultation frequent en ophtalmologie. Elle regroupe de tres nombreuses pathologies, allant de l’œil au cerveau. Messages principaux Il n’existe pas un seul examen d’imagerie « de choix » permettant d’explorer l’ensemble des structures pouvant etre touchees en cas de baisse d’acuite visuelle. Au contraire, il convient d’adapter et de personnaliser chaque protocole d’imagerie en fonction de l’orientation clinique et des examens ophtalmologiques et paracliniques deja realises. L’analyse du deficit du champ visuel permet d’orienter rapidement et efficacement vers la region a explorer : globe oculaire, orbite et nerf optique en cas de baisse d’acuite visuelle monoculaire ; chiasma et region hypophysaire en cas d’hemianopsie bitemporale ; structures retro-chiasmatiques incluant les bandelettes optiques, les radiations optiques et le cortex occipital en cas d’hemianopsie ou de quadranopsie laterale homonyme. Conclusion Les strategies diagnostiques devant une baisse d’acuite visuelle incluent l’utilisation de plusieurs modalites d’imagerie en fonction de la clinique.

Background and purpose To compare the accuracy and utility of contrast enhanced magnetic resonance angiography (MRA) (CEMRA) to Time of Flight MRA (TOF MRA) during detection and evaluation of occlusions on patients diagnosed with acute ischemic stroke (AIS). Methods This single-center study was approved by our local institutional research ethics board. From August 2014 to July 2016, 131 consecutive adult patients with confirmed AIS were included. Detection of an arterial occlusion and its characterization were evaluated independently with CEMRA or TOF MRA by two blinded neuroradiologists, then by consensus using all available MR sequences. A Cohen's Kappa coefficient (κ) and intra-class correlation coefficients (ICC) were used to compare the two techniques. Results There was substantial concordance in the detection of arterial occlusion between CEMRA and TOF MRA (κ = 0.75). TOF MRA was more likely to show an arterial occlusion than CEMRA (63 versus 52 patients respectively). There were 13 and 1 false positive arterial occlusion with TOF MRA and CEMRA respectively, and 1 false negative with TOF MRA. There was excellent concordance between the location of arterial occlusions and CEMRA and TOF MRA [κ = 0.89 (0.72–0.97)]. CEMRA was significantly more likely to allow measurement of the thrombus than was TOF MRA [38 (75%) versus 14 (22%)] (P Conclusions Our study showed that CEMRA imaging detected arterial occlusions better than TOF MRA in AIS patients and more precisely such that thrombus length and location could be known, which improves the patient's management and care.

Resume Introduction L’IRM orbitaire est l’examen de choix dans l’exploration des pathologies orbitaires, en complement de l’echographie. Sa realisation et son interpretation sont delicates, car les pathologies a explorer sont diverses. Messages principaux Il n’existe pas un protocole d’IRM orbitaire « standard » permettant de couvrir l’ensemble de la pathologie orbitaire. Au contraire, il convient d’adapter et de personnaliser chaque protocole en fonction des indications cliniques et des examens ophtalmologiques et paracliniques deja realises. Compte tenu de la petite taille des orbites, des sequences en haute resolution sont a privilegier afin de detecter et d’analyser correctement la pathologie rencontree. L’injection de produit de contraste est souvent necessaire, notamment lors des explorations de baisse d’acuite visuelle ou dans les bilans de caracterisation tumorale. Conclusion L’IRM orbitaire est une modalite d’imagerie performante pour l’exploration des pathologies ophtalmologiques orbitaires.

Characterizing orbital lesions remains challenging with imaging. The purpose of this study was to compare 3 Tesla (T) to 7 T magnetic resonance imaging (MRI) for characterizing orbital lesions.This prospective single-center study enrolled participants presenting with orbital lesions from May to October 2019, who underwent both 7 T and 3 T MRI examinations. Two neuroradiologists, blinded to all data, read both datasets independently and randomly. They assessed general characteristics of each orbital lesion as well as image quality and presence of artifacts. Comparison between both datasets was made using Fisher exact test.Seven patients (4 women, 3 men) with a median age of 52 years were enrolled. Orbital lesion conspicuity was better scored at 7 T compared to 3 T MRI, with 3/7 lesions (43%) scored as very conspicuous at 7 T compared to 0/7 lesion (0%) at 3 T, although the difference was not significant (P = 0.16). Delineation of lesion margins was better scored at 7 T compared to 3 T with 3/7 lesions (43%) scored as very well delineated on 7 T compared to 0/7 lesions (0%) at 3 T, although the difference was not significant (P = 0.34). Details of internal structure were better assessed at 7 T compared to 3 T, with 4/7 lesions (57%) displaying numerous internal details compared to 0/7 lesions (0%) at 3 T (P = 0.10). Internal microvessels were visible in 3/7 lesions (43%) at 7 T compared to 0/7 lesions (0%) at 3 T (P = 0.19).Although no significant differences were found between 7 T and 3 T MRI, assumably due to a limited number of patients, our study suggests that 7 Tesla MRI might help improve the characterization of orbital lesions. However, further studies with more patients are needed.

To differentiate OCVM from other orbital lesions using structural MRI.This IRB-approved a historical-prospective cohort single-center analysis of a prospective cohort that included consecutive adult patients presenting with an orbital lesion undergoing a 3T MRI before surgery from December 2015 to May 2021. Two readers blinded to all data read all MRIs assessing structural MRI characteristics. A univariate analysis followed by a stepwise multivariate analysis identified structural MRI features showing the highest sensitivity and specificity when diagnosing OCVM.One hundred ninety-one patients with 30/191 (16%) OCVM and 161/191 (84%) other orbital lesions were included. OCVM were significantly more likely to present with a higher signal intensity than that of the cortex on T2WI: 26/29 (89.7%) versus 28/160 (17.5%), p0.001, or with a chemical shift artifact (CSA): 26/29 (89.7%) versus 16/155 (10.3%), p0.001, or to present with a single starting point of enhancement, as compared to other orbital lesions: 18/29 (62.1%) versus 4/159 (2.5%), p = 0.001. The step-wise analysis identified 2 signatures increasing performances. Signature 1 combined a higher signal intensity than that of the cortex on T2WI and a CSA. Signature 2 included these two features and the presence of a single starting point of enhancement. Sensitivity, specificity, and accuracy were 0.83, 0.94, and 0.92 for signature 1 and 0.97, 0.93, and 0.93 for signature 2, respectively.Structural MRI yields high sensitivity and specificity when diagnosing OCVM.• Structural MRI shows high sensitivity and specificity when diagnosing orbital cavernous venous malformation. • We identified two signatures combining structural MRI features which might be used easily in routine clinical practice. • The combination of higher signal intensity of the lesion as compared to the cortex on T2WI and of a chemical shift artifact yields a sensitivity and specificity of 0.83 and 0.94 for the diagnosis of orbital cavernous venous malformation, respectively.

The purpose of this study was to assess the inter-slice radiomic feature repeatability in ultrasound imaging and the impact of preprocessing using intensity standardization and grey-level discretization to help improve radiomics reproducibility.This single-center study enrolled consecutive patients with an orbital lesion who underwent ultrasound examination of the orbit from December 2015 to July 2019. Two images per lesion were randomly assigned to two subsets. Radiomic features were extracted and inter-slice repeatability was assessed using the intraclass correlation coefficient (ICC) between the subsets. The impact of preprocessing on feature repeatability was assessed using image intensity standardization with or without outliers removal on whole images, bounding boxes or regions of interest (ROI), and fixed bin size or fixed bin number grey-level discretization. Number of inter-slice repeatable features (ICC ≥0.7) between methods was compared.Eighty-eight patients (37 men, 51 women) with a mean age of 51.5 ± 17 (SD) years (range: 20-88 years) were enrolled. Without preprocessing, 29/101 features (28.7%) were repeatable between slices. The greatest number of repeatable features (41/101) was obtained using intensity standardization with outliers removal on the ROI and fixed bin size discretization. Standardization performed better with outliers removal than without (P 0.001), and on ROIs than on native images (P 0.001). Fixed bin size discretization performed better than fixed bin number (P = 0.008).Radiomic features extracted from ultrasound images are impacted by the slice and preprocessing. The use of intensity standardization with outliers removal applied to the ROI and a fixed bin size grey-level discretization may improve feature repeatability.

Anterior ischemic optic neuropathy (AION) is the most common cause of acute optic neuropathy in older patients. Distinguishing between arteritic AION (A-AION) and nonarteritic (NA-AION) is paramount for improved patient management.The aim of this study was to evaluate 3-dimensional high-resolution vessel wall (HR-VW) magnetic resonance imaging (MRI) at 3 T to discriminate A-AION from NA-AION.This prospective single-center study was approved by a national research ethics board and included 27 patients (17 A-AION and 10 NA-AION) with 36 AIONs from December 2014 to August 2017 who underwent 3 T HR-VW MRI. Two radiologists blinded to clinical data individually analyzed the imaging separately and in random order. Discrepancies were resolved by consensus with a third neuroradiologist. The primary diagnostic criterion was the presence of inflammatory changes of the ophthalmic artery. Secondary diagnostic criteria included the presence of an enhancement of the optic nerve or its sheath, the optic disc, or inflammatory changes of posterior ciliary or extracranial arteries. A Fisher exact test was used to compare A-AION from NA-AION patients.Inflammatory changes of the ophthalmic artery were present in all patients with A-AION but in none of NA-AION (P0.0001). Its sensitivity, specificity, positive predictive value, and negative predictive value were 100%. Inflammatory changes of posterior ciliary arteries were significantly more likely in A-AOIN (82% vs 0%, P0.0001). Interreader and intrareader agreements were almost perfect (κ = 0.82-1).High-resolution vessel wall MRI seems highly accurate when distinguishing A-AION from NA-AION and might be useful to improve patient management.

To validate a deep learning (DL) algorithm for measurement of skeletal muscular index (SMI) and prediction of overall survival in oncology populations.A retrospective single-center observational study included patients with metastatic renal cell carcinoma between 2007 and 2019. A set of 37 patients was used for technical validation of the algorithm, comparing manual vs DL-based evaluations. Segmentations were compared using mean Dice similarity coefficient (DSC), SMI using concordance correlation coefficient (CCC) and Bland-Altman plots. Overall survivals (OS) were compared using log-rank (Kaplan-Meier) and Mann-Whitney tests. Generalizability of the prognostic value was tested in an independent validation population (N = 87).Differences between two manual segmentations (DSC = 0.91, CCC = 0.98 for areas) or manual vs. automated segmentation (DSC = 0.90, CCC = 0.98 for areas, CCC = 0.97 for SMI) had the same order of magnitude. Bland-Altman plots showed a mean difference of -3.33 cmA DL algorithm allowed accurate estimation of SMI compared to manual reference standard. The DL-calculated SMI demonstrated a prognostic value in terms of OS.• A deep learning algorithm allows accurate estimation of skeletal muscle index compared to a manual reference standard with a concordance correlation coefficient of 0.97. • Sarcopenic patients according to SMI thresholds after segmentation by the deep learning algorithm had statistically significantly lower overall survival compared to non-sarcopenic patients.

Background The interpretation of radiographs suffers from an ever-increasing workload in emergency and radiology departments, while missed fractures represent up to 80% of diagnostic errors in the emergency department. Purpose To assess the performance of an artificial intelligence (AI) system designed to aid radiologists and emergency physicians in the detection and localization of appendicular skeletal fractures. Materials and Methods The AI system was previously trained on 60 170 radiographs obtained in patients with trauma. The radiographs were randomly split into 70% training, 10% validation, and 20% test sets. Between 2016 and 2018, 600 adult patients in whom multiview radiographs had been obtained after a recent trauma, with or without one or more fractures of shoulder, arm, hand, pelvis, leg, and foot, were retrospectively included from 17 French medical centers. Radiographs with quality precluding human interpretation or containing only obvious fractures were excluded. Six radiologists and six emergency physicians were asked to detect and localize fractures with (

To determine the diagnostic accuracy of MRI intravoxel incoherent motion (IVIM) when characterizing orbital lesions, which is challenging due to a wide range of locations and histologic types. This IRB-approved prospective single-center study enrolled participants presenting with an orbital lesion undergoing a 3-T MRI prior to surgery from December 2015 to July 2019. An IVIM sequence with 15 b values ranging from 0 to 2000 s/mm2 was performed. Two neuroradiologists, blinded to clinical data, individually analyzed morphological MRIs. They drew one region of interest inside each orbital lesion, providing apparent diffusion coefficient (ADC), true diffusion coefficient (D), perfusion fraction (f), and pseudodiffusion coefficient (D*) values. T test, Mann-Whitney U test, and receiver operating characteristic curve analyses were performed to discriminate between orbital lesions and to determine the diagnostic accuracy of the IVIM parameters. One hundred fifty-six participants (84 women and 72 men, mean age 54.4 ± 17.5 years) with 167 orbital lesions (98/167 [59%] benign lesions including 54 orbital inflammations and 69/167 [41%] malignant lesions including 32 lymphomas) were included in the study. ADC and D were significantly lower in malignant than in benign lesions: 0.8 × 10−3 mm2/s [0.45] versus 1.04 × 10−3 mm2/s [0.33], p

OBJECTIVES Distinguishing benign from malignant orbital lesions remains challenging both clinically and with imaging, leading to risky biopsies. The objective was to differentiate benign from malignant orbital lesions using radiomics on 3 T magnetic resonance imaging (MRI) examinations. MATERIALS AND METHODS This institutional review board-approved prospective single-center study enrolled consecutive patients presenting with an orbital lesion undergoing a 3 T MRI prior to surgery from December 2015 to July 2019. Radiomics features were extracted from 6 MRI sequences (T1-weighted images [WIs], DIXON-T2-WI, diffusion-WI, postcontrast DIXON-T1-WI) using the Pyradiomics software. Features were selected based on their intraobserver and interobserver reproducibility, nonredundancy, and with a sequential step forward feature selection method. Selected features were used to train and optimize a Random Forest algorithm on the training set (75%) with 5-fold cross-validation. Performance metrics were computed on a held-out test set (25%) with bootstrap 95% confidence intervals (95% CIs). Five residents, 4 general radiologists, and 3 expert neuroradiologists were evaluated on their ability to visually distinguish benign from malignant lesions on the test set. Performance comparisons between reader groups and the model were performed using McNemar test. The impact of clinical and categorizable imaging data on algorithm performance was also assessed. RESULTS A total of 200 patients (116 [58%] women and 84 [42%] men; mean age, 53.0 ± 17.9 years) with 126 of 200 (63%) benign and 74 of 200 (37%) malignant orbital lesions were included in the study. A total of 606 radiomics features were extracted. The best performing model on the training set was composed of 8 features including apparent diffusion coefficient mean value, maximum diameter on T1-WIs, and texture features. Area under the receiver operating characteristic curve, accuracy, sensitivity, and specificity on the test set were respectively 0.869 (95% CI, 0.834-0.898), 0.840 (95% CI, 0.806-0.874), 0.684 (95% CI, 0.615-0.751), and 0.935 (95% CI, 0.905-0.961). The radiomics model outperformed all reader groups, including expert neuroradiologists (P < 0.01). Adding clinical and categorizable imaging data did not significantly impact the algorithm performance (P = 0.49). CONCLUSIONS An MRI radiomics signature is helpful in differentiating benign from malignant orbital lesions and may outperform expert radiologists.

To assess the diagnostic performance of radiomic analysis using high temporal resolution (HTR)-dynamic contrast enhancement (DCE) MR sequences compared to BI-RADS analysis to distinguish benign from malignant breast lesions. We retrospectively analyzed data from consecutive women who underwent breast MRI including HTR-DCE MR sequencing for abnormal enhancing lesions and who had subsequent pathological analysis at our tertiary center. Semi-quantitative enhancement parameters and textural features were extracted. Temporal change across each phase of textural features in HTR-DCE MR sequences was calculated and called “kinetic textural parameters.” Statistical analysis by LASSO logistic regression and cross validation was performed to build a model. The diagnostic performance of the radiomic model was compared to the results of BI-RADS MR score analysis. We included 117 women with a mean age of 54 years (28–88). Of the 174 lesions analyzed, 75 were benign and 99 malignant. Seven semi-quantitative enhancement parameters and 57 textural features were extracted. Regression analysis selected 15 significant variables in a radiomic model (called “malignant probability score”) which displayed an AUC = 0.876 (sensitivity = 0.98, specificity = 0.52, accuracy = 0.78). The performance of the malignant probability score to distinguish benign from malignant breast lesions (AUC = 0.876, 95%CI 0.825–0.925) was significantly better than that of BI-RADS analysis (AUC = 0.831, 95%CI 0.769–0.892). The radiomic model significantly reduced false positives (42%) with the same number of missed cancers (n = 2). A radiomic model including kinetic textural features extracted from an HTR-DCE MR sequence improves diagnostic performance over BI-RADS analysis. • Radiomic analysis using HTR-DCE is of better diagnostic performance (AUC = 0.876) than conventional breast MRI reading with BI-RADS (AUC = 0.831) (p

Test a practical realignment approach to compensate the technical variability of MR radiomic features. T1 phantom images acquired on 2 scanners, FLAIR and contrast-enhanced T1-weighted (CE-T1w) images of 18 brain tumor patients scanned on both 1.5-T and 3-T scanners, and 36 T2-weighted (T2w) images of prostate cancer patients scanned in one of two centers were investigated. The ComBat procedure was used for harmonizing radiomic features. Differences in statistical distributions in feature values between 1.5- and 3-T images were tested before and after harmonization. The prostate studies were used to determine the impact of harmonization to distinguish between Gleason grades (GGs). In the phantom data, 40 out of 42 radiomic feature values were significantly different between the 2 scanners before harmonization and none after. In white matter regions, the statistical distributions of features were significantly different (p < 0.05) between the 1.5- and 3-T images for 37 out of 42 features in both FLAIR and CE-T1w images. After harmonization, no statistically significant differences were observed. In brain tumors, 41 (FLAIR) or 36 (CE-T1w) out of 42 features were significantly different between the 1.5- and 3-T images without harmonization, against 1 (FLAIR) or none (CE-T1w) with harmonization. In prostate studies, 636 radiomic features were significantly different between GGs after harmonization against 461 before. The ability to distinguish between GGs using radiomic features was increased after harmonization. ComBat harmonization efficiently removes inter-center technical inconsistencies in radiomic feature values and increases the sensitivity of studies using data from several scanners. • Radiomic feature values obtained using different MR scanners or imaging protocols can be harmonized by combining off-the-shelf image standardization and feature realignment procedures. • Harmonized radiomic features enable one to pool data from different scanners and centers without a substantial loss of statistical power caused by intra- and inter-center variability. • The proposed realignment method is applicable to radiomic features from different MR sequences and tumor types and does not rely on any phantom acquisition.

Magnetic resonance imaging (MRI) is the diagnostic cornerstone for precisely identifying acute ischaemic strokes and locating vascular occlusions, especially since mechanical thrombectomy has become a reference treatment. We observed that a post-contrast three-dimensional turbo-spin-echo T1-weighted sequence showed striking post-contrast vascular hyperintensities (PCVH) in ischaemic territories. We aimed to evaluate the prevalence and the meaning of this finding. This retrospective single centre study included 130 consecutive patients admitted for acute ischaemic stroke with a 3-T MRI performed in the first 12 h of symptom onset from September 2014 through September 2016. Two neuroradiologists blinded to clinical data analysed the first MRI assessments. The association between PCVH and clinical, radiological and follow-up findings was assessed, as well as inter- and intra-observer agreements. Of 130 patients, 105 (81%) had PCVH in the ischaemic territory. PCVH were associated with the presence of thrombus on susceptibility weighted imaging (p < 0.0001) and vascular occlusions on MR angiography (p < 0.0001). All patients with a visible thrombus had PCVH closely surrounding the clot. PCVH were associated with higher initial (p < 0.01) and follow-up (p < 0.01) National Institutes of Health Stroke Scale score, and higher mRS score (p < 0.05). Thrombectomy was the reference treatment for all patients with arterial occlusions. Inter- and intra-observer agreements for the detection of PCVH were excellent (κ = 0.95 and κ = 0.91, respectively). PCVH during acute strokes are a striking sensitive and reproducible tool for diagnosing and locating vascular occlusions. It may help triage patients who can benefit from thrombectomy. • Post-contrast vascular hyperintensities (PCVH) are a sensitive MR finding in acute stroke • PCVH are strongly associated with the presence and location of arterial occlusions • Inter- and intra-observer agreements for the detection of PCVH are excellent • PCVH are visible even in the case of significant motion artefacts • PCVH may help triage patients who can benefit from mechanical thrombectomy

The current staging system of central nervous system (CNS) germ cell tumors (GCT) includes a binary classification in “localized” or “metastatic” disease based on the absence or presence of leptomeningeal dissemination. Loco-regional tumor dissemination has been barely described whereas its accurate definition might be useful in terms of prognosis and treatment, especially for radiation therapy planning. Our purpose was therefore to describe MR patterns and prevalence of loco-regional extensions of these tumors. One hundred consecutive patients (median age 16.3 years, range 7–41 years, sex ratio 7:1) with a histologically or biologically proven CNS GCT were retrospectively included. Brain and spinal MRI at diagnosis were reviewed by two neuroradiologists focusing on MR patterns of primaries and loco-regional extensions. When available, follow-up MR exams were analyzed. Pure germinoma represented 84/100 cases. Primaries were unifocal pineal (n = 49/100), bifocal pineal and supra-sellar (n = 27/100), isolated supra-sellar (n = 21/100), isolated basal ganglia (n = 2/100) or trifocal pineal, supra-sellar, and basal ganglia (n = 1/100). Metastatic disease occurred in 6/100 patients (depicted by MRI in two and CSF cytology in four). Loco-regional extensions were observed in all patients and classified as follows: third ventricle (n = 88/100), thalamus (n = 47/100), midbrain (n = 42/100), distant sub-ependymal areas (n = 19/100), optic pathways (n = 19/100), lateral ventricles (n = 7/100), cavernous sinus (n = 6/100), corpus callosum (n = 4/100), and fourth ventricle (n = 3/100). CNS GCT present with specific loco-regional extensions at diagnosis. Improving their recognition will be helpful to further understand their prognostic value and potentially to optimize the treatment.

Background and purpose Multinodular and vacuolating neuronal tumor (MVNT) of the cerebrum is a rare brain lesion with suggestive imaging features. The aim of our study was to report the largest series of MVNTs so far and to evaluate the utility of advanced multiparametric magnetic resonance (MR) techniques. Methods This multicenter retrospective study was approved by our institutional research ethics board. From July 2014 to May 2019, two radiologists read in consensus the MR examinations of patients presenting with a lesion suggestive of an MVNT. They analyzed the lesions' MR characteristics on structural images and advanced multiparametric MR imaging. Results A total of 64 patients (29 women and 35 men, mean age 44.2 ± 15.1 years) from 25 centers were included. Lesions were all hyperintense on fluid-attenuated inversion recovery and T2-weighted imaging without post-contrast enhancement. The median relative apparent diffusion coefficient on diffusion-weighted imaging was 1.13 [interquartile range (IQR), 0.2]. Perfusion-weighted imaging showed no increase in perfusion, with a relative cerebral blood volume of 1.02 (IQR, 0.05) and a relative cerebral blood flow of 1.01 (IQR, 0.08). MR spectroscopy showed no abnormal peaks. Median follow-up was 2 (IQR, 1.2) years, without any changes in size. Conclusions A comprehensive characterization protocol including advanced multiparametric magnetic resonance imaging sequences showed no imaging patterns suggestive of malignancy in MVNTs. It might be useful to better characterize MVNTs.

Multinodular and vacuolating neuronal tumor of the cerebrum is a rare supratentorial brain tumor described for the first time in 2013. Here, we report 11 cases of infratentorial lesions showing similar striking imaging features consisting of a cluster of low T1-weighted imaging and high T2-FLAIR signal intensity nodules, which we referred to as multinodular and vacuolating posterior fossa lesions of unknown significance. No relationship was found between the location of the lesion and clinical symptoms. A T2-FLAIR hypointense central dot sign was present in images of 9/11 (82%) patients. Cortical involvement was present in 2/11 (18%) of patients. Only 1 nodule of 1 multinodular and vacuolating posterior fossa lesion of unknown significance showed enhancement on postcontrast T1WI. DWI, SWI, MRS, and PWI showed no malignant pattern. Lesions did not change in size or signal during a median follow-up of 3 years, suggesting that multinodular and vacuolating posterior fossa lesions of unknown significance are benign malformative lesions that do not require surgical intervention or removal.

PurposeThe DAWN trial (Diffusion weighted imaging or CT perfusion Assessment with clinical mismatch in the triage of Wake-up and late presenting strokes undergoing Neurointervention with Trevo) has demonstrated the benefits of thrombectomy in patients with unknown or late onset strokes, using automated software (RAPID) for measurement of infarct volume. Because RAPID is not available in all centers, we aimed to assess the accuracy and repeatability of visual infarct volume estimation by clinicians and the consequences for thrombectomy decisions based on the DAWN criteria.Materials and methods18 physicians, who routinely depend on MRI for acute stroke imaging, assessed 32 MR scans selected from a prospective databaseover two independent sessions. Raters were asked to visually estimate the diffusion weighted imaging (DWI) infarct volume for each case. Sensitivity, specificity, and accuracy of the estimated volumes were compared with the available RAPID measurements for various volume cut-off points. Thrombectomy decisions based on DAWN criteria with RAPID measurements and raters’ visual estimates were compared. Inter-rater and intra-rater agreement was measured using kappa statistics.ResultsThe mean accuracy of raters was ConclusionThe visual assessment of DWI infarct volume lacks accuracy and repeatability, and could lead to a significant number of erroneous decisions when applying the DAWN criteria.

BACKGROUND AND PURPOSE: MR imaging is the key examination in the follow-up of patients with MS, by identification of new high-signal T2 brain lesions. However, identifying new lesions when scrolling through 2 follow-up MR images can be difficult and time-consuming. Our aim was to compare an automated coregistration-fusion reading approach with the standard approach by identifying new high-signal T2 brain lesions in patients with multiple sclerosis during follow-up MR imaging. MATERIALS AND METHODS: This prospective monocenter study included 94 patients (mean age, 38.9 years) treated for MS with dimethyl fumarate from January 2014 to August 2016. One senior neuroradiologist and 1 junior radiologist checked for new high-signal T2 brain lesions, independently analyzing blinded image datasets with automated coregistration-fusion or the standard scroll-through approach with a 3-week delay between the 2 readings. A consensus reading with a second senior neuroradiologist served as a criterion standard for analyses. A Poisson regression and logistic and γ regressions were used to compare the 2 methods. Intra- and interobserver agreement was assessed by the κ coefficient. RESULTS: There were significantly more new high-signal T2 lesions per patient detected with the coregistration-fusion method (7 versus 4, P < .001). The coregistration-fusion method detected significantly more patients with at least 1 new high-signal T2 lesion (59% versus 46%, P = .02) and was associated with significantly faster overall reading time (86 seconds faster, P < .001) and higher reader confidence (91% versus 40%, P < 1 × 10(−4)). Inter- and intraobserver agreement was excellent for counting new high-signal T2 lesions. CONCLUSIONS: Our study showed that an automated coregistration-fusion method was more sensitive for detecting new high-signal T2 lesions in patients with MS and reducing reading time. This method could help to improve follow-up care.

Background and Purpose— We aimed to study the intrarater and interrater agreement of clinicians attributing DWI-ASPECTS (Diffusion-Weighted Imaging–Alberta Stroke Program Early Computed Tomography Scores) and DWI-FLAIR (Diffusion-Weighted Imaging–Fluid Attenuated Inversion Recovery) mismatch in patients with acute ischemic stroke referred for mechanical thrombectomy. Methods— Eighteen raters independently scored anonymized magnetic resonance imaging scans of 30 participants from a multicentre thrombectomy trial, in 2 different reading sessions. Agreement was measured using Fleiss κ and Cohen κ statistics. Results— Interrater agreement for DWI-ASPECTS was slight (κ=0.17 [0.14–0.21]). Four raters (22.2%) had a substantial (or higher) intrarater agreement. Dichotomization of the DWI-ASPECTS (0–5 versus 6–10 or 0–6 versus 7–10) increased the interrater agreement to a substantial level (κ=0.62 [0.48–0.75] and 0.68 [0.55–0.79], respectively) and more raters reached a substantial (or higher) intrarater agreement (17/18 raters [94.4%]). Interrater agreement for DWI-FLAIR mismatch was moderate (κ=0.43 [0.33–0.57]); 11 raters (61.1%) reached a substantial (or higher) intrarater agreement. Conclusions— Agreement between clinicians assessing DWI-ASPECTS and DWI-FLAIR mismatch may not be sufficient to make repeatable clinical decisions in mechanical thrombectomy. The dichotomization of the DWI-ASPECTS (0–5 versus 0–6 or 0–6 versus 7–10) improved interrater and intrarater agreement, however, its relevance for patients selection for mechanical thrombectomy needs to be validated in a randomized trial.

Objectifs Comparer une methode automatisee de lecture en Coregistration-Fusion (CF) avec la methode standard de detection de nouvelles lesions cerebrales en hypersignal T2 (HST2) chez des patients atteints de sclerose en plaques (SEP) au cours de leur suivi. Materiels et methodes Cette etude monocentrique approuvee par l’IRB incluait 94 patients traites par dimethyl fumarate de janvier 2014 a aout 2016. Un neuroradiologue senior et un radiologue junior ont verifie la presence de nouvelles lesions cerebrales HST2, analysant de maniere independante les ensembles d’images en aveugles avec la CF automatisee ou la methode standard de defilement manuel. Un delai de 3 semaines entre les deux lectures etait requis. Des tests de Poisson et de Wilcoxon ont ete utilises pour comparer les deux methodes. Les accords intra et inter-observateurs ont ete evalues par le coefficient Kappa. Resultats L’âge moyen des patients etait de 38,9 ans. Il y avait significativement plus de nouvelles lesions HST2 detectees avec la methode CF (712,2 versus 47,5 p Conclusion Notre etude a montre qu’une methode CF automatisee etait considerablement plus facile et plus sensible pour detecter de nouvelles lesions HST2 chez les patients atteints de SEP, ainsi que pour reduire le temps de lecture. Cette nouvelle methode pourrait considerablement ameliorer le suivi.

International audience; Pulmonary hyalinizing granuloma (PHG) is a rare disease characterized by single or multiple benign lung nodules mimicking lung neoplasma. Histologic analysis reveals homogenous hyaline lamellae, usually surrounded by collection of plasma cells, lymphocytes and histiocytes in a perivascular distribution. The clinical and radiological findings have been described in small series, but the long-term outcomes have rarely been reported. The objectives were to describe the clinical, radiological and outcomes of PHG in new cases and through a literature review. Patients with PHG were found by a multicenter search among French departments of internal medicine, pulmonology and anatomo-pathology. Review of the literature was made through the National Library of Medicine’s MEDLINE database using keywords “hyalinizing granuloma.” Five news cases and 135 cases of the literature were found. There were 82 men and 57 women, mean age at the diagnosis 44.6 years (15–83). Patients were frequently asymptomatic (n = 39, 27.4 %). The nodule was unique in 37 cases (28.9 %) and multiple in 91 cases (71.1 %). 18FDG PET scan revealed hypermetabolism of the nodule in 9/15 cases (60 %). A systemic disease was associated in 65 cases (mainly mediastinal and retroperitoneal fibrosis, autoimmune, tumoral or infectious disease or thromboembolism). The outcomes were evaluated in 73 patients when follow-up was available: 14 patients had a surgical resection of the nodule. Forty-five patients did not receive any immunosuppressive drug. Among these patients, 2 improved, 29 were stable and 14 worsened. Corticosteroids were used as a monotherapy in 19 patients and led to radiological improvement in 8 cases, stabilization in 8 cases and worsening in 3 cases. Five patients were treated with corticosteroids and at least one immunosuppressive drug and 4 patients improved. PHG is a rare benign disease, mimicking lung neoplasma, frequently associated with systemic diseases.