RÉSUMÉ
BACKGROUND: Multiple Sclerosis (MS) is a common autoimmune inflammatory disease of the central nervous system (CNS). Magnetic Resonance Imaging (MRI) allows a sensitive assessment of the CNS and is established for diagnostic, prognostic and (therapy-) monitoring purposes. Especially lesion counting in T2- or Fluid Attenuated Inversion Recovery (FLAIR)-weighted images plays a decisive role in clinical routine. Software-packages allowing an automatic evaluation of image data are increasingly established aiming a faster and improved workflow. These programs allow e.g. the counting, spatial attribution and volumetry of MS-lesions in FLAIR-weighted images. Research has shown that 3D-FLAIR-sequences are superior to 2D-FLAIR-sequences in visual evaluation of lesion burden in MS. An influence on the automatic analysis is expectable but not yet systematically studied. This work will therefore investigate the influence of 2D- and 3D datasets on the results of an automatic assessment. MATERIAL AND METHODS: In this prospective study, 80 Multiple Sclerosis patients underwent a clinically indicated routine MRI examination. The clinical routine protocol already including a 3D-FLAIR sequence was adapted by an additional 2D-FLAIR sequence also conform to the 2021 MAGNIMS-CMSCNAIMS consensus recommendations. To obtain a quantitative analysis for assessment of amount, dissemination and volume of the lesions, the acquired MR images were post-processed using the CE-certified Software mdbrain (mediaire, Berlin, Germany). The resulting data were statistically analysed using the paired t-test for normally distributed data and the Wilcoxon-signed-rank-test for not normally distributed data respectively. Demographic data and data such as the subtype, duration, severity and therapy of the disease were collected, pseudonymized and evaluated. RESULTS: There is a significant difference concerning the total number and lesion volume with more lesions being detected (2D: 29.7, +/- 20.22 sd; 3D: 40.1 +/- 31.67 sd; p < 0.0001) but lower total volume (2D: 6.24 +/- 6.11 sd; 3D: 5.39 +/- 6.37 sd; p < 0.0001) when using the 3D- sequence. Especially significantly more small lesions in the unspecific white matter and infratentorial region were detected by using the 3D-FLAIR sequence (p < 0.0001) compared to the 2D-FLAIR image. Main reason for the lower total volume in the 3D-FLAIR sequence was the calculated volume for periventricular lesions which was significantly beneath the calculated volume from the 2D-FLAIR sequence (p < 0.0001). CONCLUSION: Automatic lesion counting and volumetry is feasible with both 2D- and 3D-weightend FLAIR images. Still, it leads to partly significant differences even between two sequences that both are conform to the 2021 MAGNIMS-CMSCNAIMS consensus recommendations. This study contributes valuable insights into the impact of using different input data from the same patient for automated MS lesion evaluation.
Sujet(s)
Encéphale , Imagerie tridimensionnelle , Imagerie par résonance magnétique , Sclérose en plaques , Humains , Femelle , Adulte , Mâle , Sclérose en plaques/imagerie diagnostique , Sclérose en plaques/anatomopathologie , Adulte d'âge moyen , Encéphale/imagerie diagnostique , Encéphale/anatomopathologie , Études prospectives , Interprétation d'images assistée par ordinateur/méthodes , Jeune adulteRÉSUMÉ
BACKGROUND: Perivascular spaces (synonym: Virchow-Robin spaces) were first described over 150 years ago. They are defined as the fluid-filled spaces surrounding the small penetrating cerebral vessels. They gained growing scientific interest especially with the postulation of the so-called glymphatic system and their possible role in neurodegenerative and neuroinflammatory diseases. METHODS: PubMed was used for a systematic search with a focus on literature regarding MRI imaging and evaluation methods of perivascular spaces. Studies on human in-vivo imaging were included with a focus on studies involving healthy populations. No time frame was set. The nomenclature in the literature is very heterogeneous with terms like "large", "dilated", "enlarged" perivascular spaces whereas borders and definitions often remain unclear. This work generally talks about perivascular spaces. RESULTS: This review article discusses the morphologic MRI characteristics in different sequences. With the continual improvement of image quality, more and tinier structures can be depicted in detail. Visual analysis and semi or fully automated segmentation methods are briefly discussed. CONCLUSION: If they are looked for, perivascular spaces are apparent in basically every cranial MRI examination. Their physiologic or pathologic value is still under debate. KEY POINTS: · Perivascular spaces can be seen in basically every cranial MRI examination.. · Primarily T2-weighend sequences are used for visual analysis. Additional sequences are helpful for distinction from their differential diagnoses.. · There are promising approaches for the semi or fully automated segmentation of perivascular spaces with the possibility to collect more quantitative parameters.. CITATION FORMAT: · Seehafer S, Larsen N, Aludin S etâal. Perivascular spaces and where to find them - MRI imaging and evaluation methods. Fortschr Röntgenstr 2024; DOI: 10.1055/a-2254-5651.
RÉSUMÉ
Introduction: Unilateral pulmonary edema (UPE) is a potential complication after mitral valve surgery (MVS), and its cause is not yet fully understood. Definitions are inconsistent, and previous studies have reported wide variance in the incidence of UPE. This research aims at the evaluation of the Radiographic Assessment of Lung Edema (RALE) score concerning assessment of UPE after MVS in order to provide an accurate and consistent definition of this pathology. Methods and Results: Postoperative chest X-ray images of 676 patients after MVS (minimally invasive MVS, n = 434; conventional MVS, n = 242) were retrospectively analyzed concerning presence of UPE. UPE was diagnosed only after exclusion of other pathologies up until the eighth postoperative day. RALE values were calculated for each patient. ROC analysis was performed to assess diagnostic performance. UPE was diagnosed in 18 patients (2.8%). UPE occurred significantly more often in the MI-MVS group (p = 0.045; MI-MVS n = 15; C-MVS n = 3). Postoperative RALE values for the right hemithorax (Q1 + Q2) > 12 and the right-to-left RALE difference ((Q1 + Q2) - (Q3 + Q4)) > 13 provide a sensitivity of up to 100% and 94.4% and a specificity of up to 88.4% and 94.2% for UPE detection. Conclusion: The RALE score is a practical tool for assessment of chest X-ray images after MVS with regard to UPE and provides a clear definition of UPE. In addition, it enables objective comparability when assessing of the postoperative course. The given score thresholds provide a sensitivity and specificity of up to 94%. Further, UPE after MVS seems to be a rather rare pathology with an incidence of 2.6%.