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A 30-year-old man presented with minute-long episodes of vertigo and severe autophony. CVEMP showed a decreased threshold when testing the left side, potentially indicating SSCD. A subsequent MRI demonstrated a multi-lobulated, cystic mass in the temporal bone and the radiological diagnosis at that time was ELST. Tumor excision was performed, and microscopic examination of the excised material revealed fibrovascular tissue without signs of papillary or cystic projections. The conclusion of the histological assessment rendered a diagnosis of angiofibroma. We were unable to find a previous report of ENA originating around the endolymphatic sac.

Background Phase-contrast magnetic resonance imaging (PC-MRI) quantifies blood flow and velocity noninvasively. Challenges arise in neurovascular disorders due to small vessels. We evaluated the impact of voxel size, number of signal averages (NSA), and velocity encoding (VENC) on PC-MRI measurement accuracy and precision in a small-lumen vessel phantom. Methods We constructed an in vitro model with a constant flow rate using a 2.2-mm inner diameter plastic tube. A reservoir with a weight scale and timer was used as standard reference. Gradient-echo T1 weighted PC-MRI sequence was performed on a 3-T scanner with varying voxel size (2.5, 5.0, 7.5 mm3), NSA (1, 2, 3), and VENC (200, 300, 400 cm/s). We repeated measurements nine times per setting, calculating mean flow rate, maximum velocity, and least detectable difference (LDD). Results PC-MRI flow measurements were higher than standard reference values (mean ranging from 7.3 to 9.5 mL/s compared with 6.6 mL/s). Decreased voxel size improved accuracy, reducing flow rate measurements from 9.5 to 7.3 mL/s. The LDD for flow rate and velocity varied between 1 and 5%. The LDD for flow rate decreased with increased voxel size and NSA (p = 0.033 and 0.042). The LDD for velocity decreased with increased voxel size (p < 10-16). No change was observed when VENC varied. Conclusions PC-MRI overestimated flow. However, it has high precision in a small-vessel phantom with constant flow rate. Improved accuracy was obtained with increasing spatial resolution (smaller voxels). Improved precision was obtained with increasing signal-to-noise ratio (larger voxels and/or higher NSA). Relevance statement Phase-contrast MRI is clinically used in large vessels. To further investigate the possibility of using phase-contrast MRI for smaller intracranial vessels in neurovascular disorders, we need to understand how acquisition parameters affect phase-contrast MRI-measured flow rate and velocity in small vessels. Key points • PC-MRI measures

Premenstrual dysphoric disorder (PMDD) is a mood disorder for which selective progesterone receptor modulator (SPRM) treatment has been demonstrated to be beneficial. The neural signatures of this treatment have been so far identified as greater fronto-cingulate reactivity during aggressive response to provocation, but no changes in terms of gray matter structure. White matter has recently been found to differ between patients with PMDD and healthy controls. The present study thus sought to investigate the relationship between white matter volume and SPRM treatment in patients with PMDD. A pharmaco-neuroimaging study was conducted on patients with PMDD participating in a randomized controlled trial. Participants underwent magnetic resonance imaging before and after treatment randomization to ulipristal acetate (an SPRM), or placebo, for three months. The interaction effect of treatment by time on white matter volume (WMV) was assessed. Voxel based morphometry analyses were performed on both a whole brain exploratory level and on regions of interest. No treatment effect was observed on WMV in any region, including the anterior thalamic radiations, cingulum, forceps minor, fornix, inferior fronto-occipital fasciculus, superior cerebellar peduncle, superior longitudinal fasciculus, and uncinate fasciculus. This is the first finding to indicate that no white matter volume alterations follow three-month progesterone antagonism, suggesting that white matter volume does not participate in symptom relief upon SPRM treatment for PMDD.

Background Phase-contrast magnetic resonance imaging (PC-MRI) quantifies blood flow and velocity noninvasively. Challenges arise in neurovascular disorders due to small vessels. We evaluated the impact of voxel size, number of signal averages (NSA), and velocity encoding (VENC) on PC-MRI measurement accuracy and precision in a small-lumen vessel phantom. Methods We constructed an in vitro model with a constant flow rate using a 2.2-mm inner diameter plastic tube. A reservoir with a weight scale and timer was used as standard reference. Gradient-echo T1 weighted PC-MRI sequence was performed on a 3-T scanner with varying voxel size (2.5, 5.0, 7.5 mm3), NSA (1, 2, 3), and VENC (200, 300, 400 cm/s). We repeated measurements nine times per setting, calculating mean flow rate, maximum velocity, and least detectable difference (LDD). Results PC-MRI flow measurements were higher than standard reference values (mean ranging from 7.3 to 9.5 mL/s compared with 6.6 mL/s). Decreased voxel size improved accuracy, reducing flow rate measurements from 9.5 to 7.3 mL/s. The LDD for flow rate and velocity varied between 1 and 5%. The LDD for flow rate decreased with increased voxel size and NSA (p = 0.033 and 0.042). The LDD for velocity decreased with increased voxel size (p < 10-16). No change was observed when VENC varied. Conclusions PC-MRI overestimated flow. However, it has high precision in a small-vessel phantom with constant flow rate. Improved accuracy was obtained with increasing spatial resolution (smaller voxels). Improved precision was obtained with increasing signal-to-noise ratio (larger voxels and/or higher NSA). Relevance statement Phase-contrast MRI is clinically used in large vessels. To further investigate the possibility of using phase-contrast MRI for smaller intracranial vessels in neurovascular disorders, we need to understand how acquisition parameters affect phase-contrast MRI-measured flow rate and velocity in small vessels. Key points • PC-MRI measures

Premenstrual dysphoric disorder (PMDD) is a mood disorder for which selective progesterone receptor modulator (SPRM) treatment has been demonstrated to be beneficial. The neural signatures of this treatment have been so far identified as greater fronto-cingulate reactivity during aggressive response to provocation, but no changes in terms of gray matter structure. White matter has recently been found to differ between patients with PMDD and healthy controls. The present study thus sought to investigate the relationship between white matter volume and SPRM treatment in patients with PMDD. A pharmaco-neuroimaging study was conducted on patients with PMDD participating in a randomized controlled trial. Participants underwent magnetic resonance imaging before and after treatment randomization to ulipristal acetate (an SPRM), or placebo, for three months. The interaction effect of treatment by time on white matter volume (WMV) was assessed. Voxel based morphometry analyses were performed on both a whole brain exploratory level and on regions of interest. No treatment effect was observed on WMV in any region, including the anterior thalamic radiations, cingulum, forceps minor, fornix, inferior fronto-occipital fasciculus, superior cerebellar peduncle, superior longitudinal fasciculus, and uncinate fasciculus. This is the first finding to indicate that no white matter volume alterations follow three-month progesterone antagonism, suggesting that white matter volume does not participate in symptom relief upon SPRM treatment for PMDD.

Background Phase-contrast magnetic resonance imaging (PC-MRI) quantifies blood flow and velocity noninvasively. Challenges arise in neurovascular disorders due to small vessels. We evaluated the impact of voxel size, number of signal averages (NSA), and velocity encoding (VENC) on PC-MRI measurement accuracy and precision in a small-lumen vessel phantom. Methods We constructed an in vitro model with a constant flow rate using a 2.2-mm inner diameter plastic tube. A reservoir with a weight scale and timer was used as standard reference. Gradient-echo T1 weighted PC-MRI sequence was performed on a 3-T scanner with varying voxel size (2.5, 5.0, 7.5 mm3), NSA (1, 2, 3), and VENC (200, 300, 400 cm/s). We repeated measurements nine times per setting, calculating mean flow rate, maximum velocity, and least detectable difference (LDD). Results PC-MRI flow measurements were higher than standard reference values (mean ranging from 7.3 to 9.5 mL/s compared with 6.6 mL/s). Decreased voxel size improved accuracy, reducing flow rate measurements from 9.5 to 7.3 mL/s. The LDD for flow rate and velocity varied between 1 and 5%. The LDD for flow rate decreased with increased voxel size and NSA (p = 0.033 and 0.042). The LDD for velocity decreased with increased voxel size (p < 10-16). No change was observed when VENC varied. Conclusions PC-MRI overestimated flow. However, it has high precision in a small-vessel phantom with constant flow rate. Improved accuracy was obtained with increasing spatial resolution (smaller voxels). Improved precision was obtained with increasing signal-to-noise ratio (larger voxels and/or higher NSA). Relevance statement Phase-contrast MRI is clinically used in large vessels. To further investigate the possibility of using phase-contrast MRI for smaller intracranial vessels in neurovascular disorders, we need to understand how acquisition parameters affect phase-contrast MRI-measured flow rate and velocity in small vessels. Key points • PC-MRI measures

Premenstrual dysphoric disorder (PMDD) is a mood disorder for which selective progesterone receptor modulator (SPRM) treatment has been demonstrated to be beneficial. The neural signatures of this treatment have been so far identified as greater fronto-cingulate reactivity during aggressive response to provocation, but no changes in terms of gray matter structure. White matter has recently been found to differ between patients with PMDD and healthy controls. The present study thus sought to investigate the relationship between white matter volume and SPRM treatment in patients with PMDD. A pharmaco-neuroimaging study was conducted on patients with PMDD participating in a randomized controlled trial. Participants underwent magnetic resonance imaging before and after treatment randomization to ulipristal acetate (an SPRM), or placebo, for three months. The interaction effect of treatment by time on white matter volume (WMV) was assessed. Voxel based morphometry analyses were performed on both a whole brain exploratory level and on regions of interest. No treatment effect was observed on WMV in any region, including the anterior thalamic radiations, cingulum, forceps minor, fornix, inferior fronto-occipital fasciculus, superior cerebellar peduncle, superior longitudinal fasciculus, and uncinate fasciculus. This is the first finding to indicate that no white matter volume alterations follow three-month progesterone antagonism, suggesting that white matter volume does not participate in symptom relief upon SPRM treatment for PMDD.

Premenstrual dysphoric disorder (PMDD) is a mood disorder for which selective progesterone receptor modulator (SPRM) treatment has been demonstrated to be beneficial. The neural signatures of this treatment have been so far identified as greater fronto-cingulate reactivity during aggressive response to provocation, but no changes in terms of gray matter structure. White matter has recently been found to differ between patients with PMDD and healthy controls. The present study thus sought to investigate the relationship between white matter volume and SPRM treatment in patients with PMDD. A pharmaco-neuroimaging study was conducted on patients with PMDD participating in a randomized controlled trial. Participants underwent magnetic resonance imaging before and after treatment randomization to ulipristal acetate (an SPRM), or placebo, for three months. The interaction effect of treatment by time on white matter volume (WMV) was assessed. Voxel based morphometry analyses were performed on both a whole brain exploratory level and on regions of interest. No treatment effect was observed on WMV in any region, including the anterior thalamic radiations, cingulum, forceps minor, fornix, inferior fronto-occipital fasciculus, superior cerebellar peduncle, superior longitudinal fasciculus, and uncinate fasciculus. This is the first finding to indicate that no white matter volume alterations follow three-month progesterone antagonism, suggesting that white matter volume does not participate in symptom relief upon SPRM treatment for PMDD.

Radiological imaging to examine intracranial blood vessels is critical for preoperative planning and postoperative follow-up. Automated segmentation of cerebrovascular anatomy from Time-Of-Flight Magnetic Resonance Angiography (TOF-MRA) can provide radiologists with a more detailed and precise view of these vessels. This paper introduces a domain generalized artificial intelligence (AI) solution for volumetric monitoring of cerebrovascular structures from multi-center MRAs. Our approach utilizes a multi-task deep convolutional neural network (CNN) with a topology-aware loss function to learn voxel-wise segmentation of the cerebrovascular tree. We use Decorrelation Loss to achieve domain regularization for the encoder network and auxiliary tasks to provide additional regularization and enable the encoder to learn higher-level intermediate representations for improved performance. We compare our method to six state-of-the-art 3D vessel segmentation methods using retrospective TOF-MRA datasets from multiple private and public data sources scanned at six hospitals, with and without vascular pathologies. The proposed model achieved the best scores in all the qualitative performance measures. Furthermore, we have developed an AI-assisted Graphical User Interface (GUI) based on our research to assist radiologists in their daily work and establish a more efficient work process that saves time.

Background Hemodynamic changes are seen in the feeding arteries of arteriovenous malformations (AVMs). Phase-contrast MRI (PC-MRI) enables the acquisition of hemodynamic information from blood vessels. There is insufficient knowledge on which flow or velocity parameter best discriminates AVMs from healthy subjects. Purpose To evaluate PC-MRI-measured flow and velocity in feeding arteries of AVMs before and, when possible, also after treatment and to compare these measurements to corresponding measurements in healthy controls. Materials and Methods Highest flow (HF), lowest flow (LF), mean flow (MF), peak systolic velocity (PSV), end-diastolic velocity (EDV), and mean velocity (MV) were measured in feeding arteries in patients with intracranial AVMs using 2D PC-MRI at 3 T. Measurements were compared to previously reported values in healthy individuals. Values in patients above the 95th percentile in the healthy cohort were categorized as pathological. Nidus volume was measured using 3D time-of-flight MR angiography. Results Ten patients with diagnosed AVMs were examined with PC-MRI. Among these, three patients also underwent follow-up PC-MRI after treatment. Pathological velocities (PSV, EDV, and MV) were seen in all five subjects with a nidus larger or equal to 5.7 cm3, whereas pathological flow values were not seen in all, that is, pathologic HF in three, pathologic LF in two, and pathologic MF in two. After treatment, there was a decrease in flow and velocity (all measured parameters). After treatment, velocities (PSV, EDV, and MV) were no longer abnormal compared to healthy controls. Conclusion Patients with a large AVM nidus show pathological velocities, but less consistent flow increases. Following treatment, velocities normalize.

Radiological imaging to examine intracranial blood vessels is critical for preoperative planning and postoperative follow-up. Automated segmentation of cerebrovascular anatomy from Time-Of-Flight Magnetic Resonance Angiography (TOF-MRA) can provide radiologists with a more detailed and precise view of these vessels. This paper introduces a domain generalized artificial intelligence (AI) solution for volumetric monitoring of cerebrovascular structures from multi-center MRAs. Our approach utilizes a multi-task deep convolutional neural network (CNN) with a topology-aware loss function to learn voxel-wise segmentation of the cerebrovascular tree. We use Decorrelation Loss to achieve domain regularization for the encoder network and auxiliary tasks to provide additional regularization and enable the encoder to learn higher-level intermediate representations for improved performance. We compare our method to six state-of-the-art 3D vessel segmentation methods using retrospective TOF-MRA datasets from multiple private and public data sources scanned at six hospitals, with and without vascular pathologies. The proposed model achieved the best scores in all the qualitative performance measures. Furthermore, we have developed an AI-assisted Graphical User Interface (GUI) based on our research to assist radiologists in their daily work and establish a more efficient work process that saves time.

Background Fetal ultrasound has limitations, especially if the patient is obese or in cases with oligohydramnios. Magnetic resonance imaging (MRI) can then be used as a complement, but only few studies have focused on examinations in the second trimester. Purpose To validate MRI as a complement to diagnose fetal anomalies in the second trimester. Material and Methods This retrospective study retrieved data from January 2008 to July 2012 from the Fetal Medicine Unit and Department of Radiology at Uppsala University Hospital. Ultrasound and MRI findings were reviewed in 121 fetuses in relation to the final diagnosis, including postpartum follow-up and autopsy results. Results Of the 121 fetuses, 51 (42%) had a CNS anomaly and 70 (58%) a non-CNS anomaly diagnosed or suspected. MRI provided additional information in 21% of all cases without changing the management and revealed information that changed the management of the pregnancy in 13%. When a CNS anomaly was detected or suspected, the MRI provided additional information in 22% and changed the management in 10%. The corresponding figures for non-CNS cases were 21% and 16%, respectively. The proportion of cases with additional information that changed the management was especially high in patients with a BMI >30 kg/m2 (25%) and in patients with oligohydramnios (38%). In five cases in category III, false-positive ultrasound findings were identified. Conclusions MRI in the second trimester complements ultrasound and improves diagnosis of fetal CNS- and non-CNS anomalies especially when oligohydramnios or maternal obesity is present.

Radiological imaging to examine intracranial blood vessels is critical for preoperative planning and postoperative follow-up. Automated segmentation of cerebrovascular anatomy from Time-Of-Flight Magnetic Resonance Angiography (TOF-MRA) can provide radiologists with a more detailed and precise view of these vessels. This paper introduces a domain generalized artificial intelligence (AI) solution for volumetric monitoring of cerebrovascular structures from multi-center MRAs. Our approach utilizes a multi-task deep convolutional neural network (CNN) with a topology-aware loss function to learn voxel-wise segmentation of the cerebrovascular tree. We use Decorrelation Loss to achieve domain regularization for the encoder network and auxiliary tasks to provide additional regularization and enable the encoder to learn higher-level intermediate representations for improved performance. We compare our method to six state-of-the-art 3D vessel segmentation methods using retrospective TOF-MRA datasets from multiple private and public data sources scanned at six hospitals, with and without vascular pathologies. The proposed model achieved the best scores in all the qualitative performance measures. Furthermore, we have developed an AI-assisted Graphical User Interface (GUI) based on our research to assist radiologists in their daily work and establish a more efficient work process that saves time.

Background Hemodynamic changes are seen in the feeding arteries of arteriovenous malformations (AVMs). Phase-contrast MRI (PC-MRI) enables the acquisition of hemodynamic information from blood vessels. There is insufficient knowledge on which flow or velocity parameter best discriminates AVMs from healthy subjects. Purpose To evaluate PC-MRI-measured flow and velocity in feeding arteries of AVMs before and, when possible, also after treatment and to compare these measurements to corresponding measurements in healthy controls. Materials and Methods Highest flow (HF), lowest flow (LF), mean flow (MF), peak systolic velocity (PSV), end-diastolic velocity (EDV), and mean velocity (MV) were measured in feeding arteries in patients with intracranial AVMs using 2D PC-MRI at 3 T. Measurements were compared to previously reported values in healthy individuals. Values in patients above the 95th percentile in the healthy cohort were categorized as pathological. Nidus volume was measured using 3D time-of-flight MR angiography. Results Ten patients with diagnosed AVMs were examined with PC-MRI. Among these, three patients also underwent follow-up PC-MRI after treatment. Pathological velocities (PSV, EDV, and MV) were seen in all five subjects with a nidus larger or equal to 5.7 cm3, whereas pathological flow values were not seen in all, that is, pathologic HF in three, pathologic LF in two, and pathologic MF in two. After treatment, there was a decrease in flow and velocity (all measured parameters). After treatment, velocities (PSV, EDV, and MV) were no longer abnormal compared to healthy controls. Conclusion Patients with a large AVM nidus show pathological velocities, but less consistent flow increases. Following treatment, velocities normalize.

Background Fetal ultrasound has limitations, especially if the patient is obese or in cases with oligohydramnios. Magnetic resonance imaging (MRI) can then be used as a complement, but only few studies have focused on examinations in the second trimester. Purpose To validate MRI as a complement to diagnose fetal anomalies in the second trimester. Material and Methods This retrospective study retrieved data from January 2008 to July 2012 from the Fetal Medicine Unit and Department of Radiology at Uppsala University Hospital. Ultrasound and MRI findings were reviewed in 121 fetuses in relation to the final diagnosis, including postpartum follow-up and autopsy results. Results Of the 121 fetuses, 51 (42%) had a CNS anomaly and 70 (58%) a non-CNS anomaly diagnosed or suspected. MRI provided additional information in 21% of all cases without changing the management and revealed information that changed the management of the pregnancy in 13%. When a CNS anomaly was detected or suspected, the MRI provided additional information in 22% and changed the management in 10%. The corresponding figures for non-CNS cases were 21% and 16%, respectively. The proportion of cases with additional information that changed the management was especially high in patients with a BMI >30 kg/m2 (25%) and in patients with oligohydramnios (38%). In five cases in category III, false-positive ultrasound findings were identified. Conclusions MRI in the second trimester complements ultrasound and improves diagnosis of fetal CNS- and non-CNS anomalies especially when oligohydramnios or maternal obesity is present.

Sediments contaminated with hazardous metals pose risks to humans and wildlife, yet viable management options are scarce. In a series of laboratory experiments, we characterized Polonite® – an activated calcium-silicate – as a novel sorbent for thin-layer capping of metal-contaminated sediments. We tested a fine-grained by-product from the Polonite production as a cheap and sustainable sorbent. First, Polonite was reacted with solutions of Cu, Pb, and Zn, and the surface chemistry of the Polonite was examined using, e.g., scanning electron microscopy to investigate metal sorption mechanisms. Batch experiments were conducted by adding Polonite to industrially contaminated harbor sediment to determine sorption kinetics and isotherms. Importantly, we measured if the Polonite could reduce metal bioavailability to sediment fauna by performing digestive fluid extraction (DFE). Finally, a cap placement technique was studied by applying a Polonite slurry in sedimentation columns. The results showed rapid metal sorption to Polonite via several mechanisms, including hydroxide and carbonate precipitation, and complexation with metal oxides on the Polonite surface. Isotherm data revealed that the sediment uptake capacity (Kf) for Cu, Pb, and Zn increased by a factor of 25, 21, and 14, respectively, after addition of 5% Polonite. The bioavailability of Cu, Pb, and Zn was reduced by 70%, 65%, and 54%, respectively, after a 25% Polonite addition. In conclusion, we propose that sediment treatment with low doses of the Polonite by-product can be a cheap, sustainable, and effective remediation method compared to other more intrusive methods such as dredging or conventional isolation capping.

Background Hemodynamic changes are seen in the feeding arteries of arteriovenous malformations (AVMs). Phase-contrast MRI (PC-MRI) enables the acquisition of hemodynamic information from blood vessels. There is insufficient knowledge on which flow or velocity parameter best discriminates AVMs from healthy subjects. Purpose To evaluate PC-MRI-measured flow and velocity in feeding arteries of AVMs before and, when possible, also after treatment and to compare these measurements to corresponding measurements in healthy controls. Materials and Methods Highest flow (HF), lowest flow (LF), mean flow (MF), peak systolic velocity (PSV), end-diastolic velocity (EDV), and mean velocity (MV) were measured in feeding arteries in patients with intracranial AVMs using 2D PC-MRI at 3 T. Measurements were compared to previously reported values in healthy individuals. Values in patients above the 95th percentile in the healthy cohort were categorized as pathological. Nidus volume was measured using 3D time-of-flight MR angiography. Results Ten patients with diagnosed AVMs were examined with PC-MRI. Among these, three patients also underwent follow-up PC-MRI after treatment. Pathological velocities (PSV, EDV, and MV) were seen in all five subjects with a nidus larger or equal to 5.7 cm3, whereas pathological flow values were not seen in all, that is, pathologic HF in three, pathologic LF in two, and pathologic MF in two. After treatment, there was a decrease in flow and velocity (all measured parameters). After treatment, velocities (PSV, EDV, and MV) were no longer abnormal compared to healthy controls. Conclusion Patients with a large AVM nidus show pathological velocities, but less consistent flow increases. Following treatment, velocities normalize.

Radiological imaging to examine intracranial blood vessels is critical for preoperative planning and postoperative follow-up. Automated segmentation of cerebrovascular anatomy from Time-Of-Flight Magnetic Resonance Angiography (TOF-MRA) can provide radiologists with a more detailed and precise view of these vessels. This paper introduces a domain generalized artificial intelligence (AI) solution for volumetric monitoring of cerebrovascular structures from multi-center MRAs. Our approach utilizes a multi-task deep convolutional neural network (CNN) with a topology-aware loss function to learn voxel-wise segmentation of the cerebrovascular tree. We use Decorrelation Loss to achieve domain regularization for the encoder network and auxiliary tasks to provide additional regularization and enable the encoder to learn higher-level intermediate representations for improved performance. We compare our method to six state-of-the-art 3D vessel segmentation methods using retrospective TOF-MRA datasets from multiple private and public data sources scanned at six hospitals, with and without vascular pathologies. The proposed model achieved the best scores in all the qualitative performance measures. Furthermore, we have developed an AI-assisted Graphical User Interface (GUI) based on our research to assist radiologists in their daily work and establish a more efficient work process that saves time.

Background Fetal ultrasound has limitations, especially if the patient is obese or in cases with oligohydramnios. Magnetic resonance imaging (MRI) can then be used as a complement, but only few studies have focused on examinations in the second trimester. Purpose To validate MRI as a complement to diagnose fetal anomalies in the second trimester. Material and Methods This retrospective study retrieved data from January 2008 to July 2012 from the Fetal Medicine Unit and Department of Radiology at Uppsala University Hospital. Ultrasound and MRI findings were reviewed in 121 fetuses in relation to the final diagnosis, including postpartum follow-up and autopsy results. Results Of the 121 fetuses, 51 (42%) had a CNS anomaly and 70 (58%) a non-CNS anomaly diagnosed or suspected. MRI provided additional information in 21% of all cases without changing the management and revealed information that changed the management of the pregnancy in 13%. When a CNS anomaly was detected or suspected, the MRI provided additional information in 22% and changed the management in 10%. The corresponding figures for non-CNS cases were 21% and 16%, respectively. The proportion of cases with additional information that changed the management was especially high in patients with a BMI >30 kg/m2 (25%) and in patients with oligohydramnios (38%). In five cases in category III, false-positive ultrasound findings were identified. Conclusions MRI in the second trimester complements ultrasound and improves diagnosis of fetal CNS- and non-CNS anomalies especially when oligohydramnios or maternal obesity is present.

Background Hemodynamic changes are seen in the feeding arteries of arteriovenous malformations (AVMs). Phase-contrast MRI (PC-MRI) enables the acquisition of hemodynamic information from blood vessels. There is insufficient knowledge on which flow or velocity parameter best discriminates AVMs from healthy subjects. Purpose To evaluate PC-MRI-measured flow and velocity in feeding arteries of AVMs before and, when possible, also after treatment and to compare these measurements to corresponding measurements in healthy controls. Materials and Methods Highest flow (HF), lowest flow (LF), mean flow (MF), peak systolic velocity (PSV), end-diastolic velocity (EDV), and mean velocity (MV) were measured in feeding arteries in patients with intracranial AVMs using 2D PC-MRI at 3 T. Measurements were compared to previously reported values in healthy individuals. Values in patients above the 95th percentile in the healthy cohort were categorized as pathological. Nidus volume was measured using 3D time-of-flight MR angiography. Results Ten patients with diagnosed AVMs were examined with PC-MRI. Among these, three patients also underwent follow-up PC-MRI after treatment. Pathological velocities (PSV, EDV, and MV) were seen in all five subjects with a nidus larger or equal to 5.7 cm3, whereas pathological flow values were not seen in all, that is, pathologic HF in three, pathologic LF in two, and pathologic MF in two. After treatment, there was a decrease in flow and velocity (all measured parameters). After treatment, velocities (PSV, EDV, and MV) were no longer abnormal compared to healthy controls. Conclusion Patients with a large AVM nidus show pathological velocities, but less consistent flow increases. Following treatment, velocities normalize.

Radiological imaging to examine intracranial blood vessels is critical for preoperative planning and postoperative follow-up. Automated segmentation of cerebrovascular anatomy from Time-Of-Flight Magnetic Resonance Angiography (TOF-MRA) can provide radiologists with a more detailed and precise view of these vessels. This paper introduces a domain generalized artificial intelligence (AI) solution for volumetric monitoring of cerebrovascular structures from multi-center MRAs. Our approach utilizes a multi-task deep convolutional neural network (CNN) with a topology-aware loss function to learn voxel-wise segmentation of the cerebrovascular tree. We use Decorrelation Loss to achieve domain regularization for the encoder network and auxiliary tasks to provide additional regularization and enable the encoder to learn higher-level intermediate representations for improved performance. We compare our method to six state-of-the-art 3D vessel segmentation methods using retrospective TOF-MRA datasets from multiple private and public data sources scanned at six hospitals, with and without vascular pathologies. The proposed model achieved the best scores in all the qualitative performance measures. Furthermore, we have developed an AI-assisted Graphical User Interface (GUI) based on our research to assist radiologists in their daily work and establish a more efficient work process that saves time.

Background Fetal ultrasound has limitations, especially if the patient is obese or in cases with oligohydramnios. Magnetic resonance imaging (MRI) can then be used as a complement, but only few studies have focused on examinations in the second trimester. Purpose To validate MRI as a complement to diagnose fetal anomalies in the second trimester. Material and Methods This retrospective study retrieved data from January 2008 to July 2012 from the Fetal Medicine Unit and Department of Radiology at Uppsala University Hospital. Ultrasound and MRI findings were reviewed in 121 fetuses in relation to the final diagnosis, including postpartum follow-up and autopsy results. Results Of the 121 fetuses, 51 (42%) had a CNS anomaly and 70 (58%) a non-CNS anomaly diagnosed or suspected. MRI provided additional information in 21% of all cases without changing the management and revealed information that changed the management of the pregnancy in 13%. When a CNS anomaly was detected or suspected, the MRI provided additional information in 22% and changed the management in 10%. The corresponding figures for non-CNS cases were 21% and 16%, respectively. The proportion of cases with additional information that changed the management was especially high in patients with a BMI >30 kg/m2 (25%) and in patients with oligohydramnios (38%). In five cases in category III, false-positive ultrasound findings were identified. Conclusions MRI in the second trimester complements ultrasound and improves diagnosis of fetal CNS- and non-CNS anomalies especially when oligohydramnios or maternal obesity is present.

Background Phase-contrast magnetic resonance imaging (PC-MRI) quantifies blood flow and velocity noninvasively. Challenges arise in neurovascular disorders due to small vessels. We evaluated the impact of voxel size, number of signal averages (NSA), and velocity encoding (VENC) on PC-MRI measurement accuracy and precision in a small-lumen vessel phantom. Methods We constructed an in vitro model with a constant flow rate using a 2.2-mm inner diameter plastic tube. A reservoir with a weight scale and timer was used as standard reference. Gradient-echo T1 weighted PC-MRI sequence was performed on a 3-T scanner with varying voxel size (2.5, 5.0, 7.5 mm3), NSA (1, 2, 3), and VENC (200, 300, 400 cm/s). We repeated measurements nine times per setting, calculating mean flow rate, maximum velocity, and least detectable difference (LDD). Results PC-MRI flow measurements were higher than standard reference values (mean ranging from 7.3 to 9.5 mL/s compared with 6.6 mL/s). Decreased voxel size improved accuracy, reducing flow rate measurements from 9.5 to 7.3 mL/s. The LDD for flow rate and velocity varied between 1 and 5%. The LDD for flow rate decreased with increased voxel size and NSA (p = 0.033 and 0.042). The LDD for velocity decreased with increased voxel size (p < 10-16). No change was observed when VENC varied. Conclusions PC-MRI overestimated flow. However, it has high precision in a small-vessel phantom with constant flow rate. Improved accuracy was obtained with increasing spatial resolution (smaller voxels). Improved precision was obtained with increasing signal-to-noise ratio (larger voxels and/or higher NSA). Relevance statement Phase-contrast MRI is clinically used in large vessels. To further investigate the possibility of using phase-contrast MRI for smaller intracranial vessels in neurovascular disorders, we need to understand how acquisition parameters affect phase-contrast MRI-measured flow rate and velocity in small vessels. Key points • PC-MRI measures

Segmentation of major brain vessels is very important for the diagnosis of cerebrovascular disorders and subsequent surgical planning. Vessel segmentation is an important pre-processing step for a wide range of algorithms for the automatic diagnosis or treatment of several vascular pathologies and as such, it is valuable to have a well-performing vascular segmentation pipeline. In this article, we propose an end-to-end multiscale residual dual attention deep neural network for resilient major brain vessel segmentation. In the proposed network, the encoder and decoder blocks of the U-Net are replaced with the multi-level atrous residual blocks to enhance the learning capability by increasing the receptive field to extract the various semantic coarse- and fine- grained features. Dual attention block is incorporated in the bottleneck to perform effective multiscale information fusion to obtain detailed structure of blood vessels. The methods were evaluated on the publicly available TubeTK data set. The proposed method outperforms the state-of-the-art techniques with dice of 0.79 on the whole-brain prediction. The statistical and visual assessments indicate that proposed network is robust to outliers and maintains higher consistency in vessel continuity than the traditional U-Net and its variations.

Volumetric quantification of tumors is usually done manually by radiologists requiring precious medical time and suffering from inter-observer variability. An automatic tool for accurate volume quantification of post-operative glioblastoma would reduce the workload of radiologists and improve the quality of follow-up monitoring and patient care. This paper deals with the 3-D segmentation of post-operative glioblastoma using channel squeeze and excitation based attention gated network (ASE-Net). The proposed deep neural network has a 3-D encoder and decoder based architecture with channel squeeze and excitation (CSE) blocks and attention blocks. The CSE block reduces the dependency on space information and put more emphasize on the channel information. The attention block suppresses the feature maps of irrelevant background and helps highlighting the relevant feature maps. The Uppsala university data set used has post-operative follow-up MRI scans for fifteen patients. A patient specific fine-tuning approach is used to improve the segmentation results for each patient. ASE-Net is also cross-validated with BraTS-2021 data set. The mean dice score of five-fold cross validation results with BraTS-2021 data set for enhanced tumor is 0.8244. The proposed network outperforms the competing networks like U-Net, Attention U-Net and Res U-Net. On the Uppsala University glioblastoma data set, the mean Dice score obtained with the proposed network is 0.7084, Hausdorff Distance-95 is 7.14 and the mean volumetric similarity achieved is 0.8579. With fine-tuning the pre-trained network, the mean dice score improved to 0.7368, Hausdorff Distance-95 decreased to 6.10 and volumetric similarity improved to 0.8736. ASE-Net outperforms the competing networks and can be used for volumetric quantification of post-operative glioblastoma from follow-up MRI scans. The network significantly reduces the probability of over segmentation.

This study investigated a new material – activated limestone – that was added to nutrient rich Baltic Sea bottom sediment with the ambition to stop nutrient release and thereby reduce eutrophication. Our results show that the activated limestone was very efficient in stopping leakage of phosphorus from eutrophic sediments collected at a fish farm on Åland from which fish faeces have contributed to the nutrient load and accumulation in its surrounding waters. The phosphate release from the sediment was completely stopped by addition of 600 g/m2 activated limestone. In addition, the risk of potential side effects, such as greenhouse gas emissions, was measured and found to be low after addition of the activated limestone.

Background Phase-contrast magnetic resonance imaging (PC-MRI) quantifies blood flow and velocity noninvasively. Challenges arise in neurovascular disorders due to small vessels. We evaluated the impact of voxel size, number of signal averages (NSA), and velocity encoding (VENC) on PC-MRI measurement accuracy and precision in a small-lumen vessel phantom. Methods We constructed an in vitro model with a constant flow rate using a 2.2-mm inner diameter plastic tube. A reservoir with a weight scale and timer was used as standard reference. Gradient-echo T1 weighted PC-MRI sequence was performed on a 3-T scanner with varying voxel size (2.5, 5.0, 7.5 mm3), NSA (1, 2, 3), and VENC (200, 300, 400 cm/s). We repeated measurements nine times per setting, calculating mean flow rate, maximum velocity, and least detectable difference (LDD). Results PC-MRI flow measurements were higher than standard reference values (mean ranging from 7.3 to 9.5 mL/s compared with 6.6 mL/s). Decreased voxel size improved accuracy, reducing flow rate measurements from 9.5 to 7.3 mL/s. The LDD for flow rate and velocity varied between 1 and 5%. The LDD for flow rate decreased with increased voxel size and NSA (p = 0.033 and 0.042). The LDD for velocity decreased with increased voxel size (p < 10-16). No change was observed when VENC varied. Conclusions PC-MRI overestimated flow. However, it has high precision in a small-vessel phantom with constant flow rate. Improved accuracy was obtained with increasing spatial resolution (smaller voxels). Improved precision was obtained with increasing signal-to-noise ratio (larger voxels and/or higher NSA). Relevance statement Phase-contrast MRI is clinically used in large vessels. To further investigate the possibility of using phase-contrast MRI for smaller intracranial vessels in neurovascular disorders, we need to understand how acquisition parameters affect phase-contrast MRI-measured flow rate and velocity in small vessels. Key points • PC-MRI measures

Premenstrual dysphoric disorder (PMDD) is a mood disorder for which selective progesterone receptor modulator (SPRM) treatment has been demonstrated to be beneficial. The neural signatures of this treatment have been so far identified as greater fronto-cingulate reactivity during aggressive response to provocation, but no changes in terms of gray matter structure. White matter has recently been found to differ between patients with PMDD and healthy controls. The present study thus sought to investigate the relationship between white matter volume and SPRM treatment in patients with PMDD. A pharmaco-neuroimaging study was conducted on patients with PMDD participating in a randomized controlled trial. Participants underwent magnetic resonance imaging before and after treatment randomization to ulipristal acetate (an SPRM), or placebo, for three months. The interaction effect of treatment by time on white matter volume (WMV) was assessed. Voxel based morphometry analyses were performed on both a whole brain exploratory level and on regions of interest. No treatment effect was observed on WMV in any region, including the anterior thalamic radiations, cingulum, forceps minor, fornix, inferior fronto-occipital fasciculus, superior cerebellar peduncle, superior longitudinal fasciculus, and uncinate fasciculus. This is the first finding to indicate that no white matter volume alterations follow three-month progesterone antagonism, suggesting that white matter volume does not participate in symptom relief upon SPRM treatment for PMDD.

Background: Paired cerebral blood flow (CBF) measurement is usually acquired before and after vasoactive stimulus to estimate cerebrovascular reserve (CVR). However, CVR may be confounded because of variations in time-to-maximum CBF response (tmax) following acetazolamide injection. With a mathematical model, CVR can be calculated insensitive to variations in tmax, and a model offers the possibility to calculate additional model-derived parameters. A model that describes the temporal CBF response following a vasodilating acetazolamide injection is proposed and evaluated. Methods: A bi-exponential model was adopted and fitted to four CBF measurements acquired using arterial spin labelling before and initialised at 5, 15 and 25 min after acetazolamide injection in a total of fifteen patients with Moyamoya disease. Curve fitting was performed using a non-linear least squares method with a priori constraints based on simulations. Results: Goodness of fit (mean absolute error) varied between 0.30 and 0.62 ml·100 g-1·min-1. Model-derived CVR was significantly higher compared to static CVR measures. Maximum CBF increase occurred earlier in healthy- compared to diseased vascular regions. Conclusions: The proposed mathematical model offers the possibility to calculate CVR insensitive to variations in time to maximum CBF response which gives a more detailed characterisation of CVR compared to static CVR measures. Although the mathematical model adapts generally well to this dataset of patients with MMD it should be considered as experimental; hence, further studies in healthy populations and other patient cohorts are warranted.

Background Fetal ultrasound has limitations, especially if the patient is obese or in cases with oligohydramnios. Magnetic resonance imaging (MRI) can then be used as a complement, but only few studies have focused on examinations in the second trimester. Purpose To validate MRI as a complement to diagnose fetal anomalies in the second trimester. Material and Methods This retrospective study retrieved data from January 2008 to July 2012 from the Fetal Medicine Unit and Department of Radiology at Uppsala University Hospital. Ultrasound and MRI findings were reviewed in 121 fetuses in relation to the final diagnosis, including postpartum follow-up and autopsy results. Results Of the 121 fetuses, 51 (42%) had a CNS anomaly and 70 (58%) a non-CNS anomaly diagnosed or suspected. MRI provided additional information in 21% of all cases without changing the management and revealed information that changed the management of the pregnancy in 13%. When a CNS anomaly was detected or suspected, the MRI provided additional information in 22% and changed the management in 10%. The corresponding figures for non-CNS cases were 21% and 16%, respectively. The proportion of cases with additional information that changed the management was especially high in patients with a BMI >30 kg/m2 (25%) and in patients with oligohydramnios (38%). In five cases in category III, false-positive ultrasound findings were identified. Conclusions MRI in the second trimester complements ultrasound and improves diagnosis of fetal CNS- and non-CNS anomalies especially when oligohydramnios or maternal obesity is present.

OBJECTIVE: A small posterior fossa (PF) has been hypothesized to explain the increased incidence of trigeminal neuralgia (TN) in females and could make microvascular decompression (MVD) more challenging. The aim of this study was to investigate the association between the PF volume and dimensions in relation to biological sex, type of neurovascular conflict (NVC), and outcome after MVD in classic TN. METHODS: In this observational study, 84 patients with TN operated on with MVD with a preoperative head computed tomography(CT) scan were included. Eighty-two adults without TN who had undergone head CT for other reasons were included as controls. PF volume and dimensions (x-axis, y-axis, and z-axis) were evaluated on the CT scans. For the patients with TN, Barrow Neurological Institute (BNI) grade was evaluated 6 months after MVD. RESULTS: There was no difference in PF volume or dimensions between the patients with TN and controls. Women showed a smaller volume and narrower (x-axis) PF than men, but these differences did not manifest when comparing patients with TN and controls within each sex. Patients with an NVC involving the superior cerebellar artery had a narrower (x-axis) and shorter (y-axis) PF than did patients with an NVC resulting from other arteries. PF volume or dimensions were not associated with BNI grade after MVD. CONCLUSIONS: PF anatomy was related to the NVC type but did not differ between patients with TN and controls and was not related to the surgical outcome after MVD.

Many women are pregnant during several percent of their lives. Occasionally, there is a need for neuroradiological examinations during pregnancy or lactation. In our clinical work, we regularly see that female patients are being withheld relevant diagnostic scans during pregnancy, due to insufficient knowledge or an unbalanced comparison between benefits and risks. This article describes the current knowledge regarding conditions for performing CT and MRI scans in pregnant and lactating patients, including the use of contrast media. PET scans and reactions to contrast media are briefly mentioned, but interventional radiology is not discussed., Neuroradiologisk DT och MR utförs rutinmässigt på gravida, efter att remisserna bedömts ur ett berättigande­perspektiv. Vid neuroradiologisk DT (hjärna/hals/halsrygg) ligger fostret inte i det primära strålfältet, och dosen som når fostret via spridd strålning ligger långt under signifikanta gränsvärden. MR utan kontrastmedel under graviditet har inga påvisade risker, men låg energideposition bör eftersträvas vid planering av undersökningen. Jodkontrastmedel kan användas hos gravida om det föreligger en tydlig medicinsk indikation, men gadoliniumkontrastmedel bör undvikas i möjligaste mån. Amning kan fortsätta som vanligt efter att jod- eller gadoliniumkontrastmedel har givits.

PURPOSE: Moyamoya (MM) disease is characterized by progressive intracranial arterial stenosis. Patients commonly need revascularization surgery to optimize cerebral blood flow (CBF). Estimation of CBF and cerebrovascular reserve (CVR) is therefore necessary before and after surgery. However, assessment of CBF before and after indirect revascularization surgery with the multiple burr hole (MBH) technique in MM has not been studied extensively. In this study, we describe our initial experience using arterial spin labeling magnetic resonance perfusion imaging (ASL-MRI) for CBF and CVR assessment before and after indirect MBH revascularization surgery in MM patients. METHODS: Eleven MM patients (initial age 6-50 years, 1 male/10 female) with 19 affected hemispheres were included. A total of 35 ASL-MRI examinations were performed using a 3D-pCASL acquisition before and after i.v. acetazolamide challenge (1000 mg in adults and 10 mg/kg in children). Twelve MBH procedures were performed in seven patients. The first follow-up ASL-MRI was performed 7-21 (mean 12) months after surgery. RESULTS: Before surgery, CBF was 46 ± 16 (mean ± SD) ml/100 g/min and CVR after acetazolamide challenge was 38.5 ± 9.9 (mean ± SD)% in the most affected territory (middle cerebral artery). In cases in which surgery was not performed, CVR was 56 ± 12 (mean ± SD)% in affected hemispheres. After MBH surgery, there was a relative change in CVR compared to baseline (preop) of + 23.5 ± 23.3% (mean ± SD). There were no new ischemic events. CONCLUSION: Using ASL-MRI we followed changes in CBF and CVR in patients with MM. The technique was encouraging for assessments before and after revascularization surgery.

OBJECTIVE: A small posterior fossa (PF) has been hypothesized to explain the increased incidence of trigeminal neuralgia (TN) in females and could make microvascular decompression (MVD) more challenging. The aim of this study was to investigate the association between the PF volume and dimensions in relation to biological sex, type of neurovascular conflict (NVC), and outcome after MVD in classic TN. METHODS: In this observational study, 84 patients with TN operated on with MVD with a preoperative head computed tomography(CT) scan were included. Eighty-two adults without TN who had undergone head CT for other reasons were included as controls. PF volume and dimensions (x-axis, y-axis, and z-axis) were evaluated on the CT scans. For the patients with TN, Barrow Neurological Institute (BNI) grade was evaluated 6 months after MVD. RESULTS: There was no difference in PF volume or dimensions between the patients with TN and controls. Women showed a smaller volume and narrower (x-axis) PF than men, but these differences did not manifest when comparing patients with TN and controls within each sex. Patients with an NVC involving the superior cerebellar artery had a narrower (x-axis) and shorter (y-axis) PF than did patients with an NVC resulting from other arteries. PF volume or dimensions were not associated with BNI grade after MVD. CONCLUSIONS: PF anatomy was related to the NVC type but did not differ between patients with TN and controls and was not related to the surgical outcome after MVD.

BACKGROUND: Trigeminal neuralgia (TN), a severe type of facial pain, is mainly caused by a neurovascular conflict (NVC). The severity of the NVC seems associated with the outcome following microvascular decompression (MVD) surgery. This study aimed to investigate the outcome after MVD and whether it is affected by NVC severity and sex. METHODS: TN patients (n = 109) were followed for 5 to 10 years after MVD. Barrow Neurology Index (BNI), Patients Global Impression of Change (PGIC), complications, and time to relapse were evaluated. The NVC severity was retrospectively reviewed from presurgical MRI. Demographic and clinical factors and NVC severity were analyzed for potential association with outcome after MVD. RESULTS: The success rate (BNI ≤ 2) was 80% after 5 to 10 years follow-up for TN patients with severe NVC (grade 2-3) and 56% for TN patients with mild NVC (grade 0-1, P = 0.003). No sex difference was observed in outcome for patients with both mild (P = 0.924) and severe NVC (P = 0.883) respectively. Three patients (2.8%) during the hospital stay, and two patients (1.8%) at 6 weeks, experienced a complication requiring invasive treatment. At long-term 52/109 patients (47.7%) reported some type of persistent adverse event, of which the majority were mild and required no treatment. CONCLUSIONS: MVD offers an 80% probability of long-term pain relief in TN patients with severe NVC, with low frequency of serious complications. NVC severity significantly affects outcome after MVD, while no sex differences in outcome were found. In consistency with previous work, the results stress the importance of adequate neuroradiological assessment of the NVC for preoperative patient selection.

PURPOSE: Moyamoya (MM) disease is characterized by progressive intracranial arterial stenosis. Patients commonly need revascularization surgery to optimize cerebral blood flow (CBF). Estimation of CBF and cerebrovascular reserve (CVR) is therefore necessary before and after surgery. However, assessment of CBF before and after indirect revascularization surgery with the multiple burr hole (MBH) technique in MM has not been studied extensively. In this study, we describe our initial experience using arterial spin labeling magnetic resonance perfusion imaging (ASL-MRI) for CBF and CVR assessment before and after indirect MBH revascularization surgery in MM patients. METHODS: Eleven MM patients (initial age 6-50 years, 1 male/10 female) with 19 affected hemispheres were included. A total of 35 ASL-MRI examinations were performed using a 3D-pCASL acquisition before and after i.v. acetazolamide challenge (1000 mg in adults and 10 mg/kg in children). Twelve MBH procedures were performed in seven patients. The first follow-up ASL-MRI was performed 7-21 (mean 12) months after surgery. RESULTS: Before surgery, CBF was 46 ± 16 (mean ± SD) ml/100 g/min and CVR after acetazolamide challenge was 38.5 ± 9.9 (mean ± SD)% in the most affected territory (middle cerebral artery). In cases in which surgery was not performed, CVR was 56 ± 12 (mean ± SD)% in affected hemispheres. After MBH surgery, there was a relative change in CVR compared to baseline (preop) of + 23.5 ± 23.3% (mean ± SD). There were no new ischemic events. CONCLUSION: Using ASL-MRI we followed changes in CBF and CVR in patients with MM. The technique was encouraging for assessments before and after revascularization surgery.

PURPOSE: Moyamoya (MM) disease is characterized by progressive intracranial arterial stenosis. Patients commonly need revascularization surgery to optimize cerebral blood flow (CBF). Estimation of CBF and cerebrovascular reserve (CVR) is therefore necessary before and after surgery. However, assessment of CBF before and after indirect revascularization surgery with the multiple burr hole (MBH) technique in MM has not been studied extensively. In this study, we describe our initial experience using arterial spin labeling magnetic resonance perfusion imaging (ASL-MRI) for CBF and CVR assessment before and after indirect MBH revascularization surgery in MM patients. METHODS: Eleven MM patients (initial age 6-50 years, 1 male/10 female) with 19 affected hemispheres were included. A total of 35 ASL-MRI examinations were performed using a 3D-pCASL acquisition before and after i.v. acetazolamide challenge (1000 mg in adults and 10 mg/kg in children). Twelve MBH procedures were performed in seven patients. The first follow-up ASL-MRI was performed 7-21 (mean 12) months after surgery. RESULTS: Before surgery, CBF was 46 ± 16 (mean ± SD) ml/100 g/min and CVR after acetazolamide challenge was 38.5 ± 9.9 (mean ± SD)% in the most affected territory (middle cerebral artery). In cases in which surgery was not performed, CVR was 56 ± 12 (mean ± SD)% in affected hemispheres. After MBH surgery, there was a relative change in CVR compared to baseline (preop) of + 23.5 ± 23.3% (mean ± SD). There were no new ischemic events. CONCLUSION: Using ASL-MRI we followed changes in CBF and CVR in patients with MM. The technique was encouraging for assessments before and after revascularization surgery.

OBJECTIVE: A small posterior fossa (PF) has been hypothesized to explain the increased incidence of trigeminal neuralgia (TN) in females and could make microvascular decompression (MVD) more challenging. The aim of this study was to investigate the association between the PF volume and dimensions in relation to biological sex, type of neurovascular conflict (NVC), and outcome after MVD in classic TN. METHODS: In this observational study, 84 patients with TN operated on with MVD with a preoperative head computed tomography(CT) scan were included. Eighty-two adults without TN who had undergone head CT for other reasons were included as controls. PF volume and dimensions (x-axis, y-axis, and z-axis) were evaluated on the CT scans. For the patients with TN, Barrow Neurological Institute (BNI) grade was evaluated 6 months after MVD. RESULTS: There was no difference in PF volume or dimensions between the patients with TN and controls. Women showed a smaller volume and narrower (x-axis) PF than men, but these differences did not manifest when comparing patients with TN and controls within each sex. Patients with an NVC involving the superior cerebellar artery had a narrower (x-axis) and shorter (y-axis) PF than did patients with an NVC resulting from other arteries. PF volume or dimensions were not associated with BNI grade after MVD. CONCLUSIONS: PF anatomy was related to the NVC type but did not differ between patients with TN and controls and was not related to the surgical outcome after MVD.

BACKGROUND: Trigeminal neuralgia (TN), a severe type of facial pain, is mainly caused by a neurovascular conflict (NVC). The severity of the NVC seems associated with the outcome following microvascular decompression (MVD) surgery. This study aimed to investigate the outcome after MVD and whether it is affected by NVC severity and sex. METHODS: TN patients (n = 109) were followed for 5 to 10 years after MVD. Barrow Neurology Index (BNI), Patients Global Impression of Change (PGIC), complications, and time to relapse were evaluated. The NVC severity was retrospectively reviewed from presurgical MRI. Demographic and clinical factors and NVC severity were analyzed for potential association with outcome after MVD. RESULTS: The success rate (BNI ≤ 2) was 80% after 5 to 10 years follow-up for TN patients with severe NVC (grade 2-3) and 56% for TN patients with mild NVC (grade 0-1, P = 0.003). No sex difference was observed in outcome for patients with both mild (P = 0.924) and severe NVC (P = 0.883) respectively. Three patients (2.8%) during the hospital stay, and two patients (1.8%) at 6 weeks, experienced a complication requiring invasive treatment. At long-term 52/109 patients (47.7%) reported some type of persistent adverse event, of which the majority were mild and required no treatment. CONCLUSIONS: MVD offers an 80% probability of long-term pain relief in TN patients with severe NVC, with low frequency of serious complications. NVC severity significantly affects outcome after MVD, while no sex differences in outcome were found. In consistency with previous work, the results stress the importance of adequate neuroradiological assessment of the NVC for preoperative patient selection.

Accurate localization and volumetric quantification of postoperative glioblastoma are of profound importance for clinical applications like post-surgery treatment planning, monitoring of tumor regrowth, and radiotherapy map planning. Manual delineation consumes more time and error prone thus automated 3-D quantification of brain tumors using deep learning algorithms from MRI scans has been used in recent years. The shortcoming with automated segmentation is that it often over-segments or under-segments the tumor regions. An interactive deep-learning tool will enable radiologists to correct the over-segmented and under-segmented voxels. In this paper, we proposed a network named Attention-SEV-Net which outperforms state-of-the-art network architectures. We also developed an interactive graphical user interface, where the initial 3-D segmentation of contrast-enhanced tumor can be interactively corrected to remove falsely detected isolated tumor regions. Attention-SEV-Net is trained with BraTS-2021 training data set and tested on Uppsala University post-operative glioblastoma dataset. The methodology outperformed state-of-the-art networks like U-Net, VNet, Attention U-Net and Residual U-Net. The mean dice score achieved is 0.6682 and the mean Hausdorff distance-95 got is 8.96mm for the Uppsala University dataset.

Background: Of interest to women's mental health, a wealth of studies suggests sex differences in nicotine addiction and treatment response, but their psychoneuroendocrine underpinnings remain largely unknown. A pathway involving sex steroids could indeed be involved in the behavioural effects of nicotine, as it was found to inhibit aromatase in vitro and in vivo in rodents and non-human primates, respectively. Aromatase regulates the synthesis of oestrogens and, of relevance to addiction, is highly expressed in the limbic brain. Methods: The present study sought to investigate in vivo aromatase availability in relation to exposure to nicotine in healthy women. Structural magnetic resonance imaging and two [11C]cetrozole positron emission tomography (PET) scans were performed to assess the availability of aromatase before and after administration of nicotine. Gonadal hormones and cotinine levels were measured. Given the region-specific expression of aromatase, a ROI -based approach was employed to assess changes in [11C]cetrozole non-displaceable binding potential. Results: The highest availability of aromatase was found in the right and left thalamus. Upon nicotine exposure, [11C]cetrozole binding in the thalamus was acutely decreased bilaterally (Cohen's d =-0.99). In line, cotinine levels were negatively associated with aromatase availability in the thalamus, although as non-significant trend. Conclusions: These findings indicate acute blocking of aromatase availability by nicotine in the thalamic area. This suggests a new putative mechanism mediating the effects of nicotine on human behaviour, particularly relevant to sex differences in nicotine addiction.

Introduction Roux-en-Y gastric bypass (RYGB) leads to beneficial effects on glucose homeostasis, and attenuated hormonal counterregulatory responses to hypoglycemia are likely to contribute. RYGB also induces alterations in neural activity of cortical and subcortical brain regions. We aimed to characterize RYGB-induced changes in resting-state connectivity of specific brain regions of interest for energy homeostasis and behavioral control during hypoglycemia. Method Ten patients with BMI > 35 kg/m2 were investigated with brain PET/MR imaging during a hyperinsulinemic normo- and hypoglycemic clamp, before and 4 months after RYGB. Hormonal levels were assessed throughout the clamp. Resting-state (RS) fMRI scans were acquired in the glucose-lowering phase of the clamp, and they were analyzed with a seed-to-voxel approach. Results RS connectivity during initiation of hypoglycemia was significantly altered after RYGB between nucleus accumbens, thalamus, caudate, hypothalamus and their crosstalk with cortical and subcortical regions. Connectivity between the nucleus accumbens and the frontal pole was increased after RYGB, and this was associated with a reduction of ACTH (r = −0.639, p = 0.047) and cortisol (r = −0.635, p = 0.048) responses. Instead, connectivity between the caudate and the frontal pole after RYGB was reduced and this was associated with less attenuation of glucagon response during the hypoglycemic clamp (r = −0.728, p = 0.017), smaller reduction in fasting glucose (r = −0.798, p = 0.007) and less excess weight loss (r = 0.753, p = 0.012). No other significant associations were found between post-RYGB changes in ROI-to-voxel regional connectivity hormonal responses and metabolic or anthropometric outcomes. Conclusion RYGB alters brain connectivity during hypoglycemia of several neural pathways involved in reward, inhibitory control, and energy homeostasis. These changes are associated with altered hormonal responses to hypoglycemia and may be involved i

Introduction Roux-en-Y gastric bypass (RYGB) leads to beneficial effects on glucose homeostasis, and attenuated hormonal counterregulatory responses to hypoglycemia are likely to contribute. RYGB also induces alterations in neural activity of cortical and subcortical brain regions. We aimed to characterize RYGB-induced changes in resting-state connectivity of specific brain regions of interest for energy homeostasis and behavioral control during hypoglycemia. Method Ten patients with BMI > 35 kg/m2 were investigated with brain PET/MR imaging during a hyperinsulinemic normo- and hypoglycemic clamp, before and 4 months after RYGB. Hormonal levels were assessed throughout the clamp. Resting-state (RS) fMRI scans were acquired in the glucose-lowering phase of the clamp, and they were analyzed with a seed-to-voxel approach. Results RS connectivity during initiation of hypoglycemia was significantly altered after RYGB between nucleus accumbens, thalamus, caudate, hypothalamus and their crosstalk with cortical and subcortical regions. Connectivity between the nucleus accumbens and the frontal pole was increased after RYGB, and this was associated with a reduction of ACTH (r = −0.639, p = 0.047) and cortisol (r = −0.635, p = 0.048) responses. Instead, connectivity between the caudate and the frontal pole after RYGB was reduced and this was associated with less attenuation of glucagon response during the hypoglycemic clamp (r = −0.728, p = 0.017), smaller reduction in fasting glucose (r = −0.798, p = 0.007) and less excess weight loss (r = 0.753, p = 0.012). No other significant associations were found between post-RYGB changes in ROI-to-voxel regional connectivity hormonal responses and metabolic or anthropometric outcomes. Conclusion RYGB alters brain connectivity during hypoglycemia of several neural pathways involved in reward, inhibitory control, and energy homeostasis. These changes are associated with altered hormonal responses to hypoglycemia and may be involved i

This paper presents a weakly supervised deep convolutional neural network-based approach to perform voxel-level3D registration between subsequent follow-up MRI scans of the same patient. To handle the large deformation inthe surrounding brain tissues due to the tumor’s mass effect we proposed curriculum learning-based training forthe network. Weak supervision helps the network to concentrate more focus on the tumor region and resectioncavity through a saliency detection network. Qualitative and quantitative experimental results show the proposedregistration network outperformed two popular state-of-the-art methods.

Introduction Roux-en-Y gastric bypass (RYGB) leads to beneficial effects on glucose homeostasis, and attenuated hormonal counterregulatory responses to hypoglycemia are likely to contribute. RYGB also induces alterations in neural activity of cortical and subcortical brain regions. We aimed to characterize RYGB-induced changes in resting-state connectivity of specific brain regions of interest for energy homeostasis and behavioral control during hypoglycemia. Method Ten patients with BMI > 35 kg/m2 were investigated with brain PET/MR imaging during a hyperinsulinemic normo- and hypoglycemic clamp, before and 4 months after RYGB. Hormonal levels were assessed throughout the clamp. Resting-state (RS) fMRI scans were acquired in the glucose-lowering phase of the clamp, and they were analyzed with a seed-to-voxel approach. Results RS connectivity during initiation of hypoglycemia was significantly altered after RYGB between nucleus accumbens, thalamus, caudate, hypothalamus and their crosstalk with cortical and subcortical regions. Connectivity between the nucleus accumbens and the frontal pole was increased after RYGB, and this was associated with a reduction of ACTH (r = −0.639, p = 0.047) and cortisol (r = −0.635, p = 0.048) responses. Instead, connectivity between the caudate and the frontal pole after RYGB was reduced and this was associated with less attenuation of glucagon response during the hypoglycemic clamp (r = −0.728, p = 0.017), smaller reduction in fasting glucose (r = −0.798, p = 0.007) and less excess weight loss (r = 0.753, p = 0.012). No other significant associations were found between post-RYGB changes in ROI-to-voxel regional connectivity hormonal responses and metabolic or anthropometric outcomes. Conclusion RYGB alters brain connectivity during hypoglycemia of several neural pathways involved in reward, inhibitory control, and energy homeostasis. These changes are associated with altered hormonal responses to hypoglycemia and may be involved i