Outcomes in influenza and RANBP2 mutation-associated acute necrotizing encephalopathy of childhood

AIM

To evaluate clinical and imaging features in patients with acute necrotizing encephalopathy of childhood (ANEC) to identify predictors of RANBP2 mutations, influenza association, and long-term outcomes.

METHOD

A retrospective chart review in patients with ANEC (2012-2020) seen at a tertiary pediatric center was performed. Children were included if they had acute inflammatory lesions in the basal ganglia and pons. Variables included presenting features, imaging characteristics, RANBP2 gene testing, nasopharyngeal swab findings, therapies, and long-term outcomes.

RESULTS

Twenty patients were included (average age at presentation 3y 6mo, interquartile range  3y 7mo, SD  2y 8mo; 14 females, six males). Three of the 20 experienced recurrences; one of the 20 died. Ten patients were influenza positive. Seven patients were RANBP2 mutation positive. A higher likelihood of hemorrhage was observed in patients who were influenza positive compared to influenza negative (p=0.048). Patients with influenza had a higher degree of thalamic hemorrhage (2, p=0.035) and greater extent of diffusion restriction (3, p=0.035) in semiquantitive analysis.

INTERPRETATION

Children with ANEC who are positive for influenza are more likely to have hemorrhage and greater thalamic swelling. RANBP2 status was predictive of relapse but not predictive of overall outcome.

MRI Radiogenomics of Pediatric Medulloblastoma: A Multicenter Study

Background Radiogenomics of pediatric medulloblastoma (MB) offers an opportunity for MB risk stratification, which may aid therapeutic decision making, family counseling, and selection of patient groups suitable for targeted genetic analysis. Purpose To develop machine learning strategies that identify the four clinically significant MB molecular subgroups. Materials and Methods In this retrospective study, consecutive pediatric patients with newly diagnosed MB at MRI at 12 international pediatric sites between July 1997 and May 2020 were identified. There were 1800 features extracted from T2- and contrast-enhanced T1-weighted preoperative MRI scans. A two-stage sequential classifier was designed-one that first identifies non-wingless (WNT) and non-sonic hedgehog (SHH) MB and then differentiates therapeutically relevant WNT from SHH. Further, a classifier that distinguishes high-risk group 3 from group 4 MB was developed. An independent, binary subgroup analysis was conducted to uncover radiomics features unique to infantile versus childhood SHH subgroups. The best-performing models from six candidate classifiers were selected, and performance was measured on holdout test sets. CIs were obtained by bootstrapping the test sets for 2000 random samples. Model accuracy score was compared with the no-information rate using the Wald test. Results The study cohort comprised 263 patients (mean age ± SD at diagnosis, 87 months ± 60; 166 boys). A two-stage classifier outperformed a single-stage multiclass classifier. The combined, sequential classifier achieved a microaveraged F1 score of 88% and a binary F1 score of 95% specifically for WNT. A group 3 versus group 4 classifier achieved an area under the receiver operating characteristic curve of 98%. Of the Image Biomarker Standardization Initiative features, texture and first-order intensity features were most contributory across the molecular subgroups. Conclusion An MRI-based machine learning decision path allowed identification of the four clinically relevant molecular pediatric medulloblastoma subgroups. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Chaudhary and Bapuraj in this issue.

Correlations Between the DMN and the Smoking Cessation Outcome of a Real-Time fMRI Neurofeedback Supported Exploratory Therapy Approach: Descriptive Statistics on Tobacco-Dependent Patients

The aim of this study was to explore the potential of default mode network (DMN) functional connectivity for predicting the success of smoking cessation in patients with tobacco dependence in the context of a real-time function al MRI (RT-fMRI) neurofeedback (NF) supported therapy.Fifty-four tobacco-dependent patients underwent three RT-fMRI-NF sessions including resting-state functional connectivity (RSFC) runs over a period of 4 weeks during professionally assisted smoking cessation. Patients were randomized into two groups that performed either active NF of an addiction-related brain region or sham NF. After preprocessing, the RSFC baseline data were statistically evaluated using seed-based ROI (SBA) approaches taking into account the smoking status of patients after 3 months (abstinence/relapse).The results of the real study group showed a widespread functional connectivity in the relapse subgroup (n = 10) exceeding the DMN template and mainly low correlations and anticorrelations in the within-seed analysis. In contrast, the connectivity pattern of the abstinence subgroup (n = 8) primarily contained the core DMN in the seed-to-whole-brain analysis and a left lateralized correlation pattern in the within-seed analysis. Calculated Multi-Subject Dictionary Learning (MSDL) matrices showed anticorrelations between DMN regions and salience regions in the abstinence group. Concerning the sham group, results of the relapse subgroup (n = 4) and the abstinence subgroup (n = 6) showed similar trends only in the within-seed analysis.In the setting of a RT-fMRI-NF-assisted therapy, a widespread intrinsic DMN connectivity and a low negative coupling between the DMN and the salience network (SN) in patients with tobacco dependency during early withdrawal may be useful as an early indicator of later therapy nonresponse.

Automatic Artifact Detection Algorithm in Fetal MRI

Fetal MR imaging is subject to artifacts including motion, chemical shift, and radiofrequency artifacts. Currently, such artifacts are detected by the MRI operator, a process which is subjective, time consuming, and prone to errors. We propose a novel algorithm, RISE-Net, that can consistently, automatically, and objectively detect artifacts in 3D fetal MRI. It makes use of a CNN ensemble approach where the first CNN aims to identify and classify any artifacts in the image, and the second CNN uses regression to determine the severity of the detected artifacts. The main mechanism in RISE-Net is the stacked Residual, Inception, Squeeze and Excitation (RISE) blocks. This classification network achieved an accuracy of 90.34% and a F1 score of 90.39% and outperformed other state-of-the-art architectures, such as VGG-16, Inception, ResNet-50, ReNet-Inception, SE-ResNet, and SE-Inception. The severity regression network had an MSE of 0.083 across all classes. The presented algorithm facilitates rapid and accurate fetal MRI quality assurance that can be implemented into clinical use.

IMMU-13. Dual CTLA4/ PD-1 blockade improves survival for replication-repair deficient high-grade gliomas failing single agent PD-1 inhibition: An IRRDC study

BACKGROUND: High-grade gliomas (HGG) with replication-repair deficiency (RRD) harbour high mutation burden (TMB) and are rapidly fatal following chemo-radiation approaches. Although hypermutation results in objective responses and prolonged survival in >30% of patients undergoing PD1-blockade, salvage following failure of PD1-inhibition remains a challenge. METHODS: We performed a real-world study of Ipilimumab (anti-CTLA4) in combination with Nivolumab/Pembrolizumab for patients failing single-agent PD1-inhibition. RESULTS: Among 68 consortium patients with relapsed HGG treated with single-agent PD1-inhibitors, progression was observed in 43 (63%). Ipilimumab was added to 20/43 (46.5%), 14 (32.5%) received best supportive care (BSC), and 9 (21%) received miscellaneous therapies. For patients receiving CTLA4/PD1-inhibition, median age at progression was 12.3-years (IQR: 9; 15.6). Time from anti-PD1 initiation to progression was 8-months (IQR: 3.8; 18.5). Germline predisposition was observed in all patients (CMMRD: 70%, Lynch: 25%, polymerase-proofreading deficiency: 5%). All HGG were hypermutant (median TMB: 182 mutations/Mb; IQR: 15.6; 369.4). Centralized radiology review revealed objective responses in 3/20 (15%, all ultra-hypermutant: 320, 496, 834 mutations/Mb), stable disease in 5 (25%), and 12 (60%) eventually progressed (iRANO). Following failure of PD1-blockade, estimated progression-free and overall survival at 18-months for patients receiving CTLA4/PD1-inhibition were 11% and 25%, respectively. Importantly, survival was superior to patients receiving BSC (median OS <1-month versus 12-months on CTLA4/PD1-inhibition; p<0.001). All patients receiving BSC died within 3.5-months, while 4/8 survivors were alive for >1-year on the anti-CTLA4/PD1combination (range:1-48 months). The combinational immunotherapy resulted in significant autoimmune toxicity in 11/20 (55%), warranting immunosuppressive therapy in all, and treatment abandonment in 6 patients. CONCLUSION: Combined CTLA4/PD1-blockade after failure of single-agent PD1-inhibition revealed objective responses and prolonged survival in an otherwise rapidly-fatal disease. This needs to be assessed in the context of significant autoimmunity, supporting the need for the current prospective trial (NCT04500548), and novel strategies to limit treatment-related toxicity.

LGG-41. The clinical and molecular landscape of gliomas in adolescents and young adults

OBJECTIVE: Gliomas in adolescents and young adults (AYA) are commonly treated with a standard chemo-radiation approach based on data from adults. The clinical impact of paediatric-type alterations in these tumours is unknown. METHODS: We compiled a multi-institutional cohort of patients diagnosed with glioma between 15-39.9 years over 20 years. Complete molecular analysis, therapeutic data and outcome was collected. For specific alterations, analysis included patients aged 0-39.9 years. RESULTS: A total of 1900 patients with 876 AYA gliomas were included. Ongoing analysis reveals genetic alterations in 95% of available tumours. IDH-mutant tumours account for only 53%, while paediatric-type mutations were found in 35% of AYA tumours with IDH-WT GBM accounting for the remaining 12%. The most common paediatric alterations in AYAs included BRAF p.V600E (11%) and FGFR alterations (6%) while BRAF fusions, H3 p.K27M and H3.3 p.G34R were rarely observed (4%, 4% and 1% respectively). BRAF fused tumours with non-canonical binding partners were enriched in AYAs. Analysis of BRAF-V600E gliomas between ages 0-40 revealed increased tendency for malignant tumours in patients &gt;20 years suggesting malignant transformation possibly due to higher rate of secondary hits including TP53, CDKN2A and ATRX mutations. This resulted in worse overall-survival for AYA patients with BRAF-V600E glioma when compared to children under 20 years (p=0.0032). Ten-year OS of 100%, 90% and 95% was seen for BRAF fused, BRAF-V600E and FGFR-altered AYA low grade glioma respectively, compared to 14% and 25% for BRAF-V600E and FGFR-altered high grade glioma. In contrast, continuous decline was observed in the IDH-mutant gliomas with 10-year OS of 50% which declined to 29% at 15 years. CONCLUSIONS: Gliomas in AYA are enriched for paediatric-type alterations with distinct molecularly-based outcomes. As these tumours carry different outcomes than childhood glioma and may respond to targeted inhibitors, AYA gliomas would benefit from comprehensive diagnostic and therapeutic approaches.

GCT-22. OUTCOMES OF CHILDREN WITH LOCALIZED AND METASTATIC GERMINOMA TREATED WITH CHEMOTHERAPY FOLLOWED BY RADIATION THERAPY WITHOUT PRIMARY TUMOR BOOST

BACKGROUND: Response-based radiation therapy has been the approach for germinoma after chemotherapy. However, the presence of residual lesions at the end of chemotherapy did not demonstrate a negative impact on progression-free survival (PFS). Similarly, resection of residual tumors after chemotherapy did not show a survival benefit. AIM: Our study objective was to determine long-term outcomes of a cohort who received chemotherapy and radiation therapy without primary tumor boost even in the absence of complete response to chemotherapy. METHOD: This retrospective study analyzed the outcome of germinoma patients diagnosed and treated at a tertiary care center from January 2006 to December 2021. RESULTS: Twenty-nine children (14 male; median age 12.8 years) were identified. Median follow-up was 63 months (range 9-187 months). Twenty children had localized disease and tumor location was suprasellar (n= 9), pineal (n= 10), and bifocal (n= 1) while 9 children had metastatic disease at presentation. All patients completed multi-agent chemotherapy followed by either whole ventricular (WVI) (23.4 Gy) (n = 23), whole brain (WBI) (23.4 Gy) (n = 5) or craniospinal radiation (CSI) (23.4 Gy) (n= 1). Two children, who had localized disease at presentation and received WVI after chemotherapy, relapsed 9 months and 32 months after completion of treatment respectively. None of them had local relapses. Location of relapse was distant, outside (n= 1) and inside (n= 1) the radiation field. Five-year PFS was 93% and overall survival (OS) was 100%. CONCLUSION: In this limited experience, excellent 5-year PFS and OS rates were achieved with chemotherapy followed by radiation therapy delivered without primary tumor boost. This study also demonstrated the absence of local relapse despite omitting primary tumor boost in patients with localized and metastatic germinoma.

Functional and clinical outcomes of FMRI-based neurofeedback training in patients with alcohol dependence: a pilot study

Identifying treatment options for patients with alcohol dependence is challenging. This study investigates the application of real-time functional MRI (rtfMRI) neurofeedback (NF) to foster resistance towards craving-related neural activation in alcohol dependence. We report a double-blind, placebo-controlled rtfMRI study with three NF sessions using alcohol-associated cues as an add-on therapy to the standard treatment. Fifty-two patients (45 male; 7 female) diagnosed with alcohol dependence were recruited in Munich, Germany. RtfMRI data were acquired in three sessions and clinical abstinence was evaluated 3 months after the last NF session. Before the NF training, BOLD responses and clinical data did not differ between groups, apart from anger and impulsiveness. During NF training, BOLD responses of the active group were decreased in medial frontal areas/caudate nucleus, and increased, e.g. in the cuneus/precuneus and occipital cortex. Within the active group, the down-regulation of neuronal responses was more pronounced in patients who remained abstinent for at least 3 months after the intervention compared to patients with a relapse. As BOLD responses were comparable between groups before the NF training, functional variations during NF cannot be attributed to preexisting distinctions. We could not demonstrate that rtfMRI as an add-on treatment in patients with alcohol dependence leads to clinically superior abstinence for the active NF group after 3 months. However, the study provides evidence for a targeted modulation of addiction-associated brain responses in alcohol dependence using rtfMRI.

Hearing Instability in Children with Congenital Cytomegalovirus: Evidence and Neural Consequences

OBJECTIVE/HYPOTHESIS

Sensorineural hearing loss (SNHL) is a common sequela of congenital cytomegalovirus (cCMV), potentially exacerbating neurocognitive delay. The objectives of this study were to assess: (1) age at which SNHL in children with cCMV; (2) stimulability of the auditory system in children with cCMV following cochlear implantation (CI); and (3) whether features of magnetic resonance imaging (MRI) potentially are predictive of hearing outcomes.

METHODS

In this retrospective study of a prospectively acquired cohort, 123 children with cCMV who were referred for hearing loss at a single tertiary referral hospital over 20 years were compared with an unmatched comparative group of 90 children with GJB2-related deafness. Outcome measures were results of newborn hearing screening (NHS), behavioral audiograms, and, in a subgroup of cochlear implant (CI) users, responses from the auditory nerve and brainstem evoked by CI at initial activation, as well as lesional volume of FLAIR-hyperintense signal alterations on MRI.

RESULTS

All but 3 of 123 children with cCMV had confirmed and persistent SNHL. At birth, 113 children with cCMV underwent NHS, 31 (27%) passed in both ears and 23 (20%) passed in one ear (no NHS data in 10 children). At the first audiologic assessment, 32 of 123 (26%) had normal hearing bilaterally; 35 of 123 (28%) had unilateral SNHL; and 57 of 123 (46%) had bilateral SNHL. More than half (67 of 123, 54%) experienced hearing deterioration in at least one ear. Survival analyses suggested that 60% of children who developed SNHL did so by 2.5 years and 80% by 5 years. In the children who passed NHS in one or both ears, 50% developed hearing loss by 3.5 years in the ear, which passed unilaterally (n = 23 ears), and 50% by 5 years in bilateral passes (n = 62 ears). Hearing loss was significant enough in all but one child with isolated high-frequency loss for rehabilitation to be indicated. Hearing thresholds in individual ears were in the CI range in 83% (102 of 123), although duration of deafness was sufficient to preclude implantation at our center in 13 children with unilateral SNHL. Hearing aids were indicated in 16% (20 of 123). Responses from the auditory nerve and brainstem to initial CI stimulation were similar in children with cCMV-related SNHL compared with GJB2-related SNHL. Characteristic white matter changes on MRI were seen in all children with cCMV-related SNHL (n = 91), but the lesion volume in each cortical hemisphere did not predict degree of SNHL.

CONCLUSIONS

cCMV-related SNHL is often not detected by NHS but occurs with high prevalence in early childhood. Electrophysiological measures suggest equivalent stimulability of the auditory nerve and brainstem with CI in children with cCMV and GJB2-related SNHL. Hyperintense white matter lesions on FLAIR MRI are consistently present in children with cCMV-related SNHL but cannot be used to predict its time course or degree. Combined, the data show early and rapid deterioration of hearing in children with cCMV-related SNHL with potential for good CI outcomes if SNHL is identified and managed without delay. Findings support universal newborn screening for cCMV followed by careful audiological monitoring.

LEVEL OF EVIDENCE

3 Laryngoscope, 2022.

Fetal Organ Anomaly Classification Network for Identifying Organ Anomalies in Fetal MRI

Rapid development in Magnetic Resonance Imaging (MRI) has played a key role in prenatal diagnosis over the last few years. Deep learning (DL) architectures can facilitate the process of anomaly detection and affected-organ classification, making diagnosis more accurate and observer-independent. We propose a novel DL image classification architecture, Fetal Organ Anomaly Classification Network (FOAC-Net), which uses squeeze-and-excitation (SE) and naïve inception (NI) modules to automatically identify anomalies in fetal organs. This architecture can identify normal fetal anatomy, as well as detect anomalies present in the (1) brain, (2) spinal cord, and (3) heart. In this retrospective study, we included fetal 3-dimensional (3D) SSFP sequences of 36 participants. We classified the images on a slice-by-slice basis. FOAC-Net achieved a classification accuracy of 85.06, 85.27, 89.29, and 82.20% when predicting brain anomalies, no anomalies (normal), spinal cord anomalies, and heart anomalies, respectively. In a comparison study, FOAC-Net outperformed other state-of-the-art classification architectures in terms of class-average F1 and accuracy. This work aims to develop a novel classification architecture identifying the affected organs in fetal MRI.

Decreased Craniocervical CSF Flow in Patients with Normal Pressure Hydrocephalus: A Pilot Study

BACKGROUND AND PURPOSE

Normal pressure hydrocephalus is characterized by systolic peaks of raised intracranial pressure, possibly due to a reduced compliance of the spinal CSF spaces. This concept of a reduced spinal CSF buffer function may be reflected by a low cervical CSF outflow from the cranium. The aim of this study was to investigate craniospinal CSF flow rates by phase-contrast MR imaging in patients with normal pressure hydrocephalus.

MATERIALS AND METHODS

A total of 42 participants were included in this prospective study, consisting of 3 study groups: 1) 10 patients with normal pressure hydrocephalus (mean age, 74 [SD, 6] years, with proved normal pressure hydrocephalus according to current scientific criteria); 2) eighteen age-matched healthy controls (mean age, 71 [SD, 5] years); and 3) fourteen young healthy controls (mean age, 21 [SD, 2] years, for investigation of age-related effects). Axial phase-contrast MR imaging was performed, and the maximal systolic CSF and total arterial blood flow rates were measured at the level of the upper second cervical vertebra and compared among all study groups (2-sample unpaired t test).

RESULTS

The maximal systolic CSF flow rate was significantly decreased in patients with normal pressure hydrocephalus compared with age-matched and young healthy controls (53 [SD,  40] mL/m; 329 [SD,  175] mL/m; 472 [SD, 194] mL/m; each P < .01), whereas there were no significant differences with regard to maximal systolic arterial blood flow (1160 [SD, 404] mL/m; 1470 [SD,  381] mL/m; 1400 [SD, 254] mL/m; each P > .05).

CONCLUSIONS

The reduced maximal systolic craniospinal CSF flow rate in patients with normal pressure hydrocephalus may be reflective of a reduced compliance of the spinal CSF spaces and an ineffective spinal CSF buffer function. Systolic craniospinal CSF flow rates are an easily obtainable MR imaging-based measure that may support the diagnosis of normal pressure hydrocephalus.

Abstract TMP94: Health Inequity And Time From Stroke Onset To Arrival Trends: A Single-centre Experience

Introduction: Clinical outcomes post childhood stroke have been shown to largely depend on age at the time of stroke, and the size and location of the infarct. However, the impact of health inequities on time to hospital arrival and outcomes remain inadequately addressed. This study examined trends in material deprivation and its impact on time from stroke onset to arrival in the ER for children with arterial ischemic stroke.

Methods: A consecutive cohort of children >28 days-18 years of age diagnosed with arterial ischemic stroke between 2004 and 2019 at a comprehensive stroke centre were included. The Ontario Marginalization Index data for each child was derived from their residential postal code using validated mapping techniques. Within the index, material deprivation measures the income, education, single-parent families, and housing quality in a region. Patients were stratified into 3 cohorts by year of presentation; Cohort 1: 2004-2008, Cohort 2: 2009-2013, and Cohort 3: 2014-2019, while their postal codes were dichotomized into low or highly deprived neighbourhoods. The time from stroke onset to arrival was stratified into < 6 hours, 6 to 24 hours, and > 24 hours.

Results: Amongst 285 children, more lived in a highly deprived neighbourhood in the later cohort (Cohort 3: 2014-2019) than the earlier cohort (Cohort 1: 2004-2008) (47.5% vs. 40.3%). Compared to Cohort 1, more patients in Cohort 3 arrived in the ER within 6 hours of stroke onset (28.3% vs 52.5%) while a similar trend was found in patients arriving 6 to 24 hours post onset of stroke (10.1% vs. 23.2%). From Cohorts 1 to 3, a significant increase in the proportion of patients arriving in the ER within 6 hours of stroke onset was found (χ 2 = 10.9, p = 0.027).

Conclusion: Our study demonstrated an increasing trend toward more patients with stroke coming from highly deprived neighbourhoods. This is a cause for concern. However, whether this has an impact on stroke severity and outcomes is yet to be determined. Over the same period, more patients within the later cohort arrived in the ER within 6 hours of stroke onset. These findings may be attributed to sustained community-based education and primary-care initiatives that have led to increased awareness of childhood stroke symptoms over the past 15 years.

Cognitive and functional deficits are associated with white matter abnormalities in two independent cohorts of patients with schizophrenia

BACKGROUND

Significant evidence links white matter (WM) microstructural abnormalities to cognitive impairment in schizophrenia (SZ), but the relationship of these abnormalities with functional outcome remains unclear.

METHODS

In two independent cohorts (C1, C2), patients with SZ were divided into two subgroups: patients with higher cognitive performance (SZ-HCP-C1, n = 25; SZ-HCP-C2, n = 24) and patients with lower cognitive performance (SZ-LCP-C1, n = 25; SZ-LCP-C2, n = 24). Healthy controls (HC) were included in both cohorts (HC-C1, n = 52; HC-C2, n = 27). We compared fractional anisotropy (FA) of the whole-brain WM skeleton between the three groups (SZ-LCP, SZ-HCP, HC) by a whole-brain exploratory approach and an atlas-defined WM regions-of-interest approach via tract-based spatial statistics. In addition, we explored whether FA values were associated with Global Assessment of Functioning (GAF) scores in the SZ groups.

RESULTS

In both cohorts, mean FA values of whole-brain WM skeleton were significantly lower in the SCZ-LCP group than in the SCZ-HCP group. Whereas in C1 the FA of the frontal part of the left inferior fronto-occipital fasciculus (IFOF) was positively correlated with GAF score, in C2 the FA of the temporal part of the left IFOF was positively correlated with GAF score.

CONCLUSIONS

We provide robust evidence for WM microstructural abnormalities in SZ. These abnormalities are more prominent in patients with low cognitive performance and are associated with the level of functioning.

Association between aerobic fitness and the functional connectome in patients with schizophrenia

BACKGROUND

Schizophrenia is accompanied by widespread alterations in static functional connectivity associated with symptom severity and cognitive deficits. Improvements in aerobic fitness have been demonstrated to ameliorate symptomatology and cognition in people with schizophrenia, but the intermediary role of macroscale connectivity patterns remains unknown.

OBJECTIVE

Therefore, we aim to explore the relation between aerobic fitness and the functional connectome in individuals with schizophrenia. Further, we investigate clinical and cognitive relevance of the identified fitness-connectivity links.

METHODS

Patients diagnosed with schizophrenia were included in this cross-sectional resting-state fMRI analysis. Multilevel Bayesian partial correlations between aerobic fitness and functional connections across the whole brain as well as between static functional connectivity patterns and clinical and cognitive outcome were performed. Preliminary causal inferences were enabled based on mediation analyses.

RESULTS

Static functional connectivity between the subcortical nuclei and the cerebellum as well as between temporal seeds mediated the attenuating relation between aerobic fitness and total symptom severity. Functional connections between cerebellar seeds affected the positive link between aerobic fitness and global cognition, while the functional interplay between central and limbic seeds drove the beneficial association between aerobic fitness and emotion recognition.

CONCLUSION

The current study provides first insights into the interactions between aerobic fitness, the functional connectome and clinical and cognitive outcome in people with schizophrenia, but causal interpretations are preliminary. Further interventional aerobic exercise studies are needed to replicate the current findings and to enable conclusive causal inferences.

TRIAL REGISTRATION

The study which the manuscript is based on is registered in the International Clinical Trials Database (ClinicalTrials.gov identifier [NCT number]: NCT03466112) and in the German Clinical Trials Register (DRKS-ID: DRKS00009804).

In silico numerical simulation of ventilator settings during high-frequency ventilation in preterm infants

OBJECTIVE

Despite the routine use of antenatal steroids, exogenous surfactants, and different noninvasive ventilation methods, many extremely low gestational age neonates, preterm, and term infants eventually require invasive ventilation. In addition to prematurity, mechanical ventilation itself can induce ventilator-induced lung injury leading to lifelong pulmonary sequelae. Besides conventional mechanical ventilation, high-frequency oscillatory ventilation (HFOV) with tidal volumes below dead space and high ventilation frequencies is used either as a primary or rescue therapy in severe neonatal respiratory failure.

METHODS AND RESULTS

Applying a high-resolution computational lung modeling technique in a preterm infant, we studied three different high-frequency ventilation settings as well as conventional ventilation (CV) settings. Evaluating the computed oxygen delivery (OD) and lung mechanics (LM) we outline for the first time how changing ventilator settings from CV to HFOV lead to significant improvements in OD and LM.

CONCLUSION

This personalized "digital twin" strategy advances our general knowledge of protective ventilation strategies in neonatal care and can support decisions on various modes of ventilatory therapy at high frequencies.

Radiomic Signatures of Posterior Fossa Ependymoma: Molecular Subgroups and Risk Profiles

BACKGROUND

The risk profile for posterior fossa ependymoma (EP) depends on surgical and molecular status [Group A (PFA) versus Group B (PFB)]. While subtotal tumor resection is known to confer worse prognosis, MRI-based EP risk-profiling is unexplored. We aimed to apply machine learning strategies to link MRI-based biomarkers of high-risk EP and also to distinguish PFA from PFB.

METHODS

We extracted 1800 quantitative features from presurgical T2-weighted (T2-MRI) and gadolinium-enhanced T1-weighted (T1-MRI) imaging of 157 EP patients. We implemented nested cross-validation to identify features for risk score calculations and apply a Cox model for survival analysis. We conducted additional feature selection for PFA versus PFB and examined performance across three candidate classifiers.

RESULTS

For all EP patients with GTR, we identified four T2-MRI-based features and stratified patients into high- and low-risk groups, with 5-year overall survival rates of 62% and 100%, respectively (p < 0.0001). Among presumed PFA patients with GTR, four T1-MRI and five T2-MRI features predicted divergence of high- and low-risk groups, with 5-year overall survival rates of 62.7% and 96.7%, respectively (p = 0.002). T1-MRI-based features showed the best performance distinguishing PFA from PFB with an AUC of 0.86.

CONCLUSIONS

We present machine learning strategies to identify MRI phenotypes that distinguish PFA from PFB, as well as high- and low-risk PFA. We also describe quantitative image predictors of aggressive EP tumors that might assist risk-profiling after surgery. Future studies could examine translating radiomics as an adjunct to EP risk assessment when considering therapy strategies or trial candidacy.

Improving 3D convolutional neural network comprehensibility via interactive visualization of relevance maps: evaluation in Alzheimer's disease

Background

Although convolutional neural networks (CNNs) achieve high diagnostic accuracy for detecting Alzheimer’s disease (AD) dementia based on magnetic resonance imaging (MRI) scans, they are not yet applied in clinical routine. One important reason for this is a lack of model comprehensibility. Recently developed visualization methods for deriving CNN relevance maps may help to fill this gap as they allow the visualization of key input image features that drive the decision of the model. We investigated whether models with higher accuracy also rely more on discriminative brain regions predefined by prior knowledge.

Methods

We trained a CNN for the detection of AD in N = 663 T1-weighted MRI scans of patients with dementia and amnestic mild cognitive impairment (MCI) and verified the accuracy of the models via cross-validation and in three independent samples including in total N = 1655 cases. We evaluated the association of relevance scores and hippocampus volume to validate the clinical utility of this approach. To improve model comprehensibility, we implemented an interactive visualization of 3D CNN relevance maps, thereby allowing intuitive model inspection.

Results

Across the three independent datasets, group separation showed high accuracy for AD dementia versus controls (AUC ≥ 0.91) and moderate accuracy for amnestic MCI versus controls (AUC ≈ 0.74). Relevance maps indicated that hippocampal atrophy was considered the most informative factor for AD detection, with additional contributions from atrophy in other cortical and subcortical regions. Relevance scores within the hippocampus were highly correlated with hippocampal volumes (Pearson’s r ≈ −0.86, p < 0.001).

Conclusion

The relevance maps highlighted atrophy in regions that we had hypothesized a priori. This strengthens the comprehensibility of the CNN models, which were trained in a purely data-driven manner based on the scans and diagnosis labels. The high hippocampus relevance scores as well as the high performance achieved in independent samples support the validity of the CNN models in the detection of AD-related MRI abnormalities. The presented data-driven and hypothesis-free CNN modeling approach might provide a useful tool to automatically derive discriminative features for complex diagnostic tasks where clear clinical criteria are still missing, for instance for the differential diagnosis between various types of dementia.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13195-021-00924-2.

Prediction of persistent ventricular dilation by initial ventriculomegaly and clot volume in a porcine model

OBJECTIVE

While intraventricular hemorrhage (IVH) is associated with posthemorrhagic ventricular dilation (PHVD), not all infants affected by high-grade IVH develop PHVD. The authors aimed to determine clot-associated predictors of PHVD in a porcine model by varying the amount and rate of direct intraventricular injection of whole autologous blood.

METHODS

Seven 1-week-old piglets underwent craniectomy and injection of autologous blood into the right lateral ventricle. They survived for a maximum of 28 days. MRI was performed prior to injection, immediately postoperatively, and every 7 days thereafter. T1-weighted, T2-weighted, and susceptibility-weighted imaging (SWI) sequences were used to segment ventricular and clot volumes. Spearman correlations were used to determine the relationship between blood and clot volumes and ventricular volumes over time.

RESULTS

The maximum ventricular volume was up to 12 times that of baseline. One animal developed acute hydrocephalus on day 4. All other animals survived until planned endpoints. The interaction between volume of blood injected and duration of injection was significantly associated with clot volume on the postoperative scan (p = 0.003) but not the amount of blood injected alone (p = 0.38). Initial postoperative and day 7 clot volumes, but not volume of blood injected, were correlated with maximum (p = 0.007 and 0.014) and terminal (p = 0.014 and 0.036) ventricular volumes. Initial postoperative ventricular volume was correlated with maximum and terminal ventricular volume (p = 0.007 and p = 0.014).

CONCLUSIONS

Initial postoperative, maximum, and terminal ventricular dilations were associated with the amount of clot formed, rather than the amount of blood injected. This supports the hypothesis that PHVD is determined by clot burden rather than the presence of blood products and allows further testing of early clot lysis to minimize PHVD risk.

Machine Assist for Pediatric Posterior Fossa Tumor Diagnosis: A Multinational Study

BACKGROUND

Clinicians and machine classifiers reliably diagnose pilocytic astrocytoma (PA) on magnetic resonance imaging (MRI) but less accurately distinguish medulloblastoma (MB) from ependymoma (EP). One strategy is to first rule out the most identifiable diagnosis.

OBJECTIVE

To hypothesize a sequential machine-learning classifier could improve diagnostic performance by mimicking a clinician's strategy of excluding PA before distinguishing MB from EP.

METHODS

We extracted 1800 total Image Biomarker Standardization Initiative (IBSI)-based features from T2- and gadolinium-enhanced T1-weighted images in a multinational cohort of 274 MB, 156 PA, and 97 EP. We designed a 2-step sequential classifier - first ruling out PA, and next distinguishing MB from EP. For each step, we selected the best performing model from 6-candidate classifier using a reduced feature set, and measured performance on a holdout test set with the microaveraged F1 score.

RESULTS

Optimal diagnostic performance was achieved using 2 decision steps, each with its own distinct imaging features and classifier method. A 3-way logistic regression classifier first distinguished PA from non-PA, with T2 uniformity and T1 contrast as the most relevant IBSI features (F1 score 0.8809). A 2-way neural net classifier next distinguished MB from EP, with T2 sphericity and T1 flatness as most relevant (F1 score 0.9189). The combined, sequential classifier was with F1 score 0.9179.

CONCLUSION

An MRI-based sequential machine-learning classifiers offer high-performance prediction of pediatric posterior fossa tumors across a large, multinational cohort. Optimization of this model with demographic, clinical, imaging, and molecular predictors could provide significant advantages for family counseling and surgical planning.

Brain perfusion imaging in neonates

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MRI is the modality of choice to image and quantify cerebral perfusion.

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Imaging of neonatal brain perfusion is possible using MRI and ultrasound.

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Novel ultrafast ultrasound imaging allows for excellent spatiotemporal resolution.

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Understanding cerebral hemodynamic changes of neonatal adaptation is key.

Abnormal variations of the neonatal brain perfusion can result in long-term neurodevelopmental consequences and cerebral perfusion imaging can play an important role in diagnostic and therapeutic decision-making. To identify at-risk situations, perfusion imaging of the neonatal brain must accurately evaluate both regional and global perfusion. To date, neonatal cerebral perfusion assessment remains challenging. The available modalities such as magnetic resonance imaging (MRI), ultrasound imaging, computed tomography (CT), near-infrared spectroscopy or nuclear imaging have multiple compromises and limitations. Several promising methods are being developed to achieve better diagnostic accuracy and higher robustness, in particular using advanced MRI and ultrasound techniques.

The objective of this state-of-the-art review is to analyze the methodology and challenges of neonatal brain perfusion imaging, to describe the currently available modalities, and to outline future perspectives.

Multiple sclerosis and subclinical neuropathology in healthy individuals with familial risk: A scoping review of MRI studies

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MRI evidence of MS pathology in healthy individuals reflects a subclinical period.

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First-degree relatives of MS patients are ideal to study MS subclinical neuropathology.

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MRI found WM focal inflammation in a substantial proportion of these healthy relatives.

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Diffuse tissue damage is also found by MRI in healthy relatives of MS patients.

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MS prodromal phase can be characterized by studying healthy subjects at high risk.

Multiple genetic and non-heritable factors have been linked to the risk of multiple sclerosis (MS). These factors seem to contribute to disease pathogenesis before the onset of clinical symptoms, as suggested by incidental MRI evidence of subclinical MS neuropathology in individuals without clinical symptoms. Individuals with high familial risk for MS, such as first-degree relatives of patients with MS, can be studied by MRI to characterize the neuropathology during a subclinical period of MS. 16 studies published in English, which performed brain MRI on healthy individuals with high familial risk of MS were included in this scoping review. Studies suggest either no conclusive (5), or inconclusive yet considerable (4), or conclusive evidence (7) for the incidence of subclinical neuropathology, including focal and diffuse tissue damage. Across all studies, white matter lesions fulfilling MS criteria were observed in 86 of 613 individuals (14%). Future research is needed to evaluate the longitudinal dynamics and clinical relevance of preclinical imaging abnormalities in MS.

Mediterranean Diet, Alzheimer Disease Biomarkers and Brain Atrophy in Old Age

OBJECTIVE

To determine whether following a Mediterranean-like diet (MeDi) relates to cognitive functions and in vivo biomarkers for Alzheimer disease (AD), we analyzed cross-sectional data from the German DZNE-Longitudinal Cognitive Impairment and Dementia Study. METHOD: The sample (n=512, mean age: 69.5±5.9 years) included 169 cognitively normal participants and subjects at higher AD risk (53 with relatives with AD, 209 with subjective cognitive decline, and 81 with mild cognitive impairment). We defined MeDi adherence based on the Food Frequency Questionnaire. Brain volume outcomes were generated via voxel-based morphometry on T1-MRI and cognitive performance with an extensive neuropsychological battery. AD-related biomarkers (Aβ42/40 ratio, pTau181) in cerebrospinal fluid were assessed in n=226 individuals. We analyzed the associations between MeDi and the outcomes with linear regression models controlling for several covariates. Additionally, we applied hypothesis-driven mediation and moderation analysis.

RESULTS

Higher MeDi adherence related to larger mediotemporal gray matter volume (p<0.05 FWE corrected), better memory (β±SE = 0.03 ± 0.02; p=0.038), and less amyloid (Aβ42/40 ratio, β±SE = 0.003 ± 0.001; p=0.008) and pTau181 pathology (β±SE = -1.96±0.68; p=0.004). Mediotemporal volume mediated the association between MeDi and memory (40% indirect mediation). Finally, MeDi favorably moderated the associations between Aβ42/40 ratio, pTau181 and mediotemporal atrophy. Results were consistent correcting for ApoE-ε4 status.

CONCLUSION

Our findings corroborate the view of MeDi as a protective factor against memory decline and mediotemporal atrophy. Importantly, they suggest that these associations might be explained by a decrease of amyloidosis and tau-pathology. Longitudinal and dietary intervention studies should further examine this conjecture and its treatment implications.