Brain MRI Research Articles

PRIMARY VITREORETINAL LYMPHOMA MASQUERADING AS POSTOPERATIVE ENDOPHTHALMITIS IN A PREGNANT PATIENT WITH LONG-STANDING IDIOPATHIC PANUVEITIS.

To report primary vitreoretinal lymphoma after surgical 0.59 mg fluocinolone acetonide implant (FAi) exchange in a patient treated with adalimumab for idiopathic bilateral panuveitis. Retrospective case review. A 37-year-old woman with bilateral idiopathic panuveitis, who had favorable responses to previous FAi surgical implants, presented with right eye recurrent intraocular inflammation and cystoid macular edema that partially responded to systemic adalimumab. Her FAi was replaced, given her previous favorable response. She developed postoperative ocular inflammation transiently responsive to two serial vitreous taps and injections of intravitreal antimicrobials and then worsening inflammation and new layered flocculant material. Diagnostic vitrectomy showed a few atypical lymphocytes and cultures were negative. At postdiagnostic vitrectomy Month 1, flocculant material recurred. Aqueous cytology and flow cytometry revealed large CD45-positive B cells suspicious for lymphoma. Postoperatively, she revealed that she was pregnant. She was treated with eight monthly intravitreal methotrexate injections and postpartum consolidation radiotherapy. Subsequent repeat cytology, flow cytometry, and corneal pathologic examination revealed large B cells that were CD20 positive, and next-generation sequencing detected a dominant monoclonal B-cell population, diagnostic of PVRL. Nineteen months after FAi exchange, she developed an area of enhancement in the lateral aspect of the right frontal lobe on brain MRI, consistent with central nervous system involvement. The authors present a unique case of PVRL masquerading as postoperative endophthalmitis after FAi exchange in an eye with chronic panuveitis treated with adalimumab immunosuppressive therapy. The authors hypothesize that there may be a causal relationship between adalimumab and PVRL.

Life-Threatening MOG Antibody-Associated Hemorrhagic ADEM With Elevated CSF IL-6.

Acute disseminated encephalomyelitis (ADEM) is one characteristic manifestation of myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD). A previously healthy man presented with retro-orbital headache and urinary retention 14 days after Tdap vaccination. Brain and spine MRI suggested a CNS demyelinating process. Despite treatment with IV steroids, he deteriorated, manifesting hemiparesis and later impaired consciousness, requiring intubation. A repeat brain MRI demonstrated new bilateral supratentorial lesions associated with venous sinus thrombosis, hemorrhage, and midline shift. Anti-MOG antibody was present at a high titer. CSF IL-6 protein was >2,000 times above the upper limits of normal. He improved after plasma exchange, then began monthly treatment alone with anti-IL-6 receptor antibody, tocilizumab, and has remained stable. This case highlights how adult-onset MOGAD, like childhood ADEM, can rapidly become life-threatening. The markedly elevated CSF IL-6 observed here supports consideration for evaluating CSF cytokines more broadly in patients with acute MOGAD.

AN ENHANCED BRAIN TUMOR SEGMENTATION USING AN IMPROVED 3D U-NET TOPOLOGY: SOLUTION TO BRATS 2020 CHALLENGE

The process of automatically recognizing malignant brain tissues and labeling them according to tumor types is known as brain tumor segmentation. Manually segmenting a tumor from a brain MRI takes a long time and is prone to errors. Thereby, a variety of fast and accurate brain tumor segmentation approaches have been developed. Deep learning algorithms have recently exhibited outstanding segmentation performance. As a result, this research suggested U-Net architecture, which is a deep learning topology extension for segmentation. The BraTS2020 dataset is used in this study to assess the efficiency of the suggested topology. The proposed U-Net model gained an accuracy of 99.8%, which is better than the state of the result obtained so far. In terms of accuracy, the simulation results reveal that the proposed U-Net design outperforms the existing models.

An enhanced pattern detection and segmentation of brain tumors in MRI images using deep learning technique

Neuroscience is a swiftly progressing discipline that aims to unravel the intricate workings of the human brain and mind. Brain tumors, ranging from non-cancerous to malignant forms, pose a significant diagnostic challenge due to the presence of more than 100 distinct types. Effective treatment hinges on the precise detection and segmentation of these tumors early. We introduce a cutting-edge deep-learning approach employing a binary convolutional neural network (BCNN) to address this. This method is employed to segment the 10 most prevalent brain tumor types and is a significant improvement over current models restricted to only segmenting four types. Our methodology begins with acquiring MRI images, followed by a detailed preprocessing stage where images undergo binary conversion using an adaptive thresholding method and morphological operations. This prepares the data for the next step, which is segmentation. The segmentation identifies the tumor type and classifies it according to its grade (Grade I to Grade IV) and differentiates it from healthy brain tissue. We also curated a unique dataset comprising 6,600 brain MRI images specifically for this study. The overall performance achieved by our proposed model is 99.36%. The effectiveness of our model is underscored by its remarkable performance metrics, achieving 99.40% accuracy, 99.32% precision, 99.45% recall, and a 99.28% F-Measure in segmentation tasks.

Neurological diagnostic tests for patients with and without delirium: a prospective observational study.

Since most of the precipitating factors of delirium are not due to neurological disorders, neurological diagnostic tests (NDTs) may be of limited value. We hypothesized that delirium has a high burden of NDTs with a low diagnostic yield. All patients admitted to the internal medicine wards of a single secondary teaching hospital between November 2019 and January 2020 were eligible. Within the first 48 h of their admission, they had a formal evaluation by a neuropsychologist to screen for presence of delirium. NDTs (brain MRI, brain CT, electroencephalography (EEG), and lumbar puncture) performed during the hospital stay were compared between patients with and without delirium using a logistic regression model stratified by a propensity score. The proportions of diagnostic yield (acute anomalies that changed the treatment management) provided by each type of examination were compared. Of 217 patients included, 19/32 patients (61%) with delirium had one or more NDTs, compared to 48/185 (26%) without delirium (adjusted OR 2.7; 95%CI 1.1-6.7; p = 0.027). The proportions of NDT results affecting management for patients with and without delirium were 13 and 20% for brain CT scans (p = 0.71), 29 and 38% for brain MRI (p = 0.99), and 20 and 10% for EEGs (p = 0.99), respectively. The higher proportion of NDTs performed on patients with delirium was associated with a low diagnostic yield, although not statistically different from those performed among inpatients without delirium. There is a need for restrictive, evidence-based guidelines to help with the work-up for patients with delirium.

Spontaneous posterior fossa hemorrhage: profile and functional outcome in patients attending Tanta stroke unit

BackgroundThe most dangerous and least curable type of stroke is spontaneous intracerebral hemorrhage (ICH), and prognosis is highly correlated with location and size in the posterior fossa. The objective of this work was to estimate the frequency of posterior fossa hemorrhage (PFH) in Tanta University Hospitals, as well as identify functional outcomes and mortality in PFH.MethodsThis study was performed on 33 posterior fossa hemorrhagic patients and 119 posterior ischemic stroke patients (PCIS) submitted to the CT brain and the MRI brain, using the following scales: GCS and NIHSS, and the intracerebral hemorrhage scale (ICH score).ResultsPosterior fossa hemorrhage (PFH) represents 16.83% of total hemorrhagic stroke in the ER. Vertigo and DCL are more common in PFH (60.6%, 48.4%) than in PCIS. 82% of PFH patients had hypertension (HTN) hemorrhage. The cerebellum is the most common site for PFH (48%), pontine (24%), thalamic (18%), and midbrain (9%). PFH had unfavorable outcomes in 55% of the studied patients; the MRS mean was 4; and 39% died in the follow-up.ConclusionPosterior fossa hemorrhage is a potentially serious neurovascular emergency associated with complex symptomatology. PFH demonstrates diverse prognoses depending on the location of the intracerebral hemorrhage and the size of the hematoma.

Hybrid deep spatial and statistical feature fusion for accurate MRI brain tumor classification

The classification of medical images is crucial in the biomedical field, and despite attempts to address the issue, significant challenges persist. To effectively categorize medical images, collecting and integrating statistical information that accurately describes the image is essential. This study proposes a unique method for feature extraction that combines deep spatial characteristics with handmade statistical features. The approach involves extracting statistical radiomics features using advanced techniques, followed by a novel handcrafted feature fusion method inspired by the ResNet deep learning model. A new feature fusion framework (FusionNet) is then used to reduce image dimensionality and simplify computation. The proposed approach is tested on MRI images of brain tumors from the BraTS dataset, and the results show that it outperforms existing methods regarding classification accuracy. The study presents three models, including a handcrafted-based model and two CNN models, which completed the binary classification task. The recommended hybrid approach achieved a high F1 score of 96.12 ± 0.41, precision of 97.77 ± 0.32, and accuracy of 97.53 ± 0.24, indicating that it has the potential to serve as a valuable tool for pathologists.

MDB-90. PRIMARY LEPTOMENINGEAL MEDULLOBLASTOMA: A SINGLE-SITE RETROSPECTIVE STUDY OF 5 CASES

Abstract BACKGROUND Primary leptomeningeal medulloblastoma without mass is a rare entity with fewer than 10 reported paediatric cases. Establishing an accurate diagnosis is challenging and reported outcomes are very poor. METHODS We conducted a retrospective analysis of cases presenting to the Royal Children’s Hospital Melbourne between 2013 and 2023. RESULTS Between 2013 and 2023 five patients, all male, were identified, with an average age of 6.6 years [1.9 - 12.2 years]. The presenting history was short in all cases (2-3 weeks) and all had symptoms of raised intracranial pressure. Diagnostic imaging (MRI brain and spine) showed non-specific leptomeningeal thickening and enhancement with no primary posterior fossa mass seen; interestingly only two imaging reports considered malignancy in the differential diagnosis. Surgical biopsy confirmed the diagnosis of medulloblastoma on histology; 3 anaplastic and 2 with classic histology. Subgrouping by IHC, available for 4 patients, showed non-WNT/non-SHH, with one reclassified as SHH by DNA methylation (performed in 2 patients). MYC was amplified in one patient (assessed by FISH in all tumours). Four patients were treated with craniospinal irradiation (36-39.6Gy with 18Gy boost), followed by chemotherapy as per SJMB12 stratum N3 (n=3) or HeadStart III (n=1). One case, an infant, was treated according to COG ACNS0334 with concurrent intraventricular topotecan, followed by maintenance with irinotecan/temozolomide/IVent topotecan. At follow up (average 54 months; 11 – 126 months), four children with residual disease on end of treatment MRI are alive without disease progression. One patient with classical SHH medulloblastoma and MYCN amplification progressed on treatment and died of disease 11 months after diagnosis. CONCLUSIONS Contrary to the historical literature, our case series suggests a more favourable outcome if this disease is recognised early. Further studies are warranted to better understand the molecular profile of these tumours.

DIPG-59. RADIATION-INDUCED DIPG IN A CHILD PREVIOUSLY IRRADIATED FOR CRANIOPHARYNGIOMA: CASE REPORT AND LITERATURE REVIEW

Abstract BACKGROUND Radiation-induced second malignancies occur in a subset of patients following cranial radiation therapy (RT). In Craniopharyngioma (CP), adjuvant RT is commonly recommended for residual tumor or recurrence, and radiation-induced malignant gliomas (RIMGs) are rarely reported. METHODS We report a case of radiation-induced diffuse intrinsic pontine glioma (DIPG) in pediatric Craniopharyngioma and conducted a review of previously reported cases. RESULTS A 14-year-old boy presented with complaints of headaches and vomiting for 1 month; difficulty in walking, and slurred speech for 1 week, with Lansky Performance Score (LPS) of 20. Eight years before this admission, he underwent surgical excision and 3D-conformal RT for Craniopharyngioma. His recent MRI brain was suggestive of DIPG and after a multidisciplinary discussion re-irradiation (30Gy in 10 fractions) was given. He has been alive for 5 months since diagnosis with improved symptoms and LPS (70). Including the index case, 19 cases of RIMGs in CP were identified. All except one were reported from high-income countries. Only 4 involved the pons/brainstem. The median age at CP diagnosis was 7.0 years (2.0-22.0 years), and with RIMG was 18 (6.8-41.0 years). Median latency period was 10.0 years (4.5-25.0 years). The female-to-male ratio was 1.8:1. The median previous RT dose was 54.8 Gy (49.3-60.1 Gy) with 37% cases treated with 3D conformal and 37% with conventional RT (not specified in 26%). Cerebral cortex (66.6%) was the most common site for the RIMG with temporal lobe predisposition. Chemotherapy was given in 56%, surgical excision in 50% and repeat RT in 31% cases with a median survival of 4 months (0-13 months). CONCLUSION We report the first case of radiation-induced DIPG in pediatric Craniopharyngioma in an LMIC. RIMG appears to be a rare occurrence in CP and doesn’t seem to be associated with the RT type. The overall prognosis is extremely poor.

Brain age has limited utility as a biomarker for capturing fluid cognition in older individuals.

One well-known biomarker candidate that supposedly helps capture fluid cognition is Brain Age, or a predicted value based on machine-learning models built to predict chronological age from brain MRI. To formally evaluate the utility of Brain Age for capturing fluid cognition, we built 26 age-prediction models for Brain Age based on different combinations of MRI modalities, using the Human Connectome Project in Aging (n=504, 36-100 years old). First, based on commonality analyses, we found a large overlap between Brain Age and chronological age: Brain Age could uniquely add only around 1.6% in explaining variation in fluid cognition over and above chronological age. Second, the age-prediction models that performed better at predicting chronological age did NOT necessarily create better Brain Age for capturing fluid cognition over and above chronological age. Instead, better-performing age-prediction models created Brain Age that overlapped larger with chronological age, up to around 29% out of 32%, in explaining fluid cognition. Third, Brain Age missed around 11% of the total variation in fluid cognition that could have been explained by the brain variation. That is, directly predicting fluid cognition from brain MRI data (instead of relying on Brain Age and chronological age) could lead to around a 1/3-time improvement of the total variation explained. Accordingly, we demonstrated the limited utility of Brain Age as a biomarker for fluid cognition and made some suggestions to ensure the utility of Brain Age in explaining fluid cognition and other phenotypes of interest.

Framingham Stroke Risk Profile Score and White Matter Disease Progression.

To evaluate the relationship between Framingham Stroke Risk Profile (FSRP) score and rate of white matter hyperintensity (WMH) progression and cognition. Consecutive patients enrolled in the Mayo Clinic Florida Familial Cerebrovascular Diseases Registry (2011-2020) with 2 brain-MRI scans at least 1 year apart were included. The primary outcome was annual change in WMH volume (cm3/year) stratified as fast versus slow (above vs. below median). Cognition was assessed using a Mini-Mental State Exam (MMSE, 0-30). FSRP score (0 to 8) was calculated by summing the presence of age 65 years or older, smoking, systolic blood pressure greater than 130 mmHg, diabetes, coronary disease, atrial fibrillation, left ventricular hypertrophy, and antihypertensive medication use. Linear and logistic regression analyses were performed to examine the association between FSRP and WMH progression, and cognition. In all, 207 patients were included, with a mean age of 60±16 y and 54.6% female. FSRP scores risk distribution was: 31.9% scored 0 to 1, 36.7% scored 2 to 3, and 31.4% scored ≥4. The baseline WMH volume was 9.6 cm3 (IQR: 3.3-28.4 cm3), and the annual rate of WMH progression was 0.9 cm3/year (IQR: 0.1 to 3.1 cm3/year). A higher FSRP score was associated with fast WMH progression (odds ratio, 1.45; 95% CI: 1.22-1.72; P<0.001) and a lower MMSE score (23.6 vs. 27.1; P<0.001). There was a dose-dependent relationship between higher FSRP score and fast WMH progression (odds ratios, 2.20, 4.64, 7.86, 8.03 for FSRP scores 1, 2, 3, and ≥4, respectively; trend P<0.001). This study demonstrated an association between higher FSRP scores and accelerated WMH progression, as well as lower cognition.

Plasma Biomarkers of Brain Injury and Their Association With Brain MRI and Cognition in Type 1 Diabetes.

To evaluate associations between plasma biomarkers of brain injury and MRI and cognitive measures in participants with type 1 diabetes (T1D) from the Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications (DCCT/EDIC) study. Plasma amyloid-β-40, amyloid-β-42, neurofilament light chain (NfL), phosphorylated Tau-181 (pTau-181), and glial fibrillary acidic protein (GFAP) were measured in 373 adults who participated in the DCCT/EDIC study. MRI assessments included total brain and white matter hyperintensity volumes, white matter mean fractional anisotropy, and indices of Alzheimer disease (AD)-like atrophy and predicted brain age. Cognitive measures included memory and psychomotor and mental efficiency tests and assessments of cognitive impairment. Participants were 60 (range 44-74) years old with 38 (30-51) years' T1D duration. Higher NfL was associated with an increase in predicted brain age (0.51 years per 20% increase in NfL; P < 0.001) and a 19.5% increase in the odds of impaired cognition (P < 0.01). Higher NfL and pTau-181 were associated with lower psychomotor and mental efficiency (P < 0.001) but not poorer memory. Amyloid-β measures were not associated with study measures. A 1% increase in mean HbA1c was associated with a 14.6% higher NfL and 12.8% higher pTau-181 (P < 0.0001). In this aging T1D cohort, biomarkers of brain injury did not demonstrate an AD-like profile. NfL emerged as a biomarker of interest in T1D because of its association with higher HbA1c, accelerated brain aging on MRI, and cognitive dysfunction. Our study suggests that early neurodegeneration in adults with T1D is likely due to non-AD/nonamyloid mechanisms.

Sequence‐agnostic motion‐correction leveraging efficiently calibrated Pilot Tone signals

AbstractPurposeThis study leverages externally generated Pilot Tone (PT) signals to perform motion‐corrected brain MRI for sequences with arbitrary k‐space sampling and image contrast.Theory and MethodsPT signals are promising external motion sensors due to their cost‐effectiveness, easy workflow, and consistent performance across contrasts and sampling patterns. However, they lack robust calibration pipelines. This work calibrates PT signal to rigid motion parameters acquired during short blocks (˜4 s) of motion calibration (MC) acquisitions, which are short enough to unobstructively fit between acquisitions. MC acquisitions leverage self‐navigated trajectories that enable state‐of‐the‐art motion estimation methods for efficient calibration. To capture the range of patient motion occurring throughout the examination, distributed motion calibration (DMC) uses data acquired from MC scans distributed across the entire examination. After calibration, PT is used to retrospectively motion‐correct sequences with arbitrary k‐space sampling and image contrast. Additionally, a data‐driven calibration refinement is proposed to tailor calibration models to individual acquisitions. In vivo experiments involving 12 healthy volunteers tested the DMC protocol's ability to robustly correct subject motion.ResultsThe proposed calibration pipeline produces pose parameters consistent with reference values, even when distributing only six of these approximately 4‐s MC blocks, resulting in a total acquisition time of 22 s. In vivo motion experiments reveal significant () improved motion correction with increased signal to residual ratio for both MPRAGE and SPACE sequences with standard k‐space acquisition, especially when motion is large. Additionally, results highlight the benefits of using a distributed calibration approach.ConclusionsThis study presents a framework for performing motion‐corrected brain MRI in sequences with arbitrary k‐space encoding and contrast, using externally generated PT signals. The DMC protocol is introduced, promoting observation of patient motion occurring throughout the examination and providing a calibration pipeline suitable for clinical deployment. The method's application is demonstrated in standard volumetric MPRAGE and SPACE sequences.

Radiologist’s approach in diagnosing fronto-ethmoidal meningoencephalocele in an adult: a case report

BackgroundFronto-ethmoidal meningoencephalocele is an uncommon pathology. Most of the cases present a history of trauma or paranasal surgical intervention. Spontaneous development of such pathology is extremely rare. The aim of this case report was to demonstrate a rare appearance of spontaneous fronto-ethmoidal meningoencephalocele in an adult male with high-quality images in multiple modalities used in radiology.Case presentationThis case report demonstrates an extremely rare pathology of spontaneous development of fronto-ethmoidal meningoencephalocele in a 50-year-old male. The patient complained of swelling involving the nasal bridge, the left side of the nose, and the left cheek for more than 20 years, which was spontaneous without any trauma or surgical intervention. The patient underwent radiological investigations of ultrasonography, computed tomography of the paranasal sinus, and contrast-enhanced magnetic resonance imaging of the brain. The diagnosis of spontaneous development of left fronto-ethmoidal meningoencephalocele abutting the left orbit was made. No other complications of the brain tissue were noted.ConclusionsKnowledge about etiopathogenesis and various types of meningoencephalocele helps manage this pathology.

Overall survival following heterogeneous FDG-guided dose-escalation for locally advanced NSCLC in the international phase III NARLAL2 trial.

LBA8069 Background: The survival and loco-regional control for patients (pts) with locally advanced non-small cell lung cancer (LA_NSCLC) treated with radiotherapy (RT) are dismal despite adjuvant Durvalumab. However, there have been concerns about dose escalation for these pts since the unexpected result of the dose-escalation trial RTOG0617. A novel approach is therefore warranted to escalate the dose to the tumor. A possible approach is to use the principle from stereotactic body radiotherapy (SBRT) with inhomogeneous dose distribution. SBRT has demonstrated excellent local control in early-stage lung cancer. The international multicenter NARLAL2 (novel approach to RT for LA_NSCLC) phase III trial on dose escalation, randomized pts with LA_NSCLC between standard 66 Gy/ 33 fractions (F) versus heterogeneous FDG-PET driven dose escalation, aiming at mean dose to GTV-tumorPET 95 Gy/ 33 F and mean dose to GTV-nodePET 74 Gy/ 33 F while strictly respecting dose to organs at risk. We here present the data on overall survival (OS) 1 year after the end of recruitment. Methods: Pts aged ≥18 years with LA_NSCLC were recruited from seven institutions in Denmark and Norway. Eligibility criteria included ECOG PS 0-1, histological or cytological confirmed NSCLC stage IIB-IIIB, signed informed consent, and a clinically acceptable plan for RT with conventional 66 Gy/ 33 F. PET-CT and brain MR were part of staging. Pts were randomly assigned to either treatment group (1:1, stratified for center and histology). The trial aimed to have iso-lung toxicity within the treatment arms by creating two RT plans (before randomization) for each patient (one for each treatment arm) with matching mean lung dose and lung V20Gy. The follow-up (FU) were scheduled weekly during RT, every 3rd month for 2 years, and every 6th month for another 3 years after randomization. At FU visit a CT-scan and toxicity scoring were performed. All interim analyses were passed without interventions (toxicity and OS). The trial's primary endpoint was time to loco-regional failure from randomization. Secondary endpoints included OS, acute, and late toxicity. The sample size calculations requested 350 pts to be enrolled in the study. Recruitment of the pre-planned number of pts finalized in March 2023. The trial was registered with ClinicalTrials.gov (NCT02354274). Results: From January 2015 to March 2023, 350 pts were randomized: 177 and 173 pts in standard and escalated arms respectively. The two groups were well-balanced regarding age, gender, stage, and PS. The dose to GTV-tumor was 66.5 Gy [66.2, 67.1] (median [IQR]) in the standard arm and 88.1 Gy [84.9, 90.4] in the escalated arm. Median OS were 35.8 months (m) and 51.6 m for pts treated in the standard and escalated arm, respectively ( p = 0.36). Median FU time 50.8 m (reverse Kaplan-Meier). Conclusions: Dose escalation is safe in the NARLAL2 setting with respect to OS. Clinical trial information: NCT02354274 .

Brain image segmentation with fuzzy entropy clustering and PSO-GWO optimization techniques

In the field of brain MRI analysis, image segmentation serves various purposes such as quantifying and visualizing anatomical structures, analyzing brain changes, delineating pathological regions, and aiding in surgical planning and image-guided interventions. Over the past few decades, diverse segmentation techniques with varying degrees of accuracy and complexity have been developed. Real-world brain MRI images often encounter intensity in homogeneity, posing a significant challenge in accurate segmentation. The prevailing image segmentation algorithms, predominantly region-based, typically rely on the homogeneity of image intensities in specific regions of interest. However, these methods often fall short of providing precise segmentation results due to intensity in homogeneity. To address these challenges and enhance segmentation performance, this paper introduce a novel objective function named Fuzzy Entropy Clustering with Local Spatial Information and Bias Correction (FECSB). Additionally, we propose a novel hybrid algorithm that combines Particle Swarm Optimization (PSO) and Grey Wolf Optimization (GWO) to maximize the effectiveness of the FECSB function in MRI brain image segmentation. The proposed algorithm undergoes rigorous evaluation using benchmark MRI brain images, including those from the McConnell Brain Imaging Center (BrainWeb). The experimental results unequivocally demonstrate the superiority of the PSO-GWO clustering method over the traditional Fuzzy C Means (FCM) method. Across various image slices, the PSO-GWO method consistently outperforms FCM in terms of accuracy, showing improvements ranging from 1.28% to 1.46%, approximately achieving 99.37% accuracy.

Seeing more than the Tip of the Iceberg: Approaches to Subthreshold Effects in Functional Magnetic Resonance Imaging of the Brain.

Many functional magnetic resonance imaging (fMRI) studies and presurgical mapping applications rely on mass-univariate inference with subsequent multiple comparison correction. Statistical results are frequently visualized as thresholded statistical maps. This approach has inherent limitations including the risk of drawing overly-selective conclusions based only on selective results passing such thresholds. This article gives an overview of both established and newly emerging scientific approaches to supplement such conventional analyses by incorporating information about subthreshold effects with the aim to improve interpretation of findings or leverage awider array of information. Topics covered include neuroimaging data visualization, p-value histogram analysis and the related Higher Criticism approach for detecting rare and weak effects. Further examples from multivariate analyses and dedicated Bayesian approaches are provided.

Neurological abnormalities in individuals with Marfan syndrome: results from a genetically confirmed Italian cohort.

Neurological abnormalities have been frequently reported in individuals with Marfan Syndrome (MFS). However, available data relies solely on retrospective studies predating current diagnostic criteria. Cross-sectional study comprehensively investigating neurological abnormalities within a prospective cohort of adults (≥ 18years) with genetically confirmed MFS referred to an Italian hub center for heritable connective tissue diseases (Jan. 1st - Nov. 15th, 2021). We included a total of 38 individuals (53% female). The commonest neurological symptom was migraine (58%), usually without aura (73%). Neuropsychological testing was generally unremarkable, whilst anxiety and depression were highly prevalent within our cohort (42% and 34%, respectively). The most frequent brain parenchymal abnormality was the presence of cortico-subcortical hypointense spots on brain MRI T2* Gradient-Echo sequences (39%), which were found only in patients with a prior history of aortic surgery. Migraineurs had a higher frequency of brain vessels tortuosity vs. individuals without migraine (73% vs. 31%; p = 0.027) and showed higher average and maximum tortuosity indexes in both anterior and posterior circulation brain vessels (all p < 0.05). At univariate regression analysis, the presence of brain vessels tortuosity was significantly associated with a higher risk of migraine (OR 5.87, CI 95% 1.42-24.11; p = 0.014). Our study confirms that neurological abnormalities are frequent in individuals with MFS. While migraine appears to be associated with brain vessels tortuosity, brain parenchymal abnormalities are typical of individuals with a prior history of aortic surgery. Larger prospective studies are needed to understand the relationship between parenchymal abnormalities and long-term cognitive outcomes.

Carbon Monoxide-Related Vision Loss in an Acute Burn Patient.

Carbon monoxide poisoning can occur as part of smoke exposure in the burn population. Here we report the case of a 32-year-old, previously healthy male, with carbon monoxide-related blindness after smoke exposure in an apartment fire. Cerebral hypoperfusion was diagnosed using magnetic resonance imaging of the brain, and the patient was diagnosed with cortical visual impairment. He was treated with hyperbaric oxygen therapy following which he had partial recovery of his vision. There is a paucity of information regarding this phenomenon and its treatment.

Lung Function and Brain MRI Outcomes in the Atherosclerosis Risk in Communities Neurocognitive Study

Background: Brain imaging studies may provide etiologic insight into observed links between lung function and dementia and stroke. Objective: We evaluated associations of lung function measures with brain MRI markers of vascular and neurodegenerative disease in the ARIC Neurocognitive Study, as few studies have examined the associations. Methods: Lung function was measured at participants’ midlife in 1990–1992 (mean age = 56±5 years) and later-life in 2011–2013 (mean age = 76±5 years), and brain MRI was performed in 2011–2013. Linear regression models were used to examine the associations of lung function with brain and white matter hyperintensity (WMH) volumes, and logistic regression models were used for cerebral infarcts and microbleeds, adjusting for potential confounders. Results: In cross-sectional analysis (i.e., examining later-life lung function and MRI markers, n = 1,223), higher forced-expiratory volume in one second (FEV1) and forced vital capacity (FVC) were associated with larger brain and lower WMH volumes [e.g., 8.62 (95% CI:2.54–14.71) cm3 greater total brain volume per one-liter higher FEV1]. No association was seen with microbleeds in the overall sample, but higher FVC was associated with lower odds of microbleeds in never-smokers and higher odds in ever-smokers. In the cross-temporal analysis (i.e., associations with midlife lung function, n = 1,787), higher FVC levels were significantly associated with lower later-life brain volumes. Conclusions: Our results support modest associations of better lung function with less neurodegenerative and cerebrovascular pathology, although findings for microbleeds were unexpected in ever-smokers.