T1 Images Research Articles

NIMG-29. ADVANCED MRI BIOMARKERS PREDICT EARLY RESPONSE TO TUMOR TREATING FIELDS IN GLIOBLASTOMA

Abstract BACKGROUND Tumor-treating fields (TTFields) is a novel US FDA-approved antimitotic treatment modality for patients with newly diagnosed and recurrent glioblastoma, shown to improve both OS and PFS (Stupp et al 2015). Yet, how to best monitor response to TTfields remains unclear. Conventional (anatomic) MRI is unreliable, often showing initial early radiographic progression followed by tumor regression and clinical benefit, thereby delaying confirmation of response. To address this limitation, we evaluate the utility of quantitative (physiologic) MRI biomarkers. METHODS Patients with newly diagnosed or recurrent IDH wildtype glioblastoma who underwent MRI with DSC-MRI perfusion imaging at 1-2, 3-4 and 5-6 months after TTField treatment were retrospectively identified for this study. Delta T1 (dT1) images were created from standardized (calibrated) pre- and post-contrast T1-weighted images, from which an enhancing lesion volume was objectively determined. Standardized and leakage-corrected relative cerebral blood volume (sRCBV) images were created from the DSC-MRI data. Together, dT1 and sRCBV were used to generate class maps of fractional tumor burden (FTB), which identify highly-vascular and avascular (treatment effect) regions within contrast-enhancement. Kaplan-Meier survival analysis was performed to determine if positive versus negative changes in these metrics, at each time-point relative to pre-treatment values, are predictive of survival. RESULTS 20 patients with newly diagnosed (n=17) or recurrent (n=4) IDH wildtype glioblastoma with a mean TTField compliance of 74.9% were identified. At 1-2 months no metric predicted a survival difference, consistent with the known 4-week delay in tumor stabilization following TTField therapy. At months 3-4 and 5-6 decreasing dT1-determined enhancing volumes showed a survival benefit (p=0.0081, p=0.03). Likewise, a decreasing percentage of highly-vascular tissue, determined from FTB class maps, demonstrated a survival benefit (p=0.0013). CONCLUSIONS Quantitative MRI metrics, including dT1-derived enhancing volumes and FTB/sRCBV-defined regions of high vascularity, demonstrate an ability to provide early indicators of response to TTField treatment.

NIMG-41. ASSOCIATION BETWEEN PERFUSION IMAGING METRICS AND RADIO-PATHOMIC MAPS OF TUMOR PROBABILITY WITHIN AND BEYOND THE CONTRAST-ENHANCING VOLUME IN GLIOMA PATIENTS

Abstract Perfusion MRI, using both contrast-based techniques such as dynamic susceptibility imaging (DSC) and non-contrast-based techniques like arterial spin labeling (ASL) have been used to monitor blood flow as a marker of angiogenic glioma presence, and showed substantial potential in the differentiation of true progression from pseudoprogression post-treatment. This study uses radio-pathomic maps of cellularity sensitive to areas of non-enhancing tumor to test the hypothesis that perfusion-derived markers of tumor probability will associate with tumor presence within contrast-enhancement but not beyond the enhancing margin. This study included pre-surgical relative cerebral blood volume (rCBV) estimates derived from DSC perfusion data from the PENN-GBM dataset (n=456) and presurgical ASL images from the UCSF-PDGM dataset (n=426) for analyses. The T1, T1C, FLAIR, and ADC images from each patient were used to generate radio-pathomic cell density maps using a previously validated model that excels at accurate detection of non-enhancing tumor presence. Mean cell density, rCBV, and ASL were computed for each corresponding patient within included segmentations for contrast-enhancement (excluding necrotic core) and FLAIR hyperintensity (excluding both necrotic core and enhancement). Pearson’s correlations were then used to quantify the association between perfusion-derived estimates and mean cell density within each region of interest. Both rCBV and ASL showed positive associations with cell density within contrast enhancement (rCBV: R=0.280, p< 0.001; ASL: R=0.117, p=0.016). However, both perfusion metrics also showed no association with cell density within the non-enhancing, FLAIR hyperintense region (rCBV: R=0.0162, p=0.731; ASL: R=-0.213, p=0.634). These results suggest that perfusion imaging successfully identifies angiogenic tumor but may be less efficacious in detecting non-enhancing tumor presence. Future studies should examine how perfusion’s relationship with hypercellular tumor presence evolves in the presence of treatment, as well as in relation to other advanced imaging metrics such as MR spectroscopy and CEST imaging.

NIMG-11. AUTOPSY-BASED RADIO-PATHOMIC MAPS OF TISSUE COMPOSITION DELINEATE IDH1 STATS IN GLIOMAS

Abstract Isocitrate dehydrogenase 1 (IDH1) mutation status is used as an important prognostic marker for gliomas, where IDH1-wildtype patients see shorter survival than patients with an IDH1 mutation. This study uses radio-pathomic maps of cell, extracellular fluid (ECF), and cytoplasm (Cyt) density developed using conventional MRI and aligned autopsy samples to test the hypothesis that IDH1-mutant tumors differ in contrast-enhancing and non-enhancing tissue composition from IDH1-wildtype tumors. A total of 426 patients from the UCSF-PDGM data set (380 IDH1-wildtype, 46 IDH1-mutant) were included in this study. T1, T1C, FLAIR and ADC images from each patient’s pre-surgical MRI were used to generate whole brain radio-pathomic maps of cell, ECF, and Cyt density using a previously reported algorithm. This tool was trained using aligned autopsy samples as ground truth and is particularly adept at highlighting areas of tumor beyond traditional imaging signatures. The mean value from each feature map was computed for each patient both within non-necrotic contrast enhancement and non-enhancing FLAIR hyperintensity. Higher ECF density (F=15.45, p< 0.001) and lower Cyt density (F=8.51, p=0.004) was observed within contrast-enhancement for IDH1 mutant patients, with no difference observed for cell density within contrast enhancement between mutation statuses (F=0.03, p=0.86). Higher cell density (F=4.16, p< 0.042), Higher ECF density (F=4.65, p=0.032), lower Cyt density (F=4.48, p=0.035) was also found in patients with IDH1 mutations in the non-enhancing FLAIR hyperintense region. These results suggest that the large-scale tissue composition of IDH1-mutant tumors may differ from IDH1-wildtype tumors, suggesting differences in growth patterns and pathological composition between tumor types. Future studies examining how tissue composition post-treatment over time may elucidate how pathological characteristics evolve for each tumor type.

T1rho and T2rho based myocardial tissue characterisation in small animals at high-field MRI

Abstract Introduction Cardiac tissue characterisation using T2-based MRI promises non-invasive diagnosis or monitoring of inflammatory heart disease, toxic heart damage after chemotherapy and myocardial infarction or post-infarction patients. T2 relaxation is also an indicator for the detection of myocardial oedema or intramyocardial haemorrhage [1]. However, accurate T2 quantification is challenging due to motion, blood flow and field inhomogeneities, especially in high-field MRI [2]. In this work, we present an alternative to T2 imaging that uses spin-locking (SL) to provide a robust measurement of T2ρ relaxation. It is known from relaxation theory that T2ρ has a sensitivity almost identical to T2 [3]. In the small animal study presented here, cardiac T2ρ quantification is tested for the first time using a newly developed pulse sequence and compared with established methods. Methods All measurements were performed on a preclinical 7T MRI. T2 contrast was prepared using a CPMG (Carr-Purcell-Meiboom-Gill) sequence. T2ρ contrast was conventionally generated by a balanced-SL (BSL) preparation [4]. Furthermore, a new approach for T2ρ was developed based on a MLEV sequence (Malcolm-Levitt, [2]). In contrast to [2], all pulse delays were minimised here, producing pure T2ρ contrast (Fig. 1). The new method was first validated in phantom experiments and then tested in three mice with radial image acquisition accelerated for cardio-MRI. Results The results of the phantom study are shown in figure 2. No significant differences were found between BSL and MLEV for T2ρ quantification (mean deviation 0.74%). In vivo, significant artefacts were observed for T2 (Fig. 3), while both T2ρ methods showed improved image quality. For the evaluation of relaxation times in the left ventricle, the mean across all animals was: T2=22.9±2.6ms (R2=0.979), BSL-T2ρ=51.4±5.4ms (R2=0.983) and MLEV-T2ρ=60.0±3.4ms (R2>0.99). Thus, the MLEV-T2ρ method achieves the most robust quantification with a mean R2>0.99 and provides relaxation time maps with diagnostic image quality. Discussion: In the present study, myocardial T2ρ mapping was tested at 7T. While no significant differences between BSL and MLEV appeared in phantom experiments, significant difference was found in vivo. Here, only the MLEV technique could achieve robust quantification. One reason for the improved performance is the continuous refocusing and minimisation of free dephasing of the transverse magnetisation. The results also show that MLEV-T2ρ has improved image quality and more robust quantification compared to CPMG-T2. Conclusion Cardiac T2ρ quantification is a robust alternative to established T2 imaging and can be applied under high-field conditions. A combined measurement of T1ρ and T2ρ relaxation time could be used for native detection of myocardial fibrosis and oedema.Figure 1)Comparison of image qualityFigure 2)Results in a knockout model

High intensity plaque in carotid artery on magnetic resonance imaging predict long term major adverse cardiac and cerebrovascular events

Abstract Background Cardiocerebrovascular diseases remain the major cause of death in the world. The presence of carotid plaque is a surrogate marker for systemic atherosclerosis. High intensity plaque (HIP) in carotid artery on magnetic resonance imaging (MRI) was reported to be associated with the ipsilateral ischemic stroke as well as coronary artery disease. However, few studies have examined the impact of carotid HIP on long-term prognosis of cardiocerebrovascular disease. Purpose We investigated whether HIP in carotid artery associated with long term major adverse cardiac and cerebrovascular events (MACCE). Method We retrospectively analyzed 241 patients suspected carotid artery stenosis and underwent MRI at our hospital between January 2002 and December 2004. Plaque imaging was performed with non-contrast T1 imaging, and we defined as HIP if plaque-to-myocardium signal-intensity ratio (PMR) ≥2.0. Patients were divided into the HIP group (n=134) or non-HIP group (n=107). The outcome of this study was first incidence of ischemic cardiac or cerebrovascular events. Cardiovascular events were defined as cardiac death (sudden death, fetal myocardial infarction) and non-fetal myocardial infarction. Cerebrovascular events were defined as cerebral infarction. We compared the cumulative incidents of MACCE between with or without HIP groups using Kaplan-Meier method and log-rank test. Multivariate Cox regression analysis was carried out to assess whether HIP could be independent predicter of MACCE. Results Median age of study patients was 70 (inter quartile range; 65-75) and 215 (88.1%) patients were male, 185 patients (76.6%) had established vascular diseases. The median follow-up periods were 8.6 years (inter quartile range; 4.0-14.2 years). The presence of HIP was associated with MACCE (p<0.001). Multivariate analysis shows that the presence of HIP was an independent predicting factor for MACCE. When we analyzed incidence of each cardiovascular and cerebrovascular event, the presence of HIP was significantly associated with cerebrovascular events (p=0.004) and cardiovascular events(p=0.03), respectively. Conclusion The presence of carotid HIP was associated with long term prognosis for MACCE. Our findings indicate that carotid HIP is a surrogate marker for vulnerable patients with cardiocerebrovascular disease.

Research on the clinical factors of cardiac iron deposition in children with beta-thalassemia major

Magnetic resonance imaging (MRI) T2* is the gold standard for detecting iron deposition in cardiac tissue, but the technique has limitations and cannot be fully performed in paediatric thalassemia patients. The aim of this study was to analyse clinical data to identify other predictors of cardiac iron deposition. A retrospective analysis was performed on 370 children with β-TM. According to the cardiac MRI results, patients were allocated to a cardiac deposition group and noncardiac deposition group. Multivariate analysis revealed that genotype and corrected QT interval were associated with cardiac iron deposition, indicating that the-β0/β0 genotype conferred greater susceptibility to cardiac iron deposition. Receiver operating characteristic curve (ROC) analysis was performed, and the area under the curve (AUC) of genotype was 0.651. The AUC for the corrected QT interval was 0.711, at a cut-off value of 418.5 ms. ROC analysis of the combined genotype and corrected QT interval showed an AUC of 0.762 with 81.3% sensitivity and 64.7% specificity. Compared to patients with the β+/β+ and β0β+ genotypes, β0β0 children with β-TM were more likely to have cardiac iron deposition. Conclusion: The genotype and QTc interval can be used to predict cardiac iron deposition in children with β-TM who are unable to undergo MRI T2 testing.

Metal artifact reduction around cervical spine implant using diffusion tensor imaging at 3T: A phantom study

PurposeDiffusion MRI continues to play a key role in non-invasively assessing spinal cord integrity and pre-operative injury evaluation. However, post-operative Diffusion Tensor Imaging (DTI) acquisition of patients with metal implants results in severe geometric distortion. We propose and demonstrate a method to alleviate the technical challenges facing the acquisition of DTI on post-operative cases and longitudinal evaluation of therapeutics. Material and methodsThe described technique is based on the combination of the reduced Field-Of-View (rFOV) strategy and the phase segmented EPI, termed rFOV-PS-EPI. A custom-built phantom based on a cervical spine model with metal implants was used to collect DTI data at 3 Tesla scanner using: rFOV-PS-EPI, reduced Field-Of-View single-shot EPI (rFOV-SS-EPI), and conventional full FOV techniques including SS-EPI, PS-EPI, and readout-segmented EPI (RS-EPI). Geometric distortion, SNR, and signal void were assessed to evaluate images and compare the sequences. A two-sample t-test was performed with p-value of 0.05 or less to indicate statistical significance. ResultsThe reduced FOV techniques showed better capability to reduce distortions compared to the Full FOV techniques. The rFOV-PS-EPI method provided DTI images of the phantom at the level of the hardware whereas the conventional rFOV-SS-EPI is useful only when the metal is approximately 20 mm away. In addition, compared to the rFOV-SS-EPI technique, the suggested approach produced smaller signal voids area as well as significantly reduced geometric distortion in Circularity (p < 0.005) and Eccentricity (p < 0.005) measurements. No statistically significant differences were found for these geometric distortion measurements between the rFOV-PS-EPI DTI sequence and conventional structural T2 images (p > 0.05). ConclusionThe combination of rFOV and a phase-segmented acquisition approach is effective for reducing metal-induced distortions in DTI scan on spinal cord with metal hardware at 3 T.

Femoral cartilage ultrasound echo-intensity is a valid measure of cartilage composition.

This study aimed to create a conversion equation that accurately predicts cartilage magnetic resonance imaging (MRI) T2 relaxation times using ultrasound echo-intensity and common participant demographics. We recruited 15 participants with a primary anterior cruciate ligament reconstruction between the ages of 18 and 35 years at 1-5 years after surgery. A single investigator completed a transverse suprapatellar scan with the ACLR limb in max knee flexion to image the femoral trochlea cartilage. A single reader manually segmented the femoral cartilage cross-sectional area to assess the echo-intensity (i.e., mean gray-scale pixel value). At a separate visit, a T2 mapping sequence with the MRI beam set to an oblique angle was used to image the femoral trochlea cartilage. A single reader manually segmented the cartilage cross-sectional area on a single MRI slice to assess the T2 relaxation time. A stepwise, multiple linear regression was used to predict T2 relaxation time from cartilage echo-intensity and common demographic variables. We created a conversion equation using the regression betas and then used an ICC and Bland-Altman plot to assess agreement between the estimated and true T2 relaxation time. Cartilage ultrasound echo-intensity and age significantly predicted T2 relaxation time (F = 7.33, p = 0.008, R2 = 0.55). When using the new conversion equation to estimate T2 relaxation time from cartilage echo-intensity and age, there was strong agreement between the estimated and true T2 relaxation time (ICC2,k = 0.84). This study provides promising preliminary data that cartilage echo-intensity combined with age can be used as a clinically accessible tool for evaluating cartilage composition.

A novel deep learning model for glioma epilepsy associated with the identification of human cytomegalovirus infection injuries based on head MR.

In this study, a deep learning model was established based on head MRI to predict a crucial evaluation parameter in the assessment of injuries resulting from human cytomegalovirus infection: the occurrence of glioma-related epilepsy. The relationship between glioma and epilepsy was investigated, which serves as a significant indicator of labor force impairment. This study enrolled 142 glioma patients, including 127 from Shengjing Hospital of China Medical University, and 15 from the Second Affiliated Hospital of Dalian Medical University. T1 and T2 sequence images of patients' head MRIs were utilized to predict the occurrence of glioma-associated epilepsy. To validate the model's performance, the results of machine learning and deep learning models were compared. The machine learning model employed manually annotated texture features from tumor regions for modeling. On the other hand, the deep learning model utilized fused data consisting of tumor-containing T1 and T2 sequence images for modeling. The neural network based on MobileNet_v3 performed the best, achieving an accuracy of 86.96% on the validation set and 75.89% on the test set. The performance of this neural network model significantly surpassed all the machine learning models, both on the validation and test sets. In this study, we have developed a neural network utilizing head MRI, which can predict the likelihood of glioma-associated epilepsy in untreated glioma patients based on T1 and T2 sequence images. This advancement provides forensic support for the assessment of injuries related to human cytomegalovirus infection.

RBC Exchange Transfusion As an Adjunct Therapy to Control Iron Overload in Patients with Transfusion-Dependent Thalassemia

Background Patients with transfusion-dependent thalassemia (TDT) require red blood cell (RBC) transfusions as frequently as every 2-4 weeks to maintain a pre-transfusion hemoglobin of 9.0-10.5 g/dL for patients without cardiac complications. Chronic RBC transfusions increase body iron stores leading to iron deposition in liver, pancreatic, and cardiac tissues. Deferoxamine, deferiprone, and deferasirox are the iron chelators currently licensed for clinical use to manage iron overload in TDT patients with side effects ranging from nausea to nephrotoxicity and hearing loss. RBC exchange transfusion (RBCX), particularly in conjunction with isovolumic hemodilution, has been utilized for patients with sickle cell disease as a means of stabilizing iron overload. The 2015 ASFA Red Blood Cell Exchange consensus supports RBCX to reduce or prevent iron overload in sickle cell disease. Review of literature shows that RBCX can be beneficial as an acute intervention for patients with TDT and pulmonary hypertension however there is a paucity of literature documenting chronic RBCX use in TDT patients with iron overload. Case series This series presents five patients with TDT who were transitioned from chronic simple RBC transfusions to chronic RBCX after developing treatment-refractory iron overload as evidenced by serum ferritin elevation. Patients were treated on a transfusion schedule with a pre-transfusion goal hemoglobin of 9.5g/dL or higher and interval 4-6 weeks. Patient A is a 14 year-old male who developed significant iron overload (peak ferritin of 7077) on deferasirox 20 mg/kg/day and MRI T2 imaging suggestive of iron deposition. After transition to RBCX, ferritin decreased significantly with a post-RBCX mean of 1382. Blood utilization was 4200 ml three months pre-RBCX and 5625 ml three months post-RBCX. Patient B is a 23 year-old male with a peak ferritin of 1310 prior to RBCX on 23 mg/kg/day of deferasirox complicated by mild hearing loss. Serum ferritin has shown stabilization, with a mean post-RBCX ferritin of 880. Blood utilization was 2400 ml three months pre-RBCX and 8100 ml three months post-RBCX. Patient C is a 17 year-old male with a peak ferritin of 1400 with deferasirox management complicated by acute renal injury. Mean serum ferritin of 633 post-RBCX. Blood utilization was 1200 ml three months pre-RBCX and 5200 ml three months post-RBCX. Patient D is a 17 year-old male managed on 23 mg/kg/day of deferasirox with a peak ferritin of 3060 on pre-RBCX. The patient transitioned to chronic RBCX with mean serum ferritin of 1073. Blood utilization was 1800 ml three months pre-RBCX and 7700 ml three months post-RBCX. Patient E is a 17 year-old male with peak ferritin of 3404 despite 20 mg/kg/day of deferasirox prior to chronic RBCX. Mean serum ferritin after transition to RBCX was found to be 1282. Blood utilization was 1500 ml three months pre-RBCX and 4900 ml three months post-RBCX. All 5 patients have tolerated RBC exchange procedures without complications. Serum ferritin levels pre- and post-RBC exchange were trended pre- and post- RBCX (Figure 1). Serum ferritins were averaged together for each patient to obtain an equal number of time points considered prior to and after starting RBCX therapy. Descriptive statistics (Table 1) were used to summarize average ferritin levels for the patient group. A Wilcoxon signed-rank test was performed to assess the median difference in ferritin level from pre-RBCX to post-RBCX. All analyses were conducted in SAS version 9.4. P &amp;lt;0.05 is considered statistically significant. Median pre-RBCX ferritin level for the study group is 2489.3 (Inter-quartile range (IQR): 1190.0, 2659.0). The median post-RBCX ferritin level for the series is 1329.3 (IQR: 941.0, 1711.0). After subtracting the post-RBCX ferritin level from the pre-RBCX ferritin level, the median change for the group is 457 (IQR: 249.0, 1160.0) (p=0.06). Conclusion This case series documents the successful clinical application of chronic RBCX in TDT patients as a means of stabilizing serum ferritin levels over time. Mean ferritin levels were significantly lower, clinically, after transitioning from chronic simple RBC transfusion to RBCX (Table 1), though analysis is limited due to cohort size. Blood utilization increased after transitioning to RBCX. Next steps in evaluating our practice for the patient group will be to evaluate iron deposition status with MRI T2* imaging.

Comparison of compositional MRI techniques to quantify the regenerative potential of articular cartilage: a preclinical minipig model after osteochondral defect treatments with autologous mesenchymal stromal cells and unseeded scaffolds.

The field of orthopedics seeks effective, safer methods for evaluating articular cartilage regeneration. Despite various treatment innovations, non-invasive, contrast-free full quantitative assessments of hyaline articular cartilage's regenerative potential using compositional magnetic resonance (MR) sequences remain challenging. In this context, our aim was to investigate the effectiveness of different MR sequences for quantitative assessment of cartilage and to compare them with the current gold standard delayed gadolinium-enhanced MR imaging of cartilage (dGEMRIC) measurements. We employed ex vivo imaging in a preclinical minipig model to assess knee cartilage regeneration. Standardized osteochondral defects were drilled in the proximal femur of the specimens (n=14), which were divided into four groups. Porcine collagen scaffolds seeded with autologous adipose-derived stromal cells (ASC), autologous bone marrow stromal cells (BMSC), and unseeded scaffolds (US) were implanted in femoral defects. Furthermore, there was a defect group which received no treatment. After 6 months, the specimens were examined using different compositional MR methods, including the gold standard dGEMRIC as well as T1, T2, T2*, and T1ρ techniques. The statistical evaluation involved comparing the defect region with the uninjured tibia and femur cartilage layers and all measurements were performed on a clinical 3T MR Scanner. In the untreated defect group, we observed significant differences in the defect region, with dGEMRIC values significantly lower (404.86±64.2 ms, P=0.018) and T2 times significantly higher (44.24±2.75 ms, P<0.001). Contrastingly, in all three treatment groups (ASC, BMSC, US), there were no significant differences among the three regions in the dGEMRIC sequence, suggesting successful cartilage regeneration. However, T1, T2*, and T1ρ sequences failed to detect such differences, highlighting their lower sensitivity for cartilage regeneration. As expected, dGEMRIC is well suited for monitoring cartilage regeneration. Interestingly, T2 imaging also proved to be a reliable cartilage imaging technique and thus offers a contrast agent-free alternative to the former gold standard for subsequent in vivo studies investigating the cartilage regeneration potential of different treatment modalities.

Abnormal brain structure in atopic dermatitis: Evidence from Mendelian randomization study.

Structural abnormalities in the brain of patients with atopic dermatitis (AD) have been reported; however, the cause has not been determined yet. Herein, we used Mendelian randomization (MR) to reveal the causal effect of AD on brain structure. This study utilized summary statistics from genome-wide association studies (GWASs) to investigate a collection of cerebral structural measures, encompassing cortical thickness (CT), cortical surface area (CA), and subcortical volumes in T1 images. A comprehensive GWAS meta-analysis identified a total of 20 independent single nucleotide polymorphisms linked to AD, surpassing the genome-wide significance threshold (p<5 × 10⁻⁸). MR estimates were aggregated through the application of the inverse variance weighted method. Additional complementary analyses (i.e., MR-Egger and weighted median approaches) were conducted to further assess the robustness of the obtained results. Sensitivity analysis and multivariate MR (MVMR) while adjusting for brain structural changes risk factors (i.e., depression and anxiety) were performed to assess the reliability and stability of observed causality. Genetically determined AD exhibited a causal link with reduced caudate volumes (IVW-MR: β=-0.186, p=0.001, p-corrected=0.009). Furthermore, we identified potential causal associations between AD and reduced CT in the cingulate region (posterior cingulate, IVW-MR: β=-0.065, p=0.018, p-corrected=0.551; isthmus cingulate, IVW-MR: β=-0.086, p=0.003, p-corrected=0.188), as well as abnormal cortical surface area (CA) in the supramarginal (IVW-MR: β=-0.047, p=0.044, p-corrected=0.714) and isthmus cingulate (IVW-MR: β=0.053, p=0.018, p-corrected=0.714). Additional supplementary analyses yielded consistent outcomes. There was no evidence of horizontal pleiotropy. MVMR analysis showed that the causal effects of AD on abnormal brain structure remained significant while adjusting for depression and anxiety. This MR study provided suggestive evidence that decreased caudate nucleus, posterior cingulate cortex, isthmus cingulate cortex and supramarginal gyrus are suggestively associated with higher AD risk. Future investigation into the brain regions is recommended, which helps to clarify the underlying mechanisms and point to new therapies against AD.

6 Posterior cerebral artery-defined white matter hyperintensities are associated with object domain memory and transentorhinal volume independently of global beta-amyloid burden

Objective:White matter hyperintensities (WMH) are a radiological marker of small vessel cerebrovascular disease that are related to cognition and memory decline in aging and Alzheimer’s disease (AD). However, the mechanisms that link WMH to memory impairment and whether they interact with or act independently of AD pathophysiology are unclear. The transentorhinal cortex (BA35) is among the earliest anatomical regions to show tau deposition and subsequent atrophy, and baseline posterior WMH is related to longitudinal cortical thinning of the entorhinal cortex. However, it is unclear whether regional WMH are related to BA35 volume specifically, and whether this relationship is influenced by amyloid-β (Aβ) burden. We hypothesized that WMH in the vascular territory of the posterior cerebral artery (PCA), which perfuses both posterior and medial temporal lobe regions, would be associated with reduced BA35 volume and with lower memory in older adults independently of Aβ.Participants and Methods:114 older adults without dementia, aged 60 to 98 years (mean (SD) = 78.31 (11.02), 71 (62.8%) women), were included. Regional WMH volumes were derived from T2-FLAIR images using ANTs, a vascular territory atlas and manual editing. Global Aβ was assessed with 18F-florbetapir PET, using SUVR of a cortical composite region (FBP mean SUVR) with a cerebellar reference region. Total transentorhinal (BA35) volume was derived using T1 and T2-weighted images using ASHS. To assess hippocampal pattern separation ability, an index of episodic memory, participants completed both object (MDT-O) and spatial (MDT-S) versions of a mnemonic discrimination task, with the lure discrimination index as the outcome. Using linear regressions, we first tested for associations among PCA-defined WMH, Aβ, BA35 volume, and MDT-S and MDT-O scores. We then tested whether the relationship between PCA-defined WMH and MDT-O performance was mediated by BA35 volume and whether this mediation was moderated by Aβ. All models adjusted for age, sex, and education.Results:PCA-defined WMH were related to higher FBP mean SUVR (b=0.287, p=0.042) and lower BA35 volume (b=-0.222, p=0.038). PCA-defined WMH were also negatively related to MDT-O performance (b=-0.229, p=0.044), but not to MDT-S (b=-0.171, p=0.118). FBP mean SUVR was not related to BA35 volume (b=-0.131, p=0.344) or MDT performance (MDT-S: b=-0.138, p=0.348; MDT-O: b=0.059, p=0.690). Furthermore, FBP mean SUVR did not interact with PCA-defined WMH to predict memory performance (interaction b=-0.039, p=0.973), nor BA35 volume (interaction b=-0.140, p=0.894). The association of PCA-defined WMH to MDT-O was fully mediated by BA35 volume (indirect effect b=-0.0005, 95% CI (-0.0014, -0.0003)). This mediation was not moderated by FBP mean SUVR (indirect effect b=-0.00001, 95% CI (-0.001, 0.001)).Conclusions:We found that PCA-defined WMH were related to memory performance in older adults, and this association is fully mediated by transentorhinal volume. While PCA-defined WMH are related to higher global Aβ burden, there is no interaction between PCA-defined WMH and Aβ on BA35 volume. These findings point to an amyloid-independent vascular pathway towards memory decline in aging and AD. Future work should examine whether the pathway linking PCA-defined WMH to transentorhinal cortex atrophy and subsequent memory decline is mediated by regional tau pathology.

Prediction of Stroke Onset Time With Combined Fast High-Resolution Magnetic Resonance Spectroscopic and Quantitative T2 Mapping.

The purpose of this work is to develop a multispectral imaging approach that combines fast high-resolution 3D magnetic resonance spectroscopic imaging (MRSI) and fast quantitative T2 mapping to capture the multifactorial biochemical changes within stroke lesions and evaluate its potentials for stroke onset time prediction. Special imaging sequences combining fast trajectories and sparse sampling were used to obtain whole-brain maps of both neurometabolites (2.0 × 3.0 × 3.0 mm3) and quantitative T2 values (1.9 × 1.9 × 3.0 mm3) within a 9-minute scan. Participants with ischemic stroke at hyperacute (0-24 h, n = 23) or acute (24 h-7d, n = 33) phase were recruited in this study. Lesion N-acetylaspartate (NAA), lactate, choline, creatine, and T2 signals were compared between groups and correlated with patient symptomatic duration. Bayesian regression analyses were employed to compare the predictive models of symptomatic duration using multispectral signals. In both groups, increased T2 and lactate levels, as well as decreased NAA and choline levels were detected within the lesion (all p < 0.001). Changes in T2, NAA, choline, and creatine signals were correlated with symptomatic duration for all patients (all p < 0.005). Predictive models of stroke onset time combining signals from MRSI and T2 mapping achieved the best performance (hyperacute: R2 = 0.438; all: R2 = 0.548). The proposed multispectral imaging approach provides a combination of biomarkers that index early pathological changes after stroke in a clinical-feasible time and improves the assessment of the duration of cerebral infarction. Developing accurate and efficient neuroimaging techniques to provide sensitive biomarkers for prediction of stroke onset time is of great importance for maximizing the proportion of patients eligible for therapeutic intervention. The proposed method provides a clinically feasible tool for the assessment of symptom onset time post ischemic stroke, which will help guide time-sensitive clinical management.

Deep Learning Based on Enhanced MRI T1 Imaging to Differentiate Small-cell and Non-small-cell Primary Lung Cancers in Patients with Brain Metastases.

To differentiate the primary small-cell lung cancer (SCLC) and non-small-cell lung cancer (NSCLC) for patients with brain metastases (BMs) based on a deep learning (DL) model using contrast-enhanced magnetic resonance imaging (MRI) T1 weighted (T1CE) images. Out of 711 patients with BMs of lung cancer origin (SCLC 232, NSCLC 479), the MRI datasets of 192 patients (lesions' widths and heights > 30 pixels) with BMs from lung cancer (73 SCLC and 119 NSCLC) confirmed pathologically were enrolled, retrospectively. A typical convolutional neural network ResNet18 was applied for the automatic classification of BMs lesions from lung cancer based on T1CE images, with training and testing groups randomized per patient to eliminate learning bias. A 5-fold cross-validation was performed to evaluate the classification of the model. The receiver operating characteristic (ROC) curve, accuracy, precision, recall and f1 score were calculated. For a 5-fold cross-validation test, the DL model achieved AUCs of 0.8019 and 0.8024 for SCLC and NSCLC patients with BMs, respectively, and a mean overall accuracy of 0.7515±0.04. The DL model performed well in differentiating the primary SCLC and NSCLC with BMs. The proposed DL model is feasible and effective in differentiating the pathological subtypes of SCLC and NSCLC causing BMs, which may be used as a new tool for oncologists to diagnose noninvasively BMs and guide therapy based on the imaging structure of tumors.

The alteration of cortical microstructure similarity in drug-resistant epilepsy correlated with mTOR pathway genes

Drug-resistant epilepsy (DRE) is associated with distributed laminar disruptions due to cytoarchitectonic pathologies, which may be characterized by multimodal MRI approaches such as morphometric similarity networks (MSNs). However, the genetic and histological underpinning of MSN alterations in DRE remains poorly understood, hampering its clinical application. We enrolled 60 patients with DRE and 23 controls, acquiring T1 and diffusion spectrum imaging data with a 3.0T GE SIGNA Premier scanner. Morphometric similarity networks (MSNs) were constructed and analyzed to identify microstructure similarity differences between patients and controls. Subsequently, patient-specific MSN alteration patterns were associated with gene expression using the GAMBA tool, and layer-specific neuronal signature mapping were also applied. During these analyses, sex and age were adjusted as covariates and multiple comparisons corrections were applied when appropriate. We observed widespread MSN changes in patients with DRE and identified five distinct MSN alteration patterns. Major patterns presented pattern-specific associations with expressions of epilepsy-related genes, particularly involving the mTOR pathway. Histological analysis confirmed the presence of cortical microstructure changes in areas with MSN alterations and revealed cellular abnormalities matching the aforementioned genetic risks. Our findings highlight the potential of quantifying laminar-related microstructure integrity using MSN to uncover the cytoarchitectonic changes in the pathophysiology of DRE. This approach may facilitate the identification of genetic and histological underpinnings of MSN alterations in DRE, ultimately aiding in the development of targeted therapeutic strategies. The National Natural Science Foundation of China, the Ministry of Science and Technology of the People's Republic of China, and the Beijing Municipal Health Commission.

Endoscopic endonasal marsupialization of rathke cleft cysts: clinical outcomes and risk factors analysis of visual impairment, pituitary dysfunction, and CSF leak.

This paper assesses the clinical and imaging characteristics, histopathological findings, and treatment outcomes of patients with Rathke's cleft cyst (RCC), as well as identifies potential risk factors for preoperative visual and pituitary dysfunction, intraoperative cerebrospinal fluid (CSF) leak, and recurrence. Through analyzing these factors, the study aims to contribute to the current understanding of the management of RCCs and identify opportunities for improving patient outcomes. We performed a retrospective analysis of 45 RCC patients between ages 18-80 treated by Endoscopic Endonasal Approach (EEA) and cyst marsupialization between 2010 and 2022 at a single institution. The median patient age was 34, and 73% were female. The mean follow-up was 70 ± 43 months. Preoperative visual impairment correlated with cyst diameter (OR = 1.41, 95% CI = 1.07 to 1.85, p-value = 0.01) and older age (OR = 1.06, 95% CI = 1.01 to 1.11, p-value = 0.02). Intraoperative CSF leaks were 11 times more likely for cysts ≥ 2cm (OR = 11.3, 95% CI = 1.25 to 97.37, p-value = 0.03), with the odds of leakage doubling for every 0.1cm increase in cyst size (OR = 1.41, 95% CI = 1.08 to 1.84, p-value = 0.01). Preoperative RCC appearing hypointense on T1 images demonstrated significantly higher CSF leak rates than hyperintense lesions (OR = 122.88, 95% CI = 1.5 to 10077.54, p-value = 0.03). Preoperative pituitary hypofunction was significantly more likely in patients with the presence of inflammation on histopathology (OR = 20.53, 95% CI = 2.20 to 191.45, p-value = 0.008 ) and T2 hyperintensity on magnetic resonance imaging (MRI) sequences (OR = 23.2, 95% CI = 2.56 to 211.02, p-value = 0.005). Notably, except for the hyperprolactinemia, no postoperative improvement was observed in pituitary function. Carefully considering risk factors, surgeons can appropriately counsel patients and deliver expectations for complications and long-term results. In contrast to preoperative visual impairment, preoperative pituitary dysfunction was found to have the least improvement post-surgery. It was the most significant permanent complication, with our data indicating the link to the cyst signal intensity on T2 MR and inflammation on histopathology. Earlier surgical intervention might improve the preservation of pituitary function.

The Role of Improved Motion-Sensitized Driven Equilibrium Blood Suppression and Fat Saturation on T2 Relaxation Time, Using GraSE Sequence in Cardiac Magnetic Resonance Imaging.

T2 mapping is a valuable technique in cardiac MR imaging that offers insights into the microstructural characteristics of myocardial tissue. However, it was shown that myocardial T2 relaxation times (T2) measured vary significantly depending on sequence, sequence parameters, and field strength. To assess T2 variability and image quality in cardiac T2 maps using four variants of the gradient-spin echo (GraSE) sequence, having different methods of blood signal suppression (double inversion recovery (DIR) and improved motion-sensitized driven equilibrium (iMSDE) and with and without the addition of fat saturation (FS). Prospective. 48 healthy volunteers (46.7 +/- 21.5 years, 24 male) with no cardiac history. GraSE sequence with DIR (GraSEDIR), with iMSDE (GraSEiMSDE) and FS (GraSEDIR-FS) and with both iMSDE and FS (GraSEiMSDE-FS) at 1.5T. Global T2 from three short axis myocardial slices. and image quality assessments using a 5-point Lickert scale (1, (non-diagnostic) to 5, (excellent)) were conducted to evaluate the impact of DB and FS techniques on myocardial T2 measurements and image quality. Paired t-tests or non-parametric equivalents for comparisons between sequences. The Bland-Altmann plots and Pearson rank correlation analyses, as appropriate. A P value <0.05 was considered statistically significant. The mean global T2 values for GraSEDIR, GraSEDIR-FS, GraSEiMSDE, and GraSEiMSDE-FS, were 52.84 ± 5.72 msec, 54.98 ± 3.59 msec, 53.9 ± 4.05 msec, and 55.14 ± 4.28 msec, respectively, with no significant differences (P = 0.092). High image quality scores (>4 out of 5) were obtained for all sequence variants with no significant differences between them (P = 0.11). All GraSE sequence variants exhibited approximately the same results and variations in the DB technique and addition of FS did not have significant impact on myocardial T2 values. 2 TECHNICAL EFFICACY: Stage 1.

ROI-based analysis of diffusion indices in healthy subjects and subjects with deficit or non-deficit syndrome schizophrenia

We analyzed DTI data involving 22 healthy subjects (HC), 15 patients with deficit syndrome schizophrenia (DSZ), and 25 patients with non-deficit syndrome schizophrenia (NDSZ). We used a 1.5-T MRI scanner to collect diffusion-weighted images and T1 images, which were employed to correct distortions and deformations within the diffusion-weighted images. For 156 regions of interest (ROI), we calculated the average fractional anisotropy (FA), mean diffusion (MD), and radial diffusion (RD). Each ROI underwent a group-wise comparison using permutation F-test, followed by post hoc pairwise comparisons with Bonferroni correction. In general, we observed lower FA in both schizophrenia groups compared to HC (i.e., HC>(DSZ=NDSZ)), while MD and RD showed the opposite pattern. Notably, specific ROIs with reduced FA in schizophrenia patients included bilateral nucleus accumbens, left fusiform area, brain stem, anterior corpus callosum, left rostral and caudal anterior cingulate, right posterior cingulate, left thalamus, left hippocampus, left inferior temporal cortex, right superior temporal cortex, left pars triangularis and right lingual gyrus. Significantly, the right cuneus exhibited lower FA in the DSZ group compared to other groups ((HC=NDSZ)>DSZ), without affecting MD and RD. These results indicate that compromised neural integrity in the cuneus may contribute to the pathophysiological distinctions between DSZ and NDSZ.

Deep learning-driven MRI trigeminal nerve segmentation with SEVB-net.

Trigeminal neuralgia (TN) poses significant challenges in its diagnosis and treatment due to its extreme pain. Magnetic resonance imaging (MRI) plays a crucial role in diagnosing TN and understanding its pathogenesis. Manual delineation of the trigeminal nerve in volumetric images is time-consuming and subjective. This study introduces a Squeeze and Excitation with BottleNeck V-Net (SEVB-Net), a novel approach for the automatic segmentation of the trigeminal nerve in three-dimensional T2 MRI volumes. We enrolled 88 patients with trigeminal neuralgia and 99 healthy volunteers, dividing them into training and testing groups. The SEVB-Net was designed for end-to-end training, taking three-dimensional T2 images as input and producing a segmentation volume of the same size. We assessed the performance of the basic V-Net, nnUNet, and SEVB-Net models by calculating the Dice similarity coefficient (DSC), sensitivity, precision, and network complexity. Additionally, we used the Mann-Whitney U test to compare the time required for manual segmentation and automatic segmentation with manual modification. In the testing group, the experimental results demonstrated that the proposed method achieved state-of-the-art performance. SEVB-Net combined with the ωDoubleLoss loss function achieved a DSC ranging from 0.6070 to 0.7923. SEVB-Net combined with the ωDoubleLoss method and nnUNet combined with the DoubleLoss method, achieved DSC, sensitivity, and precision values exceeding 0.7. However, SEVB-Net significantly reduced the number of parameters (2.20 M), memory consumption (11.41 MB), and model size (17.02 MB), resulting in improved computation and forward time compared with nnUNet. The difference in average time between manual segmentation and automatic segmentation with manual modification for both radiologists was statistically significant (p < 0.001). The experimental results demonstrate that the proposed method can automatically segment the root and three main branches of the trigeminal nerve in three-dimensional T2 images. SEVB-Net, compared with the basic V-Net model, showed improved segmentation performance and achieved a level similar to nnUNet. The segmentation volumes of both SEVB-Net and nnUNet aligned with expert annotations but SEVB-Net displayed a more lightweight feature.