Depth- and curvature-based quantitative susceptibility mapping analyses of cortical iron in Alzheimer's disease.

In addition to amyloid beta plaques and neurofibrillary tangles, Alzheimer's disease (AD) has been associated with elevated iron in deep gray matter nuclei using quantitative susceptibility mapping (QSM). However, only a few studies have examined cortical iron, using more macroscopic approaches that cannot assess layer-specific differences. Here, we conducted column-based QSM analyses to assess whether AD-related increases in cortical iron vary in relation to layer-specific differences in the type and density of neurons. We obtained global and regional measures of positive (iron) and negative (myelin, protein aggregation) susceptibility from 22 adults with AD and 22 demographically matched healthy controls. Depth-wise analyses indicated that global susceptibility increased from the pial surface to the gray/white matter boundary, with a larger slope for positive susceptibility in the left hemisphere for adults with AD than controls. Curvature-based analyses indicated larger global susceptibility for adults with AD versus controls; the right hemisphere versus left; and gyri versus sulci. Region-of-interest analyses identified similar depth- and curvature-specific group differences, especially for temporo-parietal regions. Finding that iron accumulates in a topographically heterogenous manner across the cortical mantle may help explain the profound cognitive deterioration that differentiates AD from the slowing of general motor processes in healthy aging.

An exploratory research report on brain mineralization in postoperative delirium and cognitive decline.

Delirium is a severe postoperative complication associated with poor overall and especially neurocognitive prognosis. Altered brain mineralization is found in neurodegenerative disorders but has not been studied in postoperative delirium and postoperative cognitive decline. We hypothesized that mineralization-related hypointensity in susceptibility-weighted magnetic resonance imaging (SWI) is associated with postoperative delirium and cognitive decline. In an exploratory, hypothesis-generating study, we analysed a subsample of cognitively healthy patients ≥65 years who underwent SWI before (N = 65) and 3 months after surgery (N = 33). We measured relative SWI intensities in the basal ganglia, hippocampus and posterior basal forebrain cholinergic system (pBFCS). A post hoc analysis of two pBFCS subregions (Ch4, Ch4p) was conducted. Patients were screened for delirium until the seventh postoperative day. Cognitive testing was performed before and 3 months after surgery. Fourteen patients developed delirium. After adjustment for age, sex, preoperative cognition and region volume, only pBFCS hypointensity was associated with delirium (regression coefficient [90% CI]: B = -15.3 [-31.6; -0.8]). After adjustments for surgery duration, age, sex and region volume, perioperative change in relative SWI intensities of the pBFCS was associated with cognitive decline 3 months after surgery at a trend level (B = 6.8 [-0.9; 14.1]), which was probably driven by a stronger association in subregion Ch4p (B = 9.3 [2.3; 16.2]). Brain mineralization, particularly in the cerebral cholinergic system, could be a pathomechanism in postoperative delirium and cognitive decline. Evidence from our studies is limited because of the small sample and a SWI dataset unfit for iron quantification, and the analyses presented here should be considered exploratory.

Simultaneous time-of-flight MR angiography and quantitative susceptibility mapping with key time-of-flight features.

A technique for combined time-of-flight (TOF) MR angiography (MRA) and quantitative susceptibility mapping (QSM) was developed with key features of standard three-dimensional (3D) TOF acquisitions, including multiple overlapping thin slab acquisition (MOTSA), ramped RF excitation, and venous saturation. The developed triple-echo 3D TOF-QSM sequence enabled TOF-MRA, susceptibility-weighted imaging (SWI), QSM, and R2* mapping. The effects of ramped RF, resolution, flip angle, venous saturation, and MOTSA were studied on QSM. Six volunteers were scanned at 3 T with the developed sequence, conventional TOF-MRA, and conventional SWI. Quantitative comparison of susceptibility values on QSM and normalized arterial and venous vessel-to-background contrasts on TOF and SWI were performed. The ramped RF excitation created an inherent phase variation in the raw phase. A generic correction factor was computed to remove the phase variation to obtain QSM without artifacts from the TOF-QSM sequence. No statistically significant difference was observed between the developed and standard QSM sequence for susceptibility values. However, maintaining standard TOF features led to compromises in signal-to-noise ratio for QSM and SWI, arising from the use of MOTSA rather than one large 3D slab, higher TOF spatial resolution, increased TOF background suppression due to larger flip angles, and reduced venous signal from venous saturation. In terms of vessel contrast, veins showed higher normalized contrast on SWI derived from TOF-QSM than the standard SWI sequence. While fast flowing arteries had reduced contrast compared with standard TOF-MRA, no statistical difference was observed for slow flowing arteries. Arterial contrast differences largely arise from the longer TR used in TOF-QSM over standard TOF-MRA to accommodate additional later echoes for SWI. In conclusion, although the sequence has a longer TR and slightly lower arterial contrast, provided an adequate correction is made for ramped RF excitation effects on phase, QSM may be performed from a multiecho sequence that includes all key TOF features, thus enabling simultaneous TOF-MRA, SWI, QSM, and R2* map computation.

Enhancing Nigrosome-1 Sign Identification via Interpretable AI using True Susceptibility Weighted Imaging.

BACKGROUND: Nigrosome 1 (N1), the largest nigrosome region in the ventrolateral area of the substantia nigra pars compacta, is identifiable by the "N1 sign" in long echo time gradient echo MRI. The N1 sign's absence is a vital Parkinson's disease (PD) diagnostic marker. However, it is challenging to visualize and assess the N1 sign in clinical practice. PURPOSE: To automatically detect the presence or absence of the N1 sign from true susceptibility weighted imaging by using deep-learning method. STUDY TYPE: Prospective. POPULATION/SUBJECTS: 453 subjects, including 225 PD patients, 120 healthy controls (HCs), and 108 patients with other movement disorders, were prospectively recruited including 227 males and 226 females. They were divided into training, validation, and test cohorts of 289, 73, and 91 cases, respectively. FIELD STRENGTH/SEQUENCE: 3D gradient echo SWI sequence at 3T; 3D multiecho strategically acquired gradient echo imaging at 3T; NM-sensitive 3D gradient echo sequence with MTC pulse at 3T. ASSESSMENT: A neuroradiologist with 5 years of experience manually delineated substantia nigra regions. Two raters with 2 and 36 years of experience assessed the N1 sign on true susceptibility weighted imaging (tSWI), QSM with high-pass filter, and magnitude data combined with MTC data. We proposed NINet, a neural model, for automatic N1 sign identification in tSWI images. STATISTICAL TESTS: We compared the performance of NINet to the subjective reference standard using Receiver Operating Characteristic analyses, and a decision curve analysis assessed identification accuracy. RESULTS: NINet achieved an area under the curve (AUC) of 0.87 (CI: 0.76-0.89) in N1 sign identification, surpassing other models and neuroradiologists. NINet localized the putative N1 sign within tSWI images with 67.3% accuracy. DATA CONCLUSION: Our proposed NINet model's capability to determine the presence or absence of the N1 sign, along with its localization, holds promise for enhancing diagnostic accuracy when evaluating PD using MR images. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY: Stage 1.

An update on susceptibility-weighted imaging in brain gliomas.

Susceptibility-weighted imaging (SWI) has become a standard component of most brain MRI protocols. While traditionally used for detecting and characterising brain hemorrhages typically associated with stroke or trauma, SWI has also shown promising results in glioma assessment. Numerous studies have highlighted SWI's role in differentiating gliomas from other brain lesions, such as primary central nervous system lymphomas or metastases. Additionally, SWI aids radiologists in non-invasively grading gliomas and predicting their phenotypic profiles. Various researchers have suggested incorporating SWI as an adjunct sequence for predicting treatment response and for post-treatment monitoring. A significant focus of these studies is on the detection of intratumoural susceptibility signals (ITSSs) in gliomas, which are indicative of microhemorrhages and vessels within the tumour. The quantity, distribution, and characteristics of these ITSSs can provide radiologists with more precise information for evaluating and characterising gliomas. Furthermore, the potential benefits and added value of performing SWI after the administration of gadolinium-based contrast agents (GBCAs) have been explored. This review offers a comprehensive, educational, and practical overview of the potential applications and future directions of SWI in the context of glioma assessment. CLINICAL RELEVANCE STATEMENT: SWI has proven effective in evaluating gliomas, especially through assessing intratumoural susceptibility signal changes, and is becoming a promising, easily integrated tool in MRI protocols for both pre- and post-treatment assessments. KEY POINTS: • Susceptibility-weighted imaging is the most sensitive sequence for detecting blood and calcium inside brain lesions. • This sequence, acquired with and without gadolinium, helps with glioma diagnosis, characterisation, and grading through the detection of intratumoural susceptibility signals. • There are ongoing challenges that must be faced to clarify the role of susceptibility-weighted imaging for glioma assessment.

Deeply 3D-T1-TFE hypointense voxels are characteristic of phase-rim lesions in multiple sclerosis.

OBJECTIVES: The development of new drugs for the treatment of progressive multiple sclerosis (MS) highlights the need for new prognostic biomarkers. Phase-rim lesions (PRLs) have been proposed as markers of progressive disease but are difficult to identify and quantify. Previous studies have identified T1-hypointensity in PRLs. The aim of this study was to compare the intensity profiles of PRLs and non-PRL white-matter lesions (nPR-WMLs) on three-dimensional T1-weighted turbo field echo (3DT1TFE) MRI. We then evaluated the performance of a derived metric as a surrogate for PRLs as potential markers for risk of disease progression. METHODS: This study enrolled a cohort of relapsing-remitting (n = 10) and secondary progressive MS (n = 10) patients for whom 3 T MRI was available. PRLs and nPR-WMLs were segmented, and voxel-wise normalized T1-intensity histograms were analyzed. The lesions were divided equally into training and test datasets, and the fifth-percentile (p5)-normalized T1-intensity of each lesion was compared between groups and used for classification prediction. RESULTS: Voxel-wise histogram analysis showed a unimodal histogram for nPR-WMLs and a bimodal histogram for PRLs with a large peak in the hypointense limit. Lesion-wise analysis included 1075 nPR-WMLs and 39 PRLs. The p5 intensity of PRLs was significantly lower than that of nPR-WMLs. The T1 intensity-based PRL classifier had a sensitivity of 0.526 and specificity of 0.959. CONCLUSIONS: Profound hypointensity on 3DT1TFE MRI is characteristic of PRLs and rare in other white-matter lesions. Given the widespread availability of T1-weighted imaging, this feature might serve as a surrogate biomarker for smoldering inflammation. CLINICAL RELEVANCE STATEMENT: Quantitative analysis of 3DT1TFE may detect deeply hypointense voxels in multiple sclerosis lesions, which are highly specific to PRLs. This could serve as a specific indicator of smoldering inflammation in MS, aiding in early detection of disease progression. KEY POINTS: • Phase-rim lesions (PRLs) in multiple sclerosis present a characteristic T1-hypointensity on 3DT1TFE MRI. • Intensity-normalized 3DT1TFE can be used to systematically identify and quantify these deeply hypointense foci. • Deep T1-hypointensity may act as an easily detectable, surrogate marker for PRLs.

Deep medullary vein abnormalities impact white matter hyperintensity volume through increases in interstitial free water.

BACKGROUND: Our intent was to explore the mediating role of interstitial free water (FW) linking deep medullary vein (DMV) score to white matter hyperintensity (WMH) volume. METHODS: Our research team conducted a forward-looking analysis of initial clinical and imaging information gathered from 125 patients with cerebral small vessel disease. We identified six anatomic DMV regions on susceptibility weighted imaging (SWI) studies. Each region earned a score of 0-3, determined by the visual conditions of vessels, summing all six to generate a DMV score. We utilized fluid-attenuated inversion recovery (FLAIR) sequences to measure the volume of WMH. Additionally, we employed diffusion tensor imaging (DTI) to assess FW value. RESULTS: DMV score significantly positively correlated with FW value and with WMH volume (p < 0.05), and value of FW positively correlated with WMH volume (p < 0.05). The indirect effect of DMV score on WMH volume was mediated by FW (ß = 0.281, 95% confidence interval [CI]: 0.178-0.388), whether adjusted for age and gender (ß = 0.142, 95% CI: 0.058-0.240) or for age, gender and vascular risk factors (ß = 0.141, 95% CI: 0.054-0.249). CONCLUSION: DMV score correlate with WMH volume by virtue of FW increases in white matter.

Predictive Utility of Diffusion MRI After Mild Traumatic Brain Injury in Civilian Populations: A Systematic Review.

OBJECTIVE: A considerable number of people experience persisting symptoms and functional limitations after mild traumatic brain injury (mTBI). It is unclear whether subtle white matter changes contribute to this phenomenon. In this systematic review, the authors evaluated whether microstructural white matter indices on advanced MRI are related to clinical dysfunction among patients without abnormalities on standard brain computed tomography (CT) or MRI (uncomplicated mTBI). METHODS: A search of multiple databases was performed. Studies with individuals who experienced blast-related, sports-related, or multiple mTBIs were excluded. Diffusion tensor imaging (DTI) and susceptibility-weighted imaging (SWI) metrics and cognitive, neuropsychiatric, or functional outcome measures were extracted from each study. RESULTS: Thirteen studies were selected (participants with mTBI, N=553; healthy control group, N=438). Seven DTI studies evaluated cognitive function, with five reporting significant correlations between reduced white matter integrity and deficits in attention, processing speed, and executive function at 6-12 months after injury (three studies included only individuals with uncomplicated mTBI). Four studies found significant correlations between DTI metrics and persistent postconcussive symptoms after 3-12 months (one study included only individuals with uncomplicated mTBI). Two SWI studies reported conflicting findings regarding the relationship between the presence of microbleeds and postconcussive symptoms. CONCLUSIONS: The results revealed that indices of microstructural white matter integrity may relate to clinical presentation 3-12 months after injury in uncomplicated mTBI. However, analysis methods and brain regions studied varied across studies. Further research is needed to identify relationships between white matter indices in specific brain regions and symptom persistence beyond 12 months.

The value of susceptibility weighted imaging for immediate assessing the hyperacute outcome of MRgFUS ablation for uterine fibroids: a preliminary study.

PURPOSE: To investigate the value of susceptibility weighted imaging (SWI) for assessing the hyperacute outcome of ablation of uterine fibroids immediately after magnetic resonance-guided focused ultrasound (MRgFUS) treatment. METHODS: This retrospective imaging study included patients who underwent SWI and contrast-enhanced (CE) MR within 15 min of MRgFUS ablation for uterine fibroids. Two readers independently assessed the SWI features of ablative lesions and their association with the non-perfused volume (NPV) ratio. The intraclass correlation coefficient (ICC) and diagnostic value of SWI findings were calculated. RESULTS: A total of 27 uterine fibroids from 21 participants (mean age 40.1 ± 7.2 years) were analyzed. 51.9% (14/27) leiomyomas had NPV ratio ≥90%. In post-ablation SWI images, the interobserver ICC for the relative signal intensity and hypointense peripheral rim were 0.613 and 0.843, respectively (both p < .001). There was a significant difference in the prevalence of hypointense peripheral rim in leiomyomas with NPV ratio ≥90% and < 90% (p < .01), while the prevalence of relative signal intensity showed no significant difference (p > .05). When using the complete hypointense peripheral rim as a diagnostic criterion to identify NPV ratio ≥ 90%, readers 1 and 2 showed diagnostic sensitivity, specificity, and accuracy of 85.7%, 76.9%, 81.5%, and 78.6%, 76.9%, 77.8%, respectively. CONCLUSION: Identifying a complete hypointense peripheral rim on SWI may be a potential imaging marker for assessing the hyperacute outcome of uterine fibroids ablation by MRgFUS, specifically in determining whether the NPV ratio is ≥90%.

Predictors of cerebral microbleeds in patients with autosomal dominant polycystic kidney disease.

OBJECTIVES: Individuals with autosomal dominant polycystic kidney disease (ADPKD) can present with vascular abnormalities, including intracranial aneurysms. However, whether ADPKD is associated with cerebral small-vessel disease, such as cerebral microbleeds (CM), remains unclear. The study analyzes the prevalence of CM and the associated clinical and radiological factors in patients with ADPKD. METHODS: The retrospective study enrolled 140 consecutive patients with ADPKD from July 2014 to May 2023. Brain MRIs were analyzed for the presence of CM with susceptibility-weighted imaging (SWI), which were categorized based on lesion location (lobar, deep, or infratentorial). RESULT: In this study, the prevalence of CM is 26.4%. Chronic kidney disease (CKD) stage (odds ratio [OR]: 1.40, 95% confidence interval [CI]: 1.04-1.88, p = 0.027) and leukoaraiosis grade (OR: 3.29, 95% CI: 1.43-7.56, p = 0.005) were strongly associated with CM. Additionally, both CKD stage (OR: 1.48, 95% CI: 1.06-2.07, p = 0.023) and leukoaraiosis grade (OR: 2.81, 95% CI: 1.30-6.05, p = 0.008) were associated with lobar microbleeds, whereas only leukoaraiosis grade was also related to deep (OR: 9.00, 95% CI: 3.06-26.44, p < 0.001) and infratentorial (OR: 2.48, 95% CI: 1.10-5.61, p = 0.029) microbleeds. The prediction model based on age, CKD stage and leukoaraiosis grade had diagnostic performance with area under curve: 0.804, 0.688, 0.697, respectively. CONCLUSION: We recommend that patients with ADPKD who are aged 58 or older, and who have CKD of at least stage 3, undergo brain MRI for detection of CM.

Prediction of microvascular invasion in hepatocellular carcinoma patients with MRI radiomics based on susceptibility weighted imaging and T2-weighted imaging.

BACKGROUND: The accurate identification of microvascular invasion (MVI) in patients with hepatocellular carcinoma (HCC) is of great clinical importance. PURPOSE: To develop a radiomics nomogram based on susceptibility-weighted imaging (SWI) and T2-weighted imaging (T2WI) for predicting MVI in early-stage (Barcelona Clinic Liver Cancer stages 0 and A) HCC patients. MATERIALS AND METHODS: A prospective cohort of 189 participants with HCC was included for model training and testing, and an additional 34 participants were enrolled for external validation. ITK-SNAP was used to manually segment the tumour, and PyRadiomics was used to extract radiomic features from the SWI and T2W images. Variance filtering, student's t test, least absolute shrinkage and selection operator regression and random forest (RF) were applied to select meaningful features. Four machine learning classifiers, including K-nearest neighbour, RF, logistic regression and support vector machine-based models, were established. Independent clinical and radiological risk factors were also determined to establish a clinical model. The best radiomics and clinical models were further evaluated in the validation set. In addition, a nomogram was constructed from the radiomic model and independent clinical factors. Diagnostic efficacy was evaluated by receiver operating characteristic curve analysis with fivefold cross-validation. RESULTS: AFP levels greater than 400 ng/mL [odds ratio (OR) 2.50; 95% confidence interval (CI) 1.239-5.047], tumour diameter greater than 5 cm (OR 2.39; 95% CI 1.178-4.839), and absence of pseudocapsule (OR 2.053; 95% CI 1.007-4.202) were found to be independent risk factors for MVI. The areas under the curve (AUCs) of the best radiomic model were 1.000 and 0.882 in the training and testing cohorts, respectively, while those of the clinical model were 0.688 and 0.6691. In the validation set, the radiomic model achieved better diagnostic performance (AUC = 0.888) than the clinical model (AUC = 0.602). The combination of clinical factors and the radiomic model yielded a nomogram with the best diagnostic performance (AUC = 0.948). CONCLUSION: SWI and T2WI-derived radiomic features are valuable for noninvasively and accurately identifying MVI in early-stage HCC. Furthermore, the integration of radiomics and clinical factors yielded a predictive nomogram with satisfactory diagnostic performance and potential clinical benefits.

Brain MRI in status epilepticus: Relevance of findings.

Status epilepticus (SE) represents one of the most common neurological emergencies, associated with high mortality and an important risk of functional sequelae in survivors. Magnetic resonance imaging (MRI) offers the possibility of early and noninvasive observation of seizure-induced parenchymal disturbances secondary to the epileptic process. In the present review, we propose a descriptive and comprehensive understanding of current knowledge concerning seizure-induced MRI abnormalities in SE, also called peri-ictal MRI abnormalities (PMAs). We then discuss how PMAs, as a noninvasive biomarker, could be helpful to optimize patient prognostication in SE management. Finally, we discuss alternative promising MRI approaches, including arterial spin labeling (ASL), susceptibility-weighted imaging (SWI), dynamic contrast-enhanced (DCE) MRI and dynamic susceptibility contrast (DSC) MRI that could refine our understanding of SE, particularly in non-convulsive form.

Cervical spinal cord susceptibility-weighted MRI at 7T: Application to multiple sclerosis.

BACKGROUND: Susceptibility-weighted imaging (SWI) has been extensively studied in the brain and in diseases of the central nervous system such as multiple sclerosis (MS) providing unique opportunities to visualize cerebral vasculature and disease-related pathology, including the central vein sign (CVS) and paramagnetic rim lesions (PRLs). However, similar studies evaluating SWI in the spinal cord of patients with MS remain severely limited. PURPOSE: Based on our previous findings of enlarged spinal vessels in MS compared to healthy controls (HCs), we developed high-field SWI acquisition and processing methods for the cervical spinal cord with application in people with MS (pwMS) and HCs. Here, we demonstrate the vascular variability between the two cohorts and unique MS lesion features in the cervical cord. METHODS: In this retrospective, exploratory pilot study conducted between March 2021 and March 2022, we scanned 12 HCs and 9 pwMS using an optimized non-contrast 2D T2*-weighted gradient echo sequence at 7 tesla. The overall appearance of the white and gray matter as well as tissue vasculature were compared between the two cohorts and areas of MS pathology in the patient group were assessed using both the magnitude and processed SWI images. RESULTS: We show improved visibility of vessels and more pronounced gray and white matter contrast in the MS group compared to HCs, hypointensities surrounding the cord in the MS cohort, and identify signal changes indicative of the CVS and paramagnetic rims in 66 % of pwMS with cervical spinal lesions. CONCLUSION: In this first study of SWI at 7T in the human spinal cord, SWI holds promise in advancing our understanding of disease processes in the cervical cord in MS.

Detection of Cerebral Microbleeds in MR Images Using a Single-Stage Triplanar Ensemble Detection Network (TPE-Det).

BACKGROUND: Cerebral microbleeds (CMBs) are microscopic brain hemorrhages with implications for various diseases. Automated detection of CMBs is a challenging task due to their wide distribution throughout the brain, small size, and visual similarity to their mimics. For this reason, most of the previously proposed methods have been accomplished through two distinct stages, which may lead to difficulties in integrating them into clinical workflows. PURPOSE: To develop a clinically feasible end-to-end CMBs detection network with a single-stage structure utilizing 3D information. This study proposes triplanar ensemble detection network (TPE-Det), ensembling 2D convolutional neural networks (CNNs) based detection networks on axial, sagittal, and coronal planes. STUDY TYPE: Retrospective. SUBJECTS: Two datasets (DS1 and DS2) were used: 1) 116 patients with 367 CMBs and 12 patients without CMBs for training, validation, and testing (70.39 ± 9.30 years, 68 women, 60 men, DS1); 2) 58 subjects with 148 microbleeds and 21 subjects without CMBs only for testing (76.13 ± 7.89 years, 47 women, 32 men, DS2). FIELD STRENGTH/SEQUENCE: A 3 T field strength and 3D GRE sequence scan for SWI reconstructions. ASSESSMENT: The sensitivity, FPavg (false-positive per subject), and precision measures were computed and analyzed with statistical analysis. STATISTICAL TESTS: A paired t-test was performed to investigate the improvement of detection performance by the suggested ensembling technique in this study. A P value < 0.05 was considered significant. RESULTS: The proposed TPE-Det detected CMBs on the DS1 testing set with a sensitivity of 96.05% and an FPavg of 0.88, presenting statistically significant improvement. Even when the testing on DS2 was performed without retraining, the proposed model provided a sensitivity of 85.03% and an FPavg of 0.55. The precision was significantly higher than the other models. DATA CONCLUSION: The ensembling of multidimensional networks significantly improves precision, suggesting that this new approach could increase the benefits of detecting lesions in the clinic. EVIDENCE LEVEL: 1 TECHNICAL EFFICACY: Stage 2.

DeepSWI: Using Deep Learning to Enhance Susceptibility Contrast on T2*-Weighted MRI.

BACKGROUND: Although susceptibility-weighted imaging (SWI) is the gold standard for visualizing cerebral microbleeds (CMBs) in the brain, the required phase data are not always available clinically. Having a postprocessing tool for generating SWI contrast from T2*-weighted magnitude images is therefore advantageous. PURPOSE: To create synthetic SWI images from clinical T2*-weighted magnitude images using deep learning and evaluate the resulting images in terms of similarity to conventional SWI images and ability to detect radiation-associated CMBs. STUDY TYPE: Retrospective. POPULATION: A total of 145 adults (87 males/58 females; 43.9 years old) with radiation-associated CMBs were used to train (16,093 patches/121 patients), validate (484 patches/4 patients), and test (2420 patches/20 patients) our networks. FIELD STRENGTH/SEQUENCE: 3D T2*-weighted, gradient-echo acquired at 3 T. ASSESSMENT: Structural similarity index (SSIM), peak signal-to-noise-ratio (PSNR), normalized mean-squared-error (nMSE), CMB counts, and line profiles were compared among magnitude, original SWI, and synthetic SWI images. Three blinded raters (J.E.V.M., M.A.M., B.B. with 8-, 6-, and 4-years of experience, respectively) independently rated and classified test-set images. STATISTICAL TESTS: Kruskall-Wallis and Wilcoxon signed-rank tests were used to compare SSIM, PSNR, nMSE, and CMB counts among magnitude, original SWI, and predicted synthetic SWI images. Intraclass correlation assessed interrater variability. P values <0.005 were considered statistically significant. RESULTS: SSIM values of the predicted vs. original SWI (0.972, 0.995, 0.9864) were statistically significantly higher than that of the magnitude vs. original SWI (0.970, 0.994, 0.9861) for whole brain, vascular structures, and brain tissue regions, respectively; 67% (19/28) CMBs detected on original SWI images were also detected on the predicted SWI, whereas only 10 (36%) were detected on magnitude images. Overall image quality was similar between the synthetic and original SWI images, with less artifacts on the former. CONCLUSIONS: This study demonstrated that deep learning can increase the susceptibility contrast present in neurovasculature and CMBs on T2*-weighted magnitude images, without residual susceptibility-induced artifacts. This may be useful for more accurately estimating CMB burden from magnitude images alone. EVIDENCE LEVEL: 3. TECHNICAL EFFICACY: Stage 2.

Automatic Segmentation and Quantification of Nigrosome-1 Neuromelanin and Iron in MRI: A Candidate Biomarker for Parkinson's Disease.

BACKGROUND: There is a lack of automated tools for the segmentation and quantification of neuromelanin (NM) and iron in the nigrosome-1 (N1). Existing tools evaluate the N1 sign, i.e., the presence or absence of the "swallow-tail" in iron-sensitive MRI, or globally analyze the MRI signal in an area containing the N1, without providing a volumetric delineation. PURPOSE: Present an automated method to segment the N1 and quantify differences in N1's NM and iron content between Parkinson's disease (PD) patients and healthy controls (HCs). Study whether N1 degeneration is clinically related to PD and could be used as a biomarker of the disease. STUDY TYPE: Prospective. SUBJECTS: Seventy-one PD (65.3 ± 10.3 years old, 34 female/37 male); 30 HC (62.7 ± 7.8 years old, 17 female/13 male). FIELD STRENGTH/SEQUENCE: 3 T Anatomical T1-weighted MPRAGE, NM-MRI T1-weighted gradient with magnetization transfer, susceptibility-weighted imaging (SWI). ASSESSMENT: N1 was automatically segmented in SWI images using a multi-image atlas, populated with healthy N1 structures manually annotated by a neurologist. Relative NM and iron content were quantified and their diagnostic performance assessed and compared with the substantia nigra pars compacta (SNc). The association between image parameters and clinically relevant variables was studied. STATISTICAL TESTS: Nonparametric tests were used (Mann-Whitney's U, chi-square, and Friedman tests) at P = 0.05. RESULTS: N1's relative NM content decreased and relative iron content increased in PD patients compared with HCs (NM-CRHC = 22.55 ± 1.49; NM-CRPD = 19.79 ± 1.92; NM-nVolHC = 2.69 × 10-5 ± 1.02 × 10-5 ; NM-nVolPD = 1.18 × 10-5 ± 0.96 × 10-5 ; Iron-CRHC = 10.51 ± 2.64; Iron-CRPD = 19.35 ± 7.88; Iron-nVolHC = 0.72 × 10-5 ± 0.81 × 10-5 ; Iron-nVolPD = 2.82 × 10-5 ± 2.04 × 10-5 ). Binary logistic regression analyses combining N1 and SNc image parameters yielded a top AUC = 0.955. Significant correlation was found between most N1 parameters and both disease duration (ρNM-CR = -0.31; ρiron-CR = 0.43; ρiron-nVol = 0.46) and the motor status (ρNM-nVol = -0.27; ρiron-CR = 0.33; ρiron-nVol = 0.28), suggesting NM reduction along with iron accumulation in N1 as the disease progresses. DATA CONCLUSION: This method provides a fully automatic N1 segmentation, and the analyses performed reveal that N1 relative NM and iron quantification improves diagnostic performance and suggest a relative NM reduction along with a relative iron accumulation in N1 as the disease progresses. EVIDENCE LEVEL: 1 TECHNICAL EFFICACY: Stage 1.

Relationship between paramagnetic rim lesions and slowly expanding lesions in multiple sclerosis.

BACKGROUND: Magnetic resonance imaging (MRI) markers for chronic active lesions in MS include slowly expanding lesions (SELs) and paramagnetic rim lesions (PRLs). OBJECTIVES: To identify the relationship between SELs and PRLs in MS, and their association with disability. METHODS: 61 people with MS (pwMS) followed retrospectively with MRI including baseline susceptibility-weighted imaging, and longitudinal T1 and T2-weighted scans. SELs were computed using deformation field maps; PRLs were visually identified. Mixed-effects models assessed differences in Expanded Disability Status Scale (EDSS) score changes between the group defined by the presence of SELs and or PRLs. RESULTS: The median follow-up time was 3.2 years. At baseline, out of 1492 lesions, 616 were classified as SELs, and 80 as PRLs. 92% of patients had ⩾ 1 SEL, 56% had ⩾ 1 PRL, while both were found in 51%. SELs compared to non-SELs were more likely to also be PRLs (7% vs. 4%, p = 0.027). PRL counts positively correlated with SEL counts (ρ= 0.28, p = 0.03). SEL + PRL + patients had greater increases in EDSS over time (beta = 0.15/year, 95% confidence interval (0.04, 0.27), p = 0.009) than SEL+PRL-patients. CONCLUSION: SELs are more numerous than PRLs in pwMS. Compared with either SELs or PRLs found in isolation, their joint occurrence was associated with greater clinical progression.

Paramagnetic rim lesions are associated with greater incidence of relapse and worse cognitive recovery following relapse.

BACKGROUND: Paramagnetic rim lesions (PRL) may be linked to relapse risk of people with relapsing-remitting multiple sclerosis (pwRRMS). OBJECTIVE: To determine the relationship between presence of PRL lesions and cognitive recovery after relapse. METHODS: PRL load was compared between acutely relapsing pwRRMS and matched stable pwRRMS controls (each group n = 21). In addition, cognitive recovery was compared between acutely relapsing pwRRMS with at least one PRL (PRL+) and those without any PRL (PRL-). RESULTS: Acutely relapsing pwRRMS had significantly greater prevalence and number of PRL (p = 0.004 and p = 0.003) compared with stable controls. These findings remained significant after adjusting for global neuroinflammatory burden (enhancing and non-enhancing lesions). In addition, acutely relapsing PRL + pwRRMS (n = 10) had worse recovery of verbal memory following relapse compared with acutely relapsing PRL - pwRRMS (n = 7; p = 0.027). CONCLUSION: These findings may partially explain previously suggested associations between presence of PRL with more severe disease course.

Iron quantitative analysis of motor combined with bulbar region in M1 cortex may improve diagnosis performance in ALS.

OBJECTIVES: To explore whether the combined analysis of motor and bulbar region of M1 on susceptibility-weighted imaging (SWI) can be a valid biomarker for amyotrophic lateral sclerosis (ALS). METHODS: Thirty-two non-demented ALS patients and 35 age- and gender-matched healthy controls (HC) were retrospectively recruited. SWI and 3D-T1-MPRAGE images were obtained from all individuals using a 3.0-T MRI scan. The bilateral posterior band of M1 was manually delineated by three neuroradiologists on phase images and subdivided into the motor and bulbar regions. We compared the phase values in two groups and performed a stratification analysis (ALSFRS-R score, duration, disease progression rate, and onset). Receiver operating characteristic (ROC) curves were also constructed. RESULTS: ALS group showed significantly increased phase values in M1 and the two subregions than the HC group, on the all and elderly level (p < 0.001, respectively). On all-age level comparison, negative correlations were found between phase values of M1 and clinical score and duration (p < 0.05, respectively). Similar associations were found in the motor region (p < 0.05, respectively). On both the total (p < 0.01) and elderly (p < 0.05) levels, there were positive relationships between disease progression rate and M1 phase values. In comparing ROC curves, the entire M1 showed the best diagnostic performance. CONCLUSIONS: Combining motor and bulbar analyses as an integral M1 region on SWI can improve ALS diagnosis performance, especially in the elderly. The phase value could be a valuable biomarker for ALS evaluation. KEY POINTS: • Integrated analysis of the motor and bulbar as an entire M1 region on SWI can improve the diagnosis performance in ALS. • Quantitative analysis of iron deposition by SWI measurement helps the clinical evaluation, especially for the elderly patients. • Phase value, when combined with the disease progression rate, could be a valuable biomarker for ALS.

Papilledema and venous stasis in patients with cerebral venous and sinus thrombosis.

BACKGROUND: Cerebral venous and sinus thrombosis (CVST) can cause increased intracranial pressure, often leading to papilledema. In this study, we investigated the association between papilledema and venous stasis on susceptibility weighted imaging (SWI) in CVST. METHODS: Patients with CVST between 2008 and 2020 were reviewed. Patients without fundoscopic examination or SWI were excluded in this study. Venous stasis was evaluated and scored for each cerebral hemisphere: each hemisphere was divided into 5 regions according to the venous drainage territories (superior sagittal sinus, Sylvian veins, transverse sinus and vein of Labbé, deep cerebral veins, and medullary veins) and 1 point was added if venous prominence was confirmed in one territory on SWI. The venous stasis score on SWI between cerebral hemispheres with and without papilledema was compared. RESULTS: Eight of 19 patients with CVST were excluded because of the absence of fundoscopic examination or SWI. Eleven patients (26.5 ± 2.1 years) were included in this study. Papilledema was identified in 6 patients: bilateral papilledema in 4 patients and unilateral papilledema in 2 patients. The venous stasis score on SWI was significantly higher (P = 0.013) in the hemispheres with papilledema (median, 4.0; 95% CI, 3.038-4.562) than in the hemispheres without papilledema (median, 2.5; 95% CI, 0.695-2.805). CONCLUSIONS: This study shows that higher score of venous stasis on SWI is associated with papilledema. Therefore, the venous stasis on SWI may be an imaging surrogate marker of increased intracranial pressure in patients with CVST.