White matter structural bases for phase accuracy during tapping synchronization.

We determined the intersubject association between the rhythmic entrainment abilities of human subjects during a synchronization-continuation tapping task (SCT) and the macro- and microstructural properties of their superficial (SWM) and deep (DWM) white matter. Diffusion-weighted images were obtained from 32 subjects who performed the SCT with auditory or visual metronomes and five tempos ranging from 550 to 950 ms. We developed a method to determine the density of short-range fibers that run underneath the cortical mantle, interconnecting nearby cortical regions (U-fibers). Notably, individual differences in the density of U-fibers in the right audiomotor system were correlated with the degree of phase accuracy between the stimuli and taps across subjects. These correlations were specific to the synchronization epoch with auditory metronomes and tempos around 1.5 Hz. In addition, a significant association was found between phase accuracy and the density and bundle diameter of the corpus callosum (CC), forming an interval-selective map where short and long intervals were behaviorally correlated with the anterior and posterior portions of the CC. These findings suggest that the structural properties of the SWM and DWM in the audiomotor system support the tapping synchronization abilities of subjects, as cortical U-fiber density is linked to the preferred tapping tempo and the bundle properties of the CC define an interval-selective topography.

APIS: a paired CT-MRI dataset for ischemic stroke segmentation - methods and challenges.

Stroke, the second leading cause of mortality globally, predominantly results from ischemic conditions. Immediate attention and diagnosis, related to the characterization of brain lesions, play a crucial role in patient prognosis. Standard stroke protocols include an initial evaluation from a non-contrast CT to discriminate between hemorrhage and ischemia. However, non-contrast CTs lack sensitivity in detecting subtle ischemic changes in this phase. Alternatively, diffusion-weighted MRI studies provide enhanced capabilities, yet are constrained by limited availability and higher costs. Hence, we idealize new approaches that integrate ADC stroke lesion findings into CT, to enhance the analysis and accelerate stroke patient management. This study details a public challenge where scientists applied top computational strategies to delineate stroke lesions on CT scans, utilizing paired ADC information. Also, it constitutes the first effort to build a paired dataset with NCCT and ADC studies of acute ischemic stroke patients. Submitted algorithms were validated with respect to the references of two expert radiologists. The best achieved Dice score was 0.2 over a test study with 36 patient studies. Despite all the teams employing specialized deep learning tools, results reveal limitations of computational approaches to support the segmentation of small lesions with heterogeneous density.

Assessment of U-Net in the segmentation of short tracts: Transferring to clinical MRI routine.

Accurately studying structural connectivity requires precise tract segmentation strategies. The U-Net network has been widely recognized for its exceptional capacity in image segmentation tasks and provides remarkable results in large tract segmentation when high-quality diffusion-weighted imaging (DWI) data are used. However, short tracts, which are associated with various neurological diseases, pose specific challenges, particularly when high-quality DWI data acquisition within clinical settings is concerned. Here, we aimed to evaluate the U-Net network ability to segment short tracts by using DWI data acquired in different experimental conditions. To this end, we conducted three types of training experiments involving 350 healthy subjects and 11 white matter tracts, including the anterior, posterior, and hippocampal commissure, fornix, and uncinated fasciculus. In the first experiment, the model was exclusively trained with high-quality data of the Human Connectome Project (HCP) dataset. The second experiment focused on images of healthy subjects acquired from a local hospital dataset, representing a typical clinical routine acquisition. In the third experiment, a hybrid training approach was employed, combining data of the HCP and local hospital datasets. Then, the best model was also tested in unseen DWIs of 10 epilepsy patients of the local hospital and 10 healthy subjects acquired on a scanner from another company. The outcomes of the third experiment demonstrated a notable enhancement in performance when contrasted with the preceding trials. Specifically, the short tracts within the local hospital dataset achieved Dice scores ranging between 0.60 and 0.65. Similar intervals were obtained with HCP data in the first experiment, and a substantial improvement compared to the scores between 0.37 and 0.50 obtained with the local hospital dataset at the same experiment. This improvement persisted when the method was applied to diverse scenarios, including different scanner acquisitions and epilepsy patients. These results indicate that combining datasets from different sources, coupled with resolution standardization strengthens the neural network ability to generalize predictions across a spectrum of datasets. Nevertheless, short tract segmentation performance is intricately linked to the training composition, to validation, and to testing data. Moreover, curved tracts have intricate structural nature, which adds complexities to their segmenting. Although the network training approach tested herein has provided promising results, caution must be taken when extrapolating its application to datasets acquired under distinct experimental conditions, even in the case of higher-quality data or analysis of long or short tracts.

Diffusion-weighted imaging does not seem to be a predictor of consistency in pituitary adenomas.

PURPOSE: To prospectively evaluate the usefulness of T1-weighted imaging (T1WI) and diffusion-weighted imaging (DWI) sequences in predicting the consistency of macroadenomas. In addition, to determine their values ​​as prognostic factors of surgical outcomes. METHODS: Patients with pituitary macroadenoma and surgical indication were included. All patients underwent pre-surgical magnetic resonance imaging (MRI) that included the sequences T1WI before and after contrast administration and DWI with the apparent diffusion coefficient (ADC) map. Post-surgical MRI was performed at least 3 months after surgery. The consistency of the macroadenomas was evaluated at surgery, and they were grouped into soft and intermediate/hard adenomas. Mean ADC values, signal on T1WI and the ratio of tumor ADC values ​​to pons (ADCR) were compared with tumor consistency and grade of surgical resection. RESULTS: A total of 80 patients were included. A softened consistency was found at surgery in 53 patients and hardened in 27 patients. The median ADC in the soft consistency group was 0.532 × 10-3 mm2/sec (0.306 - 1.096 × 10-3 mm2/sec), and in the intermediate/hard consistency group was 0.509 × 10-3 mm2/sec (0.308 - 0.818 × 10-3 mm2/sec). There was no significant difference between the median values ​​of ADC, ADCR and signal on T1W between the soft and hard tumor groups, or between patients with and without tumor residue. CONCLUSION: Our results did not show usefulness of the DWI and T1WI for assessing the consistency of pituitary macroadenomas, nor as a predictor of the degree of surgical resection.

The BrainLat project, a multimodal neuroimaging dataset of neurodegeneration from underrepresented backgrounds.

The Latin American Brain Health Institute (BrainLat) has released a unique multimodal neuroimaging dataset of 780 participants from Latin American. The dataset includes 530 patients with neurodegenerative diseases such as Alzheimer's disease (AD), behavioral variant frontotemporal dementia (bvFTD), multiple sclerosis (MS), Parkinson's disease (PD), and 250 healthy controls (HCs). This dataset (62.7 ± 9.5 years, age range 21-89 years) was collected through a multicentric effort across five Latin American countries to address the need for affordable, scalable, and available biomarkers in regions with larger inequities. The BrainLat is the first regional collection of clinical and cognitive assessments, anatomical magnetic resonance imaging (MRI), resting-state functional MRI (fMRI), diffusion-weighted MRI (DWI), and high density resting-state electroencephalography (EEG) in dementia patients. In addition, it includes demographic information about harmonized recruitment and assessment protocols. The dataset is publicly available to encourage further research and development of tools and health applications for neurodegeneration based on multimodal neuroimaging, promoting the assessment of regional variability and inclusion of underrepresented participants in research.

Diffusion-weighted imaging in pediatric extracranial germ cell tumors.

BACKGROUND: Germ cell tumors (GCTs) comprise a rare and heterogeneous group of neoplasms presenting different clinical and histological characteristics, leading to a challenging scenario in clinical practice. Diffusion-weighted imaging (DWI) has been suggested as an indirect marker of tumor density and cellularity and could be used to monitor therapeutic response. However, its role in pediatric GCTs needs to be clarified. PURPOSE: Here, we evaluated the features of DWI in pediatric extracranial GCTs in a reference Brazilian institution. MATERIAL AND METHODS: We included 43 pediatric patients with primary GCTs treated between 2008 and 2022 in Hospital de Amor de Barretos. The patients' MRI images included T1-weighted without contrast, T2-weighted, DWI and apparent diffusion coefficient (ADC) maps. DWI was evaluated in the section that exhibited the greatest restricted diffusion in the largest hypersignal area of the image. The lowest ADC value was determined to define the region of interest (ROI). We used a small ROI, avoiding necrotic, adipose tissue, noisy or nonenhancing lesion voxels as recommended. ROI determination was established by visual inspection by two radiologists in accordance. We used two values of b (b = 50 mm2/s or b = 800) for ADC values. RESULTS: The highest mean ADC (mADC) value was observed in pure teratomas (1,403.50 ± 161.76 x10-3 mm2/s; mean ± SD) compared to other histologies (yolk sac, mixed teratoma, dysgerminoma and mixed GCT) of GCT (p<0.001). Furthermore, ROC analysis determined a cutoff mADC value of 1,179.00 x 10-3 mm2/s that differentiated pure teratomas from the other GCT histologies with a sensitivity of 95.8% and a specificity of 92.9% (AUC = 0.979; p<0.01). A significant increase in mADC was observed for malignant GCTs in treatment (1,197.00 ± 372.00 mm2/s; p<0.001) compared to that exhibited at the time of diagnosis (780.00 ± 168.00 mm2/s; mean ± SD. Our findings suggest that mADC assessment could be used as a tool to distinguish pure teratomas from malignant CGT histologies at diagnosis. Additionally, we demonstrated reasonable evidence that it could be used as a complementary tool to monitor treatment response in patients with malignant GCT.

Intracranial progression of the epidermoid cyst to a white epidermoid cyst in a pediatric patient: a case report.

BACKGROUND: Epidermoid cysts are rare benign lesions that originate from remnants of ectodermal epithelial tissue, particularly infrequent in the pediatric population. They exhibit characteristic imaging features, with occasional variations leading to the development of a "white" epidermoid cyst. This transformation results from the presence of protein and lipid material within the cyst, causing intrinsic hyperintensity in T1-weighted images, signal hypointensity in T2-weighted images, and a bright signal in diffusion-weighted imaging. CASE PRESENTATION: We describe the case of a 5-year-old Latina pediatric patient initially diagnosed with a typical epidermoid cyst. After 13 years of follow-up, this typical epidermoid cyst underwent a transformation, becoming a "white" epidermoid cyst. CONCLUSIONS: Epidermoid cysts are rare intracranial lesions. The term "white epidermoid cyst" does not denote a variant; it represents a distinct transformation within an epidermoid cyst due to liquid and protein accumulation. This transformation should be considered in cases with specific imaging characteristics.

Assessing the influence of migraine on ischemic penumbra and on the prognosis of ischemic stroke: A prospective cohort study.

INTRODUCTION: There is controversy as to whether migraine affects the behavior of ischemic penumbra during the acute phase of an ischemic stroke, thereby accelerating the formation of cerebral infarction. OBJECTIVES: To assess whether migraine modifies the existence and volume of the divergence between the areas of diffusion and perfusion in the stroke (the penumbra) and whether migraine implies a poorer prognosis after the stroke. METHODS: This was a prospective cohort study. We included hospitalized patients with ischemic stroke within 72 h of symptom onset (convenience sampling). A semi-structured questionnaire, the National Institute of Health Stroke Scale, and the modified Rankin Scale (mRS) were used. Patients underwent magnetic resonance imaging (MRI) of the brain with diffusion and with perfusion. Patients were assessed by telephone 3 months after the stroke to determine the prognosis. Scores of > 2 on the mRS were considered to have a poor prognosis. RESULTS: A total of 221 patients were included, 131/221 (59%) of whom were male, and with a mean (SD) age of 68.2 (13.8) years. Ischemic penumbra analysis was performed in 118 patients. There was no association between migraine and the absence of ischemic penumbra (16/63 [25%] vs. 12/55 [22%]; odds ratio 1.22, 95% confidence interval 0.52-2.87; p = 0.64). There was no difference in stroke volume between those with and without migraine (median [interquartile range] 1.0 [0.4-7.9] vs. 1.8 [0.3-9.4] cm3 ; p = 0.99). Migraine was not associated with the stroke prognosis after multivariable analysis. CONCLUSION: Migraine is not associated with the absence of ischemic penumbra, the volume of the ischemic penumbra, or the stroke prognosis.

Diffusion weighted imaging and apparent diffusion coefficient discrimination of odontogenic keratocyst

Radiological diagnosis of Odontogenic Keratocyst (OKC) is particularly challenging due to its radiological similarities in comparison to other odontogenic lesions. This study aimed to provide data from the literature review and to present a case report in which the diffusion-weighted imaging (DWI) and the apparent diffusion coefficient (ADC) using magnetic resonance imaging (MRI) were obtained to establish a possible way to differentiate OKC from other odontogenic lesions. Literature review data and its association with the present case report shows the potential to use DWI and ADC combination as a possible tool to differentiate OKC from ameloblastomas. (AU)

Utility of diffusion-weighted imaging to differentiate benign and malignant solid orbital tumours.

OBJECTIVE: We assessed the utility of apparent diffusion coefficients (ADCs) derived from diffusion-weighted imaging to differentiate benign and malignant orbital tumours by oculoplastic surgeons in the clinical setting and sought to validate observed ADC cut-off values. DESIGN AND PARTICIPANTS: Retrospective review of patients with benign or malignant biopsy-confirmed orbital tumours. METHODS: Blinded graders including 2 oculoplastic surgeons, 1 neuroradiologist, and 1 medical student located and measured orbital tumour ADCs (10-6 mm2/s) using the Region of Interest tool. OUTCOME MEASURES: Nonradiologist measurements were compared with each other to assess reliability and with an expert neuroradiologist measurement and final pathology to assess accuracy. RESULTS: Twenty-nine orbital tumours met inclusion criteria, consisting of 6 benign tumours and 23 malignant tumours. Mean ADC values for benign orbital tumours were 1430.59 ± 254.81 and 798.68 ± 309.12 mm2/s for malignant tumours. Our calculated optimized ADC cut-off to differentiate benign from malignant orbital tumours was 1120.84 × 10-6 mm2/s (sensitivity 1, specificity 0.9). Inter-rater reliability was excellent (intraclass correlation coefficient = 0.92; 95% CI, 0.86-0.96). Our 3 graders had a combined accuracy of 84.5% (92.3%, 92.3%, and 65.4%). CONCLUSIONS: Our ADC cut-off of 1120.84 × 10-6 mm2/s for benign and malignant orbital tumours agrees with previously established values in literature. Without priming with instructions, training, or access to patient characteristics, most tumours were correctly classified using rapid ADC measurements. Surgeons without radiologic expertise can use the ADC tool to quickly risk stratify orbital tumours during clinic visits to guide patient expectations and further work-up.

Ischemic stroke with unknown onset of symptoms: current scenario and perspectives for the future.

BACKGROUND: Stroke is a major cause of disability worldwide and a neurological emergency. Intravenous thrombolysis and mechanical thrombectomy are effective in the reperfusion of the parenchyma in distress, but the impossibility to determine the exact time of onset was an important cause of exclusion from treatment until a few years ago. OBJECTIVES: To review the clinical and radiological profile of patients with unknown-onset stroke, the imaging methods to guide the reperfusion treatment, and suggest a protocol for the therapeutic approach. METHODS: The different imaging methods were grouped according to current evidence-based treatments. RESULTS: Most studies found no difference between the clinical and imaging characteristics of patients with wake-up stroke and known-onset stroke, suggesting that the ictus, in the first group, occurs just prior to awakening. Regarding the treatment of patients with unknown-onset stroke, four main phase-three trials stand out: WAKE-UP and EXTEND for intravenous thrombolysis, and DAWN and DEFUSE-3 for mechanical thrombectomy. The length of the therapeutic window is based on the diffusion weighted imaging-fluid-attenuated inversion recovery (DWI-FLAIR) mismatch, core-penumbra mismatch, and clinical core mismatch paradigms. The challenges to approach unknown-onset stroke involve extending the length of the time window, the reproducibility of real-world imaging modalities, and the discovery of new methods and therapies for this condition. CONCLUSION: The advance in the possibilities for the treatment of ischemic stroke, while guided by imaging concepts, has become evident. New studies in this field are essential and needed to structure the health care services for this new scenario.

ANTECEDENTES: O acidente vascular cerebral (AVC) é uma das principais causas de incapacidade em todo o mundo, e uma emergência neurológica. A trombólise intravenosa e a trombectomia mecânica são eficazes na reperfusão do parênquima em sofrimento, mas a impossibilidade de determinar o tempo exato de início era uma causa importante de exclusão ao tratamento até alguns anos atrás. OBJETIVOS: Revisar o perfil clínico-radiológico dos pacientes com AVC de tempo indeterminado, os métodos de imagem para guiar o tratamento de reperfusão, e sugerir um protocolo para a abordagem terapêutica. MéTODOS: Os diferentes métodos de imagem foram agrupados de acordo com os tratamentos atuais baseados em evidências. RESULTADOS: A maioria dos estudos não encontrou diferença entre as características clínicas e de imagem dos pacientes com AVC reconhecido ao despertar e AVC de tempo definido, o que sugere que o icto, no primeiro grupo, ocorre próximo ao acordar. Quanto ao tratamento do AVC de tempo indeterminado, quatro grandes estudos na fase três sobressaem: WAKE-UP e EXTEND para trombólise intravenosa, e DAWN e DEFUSE-3 para trombectomia mecânica. A ampliação da janela terapêutica fundamenta-se nos paradigmas de incompatibilidade da imagem ponderada de difusão­recuperação da inversão atenuada por fluidos (diffusion weighted imaging­fluid-attenuated inversion recovery, DWI-FLAIR, em inglês), do núcleo isquêmico e penumbra, e clínico-radiológico. Os desafios na abordagem do AVC de tempo indeterminado envolvem a ampliação da janela terapêutica, a reprodutibilidade das modalidades de imagem no mundo real, e a identificação de novos métodos e tratamentos para essa condição. CONCLUSãO: É evidente o avanço nas possibilidades de tratamento do AVC isquêmico guiado pelos conceitos de imagem. Novos estudos nesse campo são essenciais, com necessidade de estruturar os serviços de saúde para esse novo cenário.

Investigating Tissue-Specific Abnormalities in Alzheimer's Disease with Multi-Shell Diffusion MRI.

BACKGROUND: Most studies using diffusion-weighted MRI (DW-MRI) in Alzheimer's disease (AD) have focused their analyses on white matter (WM) microstructural changes using the diffusion (kurtosis) tensor model. Although recent works have addressed some limitations of the tensor model, such as the representation of crossing fibers and partial volume effects with cerebrospinal fluid (CSF), the focus remains in modeling and analyzing the WM. OBJECTIVE: In this work, we present a brain analysis approach for DW-MRI that disentangles multiple tissue compartments as well as micro- and macroscopic effects to investigate differences between groups of subjects in the AD continuum and controls. METHODS: By means of the multi-tissue constrained spherical deconvolution of multi-shell DW-MRI, underlying brain tissue is modeled with a WM fiber orientation distribution function along with the contributions of gray matter (GM) and CSF to the diffusion signal. From this multi-tissue model, a set of measures capturing tissue diffusivity properties and morphology are extracted. Group differences were interrogated following fixel-, voxel-, and tensor-based morphometry approaches while including strong FWE control across multiple comparisons. RESULTS: Abnormalities related to AD stages were detected in WM tracts including the splenium, cingulum, longitudinal fasciculi, and corticospinal tract. Changes in tissue composition were identified, particularly in the medial temporal lobe and superior longitudinal fasciculus. CONCLUSION: This analysis framework constitutes a comprehensive approach allowing simultaneous macro and microscopic assessment of WM, GM, and CSF, from a single DW-MRI dataset.

An inception-based deep multiparametric net to classify clinical significance MRI regions of prostate cancer.

Objective.Multi-parametric magnetic resonance imaging (MP-MRI) has played an important role in prostate cancer diagnosis. Nevertheless, in the clinical routine, these sequences are principally analyzed from expert observations, which introduces an intrinsic variability in the diagnosis. Even worse, the isolated study of these MRI sequences trends to false positive detection due to other diseases that share similar radiological findings. Hence, the main objective of this study was to design, propose and validate a deep multimodal learning framework to support MRI-based prostate cancer diagnosis using cross-correlation modules that fuse MRI regions, coded from independent MRI parameter branches.Approach.This work introduces a multimodal scheme that integrates MP-MRI sequences and allows to characterize prostate lesions related to cancer disease. For doing so, potential 3D regions were extracted around expert annotations over different prostate zones. Then, a convolutional representation was obtained from each evaluated sequence, allowing a rich and hierarchical deep representation. Each convolutional branch representation was integrated following a special inception-like module. This module allows a redundant non-linear integration that preserves textural spatial lesion features and could obtain higher levels of representation.Main results.This strategy enhances micro-circulation, morphological, and cellular density features, which thereafter are integrated according to an inception late fusion strategy, leading to a better differentiation of prostate cancer lesions. The proposed strategy achieved a ROC-AUC of 0.82 over the PROSTATEx dataset by fusing regions ofKtransand apparent diffusion coefficient (ADC) maps coded from DWI-MRI.Significance.This study conducted an evaluation about how MP-MRI parameters can be fused, through a deep learning representation, exploiting spatial correlations among multiple lesion observations. The strategy, from a multimodal representation, learns branches representations to exploit radio-logical findings from ADC andKtrans. Besides, the proposed strategy is very compact (151 630 trainable parameters). Hence, the methodology is very fast in training (3 s for an epoch of 320 samples), being potentially applicable in clinical scenarios.

Whole lesion histogram analysis of apparent diffusion coefficient predicts therapy response in locally advanced rectal cancer.

BACKGROUND: Whole-tumor apparent diffusion coefficient (ADC) histogram analysis is relevant to predicting the neoadjuvant chemoradiation therapy (nCRT) response in patients with locally advanced rectal cancer (LARC). AIM: To evaluate the performance of ADC histogram-derived parameters for predicting the outcomes of patients with LARC. METHODS: This is a single-center, retrospective study, which included 48 patients with LARC. All patients underwent a pre-treatment magnetic resonance imaging (MRI) scan for primary tumor staging and a second restaging MRI for response evaluation. The sample was distributed as follows: 18 responder patients (R) and 30 non-responders (non-R). Eight parameters derived from the whole-lesion histogram analysis (ADCmean, skewness, kurtosis, and ADC10th, 25th, 50th, 75th, 90th percentiles), as well as the ADCmean from the hot spot region of interest (ROI), were calculated for each patient before and after treatment. Then all data were compared between R and non-R using the Mann-Whitney U test. Two measures of diagnostic accuracy were applied: the receiver operating characteristic curve and the diagnostic odds ratio (DOR). We also reported intra- and interobserver variability by calculating the intraclass correlation coefficient (ICC). RESULTS: Post-nCRT kurtosis, as well as post-nCRT skewness, were significantly lower in R than in non-R (both P < 0.001, respectively). We also found that, after treatment, R had a larger loss of both kurtosis and skewness than non-R (∆%kurtosis and ∆skewness, P < 0.001). Other parameters that demonstrated changes between groups were post-nCRT ADC10th, ∆%ADC10th, ∆%ADCmean, and ROI ∆%ADCmean. However, the best diagnostic performance was achieved by ∆%kurtosis at a threshold of 11.85% (Area under the receiver operating characteristic curve [AUC] = 0.991, DOR = 376), followed by post-nCRT kurtosis = 0.78 × 10-3 mm2/s (AUC = 0.985, DOR = 375.3), ∆skewness = 0.16 (AUC = 0.885, DOR = 192.2) and post-nCRT skewness = 1.59 × 10-3 mm2/s (AUC = 0.815, DOR = 168.6). Finally, intraclass correlation coefficient analysis showed excellent intraobserver and interobserver agreement, ensuring the implementation of histogram analysis into routine clinical practice. CONCLUSION: Whole-tumor ADC histogram parameters, particularly kurtosis and skewness, are relevant biomarkers for predicting the nCRT response in LARC. Both parameters appear to be more reliable than ADCmean from one-slice ROI.

RFC1-Related Disorder: In Vivo Evaluation of Spinal Cord Damage.

BACKGROUND: RFC1-related disorder is a novel heredodegenerative condition with a broad phenotypic spectrum. Its neuropathological bases are not yet fully understood, particularly regarding the pattern, extent, and clinical relevance of spinal cord (SC) damage. OBJECTIVES: The objectives were to determine the SC structural signature in RFC1-related disorder in vivo and to identify potential clinical correlates for these imaging abnormalities. METHODS: We enrolled 17 subjects with biallelic RFC1 (AAGGG)n expansions and 11 age- and sex-matched healthy controls that underwent multimodal magnetic resonance imaging SC acquisitions in a 3T Philips Achieva scanner. Both global morphometry and tract-specific analyses were then performed across all cervical levels. Between-group comparisons were assessed using nonparametric tests. RESULTS: In the patient group, mean age and disease duration were 62.9 ± 9.3 and 9.3 ± 4.0, respectively. Compared to controls, patients had remarkable SC cross-sectional area reduction along all cervical levels but anteroposterior flattening only in the lower cervical levels. There was also prominent SC gray matter atrophy. Diffusivity abnormalities were identified in the dorsal columns but not in the lateral corticospinal tracts. Disease severity did not correlate with these imaging parameters. CONCLUSION: SC damage is a hallmark of RFC1-related disorder and characterized by gray as well as white matter involvement. In particular, dorsal columns are severely and diffusely affected. The clinical correlates of these imaging abnormalities still deserve additional investigations. © 2022 International Parkinson and Movement Disorder Society.

Diffusion-weighted imaging as predictor of acute ischemic stroke etiology.

BACKGROUND: Topographic patterns may correlate with causes of ischemic stroke. OBJECTIVE: To investigate the association between diffusion-weighted imaging (DWI) and Trial of Org 10172 in Acute Stroke Treatment (TOAST) classification. METHODS: We included 1019 ischemic stroke patients. DWI were classified as: i) negative; ii) DWI single lesion (cortico-subcortical, cortical, subcortical ≥20 mm, or subcortical <20 mm); iii) scattered lesions in one territory (small scattered lesions or confluent with additional lesions); and iv) multiple lesions (multiple unilateral anterior circulation [MAC], multiple posterior circulation [MPC], multiple bilateral anterior circulation [MBAC], and multiple anterior and posterior circulations [MAP]). RESULTS: There was a relationship between DWI patterns and TOAST classification (p<0.001). Large artery atherosclerosis was associated with small, scattered lesions in one vascular territory (Odds Ratio [OR] 4.22, 95% confidence interval [95%CI] 2.61-6.8), MPC (OR 3.52; 95%CI 1.54-8.03), and subcortical lesions <20 mm (OR 3.47; 95%CI 1.76-6.85). Cardioembolic strokes correlated with MAP (OR 4.3; 95%CI 1.64-11.2), cortico-subcortical lesions (OR 3.24; 95%CI 1.9-5.5) and negative DWI (OR 2.46; 95%CI 1.1-5.49). Cryptogenic strokes correlated with negative DWI (OR 4.1; 95%CI 1,84-8.69), cortical strokes (OR 3.3; 95%CI 1.25-8.8), MAP (OR 3.33; 95%CI 1.25-8.81) and subcortical lesion ≥20 mm (OR 2.44; 95%CI 1,04-5.73). Lacunar strokes correlated with subcortical lesions diameter <20 mm (OR 42.9; 95%CI 22.7-81.1) and negative DWI (OR 8.87; 95%CI 4.03-19.5). Finally, MBAC (OR 9.25; 95%CI 1.12-76.2), MAP (OR 5.54; 95%CI 1.94-15.1), and MPC (OR 3.61; 95%CI 1.5-8.7) correlated with stroke of other etiologies. CONCLUSIONS: A relationship exists between DWI and stroke subtype.

Hippocampal infarction: redefining transient global amnesia.

BACKGROUND AND AIMS: Transient global amnesia (TGA) is a clinical syndrome characterized by sudden anterograde amnesia not accompanied by other neurological symptoms. There is no consensus on the underlying pathophysiological mechanism. However, diffusion-weighted imaging (DWI) of the magnetic resonance imaging (MRI) has demonstrated hippocampal lesions in as many as 50% of cases. This paper describes a series of patients with TGA and hippocampal lesions. METHODS: This study assessed vascular risk factors in patients older than age 18 admitted to the Hospital Universitario San Ignacio, Bogota, Colombia, from May 2017 to June 2020 with a diagnosis of TGA and evidence of hippocampal ischemic lesion on 3 Tesla brain MRI. RESULTS: The authors identified 36 patients, 72.2% female, with mean age 62 years. Cardiovascular risk factors, most frequently high blood pressure, carotid disease, and dyslipidemia, were present in 75% of these patients. Hippocampal lesions were unilateral in 80% of cases, with median size 2.5 mm, most frequently located at the hippocampal body. Approximately 14% of patients also presented acute ischemic lesions in locations other than the hippocampus. CONCLUSIONS: TGA is a clinical entity previously considered to have undetermined etiology. The present study used brain MRI to identify a group of patients with hippocampal ischemic lesions, finding associated vascular risk factors in a high proportion of them.