Diffusion weighted imaging: Technique and applications

The potential role of machine learning and deep learning in differential diagnosis of Alzheimer's disease and FTD using imaging biomarkers: A review

INTRODUCTION

The prevalence of neurodegenerative diseases has significantly increased, necessitating a deeper understanding of their symptoms, diagnostic processes, and prevention strategies. Frontotemporal dementia (FTD) and Alzheimer's disease (AD) are two prominent neurodegenerative conditions that present diagnostic challenges due to overlapping symptoms. To address these challenges, experts utilize a range of imaging techniques, including magnetic resonance imaging (MRI), diffusion tensor imaging (DTI), functional MRI (fMRI), positron emission tomography (PET), and single-photon emission computed tomography (SPECT). These techniques facilitate a detailed examination of the manifestations of these diseases. Recent research has demonstrated the potential of artificial intelligence (AI) in automating the diagnostic process, generating significant interest in this field.

MATERIALS AND METHODS

This narrative review aims to compile and analyze articles related to the AI-assisted diagnosis of FTD and AD. We reviewed 31 articles published between 2012 and 2024, with 23 focusing on machine learning techniques and 8 on deep learning techniques. The studies utilized features extracted from both single imaging modalities and multi-modal approaches, and evaluated the performance of various classification models.

RESULTS

Among the machine learning studies, Support Vector Machines (SVM) exhibited the most favorable performance in classifying FTD and AD. In deep learning studies, the ResNet convolutional neural network outperformed other networks.

CONCLUSION

This review highlights the utility of different imaging modalities as diagnostic aids in distinguishing between FTD and AD. However, it emphasizes the importance of incorporating clinical examinations and patient symptom evaluations to ensure comprehensive and accurate diagnoses.

White matter changes in paediatric bipolar disorder: A systematic review of diffusion magnetic resonance imaging studiesA systematic review of diffusion magnetic resonance imaging studies

BACKGROUND

Paediatric bipolar disorder (PBD) is characterized by severe mood fluctuations that deviate from typical childhood emotional development. Despite the efforts, the pathophysiology of this disorder is not well understood yet. In this review, we aimed to synthesize existing diffusion magnetic resonance imaging (dMRI) research findings in PBD.

METHODS

A literature search was conducted using PubMed, Embase, Scopus, and Web of Science databases to identify relevant studies published before April 2024.

RESULTS

A total of 23 studies were included in the review. The findings showed variations of fractional anisotropy (FA), axial diffusivity, radial diffusivity, and apparent diffusion coefficient in PBD compared to healthy controls (HCs). Key findings included decreased FA in the anterior cingulate, anterior corona radiata, and corpus callosum, particularly the genu, which correlated with clinical symptoms. Furthermore, longitudinal studies emphasized the significance of the uncinate fasciculus as having atypical developmental trajectories in PBD compared to HCs. In addition, graph analysis revealed widespread changes in structural connectivity, especially affecting the orbitofrontal cortex, frontal gyrus, and basal ganglia. Lastly, machine learning models showed promising results in differentiating PBD from HCs.

LIMITATIONS

Cross-sectional design of the studies, small sample sizes, and different imaging protocols preclude integration of the findings.

CONCLUSION

PBD seems to be associated with widespread structural changes compared to HC. Understanding these changes, which might account for the clinical manifestations of this disorder, increase our knowledge of the neurobiological underpinnings of PBD. This, in turn, may help develop more effective treatments for this disorder.

Diagnostic modalities in the mediastinum and the role of bronchoscopy in mediastinal assessment: a narrative review

Background and Objective

Diagnosis of pathology in the mediastinum has proven quite challenging, given the wide variability of both benign and malignant diseases that affect a diverse array of structures. This complexity has led to the development of many different non-invasive and invasive diagnostic modalities. Historically, diagnosis of the mediastinum has relied on different imaging modalities such as chest X-ray, computed tomography (CT), magnetic resonance imaging, and positron emission topography. Once a suspicious lesion was identified with one of these techniques, the gold standard for diagnosis was mediastinoscopy for diagnosis and staging of disease. More recently, many minimally invasive techniques such as CT-guided biopsy, endobronchial ultrasound with transbronchial needle aspiration, and endoscopic ultrasound with fine needle aspiration have revolutionized the diagnosis of the mediastinum. This review provides a comprehensive analysis of all the modalities available for diagnosing mediastinal disease with an emphasis on bronchoscopic techniques.

Methods

Literature search was performed via the PubMed database. We included all types of articles and study designs, including original research, meta-analyses, reviews, and abstracts.

Key Content and Findings

Minimally invasive techniques such as endobronchial ultrasound-transbronchial needle aspiration (EBUS-TBNA) and endoscopic ultrasound-fine needle aspiration (EUS-FNA) have demonstrated high diagnostic yield and low complication rate and have made a significant difference in the time to diagnosis and lives of patients. There continues to be innovation in the field of bronchoscopy with the development of new technologies such as confocal laser endomicroscopy, optical coherence tomography, and artificial intelligence.

Conclusions

Bronchoscopy is and will continue to be an integral modality in minimally invasive diagnosis of the mediastinum.

Spherical-deconvolution informed filtering of tractograms changes laterality of structural connectome

Diffusion MRI-driven tractography, a non-invasive technique that reveals how the brain is connected, is widely used in brain lateralization studies. To improve the accuracy of tractography in showing the underlying anatomy of the brain, various tractography filtering methods were applied to reduce false positives. Based on different algorithms, tractography filtering methods are able to identify the fibers most consistent with the original diffusion data while removing fibers that do not align with the original signals, ensuring the tractograms are as biologically accurate as possible. However, the impact of tractography filtering on the lateralization of the brain connectome remains unclear. This study aims to investigate the relationship between fiber filtering and laterality changes in brain structural connectivity. Three typical tracking algorithms were used to construct the raw tractography, and two popular fiber filtering methods(SIFT and SIFT2) were employed to filter the tractography across a range of parameters. Laterality indices were computed for six popular biological features, including four microstructural measures (AD, FA, RD, and T1/T2 ratio) and two structural features (fiber length and connectivity) for each brain region. The results revealed that tractography filtering may cause significant laterality changes in more than 10% of connections, up to 25% for probabilistic tracking, and deterministic tracking exhibited minimal laterality changes compared to probabilistic tracking, experiencing only about 6%. Except for tracking algorithms, different fiber filtering methods, along with the various biological features themselves, displayed more variable patterns of laterality change. In conclusion, this study provides valuable insights into the intricate relationship between fiber filtering and laterality changes in brain structural connectivity. These findings can be used to develop improved tractography filtering methods, ultimately leading to more robust and reliable measurements of brain asymmetry in lateralization studies.

Distortion-free water-fat separated diffusion-weighted imaging using spatiotemporal joint reconstruction

PURPOSE

Diffusion-weighted imaging (DWI) suffers from geometric distortion and chemical shift artifacts due to the commonly used Echo Planar Imaging (EPI) trajectory. Even with fat suppression in DWI, severe B0 and B1 variations can result in residual fat, which becomes both a source of image artifacts and a confounding factor in diffusion-weighted contrast in distinguishing benign and malignant tissues. This work presents a method for acquiring distortion-free diffusion-weighted images using spatiotemporal acquisition and joint reconstruction. Water-fat separation is performed by chemical-shift encoding.

METHODS

Spatiotemporal acquisition is employed to obtain distortion-free images at a series of echo times. Chemical-shift encoding is used for water-fat separation. Reconstruction and separation are performed jointly in the spat-spectral domain. To address the shot-to-shot motion-induced phase in DWI, an Fast Spin Echo (FSE)-based phase navigator is incorporated into the sequence to obtain distortion-free phase information. The proposed method was validated in phantoms and in vivo for the brain, head and neck, and breast.

RESULTS

The proposed method enables the acquisition of distortion-free diffusion-weighted images in the presence of B0 field inhomogenieties commonly observed in the body. Water and fat components are separated with no obvious spectral leakage artifacts. The estimated Apparent Diffusion Coefficient (ADC) is comparable to that of multishot DW-EPI.

CONCLUSION

Distortion-free, water-fat separated diffusion-weighted images in body can be obtained through the utilization of spatiotemporal acquisition and joint reconstruction methods.

Motor Unit Magnetic Resonance Imaging (MUMRI) In Skeletal Muscle

Magnetic resonance imaging (MRI) is routinely used in the musculoskeletal system to measure skeletal muscle structure and pathology in health and disease. Recently, it has been shown that MRI also has promise for detecting the functional changes, which occur in muscles, commonly associated with a range of neuromuscular disorders. This review focuses on novel adaptations of MRI, which can detect the activity of the functional sub-units of skeletal muscle, the motor units, referred to as "motor unit MRI (MUMRI)." MUMRI utilizes pulsed gradient spin echo, pulsed gradient stimulated echo and phase contrast MRI sequences and has, so far, been used to investigate spontaneous motor unit activity (fasciculation) and used in combination with electrical nerve stimulation to study motor unit morphology and muscle twitch dynamics. Through detection of disease driven changes in motor unit activity, MUMRI shows promise as a tool to aid in both earlier diagnosis of neuromuscular disorders and to help in furthering our understanding of the underlying mechanisms, which proceed gross structural and anatomical changes within diseased muscle. Here, we summarize evidence for the use of MUMRI in neuromuscular disorders and discuss what future research is required to translate MUMRI toward clinical practice. LEVEL OF EVIDENCE: 5 TECHNICAL EFFICACY: Stage 3.

Single-shot multi-b-value (SSMb) diffusion-weighted MRI using spin echo and stimulated echoes with variable flip angles

Conventional diffusion-weighted imaging (DWI) sequences employing a spin echo or stimulated echo sensitize diffusion with a specific b-value at a fixed diffusion direction and diffusion time (Δ). To compute apparent diffusion coefficient (ADC) and other diffusion parameters, the sequence needs to be repeated multiple times by varying the b-value and/or gradient direction. In this study, we developed a single-shot multi-b-value (SSMb) diffusion MRI technique, which combines a spin echo and a train of stimulated echoes produced with variable flip angles. The method involves a pair of 90° radio frequency (RF) pulses that straddle a diffusion gradient lobe (GD), to rephase the magnetization in the transverse plane, producing a diffusion-weighted spin echo acquired by the first echo-planar imaging (EPI) readout train. The magnetization stored along the longitudinal axis is successively re-excited by a series of n variable-flip-angle pulses, each followed by a diffusion gradient lobe GD and a subsequent EPI readout train to sample n stimulated-echo signals. As such, (n + 1) diffusion-weighted images, each with a distinct b-value, are acquired in a single shot. The SSMb sequence was demonstrated on a diffusion phantom and healthy human brain to produce diffusion-weighted images, which were quantitative analyzed using a mono-exponential model. In the phantom experiment, SSMb provided similar ADC values to those from a commercial spin-echo EPI (SE-EPI) sequence (r = 0.999). In the human brain experiment, SSMb enabled a fourfold scan time reduction and yielded slightly lower ADC values (0.83 ± 0.26 μm2/ms) than SE-EPI (0.88 ± 0.29 μm2/ms) in all voxels excluding cerebrospinal fluid, likely due to the influence of varying diffusion times. The feasibility of using SSMb to acquire multiple images in a single shot for intravoxel incoherent motion (IVIM) analysis was also demonstrated. In conclusion, despite a relatively low signal-to-noise ratio, the proposed SSMb technique can substantially increase the data acquisition efficiency in DWI studies.

Impact of diffusion-weighted imaging on agreement between radiologists and non-radiologist in musculoskeletal tumor imaging using magnetic resonance

Background

Diffusion-weighted imaging (DWI) is widely used in neuroradiology or abdominal imaging but not yet implemented in the diagnosis of musculoskeletal tumors.

Aim

This study aimed to evaluate how including diffusion imaging in the MRI protocol for patients with musculoskeletal tumors affects the agreement between radiologists and non-radiologist.

Methods

Thirty-nine patients with musculoskeletal tumors (Ewing sarcoma, osteosarcoma, and benign tumors) consulted at our institution were included. Three raters with different experience levels evaluated examinations blinded to all clinical data. The final diagnosis was determined by consensus. MRI examinations were split into 1) conventional sequences and 2) conventional sequences combined with DWI. We evaluated the presence or absence of diffusion restriction, solid nature, necrosis, deep localization, and diameter >4 cm as known radiological markers of malignancy. Agreement between raters was evaluated using Gwet's AC1 coefficients and interpreted according to Landis and Koch.

Results

The lowest agreement was for diffusion restriction in both groups of raters. Agreement among all raters ranged from 0.51 to 0.945, indicating moderate to almost perfect agreement, and 0.772-0.965 among only radiologists indicating substantial to almost perfect agreement.

Conclusion

The agreement in evaluating diffusion-weighted MRI sequences was lower than that for conventional MRI sequences, both among radiologists and non-radiologist and among radiologists alone. This indicates that assessing diffusion imaging is more challenging, and experience may impact the agreement.

Characterisation of Paediatric Neuroblastic Tumours by Quantitative Structural and Diffusion-Weighted MRI

Purpose: To determine the diagnostic accuracy of quantitative diffusion-weighted (DW) MRI apparent diffusion coefficient (ADC) and tumour volumes to differentiate between malignant (neuroblastoma (NB)) and benign types of neuroblastic tumours (ganglioneuroma (GN) and ganglioneuroblastoma (GNB)) using different region-of-interest (ROI) sizes. Materials and Methods: This single-centre retrospective study included malignant and benign paediatric neuroblastic tumours that had undergone DW MRI at diagnosis. The outcome was diagnostic accuracy of the tumour volume from structural and ADC DW MRI, in comparison to histopathology (reference standard). Results: Data from 40 patients (NB, n = 24; GNB, n = 6; GN, n = 10), 18 (45%) females and 22 (55%) males, with a median age at diagnosis of 21 months (NB), 64 months (GNB), and 133 months (GN), respectively, ranging from 0 to 193 months, were evaluated. The area under the receiver operating characteristic (AUROC) curve for ADC for discriminating between neuroblastic tumours' histopathology for a small ROI was 0.86 (95% CI: 0.75-0.98), and for a large ROI, 0.83 (95% CI: 0.71-0.96). An ADC cut-off value of 1.06 × 10-3 mm2/s was able to distinguish malignant from benign tumours with 83% (68-98%) sensitivity and 75% (95% CI: 54-98%) specificity. Tumour volume was not indicative of malignant vs. benign tumour diagnosis. Conclusions: In this study, both small and large ROIs used to derive ADC DW MRI metrics demonstrated high accuracy to differentiate malignant from benign neuroblastic tumours, with the ADC AUROC for the averaged multiple small ROIs being slightly greater than that of large ROIs, but with overlapping 95% CIs. This should be taken into consideration for standardisation of ROI-related data analysis by international initiatives.

Magnetic Resonance Imaging Assessment of Morphological Changes and Molecular Behavior to Evaluate Treatment Response of Brain Metastatic Lesions After Stereotactic Radiosurgery

BACKGROUND

Brain metastases (BMs) are the most common type of intracranial tumors, frequently arising from primary cancers such as lung, breast, melanoma, and renal cell carcinoma. Magnetic resonance imaging (MRI) plays a crucial role in assessing both the morphological and molecular characteristics of BMs, particularly in evaluating treatment response following radiosurgery. However, the interpretation of these imaging changes remains complex, often influencing clinical decision-making.

OBJECTIVE

This study aims to evaluate the morphological changes and molecular behavior of BMs postradiosurgery using MRI to assess treatment response.

MATERIALS AND METHODS

A retrospective review was conducted at a high specialty medical center, including 41 patients with BMs treated with stereotactic radiosurgery (SRS) from 2018 to 2022. Patients had a baseline MRI (pre-SRS) prior to treatment and follow-ups at 2-3 months (MRI-2) and 5-6 months (MRI-3). The response assessment in neuro-oncology brain metastases (RANO-BM) criteria were used, and T1/T2 matching was analyzed for each follow-up. Logistic regression was performed relating the T1/T2 matching and susceptibility areas (susceptibility-weighted imaging (SWI)) for MRI-2 and MRI-3. Cross tables were created regarding treatment response and demographic characteristics according to Pearson's Chi-squared test.

RESULTS

The mean age was 56.7 years; 53.7% (n = 22) were female. Primary tumors included lung (29.3%, n = 12), breast (19.5%, n = 8), colon (12.2%, n = 5), and melanoma and kidney tumors (7.3%, n = 3). Post-SRS changes included transitions from solid to cystic lesions, reduced perilesional edema, size reduction, and increased areas of magnetic susceptibility. A mixed pattern (areas of T1/T2 match + mismatch) was noted at lesion margins during follow-ups (MRI-2: 70.7% (n = 29), MRI-3: 68.3% (n = 28)). Most patients exhibited a partial response at MRI-2 (43.9%, n = 18), while at MRI-3, disease progression occurred (43.9%, n = 18) due to an increase in lesion number. Logistic regression linking T1/T2 matching and SWI demonstrated a significantly central-peripheral SWI distribution for T1/T2 match during both follow-ups (MRI-2: p = 0.005, R2: 0.52; MRI-3: p = 0.002, R2: 0.56). SWI distribution was higher when a mixed T1/T2 matching was present. Significant associations were found with systemic treatment and response type at MRI-2 (p =0.001), predominantly showing a partial response for those receiving chemotherapy + targeted therapy.

CONCLUSIONS

SWI and T1/T2 mismatch are valuable tools reflecting changes in the tumor microenvironment postradiosurgery, aiding in treatment response monitoring. The appearance of susceptibility areas may precede changes in the enhancement of the lesion margin. Short-term follow-ups (2-3 months) are crucial due to prevalent progression, marked primarily by the appearance of new lesions in approximately 50% of patients.

ACR Appropriateness Criteria® Acute Onset of Scrotal Pain-Without Trauma, Without Antecedent Mass: 2024 Update

Acute scrotum is a medical emergency that requires prompt accurate diagnosis to appropriately triage potentially surgical conditions. Numerous differential diagnoses with overlapping clinical presentations make this a diagnostic challenge. Ultrasound is the established first-line imaging modality for acute scrotal disease and can be used to diagnose most scrotal disorders promptly and with high accuracy. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision process support the systematic analysis of the medical literature from peer reviewed journals. Established methodology principles such as Grading of Recommendations Assessment, Development, and Evaluation or GRADE are adapted to evaluate the evidence. The RAND/UCLA Appropriateness Method User Manual provides the methodology to determine the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where peer reviewed literature is lacking or equivocal, experts may be the primary evidentiary source available to formulate a recommendation.

Comparison of Echo Planar and Turbo Spin Echo Diffusion-Weighted Imaging in Intraoperative MRI

BACKGROUND

Diffusion-weighted imaging (DWI) is routinely used in brain tumor surgery guided by intraoperative MRI (IoMRI). However, conventional echo planar imaging DWI (EPI-DWI) is susceptible to distortion and artifacts that affect image quality. Turbo spin echo DWI (TSE-DWI) is an alternative technique with minimal spatial distortions that has the potential to be the radiologically preferred sequence.

PURPOSE

To compare via single- and multisequence assessment EPI-DWI and TSE-DWI in the IoMRI setting to determine whether there is a radiological preference for either sequence.

STUDY TYPE

Retrospective.

POPULATION

Thirty-four patients (22 female) aged 2-61 years (24 under 18 years) undergoing IoMRI during surgical resection of intracranial tumors.

FIELD STRENGTH/SEQUENCE

3-T, EPI-DWI, and TSE-DWI.

ASSESSMENT

Patients were scanned with EPI- and TSE-DWI as part of the standard IoMRI scanning protocol. A single-sequence assessment of spatial distortion and image artifact was performed by three neuroradiologists blinded to the sequence type. Images were scored regarding distortion and artifacts, around and remote to the resection cavity. A multisequence radiological assessment was performed by three neuroradiologists in full radiological context including all other IoMRI sequences from each case. The DWI images were directly compared with scorings of the radiologists on which they preferred with respect to anatomy, abnormality, artifact, and overall preference.

STATISTICAL TESTS

Wilcoxon signed-rank tests for single-sequence assessment, weighted kappa for single and multisequence assessment. A P-value <0.001 was considered statistically significant.

RESULTS

For the blinded single-sequence assessment, the TSE-DWI sequence was scored equal to or superior to the EPI-DWI sequence for distortion and artifacts, around and remote to the resection cavity for every case. In the multisequence assessment, all radiologists independently expressed a preference for TSE-DWI over EPI-DWI sequences on viewing brain anatomy, abnormalities, and artifacts.

DATA CONCLUSION

The TSE-DWI sequences may be favored over EPI-DWI for IoMRI in patients with intracranial tumors.

LEVEL OF EVIDENCE

2 TECHNICAL EFFICACY: Stage 5.

Deep Learning Accelerated Brain Diffusion-Weighted MRI with Super Resolution Processing

OBJECTIVES

To investigate the clinical feasibility and image quality of accelerated brain diffusion-weighted imaging (DWI) with deep learning image reconstruction and super resolution.

METHODS

85 consecutive patients with clinically indicated MRI at a 3 T scanner were prospectively included. Conventional diffusion-weighted data (c-DWI) with four averages were obtained. Reconstructions of one and two averages, as well as deep learning diffusion-weighted imaging (DL-DWI), were accomplished. Three experienced readers evaluated the acquired data using a 5-point Likert scale regarding overall image quality, overall contrast, diagnostic confidence, occurrence of artefacts and evaluation of the central region, basal ganglia, brainstem, and cerebellum. To assess interrater agreement, Fleiss' kappa (ϰ) was determined. Signal intensity (SI) levels for basal ganglia and the central region were estimated via automated segmentation, and SI values of detected pathologies were measured.

RESULTS

Intracranial pathologies were identified in 35 patients. DL-DWI was significantly superior for all defined parameters, independently from applied averages (p-value <0.001). Optimum image quality was achieved with DL-DWI by utilizing a single average (p-value <0.001), demonstrating very good (80.9%) to excellent image quality (14.5%) in nearly all cases, compared to 12.5% with very good and 0% with excellent image quality for c-MRI (p-value <0.001). Comparable results could be shown for diagnostic confidence. Inter-rater Fleiss' Kappa demonstrated moderate to substantial agreement for virtually all defined parameters, with good accordance, particularly for the assessment of pathologies (p = 0.74). Regarding SI values, no significant difference was found.

CONCLUSION

Ultra-fast diffusion-weighted imaging with super resolution is feasible, resulting in highly accelerated brain imaging while increasing diagnostic image quality.

A Pilot Study of Adolescents with Psychotic Experiences: Potential Cerebellar Circuitry Disruption Early Along the Psychosis Spectrum

A berrant connectivity in the cerebellum has been found in psychotic conditions such as schizophrenia corresponding with cognitive and motor deficits found in these conditions. Diffusion differences in the superior cerebellar peduncles, the white matter connecting the cerebellar circuitry to the rest of the brain, have also been found in schizophrenia and high-risk states. However, white matter diffusivity in the peduncles in individuals with sub-threshold psychotic experiences (PEs) but not reaching the threshold for a definitive diagnosis remains unstudied. This study investigates the cerebellar peduncles in adolescents with PEs but no formal psychiatric diagnosis.Sixteen adolescents with PEs and 17 age-matched controls recruited from schools underwent High-Angular-Resolution-Diffusion neuroimaging. Following constrained spherical deconvolution whole-brain tractography, the superior, inferior and middle peduncles were isolated and virtually dissected out using ExploreDTI. Differences for macroscopic and microscopic tract metrics were calculated using one-way between-group analyses of covariance controlling for age, sex and estimated Total Intracranial Volume (eTIV). Multiple comparisons were corrected using Bonferroni correction.A decrease in fractional anisotropy was identified in the right (p = 0.045) and left (p = 0.058) superior cerebellar peduncle; however, this did not survive strict Bonferroni multiple comparison correction. There were no differences in volumes or other diffusion metrics in either the middle or inferior peduncles.Our trend level changes in the superior cerebellar peduncle in a non-clinical sample exhibiting psychotic experiences complement similar but more profound changes previously found in ultra-high-risk individuals and those with psychotic disorders. This suggests that superior cerebellar peduncle circuitry perturbations may occur early along in the psychosis spectrum.

Insights into pathophysiology, management, and outcomes of near-hanging patients: A narrative review

Hanging is suspension of a person by noose or ligature around the neck. Hanging has been used as a judicial execution method since medieval times and is still a common method of suicide in developing countries. The term "near hanging" is used for those who survive long enough to reach the hospital, and these patients still hold mortality as high as 45%. These patients can present with a wide array of complaints involving cardiovascular, neurologic, and pulmonary systems and local injuries to the airway and vascular structures. High serum lactate and cardiac arrest at arrival are some of the prognostic factors which portend a poor prognosis. Early admission and aggressive treatment are essential to provide best neurologic outcome. Due to paucity of definitive guidelines, therapy has to be based on clinical reports and expertise of the treating physician. Hence, near-hanging patients pose a great challenge in primary emergency care and intensive care management. This review aims to outline the pathophysiology, prognostic indicators, and recent evidence in the management of near-hanging patients.

Mesoscale Brain Mapping: Bridging Scales and Modalities in Neuroimaging - A Symposium Review

Advances in the spatiotemporal resolution and field-of-view of neuroimaging tools are driving mesoscale studies for translational neuroscience. On October 10, 2023, the Center for Mesoscale Mapping (CMM) at the Massachusetts General Hospital (MGH) Athinoula A. Martinos Center for Biomedical Imaging and the Massachusetts Institute of Technology (MIT) Health Sciences Technology based Neuroimaging Training Program (NTP) hosted a symposium exploring the state-of-the-art in this rapidly growing area of research. "Mesoscale Brain Mapping: Bridging Scales and Modalities in Neuroimaging" brought together researchers who use a broad range of imaging techniques to study brain structure and function at the convergence of the microscopic and macroscopic scales. The day-long event centered on areas in which the CMM has established expertise, including the development of emerging technologies and their application to clinical translational needs and basic neuroscience questions. The in-person symposium welcomed more than 150 attendees, including 57 faculty members, 61 postdoctoral fellows, 35 students, and four industry professionals, who represented institutions at the local, regional, and international levels. The symposium also served the training goals of both the CMM and the NTP. The event content, organization, and format were planned collaboratively by the faculty and trainees. Many CMM faculty presented or participated in a panel discussion, thus contributing to the dissemination of both the technologies they have developed under the auspices of the CMM and the findings they have obtained using those technologies. NTP trainees who benefited from the symposium included those who helped to organize the symposium and/or presented posters and gave "flash" oral presentations. In addition to gaining experience from presenting their work, they had opportunities throughout the day to engage in one-on-one discussions with visiting scientists and other faculty, potentially opening the door to future collaborations. The symposium presentations provided a deep exploration of the many technological advances enabling progress in structural and functional mesoscale brain imaging. Finally, students worked closely with the presenting faculty to develop this report summarizing the content of the symposium and putting it in the broader context of the current state of the field to share with the scientific community. We note that the references cited here include conference abstracts corresponding to the symposium poster presentations.