Citations

AbstractPurposeWhile standard MR elastography (MRE) uses harmonic mechanical waves, there are some applications in which imaging and analysis of transient mechanical motion are of interest. Wavelet MRE has been developed for detecting broadband motion from transient excitation. The goal of this study was to evaluate the accuracy and efficiency of wavelet MRE for transient displacement detection in brain MRE applications.MethodsTransient motion was induced in a gel phantom, while MRE images were acquired using bipolar motion‐encoding gradient (MEG) at multiple frequencies (20–200 Hz). Displacements were estimated using (1) combinations of multiple MEGs forming the wavelet MRE and (2) deconvolution from a single MEG. These estimated displacements were used to calculate the MRE phase for each MEG. Correlation (r2) between the calculated and acquired phases was evaluated.Three healthy volunteers were scanned twice in a clinical scanner using wavelet MRE with an occipital impact. Time‐resolved brain translation, rotation, and maximal principal strain were calculated. Repeatability was assessed both qualitatively and through Pearson correlation.ResultsWavelet MRE outperformed standard MRE in displacement estimation, showing higher correlations between calculated and acquired phase, even with fewer phase offsets. In the volunteer study, consistent temporal motion dynamics and spatial maximal principal strain distributions across repeated scans demonstrated the repeatability of wavelet MRE.ConclusionThis study validated the accuracy and efficiency of wavelet MRE for broadband motion detection and demonstrated its feasibility and repeatability in vivo. This technique shows promise for advancing our understanding of the injury risks and mechanisms associated with sports‐related head trauma.

Recent advancements in compact MRI scanners, portable low-field-strength MRI systems, and high-performance gradient inserts address the challenges of conventional MRI for brain imaging, providing more accessible and versatile technology.

BACKGROUND: Spinal cord involvement is infrequently reported in primary central nervous system vasculitis (PCNSV). This study describes the clinical findings, therapeutic responses, and outcomes of spinal cord involvement in a large cohort of patients with PCNSV. METHODS: We retrospectively studied 216 consecutive patients with PCNSV evaluated at the Mayo Clinic from 1983 to 2023. Spinal cord involvement was documented by histological examination or imaging. The clinical, laboratory, radiological, and pathological findings, along with management and outcomes, were compared between patients with and without spinal cord involvement. RESULTS: Of 216 patients, 10 (4.6%) had spinal cord involvement, with cerebral involvement in 9 cases. One patient (0.5%) had isolated spinal cord vasculitis. Histological evidence of vasculitis was found in all 10, with necrotizing vasculitis in 5 (50%). Magnetic resonance imaging showed thoracic abnormalities in 8 patients, cervical spine involvement in 2, conus medullaris involvement in 3, and cauda equina enhancement in 4. Compared with the 206 patients without spinal cord involvement, those with spinal cord vasculitis were more likely to present with paraparesis/tetraparesis ( P <0.001) and necrotizing vasculitis ( P =0.01) and less likely with hemiparesis ( P =0.006) and granulomatous vasculitis ( P =0.03). Patients with spinal cord involvement were more likely to have at least 1 relapse ( P <0.001) or more ( P <0.001). No differences between the 2 groups were observed regarding long-term remission, therapy response, and high disability scores (modified Rankin Scale score, 4–6) or death at last follow-up. Spinal cord involvement was associated with meningeal enhancement on brain imaging (odds ratio, 10.50) and the presence of lymphoma (odds ratio, 6.49), specifically Hodgkin lymphoma diagnosed simultaneously with PCNSV. Spinal involvement was negatively associated with increasing age (odds ratio, 0.64) and cerebral infarction on imaging (odds ratio, 0.08). CONCLUSIONS: Spinal cord involvement defines a distinct subset of patients with PCNSV.

Background: Previous reports have established a relationship between asymptomatic high-grade carotid artery stenosis (CAS) and impaired cognition. Different forms of cardiac disease have also been associated with cognitive impairment and dementia. The effect of concurrent high-grade CAS and cardiac disease on cognition is unknown. We hypothesize the presence of comorbid cardiac disease has a synergistic effect on cognitive impairment in patients with asymptomatic CAS. Methods: Patients with ≥80% internal carotid artery stenosis with no history of stroke were recruited from inpatient and outpatient practices at a single, large, comprehensive stroke center. Patients with vs without comorbid cardiac disease (coronary artery disease [CAD], CAD with history of coronary artery bypass graft [CABG] or percutaneous intervention [PCI], heart failure [HF], atrial fibrillation [AF], or valvular disease [aortic or mitral]) were identified. Cognitive assessments were performed using a battery of 14 standardized tests of attention, memory, processing speed, visual construction, language and executive function. Z-scores were generated based on age-specifc norms. Multivariable linear regression was used to compare test-specific Z-scores in patients with vs without cardiac disease controlling for age, sex, years of education and depression. Results: Thirty-three patients with asymptomatic CAS were identified (21 males, age 74+/-10 years, education=16+/-3 years). Twenty-six (79%) had cardiac disease. Patients with comorbid cardiac disease had significantly lower Z-scores across multiple tests of memory compared to patients without cardiac disease (Fig). After adjusting for age, sex, years of education and depression, significant differences persisted in tests of memory in patients with CAD [Hopkins Recognition Memory Test, β= -1.127 (95% CI: -2.234, -0.020), P=0.046], CABG [Hopkins Learning Trial Memory Test, β= -1.441 (95% CI: -2.532, -0.350), P=0.012], and valvular disease [Hopkins Learning Trials Memory Test, β= -1.121 (95% CI: -2.224, -0.018), P=0.047]. Conclusion: Cardiac disease is common among patients with asymptomatic high-grade carotid stenosis and may have a synergistic effect on impairments in memory in a manner not mediated by stroke. Further work is needed to confirm these relationships and their longterm implications on vascular brain health.

AbstractBackgroundSleep’s crucial role in maintaining brain health is increasingly recognized, particularly due to the rising prevalence of neurodegenerative diseases. It not only supports cognitive function but also aids in clearing brain metabolic waste through cerebrospinal fluid (CSF) dynamics. During sleep, especially in the non‐rapid eye movement (NREM) phase, CSF flow increases, essential for removing neurotoxic substances like amyloid‐beta proteins. This study explores the link between sleep respiratory patterns and CSF flow promotion.MethodElectroencephalography (EEG), and functional magnetic resonance imaging (fMRI) were simultaneously acquired during sleep from Gu, et al. (n = 29) (Gu et al. 2022). Respiration, measured via a respiratory belt, calculated respiratory volume (RV) as the standard deviation within a 5 second sliding window. EEG data processed delta band power (1‐4Hz) averaged across channels. Parcellated fMRI data using the brain template followed by the calculation of the averaged gray matter (GM) blood‐oxygen‐level‐dependent (BOLD) signal using the GM mask. CSF inflow was manually extracted from the fMRI’s bottom slice at the foramen magnum level. Subsequently, all signals were temporally aligned to the peak of the CSF inflow signal.ResultAt the time of CSF inflow (time = 0 sec. in the Figure 1A‐D), we observed an earlier increase in RV and EEG delta power, followed by changes in the GM BOLD signal (Figure 1). EEG and RV changes preceded the BOLD signal changes, which, in turn, preceded changes in CSF flow. Sensitivity to detect RV involvement during MRI varied with the placement of the respiratory belt, being least sensitive on the chest and more on the abdomen.ConclusionThese findings raise an interesting question on the role respiratory patterns during sleep, particularly in the NREM phase. Speculatively, RV change may influence CSF circulation during NREM sleep (Figure 1E). This enhancement in CSF flow is crucial for the clearance of metabolic waste from the brain, potentially reducing the risk of neurodegenerative diseases. Our findings indicate that respiratory volume may serve as a significant marker for CSF circulation during sleep.

ABSTRACT Background and Purpose In idiopathic normal pressure hydrocephalus (iNPH) patients, cerebrospinal fluid (CSF) flow is typically evaluated with a cardiac‐gated two‐dimensional (2D) phase‐contrast (PC) MRI through the cerebral aqueduct. This approach is limited by the evaluation of a single location and does not account for respiration effects on flow. In this study, we quantified the cardiac and respiratory contributions to CSF movement at multiple intracranial locations using a real‐time 2D PC‐MRI and evaluated the diagnostic value of CSF dynamics biomarkers in classifying iNPH patients. Methods This study included 37 participants: 16 iNPH, 10 Alzheimer's disease (AD), and 11 cognitively unimpaired (CU) controls. Anatomical and real‐time (non‐gated) PC images were acquired in a 3T Philips scanner. CSF flow was assessed at the foramen magnum, fourth ventricle, Sylvian fissure, lateral ventricle, and cerebral aqueduct. We calculated three CSF dynamics biomarkers: mean velocity amplitude, cardiac signal power, and respiratory signal power. Biomarkers from each location were evaluated for classifying iNPH versus AD and CU using support vector machine (SVM). A p ‐value of 0.05 or less was considered statistically significant. Results The velocity amplitude and cardiac signal power were significantly reduced in iNPH compared to CU ( p < 0.005) and AD ( p < 0.05) at the lateral ventricle. The SVM model using biomarkers from the lateral ventricle performed significantly better at classifying iNPH than the other locations in terms of accuracy ( p < 0.005) and diagnostic odds ratio ( p < 0.05). Conclusion Evaluation of CSF movement beyond the cerebral aqueduct may aid in identifying patients with and understanding the pathophysiology of iNPH.

Background: As machine learning becomes increasingly utilized in orthopaedic clinical research, the application of machine learning methodology to cohort data from the Multicenter ACL Revision Study (MARS) presents a valuable opportunity to translate data into patient-specific insights. Purpose: To apply novel machine learning methodology to MARS cohort data to determine a predictive model of revision anterior cruciate ligament reconstruction (rACLR) graft failure and features most predictive of failure. Study Design: Cohort study; Level of evidence, 3. Methods: The authors prospectively recruited patients undergoing rACLR from the MARS cohort and obtained preoperative radiographs, surgeon-reported intraoperative findings, and 2- and 6-year follow-up data on patient-reported outcomes, additional surgeries, and graft failure. Machine learning models including logistic regression (LR), XGBoost, gradient boosting (GB), random forest (RF), and a validated ensemble algorithm (AutoPrognosis) were built to predict graft failure by 6 years postoperatively. Validated performance metrics and feature importance measures were used to evaluate model performance. Results: The cohort included 960 patients who completed 6-year follow-up, with 5.7% (n = 55) experiencing graft failure. AutoPrognosis demonstrated the highest discriminative power (model area under the receiver operating characteristic curve: AutoPrognosis, 0.703; RF, 0.618; GB, 0.660; XGBoost, 0.680; LR, 0.592), with well-calibrated scores (model Brier score: AutoPrognosis, 0.053; RF, 0.054; GB, 0.057; XGBoost, 0.058; LR, 0.111). The most important features for AutoPrognosis model performance were prior compromised femoral and tibial tunnels (placement and size) and allograft graft type used in current rACLR. Conclusion: The present study demonstrated the ability of the novel AutoPrognosis machine learning model to best predict the risk of graft failure in patients undergoing rACLR at 6 years postoperatively with moderate predictive ability. Femoral and tibial tunnel size and position in prior ACLR and allograft use in current rACLR were all risk factors for rACLR failure in the context of the AutoPrognosis model. This study describes a unique model that can be externally validated with larger data sets and contribute toward the creation of a robust rACLR bedside risk calculator in future studies. Registration: NCT00625885 (ClinicalTrials.gov identifier).

Background: Revision anterior cruciate ligament (ACL) reconstruction has been documented to have inferior outcomes compared with primary ACL reconstruction. The reasons why remain unknown. Purpose: To determine whether surgical factors performed at the time of revision ACL reconstruction can influence a patient’s outcome at 6-year follow-up. Study Design: Cohort study; Level of evidence, 2. Methods: Patients who underwent revision ACL reconstruction were identified and prospectively enrolled between 2006 and 2011. Data collected included baseline patient characteristics, surgical technique and pathology, and a series of validated patient-reported outcome instruments: Knee injury and Osteoarthritis Outcome Score (KOOS), International Knee Documentation Committee (IKDC) subjective form, Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), and Marx activity rating score. Patients were followed up for 6 years and asked to complete the identical set of outcome instruments. Regression analysis was used to control for baseline patient characteristics and surgical variables to assess the surgical risk factors for clinical outcomes 6 years after surgery. Results: A total of 1234 patients were enrolled (716 men, 58%; median age, 26 years), and 6-year follow-up was obtained on 79% of patients (980/1234). Using an interference screw for femoral fixation compared with a cross-pin resulted in significantly better outcomes in 6-year IKDC scores (odds ratio [OR], 2.2; 95% CI, 1.2-3.9; P = .008) and KOOS sports/recreation and quality of life subscale scores (OR range, 2.2-2.7; 95% CI, 1.2-4.8; P < .01). Use of an interference screw compared with a cross-pin resulted in a 2.6 times less likely chance of having a subsequent surgery within 6 years. Use of an interference screw for tibial fixation compared with any combination of tibial fixation techniques resulted in significantly improved scores for IKDC (OR, 1.96; 95% CI, 1.3-2.9; P = .001); KOOS pain, activities of daily living, and sports/recreation subscales (OR range, 1.5-1.6; 95% CI, 1.0-2.4; P < .05); and WOMAC pain and activities of daily living subscales (OR range, 1.5-1.8; 95% CI, 1.0-2.7; P < .05). Use of a transtibial surgical approach compared with an anteromedial portal approach resulted in significantly improved KOOS pain and quality of life subscale scores at 6 years (OR, 1.5; 95% CI, 1.02-2.2; P≤ .04). Conclusion: There are surgical variables at the time of ACL revision that can modify clinical outcomes at 6 years. Opting for a transtibial surgical approach and choosing an interference screw for femoral and tibial fixation improved patients’ odds of having a significantly better 6-year clinical outcome in this cohort.

Abstract Functional MRI (fMRI) is widely used to spatially localize neural activity in the brain associated with functional stimuli. Functional MR Elastography (fMRE) has recently been introduced as a complementary approach that measures the mechanical response to functional stimulus. The hypothesis of the current study is that the stiffness change in fMRE is proportional to the underlying neural activity. This hypothesis is tested by measuring the median stiffness change in the visual cortex as a function of luminance-matched contrast intensity of a checkerboard visual stimulus in 16 healthy subjects. The fMRE signal in the visual cortex was observed to be proportional to the contrast intensity of the visual stimulus. In regions of activation, fMRE signal increased in the range of 2 ± 1% to 5.8 ± 1% and fMRI signal increased by the expected 0.4 ± 0.2% to 0.9 ± 0.2%, for contrast levels of 5% to 100%, respectively. In conclusion, this study shows that the fMRE signal in the visual cortex can be directly modulated by the contrast intensity of a visual stimulus. The presence of some overlap between fMRI and fMRE regions of activation may suggest two distinct mechanisms governing the fMRI and fMRE signals, which will be investigated in future studies.