Diffusion-derived intravoxel-incoherent motion anisotropy relates to CSF and blood flow.

This study investigates the feasibility of multi-b-value, multi-directional diffusion MRI for assessing the anisotropy of the cerebral pseudo-diffusion (D*)-tensor. We examine D*-tensor's potential to (1) reflect CSF and blood flow, and (2) detect microvascular architectural alterations in cerebral small vessel disease (cSVD) and aging. METHODS: Multi-b-value diffusion MRI was acquired in 32 gradient directions for 11 healthy volunteers, and in six directions for 29 patients with cSVD and 14 controls at 3 T. A physics-informed neural network was used to estimate intravoxel incoherent motion (IVIM)-DTI model parameters, including the parenchymal slow diffusion (D-)tensor and the pseudo-diffusion (D*)-tensor, from which the fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) were derived. Comparisons of D*-tensor metrics were made between lateral, third, and fourth ventricles and between the middle cerebral arteries and superior sagittal sinus. Group differences in D*-tensor metrics in normal-appearing white matter were analyzed using multivariable linear regression, correcting for age and sex. RESULTS: D*-anisotropy aligned well with CSF flow and arterial blood flow. FA(D*), MD(D*), AD(D*), and RD(D*) were highest in the third, moderate in the fourth, and lowest in the lateral ventricles. The arteries showed higher MD(D*), AD(D*), and RD(D*) than the sagittal sinus. Higher FA(D*) in the normal-appearing white matter was related to cSVD diagnosis and older age, suggesting microvascular architecture alterations. CONCLUSION: Multi-b-value, multi-directional diffusion analysis using the IVIM-DTI model enables assessment of the cerebral microstructure, fluid flow, and microvascular architecture, providing information on neurodegeneration, glymphatic waste clearance, and the vasculature in one measurement.

Results of the 2023 ISBI challenge to reduce GABA-edited MRS acquisition time.

PURPOSE: Use a conference challenge format to compare machine learning-based gamma-aminobutyric acid (GABA)-edited magnetic resonance spectroscopy (MRS) reconstruction models using one-quarter of the transients typically acquired during a complete scan. METHODS: There were three tracks: Track 1: simulated data, Track 2: identical acquisition parameters with in vivo data, and Track 3: different acquisition parameters with in vivo data. The mean squared error, signal-to-noise ratio, linewidth, and a proposed shape score metric were used to quantify model performance. Challenge organizers provided open access to a baseline model, simulated noise-free data, guides for adding synthetic noise, and in vivo data. RESULTS: Three submissions were compared. A covariance matrix convolutional neural network model was most successful for Track 1. A vision transformer model operating on a spectrogram data representation was most successful for Tracks 2 and 3. Deep learning (DL) reconstructions with 80 transients achieved equivalent or better SNR, linewidth and fit error compared to conventional 320 transient reconstructions. However, some DL models optimized linewidth and SNR without actually improving overall spectral quality, indicating a need for more robust metrics. CONCLUSION: DL-based reconstruction pipelines have the promise to reduce the number of transients required for GABA-edited MRS.

Comparing the efficacy of data-driven denoising methods for a multi-echo fMRI acquisition at 7T.

In functional magnetic resonance imaging (fMRI) of the brain the measured signal is corrupted by several (e.g. physiological, motion, and thermal) noise sources and depends on the image acquisition. Imaging at ultrahigh field strength is becoming increasingly popular as it offers increased spatial accuracy. The latter is of particular benefit in brainstem neuroimaging given the small cross-sectional area of most nuclei. However, physiological noise scales with field strength in fMRI acquisitions. Although this problem is in part solved by decreasing voxel size, it is clear that adequate physiological denoising is of utmost importance in brainstem-focused fMRI experiments. Multi-echo sequences have been reported to facilitate highly effective denoising through TE-dependence of Blood Oxygen Level Dependent (BOLD) signals, in a denoising method referred to as multi-echo independent component analysis (ME-ICA). It has not been explored previously how ME-ICA compares to other data-driven denoising approaches at ultrahigh field strength. In the current study, we compared the efficacy of several denoising methods, including anatomical component based correction (aCompCor), Automatic Removal of Motion Artifacts (ICA-AROMA) aggressive and non-aggressive options, ME-ICA, and a combination of ME-ICA and aCompCor. We assessed several data quality metrics, including temporal signal-to-noise ratio (tSNR), delta variation signal (DVARS), spectral density of the global signal, functional connectivity and Shannon spectral entropy. Moreover, we looked at the ability of each method to uncouple the global signal and respiration. In line with previous reports at lower field strengths, we demonstrate that after applying ME-ICA, the data is best post-processed in order to remove spatially diffuse noise with a method such as aCompCor. Our findings indicate that ME-ICA combined with aCompCor and the aggressive option of ICA-AROMA are highly effective denoising approaches for multi-echo data acquired at 7T. ME-ICA combined with aCompCor potentially preserves more signal-of-interest as compared to the aggressive option of ICA-AROMA.

Advances in Image Processing for Epileptogenic Zone Detection with MRI.

Focal epilepsy is a common and severe neurologic disorder. Neuroimaging aims to identify the epileptogenic zone (EZ), preferably as a macroscopic structural lesion. For approximately a third of patients with chronic drug-resistant focal epilepsy, the EZ cannot be precisely identified using standard 3.0-T MRI. This may be due to either the EZ being undetectable at imaging or the seizure activity being caused by a physiologic abnormality rather than a structural lesion. Computational image processing has recently been shown to aid radiologic assessments and increase the success rate of uncovering suspicious regions by enhancing their visual conspicuity. While structural image analysis is at the forefront of EZ detection, physiologic image analysis has also been shown to provide valuable information about EZ location. This narrative review summarizes and explains the current state-of-the-art computational approaches for image analysis and presents their potential for EZ detection. Current limitations of the methods and possible future directions to augment EZ detection are discussed.

An optimized b-value sampling for the quantification of interstitial fluid using diffusion-weighted MRI, a genetic algorithm approach.

PURPOSE: Multi-b-value diffusion-weighted MRI techniques can simultaneously measure the parenchymal diffusivity, microvascular perfusion, and a third, intermediate diffusion component. This component is related to the interstitial fluid in the brain parenchyma. However, simultaneously estimating three diffusion components from multi-b-value data is difficult and has strong dependence on SNR and chosen b-values. As the number of acquired b-values is limited due to scanning time, it is important to know which b-values are most effective to be included. Therefore, this study evaluates an optimized b-value sampling for interstitial fluid estimation. METHOD: The optimized b-value sampling scheme is determined using a genetic algorithm. Subsequently, the performance of this optimized sampling is assessed by comparing it with a linear, logarithmic, and previously proposed sampling scheme, in terms of the RMS error (RMSE) for the intermediate component estimation. The in vivo performance of the optimized sampling is assessed using 7T data with 101 equally spaced b-values ranging from 0 to 1000 s/mm2 . In this case, the RMSE was determined by comparing the fit that includes all b-values. RESULTS: The optimized b-value sampling for estimating the intermediate component was reported to be [0, 30, 90, 210, 280, 350, 580, 620, 660, 680, 720, 760, 980, 990, 1000] s/mm2 . For computer simulations, the optimized sampling had a lower RMSE, compared with the other samplings for varying levels of SNR. For the in vivo data, the voxel-wise RMSE of the optimized sampling was lower compared with other sampling schemes. CONCLUSION: The genetic algorithm-optimized b-value scheme improves the quantification of the diffusion component related to interstitial fluid in terms of a lower RMSE.

Improving microstructural integrity, interstitial fluid, and blood microcirculation images from multi-b-value diffusion MRI using physics-informed neural networks in cerebrovascular disease.

PURPOSE: To obtain better microstructural integrity, interstitial fluid, and microvascular images from multi-b-value diffusion MRI data by using a physics-informed neural network (PINN) fitting approach. METHODS: Test-retest whole-brain inversion recovery diffusion-weighted images with multiple b-values (IVIM: intravoxel incoherent motion) were acquired on separate days for 16 patients with cerebrovascular disease on a 3.0T MRI system. The performance of the PINN three-component IVIM (3C-IVIM) model fitting approach was compared with conventional fitting approaches (i.e., non-negative least squares and two-step least squares) in terms of (1) parameter map quality, (2) test-retest repeatability, and (3) voxel-wise accuracy. Using the in vivo data, the parameter map quality was assessed by the parameter contrast-to-noise ratio (PCNR) between normal-appearing white matter and white matter hyperintensities, and test-retest repeatability was expressed by the coefficient of variation (CV) and intraclass correlation coefficient (ICC). The voxel-wise accuracy of the 3C-IVIM parameters was determined by 10,000 computer simulations mimicking our in vivo data. Differences in PCNR and CV values obtained with the PINN approach versus conventional fitting approaches were assessed using paired Wilcoxon signed-rank tests. RESULTS: The PINN-derived 3C-IVIM parameter maps were of higher quality and more repeatable than those of conventional fitting approaches, while also achieving higher voxel-wise accuracy. CONCLUSION: Physics-informed neural networks enable robust voxel-wise estimation of three diffusion components from the diffusion-weighted signal. The repeatable and high-quality biological parameter maps generated with PINNs allow for visual evaluation of pathophysiological processes in cerebrovascular disease.

The relationship between sex and functional outcome in first-episode schizophrenia: the role of premorbid adjustment and insight.

BACKGROUND: Studies that examined sex differences in first-episode patients consistently show that males compared to females have poor premorbid adjustment, earlier age of onset, worse clinical characteristics, and poorer outcomes. However, little is known about potential mediators that could explain these sex differences. METHODS: Our sample consisted of 137 individuals with first episode schizophrenia (males, n = 105; 77%) with a mean age of 22.1(s.d. = 4.1) years and mean education of 12.5(s.d. = 1.7) years. At entry, patients were within 2 years of their first psychotic episode onset. Baseline assessments were conducted for premorbid adjustment, symptoms, cognitive functioning, insight, and at 6-months for role and social functioning. RESULTS: Males as compared to females had poorer premorbid adjustment across several key developmental periods (p < 0.01), an earlier age of onset [M = 20.3(3.3) v. 22.8(5.6), p = 0.002], more negative symptoms (p = 0.044), poorer insight (p = 0.031), and poorer baseline and 6-month role (p = 0.002) and social functioning (p = 0.034). Several of these variables in which males showed impairment were significant predictors of 6-month role and social functioning. Premorbid adjustment and insight mediated the relationship between sex and role and social functioning at 6-months, but not negative symptoms. DISCUSSION: Males compared to females were at lower levels across several key premorbid and clinical domains which are strongly associated with functional outcome supporting the hypothesis that males might have a more disabling form of schizophrenia. The relationship between sex with role and social functioning was mediated through premorbid adjustment and insight suggesting pathways for understanding why females might have a less disabling form of schizophrenia.

Imaging Interstitial Fluid With MRI: A Narrative Review on the Associations of Altered Interstitial Fluid With Vascular and Neurodegenerative Abnormalities.

Interstitial fluid (ISF) refers to the fluid between the parenchymal cells and along the perivascular spaces (PVS). ISF plays a crucial role in delivering nutrients and clearing waste products from the brain. This narrative review focuses on the use of MRI techniques to measure various ISF characteristics in humans. The complementary value of contrast-enhanced and noncontrast-enhanced techniques is highlighted. While contrast-enhanced MRI methods allow measurement of ISF transport and flow, they lack quantitative assessment of ISF properties. Noninvasive MRI techniques, including multi-b-value diffusion imaging, free-water-imaging, T2 -decay imaging, and DTI along the PVS, offer promising alternatives to derive ISF measures, such as ISF volume and diffusivity. The emerging role of these MRI techniques in investigating ISF alterations in neurodegenerative diseases (eg, Alzheimer's disease and Parkinson's disease) and cerebrovascular diseases (eg, cerebral small vessel disease and stroke) is discussed. This review also emphasizes current challenges of ISF imaging, such as the microscopic scale at which ISF has to be measured, and discusses potential focus points for future research to overcome these challenges, for example, the use of high-resolution imaging techniques. Noninvasive MRI methods for measuring ISF characteristics hold significant potential and may have a high clinical impact in understanding the pathophysiology of neurodegenerative and cerebrovascular disorders, as well as in evaluating the efficacy of ISF-targeted therapies in clinical trials. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY: Stage 2.

The Impact of Exogenous Testosterone on Breast Cancer Risk in Transmasculine Individuals.

BACKGROUND: Exogenous testosterone is vital to gender-affirming therapy for transmasculine individuals. Testosterone may be implicated in breast cancer (BCa) because it can activate androgen and estrogen receptors. To further explore this risk, we performed a systematic review to investigate the impact of exogenous testosterone on BCa risk in transmasculine individuals. METHODS: We searched PubMed/MEDLINE and Ovid/Embase for clinical and preclinical studies assessing BCa and testosterone therapy and screened 6125 articles independently. We ascertained level of evidence using a modified tool from Cook et al (Chest. 1992;102:305S-311S) and risk of bias using a modified Joanna Briggs Institute's Critical Appraisal Tool. RESULTS: Seventy-six studies were included. Epidemiological data suggested that BCa incidence was higher in transmasculine individuals compared with cisgender men but lower compared with cisgender women. Histological studies of transmasculine breast tissue samples also demonstrated a low incidence of precancerous lesions. Interestingly, cases demonstrated that BCa occurred at a younger average age in transmasculine individuals and was predominantly hormone receptor positive. The mechanism for BCa in transmasculine individuals may be related to androgen receptor stimulation or conversion to estradiol. Serum studies reported varied estradiol levels associated with exogenous testosterone. Animal and in vitro studies demonstrated that testosterone was growth inhibitory but may induce proliferation at higher doses or with low estradiol levels. CONCLUSIONS: Plastic surgeons play a critical role in providing gender-affirming care for transmasculine patients. The limited studies available suggest that this patient population has decreased risk for BCa when compared with cisgender women; however, any BCa that does occur may have different clinical presentations and underlying mechanisms compared with cisgender women and men. Overall, the limitations for clinical studies and discrepancies among preclinical studies warrant further investigation.

Estimating myelin-water content from anatomical and diffusion images using spatially undersampled myelin-water imaging through machine learning.

Myelin is vital for healthy neuronal development, and can therefore provide valuable information regarding neuronal maturation. Anatomical and diffusion weighted images (DWI) possess information related to the myelin content and the current study investigates whether quantitative myelin markers can be extracted from anatomical and DWI using neural networks. Thirteen volunteers (mean age 29y) are included, and for each subject, a residual neural network was trained using spatially undersampled reference myelin-water markers. The network is trained on a voxel-by-voxel basis, resulting in a large amount of training data for each volunteer. The inputs used are the anatomical contrasts (cT1w, cT2w), the standardized T1w/T2w ratio, estimates of the relaxation times (T1, T2) and their ratio (T1/T2), and common DWI metrics (FA, RD, MD, λ1, λ2, λ3). Furthermore, to estimate the added value of the DWI metrics, neural networks were trained using either the combined set (DWI, T1w and T2w) or only the anatomical (T1w and T2w) images. The reconstructed myelin-water maps are in good agreement with the reference myelin-water content in terms of the coefficient of variation (CoV) and the intraclass correlation coefficient (ICC). A 6-fold undersampling using both anatomical and DWI metrics resulted in ICC = 0.68 and CoV = 5.9%. Moreover, using twice the training data (3-fold undersampling) resulted in an ICC that is comparable to the reproducibility of the myelin-water imaging itself (CoV = 5.5% vs. CoV = 6.7% and ICC = 0.74 vs ICC = 0.80). To achieve this, beside the T1w, T2w images, DWI is required. This preliminary study shows the potential of machine learning approaches to extract specific myelin-content from anatomical and diffusion-weighted scans.

Quality control strategies for brain MRI segmentation and parcellation: Practical approaches and recommendations - insights from the Maastricht study.

Quality control of brain segmentation is a fundamental step to ensure data quality. Manual quality control strategies are the current gold standard, although these may be unfeasible for large neuroimaging samples. Several options for automated quality control have been proposed, providing potential time efficient and reproducible alternatives. However, those have never been compared side to side, which prevents consensus in the appropriate quality control strategy to use. This study aimed to elucidate the changes manual editing of brain segmentations produce in morphological estimates, and to analyze and compare the effects of different quality control strategies on the reduction of the measurement error. Structural brain MRI from 259 participants of The Maastricht Study were used. Morphological estimates were automatically extracted using FreeSurfer 6.0. Segmentations with inaccuracies were manually edited, and morphological estimates were compared before and after editing. In parallel, 12 quality control strategies were applied to the full sample. Those included: two manual strategies, in which images were visually inspected and either excluded or manually edited; five automated strategies, where outliers were excluded based on the tools "MRIQC" and "Qoala-T", and the metrics "morphological global measures", "Euler numbers" and "Contrast-to-Noise ratio"; and five semi-automated strategies, where the outliers detected through the mentioned tools and metrics were not excluded, but visually inspected and manually edited. In order to quantify the effects of each quality control strategy, the proportion of unexplained variance relative to the total variance was extracted after the application of each strategy, and the resulting differences compared. Manually editing brain surfaces produced particularly large changes in subcortical brain volumes and moderate changes in cortical surface area, thickness and hippocampal volumes. The performance of the quality control strategies depended on the morphological measure of interest. Overall, manual quality control strategies yielded the largest reduction in relative unexplained variance. The best performing automated alternatives were those based on Euler numbers and MRIQC scores. The exclusion of outliers based on global morphological measures produced an increase of relative unexplained variance. Manual quality control strategies are the most reliable solution for quality control of brain segmentation and parcellation. However, measures must be taken to prevent the subjectivity associated with these strategies. The detection of inaccurate segmentations based on Euler numbers or MRIQC provides a time efficient and reproducible alternative. The exclusion of outliers based on global morphological estimates must be avoided.

Integrating Mental Health in Safety-net Primary Care: A Five-year Observational Study on Visits in a County Health System.

BACKGROUND: Beginning in 2010, Los Angeles County Departments of Health Services and Mental Health collaborated to increase access to effective mental health care. The Mental Health Integration Program (MHIP) embedded behavioral health specialists in primary care clinics to deliver brief, problem-focused treatments, and psychiatric consultation support for primary care-prescribed psychotropic medications. OBJECTIVE: The aim was to compare primary care visits associated with psychiatric diagnoses before and after MHIP implementation. METHODS: This retrospective cohort study (2009-2014) examined 62,945 patients from 8 safety-net clinics that implemented MHIP in a staggered manner in Los Angeles. Patients' primary care visits (n=695,354) were either associated or not with a previously identified or "new" (defined as having no diagnosis within the prior year) psychiatric diagnosis. Multilevel regression models used MHIP implementation to predict odds of visits being associated with psychiatric diagnoses, controlling for time, clinic, and patient characteristics. RESULTS: 9.4% of visits were associated with psychiatric diagnoses (6.4% depression, 3.1% anxiety, <1% alcohol, and substance use disorders). Odds of visits being associated with psychiatric diagnoses were 9% higher [95% confidence interval (CI)=1.05-1.13; P<0.0001], and 10% higher for diagnoses that were new (CI=1.04-1.16; P=0.002), after MHIP implementation than before. This appeared to be fueled by increased visits for depression post-MHIP (odds ratio=1.11; CI=1.06-1.15; P<0.0001). CONCLUSIONS: MHIP implementation was associated with more psychiatric diagnoses coded in safety-net primary care visits. Scaling up this effort will require greater attention to the notable differences across patient populations and languages, as well as the markedly low coding of alcohol and substance use services in primary care.

Sex Differences in the Association of Cigarette Craving With Insula Structure.

BACKGROUND: Cigarette craving, which can negatively impact smoking cessation, is reportedly stronger in women than in men when they initiate abstinence from smoking. Identifying approaches to counteract craving in people of different sexes may facilitate the development of personalized treatments for Tobacco Use Disorder, which disproportionately affects women. Because cigarette craving is associated with nicotine dependence and structure of the insula, this study addressed whether a person's sex influences these associations. METHODS: The research participants (n = 99, 48 women) reported daily cigarette smoking and provided self-reports of nicotine dependence. After overnight abstinence from smoking, they underwent structural magnetic resonance imaging scanning to determine cortical thickness of the left and right anterior circular insular sulcus, and self-rated their cigarette craving before and after their first cigarette of the day. RESULTS: Women reported stronger craving than men irrespective of smoking condition (i.e., pre- and post-smoking) (P = .048), and smoking reduced craving irrespective of sex (P < .001). A 3-way interaction of sex, smoking condition, and right anterior circular insular sulcus thickness on craving (P = .033) reflected a negative association of cortical thickness with pre-smoking craving in women only (P = .012). No effects of cortical thickness in the left anterior circular insular sulcus were detected. Nicotine dependence was positively associated with craving (P < .001) across groups and sessions, with no sex differences in this association. CONCLUSIONS: A negative association of right anterior insula thickness with craving in women only suggests that this region may be a relevant therapeutic target for brain-based smoking cessation interventions in women.

Predictive value of functional MRI and EEG in epilepsy diagnosis after a first seizure.

It is often difficult to predict seizure recurrence in subjects who have suffered a first-ever epileptic seizure. In this study, the predictive value of physiological signals measured using Electroencephalography (EEG) and functional MRI (fMRI) is assessed. In particular those patients developing epilepsy (i.e. a second unprovoked seizure) that were initially evaluated as having a low risk of seizure recurrence are of interest. In total, 26 epilepsy patients, of which 8 were initially evaluated as having a low risk of seizure recurrence (i.e. converters), and 17 subjects with only a single seizure were included. All subjects underwent routine EEG as well as fMRI measurements. For diagnostic classification, features related to the temporal dynamics were determined for both the processed EEG and fMRI data. Subsequently, a logistic regression classifier was trained on epilepsy and first-seizure subjects. The trained model was tested using the clinically relevant converters group. The sensitivity, specificity, and AUC (mean ±â€¯SD) of the regression model including metrics from both modalities were 74 ±â€¯19%, 82 ±â€¯18%, and 0.75 ±â€¯0.12, respectively. Positive and negative predictive values (mean ±â€¯SD) of the regression model with both EEG and fMRI features are 84 ±â€¯14% and 78 ±â€¯12%. Moreover, this EEG/fMRI model showed significant improvements compared to the clinical diagnosis, whereas the models using metrics from either EEG or fMRI do not reach significance (p > 0.05). Temporal metrics computationally derived from EEG and fMRI time signals may clinically aid and synergistically improve the predictive value in a first-seizure sample.

Spectral Diffusion Analysis of Intravoxel Incoherent Motion MRI in Cerebral Small Vessel Disease.

BACKGROUND: Cerebral intravoxel incoherent motion (IVIM) imaging assumes two components. However, more compartments are likely present in pathologic tissue. We hypothesized that spectral analysis using a nonnegative least-squares (NNLS) approach can detect an additional, intermediate diffusion component, distinct from the parenchymal and microvascular components, in lesion-prone regions. PURPOSE: To investigate the presence of this intermediate diffusion component and its relation with cerebral small vessel disease (cSVD)-related lesions. STUDY TYPE: Prospective cross-sectional study. POPULATION: Patients with cSVD (n = 69, median age 69.8) and controls (n = 39, median age 68.9). FIELD STRENGTH/SEQUENCE: Whole-brain inversion recovery IVIM acquisition at 3.0T. ASSESSMENT: Enlarged perivascular spaces (PVS) were rated by three raters. White matter hyperintensities (WMH) were identified on a fluid attenuated inversion recovery (FLAIR) image using a semiautomated algorithm. STATISTICAL TESTS: Relations between IVIM measures and cSVD-related lesions were studied using the Spearman's rank order correlation. RESULTS: NNLS yielded diffusion spectra from which the intermediate volume fraction fint was apparent between parenchymal diffusion and microvasular pseudodiffusion. WMH volume and the extent of MRI-visible enlarged PVS in the basal ganglia (BG) and centrum semiovale (CSO) were correlated with fint in the WMHs, BG, and CSO, respectively. fint was 4.2 ± 1.7%, 7.0 ± 4.1% and 13.6 ± 7.7% in BG and 3.9 ± 1.3%, 4.4 ± 1.4% and 4.5 ± 1.2% in CSO for the groups with low, moderate, and high number of enlarged PVS, respectively, and increased with the extent of enlarged PVS (BG: r = 0.49, P < 0.01; CSO: r = 0.23, P = 0.02). fint in the WMHs was 27.1 ± 13.1%, and increased with the WMH volume (r = 0.57, P < 0.01). DATA CONCLUSION: We revealed the presence of an intermediate diffusion component in lesion-prone regions of cSVD and demonstrated its relation with enlarged PVS and WMHs. In tissue with these lesions, tissue degeneration or perivascular edema can lead to more freely diffusing interstitial fluid contributing to fint . LEVEL OF EVIDENCE: 2 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2020;51:1170-1180.

Experimental Model of Zygomatic and Mandibular Defects to Support the Development of Custom Three-Dimensional--Printed Bone Scaffolds.

INTRODUCTION: Autologous reconstruction of segmental craniomaxillofacial bone defects is limited by insufficient graft material, donor site morbidity, and need for microsurgery. Reconstruction is challenging due to the complex three-dimensional (3D) structure of craniofacial skeleton. Customized 3D-printed patient-specific biologic scaffolds hold promise for reconstruction of the craniofacial skeleton without donor site morbidity. The authors report a porcine craniofacial defect model suitable for further evaluation of custom 3D-printed engineered bone scaffolds. METHODS: The authors created a 6 cm critical load-bearing defect in the left mandibular angle and a 1.5 cm noncritical, nonload bearing defect in the contralateral right zygomatic arch in 4 Yucatan minipigs. Defects were plated with patient-specific titanium hardware based on preoperative CT scans. Serial CT imaging was done immediately postoperatively, and at 3 and 6 months. Animals were clinically assessed for masticatory function, ambulation, and growth. At the 6-month study endpoint, animals were euthanized, and bony regeneration was evaluated through histological staining and micro-CT scanning compared to contralateral controls. RESULTS: All 4 animals reached study endpoint. Two mandibular plates fractured, but did not preclude study completion due to loss of masticatory function. One zygoma plate loosened while the site of another underwent heterotopic ossification. Gross examination of site defects revealed heterotopic ossification, confirmed by histological and micro-CT evaluation. Biomechanical testing was unavailable due to insufficient bony repair. CONCLUSIONS: The presented porcine zygoma and mandibular defect models are incapable of repair in the absence of bone scaffolds. Based on the authors' results, this model is appropriate for further study of custom 3D-printed engineered bone scaffolds.

Variability in Current Procedural Terminology Codes for Craniomaxillofacial Trauma Reconstruction: A National Survey.

BACKGROUND: Current Procedural Terminology (CPT) codes are an important part of surgical documentation and billing for services provided within the United States. This limited coding language presents a challenge in the heterogenous and rapidly evolving field of craniofacial surgery. The authors aimed to survey members of the American Society of Maxillofacial Surgery (ASMS) to characterize the variability in coding practices in the surgical management of craniofacial trauma. METHODS: A cross-sectional of 500 members of the ASMS survey was carried out. Descriptive statistics were calculated. The effect of various practice characteristics on coding practices was evaluated using Chi-squared tests and Fisher's exact tests. RESULTS: In total, 79 participants responded including 77 plastic surgeons. About 75% worked in academic centers and 38% reported being in practice over 20 years. Coding practices were not significantly associated with training background or years in practice. Unilateral mandibular and unilateral nasoorbitoethmoid fractures demonstrated the greatest agreement with 99% and 88% of respondents agree upon a single coding strategy, respectively. Midface fractures, bilateral nasoorbitoethmoid fractures, and more complex mandibular demonstrated considerable variability in coding. CONCLUSION: There is a wide variability among members of the ASMS in CPT coding practices for the operative management of craniofacial trauma. To more accurately convey the complexity of craniofacial trauma reconstruction to billers and insurance companies, the authors must develop a more descriptive coding language that captures the heterogeneity of patient presentation and surgical procedures.

Applicability and reproducibility of 2D multi-slice GRASE myelin water fraction with varying acquisition acceleration.

Non-invasive quantification of the in vivo myelin content may provide valuable information regarding healthy maturation of the brain, as well as insights into demyelination of several neurological disorders. However, these scans are often long thereby limiting acquisition of large brain parts in clinically feasible acquisition times. Therefore, fast acquisition of whole brain myelin content is important. To avoid errors related to slice-selective pulses, most of the previous whole brain studies on myelin content relied on a 3D acquisition. However, multi-slice (2D) acquisition methods are often faster, and less susceptible to motion artifacts. Therefore, multi-slice approaches can be beneficial in a clinical setting. We investigated the applicability and reproducibility of whole brain multi-slice GRASE myelin-water imaging with post-acquisition slice-profile correction in healthy volunteers (aged 25-32y). The applicability was evaluated using the agreement between the multi-slice GRASE and the reference method for myelin-water imaging, single-slice multi spin-echo (MSE) acquisition. Additionally, we assessed the effect of varying acquisition acceleration using parallel imaging on the reproducibility values. First, the multi-slice myelin-water maps showed good agreement with the single-slice reference method, with a bias of at most 1.2% in absolute MWF values. Second, we found an average within-subject coefficient of variation (CoV) of 5.9% and an average intra-class correlation coefficient (ICC) of 0.90 for myelin-water estimation using a multi-slice GRASE sequence without parallel acceleration (scan time 14:06 min), while acquisition with a parallel acceleration factor of 2 resulted in a slightly worse average within-subject CoV of 6.4% and an average ICC of 0.83 at half the scan time. Hence, a multi-slice GRASE acquisition with parallel acceleration factor 2 and a scan time of 7:30 min still provides an excellent reproducibility.

A new analysis approach for T2 relaxometry myelin water quantification: Orthogonal Matching Pursuit.

PURPOSE: In vivo myelin quantification can provide valuable noninvasive information on neuronal maturation and development, as well as insights into neurological disorders. Multiexponential analysis of multiecho T2 relaxation is a powerful and widely applied method for the quantification of the myelin water fraction (MWF). In recent literature, the MWF is most commonly estimated using a regularized nonnegative least squares algorithm. METHODS: The orthogonal matching pursuit algorithm is proposed as an alternative method for the estimation of the MWF. The orthogonal matching pursuit is a greedy sparse reconstruction algorithm with a low computation complexity. For validation, both methods are compared to a ground truth using numerical simulations and a phantom model using comparable computation times. The numerical simulations were used to measure the theoretical errors, as well as the effects of varying the SNR, strength of the regularization, and resolution of the basis set. Additionally, a phantom model was used to estimate the performance of the 2 methods while including errors occurring due to the MR measurement. Lastly, 4 healthy subjects were scanned to evaluate the in vivo performance. RESULTS: The results in simulations and phantoms demonstrate that the MWFs determined with the orthogonal matching pursuit are 1.7 times more accurate as compared to the nonnegative least squares, with a comparable precision. The remaining bias of the MWF is shown to be related to the regularization of the nonnegative least squares algorithm and the Rician noise present in magnitude MR images. CONCLUSION: The orthogonal matching pursuit algorithm provides a more accurate alternative for T2 relaxometry myelin water quantification.

Parsing components of auditory predictive coding in schizophrenia using a roving standard mismatch negativity paradigm.

BACKGROUND: Mismatch negativity (MMN) is an event-related potential (ERP) component reflecting auditory predictive coding. Repeated standard tones evoke increasing positivity ('repetition positivity'; RP), reflecting strengthening of the standard's memory trace and the prediction it will recur. Likewise, deviant tones preceded by more standard repetitions evoke greater negativity ('deviant negativity'; DN), reflecting stronger prediction error signaling. These memory trace effects are also evident in MMN difference wave. Here, we assess group differences and test-retest reliability of these indices in schizophrenia patients (SZ) and healthy controls (HC). METHODS: Electroencephalography was recorded twice, 2 weeks apart, from 43 SZ and 30 HC, during a roving standard paradigm. We examined ERPs to the third, eighth, and 33rd standards (RP), immediately subsequent deviants (DN), and the corresponding MMN. Memory trace effects were assessed by comparing amplitudes associated with the three standard repetition trains. RESULTS: Compared with controls, SZ showed reduced MMNs and DNs, but normal RPs. Both groups showed memory trace effects for RP, MMN, and DN, with a trend for attenuated DNs in SZ. Intraclass correlations obtained via this paradigm indicated good-to-moderate reliabilities for overall MMN, DN and RP, but moderate to poor reliabilities for components associated with short, intermediate, and long standard trains, and poor reliability of their memory trace effects. CONCLUSION: MMN deficits in SZ reflected attenuated prediction error signaling (DN), with relatively intact predictive code formation (RP) and memory trace effects. This roving standard MMN paradigm requires additional development/validation to obtain suitable levels of reliability for use in clinical trials.