Moderators, Mediators, and Prognostic Indicators of Treatment With Hip Arthroscopy or Physical Therapy for Femoroacetabular Impingement Syndrome: Secondary Analyses From the Australian FASHIoN Trial.

BACKGROUND: Although randomized controlled trials comparing hip arthroscopy with physical therapy for the treatment of femoroacetabular impingement (FAI) syndrome have emerged, no studies have investigated potential moderators or mediators of change in hip-related quality of life. PURPOSE: To explore potential moderators, mediators, and prognostic indicators of the effect of hip arthroscopy and physical therapy on change in 33-item international Hip Outcome Tool (iHOT-33) score for FAI syndrome. STUDY DESIGN: Cohort study; Level of evidence, 2. METHODS: Overall, 99 participants were recruited from the clinics of orthopaedic surgeons and randomly allocated to treatment with hip arthroscopy or physical therapy. Change in iHOT-33 score from baseline to 12 months was the dependent outcome for analyses of moderators, mediators, and prognostic indicators. Variables investigated as potential moderators/prognostic indicators were demographic variables, symptom duration, alpha angle, lateral center-edge angle (LCEA), Hip Osteoarthritis MRI Scoring System (HOAMS) for selected magnetic resonance imaging (MRI) features, and delayed gadolinium-enhanced MRI of cartilage (dGEMRIC) score. Potential mediators investigated were change in chosen bony morphology measures, HOAMS, and dGEMRIC score from baseline to 12 months. For hip arthroscopy, intraoperative procedures performed (femoral ostectomy ± acetabular ostectomy ± labral repair ± ligamentum teres debridement) and quality of surgery graded by a blinded surgical review panel were investigated for potential association with iHOT-33 change. For physical therapy, fidelity to the physical therapy program was investigated for potential association with iHOT-33 change. RESULTS: A total of 81 participants were included in the final moderator/prognostic indicator analysis and 85 participants in the final mediator analysis after exclusion of those with missing data. No significant moderators or mediators of change in iHOT-33 score from baseline to 12 months were identified. Patients with smaller baseline LCEA (ß = -0.82; P = .034), access to private health care (ß = 12.91; P = .013), and worse baseline iHOT-33 score (ß = -0.48; P < .001) had greater iHOT-33 improvement from baseline to 12 months, irrespective of treatment allocation, and thus were prognostic indicators of treatment response. Unsatisfactory treatment fidelity was associated with worse treatment response (ß = -24.27; P = .013) for physical therapy. The quality of surgery and procedures performed were not associated with iHOT-33 change for hip arthroscopy (P = .460-.665 and P = .096-.824, respectively). CONCLUSION: No moderators or mediators of change in hip-related quality of life were identified for treatment of FAI syndrome with hip arthroscopy or physical therapy in these exploratory analyses. Patients who accessed the Australian private health care system, had smaller LCEAs, and had worse baseline iHOT-33 scores, experienced greater iHOT-33 improvement, irrespective of treatment allocation.

Correction to: Prospective pediatric study comparing glomerular filtration rate estimates based on motion-robust dynamic contrast-enhanced magnetic resonance imaging and serum creatinine (eGFR) to 99mTc DTPA.

The originally published version of this article contained a typographical error. In the text under the subheading "Dynamic contrast-enhanced MRI method, post-processing, and MR-GFR calculation" and in Table 1 the intravenous injection rate of gadobutrol was incorrectly listed as 0.2 mL/s.

White matter mean diffusivity correlates with myelination in tuberous sclerosis complex.

OBJECTIVE: Diffusion tensor imaging (DTI) of the white matter is a biomarker for neurological disease burden in tuberous sclerosis complex (TSC). To clarify the basis of abnormal diffusion in TSC, we correlated ex vivo high-resolution diffusion imaging with histopathology in four tissue types: cortex, tuber, perituber, and white matter. METHODS: Surgical specimens of three children with TSC were scanned in a 3T or 7T MRI with a structural image isotropic resolution of 137-300 micron, and diffusion image isotropic resolution of 270-1,000 micron. We stained for myelin (luxol fast blue, LFB), gliosis (glial fibrillary acidic protein, GFAP), and neurons (NeuN) and registered the digitized histopathology slides (0.686 micron resolution) to MRI for visual comparison. We then performed colocalization analysis in four tissue types in each specimen. Finally, we applied a linear mixed model (LMM) for pooled analysis across the three specimens. RESULTS: In white matter and perituber regions, LFB optical density measures correlated with fractional anisotropy (FA) and inversely with mean diffusivity (MD). In white matter only, GFAP correlated with MD, and inversely with FA. In tubers and in the cortex, there was little variation in mean LFB and GFAP signal intensity, and no correlation with MRI metrics. Neuronal density correlated with MD. In the analysis of the combined specimens, the most robust correlation was between white matter MD and LFB metrics. INTERPRETATION: In TSC, diffusion imaging abnormalities in microscopic tissue types correspond to specific histopathological markers. Across all specimens, white matter diffusivity correlates with myelination.

Perioperatively Inhaled Hydrogen Gas Diminishes Neurologic Injury Following Experimental Circulatory Arrest in Swine.

This study used a swine model of mildly hypothermic prolonged circulatory arrest and found that the addition of 2.4% inhaled hydrogen gas to inspiratory gases during and after the ischemic insult significantly decreased neurologic and renal injury compared with controls. With proper precautions, inhalational hydrogen may be administered safely through conventional ventilators and may represent a complementary therapy that can be easily incorporated into current workflows. In the future, inhaled hydrogen may diminish the sequelae of ischemia that occurs in congenital heart surgery, cardiac arrest, extracorporeal life-support events, acute myocardial infarction, stroke, and organ transplantation.

Linear Time Invariant Model based Motion Correction (LiMo-MoCo) of Dynamic Radial Contrast Enhanced MRI.

Early identification of kidney function deterioration is essential to determine which newborn patients with dilation of the renal pelvis (hydronephrosis) should undergo surgery. Kidney function can be measured by fitting a tracer kinetic (TK) model onto a series of Dynamic Contrast Enhanced (DCE) MR images and deriving the glomerular filtration rate (GFR) from the TK model. Unfortunately, heavy breathing and large bulk motion events create outliers and misalignments that introduce large errors in the TK estimates. Moreover, aligning the series of DCE images is not trivial due to the contrast differences between them and the undersampling artifacts due to fast imaging. We present a bulk motion detection and a linear time invariant (LTI) model-based motion correction approach for DCE-MRI alignment that leverages the temporal dynamics of the DCE data at each voxel. We evaluate our approach on 10 newborn patients that underwent DCE imaging without sedation. For each patient, we reconstructed the sequence of DCE images, detected and removed the volumes corrupted by motion using a self navigation approach, aligned the sequence using our approach and fitted the TK model to compute GFR. The results show that our approach correctly aligned all volumes and improved the TK model fit and, on average, reducing the normalized root-mean-squared error by 0.17.

Fetal Neuropathology in Zika Virus-Infected Pregnant Female Rhesus Monkeys.

The development of interventions to prevent congenital Zika syndrome (CZS) has been limited by the lack of an established nonhuman primate model. Here we show that infection of female rhesus monkeys early in pregnancy with Zika virus (ZIKV) recapitulates many features of CZS in humans. We infected 9 pregnant monkeys with ZIKV, 6 early in pregnancy (weeks 6-7 of gestation) and 3 later in pregnancy (weeks 12-14 of gestation), and compared findings with uninfected controls. 100% (6 of 6) of monkeys infected early in pregnancy exhibited prolonged maternal viremia and fetal neuropathology, including fetal loss, smaller brain size, and histopathologic brain lesions, including microcalcifications, hemorrhage, necrosis, vasculitis, gliosis, and apoptosis of neuroprogenitor cells. High-resolution MRI demonstrated concordant lesions indicative of deep gray matter injury. We also observed spinal, ocular, and neuromuscular pathology. Our data show that vascular compromise and neuroprogenitor cell dysfunction are hallmarks of CZS pathogenesis, suggesting novel strategies to prevent and to treat this disease.

Motion-robust parameter estimation in abdominal diffusion-weighted MRI by simultaneous image registration and model estimation.

Quantitative body DW-MRI can detect abdominal abnormalities as well as monitor response-to-therapy for applications including cancer and inflammatory bowel disease with increased accuracy. Parameter estimates are obtained by fitting a forward model of DW-MRI signal decay to the observed data acquired with several b-values. The DW-MRI signal decay models typically used do not account for respiratory, cardiac and peristaltic motion, however, which may deteriorate the accuracy and robustness of parameter estimates. In this work, we introduce a new model of DW-MRI signal decay that explicitly accounts for motion. Specifically, we estimated motion-compensated model parameters by simultaneously solving image registration and model estimation (SIR-ME) problems utilizing the interdependence of acquired volumes along the diffusion-weighting dimension. To accomplish this, we applied the SIR-ME model to the in-vivo DW-MRI data sets of 26 Crohn's disease (CD) patients and achieved improved precision of the estimated parameters by reducing the coefficient of variation by 8%, 24% and 8% for slow diffusion (D), fast diffusion (D*) and fast diffusion fraction (f) parameters respectively, compared to parameters estimated with independent registration in normal-appearing bowel regions. Moreover, the parameters estimated with the SIR-ME model reduced the error rate in classifying normal and abnormal bowel loops to 12% for D and 10% for f parameter with a reduction in error rate by 13% and 11% for D and f parameters, respectively, compared to the error rate in classifying parameter estimates obtained with independent registration. The experiments in DW-MRI of liver in 20 subjects also showed that the SIR-ME model improved the precision of parameter estimation by reducing the coefficient of variation to 7% for D, 23% for D*, and 8% for the f parameter. Using the SIR-ME model, the coefficient of variation was reduced by 4%, 14% and 6% for D, D* and f parameters, respectively, compared to parameters estimated with independent registration. These results demonstrate that the proposed SIR-ME model improves the accuracy and robustness of quantitative body DW-MRI in characterizing tissue microstructure.

Super-resolution reconstruction in frequency, image, and wavelet domains to reduce through-plane partial voluming in MRI.

PURPOSE: To compare and evaluate the use of super-resolution reconstruction (SRR), in frequency, image, and wavelet domains, to reduce through-plane partial voluming effects in magnetic resonance imaging. METHODS: The reconstruction of an isotropic high-resolution image from multiple thick-slice scans has been investigated through techniques in frequency, image, and wavelet domains. Experiments were carried out with thick-slice T2-weighted fast spin echo sequence on the Academic College of Radiology MRI phantom, where the reconstructed images were compared to a reference high-resolution scan using peak signal-to-noise ratio (PSNR), structural similarity image metric (SSIM), mutual information (MI), and the mean absolute error (MAE) of image intensity profiles. The application of super-resolution reconstruction was then examined in retrospective processing of clinical neuroimages of ten pediatric patients with tuberous sclerosis complex (TSC) to reduce through-plane partial voluming for improved 3D delineation and visualization of thin radial bands of white matter abnormalities. RESULTS: Quantitative evaluation results show improvements in all evaluation metrics through super-resolution reconstruction in the frequency, image, and wavelet domains, with the highest values obtained from SRR in the image domain. The metric values for image-domain SRR versus the original axial, coronal, and sagittal images were PSNR = 32.26 vs 32.22, 32.16, 30.65; SSIM = 0.931 vs 0.922, 0.924, 0.918; MI = 0.871 vs 0.842, 0.844, 0.831; and MAE = 5.38 vs 7.34, 7.06, 6.19. All similarity metrics showed high correlations with expert ranking of image resolution with MI showing the highest correlation at 0.943. Qualitative assessment of the neuroimages of ten TSC patients through in-plane and out-of-plane visualization of structures showed the extent of partial voluming effect in a real clinical scenario and its reduction using SRR. Blinded expert evaluation of image resolution in resampled out-of-plane views consistently showed the superiority of SRR compared to original axial and coronal image acquisitions. CONCLUSIONS: Thick-slice 2D T2-weighted MRI scans are part of many routine clinical protocols due to their high signal-to-noise ratio, but are often severely affected by through-plane partial voluming effects. This study shows that while radiologic assessment is performed in 2D on thick-slice scans, super-resolution MRI reconstruction techniques can be used to fuse those scans to generate a high-resolution image with reduced partial voluming for improved postacquisition processing. Qualitative and quantitative evaluation showed the efficacy of all SRR techniques with the best results obtained from SRR in the image domain. The limitations of SRR techniques are uncertainties in modeling the slice profile, density compensation, quantization in resampling, and uncompensated motion between scans.

Motion Compensated Abdominal Diffusion Weighted MRI by Simultaneous Image Registration and Model Estimation (SIR-ME).

Non-invasive characterization of water molecule's mobility variations by quantitative analysis of diffusion-weighted MRI (DW-MRI) signal decay in the abdomen has the potential to serve as a biomarker in gastrointestinal and oncological applications. Accurate and reproducible estimation of the signal decay model parameters is challenging due to the presence of respiratory, cardiac, and peristalsis motion. Independent registration of each b-value image to the b-value=0 s/mm(2) image prior to parameter estimation might be sub-optimal because of the low SNR and contrast difference between images of varying b-value. In this work, we introduce a motion-compensated parameter estimation framework that simultaneously solves image registration and model estimation (SIR-ME) problems by utilizing the interdependence of acquired volumes along the diffusion weighting dimension. We evaluated the improvement in model parameters estimation accuracy using 16 in-vivo DW-MRI data sets of Crohn's disease patients by comparing parameter estimates obtained using the SIR-ME model to the parameter estimates obtained by fitting the signal decay model to the acquired DW-MRI images. The proposed SIR-ME model reduced the average root-mean-square error between the observed signal and the fitted model by more than 50%. Moreover, the SIR-ME model estimates discriminate between normal and abnormal bowel loops better than the standard parameter estimates.

Spatially constrained incoherent motion method improves diffusion-weighted MRI signal decay analysis in the liver and spleen.

PURPOSE: To evaluate the effect of the spatially constrained incoherent motion (SCIM) method on improving the precision and robustness of fast and slow diffusion parameter estimates from diffusion-weighted MRI in liver and spleen in comparison to the independent voxel-wise intravoxel incoherent motion (IVIM) model. METHODS: We collected diffusion-weighted MRI (DW-MRI) data of 29 subjects (5 healthy subjects and 24 patients with Crohn's disease in the ileum). We evaluated parameters estimates' robustness against different combinations of b-values (i.e., 4 b-values and 7 b-values) by comparing the variance of the estimates obtained with the SCIM and the independent voxel-wise IVIM model. We also evaluated the improvement in the precision of parameter estimates by comparing the coefficient of variation (CV) of the SCIM parameter estimates to that of the IVIM. RESULTS: The SCIM method was more robust compared to IVIM (up to 70% in liver and spleen) for different combinations of b-values. Also, the CV values of the parameter estimations using the SCIM method were significantly lower compared to repeated acquisition and signal averaging estimated using IVIM, especially for the fast diffusion parameter in liver (CVIV IM = 46.61 ± 11.22, CVSCIM = 16.85 ± 2.160, p < 0.001) and spleen (CVIV IM = 95.15 ± 19.82, CVSCIM = 52.55 ± 1.91, p < 0.001). CONCLUSIONS: The SCIM method characterizes fast and slow diffusion more precisely compared to the independent voxel-wise IVIM model fitting in the liver and spleen.

Improved multi B-value diffusion-weighted MRI of the body by simultaneous model estimation and image reconstruction (SMEIR).

Diffusion-weighted MRI images acquired with multiple b-values have the potential to improve diagnostic accuracy by increasing the conspicuity of lesions and inflammatory activity with background suppression. Unfortunately, the inherently low signal-to-noise ratio (SNR) of DW-MRI reduces enthusiasm for using these images for diagnostic purposes. Moreover, lengthy acquisition times limit our ability to improve the quality of multi b-value DW-MRI images by multiple excitations acquisition and signal averaging at each b-value. To offset these limitations, we propose the Simultaneous Model Estimation and Image Reconstruction (SMEIR) for DW-MRI, which substantially improves the quality of multi b-value DW-MRI images without increasing acquisition times. Our model introduces the physiological signal decay model of DW-MRI as a constraint in the reconstruction of the DW-MRI images. An in-vivo experiment using 6 low-quality DW-MRI datasets of a healthy subject showed that SMEIR reconstruction of low-quality data improved SNR by 55% in the liver and by 41% in the kidney without increasing acquisition times. We also demonstrated the clinical impact of our SMEIR reconstruction by increasing the conspicuity of inflamed bowel regions in DW-MRI of 12 patients with Crohn's disease. The contrast-to-noise ratio (CNR) of the inflamed regions in the SMEIR images was higher by 12.6% relative to CNR in the original DW-MRI images.