Long-term blood pressure variability (BPV) has been proposed as a potential risk factor for dementia and cerebral small vessel disease progression. In this study, we investigate the association between BPV, brain injury, and cognitive decline in probable cerebral amyloid angiopathy (CAA). Using a prospective memory clinic cohort, we enrolled 102 participants, including 52 with probable CAA and mild cognitive symptoms. BPV was assessed using a coefficient of variation derived from outpatient BP measurements (median 12) over 5 years before imaging with 3-tesla research magnetic resonance imaging. We measured peak width of skeletonized mean diffusivity and neuroimaging markers of CAA, including lacunes and cortical cerebral microinfarcts. Using regression models, we evaluated the association of BPV with white matter integrity and whether CAA modified this association. We also examined the association of BPV with longitudinal cognitive decline. Systolic BPV had a dose-dependent association with peak width of skeletonized mean diffusivity (standardized β=0.22, 95% CI: 0.06-0.39, P=0.010), independent of age, sex, mean BP, common vascular risk factors, brain atrophy, and CAA severity. The presence of probable CAA strengthened the association between BPV and peak width of skeletonized mean diffusivity (β=9.33, 95% CI: 1.32-17.34, P for interaction=0.023). Higher BPV correlated with the presence of lobar lacunes, cortical cerebral microinfarcts, and a decline in global cognition and processing speed. Long-term BPV had a dose-dependent association with altered white matter integrity, ischemic brain injury, and cognitive decline. Controlling BPV might be a potential novel therapeutic target to prevent cognitive decline in memory clinic patients with probable CAA and mild cognitive symptoms.
Background and Clinical Significance: CTC1-related cerebroretinal microangiopathy with calcifications and cysts (CRMCC), or Coats-plus syndrome, is an extremely rare autosomal recessive telomere-dysfunction disorder. A total of 29 cases in 15 reports have been reported in the English literature. The primary imaging characteristics include leukoencephalopathy, intracranial calcifications, and parenchymal cysts. Case Presentation: We describe a patient with CRMCC, who presented with a large intracranial cystic mass and basal ganglia calcifications, with imaging findings strongly mimicking a primary CNS tumor. The patient underwent multiple surgeries with inconclusive biopsies. Ultimately, it took five years and the collaboration of several specialists to arrive at the final diagnosis. Furthermore, we present dedicated clinical 7T orbit MRI findings on the patient's brother, who has the same disease. Conclusions: We present a rare case of CRMCC with lack of overt leukoencephalopathy at presentation and absence of characteristic extracranial/extraocular manifestations, significantly complicating diagnosis. Furthermore, to the best of our knowledge, we share the first reported clinical 7T orbital MRI in the pediatric population.
Magnetic resonance (MR) imaging-linear accelerator-based real-time adaptive planning for delivering ultra-hypofractionated stereotactic body radiotherapy (SBRT) has advanced clinical accuracy yet added complexity to the radiotherapy workflow. We retrospectively evaluated whether the addition of a Parallel Automated Contouring module with Enhancement of AI (PACE-AI) reduced contouring time and overall SBRT duration, and its impact on intra-fractional target motion. This study included 250 fractions from 90 prostate cancer patients from which fraction time were tracked. All patients received definitive SBRT to the prostate on the 1.5-Tesla Unity (Elekta©) system, through the Adapt-To-Shape (ATS) workflow, which required real-time re-contouring of the normal tissues by the dosimetrists and target contouring by the physician for each of the fractions. We compared the fraction durations for 125 consecutive fractions treated with the incorporation of PACE-AI with 125 fractions previously treated without PACE-AI to determine whether PACE-AI improved efficiency and reduced treatment session duration. For the cohort treated without PACE-AI, the overall median duration was 67.6 min, including 23.9 min contouring time. With the incorporation of PACE-AI, the overall median duration was 51.2 min, representing a 24.3% reduction. The average contouring time was reduced by 55% to 10.8 min. In addition, the extent of positional shifts prior to beam delivery was significantly reduced from an average of 1.8 mm to 1.3 mm (p < 0.001) in both superior/inferior (range reduced from 0 to 6.3 mm to 0-4.2 mm) and anterior/posterior directions (range reduced from 0 to 6.6 mm to 0-5.0 mm). The incorporation of PACE-AI improved workflow efficiency during SBRT. The reduction in treatment duration also helped reduce organ motion during real-time adaptive planning.
Background Glenoid labral tears are a common cause of shoulder pain and instability, particularly in young and physically active individuals, and are frequently associated with recurrent dislocations and functional impairment. Accurate diagnosis is essential for appropriate management and prevention of long-term morbidity. While MRI is widely used as a non-invasive modality for evaluating intra-articular shoulder pathologies, arthroscopy remains the gold standard for definitive diagnosis. However, the diagnostic performance of conventional MRI, even at higher field strengths such as 3.0 Tesla, continues to be an area of active investigation. This study aims to assess the correlation between 3-Tesla MRI and arthroscopic findings in the detection of glenoid labral tears and to evaluate the ability of MRI to identify associated variants and coexisting shoulder pathologies. Methodology This cross-sectional diagnostic validity study included 50 patients presenting with clinically suspected labral tears. All participants underwent evaluation by a standardized 3.0-Tesla MRI of the shoulder followed by arthroscopy. Tear presence, type, and associated abnormalities were documented. Diagnostic performance parameters, including sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy, were calculated using arthroscopy as the reference standard. Data were analyzed using SPSS version 20. Results MRI detected labral tears in 40 (80%) patients, while arthroscopy identified tears in 43 (86%) patients. The most common tear pattern on both modalities was anteroinferior labral tear in 22 (44%) patients, followed by superior labral anteroposterior lesions. MRI demonstrated sensitivity of 90.7%, specificity of 85.7%, PPV of 97.5%, NPV of 60%, and overall accuracy of 90% for tear detection. Additional pathologies were found in 35 patients, with Hill-Sachs defect in 10 (28.6%), adhesive capsulitis in six (17.1%), and rotator cuff abnormalities in five (14.4%) patients. Conclusions MRI shows excellent diagnostic sensitivity and overall accuracy for detecting glenoid labral tears, particularly anteroinferior lesions, and serves as a reliable first-line, non-invasive modality. However, its lower NPV indicates that a normal MRI cannot reliably exclude pathology, affirming the role of arthroscopy in definitive assessment.
Maritime Search and Rescue (SAR) operations are often challenged by vast search zones, poor visibility, and extreme lighting conditions, especially during nighttime missions. This study investigates the use of computer vision and object detection algorithms to automate life jacket detection and improve SAR effectiveness. To address the absence of domain-specific datasets, a custom image dataset featuring multiple life jacket types was developed. A two-fold methodology was adopted: evaluating the performance of YOLO object detection models (versions 5 through 12) on the dataset, and incorporating advanced image preprocessing techniques to enhance detection under challenging lighting conditions. The results demonstrate that preprocessing significantly improves detection performance in both overexposed and underexposed scenarios. Among all evaluated models, YOLOv10 achieved the strongest combination of precision and real-time inference speed (43.9 FPS on Tesla T4 GPU), making it a promising candidate for time-sensitive rescue applications. While individual cells of Tables 5, 6, 7, 8 and 9 show other detectors achieving higher precision under specific lighting × preprocessing combinations, YOLOv10 offers the best aggregate trade-off across the evaluated criteria. This work contributes a scalable benchmark solution for improving SAR outcomes by enabling faster and more reliable identification of individuals in distress at sea.
Accurate deformable image registration (DIR) is required for contour propagation and dose accumulation for magnetic resonance guided adaptive radiotherapy (MRgART). The goal of this study was to train segmentation regularized deep learning (DL) DIR and assess domain invariant MR-MR registration. DL-DIR based progressively refined registration and segmentation (ProRSeg) and VoxelMorph were trained with and without organ weighted segmentation regularization with 262 MR pairs from same domain dataset of longitudinal 3 Tesla MR simulation (MR-Sim) scans of patients with prostate cancer acquired before and every 3 months following radiotherapy. Models were compared against variational DIR by measuring accuracy of organs and clinical target volume (CTV) contour propagation accuracy on same- (58 pairs), cross- (72 1.5 Tesla MR-Linac pairs from consecutive daily treatment fractions), and mixed-domain (42 MRSim planning - MR-Linac first fraction pairs) datasets. Dose accumulation was performed for 42 patients undergoing 5-fraction MRgART on MR-Linac. ProRSeg produced robust DIR on cross- (all organs) and mixed-domain (bladder, CTV) datasets. It was the most accurate method for highly deforming organs including bladder and rectum. Segmentation regularization enhanced accuracy of both ProRSeg and VoxelMorph compared to unregularized versions. Dose accumulation feasibility study with ProRSeg indicated that 83.3% of patients met key institutional constraints for CTV coverage and bladder sparing. ProRSeg was a feasible approach for multi-domain MR-MR registration for prostate cancer patients. Dose accumulation analysis indicated preliminary feasibility to evaluate compliance of delivered treatments to clinical constraints.
Magnetic resonance spectroscopy techniques are widely used to non-invasively study brain metabolism. Despite advances in magnetic resonance spectroscopic imaging (MRSI), there is a notable absence of research on comparing fast non-Cartesian MRSI with single-voxel spectroscopy (SVS), limiting our understanding of its performance and applicability. In this study, we compared the spectral quality and metabolite concentrations obtained using short-TE 2D spiral MRSI and SVS in the same region in the human brain at 3T. Five healthy subjects were scanned at 3T. 2D spiral MRSI data were acquired in a transverse slice through the posterior cingulate cortex (PCC), while the SVS volume was placed within the PCC region. Both techniques employed the standardized semi-LASER sequence for localization. All data were processed in Matlab and fitted with LCModel. Visual inspection suggested comparable overall spectral quality between the two acquisitions. Quantitatively, however, the PCC voxel measured with MRSI exhibited lower signal-to-noise ratio (SNR) compared to SVS at identical scan times, when the SVS voxel matched the effective MRSI voxel. Consistent with lower SNR, metabolite quantification showed higher Cramer-Rao lower bounds with MRSI. In addition, concentrations of glutamate and glutamate plus glutamine were lower with MRSI. Our findings demonstrate that the quality of semi-LASER localized short-TE spiral MRSI spectra is very comparable to that of semi-LASER localized SVS spectra. Small metabolic-specific concentration differences may be due to different WM/GM tissue weighting within the voxel (slice selection profile in SVS vs. point-spread function in MRSI) and different SNR between the two techniques.
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The 7T-DLB study investigated whether atrophy of individual hippocampal and amygdala subfields is present in dementia with Lewy bodies (DLB) as well as in Alzheimer's disease (AD) in which it has previously been established. MRI at standard clinical and research field strengths may have insufficient resolution to reveal the presence of atrophy in these regions in DLB; seven tesla MRI is ideally placed to examine subtle volumetric differences in these brain areas due to increased signal to noise ratio and tissue contrast.In this prospective, cross-sectional, seven tesla imaging study, 20 participants with probable DLB underwent MRI, clinical assessment, and cognitive testing, alongside a patient comparison group of 25 participants with probable AD, and 19 healthy controls. Scans were segmented using FreeSurfer automated pipelines. Hippocampal and amygdala subfield volumes were compared between diagnostic groups using a generalised linear model with age, sex, education, and total intracranial volume as covariates. Associations between volumes and cognition were examined using Kendall's tau. Exploratory analyses investigated associations between subfield volumes and visual hallucinations scores, and in a sub-set of 41 participants (DLB = 13, AD = 17, controls = 11), with plasma ptau-217 concentrations.Four (of 13) hippocampal subfields (molecular layer, subiculum, presubiculum, and entorhinal cortex) and five (of nine) amygdala subfields (accessory basal, central, medial and cortical nuclei, and anterior amygdaloid area) were significantly smaller in DLB compared to controls (pFDR<0.05). In DLB, significant correlations between subfield volumes and Addenbrookes Cognitive Examination Scores were found for seven hippocampal subfields (Cornu Ammonis (CA)1, CA2/3, CA4, molecular layer, dentate gyrus, hippocampal amygdala transition area, and presubiculum), and five amygdala subfields (basal, accessory basal, central, cortical, and cortico-amygdala transition area) (all pFDR<0.05). Exploratory analyses suggest that amygdala subfield volumes may be associated with visual hallucinations, though these provisional findings require replication.We conclude that structural seven tesla MRI reveals volumetric differences in individual hippocampal and amygdala subfields between DLB and controls, as well as between AD and controls where they have previously been described. Atrophy of individual subfields may potentially help explain the presence of cognitive and non-cognitive symptoms in DLB.
Cerebrospinal fluid (CSF) flow disturbance is not clear in craniosynostosis (CS). As far as we know, there are no reports that have evaluated changes in CSF flow disturbance after distraction osteogenesis. The aim of our pilot study was to examine CSF, grey matter (GM) and white matter (WM) volume ratios in CS patients before and after surgery using voxel based morphometry (VBM) in statistical parametric mapping (SPM) 12 software. We performed a retrospective cohort study of CS patients with distraction osteogenesis. We compared CSF, GM, and WM volume ratios between preoperative and postoperative cases. Data was analyzed using VBM in SPM 12 software. A 3 Tesla MRI machine provided 3DSPGR (spoiled gradient-recalled) sequence for all cases. Between April 2017 and June 2023, we assessed 14 consecutive cases. The ratio of GM and WM volume and CSF volume in preoperative cases was significantly higher in postoperative cases (19.8% vs 15.1%, p = 0.022, respectively). In our pilot study CS patients had CSF flow disturbance that was alleviated by cranial distraction osteogenesis.
(1) Background: This study aims to investigate the differences in body composition, muscle strength, and power between young karate athletes from different competitive disciplines. (2) Methods: The study sample consisted of 131 participants (69 boys and 62 girls) aged 10-14 years divided into three groups: kata (n = 48), kumite (n = 40), and athletes competing in both disciplines (n = 43). The set of variables included 1 anthropometric variable, 6 variables for assessing body composition (InBody 270), 8 variables for assessing handgrip strength (handgrip strength test, Fmax, RFD, absolute and relative, both hands), and 3 variables for assessing lower limb muscle power (force plate, CMJ height and power). Of the statistic analysis, MANOVA and ANOVA, along with MANCOVA and ANCOVA were performed. (3) Results: The adjusted results revealed significant general differences between groups (from p = 0.005 to p = 0.009). Regarding body composition, kumite athletes are taller, have greater body mass, body water, proteins, minerals, and muscle mass content than kata athletes and athletes specialized in both disciplines (from p = 0.002 to p = 0.045). The young karate athletes specialized in kumite competition exhibit higher levels of absolute handgrip muscle strength, rate of force development, and absolute lower limb muscle power than kata athletes and athletes specialized in both disciplines (from p = 0.002 to p = 0.041). There were no significant differences in any measured parameters between kata athletes and young karate athletes specialised in both disciplines. (4) Conclusions: The results are associated with higher values of body composition, muscle strength, and power in kumite athletes compared to kata athletes and athletes competing in both disciplines.
To date, there is a notable lack of comprehensive normative datasets that focus on youth volleyball players, which limits coaches' and practitioners' ability to objectively interpret individual test results, monitor longitudinal development, and distinguish normal maturation from training-induced adaptations. The study aims to establish reference values for muscle strength and power in young volleyball players across various age groups, and to determine age group differences. The sample consisted of 3,337 boys and girls aged 10 to 18 years. For assessment of muscle strength and power, the Hand Grip Strength test (HGS), along with countermovement jump without arm swing (CMJ), was implemented. To determine age group differences, one-way MANOVA and ANOVA with a Bonferroni post-hoc test were applied. The study results revealed the presence of significant age group differences in muscle strength and power in young volleyball players, in both males (F = 24.70, p < 0.001, η2 = 0.26) and females (F = 45.86, p < 0.001, η2 = 0.11). A significant increase according to age was observed in all measured parameters. Coaches are encouraged to implement tests for assessing the muscle strength and power, and use these reference values and percentile range in order to track the growth and development of children and youth involved in volleyball, monitor the training process, and identify potential talents in volleyball from the aspect of muscle strength and power.
Atrial fibrillation (AF) and cerebral small vessel disease (CSVD) are prevalent in older adults and may synergistically contribute to cognitive decline and stroke risk. This study investigates the association between AF and CSVD markers, including white matter hyperintensities (WMHs), cerebral microbleeds (CMBs), lacunes, and silent brain infarcts, focusing on sex-specific patterns, anticoagulation status, and predictive modeling. In a cross-sectional study of 923 individuals aged ≥70 years undergoing 3.0-Tesla brain MRI, AF was identified via ECG, self-reports, and hospital records. CSVD markers were quantified using standardized MRI protocols. Regression models, adjusted for demographic and vascular risk factors, assessed associations between AF and CSVD markers, stratified by sex, anticoagulation status, and AF onset age. Random Forest and logistic regression models predicted high WMH burden and stroke risk. Of 923 participants, 85 (9.2%) had AF. AF was associated with higher WMH volumes (adjusted mean: 0.0046 vs. 0.0034 mL/TIV, p = 0.051; approaching statistical significance), particularly in men (p = 0.072) and in participants receiving anticoagulation therapy (p = 0.007). AF increased odds of symptomatic stroke (OR: 4.2, 95% CI: 2.0-8.8), large infarcts, lacunes, and silent infarcts, with stronger effects in men. Frontal lobe CMBs were more prevalent in men with AF (OR: 3.9, p = 0.049). Predictive models showed high accuracy for WMH burden (81.2%, AUC-ROC: 0.88) and stroke (84.9%, AUC-ROC: 0.91). AF is independently associated with CSVD, particularly in men and anticoagulated individuals, emphasizing the need for targeted strategies to mitigate AF-related brain injury.
Cerebral microbleeds (CMBs) are recognized as significant markers in acute ischemic stroke (AIS). Although prior studies conducted in southern China have reported CMB prevalence ranging from 27.8% to 56.7% among patients with AIS, data from northern China remain limited, and associated risk factors are not well defined. The aim of this study was to assess the prevalence and determinants of CMBs in a cohort of Chinese patients with AIS. In this hospital-based retrospective study, 171 consecutive patients diagnosed with AIS were assessed for the presence, number, and anatomical distribution of CMBs using standardized 3.0 Tesla susceptibility-weighted magnetic resonance imaging protocols. Baseline demographic and clinical variables were collected and analyzed in relation to CMB presence, burden, and location. The cohort (mean age 64.8 ± 13.0 years; 73.7% male) demonstrated a CMB prevalence of 49.1%, with variation across TOAST subtypes: large artery atherosclerosis (LAA) (59.4%), small vessel disease (SVD) (47.5%), cardioembolism (21.4%), and other etiologies (25.0%). Multivariate logistic regression identified hypertension (adjusted odds ratio [AOR] = 2.07, 95% confidence interval [CI]: 1.01-4.24) and severe white matter hyperintensity (WMH) (AOR = 4.38, 95% CI: 1.69-11.35) as independent risk factors for the presence of CMBs. Patients with ≥ 3 CMBs had a significantly higher proportion of SVD subtype (58.1% vs. 31.7%, p < 0.01) and lower levels of low-density lipoprotein cholesterol (1.85 vs. 2.38 mmol/L, p < 0.01) when compared with those with 1-2 CMBs. Deep and infratentorial CMBs were associated with a higher frequency of SVD (59.3% and 51.4% vs. 15.0%, p < 0.01) and moderate-to-severe WMH (51.8% and 81.0% vs. 45.0%, p < 0.05) when compared with strictly lobar CMBs. Approximately half of the patients with AIS exhibited CMBs, particularly those classified under LAA and SVD subtypes. Hypertension and severe WMH were independently associated with CMB presence. Distinct clinical profiles were observed based on CMB burden and location. Further research is warranted to elucidate underlying mechanisms and clinical implications.
Breast cancer remains the leading cause of cancer-related mortality in women, with conventional chemotherapy often limited by systemic toxicity due to poor drug targeting. Here, we present an integrated microfluidic chip (MMLP) that enables one-step integrated postprocessing, including solvent removal and ligand conjugation. The MMLP chip combines Y-shaped, crescent-shaped, U-shaped, and Tesla-type microchannels, augmented with pillar arrays to enhance mixing efficiency at low flow rates. A dedicated third channel allows simultaneous solvent removal and aptamer conjugation. Through computational fluid dynamics (CFD) simulations, we optimized the flow-rate ratio (lipid phase/aqueous phase/postprocessing phase = 1:5:2) and achieved AS1411 aptamer modification via thiol-maleimide chemistry. The resulting AS1411 aptamer-functionalized liposomes loaded with doxorubicin (D@Lip-Apt) exhibited uniform size (155 ± 3.2 nm, PDI = 0.17) and high drug encapsulation efficiency (76.64 ± 0.52%). In vitro and in vivo studies confirmed the nanoparticles' superior stability and tumor-targeting specificity. This modular microreactor offers exceptional flexibility in tailoring liposome properties for breast cancer therapy and demonstrates scalability for industrial production through dimensional or parallel amplification.
The accumulation of polyethylene (PE) in aquatic ecosystems represents a significant environmental challenge due to the polymer's high molecular weight and chemical stability. This study investigates the biodegradation potential of Hafnia paralvei UUNT_MP29, a bacterial strain isolated from the gut of common carp (Cyprinus carpio), for low-density polyethylene (LDPE). Initial screening on LDPE-emulsified agar confirmed extracellular enzymatic activity through the formation of distinct clear zones. Quantitative analysis showed a cumulative mass loss of 24.10% by Day 16, with the most intensive degradation occurring between Days 4 and 8, which closely correlated with maximum bacterial count (CFU/mL). Kinetic modeling indicated that the degradation followed a first-order rate law (R2 = 0.9269), with a rate constant (k) of 0.2991 days-1 and a remarkably short half-life (t1/2) of 2.32 days. Structural characterization via FTIR spectroscopy demonstrated oxidative transformation, evidenced by a reduction in sp3 C-H stretching and the emergence of C-O/C-O-C functional groups. SEM micrographs further confirmed extensive bio-deterioration, including surface pitting and macroscale erosion. Thermal analysis (TGA/DTG) supported these findings, showing a significant 10.95 °C decrease in the maximum degradation temperature (Tmax), indicating a reduction in polymer chain length. These results suggest that H. paralvei UUNT_MP29 is a highly efficient agent for the rapid breakdown of polyethylene and highlight the potential of aquatic gut microbiota as reservoirs for plastic-degrading biotechnologies.
Deep brain stimulation (DBS) of the subthalamic nucleus (STN) is an effective treatment for Parkinson's disease (PD), yet individual motor outcome remains insufficiently predictable. The effect of DBS depends on modulating brain networks, and this study evaluates whether targeting using patient-specific connectivity with 7-Tesla (7T) MRI probabilistic tractography enhances motor outcome. For connectivity analysis, selective visualization of STN connectivity to the primary cortical motor areas was performed before surgery, and electrode lead placement was directed at the connectivity-derived motor subdivision of the STN. Motor outcome, measured using the Movement Disorders Society Unified Parkinson Disease Rating Scale motor part (MDS-UPDRS part III), of 102 PD-DBS patients for whom 7T MRI connectivity analysis was used for DBS targeting, was compared to a matched control group of 118 PD-DBS patients for whom 7T MRI T2-weighted classical anatomical landmarks were used for targeting. Results of this prospective comparison show that patients operated with connectivity-guided targeting showed significantly more motor improvement compared to the control group: 56 ± 15% vs. 50 ± 20% (p = 0.015), and the connectivity-guided group showed a higher optimal response rate (96% vs. 86%, p = 0.008). Connectivity analysis enabled localization of DBS electrodes in reference to the motor subdivision. The leads that were optimally located inside the motor subdivision showed an average of 60 ± 11% motor improvement. Our findings demonstrate the clinical applicability of 7T MRI probabilistic tractography for visualizing connectivity between the STN and cortical motor areas to enable electrode lead placement directed at the motor subdivision of the STN, introducing patient-specific connectivity analysis guided DBS. This proved to be an individual biomarker for implantation location that increased the effectiveness of DBS in patients with PD.
"My science "heroes" are Nikola Tesla, Michael Faraday, and Richard Feynman because they represent the perfect blend of innovation, experimental brilliance, and fundamental understanding that I strive to bring into my work… My motto is: enjoy your life, enjoy what you do, and turn your work into something you love…" Find out more about Jerry Alfred Fereiro in his Introducing… Profile.
The SuperPATH approach for total hip arthroplasty (THA) is promoted as tissue-preserving, but objective evidence of its impact on periarticular muscles is lacking. This study aimed to evaluate periarticular muscle damage one year after THA performed via the SuperPATH approach. The hypothesis was that the SuperPATH approach causes no damage to the muscles surrounding the hip joint. A retrospective, single-surgeon study included 41 patients who underwent primary unilateral THA via the SuperPATH approach for osteonecrosis or osteoarthritis. All patients underwent preoperative and 12-month postoperative 3.0 Tesla MRI scans. Muscle condition was assessed by quantifying fatty infiltration (FI) using the Goutallier classification (with grade ≥2 defined as significant) and measuring muscle size [cross-sectional area (CSA) for gluteus medius/minimus and maximal transverse diameter (MTD) for piriformis, obturator internus, and quadratus femoris]. Statistical comparisons were made using paired t-tests and chi-square tests. One year postoperatively, a significant increase in significant FI (Goutallier grade ≥2) was observed in the piriformis (2.4% vs. 80.5%, p < 0.001), gluteus minimus (7.3% vs. 61.0%, p < 0.001), and obturator internus (4.9% vs. 85.4%, p < 0.001). Concurrently, these muscles showed a significant decrease in muscle size (CSA or MTD). The quadratus femoris showed no FI and a slight increase in MTD. The gluteus medius showed no significant change in FI (2.4% vs. 7.3%, p = 0.608) and a non-significant increase in CSA. Tendon discontinuities were observed postoperatively in the piriformis (15 cases) and obturator internus (25 cases). All patients were pain-free and walking without a limp at one year. Our hypothesis was not confirmed: the SuperPATH technique results in significant radiological evidence of damage to the piriformis, obturator internus, and gluteus minimus muscles at one year postoperatively, characterized by increased fatty infiltration and atrophy. IV; Retrospective Case Series.
Cannabis Use Disorder (CUD) can come with intense cravings, which can trigger compulsive use/relapse, underscored by anterior cingulate cortex (ACC) hyperactivity during cannabis cue-reactivity functional neuroimaging (fMRI) tasks. ACC activity can be reduced during real-time fMRI-based neurofeedback (fMRI-neurofeedback) in participants who use substances other than cannabis, but remains untested in CUD. We investigated the feasibility of fMRI-neurofeedback to reduce ACC activity and subjective craving in 10 participants with moderate-to-severe CUD. A cue-reactivity fMRI task identified participants' voxels-of-interest (VOI) within the ACC (ACCVOI). During two identical runs of 7 Tesla fMRI-neurofeedback, participants were instructed to use self-selected strategies to reduce ACCVOI activity while receiving real-time feedback via a digital craving bar (ACCVOI activity) when viewing cannabis images (down-regulation), and to simply look at neutral images (non-regulation). We examined the change in real-time percentage signal change (PSC) of the ACCVOI during down-regulation versus non-regulation, and post-hoc (offline) whole-brain activation changes. Analysis of real-time data revealed that down-regulation versus non-regulation was associated with reductions in ACCVOI PSC (p < 0.05). Further, whole-brain analysis reported down-regulation versus non-regulation was associated with lower activity in the ACC, posterior insula, and hippocampus; and greater activity in the anterior insula and middle frontal gyrus (p < 0.05, FWE-corrected). Subjective craving did not change pre-to-post fMRI-neurofeedback and did not correlate with ACCVOI PSC or whole-brain brain activity (p > 0.05). fMRI-neurofeedback may reduce the activity of regions associated with craving in CUD. This effect appeared to be dissociable from subjective craving. These observations need to be confirmed in larger samples with placebo-controlled conditions.