Search Results (138)

Background: Identifying the etiological factors of syringomyelia, which can cause progressive neurological deficits in the spinal cord, is critically important for both diagnosis and treatment. This study aimed to assess the cranial morphometric features of patients with idiopathic syringomyelia by conducting comparative analyses with individuals diagnosed with Chiari Type I, Chiari Type I accompanied by syringomyelia, and healthy controls, in order to elucidate the potential structural contributors to the pathogenesis of idiopathic syringomyelia. Methods: In this retrospective and comparative study, a total of 172 patients diagnosed with Chiari Type I and/or syringomyelia between 2016 and 2024, along with 156 radiologically normal individuals, were included. The participants were categorized into four groups: healthy controls, Chiari Type I, Chiari Type I with syringomyelia, and idiopathic syringomyelia (defined as syringomyelia without an identifiable cause). Midline sagittal T1-weighted MR images were used to obtain quantitative measurements of the posterior fossa, cerebellum, intracranial area, and foramen magnum. All measurements were stratified and statistically analyzed by sex. Results: In cases with idiopathic syringomyelia, both the posterior fossa area and the cerebellum/posterior fossa ratio differed significantly from those of healthy controls. In male patients, the foramen magnum diameter was significantly larger in the Chiari + syringomyelia group compared with the idiopathic group. A significant correlation was found between the degree of tonsillar descent and selected morphometric parameters in female subjects, whereas no such correlation was observed in males. Both Chiari groups exhibited significantly smaller posterior fossa dimensions compared with the healthy and idiopathic groups, indicating greater neural crowding. Additionally, in Chiari Type I patients, increasing degrees of tonsillar descent were associated with a decreased incidence of syringomyelia. Conclusions: Anatomical variations such as a reduced posterior fossa area or altered foramen magnum diameter may contribute to the pathogenesis of idiopathic syringomyelia. Cranial morphometric analysis appears to offer diagnostic value in these cases. Further prospective, multicenter studies incorporating advanced neuroimaging modalities, particularly those assessing cerebrospinal fluid dynamics, are warranted to better understand the mechanisms underlying syringomyelia of unknown etiology. Full article

Introduction: Sepsis-associated encephalopathy (SAE) is an acute brain dysfunction secondary to systemic infection, occurring without direct central nervous system involvement. Despite its clinical relevance, reliable biomarkers for diagnosing SAE and assessing its severity remain limited. This study aimed to evaluate the feasibility of amide proton transfer-weighted (APTw) chemical exchange saturation transfer (CEST) MRI as a non-invasive molecular imaging technique for detecting metabolic alterations related to neuroinflammation in SAE. Using a lipopolysaccharide (LPS)-induced rat model, we focused on hippocampal changes associated with neuronal inflammation. Materials and Methods: Twenty-one Sprague–Dawley rats (8 weeks old, male) were divided into three groups: control (CTRL, n = 7), LPS-induced sepsis at 5 mg/kg (LPS05, n = 7), and 10 mg/kg (LPS10, n = 7). Sepsis was induced via a single intraperitoneal injection of LPS. APTw imaging was performed using a 7 T preclinical MRI system, and signal quantification in the hippocampus was conducted using the magnetization transfer ratio asymmetry analysis. Results and Discussion: APTw imaging at 7 T demonstrated significantly elevated hippocampal APTw signals in SAE model rats (LPS05 and LPS10) compared to the control (CTRL) group: CTRL (−1.940 ± 0.207%) vs. LPS05 (−0.472 ± 0.485%) (p < 0.001) and CTRL vs. LPS10 (−0.491 ± 0.279%) (p < 0.001). However, no statistically significant difference was observed between the LPS05 and LPS10 groups (p = 0.994). These results suggest that APTw imaging can effectively detect neuroinflammation-related metabolic alterations in the hippocampus. Conclusion: Our findings support the feasibility of APTw CEST imaging as a non-invasive molecular MRI technique for SAE, with potential applications in diagnosis, disease monitoring, and therapeutic evaluation. Full article

Identifying chicken breeds and genders accurately is essential for conserving local breeds and maintaining gender ratios on farms. This study developed a system based on the Swin Transformer that efficiently and accurately classifies chicken breeds and genders. The system incorporates a target detection module to eliminate background noise and employs data augmentation techniques to prevent overfitting. A high-quality dataset, consisting of 10,482 locally captured images representing 13 Chinese native chicken breeds, was created for training and testing the model. The system was evaluated using a custom dataset and compared against popular image classification models, such as ResNet and ViT. Results indicate that the target detection module and data augmentation effectively improved the model’s performance. Additionally, strategies such as increasing the input size appropriately and utilizing pre-trained weights significantly enhanced the model’s accuracy. Interpretability analysis reveals that the system successfully identifies specific chicken body parts across different breeds and genders, aligning with human visual attention and highlighting its effectiveness. This work provides a robust solution for poultry management, aiding in tasks such as breed selection, gender ratio control, and genetic conservation. Furthermore, the methodology and dataset presented in this research provide a foundation for future studies in agricultural computer vision applications. Full article

Background and Objectives: Gliomas are characterized by high disability rates, frequent recurrence, and low survival rates, posing a significant threat to human health. Accurate grading of gliomas is crucial for treatment plan selection and prognostic assessment. Previous studies have primarily focused on the binary classification (i.e., high grade vs. low grade) of gliomas. In order to perform the four-grade (grades I, II, III, and IV) glioma classification preoperatively, we constructed an artificial neural network (ANN) model using magnetic resonance imaging data. Materials and Methods: We reviewed and included patients with gliomas who underwent preoperative MRI examinations. Radiomics features were derived from contrast-enhanced T1-weighted images (CE-T₁WI) using Pyradiomics and were selected based on their Spearman’s rank correlation with glioma grades. We developed an ANN model to classify the four pathological grades of glioma, assigning training and validation sets at a 3:1 ratio. A diagnostic confusion matrix was employed to demonstrate the model’s diagnostic performance intuitively. Results: Among the 362-patient cohort, the ANN model’s diagnostic performance plateaued after incorporating the first 19 of the 530 extracted radiomic features. At this point, the average overall diagnostic accuracy ratings for the training and validation sets were 91.28% and 87.04%, respectively, with corresponding coefficients of variation (CVs) of 0.0190 and 0.0272. The diagnostic accuracies for grades I, II, III, and IV in the training set were 91.9%, 89.9%, 92.1%, and 90.7%, respectively. The diagnostic accuracies for grades I, II, III, and IV in the validation set were 88.7%, 87.1%, 86.5%, and 86.9%, respectively. Conclusions: The MRI radiomics-based ANN model shows promising potential for the four-type classification of glioma grading, offering an objective and noninvasive method for more refined glioma grading. This model could aid in clinical decision making regarding the treatment of patients with various grades of gliomas. Full article

Background/Objectives: Degenerative cervical myelopathy (DCM) is the leading cause of functional disabilities of spinal origin in people over 50 years old. The objective of the present study was to establish a multi-parametric weighted scoring system that is easy to use in daily practice, based on the most significant MRI signs and correlated as strongly as possible with the clinical presentation (mJOA)—we call this system the SIMS or Severity on Imaging Myelopathy Score. Methods: Ninety-nine patients who underwent clinical and radiological evaluation by mJOA and MRI between January 2015 and March 2021 were retrospectively included. The variables included in the score were the Fujiwara ratio, the T2-weighted intramedullary hyperintensity, the aspect of the peri-medullary fluid cisterns, the Torg–Pavlov ratio, the local kyphosis and the number of stenotic levels. Each variable was first correlated to the mJOA score for each patient, making it possible to construct the final SIMS at the end, and validate it by comparison with mJOA scores. Results: The variables that were significantly correlated with one another were the T2-weighted intramedullary hyperintensity, the reduction in peri-medullary fluid spaces and the number of stenotic levels (p < 0.05). Then, points were assigned to each variable according to their relative importance and made it possible to construct the definitive SIMS. The final Spearman correlation coefficient between the SIMS and the mJOA score was −0.747. Conclusions: This work showed that this new multi-parametric MRI-based scoring system represents a consistent means to characterize the degree of severity of degenerative cervical myelopathy. Full article

Background/Objectives: Hepatocyte-specific contrast agent (Gd-EOB-DTPA) can improve the detection of liver lesions during MRI-guided thermal ablation. This study aimed to assess the impact of contrast agent administration on the delineation of the ablation zone during therapy monitoring. Methods: From 2010 to 2020, 358 patients with primary and secondary hepatic malignancies underwent MRI-guided thermoablation. A total of 27 patients with 30 liver lesions received Gd-EOB-DTPA during the procedure to improve target lesion visibility (Group 1), while 30 patients with 30 lesions underwent MRI-guided thermoablation without contrast administration (Group 2). T1-weighted volumetric interpolated breath-hold examination (VIBE) sequences were used for intraprocedural imaging, and post-procedural control imaging involved intravenous Gadobutrol administration in both groups. The contrast-to-noise ratio (CNR) was assessed for three key structures: the target lesion before applicator placement, the ablation zone during unenhanced therapy monitoring, and the ablation zone in contrast-enhanced control imaging. A statistical comparison of CNR values between the two groups was performed using the non-parametric Wilcoxon test (p < 0.05). Results: The CNR of lesions in group 1 significantly increased following the administration of Gd-EOB-DTPA. During therapy monitoring, the ablation zone in group 2 exhibited a significantly higher CNR compared to group 1 (median: 7.9 vs. 2.1; p < 0.001). Similarly, at the contrast-enhanced final control, the CNR of the ablation zone remained significantly greater in group 2 than in group 1 (median: 7.7 vs. 2.0; p < 0.001). Conclusions: The administration of a hepatocyte-specific contrast agent (Gd-EOB-DTPA) prior to intervention improves the visualization of liver lesions that are poorly demarcated but significantly reduces the contrast of the ablation zone during intra- and post-procedural imaging. Therefore, its use should be reserved for cases in which the target lesion cannot be sufficiently delineated without contrast. Full article

Background/Objectives: Infant FreeSurfer was introduced to address robust quantification and segmentation in the infant brain. The purpose of this study is to develop a new model for predicting the long-term neurodevelopmental outcomes of very low birth weight preterm infants using automated volumetry extracted from term-equivalent age (TEA) brain MRIs, diffusion tensor imaging, and clinical information. Methods: Preterm infants hospitalized at Severance Children’s Hospital, born between January 2012 and December 2019, were consecutively enrolled. Inclusion criteria included infants with birth weights under 1500 g who underwent both TEA MRI and Bayley Scales of Infant and Toddler Development, Second Edition (BSID-II), assessments at 18–24 months of corrected age (CA). Brain volumetric information was derived from Infant FreeSurfer using 3D T1WI of TEA MRI. Mean and standard deviation of fractional anisotropy of posterior limb of internal capsules were measured. Demographic information and comorbidities were used as clinical information. Study cohorts were split into training and test sets with a 7:3 ratio. Random forest and logistic regression models were developed to predict low Psychomotor Development Index (PDI < 85) and low Mental Development Index (MDI < 85), respectively. Performance metrics, including the area under the receiver operating curve (AUROC), accuracy, sensitivity, precision, and F1 score, were evaluated in the test set. Results: A total of 150 patient data were analyzed. For predicting low PDI, the random forest classifier was employed. The AUROC values for models using clinical variables, MR volumetry, and both clinical variables and MR volumetry were 0.8435, 0.7281, and 0.9297, respectively. To predict low MDI, a logistic regression model was chosen. The AUROC values for models using clinical variables, MR volumetry, and both clinical variables and MR volumetry were 0.7483, 0.7052, and 0.7755, respectively. The model incorporating both clinical variables and MR volumetry exhibited the highest AUROC values for both PDI and MDI prediction. Conclusions: This study presents a promising new prediction model utilizing an automated volumetry algorithm to distinguish long-term psychomotor developmental outcomes in preterm infants. Further research and validation are required for its clinical application. Full article

Background/Objectives: To evaluate the feasibility of reducing contrast volume in oncologic body imaging using dual-energy CT (DECT) by (1) identifying the optimal virtual monochromatic imaging (VMI) reconstruction using DECT and (2) comparing DECT performed with reduced iodinated contrast media (ICM) volume to single-energy CT (SECT) performed with standard ICM volume. Methods: In this retrospective study, we quantitatively and qualitatively compared the image quality of 35 thoracoabdominopelvic DECT across 9 different virtual monoenergetic image (VMI) levels (from 40 to 80 keV) using a reduced volume of ICM (0.3 gI/kg of body weight) to determine the optimal keV reconstruction level. Out of these 35 patients, 20 had previously performed SECT with standard ICM volume (0.3 gI/kg of body weight + 9 gI), enabling protocol comparison. The qualitative analysis included overall image quality, noise, and contrast enhancement by two radiologists. Quantitative analysis included contrast enhancement measurements, contrast-to-noise ratio, and signal-to-noise ratio of the liver parenchyma and the portal vein. ANOVA was used to identify the optimal VMI level reconstruction, while t-tests and paired t-tests were used to compare both protocols. Results: VMI_{60 keV} provided the highest overall image quality score. DECT with reduced ICM volume demonstrated higher contrast enhancement and lower noise than SECT with standard ICM volume (p < 0.001). No statistical difference was found in the overall image quality between the two protocols (p = 0.290). Conclusions: VMI_{60 keV} with reduced contrast volume provides higher contrast and lower noise than SECT at a standard contrast volume. DECT using a reduced ICM volume is the technique of choice for oncologic body CT. Full article

Background/Objectives: Diabetes-related pancreatic changes on MRI remain unclear. Thus, we evaluated the pancreatic changes on MRI in patients with both type 1 diabetes (T1D) and type 2 diabetes (T2D) using multiparametric MRI. Methods: This prospective study involved patients with T1D or T2D who underwent upper abdominal 3-T MRI. Additionally, patients without impaired glucose metabolism were retrospectively included as a control. The imaging data included pancreatic anteroposterior (AP) diameter, pancreas-to-muscle signal intensity ratio (SIR) on fat-suppressed T1-weighted image (FS-T1WI), apparent diffusion coefficient (ADC) value, T1 value on T1 map, proton density fat fraction (PDFF), and mean secretion grade of pancreatic juice flow on cine-dynamic magnetic resonance cholangiopancreatography (MRCP). The MR measurements were compared using one-way analysis of variance and the Kruskal–Wallis test. Results: Sixty-one patients with T1D (n = 7) or T2D (n = 54) and 21 control patients were evaluated. The pancreatic AP diameters were significantly smaller in patients with T1D than in patients with T2D (p < 0.05). The average SIR on FS-T1WI was significantly lower in patients with T1D than in controls (p < 0.001). The average ADC and T1 values of the pancreas were significantly higher in patients with T1D than in patients with T2D (p < 0.01) and controls (p < 0.05). The mean secretion grade of pancreatic juice flow was significantly lower in patients with T1D than in controls (p = 0.019). The average PDFF of the pancreas was significantly higher in patients with T2D than in controls (p = 0.029). Conclusions: Patients with T1D had reduced pancreas size, increased pancreatic T1 and ADC values, and decreased pancreatic juice flow on cine-dynamic MRCP, whereas patients with T2D had increased pancreatic fat content. Full article

Background: The obesity epidemic among adolescents significantly impacts not only their physical health but also various psychological factors, including their perception of body image. Thus, this study pursued three main objectives: (1) to update the reference standard values for all the physical fitness tests performed; (2) to examine the impact of overweight and obesity on factors influencing physical fitness in adolescents; and (3) to determine the relationship between the physical fitness level and the body image dissatisfaction among a population of French-Canadian adolescents. Methods: A total of 1862 adolescents aged 12 to 17 (1008 boys and 854 girls) participated in this study. Data were collected from 12 French-language high-schools from different socioeconomic backgrounds and spread across four regions of the province of Québec, Canada. Anthropometric measures (body mass, body height, body mass index (BMI), waist circumference, waist-to-height ratio) and fitness tests (aerobic power, anaerobic power, muscle endurance, muscular power, flexibility) were conducted. To assess adolescents’ body perception, a silhouette scale was used. Results: Standardized normative values were established for each fitness test (Lambda Mu Sigma; LMS method). In boys, performance generally improved with age, except for the V-test and sit-ups, which remained stable, and VO₂peak, which declined during adolescence in both genders (unpaired t-test and Cohen’s d effect size). In girls, only the vertical jump and 30 m sprint improved with age, while the other tests stabilized by age 13. Fitness level was significantly influenced by obesity status. Boys and girls with a normal BMI performed better than those who were overweight or obese (ANOVA = p < 0.001 and effect size F). Girls appeared to be less affected by obesity status, with differences between overweight and obese groups rarely being significant (p > 0.05). Fitness level was also linked to body satisfaction, with satisfied adolescents generally achieving better scores than dissatisfied ones, even among those with a typical BMI. Socioeconomic status did not impact body image perception in boys (p = 0.351). In contrast, girls from lower socioeconomic backgrounds exhibited significantly more negative perceptions (p = 0.002) than their peers from more affluent families. Conclusions: Obesity status is strongly associated with poorer performance on fitness tests. Conversely, higher levels of physical fitness are linked to improved body image satisfaction. This positive relationship between fitness and body image holds true even for individuals with a healthy body weight (typical BMI). Full article

Background/Objectives: Although multiple magnetic resonance imaging (MRI) indices are known to be sensitive to the noninvasive assessment of myelin integrity, their relative sensitivities have not been directly compared. This study aimed to identify the most sensitive MRI index for characterizing myelin composition in the spinal cord’s gray matter (GM) and white matter (WM). Methods: MRI was performed on a deer’s ex vivo cervical spinal cord. Quantitative indices known to be sensitive to myelin, including the myelin water fraction (MWF), magnetization transfer ratio (MTR), the signal ratio between T1- and T2-weighted images (T1W/T2W), fractional anisotropy (FA), mean diffusivity (MD), electrical conductivity (σ), and T1, T2, and T1ρ relaxation times were calculated. Their mean values were compared using repeated measures analysis of variance (ANOVA) and post hoc Bonferroni tests or Friedman and post hoc Wilcoxon tests to identify differences across GM and WM columns possessing distinct myelin distributions, as revealed by histological analysis. Relationships among the indices were examined using Spearman’s rank-order correlation analysis. Corrected p < 0.05 was considered statistically significant. Results: All indices except σ differed significantly between GM and all WM columns. Two of the three WM columns had significantly different MWF, FA, MD, and T2, whereas one WM column had significantly different MTR, σ, T1, and T1ρ from the others. A significant moderate to very strong correlation was observed among most indices. Conclusions: The sensitivity of MRI indices in distinguishing spinal cord regions varied. A strategic combination of two or more indices may allow the accurate differentiation of spinal cord regions. Full article

Traditional image classification often misclassifies unknown samples as known classes during testing, degrading recognition accuracy. Open-set image recognition can simultaneously detect known classes (KCs) and unknown classes (UCs) but still struggles to improve recognition performance caused by open space risk. Therefore, we introduce a cosine distance loss function (CDLoss), which exploits the orthogonality of one-hot encoding vectors to align known samples with their corresponding one-hot encoder directions. This reduces the overlap between the feature spaces of KCs and UCs, mitigating open space risk. CDLoss was incorporated into both Softmax-based and prototype-learning-based frameworks to evaluate its effectiveness. Experimental results show that CDLoss improves AUROC, OSCR, and accuracy across both frameworks and different datasets. Furthermore, various weight combinations of the ARPL and CDLoss were explored, revealing optimal performance with a 1:2 ratio. T-SNE analysis confirms that CDLoss reduces the overlap between the feature spaces of KCs and UCs. These results demonstrate that CDLoss helps mitigate open space risk, enhancing recognition performance in open-set image classification tasks. Full article

Purpose: Breath-hold T2-weighted half-Fourier acquisition single-shot turbo spin echo (HASTE) magnetic resonance imaging (MRI) of the upper abdomen with a slice thickness below 5 mm suffers from high image noise and blurring. The purpose of this prospective study was to improve image quality and accelerate imaging acquisition by using single-breath-hold T2-weighted HASTE with deep learning (DL) reconstruction (DL-HASTE) with a 3 mm slice thickness. Method: MRI of the upper abdomen with DL-HASTE was performed in 35 participants (5 healthy volunteers and 30 patients) at 3 Tesla. In a subgroup of five healthy participants, signal-to-noise ratio (SNR) analysis was used after DL reconstruction to identify the smallest possible layer thickness (1, 2, 3, 4, 5 mm). DL-HASTE was acquired with a 3 mm slice thickness (DL-HASTE-3 mm) in 30 patients and compared with 5 mm DL-HASTE (DL-HASTE-5 mm) and with standard HASTE (standard-HASTE-5 mm). Image quality and motion artifacts were assessed quantitatively using Laplacian variance and semi-quantitatively by two radiologists using five-point Likert scales. Results: In the five healthy participants, DL-HASTE-3 mm was identified as the optimal slice (SNR 23.227 ± 3.901). Both DL-HASTE-3 mm and DL-HASTE-5 mm were assigned significantly higher overall image quality scores than standard-HASTE-5 mm (Laplacian variance, both p < 0.001; Likert scale, p < 0.001). Compared with DL-HASTE-5 mm (1.10 × 10⁻⁵ ± 6.93 × 10⁻⁶), DL-HASTE-3 mm (1.56 × 10⁻⁵ ± 8.69 × 10⁻⁶) provided a significantly higher SNR Laplacian variance (p < 0.001) and sharpness sub-scores for the intestinal tract, adrenal glands, and small anatomic structures (bile ducts, pancreatic ducts, and vessels; p < 0.05). Lesion detectability was rated excellent for both DL-HASTE-3 mm and DL-HASTE-5 mm (both: 5 [IQR4–5]) and was assigned higher scores than standard-HASTE-5 mm (4 [IQR4–5]; p < 0.001). DL-HASTE reduced the acquisition time by 63–69% compared with standard-HASTE-5 mm (p < 0.001). Conclusions: DL-HASTE is a robust abdominal MRI technique that improves image quality while at the same time reducing acquisition time compared with the routine clinical HASTE sequence. Using ultra-thin DL-HASTE-3 mm results in an even greater improvement with a similar SNR. Full article

Background and Objectives: This study aimed to determine the minimal effective dose of indocyanine green (ICG) required for accurately assessing colonic perfusion during laparoscopic colorectal surgery using a laser-assisted laparoscopic near-infrared (NIR) camera system. Materials and Methods: In 15 patients with colorectal cancer undergoing right hemicolectomy, the left branch of the middle colic artery was preserved, and ICG angiography was performed in the transverse colon. To determine the optimal ICG dose, experimental doses of 0.01, 0.02, 0.03, 0.04, and 0.05 mg of ICG per patient’s body weight (kg) were administered intravenously in each group. Additionally, a conventional dose of 0.2 mg/kg was administered in the same patients more than 30 min after the initial dose. For quantitative analysis, the fluorescent expression region was extracted, and fluorescence intensity was analyzed using automatic image processing. Analysis accessibility, T_1/2MAX, perfusion time ratio, slope, artificial intelligence (AI)-based perfusion pattern analysis, and washout time were measured in 150 detailed regions of interest in each image. Results: Group 1 (0.01 mg/kg) showed significantly lower accessibility rates for quantitative analysis (48.0%) compared with Groups 2–5 (84.7–100%). The mean slope value in Group 1 was 3.7, which fell below the acceptable threshold (>4) and was significantly lower than that of the other groups (p < 0.001). An acceptable AI-based perfusion pattern was 14.2% in Group 1, significantly lower than in Groups 2–5 (66.4–100%). Washout time was significantly faster with minimal doses compared with conventional doses (39.0 ± 15.8 s vs. 117.5 ± 4.9 s, respectively, p < 0.001). Conclusions: This study supports the use of minimal ICG doses, ranging from 0.02 to 0.05 mg/kg, to optimize repetitive ICG angiography using a laser-assisted laparoscopic NIR camera. Full article

Background and Purpose: Perivascular spaces (PVS) are usually enlarged in small vessel disease (SVD). However, the significance of PVS patterns in different locations is uncertain. Hence, we analyzed the distribution of PVS in patients with a recent small subcortical infarct (RSSI) and their correlation with clinical and imaging factors. Materials and Methods: In a cohort of 71 patients with an RSSI with complete clinical data, including the Pittsburgh Sleep Quality Index (PSQI), we segmented PVS in white matter (WM-PVS), basal ganglia (BG-PVS), and brainstems (BS-PVS) on 3T-MRI T2-weighted sequences, obtaining fractional volumes (%), and calculated the WM/BG-PVS ratio. We analyzed the Pearson’s correlation coefficients between PVS regional loads. We used normalized PVS measures to assess the associations with clinical and MRI-SVD features (white matter hyperintensities (WMHs), number of lacunes, and microbleeds) in univariable and multivariable linear regressions adjusted for age, sex, and hypertension. Results: In our cohort (mean age 70 years; 27% female), the Pearson’s correlation coefficients between WM-PVS/BG-PVS, WM-PVS/BS-PVS, and BG-PVS/BS-PVS were 0.67, 0.61, and 0.59 (all p < 0.001). In the adjusted models, BG-PVS were associated with lacunes (p = 0.034), WMHs (p = 0.006), and microbleeds (p = 0.017); WM-PVS with lacunes (p = 0.003); while BS-PVS showed no associations. The WM/BG-PVS ratio was associated with lacunes (p = 0.018) and the PSQI (p = 0.046). Conclusions: PVS burdens in different regions are highly correlated in patients with RSSI but with different SVD patterns. Sleep quality impairment might affect waste removal mechanisms differently in the WM and BG regions. Full article