Utilizing collimated aperture with proton pencil beam scanning (PBS) for stereotactic radiotherapy.

PURPOSE: Proton stereotactic radiosurgery (PSRS) has emerged as an innovative proton therapy modality aimed at achieving precise dose delivery with minimal impact on healthy tissues. This study explores the dosimetric outcomes of PSRS in comparison to traditional intensity-modulated proton therapy (IMPT) by focusing on cases with small target volumes. A custom-made aperture system designed for proton therapy, specifically tailored to small target volumes, was developed and implemented for this investigation. METHODS: A prerequisite mechanical validation through an isocentricity test precedes dosimetric assessments, ensuring the seamless integration of mechanical and dosimetry analyses. Five patients were enrolled in the study, including two with choroid melanoma and three with arteriovenous malformations (AVM). Two treatment plans were meticulously executed for each patient, one utilizing a collimated aperture and the other without. Both plans were subjected to robust optimization, maintaining identical beam arrangements and consistent optimization parameters to account for setup errors of 2 mm and range uncertainties of 3.5%. Plan evaluation metrics encompassing the Heterogeneity Index (HI), Paddick Conformity Index (CIPaddick), Gradient Index (GI), and the R50% index to evaluate alterations in low-dose volume distribution. RESULTS: The comparative analysis between PSRS and traditional PBS treatment revealed no significant differences in plan outcomes, with both modalities demonstrating comparable target coverage. However, collimated apertures resulted in discernible improvements in dose conformity, dose fall-off, and reduced low-dose volume. CONCLUSIONS: This study underscores the advantageous impact of the aperture system on proton therapy, particularly in cases involving small target volumes.

Diffusion and structural MRI as potential biomarkers in people with Parkinson's disease and cognitive impairment.

OBJECTIVE: To explore the neuroimage change in Parkinson's disease (PD) patients with cognitive impairments, this study investigated the correlation between plasma biomarkers and morphological brain changes in patients with normal cognition and mild cognitive impairment. The objective was to identify the potential target deposition regions of the plasma biomarkers and to search for the relevant early neuroimaging biomarkers on the basis of different cognitive domains. METHODS: Structural brain MRI and diffusion weighted images were analyzed from 49 eligible PD participants (male/female: 27/22; mean age: 73.4 ± 8.5 years) from a retrospective analysis. Plasma levels of α-synuclein, amyloid beta peptide, and total tau were collected. A comprehensive neuropsychological assessment of the general and specific cognitive domains was performed. Difference between PD patients with normal cognition and impairment was examined. Regression analysis was performed to evaluate the correlation between image-derived index and plasma biomarkers or neuropsychological assessments. RESULTS: Significant correlation was found between plasma Aß-42 level and fractional anisotropy of the middle occipital, angular, and middle temporal gyri of the left brain, as well as plasma T-tau level and the surface area of the isthmus or the average thickness of the posterior part of right cingulate gyrus. Visuospatial and executive function is positively correlated with axial diffusivity in bilateral cingulate gyri. CONCLUSION: In nondemented PD patients, the target regions for plasma deposition might be located in the cingulate, middle occipital, angular, and middle temporal gyri. Changes from multiple brain regions can be correlated to the performance of different cognitive domains. CLINICAL RELEVANCE STATEMENT: Cognitive impairment in Parkinson's disease is primarily linked to biomarkers associated with Alzheimer's disease rather than those related to Parkinson's disease and resembles the frontal variant of Alzheimer's disease, which may guide management strategies for cognitive impairment in Parkinson's disease. KEY POINTS: • Fractional anisotropy, surface area, and thickness in the cingulate, middle occipital, angular, and middle temporal gyri can be significantly correlated with plasma Aß-42 and T-tau level. • Axial diffusivity in the cingulate gyri was correlated with visuospatial and executive function. • The pattern of cognitive impairment in Parkinson's disease can be similar to the frontal variant than typical Alzheimer's disease.

A fixel-based analysis of white matter reductions early detects Parkinson disease with mild cognitive impairment.

BACKGROUND: White matter (WM) tract alterations are early signs of cognitive impairment in Parkinson disease (PD) patients. Fixel-based analysis (FBA) has advantages over traditional diffusion tensor imaging in managing complex and crossing fibers. We used FBA to measure fiber-specific changes in patients with PD mild cognitive impairment (PD-MCI) and PD normal cognition (PD-NC). METHODS: Seventy-one patients with PD without dementia were included: 39 PD-MCI and 32 PD-NC. All underwent diffusion-weighted imaging, clinical examinations, and tests to evaluate their cognitive function globally and in five cognitive domains. FBA was used to investigate fiber-tract alterations and compare PD-MCI with PD-NC subjects. Correlations with each cognitive test were analyzed. RESULTS: Patients with PD-MCI were significantly older (P = 0.044), had a higher male-to-female ratio (P = 0.006) and total Unified Parkinson's Disease Rating Scale score (P = 0.001). All fixel-based metrics were significantly reduced within the body of the corpus callosum and superior corona radiata in PD-MCI patients (family-wise error-corrected P value < 0.05) compared with PD-NC patients. The cingulum, superior longitudinal fasciculi, and thalamocortical circuit exhibited predominantly fiber-bundle cross-section (FC) changes. In regression analysis, reduced FC values in cerebellar circuits were associated with poor motor function in PD-MCI patients and poor picture-naming ability in PD-NC patients. CONCLUSIONS: PD-MCI patients have significant WM alterations compared with PD-NC patients. FBA revealed these changes in various bundle tracts, helping us to better understand specific WM changes that are functionally implicated in PD cognitive decline. FBA is potentially useful in detecting early cognitive decline in PD.

Neuroplastic Changes Associated With Hybrid Exercise-Cognitive Training in Stroke Survivors With Mild Cognitive Decline: A Randomized Controlled Trial.

BACKGROUND: Exercise and cognitive training have been shown to induce neuroplastic changes and modulate cognitive function following stroke. However, it remains unclear whether hybridized exercise-cognitive training facilitates cortical activity and further influences cognitive function after stroke. OBJECTIVE: The study aimed to investigate the effects of 2 hybridized exercise-cognitive trainings on neuroplastic changes and behavioral outcomes in stroke survivors with mild cognitive decline. METHODS: This study was a single-blind randomized controlled trial. Stroke survivors were randomly assigned to 1 of 3 groups: (1) sequential exercise-cognitive training (SEQ), (2) dual-task exercise-cognitive training (DUAL), or (3) control group (CON). All groups underwent training 60 min per day, 3 days per week, for a total of 12 weeks. The primary outcome was the resting-state (RS) functional connectivity (FC) in functional magnetic resonance imaging. Secondary behavioral outcomes included cognitive and physical functions. RESULTS: After 12 weeks of training, patients in the SEQ group (n = 21) exhibited increased RS FC between the left occipital lobe and posterior cingulate gyrus with right parietal lobe, compared to the DUAL (n = 22) and CON (n = 20) groups. Additionally, patients in the DUAL group showed increased FC of the left temporal lobe. However, changes in behavioral outcome measures were non-significant among the 3 groups (all P's > .05). CONCLUSIONS: This study highlights the distinct neuroplastic mechanisms associated with 2 types of exercise-cognitive hybridized trainings. The pre-post functional magnetic resonance imaging measurements illustrated the time course of neural mechanisms for cognitive recovery in stroke survivors following different exercise-cognitive training approaches. Trial registration. NCT03230253.

The Image-Histology Correlation of Subcutaneous mPEG-poly(Ala) Hydrogel-Embedded MIN6 Cell Grafts in Nude Mice.

Previously, we have successfully used noninvasive magnetic resonance (MR) and bioluminescence imaging to detect and monitor mPEG-poly(Ala) hydrogel-embedded MIN6 cells at the subcutaneous space for up to 64 days. In this study, we further explored the histological evolution of MIN6 cell grafts and correlated it with image findings. MIN6 cells were incubated overnight with chitosan-coated superparamagnetic iron oxide (CSPIO) and then 5 × 106 cells in the 100 µL hydrogel solution were injected subcutaneously into each nude mouse. Grafts were removed and examined the vascularization, cell growth and proliferation with anti-CD31, SMA, insulin and ki67 antibodies, respectively, at 8, 14, 21, 29 and 36 days after transplantation. All grafts were well-vascularized with prominent CD31 and SMA staining at all time points. Interestingly, insulin-positive cells and iron-positive cells were scattered in the graft at 8 and 14 days; while clusters of insulin-positive cells without iron-positive cells appeared in the grafts at 21 days and persisted thereafter, indicating neogrowth of MIN6 cells. Moreover, proliferating MIN6 cells with strong ki67 staining was observed in 21-, 29- and 36-day grafts. Our results indicate that the originally transplanted MIN6 cells proliferated from 21 days that presented distinctive bioluminescence and MR images.

Fully automated segmentation and radiomics feature extraction of hypopharyngeal cancer on MRI using deep learning.

OBJECTIVES: To use convolutional neural network for fully automated segmentation and radiomics features extraction of hypopharyngeal cancer (HPC) tumor in MRI. METHODS: MR images were collected from 222 HPC patients, among them 178 patients were used for training, and another 44 patients were recruited for testing. U-Net and DeepLab V3 + architectures were used for training the models. The model performance was evaluated using the dice similarity coefficient (DSC), Jaccard index, and average surface distance. The reliability of radiomics parameters of the tumor extracted by the models was assessed using intraclass correlation coefficient (ICC). RESULTS: The predicted tumor volumes by DeepLab V3 + model and U-Net model were highly correlated with those delineated manually (p < 0.001). The DSC of DeepLab V3 + model was significantly higher than that of U-Net model (0.77 vs 0.75, p < 0.05), particularly in those small tumor volumes of < 10 cm3 (0.74 vs 0.70, p < 0.001). For radiomics extraction of the first-order features, both models exhibited high agreement (ICC: 0.71-0.91) with manual delineation. The radiomics extracted by DeepLab V3 + model had significantly higher ICCs than those extracted by U-Net model for 7 of 19 first-order features and for 8 of 17 shape-based features (p < 0.05). CONCLUSION: Both DeepLab V3 + and U-Net models produced reasonable results in automated segmentation and radiomic features extraction of HPC on MR images, whereas DeepLab V3 + had a better performance than U-Net. CLINICAL RELEVANCE STATEMENT: The deep learning model, DeepLab V3 + , exhibited promising performance in automated tumor segmentation and radiomics extraction for hypopharyngeal cancer on MRI. This approach holds great potential for enhancing the radiotherapy workflow and facilitating prediction of treatment outcomes. KEY POINTS: • DeepLab V3 + and U-Net models produced reasonable results in automated segmentation and radiomic features extraction of HPC on MR images. • DeepLab V3 + model was more accurate than U-Net in automated segmentation, especially on small tumors. • DeepLab V3 + exhibited higher agreement for about half of the first-order and shape-based radiomics features than U-Net.

The neural basis of pain during labor.

Characterizing a labor pain-related neural signature is a key prerequisite for devising optimized pharmacologic and nonpharmacologic labor pain relief methods. The aim of this study was to describe the neural basis of labor pain and to provide a brief summary of how epidural anesthesia may affect pain-related neuronal activity during labor. Possible future directions are also highlighted. By taking advantage of functional magnetic resonance imaging, brain activation maps and functional neural networks of women during labor that have been recently characterized were compared between pregnant women who received epidural anesthesia and those who did not. In the subgroup of women who did not receive epidural anesthesia, labor-related pain elicited activations in a distributed brain network that included regions within the primary somatosensory cortex (postcentral gyrus and left parietal operculum cortex) and within the traditional pain network (lentiform nucleus, insula, and anterior cingulate gyrus). The activation maps of women who had been administered epidural anesthesia were found to be different-especially with respect to the postcentral gyrus, the insula, and the anterior cingulate gyrus. Parturients who received epidural anesthesia were also compared with those who did not in terms of functional connectivity from selected sensory and affective regions. When analyzing women who did not receive epidural anesthesia, marked bilateral connections from the postcentral gyrus to the superior parietal lobule, supplementary motor area, precentral gyrus, and the right anterior supramarginal gyrus were observed. In contrast, women who received epidural anesthesia showed fewer connections from the postcentral gyrus-being limited to the superior parietal lobule and supplementary motor area. Importantly, one of the most noticeable effects of epidural anesthesia was observed in the anterior cingulate cortex-a primary region that modulates pain perception. The increased outgoing connectivity from the anterior cingulate cortex in women who received epidural anesthesia indicates that the cognitive control exerted by this area might play a major role in the relief from labor pain. These findings not only affirmed the existence of a brain signature for pain experienced during labor, but they also showed that this signature can be altered by the administration of epidural anesthesia. This finding raises a question about the extent to which the cingulo-frontal cortex may exert top-down influences to gate women's experiences of labor-related pain. Because the anterior cingulate cortex is also involved in the processing and modulation of emotional content, such as fear and anxiety, a related question is about the extent to which the use of epidural anesthesia can affect different components of pain perception. Finally, inhibition of anterior cingulate cortex neurons may represent a potential new therapeutic target for alleviating labor-associated pain.

Generalizable transfer learning of automated tumor segmentation from cervical cancers toward a universal model for uterine malignancies in diffusion-weighted MRI.

PURPOSE: To investigate the generalizability of transfer learning (TL) of automated tumor segmentation from cervical cancers toward a universal model for cervical and uterine malignancies in diffusion-weighted magnetic resonance imaging (DWI). METHODS: In this retrospective multicenter study, we analyzed pelvic DWI data from 169 and 320 patients with cervical and uterine malignancies and divided them into the training (144 and 256) and testing (25 and 64) datasets, respectively. A pretrained model was established using DeepLab V3 + from the cervical cancer dataset, followed by TL experiments adjusting the training data sizes and fine-tuning layers. The model performance was evaluated using the dice similarity coefficient (DSC). RESULTS: In predicting tumor segmentation for all cervical and uterine malignancies, TL models improved the DSCs from the pretrained cervical model (DSC 0.43) when adding 5, 13, 26, and 51 uterine cases for training (DSC improved from 0.57, 0.62, 0.68, 0.70, p < 0.001). Following the crossover at adding 128 cases (DSC 0.71), the model trained by combining data from adding all the 256 patients exhibited the highest DSCs for the combined cervical and uterine datasets (DSC 0.81) and cervical only dataset (DSC 0.91). CONCLUSIONS: TL may improve the generalizability of automated tumor segmentation of DWI from a specific cancer type toward multiple types of uterine malignancies especially in limited case numbers.

Diffusion tensor imaging for the differential diagnosis of Parkinsonism by machine learning.

BACKGROUND: There are currently no specific tests for either idiopathic Parkinson's disease or Parkinson-plus syndromes. The study aimed to investigate the diagnostic performance of features extracted from the whole brain using diffusion tensor imaging concerning parkinsonian disorders. METHODS: The retrospective data yielded 625 participants (average age: 61.4 ± 8.2, men/women: 313/312; healthy controls/idiopathic Parkinson's disease/multiple system atrophy/progressive supranuclear palsy: 219/286/51/69) between 2008 and 2017. Diffusion-weighted images were obtained using a 3T MR scanner. The 90th, 50th, and 10th percentiles of fractional anisotropy and mean/axial/radial diffusivity from each parcellated brain area were recorded. Statistical analysis was evaluated based on the features extracted from the whole brain, as determined using discriminant function analysis and support vector machine. 20% of the participants were used as an independent blind dataset with 5 times cross-verification. Diagnostic performance was evaluated by the sensitivity and the F1 score. RESULTS: Diagnoses were accurate for distinguishing idiopathic Parkinson's disease from healthy control and Parkinson-plus syndromes (87.4 ± 2.1% and 82.5 ± 3.9%, respectively). Diagnostic F1 scores varied for Parkinson-plus syndromes with 67.2 ± 3.8% for multiple system atrophy and 71.6 ± 3.5% for progressive supranuclear palsy. For early and late detection of idiopathic Parkinson's disease, the diagnostic performance was 79.2 ± 7.4% and 84.4 ± 6.9%, respectively. The diagnostic performance was 68.8 ± 11.0% and 52.5 ± 8.9% in early and late detection to distinguish different Parkinson-plus syndromes. CONCLUSIONS: Features extracted from diffusion tensor imaging of the whole brain can provide objective evidence for the diagnosis of healthy control, idiopathic Parkinson's disease, and Parkinson-plus syndromes with fair to very good diagnostic performance.

Deep Learning-Based Brain Computed Tomography Image Classification with Hyperparameter Optimization through Transfer Learning for Stroke.

Brain computed tomography (CT) is commonly used for evaluating the cerebral condition, but immediately and accurately interpreting emergent brain CT images is tedious, even for skilled neuroradiologists. Deep learning networks are commonly employed for medical image analysis because they enable efficient computer-aided diagnosis. This study proposed the use of convolutional neural network (CNN)-based deep learning models for efficient classification of strokes based on unenhanced brain CT image findings into normal, hemorrhage, infarction, and other categories. The included CNN models were CNN-2, VGG-16, and ResNet-50, all of which were pretrained through transfer learning with various data sizes, mini-batch sizes, and optimizers. Their performance in classifying unenhanced brain CT images was tested thereafter. This performance was then compared with the outcomes in other studies on deep learning-based hemorrhagic or ischemic stroke diagnoses. The results revealed that among our CNN-2, VGG-16, and ResNet-50 analyzed by considering several hyperparameters and environments, the CNN-2 and ResNet-50 outperformed the VGG-16, with an accuracy of 0.9872; however, ResNet-50 required a longer time to present the outcome than did the other networks. Moreover, our models performed much better than those reported previously. In conclusion, after appropriate hyperparameter optimization, our deep learning-based models can be applied to clinical scenarios where neurologist or radiologist may need to verify whether their patients have a hemorrhage stroke, an infarction, and any other symptom.

Magnetic Resonance Imaging of Transplanted Porcine Neonatal Pancreatic Cell Clusters Labeled with Exendin-4-Conjugated Manganese Magnetism-Engineered Iron Oxide Nanoparticles.

Recently, we have shown that manganese magnetism-engineered iron oxide nanoparticles (MnMEIO NPs) conjugated with exendin-4 (Ex4) act as a contrast agent that directly trace implanted mouse islet ß-cells by magnetic resonance imaging (MRI). Here we further advanced this technology to track implanted porcine neonatal pancreatic cell clusters (NPCCs) containing ducts, endocrine, and exocrine cells. NPCCs from one-day-old neonatal pigs were isolated, cultured for three days, and then incubated overnight with MnMEIO-Ex4 NPs. Binding of NPCCs and MnMEIO-Ex4 NPs was confirmed with Prussian blue staining in vitro prior to the transplantation of 2000 MnMEIO-Ex4 NP-labeled NPCCs beneath the left renal capsule of six nondiabetic nude mice. The 7.0 T MRI on recipients revealed persistent hypointense areas at implantation sites for up to 54 days. The MR signal intensity of the graft on left kidney reduced 62-88% compared to the mirror areas on the contralateral kidney. Histological studies showed colocalization of insulin/iron and SOX9/iron staining in NPCC grafts, indicating that MnMEIO-Ex4 NPs were taken up by mature ß-cells and pancreatic progenitors. We conclude that MnMEIO-Ex4 NPs are excellent contrast agents for detecting and long-term monitoring implanted NPCCs by MRI.

Deep learning based diagnosis of Parkinson's Disease using diffusion magnetic resonance imaging.

The diagnostic performance of a combined architecture on Parkinson's disease using diffusion tensor imaging was evaluated. A convolutional neural network was trained from multiple parcellated brain regions. A greedy algorithm was proposed to combine the models from individual regions into a complex one. Total 305 Parkinson's disease patients (aged 59.9±9.7 years old) and 227 healthy control subjects (aged 61.0±7.4 years old) were enrolled from 3 retrospective studies. The participants were divided into training with ten-fold cross-validation (N = 432) and an independent blind dataset (N = 100). Diffusion-weighted images were acquired from a 3T scanner. Fractional anisotropy and mean diffusivity were calculated and was subsequently parcellated into 90 cerebral regions of interest based on the Automatic Anatomic Labeling template. A convolutional neural network was implemented which contained three convolutional blocks and a fully connected layer. Each convolutional block consisted of a convolutional layer, activation layer, and pooling layer. This model was trained for each individual region. A greedy algorithm was implemented to combine multiple regions as the final prediction. The greedy algorithm predicted the area under curve of 94.1±3.2% from the combination of fractional anisotropy from 22 regions. The model performance analysis showed that the combination of 9 regions is equivalent. The best area under curve was 74.7±5.4% from the right postcentral gyrus. The current study proposed an architecture of convolutional neural network and a greedy algorithm to combine from multiple regions. With diffusion tensor imaging, the algorithm showed the potential to distinguish patients with Parkinson's disease from normal control with satisfactory performance.

Exendin-4-Conjugated Manganese Magnetism-Engineered Iron Oxide Nanoparticles as a Potential Magnetic Resonance Imaging Contrast Agent for Tracking Transplanted ß-Cells.

To specifically detect and trace transplanted islet ß-cells by magnetic resonance imaging (MRI), we conjugated manganese magnetism-engineered iron oxide nanoparticles (MnMEIO NPs) with exendin-4 (Ex4) which specifically binds glucagon-like peptide-1 receptors on the surface of ß-cells. The size distribution of MnMEIO and MnMEIO-Ex4 NPs were 67.8 ± 1.3 and 70.2 ± 2.3 nm and zeta potential 33.3 ± 0.5 and 0.6 ± 0.1 mV, respectively. MnMEIO and MnMEIO-Ex4 NPs with iron content ≤ 40 µg/mL did not affect MIN6 ß-cell viability and insulin secretion. Positive iron staining was found in MIN6 ß-cells loaded with MnMEIO-Ex4 NPs but not in those with MnMEIO NPs. A transmission electron microscope confirmed MnMEIO-Ex4 NPs were distributed in the cytoplasm of MIN6. In vitro MR images revealed a loss of signal intensity in MIN6 ß-cells labeled with MnMEIO-Ex4 NPs but not with MnMEIO NPs. After transplantation of islets labeled with MnMEIO-Ex4, the graft under kidney capsule could be visualized on MRI as persistent hypointense areas up to 17 weeks. Moreover, histology of the islet graft showed positive staining for insulin, glucagon and iron. Our results indicate MnMEIO-Ex4 NPs are safe and effective for the detection and long-term monitoring of transplanted ß-cells by MRI.

Fixel-Based Analysis Effectively Identifies White Matter Tract Degeneration in Huntington's Disease.

Microstructure damage in white matter might be linked to regional and global atrophy in Huntington's Disease (HD). We hypothesize that degeneration of subcortical regions, including the basal ganglia, is associated with damage of white matter tracts linking these affected regions. We aim to use fixel-based analysis to identify microstructural changes in the white matter tracts. To further assess the associated gray matter damage, diffusion tensor-derived indices were measured from regions of interest located in the basal ganglia. Diffusion weighted images were acquired from 12 patients with HD and 12 healthy unrelated controls using a 3 Tesla scanner. Reductions in fixel-derived metrics occurs in major white matter tracts, noticeably in corpus callosum, internal capsule, and the corticospinal tract, which were closely co-localized with the regions of increased diffusivity in basal ganglia. These changes in diffusion can be attributed to potential axonal degeneration. Fixel-based analysis is effective in studying white matter tractography and fiber changes in HD.

International Multicenter Analysis of Brain Structure Across Clinical Stages of Parkinson's Disease.

BACKGROUND: Brain structure abnormalities throughout the course of Parkinson's disease have yet to be fully elucidated. OBJECTIVE: Using a multicenter approach and harmonized analysis methods, we aimed to shed light on Parkinson's disease stage-specific profiles of pathology, as suggested by in vivo neuroimaging. METHODS: Individual brain MRI and clinical data from 2357 Parkinson's disease patients and 1182 healthy controls were collected from 19 sources. We analyzed regional cortical thickness, cortical surface area, and subcortical volume using mixed-effects models. Patients grouped according to Hoehn and Yahr stage were compared with age- and sex-matched controls. Within the patient sample, we investigated associations with Montreal Cognitive Assessment score. RESULTS: Overall, patients showed a thinner cortex in 38 of 68 regions compared with controls (dmax  = -0.20, dmin  = -0.09). The bilateral putamen (dleft  = -0.14, dright  = -0.14) and left amygdala (d = -0.13) were smaller in patients, whereas the left thalamus was larger (d = 0.13). Analysis of staging demonstrated an initial presentation of thinner occipital, parietal, and temporal cortices, extending toward rostrally located cortical regions with increased disease severity. From stage 2 and onward, the bilateral putamen and amygdala were consistently smaller with larger differences denoting each increment. Poorer cognition was associated with widespread cortical thinning and lower volumes of core limbic structures. CONCLUSIONS: Our findings offer robust and novel imaging signatures that are generally incremental across but in certain regions specific to disease stages. Our findings highlight the importance of adequately powered multicenter collaborations. © 2021 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Magnetic Resonance Imaging of Transplanted Porcine Neonatal Pancreatic Cell Clusters Labeled with Chitosan-Coated Superparamagnetic Iron Oxide Nanoparticles in Mice.

Neonatal pancreatic cell clusters (NPCCs) are potential tissues for the treatment of diabetes. Different from adult cells, they continuously proliferate and differentiate after transplantation. In this study, we utilized magnetic resonance imaging (MRI) to detect and monitor implanted NPCCs. NPCCs were isolated from one-day-old neonatal pigs, cultured for three days, and then incubated overnight with the contrast agent chitosan-coated superparamagnetic iron oxide (CSPIO) nanoparticles. In vitro, Prussian blue staining and MR scans of CSPIO-labeled NPCCs were performed. In vivo, we transplanted 2000 CSPIO-labeled NPCCs under the kidney capsule of nondiabetic nude mice. Recipients were scanned with 7.0T MRI. Grafts were removed for histology with insulin and Prussian blue staining. After being incubated overnight with CSPIO, NPCCs showed positive iron staining and appeared as dark spots on MR scans. After transplantation of CSPIO-labeled NPCCs, persistent hypointense areas were observed at recipients' implant sites for up to 54 days. Moreover, histology showed colocalization of the insulin and iron staining in 15-, 51- and 55-day NPCC grafts. Our results indicate that transplanted NPCCs survived and differentiated to ß cells after transplantation, and that MRI is a useful tool for the detection and monitoring of CSPIO-labeled NPCC grafts.

Fixel-Based Analysis of White Matter Degeneration in Patients With Progressive Supranuclear Palsy or Multiple System Atrophy, as Compared to Parkinson's Disease.

Introduction: White matter degeneration may contribute to clinical symptoms of parkinsonism. Objective: We used fixel-based analysis (FBA) to compare the extent and patterns of white matter degeneration in different parkinsonian syndromes-including idiopathic Parkinson's disease (PD), multiple system atrophy (MSA), and progressive supranuclear palsy (PSP). Methods: This is a retrospective interpretation of prospectively acquired data of patients recruited in previous studies during 2008 and 2019. Diffusion-weighted images were acquired on a 3-Tesla scanner (diffusion weighting b = 1000 s/mm2-applied along either 64 or 30 non-collinear directions) from 53 patients with PD (men/women: 29/24; mean age: 65.06 ± 5.51 years), 47 with MSA (men/women: 20/27; mean age: 63.00 ± 7.19 years), and 50 with PSP men/women: 20/30; mean age: 65.96 ± 3.14 years). Non-parametric permutation tests were used to detect intergroup differences in fixel-related indices-including fiber density, fiber cross-section, and their combination. Results: Patterns of white matter degeneration were significantly different between PD and atypical parkinsonisms (MSA and PSP). Compared with patients with PD, those with MSA and PSP showed a more extensive white matter involvement-noticeably descending tracts from primary motor cortex to corona radiata and cerebral peduncle. Lesions of corpus callosum were specific to PSP and absent in both MSA and PD. Discussion: FBA identified specific patterns of white matter changes in MSA and PSP patients compared to PD. Our results proved the utility of FBA in evaluation of implied biological processes of white matter changes in parkinsonism. Our study set the stage for future applications of this technique in patients with parkinsonian syndromes.

Noninvasive Tracking of mPEG-poly(Ala) Hydrogel-Embedded MIN6 Cells after Subcutaneous Transplantation in Mice.

Recently, we demonstrated the feasibility of subcutaneous transplantation of MIN6 cells embedded in a scaffold with poly(ethylene glycol) methyl ether (mPEG)-poly(Ala) hydrogels. In this study, we further tracked these grafts using magnetic resonance (MR) and bioluminescence imaging. After being incubated overnight with chitosan-coated superparamagnetic iron oxide (CSPIO) nanoparticles and then mixed with mPEG-poly(Ala) hydrogels, MIN6 cells appeared as dark spots on MR scans. For in vivo experiments, we transfected MIN6 cells with luciferase and/or incubated them overnight with CSPIO overnight; 5 × 106 MIN6 cells embedded in mPEG-poly(Ala) hydrogels were transplanted into the subcutaneous space of each nude mouse. The graft of CSPIO-labeled MIN6 cells was visualized as a distinct hypointense area on MR images located at the implantation site before day 21. However, this area became hyperintense on MR scans for up to 64 days. In addition, positive bioluminescence images were also observed for up to 64 days after transplantation. The histology of removed grafts showed positive insulin and iron staining. These results indicate mPEG-poly(Ala) is a suitable scaffold for ß-cell encapsulation and transplantation. Moreover, MR and bioluminescence imaging are useful noninvasive tools for detecting and monitoring mPEG-poly(Ala) hydrogel-embedded MIN6 cells at a subcutaneous site.

T1 and T2∗ relaxation time in the parcellated myocardium of healthy Taiwanese participants: A single center study.

BACKGROUND: Quantitative maps from cardiac MRI provide objective information for myocardial tissue. The study aimed to report the T1 and T2∗ relaxation time and its relationship with clinical parameters in healthy Taiwanese participants. METHODS: Ninety-three participants were enrolled between 2014 and 2016 (Males/Females: 43/50; age: 49.7 ± 11.3/49.9 ± 10.3). T1 and T2∗ weighted images were obtained by MOLLI recovery and 3D fully flow compensated gradient echo sequences with a 3T MR scanner, respectively. The T1 map of the myocardium was parcellated into 16 partitions from the American Heart Association. The septal part of basal, mid-cavity, and apical view was selected for the T2∗ map. The difference of quantitative map by sex and age groups were evaluated by Student's TTEST and ANOVA, respectively. The relationship between T1, T2∗ map, and clinical parameters, such as ejection fraction, pulse rate, and blood pressures, were evaluated with partial correlation by controlling BMI and age. RESULTS: Male participants decreased T1 relaxation time in partitions which located in the mid-cavity and apical before 55 years old compared with females (Male/Female: 1143.1.4 ± 72.0-1191.1 ± 37.0/1180.1 ± 54.5-1326.1 ± 113.3 msec, p < 0.01). For female participants, T1 relaxation time was correlated negatively with systolic pressure (p < 0.01) and pulse rate (p < 0.01) before 45 years old. Besides, T1 and T2∗ relaxation time were positively and negatively correlated with ejection fraction and pulse rate after 45 years old in male participants, respectively. Decreased T2∗ relaxation time could be noticed in participants after 45 years old compared with youngers (26.0 ± 6.5/21.9 ± 8.0 msec; 25.2 ± 5.0/21.6 ± 7.2 msec, p < 0.05). CONCLUSION: Reference T1 and T2∗ relaxation time from cardiac MRI in healthy Taiwanese participants were provided with sex and age-dependent manners. The relationship between clinical parameters and T1 or T2∗ relaxation time was also established and could be further investigated for its potential application in healthy/sub-healthy participants.

Oxygen-sensitive T2* magnetic resonance imaging to correlate heart function and ischemic etiology of post-hospitalized chronic heart failure patients.

PURPOSE: Myocardial oxygenation imaging is a field-of-interest but its clinical utility largely unexplored. We aimed to investigate the myocardial oxygenation status via T2* imaging and compared with the left ventricular ejection fraction (LVEF) in chronic heart failure (HF) patients after hospitalization. Also, we sought to compare the differences in myocardial oxygenation status among patients with ischemic HF, non-ischemic HF and controls. METHODS: We prospectively enrolled 60 participants, comprising 20 HF patients with LVEF ≥ 50 % as the improved ejection fraction (HFIEF) group, 20 H F patients with ejection fraction <50 % as the reduced ejection fraction (HFREF) group, and 20 controls. Patients were also dichotomized into ischemic and non-ischemic subgroups. T2* values were compared across the study groups, and correlated with LVEF, myocardial scar distribution and quantity. RESULTS: T2* values positively correlated with LVEF and were significantly lower in the HFREF group as compared with both HFIEF and controls (20.06 vs. 24.23; 20.06 vs. 26.32, respectively, both p < 0.05). Lower T2* values were observed in the HFREF group than the HFIEF group and the ischemic subgroup than the non-ischemic subgroup. No significant correlation existed between T2* value and the myocardial scar amounts in ischemic territory. CONCLUSIONS: Oxygen-sensitive T2* measurements showed correlation with LVEF and ischemic etiology in chronic heart failure patients, while the ischemic HFREF patients appeared to be more vulnerable to myocardial oxygen reduction than other groups. T2* measurements may be clinically feasible in monitoring heart failure via myocardial oxygenation and lay the foundation for future studies in prediction heart failure recovery.