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Alterations in white matter (WM) microstructure of the central nervous system have been shown to be pathophysiological presentations of various neurodegenerative disorders. Current methods for measuring such WM features require ex vivo tissue samples analyzed using electron microscopy. Magnetic Resonance Imaging (MRI) diffusion-weighted pulse sequences provide a non-invasive tool for estimating such microstructural features in vivo. The current project investigated the use of two methods of analysis, including the ROI-based (Region of Interest, RBA) and voxel-based analysis (VBA), as well as four mathematical models of WM microstructure, including the ActiveAx Frequency-Independent Extra-Axonal Diffusion (AAI), ActiveAx Frequency-Dependent Extra-Axonal Diffusion (AAD), AxCaliber Frequency-Independent Extra-Axonal Diffusion (ACI), and AxCaliber Frequency-Dependent Extra-Axonal Diffusion (ACD) models. Two mice samples imaged at 7 T and 15.2 T were analyzed. Both the AAI and AAD models provide a single value for each of the fit parameters, including mean effective axon diameter AxD¯, packing fraction fin, intra-cellular and Din and extra-cellular Dex diffusion coefficients, as well as the frequency dependence of Dex, ßex for the AAD model. The ACI and ACD models provide this, in addition to a distribution of axon diameters for a chosen ROI. VBA extends this, providing a parameter value for each voxel within the selected ROI, at the cost of increased computational load and analysis time. Overall, RBA-ACD and VBA-AAD were found to be optimal for parameter fitting to physically relevant values in a reasonable time frame. A full comparison of each combination of RBA and VBA with AAI, AAD, ACI, and ACD is provided to give the reader sufficient information to make an informed decision of which model is best for their own experiments.

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Repetitive subconcussive head impacts (RSHI) are believed to induce sub-clinical brain injuries, potentially resulting in cumulative, long-term brain alterations. This study explores patterns of longitudinal brain white matter changes across sports with RSHI-exposure. A systematic literature search identified 22 datasets with longitudinal diffusion magnetic resonance imaging data. Four datasets were centrally pooled to perform uniform quality control and data preprocessing. A total of 131 non-concussed active athletes (American football, rugby, ice hockey; mean age: 20.06 ± 2.06 years) with baseline and post-season data were included. Nonparametric permutation inference (one-sample t tests, one-sided) was applied to analyze the difference maps of multiple diffusion parameters. The analyses revealed widespread lateralized patterns of sports-season-related increases and decreases in mean diffusivity (MD), radial diffusivity (RD), and axial diffusivity (AD) across spatially distinct white matter regions. Increases were shown across one MD-cluster (3195 voxels; mean change: 2.34%), one AD-cluster (5740 voxels; mean change: 1.75%), and three RD-clusters (817 total voxels; mean change: 3.11 to 4.70%). Decreases were shown across two MD-clusters (1637 total voxels; mean change: -1.43 to -1.48%), two RD-clusters (1240 total voxels; mean change: -1.92 to -1.93%), and one AD-cluster (724 voxels; mean change: -1.28%). The resulting pattern implies the presence of strain-induced injuries in central and brainstem regions, with comparatively milder physical exercise-induced effects across frontal and superior regions of the left hemisphere, which need further investigation. This article highlights key considerations that need to be addressed in future work to enhance our understanding of the nature of observed white matter changes, improve the comparability of findings across studies, and promote data pooling initiatives to allow more detailed investigations (e.g., exploring sex- and sport-specific effects).

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INTRODUCTION: Radiotherapy (RT) is the main treatment for patients with nasopharyngeal carcinoma (NPC). NPC patients at different stages have varying levels of damage to normal brain tissue after RT. No study has yet thoroughly analyzed the variations in radiation dosages in the brain for different stages of NPC patients treated with RT. This study aims to examine these variations. METHODS: 1446 NPC patients' CT and RTdose data were retrospectively reviewed. Analysis of the radiation dosage was executed on these 803 patients. The RTdose images for several patient groups were averaged after registering each patient's RTdose data to the CT brain template created in our earlier study. The voxel-based (VB) analysis was used to examine the dose variations in the brains of three groups of NPC patients: the early-stage group, the stage III group, and the stage IV group. RESULTS: As the disease progresses from early to advanced stages, the intensity and volume of radiation in the brain increase. The normal brain tissue accepted a substantially larger dosage in more advanced NPC patients. Differences in brain regions between stage III and early-stage patients were minimal compared to any other two groups. Brain regions exhibited substantial variations between the stage IV group and all other patient groups were broadly distributed. CONCLUSION: Our findings highlight the critical role of NPC staging in the therapeutic strategy, emphasizing the heterogeneity of radiation-induced tissue damage across disease stages and implying the need to develop stage-specific RT plans.

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PURPOSE: Image-based data mining (IBDM) is a voxel-based analysis technique to investigate dose-response. Most often, IBDM uses radiotherapy planning CTs because of their broad accessibility, however, it was unknown whether CT provided sufficient soft tissue contrast for brain IBDM. This study evaluates whether MR-based IBDM improves upon CT-based IBDM for studies of children with brain tumours. METHODS: We compared IBDM pipelines using either CT- or MRI-based spatial normalisation in 128 children (ages 3.3-19.7 years) who received photon radiotherapy for primary brain tumours at a single institution. We quantified spatial-normalisation accuracy using contour comparison measures (centre-of-mass separation, average contour distance-to-agreement (DTavg), and Hausdorff distance) at multiple anatomic loci. We performed an end-to-end test of CT- and MRI-IBDM using modified clinical dose distributions and simulated effect labels to detect associations in pre-defined anatomic loci. Accuracy was assessed via sensitivity and specificity. RESULTS: Spatial normalisation accuracy was comparable for both modalities, with a significant but small improvement for MRI compared to CT in all structures except the brainstem. The median (range) difference between the DTavg for the two pipelines was 0.37 (0.00-2.91) mm. The end-to-end test revealed no significant difference in sensitivity of the IBDM-identified regions for the two pipelines. Specificity slightly improved for MR-IBDM at the 99% significance level. CONCLUSION: CT-based IBDM was comparable to MR-based IBDM, despite a small advantage in spatial normalisation accuracy with MRI. The use of CT-IBDM over MR-IBDM is useful for multi-institutional retrospective IBDM studies, where the availability of standardised MRI data can be limited.

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BACKGROUND: A contrast agent-free approach would be preferable to the frequently used invasive approaches for evaluating cerebral perfusion in chronic migraineurs (CM). In this work, non-invasive quantitative volumetric perfusion imaging was used to evaluate alterations in cerebral perfusion in CM. METHODS: We used conventional brain structural imaging sequences and 3D pseudo-continuous arterial spin labeling (3D PCASL) to examine thirteen CM patients and fifteen normal controls (NCs). The entire brain gray matter underwent voxel-based analysis, and the cerebral blood flow (CBF) values of the altered positive areas were retrieved to look into the clinical variables' significant correlation. RESULTS: Brain regions with the decreased perfusion were located in the left postcentral gyrus, bilateral middle frontal gyrus, left middle occipital gyrus, left superior parietal lobule, left medial segment of superior frontal gyrus, and right orbital part of the inferior frontal gyrus. White matter fibers with decreased perfusion were located in bilateral superior longitudinal tracts, superior corona radiata, external capsules, anterior and posterior limbs of the internal capsule, anterior corona radiata, inferior longitudinal fasciculus, and right corticospinal tract. However, the correlation analysis showed no significant correlation between the CBF value of the above positive brain regions with clinical variables (p > 0.05). CONCLUSION: The current study provided more useful information to comprehend the pathophysiology of CM and revealed a new insight into the neural mechanism of CM from the pattern of cerebral hypoperfusion.

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Objectives: To investigate the relationship between nutritional supplementation and radiation dose to the pharyngeal constrictor muscles and larynx for head and neck (HN) cancer patients undergoing radiotherapy. Methods: We retrospectively analyzed radiotherapy (RT) dose for 231 HN cancer patients, focusing on the pharyngeal constrictors and larynx. We defined nutritional supplementation as feeding tube utilization or >10% weight loss from baseline within 90 days after radiotherapy completion. Using deformable image registration (DIR), we mapped each patient's anatomical structures to a reference coordinate system, and corresponding deformations were applied to dose matrices. Voxel doses were utilized as features for ridge logistic regression models, optimized through 5-fold cross-validation. Model performance was assessed with area under the curve of a receiver operating curve (AUC) and F1 score. We built and compared models using 1) pharyngeal constrictor voxels, 2) larynx voxels, 3) clinical factors and mean regional dose metrics, and 4) clinical factors and dose-volume histogram metrics. Test set AUCs were compared among the models, and feature importance was evaluated. Results: DIR of the pharyngeal constrictors and larynx yielded mean Dice coefficients of 0.80 and 0.84, respectively. Pharyngeal constrictors voxels and larynx voxel models had AUC of 0.88 and 0.82, respectively. Voxel-based dose modeling identified the superior to middle regions of the pharyngeal constrictors and the superior region of larynx as most predictive of feeding tube use/weight loss. Univariate analysis found treatment setting, treatment laterality, chemotherapy, baseline dysphagia, weight, and socioeconomic status predictive of outcome. An aggregated model using mean doses of pharyngeal constrictors and larynx subregions had an AUC of 0.87 and the model using conventional DVH metrics had an AUC of 0.85 with p-value of 0.04. Feature importance calculations from the regional dose model indicated that mean doses to the superior-middle pharyngeal constrictor muscles followed by mean dose to the superior larynx were most predictive of nutritional supplementation. Conclusions: Machine learning modeling of voxel-level doses enables identification of subregions within organs that correlate with toxicity. For HN radiotherapy, doses to the superior-middle pharyngeal constrictors are most predictive of feeding tube use/weight loss followed by the doses to superior portion of the larynx.

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Radiation-induced lymphopenia (RIL) is a frequent, and often considered unavoidable, side effect of radiation therapy (RT), whether or not chemotherapy is included. However, in the last few years several studies have demonstrated the detrimental effect of RIL on therapeutic outcomes, with conflicting findings concerning possible inferior patient survival. In addition, since immunotherapeutic treatment has become an integral part of cancer therapy, preserving the immune system is recognized as crucial. Given this background, various research groups have reported on different frameworks for modelling RIL, frequently based on different definitions of RIL itself, and discordant results have been reported. Our aim is to critically review the current literature on RIL modelling and summarize the different approaches recently proposed to improve the prediction of RIL after RT and aimed at immunity-sparing RT. A detailed description of these approaches will be outlined and illustrated through their applications as found in the literature from the last five years. Such a critical analysis represents the necessary starting step to develop an effective strategy that ultimately could harmonize the diverse modelling methods.

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OBJECTIVE: To investigate iron accumulation level over the whole brain and explore the possible neuromechanism of medication-overuse headache (MOH) using quantitative susceptibility mapping (QSM). METHODS: Thirty-seven MOH patients and 27 normal control subjects were enrolled in the study for examinations with both a multiecho gradient echo magnetic resonance (MR) sequence and brain high resolution structural imaging. A voxel-based analysis was performed to detect the brain regions with altered iron deposition, and the quantitative susceptibility mapping values of the positive brain regions were extracted. Correlation analysis was performed between the susceptibility values and the clinical variables of the patients. RESULTS: In patients with MOH, increased susceptibility values were found mainly in the bilateral substantia nigra (SN) (MNI coordinate: 8, -18, -14; -6, -16, -14) as compared with the normal control subjects (P < 0.001), but these alterations in iron deposition were not significantly correlated with the clinical variables of the patients (P > 0.05). The susceptibility value in the left SN had an area under curve (AUC) of 0.734, and at the cut-off value of 0.077, its diagnostic sensitivity was 72.97% and its specificity was 70.37% for distinguishing MOH from normal controls; The susceptibility value in the right SN had an AUC of 0.699 with a diagnostic sensitivity of 72.97% and a specificity of 62.96% at the cut-off value of 0.084. CONCLUSION: Increased iron deposition occurs in the bilateral SN of MOH patients, which provides a new insight into the mechanism of mesocorticolimbic dopamine system dysfunction in MOH. QSM technique can be used as a non-invasive means for quantitative analysis of brain iron deposition in migraine neuroimaging.

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Voxel-based analysis (VBA) allows the full, 3-dimensional, dose distribution to be considered in radiotherapy outcome analysis. This provides new insights into anatomical variability of pathophysiology and radiosensitivity by removing the need for a priori definition of organs assumed to drive the dose response associated with patient outcomes. This approach may offer powerful biological insights demonstrating the heterogeneity of the radiobiology across tissues and potential associations of the radiotherapy dose with further factors. As this methodological approach becomes established, consideration needs to be given to translating VBA results to clinical implementation for patient benefit. Here, we present a comprehensive roadmap for VBA clinical translation. Technical validation needs to demonstrate robustness to methodology, where clinical validation must show generalisability to external datasets and link to a plausible pathophysiological hypothesis. Finally, clinical utility requires demonstration of potential benefit for patients in order for successful translation to be feasible. For each step on the roadmap, key considerations are discussed and recommendations provided for best practice.

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Background: R2* relaxometry and quantitative susceptibility mapping can be combined to distinguish between microstructural changes and iron deposition in white matter. Here, we aimed to explore microstructural changes in the white matter associated with clinical presentations such as cognitive impairment in patients with idiopathic normal-pressure hydrocephalus (iNPH) using R2* relaxometry analysis in combination with quantitative susceptibility mapping. Methods: We evaluated 16 patients clinically diagnosed with possible or probable iNPH and 18 matched healthy controls (HC) who were chosen based on similarity in age and sex. R2* and quantitative susceptibility mapping were compared using voxel-wise and atlas-based one-way analysis of covariance (ANCOVA). Finally, partial correlation analyses were performed to assess the relationship between R2* and clinical presentations. Results: R2* was lower in some white matter regions, including the bilateral superior longitudinal fascicle and sagittal stratum, in the iNPH group compared to the HC group. The voxel-based quantitative susceptibility mapping results did not differ between the groups. The atlas-based group comparisons yielded negative mean susceptibility values in almost all brain regions, indicating no clear paramagnetic iron deposition in the white matter of any subject. R2* and cognitive performance scores between the left superior longitudinal fasciculus (SLF) and right sagittal stratum (SS) were positively correlated. In addition to that, R2* and gait disturbance scores between left SS were negatively correlated. Conclusion: Our analysis highlights the microstructural changes without iron deposition in the SLF and SS, and their association with cognitive impairment and gait disturbance in patients with iNPH.

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PURPOSE: Voxel-based quantification (VBQ) smoothing is a technique used to smooth quantitative parametric maps in the Montreal Neurological Institute standard space. Although VBQ smoothing could suppress changes in quantitative values at tissue boundaries, its effectiveness on relaxation time (T1 and T2 values and proton density PD) maps has not been investigated. The purpose of this study was to clarify the usefulness of VBQ smoothing in relaxation time mapping. METHOD: T1 and T2 values and PD maps of the brains of 20 healthy participants were obtained using a two-dimensional multi-dynamic multi-echo sequence. VBQ and Gaussian smoothing were applied to the relaxation time maps by varying the kernel size by 1 mm from 1 to 6 mm. Changes in relaxation time before and after VBQ and Gaussian smoothing for the putamen, caudate nucleus, substantia nigra, and corpus callosum on the relaxation time maps were evaluated. RESULT: The changes in relaxation time after VBQ smoothing application were smaller than those in that after Gaussian smoothing application. Although the differences in the relaxation time for all tissues before and after VBQ and Gaussian smoothing applications increased with increasing kernel size for all relaxation times for both methods, the changes in the relaxation time for VBQ smoothing were smaller than those in that for Gaussian smoothing. CONCLUSION: VBQ smoothing can suppress the change in the relaxation time on the boundary of the tissue and is thus a useful smoothing technique in relaxation time mapping.

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123I-ioflupane single-photon emission computed tomography (SPECT) is a highly sensitive and established neuroimaging technique for parkinsonian syndromes (PS). However, differentiating PS by visual inspection or analysis of regions of interest is challenging. To date, image analysis has not been able to differentiate dementia with Lewy bodies (DLB) from Parkinson's disease with dementia (PDD). This study aimed to differentiate PS based on the characteristics of striatal dopamine transporter (DAT) binding using voxel-based analysis. We acquired 123I-ioflupane SPECT data from patients with DLB (n = 30), Parkinson's disease (PD; n = 122), PDD (n = 19), multiple system atrophy with predominant parkinsonism (MSA-P; n = 18), and progressive supranuclear palsy (PSP; n = 45). DAT binding was reduced in the posterior striatum of patients with PD and PDD, whereas it was similar in MSA-P, PSP, and DLB. Hippocampal atrophy, visually evaluated by cerebral magnetic resonance imaging, did not affect striatal DAT binding in DLB. DAT binding in the anterior striatum was inversely correlated with the severity of parkinsonism in PD and PDD but not in DLB. Thus, the appearance of striatal DAT binding might indicate different pathological processes in DLB and PDD.

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BACKGROUND: Voxel-Based (VB) analysis embraces a multifaceted ensemble of sophisticated techniques, lying at the boundary between image processing and statistical modeling, that allow for a frequentist inference of pathophysiological properties anchored to an anatomical reference. VB methods has been widely adopted in neuroimaging studies and, more recently, they are gaining momentum in radiation oncology research. However, the price for the power of VB analysis is the complexity of the underlying mathematics and algorithms. PURPOSE: In this paper, we present the Multi-pAradigM voxel-Based Analysis (MAMBA) toolbox, which is intended for a flexible application of VB analysis in a wide variety of scenarios in medical imaging and radiation oncology. METHODS: The MAMBA toolbox is implemented in Matlab. It provides open-source functions to compute VB statistical models of the input data, according to a great variety of regression schemes, and to derive VB maps of the observed significance level, performing a non-parametric permutation inference. The toolbox allows for including VB and global outcomes, as well as an arbitrary amount of VB and global Explanatory Variables (EVs). In addition, the Matlab Parallel Computing Toolbox is exploited to take advantage of the perfect parallelizability of most workloads. RESULTS: The use of MAMBA was demonstrated by means of several realistic examples on a synthetic dataset mimicking a radiation oncology scenario. CONCLUSION: MAMBA is an open-source toolbox, freely available for academic and non-commercial purposes. It is designed to make state-of-the-art VB analysis accessible to research scientists without the programming resources needed to build from scratch their own software solutions. At the same time, the source code is handed out for more experienced users to complement their own tools, also customizing user-defined models. MAMBA guarantees high generality and flexibility in the design of the statistical models, significantly expanding on the features of available free tools for VB analysis. The presented toolbox aims at increasing the reach of VB studies as well as the sharing of research results.

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The era of high-throughput techniques created big data in the medical field and research disciplines. Machine intelligence (MI) approaches can overcome critical limitations on how those large-scale data sets are processed, analyzed, and interpreted. The 67th Annual Meeting of the Radiation Research Society featured a symposium on MI approaches to highlight recent advancements in the radiation sciences and their clinical applications. This article summarizes three of those presentations regarding recent developments for metadata processing and ontological formalization, data mining for radiation outcomes in pediatric oncology, and imaging in lung cancer.

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OBJECTIVE@#To investigate iron accumulation level over the whole brain and explore the possible neuromechanism of medication-overuse headache (MOH) using quantitative susceptibility mapping (QSM).@*METHODS@#Thirty-seven MOH patients and 27 normal control subjects were enrolled in the study for examinations with both a multiecho gradient echo magnetic resonance (MR) sequence and brain high resolution structural imaging. A voxel-based analysis was performed to detect the brain regions with altered iron deposition, and the quantitative susceptibility mapping values of the positive brain regions were extracted. Correlation analysis was performed between the susceptibility values and the clinical variables of the patients.@*RESULTS@#In patients with MOH, increased susceptibility values were found mainly in the bilateral substantia nigra (SN) (MNI coordinate: 8, -18, -14; -6, -16, -14) as compared with the normal control subjects (P < 0.001), but these alterations in iron deposition were not significantly correlated with the clinical variables of the patients (P > 0.05). The susceptibility value in the left SN had an area under curve (AUC) of 0.734, and at the cut-off value of 0.077, its diagnostic sensitivity was 72.97% and its specificity was 70.37% for distinguishing MOH from normal controls; The susceptibility value in the right SN had an AUC of 0.699 with a diagnostic sensitivity of 72.97% and a specificity of 62.96% at the cut-off value of 0.084.@*CONCLUSION@#Increased iron deposition occurs in the bilateral SN of MOH patients, which provides a new insight into the mechanism of mesocorticolimbic dopamine system dysfunction in MOH. QSM technique can be used as a non-invasive means for quantitative analysis of brain iron deposition in migraine neuroimaging.

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BACKGROUND: Elevated or reduced responses to sensory stimuli, known as sensory features, are common in autistic individuals and often impact quality of life. Little is known about the neurobiological basis of sensory features in autistic children. However, the brainstem may offer critical insights as it has been associated with both basic sensory processing and core features of autism. METHODS: Diffusion-weighted imaging (DWI) and parent-report of sensory features were acquired from 133 children (61 autistic children with and 72 non-autistic children, 6-11 years-old). Leveraging novel DWI processing techniques, we investigated the relationship between sensory features and white matter microstructure properties (free-water-elimination-corrected fractional anisotropy [FA] and mean diffusivity [MD]) in precisely delineated brainstem white matter tracts. Follow-up analyses assessed relationships between microstructure and sensory response patterns/modalities and analyzed whole brain white matter using voxel-based analysis. RESULTS: Results revealed distinct relationships between brainstem microstructure and sensory features in autistic children compared to non-autistic children. In autistic children, more prominent sensory features were generally associated with lower MD. Further, in autistic children, sensory hyporesponsiveness and tactile responsivity were strongly associated with white matter microstructure in nearly all brainstem tracts. Follow-up voxel-based analyses confirmed that these relationships were more prominent in the brainstem/cerebellum, with additional sensory-brain findings in the autistic group in the white matter of the primary motor and somatosensory cortices, the occipital lobe, the inferior parietal lobe, and the thalamic projections. LIMITATIONS: All participants communicated via spoken language and acclimated to the sensory environment of an MRI session, which should be considered when assessing the generalizability of this work to the whole of the autism spectrum. CONCLUSIONS: These findings suggest unique brainstem white matter contributions to sensory features in autistic children compared to non-autistic children. The brainstem correlates of sensory features underscore the potential reflex-like nature of behavioral responses to sensory stimuli in autism and have implications for how we conceptualize and address sensory features in autistic populations.

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Purpose: To investigate cerebral blood flow (CBF) characteristics in individuals with generalized tonic‒clonic seizures (GTCS) during the interictal phase using voxel-based analysis of 3D pseudocontinuous arterial spin labeling (PCASL). Patients and Methods: Patients with GTCS (GTCS group) (during the interictal period) and healthy volunteers (control group) underwent head MR imaging with a 3.0T MR scanner with a 3D PCASL sequence. CBF was compared between the two groups. Spearman correlations of CBF in regions of interest (ROIs) in GTCS patients with the duration of disease and age of onset were analyzed and corrected using the false discovery rate (FDR). Results: Twenty patients with GTCS (GTCS group) and twenty healthy volunteers (control group) were recruited for this study. On 3D PCASL, (1) GTCS patients had lower CBF in the brainstem, right cerebellum, right inferior temporal gyrus, parahippocampal gyrus, superior frontal gyrus, middle frontal gyrus, triangular part of inferior frontal gyrus, left temporal pole of superior temporal gyrus and thalamus and had higher CBF in the bilateral superior parietal gyri, precuneus, precentral gyri, postcentral gyri, and left dorsolateral superior frontal gyrus than controls. (2) The CBF of the right temporal pole of the middle temporal gyrus was negatively correlated with the duration of disease (PFDRcorrected<0.05), with a correlation coefficient r of -0.7333 and a PFDRcorrected value of 0.04. Conclusion: Voxel-based analysis of 3D PCASL imaging can be used to sensitively detect brain perfusion differences in GTCS patients. The decrease in CBF in the right temporal pole of the middle temporal gyrus may be associated with disease onset. These findings may offer new perspectives on the pathogenesis of GTCS and the underlying pathophysiological changes associated with perfusion.

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Extracting population-wise information from medical images, specifically in the neurological domain, is crucial to better understanding disease processes and progression. This is frequently done in a whole-brain voxel-wise manner, in which a population of patients and healthy controls are registered to a common co-ordinate space and a statistical test is performed on the distribution of image intensities for each location. Although this method has yielded a number of scientific insights, it is further from clinical applicability as the differences are often small and altogether do not permit for a high-performing classifier. In this article, we take the opposite approach of using a high-performing classifier, specifically a traditional convolutional neural network, and then extracting insights from it which can be applied in a population-wise manner, a method we call voxel-based diktiometry. We have applied this method to diffusion tensor imaging (DTI) analysis for Parkinson's disease (PD), using the Parkinson's Progression Markers Initiative database. By using the network sensitivity information, we can decompose what elements of the DTI contribute the most to the network's performance, drawing conclusions about diffusion biomarkers for PD that are based on metrics which are not readily expressed in the voxel-wise approach.

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BACKGROUND: The early differential diagnosis among neurodegenerative parkinsonian disorders becomes essential to set up the correct clinical-therapeutic approach. The increased utilization of [18F] fluoro-deoxy-glucose positron emission tomography (FDG PET) and the pressure for cost-effectiveness request a systematic evaluation and a validation of its utility in clinical practice. This retrospective study aims to consider the contribution, in terms of increasing accuracy and increasing diagnostic confidence, of voxel-based FDG PET analyses in the differential diagnosis of these disorders, including Parkinson's disease, multiple system atrophy, progressive supranuclear palsy, and cortico-basal syndrome. METHOD: Eighty-three subjects with a clinically confirmed diagnosis of degenerative parkinsonian disorders who underwent FDG brain PET/CT were selected. A voxel-based analysis was set up using statistical parametric mapping (SPM) on MATLAB to produce maps of brain hypometabolism and relative hypermetabolism. Four nuclear physicians (two expert and two not expert), blinded to the patients' symptoms, other physicians' evaluations, and final clinical diagnosis, independently evaluated all data by visual assessment and by adopting metabolic maps. RESULTS: In not-expert evaluators, the support of both hypometabolism and hypermetabolism maps results in a significant increase in diagnostic accuracy as well as clinical confidence. In expert evaluators, the increase in accuracy and in diagnostic confidence is mainly supported by hypometabolism maps alone. CONCLUSIONS: In this study, we demonstrated the additional value of combining voxel-based analyses with qualitative assessment of brain PET images. Moreover, maps of relative hypermetabolism can also make their contribution in clinical practice, particularly for less experienced evaluators.

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Purpose: Neuropsychiatric manifestation of lupus (NPSLE) is related with vitamin D (vit-D) deficiency which is possibly amenable to supplementation. This study was done to explore link of serum vit-D level and clinical mini-mental state examination (MMSE) with brain perfusion SPECT (BS) in patients with NPSLE. Methods: Patients who underwent BS with the diagnosis of NPSLE and had serum levels of vit-D and MMSE within a span of 1 month were retrospectively included. The BS DICOM data were used to generate 3D surface images of brain for visual identification of regional hypoperfusion, and the z-scores from eZIS software and then to perform voxel-based regression analysis in order to explore association between serum vit-D level and cerebral perfusion deficit using SPM8. Distribution of serum vit-D level was checked across MMSE and BS z-score using R. Results: A total 19 patients with means ± SD age of 28.4 ± 9.2 years, having mean levels of serum vit-D of 18.7 ± 9.8 ng/ml and mean MMSE scores 24.2 ± 1.6, had undergone BS. The eZIS-derived z-score fall in the category of normal in six (31.6%), mild perfusion deficit (PD) in 10 (52.6%) and moderate PD in three (15.8%) with the means ± SD of z-score being 0.52 ± 0.2, 1.72 ± 0.2, and 2.33 ± 0.2. Voxel-based analysis revealed significant positive correlation between vit-D level and hypoperfusion in brain regions related to cognitive function (p<0.05). Serum vit-D levels were significantly lower in NPSLE patients with lower MMSE scores as well as in higher eZIS z-score (p < 0.01). Conclusions: Our results may support the utility of vit-D supplementation in NPSLE and applicability of BS as a clinical adjunct for monitoring response to vit-D supplementation.