Neuropsychiatric symptoms and striatal monoamine availability in early Parkinson's disease without dementia.

BACKGROUND AND OBJECTIVE: Neuropsychiatric symptoms are relatively common in Parkinson's disease (PD). Many studies have revealed that striatal monoamine availability is associated with specific neuropsychiatric symptoms. This study was aimed to investigate the association between comprehensive neuropsychiatric symptoms and striatal monoamine availability in patients with early PD without dementia. METHODS: A total of 156 newly diagnosed patients with PD without dementia were included. All patients' mental and behavioral problems were assessed with the 12-item Neuropsychiatric Inventory (NPI). They underwent positron emission tomography (PET) with 18F-N-(3-fluoropropyl)-2beta-carbon ethoxy-3beta-(4-iodophenyl) nortropane and brain magnetic resonance imaging (MRI). Patients were divided into no neuropsychiatric symptoms and neuropsychiatric symptoms groups according to total NPI score. After normalizing the PET images to spatially normalized MRI, regional standardized uptake value ratios (SUVRs) with a volume of interest template were analyzed for the two groups. RESULTS: Ninety-eight patients had more than one neuropsychiatric symptom. The SUVR of the thalamus in neuropsychiatric symptoms group was significantly lower than the SUVR in no neuropsychiatric symptoms group independent of age, sex, disease duration, or severity of motor symptoms. CONCLUSION: Patients with early PD who have neuropsychiatric symptoms had a lower monoamine availability in the thalamus than those with no neuropsychiatric symptoms. This finding suggests that decreased monoamine transporter availability in the thalamus may be an imaging biomarker of neuropsychiatric symptoms in patients with PD.

"Depressed" caudate and ventral striatum dopamine transporter availability in de novo Depressed Parkinson's disease.

Depression can occur before the onset of motor symptoms in Parkinson's disease (PD) patients. The pathophysiology of depression in PD involves various brain regions and relevant functional circuits. This study investigated whether there exist distinctive patterns of presynaptic monoamine transporter densities in the basal ganglia depending on the degree of depression in patients with PD. A total of 123 early and drug-naïve PD patients were enrolled. Their affective status was evaluated by the Montgomery-Asberg Depression Rating Scale (MADRS), and subjects were subgrouped into one of the following three groups according to their MADRS scores: no depression, mild depression, and moderate-to-severe depression. All patients underwent positron emission tomography (PET) using 18F-N-(3-fluoropropyl)-2beta-carbon ethoxy-3beta-(4-iodophenyl) nortropane. The PET images were normalized, and differences in the regional standardized uptake value ratios (SUVRs) for each side of the caudate, putamen, globus pallidus, thalamus, and ventral striatum were analyzed and compared between the three groups. A trend analysis was performed across the groups to discern any associations between SUVR values of the basal ganglia and depression severity. The SUVR values of the caudate, anterior caudate nuclei, and ventral striatum declined as MADRS increased. The SUVR values of the striatum showed an inverse dose-dependent trend of antero- and ventroposterior gradient across the groups. This result indirectly revealed the involvement of the associative and limbic circuitry of the brain that are modulated by monoamines in early PD with depression. This might suggest an in vivo causal relationship between the ventral striatum, caudate and depression.

The phase value of putamen measured by susceptibility weighted images in Parkinson's disease and in other forms of Parkinsonism: a correlation study with F18 FP-CIT PET.

BACKGROUND: Iron deposition of basal ganglia in Parkinson's disease (PD) can be measured using susceptibility weighted images (SWI) on magnetic resonance imaging (MRI). Fluoropropyl carbomethoxy-3b-4-iodophenyltropane (F18 FP-CIT) positron emission tomography (PET) has been used to differentiate Parkinsonism. PURPOSE: To compare SWI phase values in Parkinsonian syndrome and age-matched control and to correlate them with F18 FP-CIT PET. MATERIAL AND METHODS: Retrospectively, patients with Parkinsonian movement disorder (n = 62) and age-matched control (n = 16) were enrolled. Mean phase values on SWI were measured by region of interest (ROI) in putamens and caudate heads. Mean standardized uptake value (SUV) on F18 FP-CIT were measured in the same ROIs of PD (n = 40) and other forms of Parkinsonism (n = 22). A statistical analysis was performed to compare the phase values and SUVs and to correlate them between groups. RESULTS: The putaminal mean phase values were higher in Parkinsonism than in the control (P ≤ 0.001). There was no difference of phase value in caudate head among the groups. Also, the mean phase value of putamen between PD and other forms of Parkinsonism was not different. Mean SUV of F18 FP-CIT in the putamen was lower in PD than other forms of Parkinsonism (P ≤ 0.014). However, there was no significant correlation between phase values and mean SUV (P > 0.05). CONCLUSION: The putaminal phase value was higher than in Parkinsonian syndrome than in the age-matched controls. F18 FP-CIT PET/CT showed different tracer activity between PD and other forms of Parkinsonism. However, no correlation between phase and SUV values was discovered.

Patient-specific molecular response dynamics can predict the possibility of relapse during the second treatment-free remission attempt in chronic myelogenous leukemia.

In chronic myelogenous leukemia (CML), treatment-free remission (TFR) is defined as maintaining a major molecular response (MMR) without a tyrosine kinase inhibitor (TKI), such as imatinib (IM). Several studies have investigated the safety of the first TFR (TFR1) attempt and suggested recommendation guidelines for such an attempt. However, the plausibility and predictive factors for a second TFR (TFR2) have yet to be reported. The present study included 21 patients in chronic myeloid leukemia who participated in twice repeated treatment stop attempts. We develop a mathematical model to analyze and explain the outcomes of TFR2. Our mathematical model framework can explain patient-specific molecular response dynamics. Fitting the model to longitudinal BCR-ABL1 transcripts from the patients generated patient-specific parameters. Binary tree decision analyses of the model parameters suggested a model based predictive binary classification factor that separated patients into low- and high-risk groups of TFR2 attempts with an overall accuracy of 76.2% (sensitivity of 81.1% and specificity of 69.9%). The low-risk group maintained a median TFR2 of 28.2 months, while the high-risk group relapsed at a median time of 3.25 months. Further, our model predicted a patient-specific optimal IM treatment duration before the second IM stop that could achieve the desired TFR2 (e.g., 5 years).

Fully automated segmentation of lumbar bone marrow in sagittal, high-resolution T1-weighted magnetic resonance images using 2D U-NET.

BACKGROUND: We investigated a 2-dimensional (2D) U-Net model to delineate lumbar bone marrow (BM) using a high resolution T1-weighted magnetic resonance imaging. METHOD: Healthy controls (n = 44, 836 images) and patients with hematologic diseases (n = 56, 1064 images) received MRI of the lumbar spines. Lumbar BM on each image was manually delineated by an experienced radiologist as a ground-truth. The 2D U-Net models were trained using a healthy lumbar BM only, diseased BM only, and using healthy and diseased BM combined, respectively. The models were validated using healthy and diseased subjects, separately. A repeated-measures analysis of variance was performed to compare segmentation accuracies with 2 validation cohorts among U-Net trained with healthy subjects (UNET_HC), U-Net trained with diseased subjects (UNET_HD), U-Net trained with all subjects including both healthy and diseased subjects (UNET_HCHD), and 3-dimensional Grow-Cut algorithm (3DGC). RESULTS: When validated with the healthy subjects, UNET_HC, UNET_HD, UNET_HCHD and 3DGC achieved the mean and standard deviation of the Dice Similarity Coefficient (DSC) of 0.9415 ± 0.07056, 0.9583 ± 0.05146, 0.9602 ± 0.0486 and 0.9139 ± 0.2039, respectively. When validated with the diseased subjects, DSCs of UNET_HC, UNET_HD, UNET_HCHD and 3DGC were 0.8303 ± 0.1073, 0.9502 ± 0.0217, 0.9502 ± 0.0217 and 0.8886 ± 0.2179, respectively. The U-Net models segmented BM better than the semi-automatic 3DGC (P < 0.0001), and UNET_HD produced better results than UNET_HC (P < 0.0001). CONCLUSIONS: We successfully constructed a fully automatic lumbar BM segmentation model for a high-resolution T1-weighted MRI using U-Net, which outperformed most of the previously reported approaches and the existing semi-automatic algorithm.

Machine Learning for Diagnosis of Hematologic Diseases in Magnetic Resonance Imaging of Lumbar Spines.

We aimed to assess feasibility of a support vector machine (SVM) texture classifier to discriminate pathologic infiltration patterns from the normal bone marrows in MRI. This retrospective study included 467 cases, which were split into a training (n = 360) and a test set (n = 107). A sagittal T1-weighted lumbar spinal MR image was normalized by an intervertebral disk, and bone marrows were segmented. The various kernel functions and SVM input dimensions were experimented to construct the most optimal classifier model. The accuracy and sensitivity increased as the number of training set sizes increased from 180 to 360. The test set was analyzed by SVM and two independent readers, and the accuracy and sensitivity of the SVM classifier, reader 1 and reader 2 were 82.2% and 85.5%, 79.4% and 82.3%, and 82.2% and 83.9%, respectively. The area under receiver operating characteristic curve (AUC) of the SVM classifier, reader 1 and reader 2 were 0.895, 0.879 and 0.880, respectively. The SVM texture classifier produced comparable performance to radiologists in isolating the hematologic diseases, which could support inexperienced physicians with spinal MRI to screen patients with marrow diseases, who need further diagnostic work-ups to make final decisions.

Striatal dopamine activity and myocardial 123I-metaiodobenzylguanidine uptake in early Parkinson's disease.

INTRODUCTION: Dopamine transporter imaging and myocardial 123I-metaiodobenzylguanidine (123I-MIBG) scintigraphy have been widely used to diagnose and discriminate degenerative parkinsonism. Many studies have reported that both imaging findings are associated with a variety of motor and non-motor phenomena in Parkinson's disease (PD). However, the association between striatal dopamine activity and myocardial 123I-MIBG uptake has not been well investigated. The objective of this study is to identify the dopamine transporter activity of the corpus striatum and thalamus according to myocardial 123I-MIBG uptake in PD. METHODS: Ninety-six newly diagnosed, non-medicated PD patients were enrolled. All patients underwent 123I-MIBG myocardial scintigraphy, positron emission tomography (PET) using 18FN-(3-fluoropropyl)-2beta-carbon ethoxy-3beta-(4-iodophenyl) nortropane and T1-weighted magnetic resonance imaging (MRI). Patients were stratified into normal and decreased 123I-MIBG groups according to their delayed heart-to-mediastinum ratio (cutoff value = 1.78). After normalizing the PET images with spatially normalized MRI, the regional standardized uptake value ratios (SUVRs) were analyzed with a volume-of-interest template between the two groups. RESULTS: Thirty-one patients showed normal myocardial 123I-MIBG uptake, and 65 patients showed reduced uptake. The SUVR of the globus pallidus in the group with reduced 123I-MIBG uptake was significantly lower than the SUVR in the normal 123I-MIBG uptake group. The heart-to-mediastinum ratio was correlated well with the SUVR of the globus pallidus, independent of age, disease duration, and the severity of motor symptoms. CONCLUSION: Early PD patients with normal 123I-MIBG uptake showed a relatively preserved dopamine reserve in the globus pallidus than patients with reduced 123I-MIBG uptake.

Analysis of Apparent Diffusion Coefficients of the Brain in Healthy Controls: A Comparison Study between Single-Shot Echo-Planar Imaging and Read-out-Segmented Echo-Planar Imaging.

OBJECTIVE: To compare apparent diffusion coefficients (ADCs) of brain segments by using two diffusion-weighted imaging acquisition modes, single-shot echo-planar imaging (ss-EPI) and read-out-segmented echo-planar imaging (rs-EPI), and to assess their correlation and agreement in healthy controls. MATERIALS AND METHODS: T2-weighted (T2W) images, rs-EPI, and ss-EPI of 30 healthy subjects were acquired using a 3T magnetic resonance scanner. The T2W images were co-registered to the rs-EPI and ss-EPI, which were then segmented into the gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF) to generate masking templates. ADC maps of rs-EPI and ss-EPI were also segmented into the GM, WM, and CSF by using the generated templates. ADCs of rs-EPI and ss-EPI were compared using Student's t tests and correlated using Pearson's correlation coefficients. Bland-Altman plots were used to assess the agreement between acquisitions. RESULTS: ADCs of rs-EPI and ss-EPI were significantly different in the GM (p < 0.001) and WM (p < 0.001). ADCs showed high agreement and correlation in the whole brain and CSF (r > 0.988; p < 0.001). ADC of the WM showed the least correlation (r = 0.894; p < 0.001), and ADCs of the WM and GM showed poor agreement. Pearson's correlation equations for each brain segment were y = 1.1x - 59.4 (GM), y = 1.45x - 255 (WM), and y = 0.98x - 63.5 (CSF), where x and y indicated ADCs of rs-EPI and ss-EPI, respectively. CONCLUSION: While ADCs of rs-EPI and ss-EPI showed high correlation and agreement in the whole brain and CSF, ADCs of the WM and GM showed significant differences and large variability, reflecting brain parenchymal inhomogeneity due to different regional microenvironments. ADCs of different acquisition methods should be interpreted carefully, especially in intra-individual comparisons.

Striatal dopamine uptake and olfactory dysfunction in patients with early Parkinson's disease.

INTRODUCTION: Olfactory dysfunction is a sensitive biomarker of neurodegeneration and a cardinal premotor symptom of Parkinson's disease (PD). Although several non-motor symptoms of PD have been correlated with decreased dopamine transporter uptake, olfactory dysfunction and reduced dopamine transporter uptake have not been widely investigated in PD. In this study, we aimed to identify the dopamine transporter status of the corpus striatum and thalamus using a magnetic resonance imaging (MRI)-guided spatial normalization method in patients with PD according to olfactory function. METHODS: Among 87 PD patients, 50 had hyposmia and 37 had normosmia. All patients underwent positron emission tomography (PET) using 18F-N-(3-fluoropropyl)-2beta-carbon ethoxy-3beta-(4-iodophenyl) nortropane (18F-FP-CIT) and T1-weighted MRI. PET images were normalized with simultaneously performed spatially normalized MRI and the regional standardized uptake value ratios (SUVR) with a volume of interest template were compared according to olfactory function. RESULTS: The bilateral caudates and the left anterior and posterior putamen of the hyposmic group showed significantly reduced dopamine transporter uptake compared to the normosmic group. In partial correlation coefficient analysis, olfactory identification impairment was correlated with the SUVR values of the caudate nuclei. CONCLUSION: More dopaminergic impairment of the bilateral caudate nuclei was found in hyposmic PD. This finding suggests that decreased dopamine uptake in the caudate nucleus may be an imaging trace of olfactory dysfunction in patients with PD.

Assessment of Arterial Wall Enhancement for Differentiation of Parent Artery Disease from Small Artery Disease: Comparison between Histogram Analysis and Visual Analysis on 3-Dimensional Contrast-Enhanced T1-Weighted Turbo Spin Echo MR Images at 3T.

OBJECTIVE: The purpose of this study was to compare the histogram analysis and visual scores in 3T MRI assessment of middle cerebral arterial wall enhancement in patients with acute stroke, for the differentiation of parent artery disease (PAD) from small artery disease (SAD). MATERIALS AND METHODS: Among the 82 consecutive patients in a tertiary hospital for one year, 25 patients with acute infarcts in middle cerebral artery (MCA) territory were included in this study including 15 patients with PAD and 10 patients with SAD. Three-dimensional contrast-enhanced T1-weighted turbo spin echo MR images with black-blood preparation at 3T were analyzed both qualitatively and quantitatively. The degree of MCA stenosis, and visual and histogram assessments on MCA wall enhancement were evaluated. A statistical analysis was performed to compare diagnostic accuracy between qualitative and quantitative metrics. RESULTS: The degree of stenosis, visual enhancement score, geometric mean (GM), and the 90th percentile (90P) value from the histogram analysis were significantly higher in PAD than in SAD (p = 0.006 for stenosis, < 0.001 for others). The receiver operating characteristic curve area of GM and 90P were 1 (95% confidence interval [CI], 0.86-1.00). CONCLUSION: A histogram analysis of a relevant arterial wall enhancement allows differentiation between PAD and SAD in patients with acute stroke within the MCA territory.

Detection of Leptomeningeal Metastasis by Contrast-Enhanced 3D T1-SPACE: Comparison with 2D FLAIR and Contrast-Enhanced 2D T1-Weighted Images.

INTRODUCTION: To compare the diagnostic accuracy of contrast-enhanced 3D(dimensional) T1-weighted sampling perfection with application-optimized contrasts by using different flip angle evolutions (T1-SPACE), 2D fluid attenuated inversion recovery (FLAIR) images and 2D contrast-enhanced T1-weighted image in detection of leptomeningeal metastasis except for invasive procedures such as a CSF tapping. MATERIALS AND METHODS: Three groups of patients were included retrospectively for 9 months (from 2013-04-01 to 2013-12-31). Group 1 patients with positive malignant cells in CSF cytology (n = 22); group 2, stroke patients with steno-occlusion in ICA or MCA (n = 16); and group 3, patients with negative results on MRI, whose symptom were dizziness or headache (n = 25). A total of 63 sets of MR images are separately collected and randomly arranged: (1) CE 3D T1-SPACE; (2) 2D FLAIR; and (3) CE T1-GRE using a 3-Tesla MR system. A faculty neuroradiologist with 8-year-experience and another 2nd grade trainee in radiology reviewed each MR image- blinded by the results of CSF cytology and coded their observations as positives or negatives of leptomeningeal metastasis. The CSF cytology result was considered as a gold standard. Sensitivity and specificity of each MR images were calculated. Diagnostic accuracy was compared using a McNemar's test. A Cohen's kappa analysis was performed to assess inter-observer agreements. RESULTS: Diagnostic accuracy was not different between 3D T1-SPACE and CSF cytology by both raters. However, the accuracy test of 2D FLAIR and 2D contrast-enhanced T1-weighted GRE was inconsistent by the two raters. The Kappa statistic results were 0.657 (3D T1-SPACE), 0.420 (2D FLAIR), and 0.160 (2D contrast-enhanced T1-weighted GRE). The 3D T1-SPACE images showed the highest inter-observer agreements between the raters. CONCLUSIONS: Compared to 2D FLAIR and 2D contrast-enhanced T1-weighted GRE, contrast-enhanced 3D T1 SPACE showed a better detection rate of leptomeningeal metastasis.

Texture analyses of quantitative susceptibility maps to differentiate Alzheimer's disease from cognitive normal and mild cognitive impairment.

PURPOSE: Although a number of studies have focused on finding anatomical regions in which iron concentrations are high, no study has been conducted to examine the overall variations in susceptibility maps of Alzheimer's disease (AD). The objective of this study, therefore, was to differentiate AD from cognitive normal (CN) and mild cognitive impairment (MCI) using a texture analysis of quantitative susceptibility maps (QSMs). METHODS: The study was approved by the local institutional review board, and informed consent was obtained from all subjects. In each participant group-CN, MCI, and AD-18 elderly subjects were enrolled. A fully first-order flow-compensated 3D gradient-echo sequence was run to obtain axial magnitudes and phase images and to produce QSM data. Sagittal structural 3D T1-weighted (3DT1W) images were also obtained with the magnetization-prepared rapid acquisition of gradient-echo sequence to obtain brain tissue images. The first- and second-order texture parameters of the QSMs and 3DT1W images were obtained to evaluate group differences using a one-way analysis of covariance. RESULTS: For the first-order QSM analysis, mean, standard deviation, and covariance of signal intensity separated the subject groups (F = 5.191, p = 0.009). For the second-order analysis, angular second moment, contrast, and correlation separated the subject groups (F = 6.896, p = 0.002). Finally, a receiver operating characteristic curve analysis differentiated MCI from CN in white matter on the QSMs (z = 3.092, p = 0.0020). CONCLUSIONS: This was the first study to evaluate the textures of QSM in AD, which overcame the limitations of voxel-based analyses. The QSM texture analysis successfully distinguished both AD and MCI from CN and outperformed the voxel-based analysis using 3DT1-weighed images in separating MCI from CN. The first-order textures were more efficient in differentiating MCI from CN than did the second-order.