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Jong-Min Lee

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YNICL Journal 2021 Journal Article

The cingulum in very preterm infants relates to language and social-emotional impairment at 2 years of term-equivalent age

  • Hyun Ju Lee
  • Hyeokjin Kwon
  • Johanna Inhyang Kim
  • Joo Young Lee
  • Ji Young Lee
  • SungKyu Bang
  • Jong-Min Lee

BACKGROUND: Relative to full-term infants, very preterm infants exhibit disrupted white matter (WM) maturation and problems related to development, including motor, cognitive, social-emotional, and receptive and expressive language processing. OBJECTIVE: The present study aimed to determine whether regional abnormalities in the WM microstructure of very preterm infants, as defined relative to those of full-term infants at a near-term age, are associated with neurodevelopmental outcomes at the age of 18-22 months. METHODS: We prospectively enrolled 89 very preterm infants (birth weight < 1500 g) and 43 normal full-term control infants born between 2016 and 2018. All infants underwent a structural brain magnetic resonance imaging scan at near-term age. The diffusion tensor imaging (DTI) metrics of the whole-brain WM tracts were extracted based on the neonatal probabilistic WM pathway. The elastic net logistic regression model was used to identify altered WM tracts in the preterm brain. We evaluated the associations between the altered WM microstructure at near-term age and motor, cognitive, social-emotional, and receptive and expressive language developments at 18-22 months of age, as measured using the Bayley Scales of Infant Development, Third Edition. RESULTS: We found that the elastic net logistic regression model could classify preterm and full-term neonates with an accuracy of 87.9% (corrected p < 0.008) using the DTI metrics in the pathway of interest with a 10% threshold level. The fractional anisotropy (FA) values of the body and splenium of the corpus callosum, middle cerebellar peduncle, left and right uncinate fasciculi, and right portion of the pathway between the premotor and primary motor cortices (premotor-PMC), as well as the mean axial diffusivity (AD) values of the left cingulum, were identified as contributive features for classification. Increased adjusted AD values in the left cingulum pathway were significantly correlated with language scores after false discovery rate (FDR) correction (r = 0.217, p = 0.043). The expressive language and social-emotional composite scores showed a significant positive correlation with the AD values in the left cingulum pathway (r = 0.226 [p = 0.036] and r = 0.31 [p = 0.003], respectively) after FDR correction. CONCLUSION: Our approach suggests that the cingulum pathways of very preterm infants differ from those of full-term infants and significantly contribute to the prediction of the subsequent development of the language and social-emotional domains. This finding could improve our understanding of how specific neural substrates influence neurodevelopment at later ages, and individual risk prediction, thus helping to inform early intervention strategies that address developmental delay.

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YNIMG Journal 2021 Journal Article

White matter hyperintensities segmentation using the ensemble U-Net with multi-scale highlighting foregrounds

  • Gilsoon Park
  • Jinwoo Hong
  • Ben A. Duffy
  • Jong-Min Lee
  • Hosung Kim

White matter hyperintensities (WMHs) are abnormal signals within the white matter region on the human brain MRI and have been associated with aging processes, cognitive decline, and dementia. In the current study, we proposed a U-Net with multi-scale highlighting foregrounds (HF) for WMHs segmentation. Our method, U-Net with HF, is designed to improve the detection of the WMH voxels with partial volume effects. We evaluated the segmentation performance of the proposed approach using the Challenge training dataset. Then we assessed the clinical utility of the WMH volumes that were automatically computed using our method and the Alzheimer's Disease Neuroimaging Initiative database. We demonstrated that the U-Net with HF significantly improved the detection of the WMH voxels at the boundary of the WMHs or in small WMH clusters quantitatively and qualitatively. Up to date, the proposed method has achieved the best overall evaluation scores, the highest dice similarity index, and the best F1-score among 39 methods submitted on the WMH Segmentation Challenge that was initially hosted by MICCAI 2017 and is continuously accepting new challengers. The evaluation of the clinical utility showed that the WMH volume that was automatically computed using U-Net with HF was significantly associated with cognitive performance and improves the classification between cognitive normal and Alzheimer's disease subjects and between patients with mild cognitive impairment and those with Alzheimer's disease. The implementation of our proposed method is publicly available using Dockerhub (https://hub.docker.com/r/wmhchallenge/pgs).

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YNICL Journal 2020 Journal Article

Cortical thinning pattern according to differential nigrosome involvement in patients with Parkinson’s disease

  • Na-Young Shin
  • Bo-Hyun Kim
  • Eunkyeong Yun
  • Uicheul Yoon
  • Jong-Min Lee
  • Young Hee Sung
  • Eung Yeop Kim

The pathological hallmark of Parkinson's disease (PD) is the progressive degeneration of dopaminergic neurons in the substantia nigra pars compacta, where the dopaminergic neurons form five clusters called nigrosomes 1-5 (N1-N5). N1 is the largest and considered to be the most affected by PD, followed by N2, N4, N3, and N5. Recently, an MRI study suggested a sequential progression of loss from N1 to N4. As the extent of cortical thinning widens as PD progresses, we aimed to define cortical thinning patterns according to the differential involvement of N1 and N4 in PD patients. Cortical thickness was analyzed in 83 PD patients (29 with N1 loss on at least one side of the brain, but no N4 loss; and 54 with N4 loss on at least one side) and 35 healthy subjects with age, sex, disease duration, and intracranial volume as covariates. On patient-wise analysis, for areas with more cortical thinning than the controls, PD patients with N4 loss had wider cortical thinning involving more dorsolateral prefrontal cortex and temporal areas than PD patients with only N1 loss, but cortical thinning did not significantly differ between these two patient groups. However, cortical thinning was more apparent in hemisphere-level analysis with statistically significant clusters being found more in hemispheres with N4 loss than hemispheres with N1 loss in PD patients compared to normal hemispheres of the controls. Cortical thinning occurred in a similar propagation pattern to that seen with PD progression, supporting past hypotheses on the sequential progression of nigrosome loss from N1 to N4.

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YNIMG Journal 2015 Journal Article

Nigrostriatal dopamine-independent resting-state functional networks in Parkinson's disease

  • Jee Hyun Ham
  • Jungho Cha
  • Jae Jung Lee
  • Gwang-Min Baek
  • Mun Kyung Sunwoo
  • Jin Yong Hong
  • Na-Young Shin
  • Young Ho Sohn

As an indicator of synchronous neural activity, resting-state functional networks are influenced by neuropathological and neurochemical changes in degenerative diseases. To further advance understanding about neurochemical and neuropathological basis for resting-state functional maps, we performed a comparative analysis of resting-state functional connectivity in patients with Parkinson's disease (PD) and drug induced parkinsonism (DIP). Resting-state neuroimaging data were analyzed with a seed-based approach to investigate striatocortical functional connectivity and cortical functional connectivity within the default mode network, executive control network, and the dorsal attention network. The striatal subregions were divided into the more or less affected sides in terms of dopamine transporter uptake. Compared with DIP, PD exhibited an increased cerebellar connectivity from the more affected side of the caudate and the less affected sides of the anterior and the posterior putamen. Additionally, PD showed increased functional connectivity in the anterior prefrontal areas from the more affected side of the anterior putamen and from the less affected side of the posterior putamen. However, PD exhibited decreased cortical functional connectivity from the posterior cingulate cortex in the left temporal area. Finally, DIP patients showed decreased cortical functional connectivity from the dorsolateral prefrontal cortex in frontal and parietal areas compared with PD patients. In summary, the present study demonstrates that PD patients exhibited a unique resting state functional connectivity that may be associated with PD-related pathological changes beyond the dopaminergic system, whereas DIP patients showed altered functional connectivity within executive control network.

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YNIMG Journal 2011 Journal Article

Quantitative comparison and analysis of sulcal patterns using sulcal graph matching: A twin study

  • Kiho Im
  • Rudolph Pienaar
  • Jong-Min Lee
  • Joon-Kyung Seong
  • Yu Yong Choi
  • Kun Ho Lee
  • P. Ellen Grant

The global pattern of cortical sulci provides important information on brain development and functional compartmentalization. Sulcal patterns are routinely used to determine fetal brain health and detect cerebral malformations. We present a quantitative method for automatically comparing and analyzing the sulcal pattern between individuals using a graph matching approach. White matter surfaces were reconstructed from volumetric T1 MRI data and sulcal pits, the deepest points in local sulci, were identified on this surface. The sulcal pattern was then represented as a graph structure with sulcal pits as nodes. The similarity between graphs was computed with a spectral-based matching algorithm by using the geometric features of nodes (3D position, depth and area) and their relationship. In particular, we exploited the feature of graph topology (the number of edges and the paths between nodes) to highlight the interrelated arrangement and patterning of sulcal folds. We applied this methodology to 48 monozygotic twins and showed that the similarity of the sulcal graphs in twin pairs was significantly higher than in unrelated pairs for all hemispheres and lobar regions, consistent with a genetic influence on sulcal patterning. This novel approach has the potential to provide a quantitative and reliable means to compare sulcal patterns.

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YNIMG Journal 2011 Journal Article

The relationship between the presence of sulcal pits and intelligence in human brains

  • Kiho Im
  • Yu Yong Choi
  • Jin-Ju Yang
  • Kun Ho Lee
  • Sun I. Kim
  • P. Ellen Grant
  • Jong-Min Lee

Sulcal pits are hypothesized to form early during development and be under tighter genetic control than other regions of the cortex. We investigated the relationship between the presence of sulcal pits and intellectual ability, estimated with the full-scale, verbal, and performance intelligence quotient (IQ), in the brains of 78 healthy young adults. We automatically extracted sulcal pits from magnetic resonance images and developed a method for their automatic labeling. The difference in the number of sulcal pits between high and average IQ groups for each labeled region was statistically analyzed. We found that in the high verbal IQ group a sulcal pit was more frequently present in the left posterior inferior frontal sulcus (70% in the high IQ group vs. 40% in the average IQ group) and the right posterior inferior temporal sulcus (70% vs. 43%), which have been reported to be regions of language function. Greater mean curvature of the deep sulcal areas in these regions was shown for the high verbal IQ group. This provides the complementary morphological information about the presence of more sulcal pits. These findings suggest that factors influencing verbal intelligence may emerge in the language areas early during cortical development and may be under tight genetic control.

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YNIMG Journal 2011 Journal Article

The relationships between extent and microstructural properties of the midsagittal corpus callosum in human brain

  • Jun-Sung Park
  • Uicheul Yoon
  • Ki-Chang Kwak
  • Sang Won Seo
  • Sun I. Kim
  • Duk L. Na
  • Jong-Min Lee

Recent quantitative analyses of the corpus callosum (CC) have tried to assess the interhemispheric connectivity. Based on histological results showing an expansion of callosal extent at the midsagittal plane, without fiber density alterations, callosal extent was interpreted as an index of interhemispheric connectivity. The microstructural properties of the CC have also been investigated extensively using diffusion tensor imaging, to assess interhemispheric connectivity. The relationships between axonal density and callosal extent need to be investigated to understand how these parameters reflect interhemispheric connectivity. We used a semi-automated CC segmentation scheme in T1-weighted magnetic resonance image and fractional anisotropy (FA) image, respectively. The parameterization method of the segmented CC was applied to 47 right-handed healthy adult subjects. The callosal extent and microstructural properties were measured using the callosal thickness and diffusion indices (FA, mean diffusivity, and axial and radial diffusivity), respectively. Our results revealed a correlation between callosal thickness and FA on the posterior body and isthmus of the CC, which suggests that these regions are more sensitive to fiber alterations than other regions. Based on this result, we suggest that both the extent of the CC and its microstructural properties should be considered together in the estimation of interhemispheric connectivity in healthy adult populations.

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YNIMG Journal 2010 Journal Article

Automatic extraction of sulcal lines on cortical surfaces based on anisotropic geodesic distance

  • Joon-Kyung Seong
  • Kiho Im
  • Sang Wook Yoo
  • Sang Won Seo
  • Duk L. Na
  • Jong-Min Lee

Analyzing cortical sulci is important for studying cortical morphology and brain functions. Although sulcal lines on cortical surfaces can be defined in various ways, it is critical in a neuroimaging study to define a sulcal line along the valley of a cortical surface with a high curvature within a sulcus. To extract the sulcal lines automatically, we present a new geometric algorithm based on the computation of anisotropic skeletons of sulcal regions. Because anisotropic skeletons are highly adaptive to the anisotropic nature of the surface shape, the resulting sulcal lines lie accurately on the valleys of the sulcal areas. Our sulcal lines remain unchanged under local shape variabilities in different human brains. Through experiments, we show that the errors of the sulcal lines for both synthetic data and real cortical surfaces were nearly as constant as the function of random noise. By measuring the changes in sulcal shape in Alzheimer's disease (AD) patients, we further investigated the effectiveness of the accuracy of our sulcal lines using a large sample of MRI data. This study involved 70 normal controls (n [men/women]: 29/41, age [mean±SD]: 71. 7±4. 9 years), and 100 AD subjects (37/63, 72. 3±5. 5). We observe significantly lower absolute average mean curvature and shallower sulcal depth in AD subjects, where the group difference becomes more significant if we measure the quantities along the sulcal lines rather than over the entire sulcal area. The most remarkable difference in the AD patients was the average sulcal depth (control: 11. 70 and AD: 11. 34).

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YNIMG Journal 2010 Journal Article

Defining functional SMA and pre-SMA subregions in human MFC using resting state fMRI: Functional connectivity-based parcellation method

  • Jae-Hun Kim
  • Jong-Min Lee
  • Hang Joon Jo
  • Sook Hui Kim
  • Jung Hee Lee
  • Sung Tae Kim
  • Sang Won Seo
  • Robert W. Cox

Noninvasive parcellation of the human cerebral cortex is an important goal for understanding and examining brain functions. Recently, the patterns of anatomical connections using diffusion tensor imaging (DTI) have been used to parcellate brain regions. Here, we present a noninvasive parcellation approach that uses “functional fingerprints” obtained by correlation measures on resting state functional magnetic resonance imaging (fMRI) data to parcellate brain regions. In other terms, brain regions are parcellated based on the similarity of their connection – as reflected by correlation during resting state – to the whole brain. The proposed method was used to parcellate the medial frontal cortex (MFC) into supplementary motor areas (SMA) and pre-SMA subregions. In agreement with anatomical landmark-based parcellation, we find that functional fingerprint clustering of the MFC results in anterior and posterior clusters. The probabilistic maps from 12 subjects showed that the anterior cluster is mainly located rostral to the vertical commissure anterior (VCA) line, whereas the posterior cluster is mainly located caudal to VCA line, suggesting the homologues of pre-SMA and SMA. The functional connections from the putative pre-SMA cluster were connected to brain regions which are responsible for complex/cognitive motor control, whereas those from the putative SMA cluster were connected to brain regions which are related to the simple motor control. These findings demonstrate the feasibility of the functional connectivity-based parcellation of the human cerebral cortex using resting state fMRI.

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YNIMG Journal 2010 Journal Article

Spectral-based automatic labeling and refining of human cortical sulcal curves using expert-provided examples

  • Ilwoo Lyu
  • Joon-Kyung Seong
  • Sung Yong Shin
  • Kiho Im
  • Jee Hoon Roh
  • Min-Jeong Kim
  • Geon Ha Kim
  • Jong Hun Kim

We present a spectral-based method for automatically labeling and refining major sulcal curves of a human cerebral cortex. Given a set of input (unlabeled) sulcal curves automatically extracted from a cortical surface and a collection of expert-provided examples (labeled sulcal curves), our objective is to identify the input major sulcal curves and assign their neuroanatomical labels, and then refines these curves based on the expert-provided example data, without employing any atlas-based registration scheme as preprocessing. In order to construct the example data, neuroanatomists manually labeled a set of 24 major sulcal curves (12 each for the left and right hemispheres) for each individual subject according to a precise protocol. We collected 30 sets of such curves from 30 subjects. Given the raw input sulcal curve set of a subject, we choose the most similar example curve to each input curve in the set to label and refine the latter according to the former. We adapt a spectral matching algorithm to choose the example curve by exploiting the sulcal curve features and their relationship. The high dimensionality of sulcal curve data in spectral matching is addressed by using their multi-resolution representations, which greatly reduces time and space complexities. Our method provides consistent labeling and refining results even under high variability of cortical sulci across the subjects. Through experiments we show that the results are comparable in accuracy to those done manually. Most output curves exhibited accuracy values higher than 80%, and the mean accuracy values of the curves in the left and the right hemispheres were 84. 69% and 84. 58%, respectively.

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